TY - THES A1 - Huang, Wanjun T1 - Temporary binding for dynamic middleware construction and web services composition T1 - Temporäre Anbindung für dynamischen Middlewareaufbau und Web Services Integration N2 - With increasing number of applications in Internet and mobile environments, distributed software systems are demanded to be more powerful and flexible, especially in terms of dynamism and security. This dissertation describes my work concerning three aspects: dynamic reconfiguration of component software, security control on middleware applications, and web services dynamic composition. Firstly, I proposed a technology named Routing Based Workflow (RBW) to model the execution and management of collaborative components and realize temporary binding for component instances. The temporary binding means component instances are temporarily loaded into a created execution environment to execute their functions, and then are released to their repository after executions. The temporary binding allows to create an idle execution environment for all collaborative components, on which the change operations can be immediately carried out. The changes on execution environment will result in a new collaboration of all involved components, and also greatly simplifies the classical issues arising from dynamic changes, such as consistency preserving etc. To demonstrate the feasibility of RBW, I created a dynamic secure middleware system - the Smart Data Server Version 3.0 (SDS3). In SDS3, an open source implementation of CORBA is adopted and modified as the communication infrastructure, and three secure components managed by RBW, are created to enhance the security on the access of deployed applications. SDS3 offers multi-level security control on its applications from strategy control to application-specific detail control. For the management by RBW, the strategy control of SDS3 applications could be dynamically changed by reorganizing the collaboration of the three secure components. In addition, I created the Dynamic Services Composer (DSC) based on Apache open source projects, Apache Axis and WSIF. In DSC, RBW is employed to model the interaction and collaboration of web services and to enable the dynamic changes on the flow structure of web services. Finally, overall performance tests were made to evaluate the efficiency of the developed RBW and SDS3. The results demonstrated that temporary binding of component instances makes slight impacts on the execution efficiency of components, and the blackout time arising from dynamic changes can be extremely reduced in any applications. N2 - Heutige Softwareanwendungen fuer das Internet und den mobilen Einsatz erfordern bezueglich Funktionalitaet und Sicherheit immer leistungsstaerkere verteilte Softwaresysteme. Diese Dissertation befasst sich mit der dynamischen Rekonfiguration von Komponentensoftware, Sicherheitskontrolle von Middlewareanwendungen und der dynamischen Komposition von Web Services. Zuerst wird eine Routing Based Workflow (RBW) Technologie vorgestellt, welche die Ausfuehrung und das Management von kollaborierenden Komponenten modelliert, sowie fuer die Realisierung einer temporaeren Anbindung von Komponenteninstanzen zustaendig ist. D.h., Komponenteninstanzen werden zur Ausfuehrung ihrer Funktionalitaet temporaer in eine geschaffene Ausfuehrungsumgebung geladen und nach Beendigung wieder freigegeben. Die temporaere Anbindung erlaubt das Erstellen einer Ausfuehrungsumgebung, in der Rekonfigurationen unmittelbar vollzogen werden koennen. Aenderungen der Ausfuehrungsumgebung haben neue Kollaborations-Beziehungen der Komponenten zufolge und vereinfachen stark die Schwierigkeiten wie z.B. Konsistenzerhaltung, die mit dynamischen Aenderungen verbunden sind. Um die Durchfuehrbarkeit von RBW zu demonstrieren, wurde ein dynamisches, sicheres Middleware System erstellt - der Smart Data Server, Version 3 (SDS3). Bei SDS3 kommt eine Open Source Softwareimplementierung von CORBA zum Einsatz, die modifiziert als Kommunikationsinfrasturkutur genutzt wird. Zudem wurden drei Sicherheitskomponenten erstellt, die von RBW verwaltet werden und die Sicherheit beim Zugriff auf die eingesetzten Anwendungen erhoehen. SDS3 bietet den Anwendungen Sicherheitskontrollfunktionen auf verschiedenen Ebenen, angefangen von einer Strategiekontrolle bis zu anwendungsspezifischen Kontrollfunktionen. Mittels RBW kann die Strategiekontrolle des SDS3 dynamisch durch Reorganisation von Kollabortions-Beziehungen zwischen den Sicherheitskomponenten angepasst werden. Neben diesem System wurde der Dynamic Service Composer (DSC) implementiert, welcher auf den Apache Open Source Projekten Apache Axis und WSIF basiert. Im DSC wird RBW eingesetzt, um die Interaktion und Zusammenarbeit von Web Services zu modellieren sowie dynamische Aenderungen der Flussstruktur von Web Services zu ermoeglichen. Nach der Implementierung wurden Performance-Tests bezueglich RBW und SDS3 durchgefuehrt. Die Ergebnisse der Tests zeigen, dass eine temporaere Anbindung von Komponenteninstanzen nur einen geringen Einfluss auf die Ausfuehrungseffizienz von Komponeten hat. Ausserdem bestaetigen die Testergebnisse, dass die mit der dynamischen Rekonfiguration verbundene Ausfallzeit extrem niedrig ist. KW - Middleware KW - Web Services KW - Temporäre Anbindung KW - Dynamische Rekonfiguration KW - temporary binding KW - dynamic reconfiguration Y1 - 2006 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-7672 ER - TY - THES A1 - Menzel, Michael T1 - Model-driven security in service-oriented architectures : leveraging security patterns to transform high-level security requirements to technical policies T1 - Modell-getriebene Sicherheit in Service-orientierten Architekturen N2 - Service-oriented Architectures (SOA) facilitate the provision and orchestration of business services to enable a faster adoption to changing business demands. Web Services provide a technical foundation to implement this paradigm on the basis of XML-messaging. However, the enhanced flexibility of message-based systems comes along with new threats and risks. To face these issues, a variety of security mechanisms and approaches is supported by the Web Service specifications. The usage of these security mechanisms and protocols is configured by stating security requirements in security policies. However, security policy languages for SOA are complex and difficult to create due to the expressiveness of these languages. To facilitate and simplify the creation of security policies, this thesis presents a model-driven approach that enables the generation of complex security policies on the basis of simple security intentions. SOA architects can specify these intentions in system design models and are not required to deal with complex technical security concepts. The approach introduced in this thesis enables the enhancement of any system design modelling languages – for example FMC or BPMN – with security modelling elements. The syntax, semantics, and notion of these elements is defined by our security modelling language SecureSOA. The metamodel of this language provides extension points to enable the integration into system design modelling languages. In particular, this thesis demonstrates the enhancement of FMC block diagrams with SecureSOA. To enable the model-driven generation of security policies, a domain-independent policy model is introduced in this thesis. This model provides an abstraction layer for security policies. Mappings are used to perform the transformation from our model to security policy languages. However, expert knowledge is required to generate instances of this model on the basis of simple security intentions. Appropriate security mechanisms, protocols and options must be chosen and combined to fulfil these security intentions. In this thesis, a formalised system of security patterns is used to represent this knowledge and to enable an automated transformation process. Moreover, a domain-specific language is introduced to state security patterns in an accessible way. On the basis of this language, a system of security configuration patterns is provided to transform security intentions related to data protection and identity management. The formal semantics of the security pattern language enable the verification of the transformation process introduced in this thesis and prove the correctness of the pattern application. Finally, our SOA Security LAB is presented that demonstrates the application of our model-driven approach to facilitate a dynamic creation, configuration, and execution of secure Web Service-based composed applications. N2 - Im Bereich der Enterprisearchitekturen hat das Paradigma der Service-orientierten Architektur (SOA) in den vergangenen Jahren eine große Bedeutung erlangt. Dieser Ansatz ermöglicht die Strukturierung und Umsetzung verteilter, IT-basierter Geschäftsfunktionen, um einen effizienten und flexiblen Einsatz von IT-Ressourcen zu ermöglichen. Während in der Vergangenheit fachliche Anforderungen in monolithischen Applikationen umgesetzt wurden, setzt dieser Architekturansatz auf wiederverwendbare Dienste, die spezifische Geschäftsfunktionen implementieren. Diese Dienste können dann dynamisch zur Umsetzung von Geschäftsprozessen herangezogen werden und ermöglichen eine schnelle Reaktion auf verändernde geschäftliche Rahmenbedingungen durch Anpassung der Prozesse. Die einzelnen Dienste existieren unabhängig voneinander und sind lose über einen Nachrichtenaustausch gekoppelt. Diese Unabhängigkeit unterscheidet den SOA-Ansatz von der bisherigen Entwicklung klassischer verteilter Anwendungen. Die Verwendung unabhängiger Dienste geht aber auch mit einem größeren Gefährdungspotential einher, da eine Vielzahl von Schnittstellen bereitgestellt wird, die mittels komplexer Protokolle angesprochen werden können. Somit ist die korrekte Umsetzung von Sicherheitsmechanismen in allen Diensten und SOA-Infrastrukturkomponeten essentiell. Kommunikationspartner müssen an jedem Kommunikationsendpunkt authentifiziert und autorisiert werden und ausgetauschte Nachrichten müssen immer geschützt werden. Solche Sicherheitsanforderungen werden in technischen Sicherheitskonfigurationen (Policydokumenten) mittels einer Policysprache kodiert und werden an die Dienste verteilt, die diese Anforderungen durchsetzen. Da Policysprachen für SOA aber durch die Vielzahl und Vielfalt an Sicherheitsmechanismen, -protokollen und -standards eine hohe Komplexität aufweisen, sind Sicherheitskonfigurationen höchst fehleranfällig und mit viel Fachwissen zu erstellen. Um die Generierung von Sicherheitskonfigurationen in komplexen Systemen zu vereinfachen, wird in dieser Arbeit ein modellgetriebener Ansatz vorgestellt, der eine visuelle Modellierung von Sicherheitsanforderungen in Architekturmodellen ermöglicht und eine automatisierte Generierung von Sicherheitskonfigurationen auf Basis dieser Anforderungen unterstützt. Die Modellierungsebene ermöglicht eine einfache und abstrakte Darstellung von Sicherheitsanforderungen, die sich auch für Systemarchitekten erschließen, welche keine Sicherheits-experten sind. Beispielsweise können modellierte Daten einfach mit einem Schloss annotiert werden, um den Schutz dieser Daten zu fordern. Die Syntax, die Semantik und die Darstellung dieser Anforderungen werden durch die in dieser Arbeit vorgestellte Sicherheitsmodellierungssprache SecureSOA spezifiziert. Der vorgestellte modellgetriebene Ansatz transformiert die modellierten Anforderungen auf ein domänen-unabhängiges Policymodell, das eine Abstraktionsschicht zu konkreten Policysprachen bildet. Diese Abstrak-tionsschicht vereinfacht die Generierung von Sicherheitspolicies in verschiedenen Policysprachen. Allerdings kann diese Transformation nur erfolgen, wenn im System Expertenwissen hinterlegt ist, das die Auswahl von konkreten Sicherheitsmechanismen und -optionen bestimmt. Im Rahmen dieser Arbeit werden Entwurfsmuster für SOA-Sicherheit zur Transformation herangezogen, die dieses Wissen repräsentieren. Dazu wird ein Katalog von Entwurfsmustern eingeführt, der die Abbildung von abstrakten Sicherheitsanforderungen auf konkrete Konfigurationen ermöglicht. Diese Muster sind mittels einer Entwurfsmustersprache definiert, die in dieser Arbeit eingeführt wird. Die formale Semantik dieser Sprache ermöglicht die formale Verifikation des Transformationsprozesses, um die Korrektheit der Entwurfsmusteranwendung nachzuweisen. Die Definition dieses Entwurfsmusterkatalogs und der darauf basierende Transformationsprozess ermöglichen die Abbildung von abstrakten Sicherheitsanforderungen auf konkrete technische Sicherheitskonfigurationen und stellen den Beitrag dieser Arbeit dar. Abschließend wird in dieser Arbeit das SOA-Security-Lab vorgestellt, das die Umsetzung dieses Ansatzes demonstriert. KW - IT-Sicherheit KW - Service-Orientierte Architekturen KW - Modell-getriebene Sicherheit KW - Sicherheitsmodellierung KW - Entwurfsmuster für SOA-Sicherheit KW - IT-Security KW - Service-oriented Architectures KW - Modell-driven Security KW - Security Modelling KW - SOA Security Pattern Y1 - 2011 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-59058 ER - TY - GEN A1 - Klieme, Eric A1 - Tietz, Christian A1 - Meinel, Christoph T1 - Beware of SMOMBIES BT - Verification of Users based on Activities while Walking T2 - The 17th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (IEEE TrustCom 2018)/the 12th IEEE International Conference on Big Data Science and Engineering (IEEE BigDataSE 2018) N2 - Several research evaluated the user's style of walking for the verification of a claimed identity and showed high authentication accuracies in many settings. In this paper we present a system that successfully verifies a user's identity based on many real world smartphone placements and yet not regarded interactions while walking. Our contribution is the distinction of all considered activities into three distinct subsets and a specific one-class Support Vector Machine per subset. Using sensor data of 30 participants collected in a semi-supervised study approach, we prove that unsupervised verification is possible with very low false-acceptance and false-rejection rates. We furthermore show that these subsets can be distinguished with a high accuracy and demonstrate that this system can be deployed on off-the-shelf smartphones. KW - gait KW - authentication KW - smartphone KW - activities KW - verification KW - behavioral KW - continuous Y1 - 2018 SN - 978-1-5386-4387-7 SN - 978-1-5386-4389-1 U6 - https://doi.org/10.1109/TrustCom/BigDataSE.2018.00096 SN - 2324-9013 SP - 651 EP - 660 PB - IEEE CY - New York ER - TY - JOUR A1 - Thienen, Julia von A1 - Noweski, Christine A1 - Meinel, Christoph A1 - Lang, Sabine A1 - Nicolai, Claudia A1 - Bartz, Andreas T1 - What can design thinking learn from behavior group theraphy? Y1 - 2012 SN - 978-3-642-31990-7 ER - TY - GEN A1 - Alhosseini Almodarresi Yasin, Seyed Ali A1 - Bin Tareaf, Raad A1 - Najafi, Pejman A1 - Meinel, Christoph T1 - Detect me if you can BT - Spam Bot Detection Using Inductive Representation Learning T2 - Companion Proceedings of The 2019 World Wide Web Conference N2 - Spam Bots have become a threat to online social networks with their malicious behavior, posting misinformation messages and influencing online platforms to fulfill their motives. As spam bots have become more advanced over time, creating algorithms to identify bots remains an open challenge. Learning low-dimensional embeddings for nodes in graph structured data has proven to be useful in various domains. In this paper, we propose a model based on graph convolutional neural networks (GCNN) for spam bot detection. Our hypothesis is that to better detect spam bots, in addition to defining a features set, the social graph must also be taken into consideration. GCNNs are able to leverage both the features of a node and aggregate the features of a node’s neighborhood. We compare our approach, with two methods that work solely on a features set and on the structure of the graph. To our knowledge, this work is the first attempt of using graph convolutional neural networks in spam bot detection. KW - Social Media Analysis KW - Bot Detection KW - Graph Embedding KW - Graph Convolutional Neural Networks Y1 - 2019 SN - 978-1-4503-6675-5 U6 - https://doi.org/10.1145/3308560.3316504 SP - 148 EP - 153 PB - Association for Computing Machinery CY - New York ER - TY - JOUR A1 - Lindberg, Tilmann A1 - Meinel, Christoph A1 - Wagner, Ralf T1 - Design thinking : a fruitful concept for IT development? Y1 - 2011 SN - 978-3-642-13756-3 ER - TY - JOUR A1 - Meinel, Christoph A1 - Klotz, Volker T1 - The first 10 years of the ECCC digital library Y1 - 2006 UR - http://portal.acm.org/cacm U6 - https://doi.org/10.1145/1107458.1107484 ER - TY - JOUR A1 - Grünewald, Franka A1 - Meinel, Christoph T1 - Implementation and Evaluation of Digital E-Lecture Annotation in Learning Groups to Foster Active Learning JF - IEEE transactions on learning technologies N2 - The use of video lectures in distance learning involves the two major problems of searchability and active user participation. In this paper, we promote the implementation and usage of a collaborative educational video annotation functionality to overcome these two challenges. Different use cases and requirements, as well as details of the implementation, are explained. Furthermore, we suggest more improvements to foster a culture of participation and an algorithm for the extraction of semantic data. Finally, evaluations in the form of user tests and questionnaires in a MOOC setting are presented. The results of the evaluation are promising, as they indicate not only that students perceive it as useful, but also that the learning effectiveness increases. The combination of personal lecture video annotations with a semantic topic map was also evaluated positively and will thus be investigated further, as will the implementation in a MOOC context. KW - eLectures KW - tele-teaching KW - video annotation KW - collaborative learning Y1 - 2015 U6 - https://doi.org/10.1109/TLT.2015.2396042 SN - 1939-1382 VL - 8 IS - 3 SP - 286 EP - 298 PB - Inst. of Electr. and Electronics Engineers CY - Los Alamitos ER - TY - THES A1 - Saleh, Eyad T1 - Securing Multi-tenant SaaS Environments N2 - Software-as-a-Service (SaaS) offers several advantages to both service providers and users. Service providers can benefit from the reduction of Total Cost of Ownership (TCO), better scalability, and better resource utilization. On the other hand, users can use the service anywhere and anytime, and minimize upfront investment by following the pay-as-you-go model. Despite the benefits of SaaS, users still have concerns about the security and privacy of their data. Due to the nature of SaaS and the Cloud in general, the data and the computation are beyond the users' control, and hence data security becomes a vital factor in this new paradigm. Furthermore, in multi-tenant SaaS applications, the tenants become more concerned about the confidentiality of their data since several tenants are co-located onto a shared infrastructure. To address those concerns, we start protecting the data from the provisioning process by controlling how tenants are being placed in the infrastructure. We present a resource allocation algorithm designed to minimize the risk of co-resident tenants called SecPlace. It enables the SaaS provider to control the resource (i.e., database instance) allocation process while taking into account the security of tenants as a requirement. Due to the design principles of the multi-tenancy model, tenants follow some degree of sharing on both application and infrastructure levels. Thus, strong security-isolation should be present. Therefore, we develop SignedQuery, a technique that prevents one tenant from accessing others' data. We use the Signing Concept to create a signature that is used to sign the tenant's request, then the server can verifies the signature and recognizes the requesting tenant, and hence ensures that the data to be accessed is belonging to the legitimate tenant. Finally, Data confidentiality remains a critical concern due to the fact that data in the Cloud is out of users' premises, and hence beyond their control. Cryptography is increasingly proposed as a potential approach to address such a challenge. Therefore, we present SecureDB, a system designed to run SQL-based applications over an encrypted database. SecureDB captures the schema design and analyzes it to understand the internal structure of the data (i.e., relationships between the tables and their attributes). Moreover, we determine the appropriate partialhomomorphic encryption scheme for each attribute where computation is possible even when the data is encrypted. To evaluate our work, we conduct extensive experiments with di↵erent settings. The main use case in our work is a popular open source HRM application, called OrangeHRM. The results show that our multi-layered approach is practical, provides enhanced security and isolation among tenants, and have a moderate complexity in terms of processing encrypted data. Y1 - 2016 ER - TY - JOUR A1 - Meinel, Christoph A1 - Wang, Long T1 - Building content clusters based on modelling page pairs N2 - We give a new view on building content clusters from page pair models. We measure the heuristic importance within every two pages by computing the distance of their accessed positions in usage sessions. We also compare our page pair models with the classical pair models used in information theories and natural language processing, and give different evaluation methods to build the reasonable content communities. And we finally interpret the advantages and disadvantages of our models from detailed experiment results Y1 - 2006 UR - http://www.springerlink.com/content/105633/ U6 - https://doi.org/10.1007/11610113_85 ER - TY - THES A1 - Sadr-Azodi, Amir Shahab T1 - Towards Real-time SIEM-based Network monitoring and Intrusion Detection through Advanced Event Normalization Y1 - 2015 ER - TY - THES A1 - Gericke, Lutz T1 - Tele-Board - Supporting and analyzing creative collaboration in synchronous and asynchronous scenario Y1 - 2014 ER - TY - JOUR A1 - Jobst, Birgit A1 - Köppen, Eva A1 - Lindberg, Tilmann A1 - Moritz, Josephine A1 - Rhinow, Holger A1 - Meinel, Christoph T1 - The faith-factor in design thinking : creative confidence through education at the design thinking schools Potsdam and Standford? Y1 - 2012 SN - 978-3-642-31990-7 ER - TY - JOUR A1 - Noweski, Christine A1 - Scheer, Andrea A1 - Büttner, Nadja A1 - Thienen, Julia von A1 - Erdmann, Johannes A1 - Meinel, Christoph T1 - Towards a paradigm shift in education practice : developing twenty-first century skills with design thinking Y1 - 2012 SN - 978-3-642-31990-7 ER - TY - JOUR A1 - Gumienny, Raja A1 - Gericke, Lutz A1 - Wenzel, Matthias A1 - Meinel, Christoph T1 - Tele-board in use : applying aq digital whiteboard system in different situations and setups Y1 - 2012 SN - 978-3-642-31990-7 ER - TY - JOUR A1 - Thienen, Julia von A1 - Noweski, Christine A1 - Rauth, Ingo A1 - Meinel, Christoph A1 - Lange, Sabine T1 - If you want to know who are, tell me where you are : the importance of places Y1 - 2012 ER - TY - JOUR A1 - Meinel, Christoph A1 - Leifer, Larry T1 - Design thinking research Y1 - 2012 SN - 978-3-642-31990-7 ER - TY - BOOK A1 - Linckels, Serge A1 - Meinel, Christoph T1 - E-Librarian service : user-friendly semantic search in digital libraries Y1 - 2011 SN - 978-3-642-17742-2 U6 - https://doi.org/10.1007/978-3-642-17743-9 PB - Springer-Verlag Berlin Heidelberg CY - Berlin, Heidelberg ER - TY - JOUR A1 - Meinel, Christoph A1 - Leifer, Larry T1 - Design thinking research Y1 - 2011 SN - 978-3-642-13756-3 ER - TY - GEN ED - Plattner, Hasso ED - Meinel, Christoph ED - Leifer, Larry T1 - Design thinking : understand - improve - apply Y1 - 2011 SN - 978-3-642-13756-3 PB - Springer-Verlag Berlin Heidelberg CY - Berlin, Heidelberg ER - TY - JOUR A1 - Gumienny, Raja A1 - Meinel, Christoph A1 - Gericke, Lutz A1 - Quasthoff, Matthias A1 - LoBue, Peter A1 - Willems, Christian T1 - Tele-board : enabling efficient collaboration in digital design spaces across time and distance Y1 - 2011 SN - 978-3-642-13756-3 ER - TY - JOUR A1 - Thienen, Julia von A1 - Noweski, Christine A1 - Meinel, Christoph A1 - Rauth, Ingo T1 - The co-evolution of theory and practice in design thinking - or - "Mind the oddness trap!" Y1 - 2011 SN - 978-3-642-13756-3 ER - TY - JOUR A1 - Lindberg, Tilmann A1 - Köppen, Eva A1 - Rauth, Ingo A1 - Meinel, Christoph T1 - On the perection, adoption and Implementation of design thinking in the IT industry Y1 - 2012 ER - TY - JOUR A1 - Gericke, Lutz A1 - Gumienny, Raja A1 - Meinel, Christoph T1 - Tele-board : folow the traces of your design process history Y1 - 2012 ER - TY - JOUR A1 - Meinel, Christoph A1 - Leifer, Larry T1 - Design thinking research Y1 - 2012 ER - TY - BOOK ED - Plattner, Hasso ED - Meinel, Christoph ED - Leifer, Larry T1 - Dsign thinking research : studying co-creation in practice Y1 - 2012 SN - 978-3-642-21642-8 U6 - https://doi.org/10.1007/978-3-642-21643-5 PB - Springer Berlin Heidelberg CY - Berlin, Heidelberg ER - TY - THES A1 - Al-Saffar, Loay Talib Ahmed T1 - Analysing prerequisites, expectations, apprehensions, and attitudes of university students studying Computer science T1 - Analyse von Voraussetzungen, Erwartungen, Haltungen, Einstellungen und Befürchtungen von Bachelor-Studierenden der Informatik N2 - The main objective of this dissertation is to analyse prerequisites, expectations, apprehensions, and attitudes of students studying computer science, who are willing to gain a bachelor degree. The research will also investigate in the students’ learning style according to the Felder-Silverman model. These investigations fall in the attempt to make an impact on reducing the “dropout”/shrinkage rate among students, and to suggest a better learning environment. The first investigation starts with a survey that has been made at the computer science department at the University of Baghdad to investigate the attitudes of computer science students in an environment dominated by women, showing the differences in attitudes between male and female students in different study years. Students are accepted to university studies via a centrally controlled admission procedure depending mainly on their final score at school. This leads to a high percentage of students studying subjects they do not want. Our analysis shows that 75% of the female students do not regret studying computer science although it was not their first choice. And according to statistics over previous years, women manage to succeed in their study and often graduate on top of their class. We finish with a comparison of attitudes between the freshman students of two different cultures and two different university enrolment procedures (University of Baghdad, in Iraq, and the University of Potsdam, in Germany) both with opposite gender majority. The second step of investigation took place at the department of computer science at the University of Potsdam in Germany and analyzes the learning styles of students studying the three major fields of study offered by the department (computer science, business informatics, and computer science teaching). Investigating the differences in learning styles between the students of those study fields who usually take some joint courses is important to be aware of which changes are necessary to be adopted in the teaching methods to address those different students. It was a two stage study using two questionnaires; the main one is based on the Index of Learning Styles Questionnaire of B. A. Solomon and R. M. Felder, and the second questionnaire was an investigation on the students’ attitudes towards the findings of their personal first questionnaire. Our analysis shows differences in the preferences of learning style between male and female students of the different study fields, as well as differences between students with the different specialties (computer science, business informatics, and computer science teaching). The third investigation looks closely into the difficulties, issues, apprehensions and expectations of freshman students studying computer science. The study took place at the computer science department at the University of Potsdam with a volunteer sample of students. The goal is to determine and discuss the difficulties and issues that they are facing in their study that may lead them to think in dropping-out, changing the study field, or changing the university. The research continued with the same sample of students (with business informatics students being the majority) through more than three semesters. Difficulties and issues during the study were documented, as well as students’ attitudes, apprehensions, and expectations. Some of the professors and lecturers opinions and solutions to some students’ problems were also documented. Many participants had apprehensions and difficulties, especially towards informatics subjects. Some business informatics participants began to think of changing the university, in particular when they reached their third semester, others thought about changing their field of study. Till the end of this research, most of the participants continued in their studies (the study they have started with or the new study they have changed to) without leaving the higher education system. N2 - Thema der Dissertation ist die Untersuchung von Voraussetzungen, Erwartungen, Haltungen, Einstellungen und Befürchtungen von Bachelor Studierenden der Informatik. Darüber hinaus werden in der vorliegenden Analyse anhand des Solomon/Felder-Modells Lerntypen unter den Informatik-Studierenden untersucht mit dem Ziel, mittels einer vorteilhafter gestalteten Lernumgebung zur Lernwirksamkeit und zur Reduktion der Abbrecherquote beizutragen. Zunächst werden anhand einer Vergleichsstudie zwischen Informatik-Studierenden an der Universität Bagdad und an der Universität Potsdam sowie jeweils zwischen männlichen und weiblichen Studierenden Unterschiede in der Wahrnehmung des Fachs herausgearbeitet. Hierzu trägt insbesondere das irakische Studienplatzvergabeverfahren bei, das den Studierenden nur wenig Freiheiten lässt, ein Studienfach zu wählen mit dem Ergebnis, dass viele Studierende, darunter überwiegend weibliche Studierende, gegen ihre Absicht Informatik studieren. Dennoch arrangieren sich auch die weiblichen Studierenden mit dem Fach und beenden das Studium oft mit Best-Noten. Der zweite Teil der Dissertation analysiert Lernstile von Studierenden des Instituts für Informatik der Universität Potsdam auf der Grundlage des Modells von Solomon/Felder mit dem Ziel, Hinweise für eine verbesserte Gestaltung der Lehrveranstaltungen zu gewinnen, die Lernende in der für sie geeigneten Form anspricht. Die Ergebnisse zeigen die Schwierigkeit, dieses Ziel zu erreichen, denn sowohl männliche und weibliche Studierende als auch Studierende von Informatik, Wirtschaftsinformatik und Lehramt Informatik weisen deutliche Unterschiede in den präferierten Lernstilen auf. In einer dritten qualitativen Studie wurden mit Studierenden von Informatik, Wirtschaftsinformatik und Lehramt Informatik Interviews über einen Zeitraum der ersten drei Studiensemester geführt, um einen detaillierten Einblick in Haltungen, Einstellungen und Erwartungen zum Studium zu gewinnen sowie Probleme zu ermitteln, die möglicherweise zum Abbruch des Studiums oder zum Wechsel des Fachs oder der Universität führen können. KW - computer science education KW - dropout KW - changing the university KW - changing the study field KW - Computer Science KW - business informatics KW - study problems KW - tutorial section KW - higher education KW - teachers KW - professors KW - Informatikvoraussetzungen KW - Studentenerwartungen KW - Studentenhaltungen KW - Universitätseinstellungen KW - Bachelorstudierende der Informatik KW - Abbrecherquote KW - Wirtschaftsinformatik KW - Informatik KW - Universität Potsdam KW - Universität Bagdad KW - Probleme in der Studie KW - Lehrer KW - Professoren KW - Theoretischen Vorlesungen KW - Programmierung KW - Anleitung KW - Hochschulsystem KW - Informatik-Studiengänge KW - Didaktik der Informatik Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-98437 ER - TY - THES A1 - Prasse, Paul T1 - Pattern recognition for computer security T1 - Mustererkennung für Computersicherheit BT - discriminative models for email spam campaign and malware detection BT - diskriminative Modelle zur Erkennung von Email Spam-Kampagnen und Malware N2 - Computer Security deals with the detection and mitigation of threats to computer networks, data, and computing hardware. This thesis addresses the following two computer security problems: email spam campaign and malware detection. Email spam campaigns can easily be generated using popular dissemination tools by specifying simple grammars that serve as message templates. A grammar is disseminated to nodes of a bot net, the nodes create messages by instantiating the grammar at random. Email spam campaigns can encompass huge data volumes and therefore pose a threat to the stability of the infrastructure of email service providers that have to store them. Malware -software that serves a malicious purpose- is affecting web servers, client computers via active content, and client computers through executable files. Without the help of malware detection systems it would be easy for malware creators to collect sensitive information or to infiltrate computers. The detection of threats -such as email-spam messages, phishing messages, or malware- is an adversarial and therefore intrinsically difficult problem. Threats vary greatly and evolve over time. The detection of threats based on manually-designed rules is therefore difficult and requires a constant engineering effort. Machine-learning is a research area that revolves around the analysis of data and the discovery of patterns that describe aspects of the data. Discriminative learning methods extract prediction models from data that are optimized to predict a target attribute as accurately as possible. Machine-learning methods hold the promise of automatically identifying patterns that robustly and accurately detect threats. This thesis focuses on the design and analysis of discriminative learning methods for the two computer-security problems under investigation: email-campaign and malware detection. The first part of this thesis addresses email-campaign detection. We focus on regular expressions as a syntactic framework, because regular expressions are intuitively comprehensible by security engineers and administrators, and they can be applied as a detection mechanism in an extremely efficient manner. In this setting, a prediction model is provided with exemplary messages from an email-spam campaign. The prediction model has to generate a regular expression that reveals the syntactic pattern that underlies the entire campaign, and that a security engineers finds comprehensible and feels confident enough to use the expression to blacklist further messages at the email server. We model this problem as two-stage learning problem with structured input and output spaces which can be solved using standard cutting plane methods. Therefore we develop an appropriate loss function, and derive a decoder for the resulting optimization problem. The second part of this thesis deals with the problem of predicting whether a given JavaScript or PHP file is malicious or benign. Recent malware analysis techniques use static or dynamic features, or both. In fully dynamic analysis, the software or script is executed and observed for malicious behavior in a sandbox environment. By contrast, static analysis is based on features that can be extracted directly from the program file. In order to bypass static detection mechanisms, code obfuscation techniques are used to spread a malicious program file in many different syntactic variants. Deobfuscating the code before applying a static classifier can be subjected to mostly static code analysis and can overcome the problem of obfuscated malicious code, but on the other hand increases the computational costs of malware detection by an order of magnitude. In this thesis we present a cascaded architecture in which a classifier first performs a static analysis of the original code and -based on the outcome of this first classification step- the code may be deobfuscated and classified again. We explore several types of features including token $n$-grams, orthogonal sparse bigrams, subroutine-hashings, and syntax-tree features and study the robustness of detection methods and feature types against the evolution of malware over time. The developed tool scans very large file collections quickly and accurately. Each model is evaluated on real-world data and compared to reference methods. Our approach of inferring regular expressions to filter emails belonging to an email spam campaigns leads to models with a high true-positive rate at a very low false-positive rate that is an order of magnitude lower than that of a commercial content-based filter. Our presented system -REx-SVMshort- is being used by a commercial email service provider and complements content-based and IP-address based filtering. Our cascaded malware detection system is evaluated on a high-quality data set of almost 400,000 conspicuous PHP files and a collection of more than 1,00,000 JavaScript files. From our case study we can conclude that our system can quickly and accurately process large data collections at a low false-positive rate. N2 - Computer-Sicherheit beschäftigt sich mit der Erkennung und der Abwehr von Bedrohungen für Computer-Netze, Daten und Computer-Hardware. In dieser Dissertation wird die Leistungsfähigkeit von Modellen des maschinellen Lernens zur Erkennung von Bedrohungen anhand von zwei konkreten Fallstudien analysiert. Im ersten Szenario wird die Leistungsfähigkeit von Modellen zur Erkennung von Email Spam-Kampagnen untersucht. E-Mail Spam-Kampagnen werden häufig von leicht zu bedienenden Tools erzeugt. Diese Tools erlauben es dem Benutzer, mit Hilfe eines Templates (z.B. einer regulären Grammatik) eine Emailvorlage zu definieren. Ein solches Template kann z.B. auf die Knoten eines Botnetzes verteilt werden. Dort werden Nachrichten mit diesem Template generiert und an verschiedene Absender verschickt. Die damit entstandenen E-Mail Spam-Kampagnen können riesige Datenmengen produzieren und somit zu einer Gefahr für die Stabilität der Infrastruktur von E-Mail-Service-Providern werden. Im zweiten Szenario wird die Leistungsfähigkeit von Modellen zur Erkennung von Malware untersucht. Malware bzw. Software, die schadhaften Programmcode enthält, kann Web-Server und Client-Computer über aktive Inhalte und Client-Computer über ausführbare Dateien beeinflussen. Somit kann die die reguläre und legitime Nutzung von Diensten verhindert werden. Des Weiteren kann Malware genutzt werden, um sensible Informationen zu sammeln oder Computer zu infiltrieren. Die Erkennung von Bedrohungen, die von E-Mail-Spam-Mails, Phishing-E-Mails oder Malware ausgehen, gestaltet sich schwierig. Zum einen verändern sich Bedrohungen von Zeit zu Zeit, zum anderen werden E-Mail-Spam-Mails oder Malware so modifiziert, dass sie von aktuellen Erkennungssystemen nicht oder nur schwer zu erkennen sind. Erkennungssysteme, die auf manuell erstellten Regeln basieren, sind deshalb wenig effektiv, da sie ständig administriert werden müssen. Sie müssen kontinuierlich gewartet werden, um neue Regeln (für veränderte oder neu auftretende Bedrohungen) zu erstellen und alte Regeln anzupassen bzw. zu löschen. Maschinelles Lernen ist ein Forschungsgebiet, das sich mit der Analyse von Daten und der Erkennung von Mustern beschäftigt, um bestimmte Aspekte in Daten, wie beispielsweise die Charakteristika von Malware, zu beschreiben. Mit Hilfe der Methoden des Maschinellen Lernens ist es möglich, automatisiert Muster in Daten zu erkennen. Diese Muster können genutzt werden, um Bedrohung gezielt und genau zu erkennen. Im ersten Teil wird ein Modell zur automatischen Erkennung von E-Mail-Spam-Kampag\-nen vorgestellt. Wir verwenden reguläre Ausdrücke als syntaktischen Rahmen, um E-Mail-Spam-Kampagnen zu beschreiben und E-Mails die zu einer E-Mail-Spam-Kampagne gehören zu identifizieren. Reguläre Ausdrücke sind intuitiv verständlich und können einfach von Administratoren genutzt werden, um E-Mail-Spam-Kampagnen zu beschreiben. Diese Arbeit stellt ein Modell vor, das für eine gegebene E-Mail-Spam-Kampagne einen regulären Ausdruck vorhersagt. In dieser Arbeit stellen wir ein Verfahren vor, um ein Modell zu bestimmen, das reguläre Ausdrücke vorhersagt, die zum Einen die Gesamtheit aller E-Mails in einer Spam-Kampagne abbilden und zum Anderen so verständlich aufgebaut sind, dass ein Systemadministrator eines E-Mail Servers diesen verwendet. Diese Problemstellung wird als ein zweistufiges Lernproblem mit strukturierten Ein- und Ausgaberäumen modelliert, welches mit Standardmethoden des Maschinellen Lernens gelöst werden kann. Hierzu werden eine geeignete Verlustfunktion, sowie ein Dekodierer für das resultierende Optimierungsproblem hergeleitet. Der zweite Teil behandelt die Analyse von Modellen zur Erkennung von Java-Script oder PHP-Dateien mit schadhaften Code. Viele neu entwickelte Malwareanalyse-Tools nutzen statische, dynamische oder eine Mischung beider Merkmalsarten als Eingabe, um Modelle zur Erkennung von Malware zu bilden. Um dynamische Merkmale zu extrahieren, wird eine Software oder ein Teil des Programmcodes in einer gesicherten Umgebung ausgeführt und das Verhalten (z.B. Speicherzugriffe oder Funktionsaufrufe) analysiert. Bei der statischen Analyse von Skripten und Software werden Merkmale direkt aus dem Programcode extrahiert. Um Erkennungsmechanismen, die nur auf statischen Merkmalen basieren, zu umgehen, wird der Programmcode oft maskiert. Die Maskierung von Programmcode wird genutzt, um einen bestimmten schadhaften Programmcode in vielen syntaktisch unterschiedlichen Varianten zu erzeugen. Der originale schadhafte Programmcode wird dabei erst zur Laufzeit generiert. Wird der Programmcode vor dem Anwenden eines Vorhersagemodells demaskiert, spricht man von einer vorwiegend statischen Programmcodeanalyse. Diese hat den Vorteil, dass enthaltener Schadcode einfacher zu erkennen ist. Großer Nachteil dieses Ansatzes ist die erhöhte Laufzeit durch das Demaskieren der einzelnen Dateien vor der Anwendung des Vorhersagemodells. In dieser Arbeit wird eine mehrstufige Architektur präsentiert, in der ein Klassifikator zunächst eine Vorhersage auf Grundlage einer statischen Analyse auf dem originalen Programmcode trifft. Basierend auf dieser Vorhersage wird der Programcode in einem zweiten Schritt demaskiert und erneut ein Vorhersagemodell angewendet. Wir betrachten dabei eine Vielzahl von möglichen Merkmalstypen, wie $n$-gram Merkmale, orthogonal sparse bigrams, Funktions-Hashes und Syntaxbaum Merkmale. Zudem wird in dieser Dissertation untersucht, wie robust die entwickelten Erkennungsmodelle gegenüber Veränderungen von Malware über die Zeit sind. Das vorgestellte Verfahren ermöglicht es, große Datenmengen mit hoher Treffergenauigkeit nach Malware zu durchsuchen. Alle in dieser Dissertation vorgestellten Modelle wurden auf echten Daten evaluiert und mit Referenzmethoden verglichen. Das vorgestellte Modell zur Erkennung von E-Mail-Spam-Kampagnen hat eine hohe richtig-positive Rate und eine sehr kleine falsch-positiv Rate die niedriger ist, als die eines kommerziellen E-Mail-Filters. Das Modell wird von einem kommerziellen E-Mail Service Provider während des operativen Geschäfts genutzt, um eingehende und ausgehende E-Mails eines E-Mails-Servers zu überprüfen. Der Ansatz zur Malwareerkennung wurde auf einem Datensatz mit rund 400.000 verdächtigen PHP Dateien und einer Sammlung von mehr als 1.000.000 Java-Script Dateien evaluiert. Die Fallstudie auf diesen Daten zeigt, dass das vorgestellte System schnell und mit hoher Genauigkeit riesige Datenmengen mit wenigen Falsch-Alarmen nach Malware durchsuchen kann. KW - malware detection KW - structured output prediction KW - pattern recognition KW - computer security KW - email spam detection KW - maschninelles Lernen KW - Computersicherheit KW - strukturierte Vorhersage KW - Klassifikation KW - Vorhersage KW - Spam KW - Malware Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-100251 ER - TY - THES A1 - Videla, Santiago T1 - Reasoning on the response of logical signaling networks with answer set programming T1 - Modellierung Logischer Signalnetzwerke mittels Antwortmengenprogrammierung N2 - Deciphering the functioning of biological networks is one of the central tasks in systems biology. In particular, signal transduction networks are crucial for the understanding of the cellular response to external and internal perturbations. Importantly, in order to cope with the complexity of these networks, mathematical and computational modeling is required. We propose a computational modeling framework in order to achieve more robust discoveries in the context of logical signaling networks. More precisely, we focus on modeling the response of logical signaling networks by means of automated reasoning using Answer Set Programming (ASP). ASP provides a declarative language for modeling various knowledge representation and reasoning problems. Moreover, available ASP solvers provide several reasoning modes for assessing the multitude of answer sets. Therefore, leveraging its rich modeling language and its highly efficient solving capacities, we use ASP to address three challenging problems in the context of logical signaling networks: learning of (Boolean) logical networks, experimental design, and identification of intervention strategies. Overall, the contribution of this thesis is three-fold. Firstly, we introduce a mathematical framework for characterizing and reasoning on the response of logical signaling networks. Secondly, we contribute to a growing list of successful applications of ASP in systems biology. Thirdly, we present a software providing a complete pipeline for automated reasoning on the response of logical signaling networks. N2 - Deciphering the functioning of biological networks is one of the central tasks in systems biology. In particular, signal transduction networks are crucial for the understanding of the cellular response to external and internal perturbations. Importantly, in order to cope with the complexity of these networks, mathematical and computational modeling is required. We propose a computational modeling framework in order to achieve more robust discoveries in the context of logical signaling networks. More precisely, we focus on modeling the response of logical signaling networks by means of automated reasoning using Answer Set Programming (ASP). ASP provides a declarative language for modeling various knowledge representation and reasoning problems. Moreover, available ASP solvers provide several reasoning modes for assessing the multitude of answer sets. Therefore, leveraging its rich modeling language and its highly efficient solving capacities, we use ASP to address three challenging problems in the context of logical signaling networks: learning of (Boolean) logical networks, experimental design, and identification of intervention strategies. Overall, the contribution of this thesis is three-fold. Firstly, we introduce a mathematical framework for characterizing and reasoning on the response of logical signaling networks. Secondly, we contribute to a growing list of successful applications of ASP in systems biology. Thirdly, we present a software providing a complete pipeline for automated reasoning on the response of logical signaling networks. KW - Systembiologie KW - logische Signalnetzwerke KW - Antwortmengenprogrammierung KW - systems biology KW - logical signaling networks KW - answer set programming Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-71890 ER - TY - THES A1 - Haider, Peter T1 - Prediction with Mixture Models T1 - Vorhersage mit Mischmodellen N2 - Learning a model for the relationship between the attributes and the annotated labels of data examples serves two purposes. Firstly, it enables the prediction of the label for examples without annotation. Secondly, the parameters of the model can provide useful insights into the structure of the data. If the data has an inherent partitioned structure, it is natural to mirror this structure in the model. Such mixture models predict by combining the individual predictions generated by the mixture components which correspond to the partitions in the data. Often the partitioned structure is latent, and has to be inferred when learning the mixture model. Directly evaluating the accuracy of the inferred partition structure is, in many cases, impossible because the ground truth cannot be obtained for comparison. However it can be assessed indirectly by measuring the prediction accuracy of the mixture model that arises from it. This thesis addresses the interplay between the improvement of predictive accuracy by uncovering latent cluster structure in data, and further addresses the validation of the estimated structure by measuring the accuracy of the resulting predictive model. In the application of filtering unsolicited emails, the emails in the training set are latently clustered into advertisement campaigns. Uncovering this latent structure allows filtering of future emails with very low false positive rates. In order to model the cluster structure, a Bayesian clustering model for dependent binary features is developed in this thesis. Knowing the clustering of emails into campaigns can also aid in uncovering which emails have been sent on behalf of the same network of captured hosts, so-called botnets. This association of emails to networks is another layer of latent clustering. Uncovering this latent structure allows service providers to further increase the accuracy of email filtering and to effectively defend against distributed denial-of-service attacks. To this end, a discriminative clustering model is derived in this thesis that is based on the graph of observed emails. The partitionings inferred using this model are evaluated through their capacity to predict the campaigns of new emails. Furthermore, when classifying the content of emails, statistical information about the sending server can be valuable. Learning a model that is able to make use of it requires training data that includes server statistics. In order to also use training data where the server statistics are missing, a model that is a mixture over potentially all substitutions thereof is developed. Another application is to predict the navigation behavior of the users of a website. Here, there is no a priori partitioning of the users into clusters, but to understand different usage scenarios and design different layouts for them, imposing a partitioning is necessary. The presented approach simultaneously optimizes the discriminative as well as the predictive power of the clusters. Each model is evaluated on real-world data and compared to baseline methods. The results show that explicitly modeling the assumptions about the latent cluster structure leads to improved predictions compared to the baselines. It is beneficial to incorporate a small number of hyperparameters that can be tuned to yield the best predictions in cases where the prediction accuracy can not be optimized directly. N2 - Das Lernen eines Modells für den Zusammenhang zwischen den Eingabeattributen und annotierten Zielattributen von Dateninstanzen dient zwei Zwecken. Einerseits ermöglicht es die Vorhersage des Zielattributs für Instanzen ohne Annotation. Andererseits können die Parameter des Modells nützliche Einsichten in die Struktur der Daten liefern. Wenn die Daten eine inhärente Partitionsstruktur besitzen, ist es natürlich, diese Struktur im Modell widerzuspiegeln. Solche Mischmodelle generieren Vorhersagen, indem sie die individuellen Vorhersagen der Mischkomponenten, welche mit den Partitionen der Daten korrespondieren, kombinieren. Oft ist die Partitionsstruktur latent und muss beim Lernen des Mischmodells mitinferiert werden. Eine direkte Evaluierung der Genauigkeit der inferierten Partitionsstruktur ist in vielen Fällen unmöglich, weil keine wahren Referenzdaten zum Vergleich herangezogen werden können. Jedoch kann man sie indirekt einschätzen, indem man die Vorhersagegenauigkeit des darauf basierenden Mischmodells misst. Diese Arbeit beschäftigt sich mit dem Zusammenspiel zwischen der Verbesserung der Vorhersagegenauigkeit durch das Aufdecken latenter Partitionierungen in Daten, und der Bewertung der geschätzen Struktur durch das Messen der Genauigkeit des resultierenden Vorhersagemodells. Bei der Anwendung des Filterns unerwünschter E-Mails sind die E-Mails in der Trainingsmende latent in Werbekampagnen partitioniert. Das Aufdecken dieser latenten Struktur erlaubt das Filtern zukünftiger E-Mails mit sehr niedrigen Falsch-Positiv-Raten. In dieser Arbeit wird ein Bayes'sches Partitionierunsmodell entwickelt, um diese Partitionierungsstruktur zu modellieren. Das Wissen über die Partitionierung von E-Mails in Kampagnen hilft auch dabei herauszufinden, welche E-Mails auf Veranlassen des selben Netzes von infiltrierten Rechnern, sogenannten Botnetzen, verschickt wurden. Dies ist eine weitere Schicht latenter Partitionierung. Diese latente Struktur aufzudecken erlaubt es, die Genauigkeit von E-Mail-Filtern zu erhöhen und sich effektiv gegen verteilte Denial-of-Service-Angriffe zu verteidigen. Zu diesem Zweck wird in dieser Arbeit ein diskriminatives Partitionierungsmodell hergeleitet, welches auf dem Graphen der beobachteten E-Mails basiert. Die mit diesem Modell inferierten Partitionierungen werden via ihrer Leistungsfähigkeit bei der Vorhersage der Kampagnen neuer E-Mails evaluiert. Weiterhin kann bei der Klassifikation des Inhalts einer E-Mail statistische Information über den sendenden Server wertvoll sein. Ein Modell zu lernen das diese Informationen nutzen kann erfordert Trainingsdaten, die Serverstatistiken enthalten. Um zusätzlich Trainingsdaten benutzen zu können, bei denen die Serverstatistiken fehlen, wird ein Modell entwickelt, das eine Mischung über potentiell alle Einsetzungen davon ist. Eine weitere Anwendung ist die Vorhersage des Navigationsverhaltens von Benutzern einer Webseite. Hier gibt es nicht a priori eine Partitionierung der Benutzer. Jedoch ist es notwendig, eine Partitionierung zu erzeugen, um verschiedene Nutzungsszenarien zu verstehen und verschiedene Layouts dafür zu entwerfen. Der vorgestellte Ansatz optimiert gleichzeitig die Fähigkeiten des Modells, sowohl die beste Partition zu bestimmen als auch mittels dieser Partition Vorhersagen über das Verhalten zu generieren. Jedes Modell wird auf realen Daten evaluiert und mit Referenzmethoden verglichen. Die Ergebnisse zeigen, dass das explizite Modellieren der Annahmen über die latente Partitionierungsstruktur zu verbesserten Vorhersagen führt. In den Fällen bei denen die Vorhersagegenauigkeit nicht direkt optimiert werden kann, erweist sich die Hinzunahme einer kleinen Anzahl von übergeordneten, direkt einstellbaren Parametern als nützlich. KW - maschinelles Lernen KW - Vorhersage KW - Clusteranalyse KW - Mischmodelle KW - machine learning KW - prediction KW - clustering KW - mixture models Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-69617 ER - TY - THES A1 - Dick, Uwe T1 - Discriminative Classification Models for Internet Security T1 - Diskriminative Klassifikationsmodelle in der Internet-Sicherheit BT - Mitigating Email Spam and HTTP-Layer DDoS Attacks BT - Verhindern von Email-Spam und HTTP-Layer DDoS-Attacken N2 - Services that operate over the Internet are under constant threat of being exposed to fraudulent use. Maintaining good user experience for legitimate users often requires the classification of entities as malicious or legitimate in order to initiate countermeasures. As an example, inbound email spam filters decide for spam or non-spam. They can base their decision on both the content of each email as well as on features that summarize prior emails received from the sending server. In general, discriminative classification methods learn to distinguish positive from negative entities. Each decision for a label may be based on features of the entity and related entities. When labels of related entities have strong interdependencies---as can be assumed e.g. for emails being delivered by the same user---classification decisions should not be made independently and dependencies should be modeled in the decision function. This thesis addresses the formulation of discriminative classification problems that are tailored for the specific demands of the following three Internet security applications. Theoretical and algorithmic solutions are devised to protect an email service against flooding of user inboxes, to mitigate abusive usage of outbound email servers, and to protect web servers against distributed denial of service attacks. In the application of filtering an inbound email stream for unsolicited emails, utilizing features that go beyond each individual email's content can be valuable. Information about each sending mail server can be aggregated over time and may help in identifying unwanted emails. However, while this information will be available to the deployed email filter, some parts of the training data that are compiled by third party providers may not contain this information. The missing features have to be estimated at training time in order to learn a classification model. In this thesis an algorithm is derived that learns a decision function that integrates over a distribution of values for each missing entry. The distribution of missing values is a free parameter that is optimized to learn an optimal decision function. The outbound stream of emails of an email service provider can be separated by the customer IDs that ask for delivery. All emails that are sent by the same ID in the same period of time are related, both in content and in label. Hijacked customer accounts may send batches of unsolicited emails to other email providers, which in turn might blacklist the sender's email servers after detection of incoming spam emails. The risk of being blocked from further delivery depends on the rate of outgoing unwanted emails and the duration of high spam sending rates. An optimization problem is developed that minimizes the expected cost for the email provider by learning a decision function that assigns a limit on the sending rate to customers based on the each customer's email stream. Identifying attacking IPs during HTTP-level DDoS attacks allows to block those IPs from further accessing the web servers. DDoS attacks are usually carried out by infected clients that are members of the same botnet and show similar traffic patterns. HTTP-level attacks aim at exhausting one or more resources of the web server infrastructure, such as CPU time. If the joint set of attackers cannot increase resource usage close to the maximum capacity, no effect will be experienced by legitimate users of hosted web sites. However, if the additional load raises the computational burden towards the critical range, user experience will degrade until service may be unavailable altogether. As the loss of missing one attacker depends on block decisions for other attackers---if most other attackers are detected, not blocking one client will likely not be harmful---a structured output model has to be learned. In this thesis an algorithm is developed that learns a structured prediction decoder that searches the space of label assignments, guided by a policy. Each model is evaluated on real-world data and is compared to reference methods. The results show that modeling each classification problem according to the specific demands of the task improves performance over solutions that do not consider the constraints inherent to an application. N2 - Viele Dienste im Internet benötigen zur Gewährleistung ihrer Erreichbarkeit die Möglichkeit, Entitäten als entweder gefährlich oder harmlos zu klassifizieren. Diskriminative Methoden des maschinellen Lernens verwenden Features von Entitäten oder Entitätengruppen, um zwischen positiven und negativen Labels zu unterscheiden. So können beispielsweise Email-Spamfilter Entscheidungen aufgrund sowohl des Inhalts der Email als auch von Informationen treffen, die vorherige Emails des gleichen versendenden Servers zusammenfassen. Darüber hinaus sind Labels zueinander in Verbindung stehender Entitäten, wie z.B. Emails des gleichen Nutzers, oftmals nicht unabhängig, so dass auch Klassifikationsentscheidungen nicht unabhängig getroffen werden sollten. Diese Arbeit beschäftigt sich mit der Formulierung diskriminativer Klassifikationsprobleme, die den speziellen Anforderungen von drei Internetsicherheitsanwendungen Rechnung tragen. Theoretische und algorithmische Lösungen zum Spamschutz von Nutzer-Inboxen eines Emailanbieters, zum Schutz von ausgehenden Emailservern gegen Missbrauch und zur Abwehr von Distributed Denial of Service-Attacken auf Webserver werden entwickelt. Beim Säubern der bei einem Emailanbieter eingehenden Menge von Emails von ungewollten Emails wie Spam können Informationen, die über den Inhalt einzelner Emails hinausgehen, von großem Nutzen sein. Etwa können Informationen über einen Mailserver zeitlich aggregiert und zum Klassifizieren neuer Emails des gleichen Servers verwendet werden. Diese Informationen sind in der Regel nur für Emails verfügbar, die vom Emailanbieter selbst empfangen werden, und fehlen bei Datensätzen, die extern gesammelte Emails beinhalten. Während des Trainings eines Spamklassifikators müssen diese Features entsprechend geschätzt werden. In dieser Arbeit wird ein Algorithmus entwickelt, der eine Entscheidungsfunktion lernt, die über eine Verteilung von fehlenden Werten integriert. Die Verteilung ist ein freier Parameter, der während des Lernens der Entscheidungsfunktion optimiert wird. Der Strom ausgehender Emails eines Emailanbieters setzt sich zusammen aus Emails einzelner Kunden. Alle Emails, die vom gleichen Kunden im gleichen Zeitraum gesendet werden, sind sowohl bzgl. Inhalt als auch Label abhängig. Kompromittierte Kundenaccounts können beispielsweise Batches von Spams an andere Emailanbieter schicken. Nach erfolgter Spamerkennung könnten diese Anbieter die Mailserver des sendenden Anbieters auf eine Blacklist setzen und somit am Versand weiterer Emails hindern. Das Risiko einer solchen Blockierung ist abhängig von der Rate ausgehender ungewollter Emails und der Dauer hoher Senderaten. Es wird ein Optimierungsproblem entwickelt, das die erwarteten Kosten des Emailproviders minimiert, indem eine Entscheidungsfunktion gelernt wird, die die erlaubte Versenderate von Kunden aufgrund der gesendeten Emails dynamisch einstellt. Um angreifende IPs während einer HTTP-Level-DDoS-Attacke zu blockieren, müssen sie als solche erkannt werden. DDoS-Angriffe werden üblicherweise von Clients durchgeführt, die dem gleichen Botnet angehören und ähnliche Traffic-Muster aufweisen. HTTP-Level-Angriffe zielen darauf, eine oder mehrere Ressourcen der Webserverinfrastruktur, wie etwa CPU-Zeit, aufzubrauchen. Für legitime Besucher ergeben sich erst dann Einschränkungen der User Experience, bis hin zur Unerreichbarkeit der Webseite, wenn Angreifer den Ressourcenverbrauch in die Nähe oder über die Maximalkapazität steigern können. Dieser durch einen Angreifer verursachte Verlust hängt von Entscheidungen für andere Angreifer ab; werden z.B. die meisten anderen Angreifer erkannt, wird ein nicht geblockter Angreifer kaum Schaden anrichten. Es wird deshalb ein Algorithmus entwickelt, der einen Dekodierer für strukturierte Vorhersagen trainiert, der, geleitet durch eine Policy, den Raum der gemeinsamen Labelzuweisungen durchsucht. Alle Modelle werden auf industriellen Daten evaluiert und mit Referenzmethoden verglichen. Die Ergebnisse zeigen, dass anforderungsspezifische Modellierung der Klassifikationsprobleme die Performance gegenüber den Vergleichsmethoden verbessert. KW - Machine Learning KW - Internet Security KW - DDoS KW - Spam-Filtering KW - DDoS KW - Internet-Sicherheit KW - Maschinelles Lernen KW - Spam-Erkennung Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-102593 ER - TY - THES A1 - Al-Areqi, Samih Taha Mohammed T1 - Semantics-based automatic geospatial service composition T1 - Semantikbasierte automatische Komposition von GIS-Diensten N2 - Although it has become common practice to build applications based on the reuse of existing components or services, technical complexity and semantic challenges constitute barriers to ensuring a successful and wide reuse of components and services. In the geospatial application domain, the barriers are self-evident due to heterogeneous geographic data, a lack of interoperability and complex analysis processes. Constructing workflows manually and discovering proper services and data that match user intents and preferences is difficult and time-consuming especially for users who are not trained in software development. Furthermore, considering the multi-objective nature of environmental modeling for the assessment of climate change impacts and the various types of geospatial data (e.g., formats, scales, and georeferencing systems) increases the complexity challenges. Automatic service composition approaches that provide semantics-based assistance in the process of workflow design have proven to be a solution to overcome these challenges and have become a frequent demand especially by end users who are not IT experts. In this light, the major contributions of this thesis are: (i) Simplification of service reuse and workflow design of applications for climate impact analysis by following the eXtreme Model-Driven Development (XMDD) paradigm. (ii) Design of a semantic domain model for climate impact analysis applications that comprises specifically designed services, ontologies that provide domain-specific vocabulary for referring to types and services, and the input/output annotation of the services using the terms defined in the ontologies. (iii) Application of a constraint-driven method for the automatic composition of workflows for analyzing the impacts of sea-level rise. The application scenario demonstrates the impact of domain modeling decisions on the results and the performance of the synthesis algorithm. N2 - Obwohl es gängige Praxis geworden ist, Anwendungen basierend auf der Wiederverwendung von existierenden Komponenten oder Diensten zu bauen, stellen technische Komplexität und semantische Herausforderungen Hindernisse beim Sicherstellen einer erfolgreichen und breiten Wiederverwendungen von Komponenten und Diensten. In der geowissenschaftlichen Anwendungsdomäne sind die Hindernisse durch heterogene geografische Daten, fehlende Interoperabilität und komplexe Analyseprozessen besonders offensichtlich. Workflows manuell zu konstruieren und passende Dienste und Daten zu finden, welche die Nutzerabsichten und -präferenzen abdecken, ist schwierig und zeitaufwändig besonders für Nutzer, die nicht in der Softwareentwicklung ausgebildet sind. Zudem erhöhen die verschiedenen Zielrichtungen der Umweltmodellierung für die Bewertung der Auswirkungen von Klimaänderungen und die unterschiedlichen Typen geografischer Daten (z.B. Formate, Skalierungen, und Georeferenzsysteme) die Komplexität. Automatische Dienstkompositionsansätze, die Semantik-basierte Unterstützung im Prozess des Workflowdesigns zur Verfügung stellen, haben bewiesen eine Lösung zur Bewältigung dieser Herausforderungen zu sein und sind besonders von Endnutzern, die keine IT-Experten sind, eine häufige Forderung geworden. Unter diesem Gesichtspunkt sind die Hauptbeiträge dieser Doktorarbeit: I. Vereinfachung der Wiederverwendung von Diensten und des Workflowdesigns von Klimafolgenanalysen durch Anwendung des Paradigma des eXtreme Model-Driven Development (XMDD) II. Design eines semantischen Domänenmodells für Anwendungen der Klimafolgenanalysen, welches speziell entwickelte Dienste, Ontologien (die domänen-spezifisches Vokabular zur Verfügung stellen, um Typen und Dienste zu beschreiben), und Eingabe-/Ausgabe-Annotationen der Dienste (unter Verwendung von Begriffen, die in den Ontologien definiert sind) enthält. III. Anwendungen einer Constraint-getriebenen Methode für die automatische Komposition von Workflows zum Analysieren der Auswirkungen des Meeresspiegelanstiegs. Das Anwendungsszenario demonstriert die Auswirkung von Domänenmodellierungsentscheidungen auf die Ergebnisse und die Laufzeit des Synthesealgorithmus. KW - geospatial services KW - service composition KW - scientific workflows KW - semantic domain modeling KW - ontologies KW - climate impact analysis KW - GIS-Dienstkomposition KW - Wissenschaftlichesworkflows KW - semantische Domänenmodellierung KW - Ontologien KW - Klimafolgenanalyse Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-402616 ER - TY - THES A1 - Glander, Tassilo T1 - Multi-scale representations of virtual 3D city models T1 - Maßstabsabhängige Repräsentationen virtueller 3D-Stadtmodelle N2 - Virtual 3D city and landscape models are the main subject investigated in this thesis. They digitally represent urban space and have many applications in different domains, e.g., simulation, cadastral management, and city planning. Visualization is an elementary component of these applications. Photo-realistic visualization with an increasingly high degree of detail leads to fundamental problems for comprehensible visualization. A large number of highly detailed and textured objects within a virtual 3D city model may create visual noise and overload the users with information. Objects are subject to perspective foreshortening and may be occluded or not displayed in a meaningful way, as they are too small. In this thesis we present abstraction techniques that automatically process virtual 3D city and landscape models to derive abstracted representations. These have a reduced degree of detail, while essential characteristics are preserved. After introducing definitions for model, scale, and multi-scale representations, we discuss the fundamentals of map generalization as well as techniques for 3D generalization. The first presented technique is a cell-based generalization of virtual 3D city models. It creates abstract representations that have a highly reduced level of detail while maintaining essential structures, e.g., the infrastructure network, landmark buildings, and free spaces. The technique automatically partitions the input virtual 3D city model into cells based on the infrastructure network. The single building models contained in each cell are aggregated to abstracted cell blocks. Using weighted infrastructure elements, cell blocks can be computed on different hierarchical levels, storing the hierarchy relation between the cell blocks. Furthermore, we identify initial landmark buildings within a cell by comparing the properties of individual buildings with the aggregated properties of the cell. For each block, the identified landmark building models are subtracted using Boolean operations and integrated in a photo-realistic way. Finally, for the interactive 3D visualization we discuss the creation of the virtual 3D geometry and their appearance styling through colors, labeling, and transparency. We demonstrate the technique with example data sets. Additionally, we discuss applications of generalization lenses and transitions between abstract representations. The second technique is a real-time-rendering technique for geometric enhancement of landmark objects within a virtual 3D city model. Depending on the virtual camera distance, landmark objects are scaled to ensure their visibility within a specific distance interval while deforming their environment. First, in a preprocessing step a landmark hierarchy is computed, this is then used to derive distance intervals for the interactive rendering. At runtime, using the virtual camera distance, a scaling factor is computed and applied to each landmark. The scaling factor is interpolated smoothly at the interval boundaries using cubic Bézier splines. Non-landmark geometry that is near landmark objects is deformed with respect to a limited number of landmarks. We demonstrate the technique by applying it to a highly detailed virtual 3D city model and a generalized 3D city model. In addition we discuss an adaptation of the technique for non-linear projections and mobile devices. The third technique is a real-time rendering technique to create abstract 3D isocontour visualization of virtual 3D terrain models. The virtual 3D terrain model is visualized as a layered or stepped relief. The technique works without preprocessing and, as it is implemented using programmable graphics hardware, can be integrated with minimal changes into common terrain rendering techniques. Consequently, the computation is done in the rendering pipeline for each vertex, primitive, i.e., triangle, and fragment. For each vertex, the height is quantized to the nearest isovalue. For each triangle, the vertex configuration with respect to their isovalues is determined first. Using the configuration, the triangle is then subdivided. The subdivision forms a partial step geometry aligned with the triangle. For each fragment, the surface appearance is determined, e.g., depending on the surface texture, shading, and height-color-mapping. Flexible usage of the technique is demonstrated with applications from focus+context visualization, out-of-core terrain rendering, and information visualization. This thesis presents components for the creation of abstract representations of virtual 3D city and landscape models. Re-using visual language from cartography, the techniques enable users to build on their experience with maps when interpreting these representations. Simultaneously, characteristics of 3D geovirtual environments are taken into account by addressing and discussing, e.g., continuous scale, interaction, and perspective. N2 - Gegenstand der Arbeit sind virtuelle 3D-Stadt- und Landschaftsmodelle, die den städtischen Raum in digitalen Repräsentationen abbilden. Sie werden in vielfältigen Anwendungen und zu unterschiedlichen Zwecken eingesetzt. Dabei ist die Visualisierung ein elementarer Bestandteil dieser Anwendungen. Durch realitätsnahe Darstellung und hohen Detailgrad entstehen jedoch zunehmend fundamentale Probleme für eine verständliche Visualisierung. So führt beispielsweise die hohe Anzahl von detailliert ausmodellierten und texturierten Objekten eines virtuellen 3D-Stadtmodells zu Informationsüberflutung beim Betrachter. In dieser Arbeit werden Abstraktionsverfahren vorgestellt, die diese Probleme behandeln. Ziel der Verfahren ist die automatische Transformation virtueller 3D-Stadt- und Landschaftsmodelle in abstrakte Repräsentationen, die bei reduziertem Detailgrad wichtige Charakteristika erhalten. Nach der Einführung von Grundbegriffen zu Modell, Maßstab und Mehrfachrepräsentationen werden theoretische Grundlagen zur Generalisierung von Karten sowie Verfahren zur 3D-Generalisierung betrachtet. Das erste vorgestellte Verfahren beschreibt die zellbasierte Generalisierung von virtuellen 3DStadtmodellen. Es erzeugt abstrakte Repräsentationen, die drastisch im Detailgrad reduziert sind, erhält dabei jedoch die wichtigsten Strukturen, z.B. das Infrastrukturnetz, Landmarkengebäude und Freiflächen. Dazu wird in einem vollautomatischen Verfahren das Eingabestadtmodell mithilfe des Infrastrukturnetzes in Zellen zerlegt. Pro Zelle wird abstrakte Gebäudegeometrie erzeugt, indem die enthaltenen Einzelgebäude mit ihren Eigenschaften aggregiert werden. Durch Berücksichtigung gewichteter Elemente des Infrastrukturnetzes können Zellblöcke auf verschiedenen Hierarchieebenen berechnet werden. Weiterhin werden Landmarken gesondert berücksichtigt: Anhand statistischer Abweichungen der Eigenschaften der Einzelgebäudes von den aggregierten Eigenschaften der Zelle werden Gebäude gegebenenfalls als initiale Landmarken identifiziert. Schließlich werden die Landmarkengebäude aus den generalisierten Blöcken mit Booleschen Operationen ausgeschnitten und realitätsnah dargestellt. Die Ergebnisse des Verfahrens lassen sich in interaktiver 3D-Darstellung einsetzen. Das Verfahren wird beispielhaft an verschiedenen Datensätzen demonstriert und bezüglich der Erweiterbarkeit diskutiert. Das zweite vorgestellte Verfahren ist ein Echtzeit-Rendering-Verfahren für geometrische Hervorhebung von Landmarken innerhalb eines virtuellen 3D-Stadtmodells: Landmarkenmodelle werden abhängig von der virtuellen Kameradistanz vergrößert, so dass sie innerhalb eines spezifischen Entfernungsintervalls sichtbar bleiben; dabei wird ihre Umgebung deformiert. In einem Vorverarbeitungsschritt wird eine Landmarkenhierarchie bestimmt, aus der die Entfernungsintervalle für die interaktive Darstellung abgeleitet werden. Zur Laufzeit wird anhand der virtuellen Kameraentfernung je Landmarke ein dynamischer Skalierungsfaktor bestimmt, der das Landmarkenmodell auf eine sichtbare Größe skaliert. Dabei wird der Skalierungsfaktor an den Intervallgrenzen durch kubisch interpoliert. Für Nicht-Landmarkengeometrie in der Umgebung wird die Deformation bezüglich einer begrenzten Menge von Landmarken berechnet. Die Eignung des Verfahrens wird beispielhaft anhand verschiedener Datensätze demonstriert und bezüglich der Erweiterbarkeit diskutiert. Das dritte vorgestellte Verfahren ist ein Echtzeit-Rendering-Verfahren, das eine abstrakte 3D-Isokonturen-Darstellung von virtuellen 3D-Geländemodellen erzeugt. Für das Geländemodell wird eine Stufenreliefdarstellung für eine Menge von nutzergewählten Höhenwerten erzeugt. Das Verfahren arbeitet ohne Vorverarbeitung auf Basis programmierbarer Grafikkarten-Hardware. Entsprechend erfolgt die Verarbeitung in der Prozesskette pro Geometrieknoten, pro Dreieck, und pro Bildfragment. Pro Geometrieknoten wird zunächst die Höhe auf den nächstliegenden Isowert quantisiert. Pro Dreieck wird dann die Konfiguration bezüglich der Isowerte der drei Geometrieknoten bestimmt. Anhand der Konfiguration wird eine geometrische Unterteilung vorgenommen, so dass ein Stufenausschnitt entsteht, der dem aktuellen Dreieck entspricht. Pro Bildfragment wird schließlich die finale Erscheinung definiert, z.B. anhand von Oberflächentextur, durch Schattierung und Höheneinfärbung. Die vielfältigen Einsatzmöglichkeiten werden mit verschiedenen Anwendungen demonstriert. Die Arbeit stellt Bausteine für die Erzeugung abstrakter Darstellungen von virtuellen 3D-Stadt und Landschaftsmodellen vor. Durch die Orientierung an kartographischer Bildsprache können die Nutzer auf bestehende Erfahrungen bei der Interpretation zurückgreifen. Dabei werden die charakteristischen Eigenschaften 3D geovirtueller Umgebungen berücksichtigt, indem z.B. kontinuierlicher Maßstab, Interaktion und Perspektive behandelt und diskutiert werden. KW - Generalisierung KW - virtuelle 3D-Stadtmodelle KW - Gebäudemodelle KW - Landmarken KW - Geländemodelle KW - generalization KW - virtual 3D city models KW - building models KW - landmarks KW - terrain models Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-64117 ER - TY - THES A1 - Seibel, Andreas T1 - Traceability and model management with executable and dynamic hierarchical megamodels T1 - Traceability und Modell Management mit ausführbaren und dynamischen Megamodellen N2 - Nowadays, model-driven engineering (MDE) promises to ease software development by decreasing the inherent complexity of classical software development. In order to deliver on this promise, MDE increases the level of abstraction and automation, through a consideration of domain-specific models (DSMs) and model operations (e.g. model transformations or code generations). DSMs conform to domain-specific modeling languages (DSMLs), which increase the level of abstraction, and model operations are first-class entities of software development because they increase the level of automation. Nevertheless, MDE has to deal with at least two new dimensions of complexity, which are basically caused by the increased linguistic and technological heterogeneity. The first dimension of complexity is setting up an MDE environment, an activity comprised of the implementation or selection of DSMLs and model operations. Setting up an MDE environment is both time-consuming and error-prone because of the implementation or adaptation of model operations. The second dimension of complexity is concerned with applying MDE for actual software development. Applying MDE is challenging because a collection of DSMs, which conform to potentially heterogeneous DSMLs, are required to completely specify a complex software system. A single DSML can only be used to describe a specific aspect of a software system at a certain level of abstraction and from a certain perspective. Additionally, DSMs are usually not independent but instead have inherent interdependencies, reflecting (partial) similar aspects of a software system at different levels of abstraction or from different perspectives. A subset of these dependencies are applications of various model operations, which are necessary to keep the degree of automation high. This becomes even worse when addressing the first dimension of complexity. Due to continuous changes, all kinds of dependencies, including the applications of model operations, must also be managed continuously. This comprises maintaining the existence of these dependencies and the appropriate (re-)application of model operations. The contribution of this thesis is an approach that combines traceability and model management to address the aforementioned challenges of configuring and applying MDE for software development. The approach is considered as a traceability approach because it supports capturing and automatically maintaining dependencies between DSMs. The approach is considered as a model management approach because it supports managing the automated (re-)application of heterogeneous model operations. In addition, the approach is considered as a comprehensive model management. Since the decomposition of model operations is encouraged to alleviate the first dimension of complexity, the subsequent composition of model operations is required to counteract their fragmentation. A significant portion of this thesis concerns itself with providing a method for the specification of decoupled yet still highly cohesive complex compositions of heterogeneous model operations. The approach supports two different kinds of compositions - data-flow compositions and context compositions. Data-flow composition is used to define a network of heterogeneous model operations coupled by sharing input and output DSMs alone. Context composition is related to a concept used in declarative model transformation approaches to compose individual model transformation rules (units) at any level of detail. In this thesis, context composition provides the ability to use a collection of dependencies as context for the composition of other dependencies, including model operations. In addition, the actual implementation of model operations, which are going to be composed, do not need to implement any composition concerns. The approach is realized by means of a formalism called an executable and dynamic hierarchical megamodel, based on the original idea of megamodels. This formalism supports specifying compositions of dependencies (traceability and model operations). On top of this formalism, traceability is realized by means of a localization concept, and model management by means of an execution concept. N2 - Die modellgetriebene Softwareentwicklung (MDE) verspricht heutzutage, durch das Verringern der inhärenten Komplexität der klassischen Softwareentwicklung, das Entwickeln von Software zu vereinfachen. Um dies zu erreichen, erhöht MDE das Abstraktions- und Automationsniveau durch die Einbindung domänenspezifischer Modelle (DSMs) und Modelloperationen (z.B. Modelltransformationen oder Codegenerierungen). DSMs sind konform zu domänenspezifischen Modellierungssprachen (DSMLs), die dazu dienen das Abstraktionsniveau der Softwareentwicklung zu erhöhen. Modelloperationen sind essentiell für die Softwareentwicklung da diese den Grad der Automatisierung erhöhen. Dennoch muss MDE mit Komplexitätsdimensionen umgehen die sich grundsätzlich aus der erhöhten sprachlichen und technologischen Heterogenität ergeben. Die erste Komplexitätsdimension ist das Konfigurieren einer Umgebung für MDE. Diese Aktivität setzt sich aus der Implementierung und Selektion von DSMLs sowie Modelloperationen zusammen. Eine solche Aktivität ist gerade durch die Implementierung und Anpassung von Modelloperationen zeitintensiv sowie fehleranfällig. Die zweite Komplexitätsdimension hängt mit der Anwendung von MDE für die eigentliche Softwareentwicklung zusammen. Das Anwenden von MDE ist eine Herausforderung weil eine Menge von heterogenen DSMs, die unterschiedlichen DSMLs unterliegen, erforderlich sind um ein komplexes Softwaresystem zu spezifizieren. Individuelle DSMLs werden verwendet um spezifische Aspekte eines Softwaresystems auf bestimmten Abstraktionsniveaus und aus bestimmten Perspektiven zu beschreiben. Hinzu kommt, dass DSMs sowie DSMLs grundsätzlich nicht unabhängig sind, sondern inhärente Abhängigkeiten besitzen. Diese Abhängigkeiten reflektieren äquivalente Aspekte eines Softwaresystems. Eine Teilmenge dieser Abhängigkeiten reflektieren Anwendungen diverser Modelloperationen, die notwendig sind um den Grad der Automatisierung hoch zu halten. Dies wird erschwert wenn man die erste Komplexitätsdimension hinzuzieht. Aufgrund kontinuierlicher Änderungen der DSMs, müssen alle Arten von Abhängigkeiten, inklusive die Anwendung von Modelloperationen, kontinuierlich verwaltet werden. Dies beinhaltet die Wartung dieser Abhängigkeiten und das sachgerechte (wiederholte) Anwenden von Modelloperationen. Der Beitrag dieser Arbeit ist ein Ansatz, der die Bereiche Traceability und Model Management vereint. Das Erfassen und die automatische Verwaltung von Abhängigkeiten zwischen DSMs unterstützt Traceability, während das (automatische) wiederholte Anwenden von heterogenen Modelloperationen Model Management ermöglicht. Dadurch werden die zuvor erwähnten Herausforderungen der Konfiguration und Anwendung von MDE überwunden. Die negativen Auswirkungen der ersten Komplexitätsdimension können gelindert werden indem Modelloperationen in atomare Einheiten zerlegt werden. Um der implizierten Fragmentierung entgegenzuwirken, erfordert dies allerdings eine nachfolgende Komposition der Modelloperationen. Der Ansatz wird als erweitertes Model Management betrachtet, da ein signifikanter Anteil dieser Arbeit die Kompositionen von heterogenen Modelloperationen behandelt. Unterstützt werden zwei unterschiedliche Arten von Kompositionen. Datenfluss-Kompositionen werden verwendet, um Netzwerke von heterogenen Modelloperationen zu beschreiben, die nur durch das Teilen von Ein- und Ausgabe DSMs komponiert werden. Kontext-Kompositionen bedienen sich eines Konzepts, das von deklarativen Modelltransformationen bekannt ist. Dies ermöglicht die Komposition von unabhängigen Transformationsregeln auf unterschiedlichsten Detailebenen. Die in dieser Arbeit eingeführten Kontext-Kompositionen bieten die Möglichkeit eine Menge von unterschiedlichsten Abhängigkeiten als Kontext für eine Komposition zu verwenden -- unabhängig davon ob diese Abhängigkeit eine Modelloperation repräsentiert. Zusätzlich müssen die Modelloperationen, die komponiert werden, selber keine Kompositionsaspekte implementieren, was deren Wiederverwendbarkeit erhöht. Realisiert wird dieser Ansatz durch einen Formalismus der Executable and Dynamic Hierarchical Megamodel genannt wird und auf der originalen Idee der Megamodelle basiert. Auf Basis dieses Formalismus' sind die Konzepte Traceability (hier Localization) und Model Management (hier Execution) umgesetzt. KW - Traceability KW - Modell Management KW - Megamodell KW - Modellgetriebene Entwicklung KW - Komposition KW - Traceability KW - Model Management KW - Megamodel KW - Model-Driven Engineering KW - Composition Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-64222 ER - TY - THES A1 - Polyvyanyy, Artem T1 - Structuring process models T1 - Strukturierung von Prozessmodellen N2 - One can fairly adopt the ideas of Donald E. Knuth to conclude that process modeling is both a science and an art. Process modeling does have an aesthetic sense. Similar to composing an opera or writing a novel, process modeling is carried out by humans who undergo creative practices when engineering a process model. Therefore, the very same process can be modeled in a myriad number of ways. Once modeled, processes can be analyzed by employing scientific methods. Usually, process models are formalized as directed graphs, with nodes representing tasks and decisions, and directed arcs describing temporal constraints between the nodes. Common process definition languages, such as Business Process Model and Notation (BPMN) and Event-driven Process Chain (EPC) allow process analysts to define models with arbitrary complex topologies. The absence of structural constraints supports creativity and productivity, as there is no need to force ideas into a limited amount of available structural patterns. Nevertheless, it is often preferable that models follow certain structural rules. A well-known structural property of process models is (well-)structuredness. A process model is (well-)structured if and only if every node with multiple outgoing arcs (a split) has a corresponding node with multiple incoming arcs (a join), and vice versa, such that the set of nodes between the split and the join induces a single-entry-single-exit (SESE) region; otherwise the process model is unstructured. The motivations for well-structured process models are manifold: (i) Well-structured process models are easier to layout for visual representation as their formalizations are planar graphs. (ii) Well-structured process models are easier to comprehend by humans. (iii) Well-structured process models tend to have fewer errors than unstructured ones and it is less probable to introduce new errors when modifying a well-structured process model. (iv) Well-structured process models are better suited for analysis with many existing formal techniques applicable only for well-structured process models. (v) Well-structured process models are better suited for efficient execution and optimization, e.g., when discovering independent regions of a process model that can be executed concurrently. Consequently, there are process modeling languages that encourage well-structured modeling, e.g., Business Process Execution Language (BPEL) and ADEPT. However, the well-structured process modeling implies some limitations: (i) There exist processes that cannot be formalized as well-structured process models. (ii) There exist processes that when formalized as well-structured process models require a considerable duplication of modeling constructs. Rather than expecting well-structured modeling from start, we advocate for the absence of structural constraints when modeling. Afterwards, automated methods can suggest, upon request and whenever possible, alternative formalizations that are "better" structured, preferably well-structured. In this thesis, we study the problem of automatically transforming process models into equivalent well-structured models. The developed transformations are performed under a strong notion of behavioral equivalence which preserves concurrency. The findings are implemented in a tool, which is publicly available. N2 - Im Sinne der Ideen von Donald E. Knuth ist die Prozessmodellierung sowohl Wissenschaft als auch Kunst. Prozessmodellierung hat immer auch eine ästhetische Dimension. Wie das Komponieren einer Oper oder das Schreiben eines Romans, so stellt auch die Prozessmodellierung einen kreativen Akt eines Individuums dar. Somit kann ein Prozess auf unterschiedlichste Weise modelliert werden. Prozessmodelle können anschließend mit wissenschaftlichen Methoden untersucht werden. Prozessmodelle liegen im Regelfall als gerichtete Graphen vor. Knoten stellen Aktivitäten und Entscheidungspunkte dar, während gerichtete Kanten die temporalen Abhängigkeiten zwischen den Knoten beschreiben. Gängige Prozessmodellierungssprachen, zum Beispiel die Business Process Model and Notation (BPMN) und Ereignisgesteuerte Prozessketten (EPK), ermöglichen die Erstellung von Modellen mit einer beliebig komplexen Topologie. Es gibt keine strukturellen Einschränkungen, welche die Kreativität oder Produktivität durch eine begrenzte Anzahl von Modellierungsalternativen einschränken würden. Nichtsdestotrotz ist es oft wünschenswert, dass Modelle bestimmte strukturelle Eigenschaften haben. Ein bekanntes strukturelles Merkmal für Prozessmodelle ist Wohlstrukturiertheit. Ein Prozessmodell ist wohlstrukturiert genau dann, wenn jeder Knoten mit mehreren ausgehenden Kanten (ein Split) einen entsprechenden Knoten mit mehreren eingehenden Kanten (einen Join) hat, und umgekehrt, so dass die Knoten welche zwischen dem Split und dem Join liegen eine single-entry-single-exit (SESE) Region bilden. Ist dies nicht der Fall, so ist das Modell unstrukturiert. Wohlstrukturiertheit ist aufgrund einer Vielzahl von Gründen wünschenswert: (i) Wohlstrukturierte Modelle sind einfacher auszurichten, wenn sie visualisiert werden, da sie planaren Graphen entsprechen. (ii) Wohlstrukturierte Modelle zeichnen sich durch eine höhere Verständlichkeit aus. (iii) Wohlstrukturierte Modelle haben oft weniger Fehler als unstrukturierte Modelle. Auch ist die Wahrscheinlichkeit fehlerhafter Änderungen größer, wenn Modelle unstrukturiert sind. (iv) Wohlstrukturierte Modelle eignen sich besser für die formale Analyse, da viele Techniken nur für wohlstrukturierte Modelle anwendbar sind. (v) Wohlstrukturierte Modelle sind eher für die effiziente Ausführung und Optimierung geeignet, z.B. wenn unabhängige Regionen eines Prozesses für die parallele Ausführung identifiziert werden. Folglich gibt es eine Reihe von Prozessmodellierungssprachen, z.B. die Business Process Execution Language (BPEL) und ADEPT, welche den Modellierer anhalten nur wohlstrukturierte Modelle zu erstellen. Solch wohlstrukturiertes Modellieren impliziert jedoch gewisse Einschränkungen: (i) Es gibt Prozesse, welche nicht mittels wohlstrukturierten Prozessmodellen dargestellt werden können. (ii) Es gibt Prozesse, für welche die wohlstrukturierte Modellierung mit einer erheblichen Vervielfältigung von Modellierungs-konstrukten einhergeht. Aus diesem Grund vertritt diese Arbeit den Standpunkt, dass ohne strukturelle Einschränkungen modelliert werden sollte, anstatt Wohlstrukturiertheit von Beginn an zu verlangen. Anschließend können, sofern gewünscht und wo immer es möglich ist, automatische Methoden Modellierungsalternativen vorschlagen, welche "besser" strukturiert sind, im Idealfall sogar wohlstrukturiert. Die vorliegende Arbeit widmet sich dem Problem der automatischen Transformation von Prozessmodellen in verhaltensäquivalente wohlstrukturierte Prozessmodelle. Die vorgestellten Transformationen erhalten ein strenges Verhaltensequivalenzkriterium, welches die Parallelität wahrt. Die Resultate sind in einem frei verfügbaren Forschungsprototyp implementiert worden. KW - Strukturierung KW - Wohlstrukturiertheit KW - Prozesse KW - Verhalten KW - Modellierung KW - Structuring KW - Well-structuredness KW - Process KW - Behavior KW - Modeling Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-59024 ER - TY - THES A1 - Middelanis, Robin T1 - Global response to local extremes—a storyline approach on economic loss propagation from weather extremes T1 - Globale Reaktion auf lokale Extreme — ein Storyline-Ansatz zu ökonomischer Schadensausbreitung aufgrund von Wetterextremen N2 - Due to anthropogenic greenhouse gas emissions, Earth’s average surface temperature is steadily increasing. As a consequence, many weather extremes are likely to become more frequent and intense. This poses a threat to natural and human systems, with local impacts capable of destroying exposed assets and infrastructure, and disrupting economic and societal activity. Yet, these effects are not locally confined to the directly affected regions, as they can trigger indirect economic repercussions through loss propagation along supply chains. As a result, local extremes yield a potentially global economic response. To build economic resilience and design effective adaptation measures that mitigate adverse socio-economic impacts of ongoing climate change, it is crucial to gain a comprehensive understanding of indirect impacts and the underlying economic mechanisms. Presenting six articles in this thesis, I contribute towards this understanding. To this end, I expand on local impacts under current and future climate, the resulting global economic response, as well as the methods and tools to analyze this response. Starting with a traditional assessment of weather extremes under climate change, the first article investigates extreme snowfall in the Northern Hemisphere until the end of the century. Analyzing an ensemble of global climate model projections reveals an increase of the most extreme snowfall, while mean snowfall decreases. Assessing repercussions beyond local impacts, I employ numerical simulations to compute indirect economic effects from weather extremes with the numerical agent-based shock propagation model Acclimate. This model is used in conjunction with the recently emerged storyline framework, which involves analyzing the impacts of a particular reference extreme event and comparing them to impacts in plausible counterfactual scenarios under various climate or socio-economic conditions. Using this approach, I introduce three primary storylines that shed light on the complex mechanisms underlying economic loss propagation. In the second and third articles of this thesis, I analyze storylines for the historical Hurricanes Sandy (2012) and Harvey (2017) in the USA. For this, I first estimate local economic output losses and then simulate the resulting global economic response with Acclimate. The storyline for Hurricane Sandy thereby focuses on global consumption price anomalies and the resulting changes in consumption. I find that the local economic disruption leads to a global wave-like economic price ripple, with upstream effects propagating in the supplier direction and downstream effects in the buyer direction. Initially, an upstream demand reduction causes consumption price decreases, followed by a downstream supply shortage and increasing prices, before the anomalies decay in a normalization phase. A dominant upstream or downstream effect leads to net consumption gains or losses of a region, respectively. Moreover, I demonstrate that a longer direct economic shock intensifies the downstream effect for many regions, leading to an overall consumption loss. The third article of my thesis builds upon the developed loss estimation method by incorporating projections to future global warming levels. I use these projections to explore how the global production response to Hurricane Harvey would change under further increased global warming. The results show that, while the USA is able to nationally offset direct losses in the reference configuration, other countries have to compensate for increasing shares of counterfactual future losses. This compensation is mainly achieved by large exporting countries, but gradually shifts towards smaller regions. These findings not only highlight the economy’s ability to flexibly mitigate disaster losses to a certain extent, but also reveal the vulnerability and economic disadvantage of regions that are exposed to extreme weather events. The storyline in the fourth article of my thesis investigates the interaction between global economic stress and the propagation of losses from weather extremes. I examine indirect impacts of weather extremes — tropical cyclones, heat stress, and river floods — worldwide under two different economic conditions: an unstressed economy and a globally stressed economy, as seen during the Covid-19 pandemic. I demonstrate that the adverse effects of weather extremes on global consumption are strongly amplified when the economy is under stress. Specifically, consumption losses in the USA and China double and triple, respectively, due to the global economy’s decreased capacity for disaster loss compensation. An aggravated scarcity intensifies the price response, causing consumption losses to increase. Advancing on the methods and tools used here, the final two articles in my thesis extend the agent-based model Acclimate and formalize the storyline approach. With the model extension described in the fifth article, regional consumers make rational choices on the goods bought such that their utility is maximized under a constrained budget. In an out-of-equilibrium economy, these rational consumers are shown to temporarily increase consumption of certain goods in spite of rising prices. The sixth article of my thesis proposes a formalization of the storyline framework, drawing on multiple studies including storylines presented in this thesis. The proposed guideline defines eight central elements that can be used to construct a storyline. Overall, this thesis contributes towards a better understanding of economic repercussions of weather extremes. It achieves this by providing assessments of local direct impacts, highlighting mechanisms and impacts of loss propagation, and advancing on methods and tools used. N2 - Mit dem kontinuierlichen Anstieg der globalen Mitteltemperatur aufgrund anthropogener Treibhausgasemissionen kann die Intensität und Häufigkeit vieler Wetterextreme zunehmen. Diese haben das Potential sowohl natürliche als auch menschliche Systeme stark zu beeinträchtigen. So hat die Zerstörung von Vermögenswerten und Infrastruktur sowie die Unterbrechung gesellschaftlicher und ökonomischer Abläufe oft negative wirtschaftliche Konsequenzen für direkt betroffene Regionen. Die Auswirkungen sind jedoch nicht lokal begrenzt, sondern können sich entlang von Lieferketten ausbreiten und somit auch indirekte Folgen in anderen Regionen haben – bis hin zu einer potenziell globalen wirtschaftlichen Reaktion. Daher sind Strategien zur Anpassung an veränderliche Klimabedingungen notwendig, um die Resilienz globaler Handelsketten zu stärken und dadurch negative sozioökonomische Folgen abzumildern. Hierfür ist ein besseres Verständnis lokaler Auswirkungen sowie ökonomischer Mechanismen zur Schadensausbreitung und deren Folgen erforderlich. Die vorliegende Dissertation umfasst insgesamt sechs Artikel, die zu diesem Verständnis beitragen. In diesen Studien werden zunächst lokale Auswirkungen von Wetterextremen unter gegenwärtigen und zukünftigen klimatischen Bedingungen untersucht. Weiterhin werden die globalen wirtschaftlichen Auswirkungen lokaler Wetterextreme sowie die darunterliegenden ökonomischen Effekte analysiert. In diesem Zusammenhang trägt diese Arbeit ferner zu der Weiterentwicklung der verwendeten Methoden und Ansätze bei. Der erste Artikel widmet sich zunächst der Betrachtung von extremem Schneefall in der nördlichen Hemisphäre unter dem Einfluss des Klimawandels. Zu diesem Zweck wird ein Ensemble von Projektionen globaler Klimamodelle bis zum Ende des Jahrhunderts analysiert. Die Projektionen zeigen dabei eine Verstärkung von extremen Schneefallereignissen, während die mittlere Schneefallintensität abnimmt. Um indirekte Auswirkungen von Wetterextremen zu erforschen, wird weiterhin das numerische agentenbasierte Modell Acclimate verwendet, welches die Ausbreitung ökonomischer Verlustkaskaden im globalen Versorgungsnetzwerk simuliert. In mehreren sogenannten Storylines werden die Auswirkungen eines historischen Referenzereignisses analysiert und mit den potentiellen Auswirkungen dieses Ereignisses unter plausiblen alternativen klimatischen oder sozioökonomischen Bedingungen verglichen. In dieser Dissertation werden drei zentrale Storylines vorgestellt, die jeweils unterschiedliche Aspekte der Schadensausbreitung von Wetterextremen untersuchen. Im zweiten und dritten Artikel dieser Arbeit werden dazu Storylines für die historischen Hurrikane Sandy (2012) und Harvey (2017) in den USA untersucht. Hierfür werden zunächst die lokalen ökonomischen Verluste durch diese Hurrikane ermittelt, welche als direkte wirtschaftliche Schockereignisse in Acclimate zur Berechnung der globalen Reaktion verwendet werden. Hierbei untersucht die Studie zu Hurricane Sandy globale Konsumpreisanomalien und damit einhergehende Auswirkungen auf das Konsumverhalten. Der direkte Schock löst hier eine wellenartige Veränderung globaler Konsumpreise mit drei Phasen aus, welche aus gegenläufigen Effekte aufwärts und abwärts der Lieferketten resultiert – sogenannten Upstream- und Downstream-Effekten. Zunächst steigt der Konsum aufgrund sinkender Preise durch Upstream-Effekte, bevor Preise aufgrund von Güterknappheit durch Downstream-Effekte wieder ansteigen und der Konsum abfällt. In einer Normalisierungsphase klingen diese Anomalien wieder ab. Ein länger anhaltender direkter wirtschaftlicher Schock verstärkt die Downstream-Phase und führt so in vielen Regionen insgesamt zu einem Konsumverlust. Die entwickelte Methode zur Berechnung direkter Verluste wird im dritten Artikel erweitert, indem Verstärkungen unter dem Einfluss des fortschreitenden Klimawandels berücksichtigt werden. Unter Nutzung dieser verstärkten direkten Verluste wird die Veränderung globaler Produktionsanomalien in Reaktion auf Hurricane Harvey simuliert. Die Ergebnisse zeigen, dass die USA bei zunehmender Erwärmung nicht mehr in der Lage sein werden, direkte Produktionsverluste auf nationaler Ebene auszugleichen. Stattdessen muss ein zunehmender Anteil dieser Verluste durch andere, insbesondere exportstarke Länder ausgeglichen werden. Der Anteil kleinerer Regionen an dieser ausgleichenden Produktion nimmt jedoch mit zunehmenden direkten Verlusten zu. Diese Produktionsverschiebungen verdeutlichen die Möglichkeit der globalen Wirtschaft, lokale Katastrophenverluste weitgehend flexibel abzumildern. Gleichzeitig veranschaulichen sie den Wettbewerbsnachteil direkt betroffener Wirtschaftsregionen. Die Storyline im vierten Artikel befasst sich mit dem Einfluss einer globalen wirtschaftlichen Krise auf die Schadensausbreitung von tropischen Wirbelstürmen, Hitzestress und Flussüberschwemmungen weltweit. Hierfür werden die indirekten Auswirkungen dieser Extreme unter dem Einfluss der global reduzierten wirtschaftlichen Aktivität während der Covid-19-Pandemie, sowie bei „normaler“ globaler Wirtschaftsleistung simuliert. Der Vergleich beider Szenarien zeigt bei global gestörter Wirtschaft eine deutliche Verstärkung negativer Konsumauswirkungen durch die simulierten Extreme. Konsumverluste steigen besonders stark in den USA und China an, wo sie sich verdoppeln bzw. verdreifachen. Diese Veränderungen resultieren aus der global verminderten wirtschaftlichen Kapazität, die für den Ausgleich der Produktionsverluste von Wetterextremen zur Verfügung steht. Dies verstärkt die Extremewetter-bedingte Güterknappheit, was zu Preisanstiegen und erhöhten Konsumverlusten führt. Abschließend werden in den letzten beiden Artikeln die in der Arbeit verwendeten Methoden und Ansätze erweitert. Hierfür wird das Modell Acclimate im fünften Artikel weiterentwickelt, indem Konsumenten als rational agierende Agenten modelliert werden. Mit dieser Erweiterung treffen lokale Verbraucher Entscheidungen über die konsumierten Güter so, dass diese den Nutzen eines begrenzten Budgets maximieren. Die entstehende Dynamik kann außerhalb eines wirtschaftlichen Gleichgewichts dazu führen, dass bestimmte Güter temporär trotz erhöhter Preise stärker nachgefragt werden. Der sechste Artikel formalisiert den Storyline-Ansatz und präsentiert einen Leitfaden für die Erstellung von Storylines. Dieser basiert auf den Ergebnissen mehrerer Studien, die diesen Ansatz verfolgen; einschließlich Storylines aus der vorliegenden Arbeit. Es werden insgesamt acht Elemente definiert, anhand derer eine Storyline-Studie erstellt werden kann. Insgesamt trägt diese Arbeit zu einem umfassenderen Verständnis der ökonomischen Auswirkungen von Wetterextremen bei. Hierfür werden lokale Auswirkungen von Extremen unter gegenwärtigen und zukünftigen klimatischen Bedingungen untersucht, sowie wichtige ökonomische Mechanismen und Auswirkungen der resultierenden Schadensausbreitung aufgedeckt. Neben diesen Erkenntnissen werden überdies Weiterentwicklungen der Methoden und Ansätze präsentiert, die weiterführende Analysen ermöglichen. KW - Klimawandel KW - Wetterextreme KW - indirekte ökonomische Effekte KW - makroökonomische Modellierung KW - climate change KW - weather extremes KW - indirect economic impacts KW - macro-economic modelling Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-611127 ER - TY - JOUR A1 - Middelanis, Robin A1 - Willner, Sven N. A1 - Otto, Christian A1 - Kuhla, Kilian A1 - Quante, Lennart A1 - Levermann, Anders T1 - Wave-like global economic ripple response to Hurricane Sandy JF - Environmental research letters : ERL / Institute of Physics N2 - Tropical cyclones range among the costliest disasters on Earth. Their economic repercussions along the supply and trade network also affect remote economies that are not directly affected. We here simulate possible global repercussions on consumption for the example case of Hurricane Sandy in the US (2012) using the shock-propagation model Acclimate. The modeled shock yields a global three-phase ripple: an initial production demand reduction and associated consumption price decrease, followed by a supply shortage with increasing prices, and finally a recovery phase. Regions with strong trade relations to the US experience strong magnitudes of the ripple. A dominating demand reduction or supply shortage leads to overall consumption gains or losses of a region, respectively. While finding these repercussions in historic data is challenging due to strong volatility of economic interactions, numerical models like ours can help to identify them by approaching the problem from an exploratory angle, isolating the effect of interest. For this, our model simulates the economic interactions of over 7000 regional economic sectors, interlinked through about 1.8 million trade relations. Under global warming, the wave-like structures of the economic response to major hurricanes like the one simulated here are likely to intensify and potentially overlap with other weather extremes. KW - supply chains KW - Hurricane Sandy KW - economic ripples KW - extreme weather KW - impacts KW - loss propagation KW - natural disasters Y1 - 2021 U6 - https://doi.org/10.1088/1748-9326/ac39c0 SN - 1748-9326 VL - 16 IS - 12 PB - IOP Publ. Ltd. CY - Bristol ER - TY - JOUR A1 - Quante, Lennart A1 - Willner, Sven N. A1 - Middelanis, Robin A1 - Levermann, Anders T1 - Regions of intensification of extreme snowfall under future warming JF - Scientific reports N2 - Due to climate change the frequency and character of precipitation are changing as the hydrological cycle intensifies. With regards to snowfall, global warming has two opposing influences; increasing humidity enables intense snowfall, whereas higher temperatures decrease the likelihood of snowfall. Here we show an intensification of extreme snowfall across large areas of the Northern Hemisphere under future warming. This is robust across an ensemble of global climate models when they are bias-corrected with observational data. While mean daily snowfall decreases, both the 99th and the 99.9th percentiles of daily snowfall increase in many regions in the next decades, especially for Northern America and Asia. Additionally, the average intensity of snowfall events exceeding these percentiles as experienced historically increases in many regions. This is likely to pose a challenge to municipalities in mid to high latitudes. Overall, extreme snowfall events are likely to become an increasingly important impact of climate change in the next decades, even if they will become rarer, but not necessarily less intense, in the second half of the century. Y1 - 2021 U6 - https://doi.org/10.1038/s41598-021-95979-4 SN - 2045-2322 VL - 11 IS - 1 PB - Macmillan Publishers Limited, part of Springer Nature CY - Berlin ER - TY - THES A1 - Makowski, Silvia T1 - Discriminative Models for Biometric Identification using Micro- and Macro-Movements of the Eyes N2 - Human visual perception is an active process. Eye movements either alternate between fixations and saccades or follow a smooth pursuit movement in case of moving targets. Besides these macroscopic gaze patterns, the eyes perform involuntary micro-movements during fixations which are commonly categorized into micro-saccades, drift and tremor. Eye movements are frequently studied in cognitive psychology, because they reflect a complex interplay of perception, attention and oculomotor control. A common insight of psychological research is that macro-movements are highly individual. Inspired by this finding, there has been a considerable amount of prior research on oculomotoric biometric identification. However, the accuracy of known approaches is too low and the time needed for identification is too long for any practical application. This thesis explores discriminative models for the task of biometric identification. Discriminative models optimize a quality measure of the predictions and are usually superior to generative approaches in discriminative tasks. However, using discriminative models requires to select a suitable form of data representation for sequential eye gaze data; i.e., by engineering features or constructing a sequence kernel and the performance of the classification model strongly depends on the data representation. We study two fundamentally different ways of representing eye gaze within a discriminative framework. In the first part of this thesis, we explore the integration of data and psychological background knowledge in the form of generative models to construct representations. To this end, we first develop generative statistical models of gaze behavior during reading and scene viewing that account for viewer-specific distributional properties of gaze patterns. In a second step, we develop a discriminative identification model by deriving Fisher kernel functions from these and several baseline models. We find that an SVM with Fisher kernel is able to reliably identify users based on their eye gaze during reading and scene viewing. However, since the generative models are constrained to use low-frequency macro-movements, they discard a significant amount of information contained in the raw eye tracking signal at a high cost: identification requires about one minute of input recording, which makes it inapplicable for real world biometric systems. In the second part of this thesis, we study a purely data-driven modeling approach. Here, we aim at automatically discovering the individual pattern hidden in the raw eye tracking signal. To this end, we develop a deep convolutional neural network DeepEyedentification that processes yaw and pitch gaze velocities and learns a representation end-to-end. Compared to prior work, this model increases the identification accuracy by one order of magnitude and the time to identification decreases to only seconds. The DeepEyedentificationLive model further improves upon the identification performance by processing binocular input and it also detects presentation-attacks. We find that by learning a representation, the performance of oculomotoric identification and presentation-attack detection can be driven close to practical relevance for biometric applications. Eye tracking devices with high sampling frequency and precision are expensive and the applicability of eye movement as a biometric feature heavily depends on cost of recording devices. In the last part of this thesis, we therefore study the requirements on data quality by evaluating the performance of the DeepEyedentificationLive network under reduced spatial and temporal resolution. We find that the method still attains a high identification accuracy at a temporal resolution of only 250 Hz and a precision of 0.03 degrees. Reducing both does not have an additive deteriorating effect. KW - Machine Learning Y1 - 2021 ER - TY - JOUR A1 - Schirrmann, Michael A1 - Landwehr, Niels A1 - Giebel, Antje A1 - Garz, Andreas A1 - Dammer, Karl-Heinz T1 - Early detection of stripe rust in winter wheat using deep residual neural networks JF - Frontiers in plant science : FPLS N2 - Stripe rust (Pst) is a major disease of wheat crops leading untreated to severe yield losses. The use of fungicides is often essential to control Pst when sudden outbreaks are imminent. Sensors capable of detecting Pst in wheat crops could optimize the use of fungicides and improve disease monitoring in high-throughput field phenotyping. Now, deep learning provides new tools for image recognition and may pave the way for new camera based sensors that can identify symptoms in early stages of a disease outbreak within the field. The aim of this study was to teach an image classifier to detect Pst symptoms in winter wheat canopies based on a deep residual neural network (ResNet). For this purpose, a large annotation database was created from images taken by a standard RGB camera that was mounted on a platform at a height of 2 m. Images were acquired while the platform was moved over a randomized field experiment with Pst-inoculated and Pst-free plots of winter wheat. The image classifier was trained with 224 x 224 px patches tiled from the original, unprocessed camera images. The image classifier was tested on different stages of the disease outbreak. At patch level the image classifier reached a total accuracy of 90%. To test the image classifier on image level, the image classifier was evaluated with a sliding window using a large striding length of 224 px allowing for fast test performance. At image level, the image classifier reached a total accuracy of 77%. Even in a stage with very low disease spreading (0.5%) at the very beginning of the Pst outbreak, a detection accuracy of 57% was obtained. Still in the initial phase of the Pst outbreak with 2 to 4% of Pst disease spreading, detection accuracy with 76% could be attained. With further optimizations, the image classifier could be implemented in embedded systems and deployed on drones, vehicles or scanning systems for fast mapping of Pst outbreaks. KW - yellow rust KW - monitoring KW - deep learning KW - wheat crops KW - image recognition KW - camera sensor KW - ResNet KW - smart farming Y1 - 2021 U6 - https://doi.org/10.3389/fpls.2021.469689 SN - 1664-462X VL - 12 PB - Frontiers Media CY - Lausanne ER - TY - JOUR A1 - Thon, Ingo A1 - Landwehr, Niels A1 - De Raedt, Luc T1 - Stochastic relational processes efficient inference and applications JF - Machine learning N2 - One of the goals of artificial intelligence is to develop agents that learn and act in complex environments. Realistic environments typically feature a variable number of objects, relations amongst them, and non-deterministic transition behavior. While standard probabilistic sequence models provide efficient inference and learning techniques for sequential data, they typically cannot fully capture the relational complexity. On the other hand, statistical relational learning techniques are often too inefficient to cope with complex sequential data. In this paper, we introduce a simple model that occupies an intermediate position in this expressiveness/efficiency trade-off. It is based on CP-logic (Causal Probabilistic Logic), an expressive probabilistic logic for modeling causality. However, by specializing CP-logic to represent a probability distribution over sequences of relational state descriptions and employing a Markov assumption, inference and learning become more tractable and effective. Specifically, we show how to solve part of the inference and learning problems directly at the first-order level, while transforming the remaining part into the problem of computing all satisfying assignments for a Boolean formula in a binary decision diagram. We experimentally validate that the resulting technique is able to handle probabilistic relational domains with a substantial number of objects and relations. KW - Statistical relational learning KW - Stochastic relational process KW - Markov processes KW - Time series KW - CP-Logic Y1 - 2011 U6 - https://doi.org/10.1007/s10994-010-5213-8 SN - 0885-6125 VL - 82 IS - 2 SP - 239 EP - 272 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Cilia, Elisa A1 - Landwehr, Niels A1 - Passerini, Andrea T1 - Relational feature mining with hierarchical multitask kFOIL JF - Fundamenta informaticae N2 - We introduce hierarchical kFOIL as a simple extension of the multitask kFOIL learning algorithm. The algorithm first learns a core logic representation common to all tasks, and then refines it by specialization on a per-task basis. The approach can be easily generalized to a deeper hierarchy of tasks. A task clustering algorithm is also proposed in order to automatically generate the task hierarchy. The approach is validated on problems of drug-resistance mutation prediction and protein structural classification. Experimental results show the advantage of the hierarchical version over both single and multi task alternatives and its potential usefulness in providing explanatory features for the domain. Task clustering allows to further improve performance when a deeper hierarchy is considered. Y1 - 2011 U6 - https://doi.org/10.3233/FI-2011-604 SN - 0169-2968 VL - 113 IS - 2 SP - 151 EP - 177 PB - IOS Press CY - Amsterdam ER - TY - JOUR A1 - Sawade, Christoph A1 - Bickel, Steffen A1 - von Oertzen, Timo A1 - Scheffer, Tobias A1 - Landwehr, Niels T1 - Active evaluation of ranking functions based on graded relevance JF - Machine learning N2 - Evaluating the quality of ranking functions is a core task in web search and other information retrieval domains. Because query distributions and item relevance change over time, ranking models often cannot be evaluated accurately on held-out training data. Instead, considerable effort is spent on manually labeling the relevance of query results for test queries in order to track ranking performance. We address the problem of estimating ranking performance as accurately as possible on a fixed labeling budget. Estimates are based on a set of most informative test queries selected by an active sampling distribution. Query labeling costs depend on the number of result items as well as item-specific attributes such as document length. We derive cost-optimal sampling distributions for the commonly used performance measures Discounted Cumulative Gain and Expected Reciprocal Rank. Experiments on web search engine data illustrate significant reductions in labeling costs. KW - Information retrieval KW - Ranking KW - Active evaluation Y1 - 2013 U6 - https://doi.org/10.1007/s10994-013-5372-5 SN - 0885-6125 VL - 92 IS - 1 SP - 41 EP - 64 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Hempel, Sabrina A1 - Adolphs, Julian A1 - Landwehr, Niels A1 - Willink, Dilya A1 - Janke, David A1 - Amon, Thomas T1 - Supervised machine learning to assess methane emissions of a dairy building with natural ventilation JF - Applied Sciences N2 - A reliable quantification of greenhouse gas emissions is a basis for the development of adequate mitigation measures. Protocols for emission measurements and data analysis approaches to extrapolate to accurate annual emission values are a substantial prerequisite in this context. We systematically analyzed the benefit of supervised machine learning methods to project methane emissions from a naturally ventilated cattle building with a concrete solid floor and manure scraper located in Northern Germany. We took into account approximately 40 weeks of hourly emission measurements and compared model predictions using eight regression approaches, 27 different sampling scenarios and four measures of model accuracy. Data normalization was applied based on median and quartile range. A correlation analysis was performed to evaluate the influence of individual features. This indicated only a very weak linear relation between the methane emission and features that are typically used to predict methane emission values of naturally ventilated barns. It further highlighted the added value of including day-time and squared ambient temperature as features. The error of the predicted emission values was in general below 10%. The results from Gaussian processes, ordinary multilinear regression and neural networks were least robust. More robust results were obtained with multilinear regression with regularization, support vector machines and particularly the ensemble methods gradient boosting and random forest. The latter had the added value to be rather insensitive against the normalization procedure. In the case of multilinear regression, also the removal of not significantly linearly related variables (i.e., keeping only the day-time component) led to robust modeling results. We concluded that measurement protocols with 7 days and six measurement periods can be considered sufficient to model methane emissions from the dairy barn with solid floor with manure scraper, particularly when periods are distributed over the year with a preference for transition periods. Features should be normalized according to median and quartile range and must be carefully selected depending on the modeling approach. KW - greenhouse gas KW - on-farm evaluation KW - emission factor KW - regression KW - ensemble methods KW - gradient boosting KW - random forest KW - neural networks KW - support vector machines Y1 - 2020 U6 - https://doi.org/10.3390/app10196938 SN - 2076-3417 VL - 10 IS - 19 PB - MDPI CY - Basel ER - TY - JOUR A1 - Gautam, Khem Raj A1 - Zhang, Guoqiang A1 - Landwehr, Niels A1 - Adolphs, Julian T1 - Machine learning for improvement of thermal conditions inside a hybrid ventilated animal building JF - Computers and electronics in agriculture : COMPAG online ; an international journal N2 - In buildings with hybrid ventilation, natural ventilation opening positions (windows), mechanical ventilation rates, heating, and cooling are manipulated to maintain desired thermal conditions. The indoor temperature is regulated solely by ventilation (natural and mechanical) when the external conditions are favorable to save external heating and cooling energy. The ventilation parameters are determined by a rule-based control scheme, which is not optimal. This study proposes a methodology to enable real-time optimum control of ventilation parameters. We developed offline prediction models to estimate future thermal conditions from the data collected from building in operation. The developed offline model is then used to find the optimal controllable ventilation parameters in real-time to minimize the setpoint deviation in the building. With the proposed methodology, the experimental building's setpoint deviation improved for 87% of time, on average, by 0.53 degrees C compared to the current deviations. KW - Animal building KW - Natural ventilation KW - Automatically controlled windows KW - Machine learning KW - Optimization Y1 - 2021 U6 - https://doi.org/10.1016/j.compag.2021.106259 SN - 0168-1699 SN - 1872-7107 VL - 187 PB - Elsevier Science CY - Amsterdam [u.a.] ER - TY - JOUR A1 - Camargo, Tibor de A1 - Schirrmann, Michael A1 - Landwehr, Niels A1 - Dammer, Karl-Heinz A1 - Pflanz, Michael T1 - Optimized deep learning model as a basis for fast UAV mapping of weed species in winter wheat crops JF - Remote sensing / Molecular Diversity Preservation International (MDPI) N2 - Weed maps should be available quickly, reliably, and with high detail to be useful for site-specific management in crop protection and to promote more sustainable agriculture by reducing pesticide use. Here, the optimization of a deep residual convolutional neural network (ResNet-18) for the classification of weed and crop plants in UAV imagery is proposed. The target was to reach sufficient performance on an embedded system by maintaining the same features of the ResNet-18 model as a basis for fast UAV mapping. This would enable online recognition and subsequent mapping of weeds during UAV flying operation. Optimization was achieved mainly by avoiding redundant computations that arise when a classification model is applied on overlapping tiles in a larger input image. The model was trained and tested with imagery obtained from a UAV flight campaign at low altitude over a winter wheat field, and classification was performed on species level with the weed species Matricaria chamomilla L., Papaver rhoeas L., Veronica hederifolia L., and Viola arvensis ssp. arvensis observed in that field. The ResNet-18 model with the optimized image-level prediction pipeline reached a performance of 2.2 frames per second with an NVIDIA Jetson AGX Xavier on the full resolution UAV image, which would amount to about 1.78 ha h(-1) area output for continuous field mapping. The overall accuracy for determining crop, soil, and weed species was 94%. There were some limitations in the detection of species unknown to the model. When shifting from 16-bit to 32-bit model precision, no improvement in classification accuracy was observed, but a strong decline in speed performance, especially when a higher number of filters was used in the ResNet-18 model. Future work should be directed towards the integration of the mapping process on UAV platforms, guiding UAVs autonomously for mapping purpose, and ensuring the transferability of the models to other crop fields. KW - ResNet KW - deep residual networks KW - UAV imagery KW - embedded systems KW - crop KW - monitoring KW - image classification KW - site-specific weed management KW - real-time mapping Y1 - 2021 U6 - https://doi.org/10.3390/rs13091704 SN - 2072-4292 VL - 13 IS - 9 PB - MDPI CY - Basel ER - TY - JOUR A1 - Abdelwahab, Ahmed A1 - Landwehr, Niels T1 - Deep Distributional Sequence Embeddings Based on a Wasserstein Loss JF - Neural processing letters N2 - Deep metric learning employs deep neural networks to embed instances into a metric space such that distances between instances of the same class are small and distances between instances from different classes are large. In most existing deep metric learning techniques, the embedding of an instance is given by a feature vector produced by a deep neural network and Euclidean distance or cosine similarity defines distances between these vectors. This paper studies deep distributional embeddings of sequences, where the embedding of a sequence is given by the distribution of learned deep features across the sequence. The motivation for this is to better capture statistical information about the distribution of patterns within the sequence in the embedding. When embeddings are distributions rather than vectors, measuring distances between embeddings involves comparing their respective distributions. The paper therefore proposes a distance metric based on Wasserstein distances between the distributions and a corresponding loss function for metric learning, which leads to a novel end-to-end trainable embedding model. We empirically observe that distributional embeddings outperform standard vector embeddings and that training with the proposed Wasserstein metric outperforms training with other distance functions. KW - Metric learning KW - Sequence embeddings KW - Deep learning Y1 - 2022 U6 - https://doi.org/10.1007/s11063-022-10784-y SN - 1370-4621 SN - 1573-773X PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Tran, Son Cao A1 - Pontelli, Enrico A1 - Balduccini, Marcello A1 - Schaub, Torsten T1 - Answer set planning BT - a survey JF - Theory and practice of logic programming N2 - Answer Set Planning refers to the use of Answer Set Programming (ASP) to compute plans, that is, solutions to planning problems, that transform a given state of the world to another state. The development of efficient and scalable answer set solvers has provided a significant boost to the development of ASP-based planning systems. This paper surveys the progress made during the last two and a half decades in the area of answer set planning, from its foundations to its use in challenging planning domains. The survey explores the advantages and disadvantages of answer set planning. It also discusses typical applications of answer set planning and presents a set of challenges for future research. KW - planning KW - knowledge representation and reasoning KW - logic programming Y1 - 2022 U6 - https://doi.org/10.1017/S1471068422000072 SN - 1471-0684 SN - 1475-3081 PB - Cambridge University Press CY - New York ER - TY - THES A1 - Schapranow, Matthieu-Patrick T1 - Real-time security extensions for EPCglobal networks Y1 - 2012 CY - Potsdam ER - TY - JOUR A1 - Brede, Nuria A1 - Botta, Nicola T1 - On the correctness of monadic backward induction JF - Journal of functional programming N2 - In control theory, to solve a finite-horizon sequential decision problem (SDP) commonly means to find a list of decision rules that result in an optimal expected total reward (or cost) when taking a given number of decision steps. SDPs are routinely solved using Bellman's backward induction. Textbook authors (e.g. Bertsekas or Puterman) typically give more or less formal proofs to show that the backward induction algorithm is correct as solution method for deterministic and stochastic SDPs. Botta, Jansson and Ionescu propose a generic framework for finite horizon, monadic SDPs together with a monadic version of backward induction for solving such SDPs. In monadic SDPs, the monad captures a generic notion of uncertainty, while a generic measure function aggregates rewards. In the present paper, we define a notion of correctness for monadic SDPs and identify three conditions that allow us to prove a correctness result for monadic backward induction that is comparable to textbook correctness proofs for ordinary backward induction. The conditions that we impose are fairly general and can be cast in category-theoretical terms using the notion of Eilenberg-Moore algebra. They hold in familiar settings like those of deterministic or stochastic SDPs, but we also give examples in which they fail. Our results show that backward induction can safely be employed for a broader class of SDPs than usually treated in textbooks. However, they also rule out certain instances that were considered admissible in the context of Botta et al. 's generic framework. Our development is formalised in Idris as an extension of the Botta et al. framework and the sources are available as supplementary material. Y1 - 2021 U6 - https://doi.org/10.1017/S0956796821000228 SN - 1469-7653 SN - 0956-7968 VL - 31 PB - Cambridge University Press CY - Cambridge ER - TY - BOOK A1 - Nazajkinskij, Vladimir E. A1 - Savin, Anton A1 - Schulze, Bert-Wolfgang A1 - Sternin, Boris T1 - Elliptic theory on manifolds with edges T3 - Preprint / Universität Potsdam, Institut für Mathematik, Arbeitsgruppe Partiell Y1 - 2004 SN - 1437-739X PB - Univ. CY - Potsdam ER - TY - BOOK A1 - Fedosov, Boris V. A1 - Schulze, Bert-Wolfgang A1 - Tarchanov, Nikolaj N. T1 - Analytic index formulas for elliptic corner operators T3 - Preprint / Universität Potsdam, Institut für Mathematik, Arbeitsgruppe Partiell Y1 - 2000 SN - 1437-739X PB - Univ. CY - Potsdam ER - TY - BOOK A1 - Egorov, Yu. A1 - Kondratiev, V. A. A1 - Schulze, Bert-Wolfgang T1 - On the completeness of root functions of elliptic boundary problems in a domain with conical points on the boundary T3 - Preprint / Universität Potsdam, Institut für Mathematik, Arbeitsgruppe Partiell Y1 - 2004 SN - 1437-739X PB - Univ. CY - Potsdam ER - TY - BOOK A1 - Nazajkinskij, Vladimir E. A1 - Savin, Anton A1 - Schulze, Bert-Wolfgang A1 - Sternin, Boris T1 - On the homotopy classification of elliptic operators on manifolds with edges T3 - Preprint / Universität Potsdam, Institut für Mathematik, Arbeitsgruppe Partiell Y1 - 2004 SN - 1437-739X PB - Univ. CY - Potsdam ER - TY - JOUR A1 - Michallek, Florian A1 - Genske, Ulrich A1 - Niehues, Stefan Markus A1 - Hamm, Bernd A1 - Jahnke, Paul T1 - Deep learning reconstruction improves radiomics feature stability and discriminative power in abdominal CT imaging BT - a phantom study JF - European Radiology N2 - Objectives To compare image quality of deep learning reconstruction (AiCE) for radiomics feature extraction with filtered back projection (FBP), hybrid iterative reconstruction (AIDR 3D), and model-based iterative reconstruction (FIRST). Methods Effects of image reconstruction on radiomics features were investigated using a phantom that realistically mimicked a 65-year-old patient's abdomen with hepatic metastases. The phantom was scanned at 18 doses from 0.2 to 4 mGy, with 20 repeated scans per dose. Images were reconstructed with FBP, AIDR 3D, FIRST, and AiCE. Ninety-three radiomics features were extracted from 24 regions of interest, which were evenly distributed across three tissue classes: normal liver, metastatic core, and metastatic rim. Features were analyzed in terms of their consistent characterization of tissues within the same image (intraclass correlation coefficient >= 0.75), discriminative power (Kruskal-Wallis test p value < 0.05), and repeatability (overall concordance correlation coefficient >= 0.75). Results The median fraction of consistent features across all doses was 6%, 8%, 6%, and 22% with FBP, AIDR 3D, FIRST, and AiCE, respectively. Adequate discriminative power was achieved by 48%, 82%, 84%, and 92% of features, and 52%, 20%, 17%, and 39% of features were repeatable, respectively. Only 5% of features combined consistency, discriminative power, and repeatability with FBP, AIDR 3D, and FIRST versus 13% with AiCE at doses above 1 mGy and 17% at doses >= 3 mGy. AiCE was the only reconstruction technique that enabled extraction of higher-order features. Conclusions AiCE more than doubled the yield of radiomics features at doses typically used clinically. Inconsistent tissue characterization within CT images contributes significantly to the poor stability of radiomics features. KW - Tomography KW - X-ray computed KW - Phantoms KW - imaging KW - Liver neoplasms KW - Algorithms KW - Reproducibility of results Y1 - 2022 U6 - https://doi.org/10.1007/s00330-022-08592-y SN - 1432-1084 VL - 32 IS - 7 SP - 4587 EP - 4595 PB - Springer CY - New York ER - TY - BOOK A1 - Harutjunjan, Gohar A1 - Schulze, Bert-Wolfgang T1 - Boundary problems with meromorphic symbols in cylindrical domains T3 - Preprint / Universität Potsdam, Institut für Mathematik, Arbeitsgruppe Partiell Y1 - 2004 SN - 1437-739X PB - Univ. CY - Potsdam ER - TY - BOOK A1 - Liu, Xiaochun A1 - Schulze, Bert-Wolfgang T1 - Boundary value problems in edge representation T3 - Preprint / Universität Potsdam, Institut für Mathematik, Arbeitsgruppe Partiell Y1 - 2004 SN - 1437-739X PB - Univ. CY - Potsdam ER - TY - JOUR A1 - Dines, Nicoleta A1 - Liu, Xiaochun A1 - Schulze, Bert-Wolfgang T1 - Edge quantisation of elliptic operators JF - Preprint / Universität Potsdam, Institut für Mathematik, Arbeitsgruppe Partiell N2 - The ellipticity of operators on a manifold with edge is defined as the bijectivity of the components of a principal symbolic hierarchy sigma = (sigma(psi), sigma(boolean AND)), where the second component takes values in operators on the infinite model cone of the local wedges. In the general understanding of edge problems there are two basic aspects: Quantisation of edge-degenerate operators in weighted Sobolev spaces, and verifying the ellipticity of the principal edge symbol sigma(boolean AND) which includes the (in general not explicity known) number of additional conditions of trace and potential type on the edge. We focus here on these questions and give explicit answers for a wide class of elliptic operators that are connected with the ellipticity of edge boundary value problems and reductions to the boundary. In particular, we study the edge quantisation and ellipticity for Dirichlet-Neumann operators with respect to interfaces of some codimension on a boundary. We show analogues of the Agranovich-Dynin formula for edge boundary value problems. Y1 - 2009 UR - http://www.springerlink.com/content/103082 U6 - https://doi.org/10.1007/s00605-008-0058-y SN - 1437-739X ER - TY - JOUR A1 - Bandyopadhyay, Soumyadip A1 - Sarkar, Dipankar A1 - Mandal, Chittaranjan A1 - Giese, Holger T1 - Translation validation of coloured Petri net models of programs on integers JF - Acta informatica N2 - Programs are often subjected to significant optimizing and parallelizing transformations based on extensive dependence analysis. Formal validation of such transformations needs modelling paradigms which can capture both control and data dependences in the program vividly. Being value-based with an inherent scope of capturing parallelism, the untimed coloured Petri net (CPN) models, reported in the literature, fit the bill well; accordingly, they are likely to be more convenient as the intermediate representations (IRs) of both the source and the transformed codes for translation validation than strictly sequential variable-based IRs like sequential control flow graphs (CFGs). In this work, an efficient path-based equivalence checking method for CPN models of programs on integers is presented. Extensive experimentation has been carried out on several sequential and parallel examples. Complexity and correctness issues have been treated rigorously for the method. Y1 - 2022 U6 - https://doi.org/10.1007/s00236-022-00419-z SN - 0001-5903 SN - 1432-0525 VL - 59 IS - 6 SP - 725 EP - 759 PB - Springer CY - New York ER - TY - JOUR A1 - Omranian, Nooshin A1 - Müller-Röber, Bernd A1 - Nikoloski, Zoran T1 - Segmentation of biological multivariate time-series data JF - Scientific reports N2 - Time-series data from multicomponent systems capture the dynamics of the ongoing processes and reflect the interactions between the components. The progression of processes in such systems usually involves check-points and events at which the relationships between the components are altered in response to stimuli. Detecting these events together with the implicated components can help understand the temporal aspects of complex biological systems. Here we propose a regularized regression-based approach for identifying breakpoints and corresponding segments from multivariate time-series data. In combination with techniques from clustering, the approach also allows estimating the significance of the determined breakpoints as well as the key components implicated in the emergence of the breakpoints. Comparative analysis with the existing alternatives demonstrates the power of the approach to identify biologically meaningful breakpoints in diverse time-resolved transcriptomics data sets from the yeast Saccharomyces cerevisiae and the diatom Thalassiosira pseudonana. Y1 - 2015 U6 - https://doi.org/10.1038/srep08937 SN - 2045-2322 VL - 5 PB - Nature Publ. Group CY - London ER - TY - JOUR A1 - Chen, Junchao A1 - Lange, Thomas A1 - Andjelkovic, Marko A1 - Simevski, Aleksandar A1 - Lu, Li A1 - Krstić, Miloš T1 - Solar particle event and single event upset prediction from SRAM-based monitor and supervised machine learning JF - IEEE transactions on emerging topics in computing / IEEE Computer Society, Institute of Electrical and Electronics Engineers N2 - The intensity of cosmic radiation may differ over five orders of magnitude within a few hours or days during the Solar Particle Events (SPEs), thus increasing for several orders of magnitude the probability of Single Event Upsets (SEUs) in space-borne electronic systems. Therefore, it is vital to enable the early detection of the SEU rate changes in order to ensure timely activation of dynamic radiation hardening measures. In this paper, an embedded approach for the prediction of SPEs and SRAM SEU rate is presented. The proposed solution combines the real-time SRAM-based SEU monitor, the offline-trained machine learning model and online learning algorithm for the prediction. With respect to the state-of-the-art, our solution brings the following benefits: (1) Use of existing on-chip data storage SRAM as a particle detector, thus minimizing the hardware and power overhead, (2) Prediction of SRAM SEU rate one hour in advance, with the fine-grained hourly tracking of SEU variations during SPEs as well as under normal conditions, (3) Online optimization of the prediction model for enhancing the prediction accuracy during run-time, (4) Negligible cost of hardware accelerator design for the implementation of selected machine learning model and online learning algorithm. The proposed design is intended for a highly dependable and self-adaptive multiprocessing system employed in space applications, allowing to trigger the radiation mitigation mechanisms before the onset of high radiation levels. KW - Machine learning KW - Single event upsets KW - Random access memory KW - monitoring KW - machine learning algorithms KW - predictive models KW - space missions KW - solar particle event KW - single event upset KW - machine learning KW - online learning KW - hardware accelerator KW - reliability KW - self-adaptive multiprocessing system Y1 - 2022 U6 - https://doi.org/10.1109/TETC.2022.3147376 SN - 2168-6750 VL - 10 IS - 2 SP - 564 EP - 580 PB - Institute of Electrical and Electronics Engineers CY - [New York, NY] ER - TY - JOUR A1 - Andjelković, Marko A1 - Chen, Junchao A1 - Simevski, Aleksandar A1 - Schrape, Oliver A1 - Krstić, Miloš A1 - Kraemer, Rolf T1 - Monitoring of particle count rate and LET variations with pulse stretching inverters JF - IEEE transactions on nuclear science : a publication of the IEEE Nuclear and Plasma Sciences Society N2 - This study investigates the use of pulse stretching (skew-sized) inverters for monitoring the variation of count rate and linear energy transfer (LET) of energetic particles. The basic particle detector is a cascade of two pulse stretching inverters, and the required sensing area is obtained by connecting up to 12 two-inverter cells in parallel and employing the required number of parallel arrays. The incident particles are detected as single-event transients (SETs), whereby the SET count rate denotes the particle count rate, while the SET pulsewidth distribution depicts the LET variations. The advantage of the proposed solution is the possibility to sense the LET variations using fully digital processing logic. SPICE simulations conducted on IHP's 130-nm CMOS technology have shown that the SET pulsewidth varies by approximately 550 ps over the LET range from 1 to 100 MeV center dot cm(2) center dot mg(-1). The proposed detector is intended for triggering the fault-tolerant mechanisms within a self-adaptive multiprocessing system employed in space. It can be implemented as a standalone detector or integrated in the same chip with the target system. KW - Particle detector KW - pulse stretching inverters KW - single-event transient KW - (SET) count rate KW - SET pulsewidth distribution Y1 - 2021 U6 - https://doi.org/10.1109/TNS.2021.3076400 SN - 0018-9499 SN - 1558-1578 VL - 68 IS - 8 SP - 1772 EP - 1781 PB - Institute of Electrical and Electronics Engineers CY - New York, NY ER - TY - JOUR A1 - Dimitriev, Alexej A1 - Saposhnikov, Vl. V. A1 - Gössel, Michael A1 - Saposhnikov, V. V. T1 - On-line testing by self-dual duplication Y1 - 1997 ER - TY - JOUR A1 - Saposhnikov, V. V. A1 - Morosov, Andrej A1 - Saposhnikov, Vl. V. A1 - Gössel, Michael T1 - A new design method for self-checking unidirectional combinational circuits Y1 - 1998 ER - TY - JOUR A1 - Seuring, Markus A1 - Gössel, Michael A1 - Sogomonyan, Egor S. T1 - A structural approach for space compaction for concurrent checking and BIST Y1 - 1998 ER - TY - JOUR A1 - Sogomonyan, Egor S. A1 - Gössel, Michael T1 - A new parity preserving multi-input signature analyser Y1 - 1995 ER - TY - JOUR A1 - Saposhnikov, Va. V. A1 - Morosov, Andrej A1 - Saposhnikov, Vl. V. A1 - Gössel, Michael T1 - Design of self-checking unidirectional combinational circuits with low area overhead Y1 - 1996 ER - TY - BOOK A1 - Saposhnikov, V. V. A1 - Saposhnikov, Vl. V. A1 - Morozov, Alexei A1 - Gössel, Michael T1 - Necessary and Sufficient Conditions for the Existence of Self-Checking Circuits ba Use of Complementary Circuits T3 - Preprint / Universität Potsdam, Institut für Informatik Y1 - 2004 SN - 0946-7580 VL - 2004, 1 PB - Univ. CY - Potsdam ER - TY - THES A1 - Andjelkovic, Marko T1 - A methodology for characterization, modeling and mitigation of single event transient effects in CMOS standard combinational cells T1 - Eine Methode zur Charakterisierung, Modellierung und Minderung von SET Effekten in kombinierten CMOS-Standardzellen N2 - With the downscaling of CMOS technologies, the radiation-induced Single Event Transient (SET) effects in combinational logic have become a critical reliability issue for modern integrated circuits (ICs) intended for operation under harsh radiation conditions. The SET pulses generated in combinational logic may propagate through the circuit and eventually result in soft errors. It has thus become an imperative to address the SET effects in the early phases of the radiation-hard IC design. In general, the soft error mitigation solutions should accommodate both static and dynamic measures to ensure the optimal utilization of available resources. An efficient soft-error-aware design should address synergistically three main aspects: (i) characterization and modeling of soft errors, (ii) multi-level soft error mitigation, and (iii) online soft error monitoring. Although significant results have been achieved, the effectiveness of SET characterization methods, accuracy of predictive SET models, and efficiency of SET mitigation measures are still critical issues. Therefore, this work addresses the following topics: (i) Characterization and modeling of SET effects in standard combinational cells, (ii) Static mitigation of SET effects in standard combinational cells, and (iii) Online particle detection, as a support for dynamic soft error mitigation. Since the standard digital libraries are widely used in the design of radiation-hard ICs, the characterization of SET effects in standard cells and the availability of accurate SET models for the Soft Error Rate (SER) evaluation are the main prerequisites for efficient radiation-hard design. This work introduces an approach for the SPICE-based standard cell characterization with the reduced number of simulations, improved SET models and optimized SET sensitivity database. It has been shown that the inherent similarities in the SET response of logic cells for different input levels can be utilized to reduce the number of required simulations. Based on characterization results, the fitting models for the SET sensitivity metrics (critical charge, generated SET pulse width and propagated SET pulse width) have been developed. The proposed models are based on the principle of superposition, and they express explicitly the dependence of the SET sensitivity of individual combinational cells on design, operating and irradiation parameters. In contrast to the state-of-the-art characterization methodologies which employ extensive look-up tables (LUTs) for storing the simulation results, this work proposes the use of LUTs for storing the fitting coefficients of the SET sensitivity models derived from the characterization results. In that way the amount of characterization data in the SET sensitivity database is reduced significantly. The initial step in enhancing the robustness of combinational logic is the application of gate-level mitigation techniques. As a result, significant improvement of the overall SER can be achieved with minimum area, delay and power overheads. For the SET mitigation in standard cells, it is essential to employ the techniques that do not require modifying the cell structure. This work introduces the use of decoupling cells for improving the robustness of standard combinational cells. By insertion of two decoupling cells at the output of a target cell, the critical charge of the cell’s output node is increased and the attenuation of short SETs is enhanced. In comparison to the most common gate-level techniques (gate upsizing and gate duplication), the proposed approach provides better SET filtering. However, as there is no single gate-level mitigation technique with optimal performance, a combination of multiple techniques is required. This work introduces a comprehensive characterization of gate-level mitigation techniques aimed to quantify their impact on the SET robustness improvement, as well as introduced area, delay and power overhead per gate. By characterizing the gate-level mitigation techniques together with the standard cells, the required effort in subsequent SER analysis of a target design can be reduced. The characterization database of the hardened standard cells can be utilized as a guideline for selection of the most appropriate mitigation solution for a given design. As a support for dynamic soft error mitigation techniques, it is important to enable the online detection of energetic particles causing the soft errors. This allows activating the power-greedy fault-tolerant configurations based on N-modular redundancy only at the high radiation levels. To enable such a functionality, it is necessary to monitor both the particle flux and the variation of particle LET, as these two parameters contribute significantly to the system SER. In this work, a particle detection approach based on custom-sized pulse stretching inverters is proposed. Employing the pulse stretching inverters connected in parallel enables to measure the particle flux in terms of the number of detected SETs, while the particle LET variations can be estimated from the distribution of SET pulse widths. This approach requires a purely digital processing logic, in contrast to the standard detectors which require complex mixed-signal processing. Besides the possibility of LET monitoring, additional advantages of the proposed particle detector are low detection latency and power consumption, and immunity to error accumulation. The results achieved in this thesis can serve as a basis for establishment of an overall soft-error-aware database for a given digital library, and a comprehensive multi-level radiation-hard design flow that can be implemented with the standard IC design tools. The following step will be to evaluate the achieved results with the irradiation experiments. N2 - Mit der Verkleinerung der Strukturen moderner CMOS-Technologien sind strahlungsinduzierte Single Event Transient (SET)-Effekte in kombinatorischer Logik zu einem kritischen Zuverlässigkeitsproblem in integrierten Schaltkreisen (ICs) geworden, die für den Betrieb unter rauen Strahlungsbedingungen (z. B. im Weltraum) vorgesehen sind. Die in der Kombinationslogik erzeugten SET-Impulse können durch die Schaltungen propagieren und schließlich in Speicherelementen (z.B. Flip-Flops oder Latches) zwischengespeichert werden, was zu sogenannten Soft-Errors und folglich zu Datenbeschädigungen oder einem Systemausfall führt. Daher ist es in den frühen Phasen des strahlungsharten IC-Designs unerlässlich geworden, die SET-Effekte systematisch anzugehen. Im Allgemeinen sollten die Lösungen zur Minderung von Soft-Errors sowohl statische als auch dynamische Maßnahmen berücksichtigen, um die optimale Nutzung der verfügbaren Ressourcen sicherzustellen. Somit sollte ein effizientes Soft-Error-Aware-Design drei Hauptaspekte synergistisch berücksichtigen: (i) die Charakterisierung und Modellierung von Soft-Errors, (ii) eine mehrstufige-Soft-Error-Minderung und (iii) eine Online-Soft-Error-Überwachung. Obwohl signifikante Ergebnisse erzielt wurden, sind die Wirksamkeit der SET-Charakterisierung, die Genauigkeit von Vorhersagemodellen und die Effizienz der Minderungsmaßnahmen immer noch die kritischen Punkte. Daher stellt diese Arbeit die folgenden Originalbeiträge vor: • Eine ganzheitliche Methodik zur SPICE-basierten Charakterisierung von SET-Effekten in kombinatorischen Standardzellen und entsprechenden Härtungskonfigurationen auf Gate-Ebene mit reduzierter Anzahl von Simulationen und reduzierter SET-Sensitivitätsdatenbank. • Analytische Modelle für SET-Empfindlichkeit (kritische Ladung, erzeugte SET-Pulsbreite und propagierte SET-Pulsbreite), basierend auf dem Superpositionsprinzip und Anpassung der Ergebnisse aus SPICE-Simulationen. • Ein Ansatz zur SET-Abschwächung auf Gate-Ebene, der auf dem Einfügen von zwei Entkopplungszellen am Ausgang eines Logikgatters basiert, was den Anstieg der kritischen Ladung und die signifikante Unterdrückung kurzer SETs beweist. • Eine vergleichende Charakterisierung der vorgeschlagenen SET-Abschwächungstechnik mit Entkopplungszellen und sieben bestehenden Techniken durch eine quantitative Bewertung ihrer Auswirkungen auf die Verbesserung der SET-Robustheit einzelner Logikgatter. • Ein Partikeldetektor auf Basis von Impulsdehnungs-Invertern in Skew-Größe zur Online-Überwachung des Partikelflusses und der LET-Variationen mit rein digitaler Anzeige. Die in dieser Dissertation erzielten Ergebnisse können als Grundlage für den Aufbau einer umfassenden Soft-Error-aware-Datenbank für eine gegebene digitale Bibliothek und eines umfassenden mehrstufigen strahlungsharten Designflusses dienen, der mit den Standard-IC-Designtools implementiert werden kann. Im nächsten Schritt werden die mit den Bestrahlungsexperimenten erzielten Ergebnisse ausgewertet. KW - Single Event Transient KW - radiation hardness design KW - Single Event Transient KW - Strahlungshärte Entwurf Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-534843 ER - TY - JOUR A1 - Schrape, Oliver A1 - Andjelkovic, Marko A1 - Breitenreiter, Anselm A1 - Zeidler, Steffen A1 - Balashov, Alexey A1 - Krstić, Miloš T1 - Design and evaluation of radiation-hardened standard cell flip-flops JF - IEEE transactions on circuits and systems : a publication of the IEEE Circuits and Systems Society: 1, Regular papers N2 - Use of a standard non-rad-hard digital cell library in the rad-hard design can be a cost-effective solution for space applications. In this paper we demonstrate how a standard non-rad-hard flip-flop, as one of the most vulnerable digital cells, can be converted into a rad-hard flip-flop without modifying its internal structure. We present five variants of a Triple Modular Redundancy (TMR) flip-flop: baseline TMR flip-flop, latch-based TMR flip-flop, True-Single Phase Clock (TSPC) TMR flip-flop, scannable TMR flip-flop and self-correcting TMR flipflop. For all variants, the multi-bit upsets have been addressed by applying special placement constraints, while the Single Event Transient (SET) mitigation was achieved through the usage of customized SET filters and selection of optimal inverter sizes for the clock and reset trees. The proposed flip-flop variants feature differing performance, thus enabling to choose the optimal solution for every sensitive node in the circuit, according to the predefined design constraints. Several flip-flop designs have been validated on IHP's 130nm BiCMOS process, by irradiation of custom-designed shift registers. It has been shown that the proposed TMR flip-flops are robust to soft errors with a threshold Linear Energy Transfer (LET) from (32.4 MeV.cm(2)/mg) to (62.5 MeV.cm(2)/mg), depending on the variant. KW - Single event effect KW - fault tolerance KW - triple modular redundancy KW - ASIC KW - design flow KW - radhard design Y1 - 2021 U6 - https://doi.org/10.1109/TCSI.2021.3109080 SN - 1549-8328 SN - 1558-0806 SN - 1057-7122 VL - 68 IS - 11 SP - 4796 EP - 4809 PB - Inst. of Electr. and Electronics Engineers CY - New York, NY ER - TY - JOUR A1 - Breitenreiter, Anselm A1 - Andjelković, Marko A1 - Schrape, Oliver A1 - Krstić, Miloš T1 - Fast error propagation probability estimates by answer set programming and approximate model counting JF - IEEE Access N2 - We present a method employing Answer Set Programming in combination with Approximate Model Counting for fast and accurate calculation of error propagation probabilities in digital circuits. By an efficient problem encoding, we achieve an input data format similar to a Verilog netlist so that extensive preprocessing is avoided. By a tight interconnection of our application with the underlying solver, we avoid iterating over fault sites and reduce calls to the solver. Several circuits were analyzed with varying numbers of considered cycles and different degrees of approximation. Our experiments show, that the runtime can be reduced by approximation by a factor of 91, whereas the error compared to the exact result is below 1%. KW - Circuit faults KW - Integrated circuit modeling KW - Programming KW - Analytical models KW - Search problems KW - Flip-flops KW - Encoding KW - Answer set programming KW - approximate model counting KW - error propagation KW - radhard design KW - reliability analysis KW - selective fault tolerance KW - single event upsets Y1 - 2022 U6 - https://doi.org/10.1109/ACCESS.2022.3174564 SN - 2169-3536 VL - 10 SP - 51814 EP - 51825 PB - Inst. of Electr. and Electronics Engineers CY - Piscataway ER - TY - JOUR A1 - Gössel, Michael A1 - Sogomonyan, Egor S. T1 - A parity-preserving multi-input signature analyzer and it application for concurrent checking and BIST Y1 - 1996 ER - TY - JOUR A1 - Li, Yuanqing A1 - Chen, Li A1 - Nofal, Issam A1 - Chen, Mo A1 - Wang, Haibin A1 - Liu, Rui A1 - Chen, Qingyu A1 - Krstić, Miloš A1 - Shi, Shuting A1 - Guo, Gang A1 - Baeg, Sang H. A1 - Wen, Shi-Jie A1 - Wong, Richard T1 - Modeling and analysis of single-event transient sensitivity of a 65 nm clock tree JF - Microelectronics reliability N2 - The soft error rate (SER) due to heavy-ion irradiation of a clock tree is investigated in this paper. A method for clock tree SER prediction is developed, which employs a dedicated soft error analysis tool to characterize the single-event transient (SET) sensitivities of clock inverters and other commercial tools to calculate the SER through fault-injection simulations. A test circuit including a flip-flop chain and clock tree in a 65 nm CMOS technology is developed through the automatic ASIC design flow. This circuit is analyzed with the developed method to calculate its clock tree SER. In addition, this circuit is implemented in a 65 nm test chip and irradiated by heavy ions to measure its SER resulting from the SETs in the clock tree. The experimental and calculation results of this case study present good correlation, which verifies the effectiveness of the developed method. KW - Clock tree KW - Modeling KW - Single-event transient (SET) Y1 - 2018 U6 - https://doi.org/10.1016/j.microrel.2018.05.016 SN - 0026-2714 VL - 87 SP - 24 EP - 32 PB - Elsevier CY - Oxford ER - TY - JOUR A1 - Morosov, Andrej A1 - Saposhnikov, Vl. V. A1 - Saposhnikov, V. V. A1 - Gössel, Michael T1 - Design of self dual fault-secure combinational circuits Y1 - 1997 ER - TY - JOUR A1 - Saposhnikov, Vl. V. A1 - Saposhnikov, V. V. A1 - Dimitriev, Alexej A1 - Gössel, Michael T1 - Self-dual duplication for error detection Y1 - 1998 ER - TY - JOUR A1 - Seuring, Markus A1 - Gössel, Michael T1 - A structural approach for space compaction for sequential circuits Y1 - 1999 ER - TY - JOUR A1 - Hartje, Hendrik A1 - Gössel, Michael A1 - Sogomonyan, Egor S. T1 - Synthesis of code-disjoint combinational circuits Y1 - 1997 ER - TY - GEN A1 - Krstić, Miloš A1 - Jentzsch, Anne-Kristin T1 - Reliability, safety and security of the electronics in automated driving vehicles - joint lab lecturing approach T2 - 2018 12TH European Workshop on Microelectronics Education (EWME) N2 - This paper proposes an education approach for master and bachelor students to enhance their skills in the area of reliability, safety and security of the electronic components in automated driving. The approach is based on the active synergetic work of research institutes, academia and industry in the frame of joint lab. As an example, the jointly organized summer school with the respective focus is organized and elaborated. KW - reliability KW - safety KW - security KW - automated driving KW - joint lab Y1 - 2018 SN - 978-1-5386-1157-9 SP - 21 EP - 22 PB - IEEE CY - New York ER - TY - JOUR A1 - Singh, Adit D. A1 - Sogomonyan, Egor S. A1 - Gössel, Michael A1 - Seuring, Markus T1 - Testability evaluation of sequential designs incorporating the multi-mode scannable memory element Y1 - 1999 ER - TY - JOUR A1 - Saposhnikov, V. V. A1 - Saposhnikov, Vl. V. A1 - Gössel, Michael A1 - Morosov, Andrej T1 - A method of construction of combinational self-checking units with detection of all single faults Y1 - 1999 ER - TY - JOUR A1 - Gössel, Michael A1 - Sogomonyan, Egor S. T1 - Self-parity combinational-circuits for self-testing, concurrent fault-detection and parity scan design Y1 - 1994 ER - TY - JOUR A1 - Gössel, Michael A1 - Sogomonyan, Egor S. A1 - Morosov, Andrej T1 - A new totally error propagating compactor for arbitrary cores with digital interfaces Y1 - 1999 ER - TY - JOUR A1 - Gössel, Michael A1 - Morosov, Andrej A1 - Saposhnikov, V. V. A1 - Saposhnikov, VL. V. T1 - Design of combinational self-testing devices with unidirectionally independent outputs Y1 - 1994 ER - TY - BOOK A1 - Marienfeld, Daniel A1 - Sogomonyan, Egor S. A1 - Ocheretnij, V. A1 - Gössel, Michael T1 - Self-checking Output-duplicated Booth-2 Multiplier T3 - Preprint / Universität Potsdam, Institut für Informatik Y1 - 2005 SN - 0946-7580 VL - 2005, 1 PB - Univ. CY - Potsdam ER - TY - JOUR A1 - Sogomonyan, Egor S. A1 - Singh, Adit D. A1 - Gössel, Michael T1 - A scan based concrrent BIST approach for low cost on-line testing Y1 - 1998 ER - TY - JOUR A1 - Dmitriev, Alexej A1 - Saposhnikov, V. V. A1 - Saposhnikov, Vl. V. A1 - Gössel, Michael T1 - Self-dual sequential circuits for concurrent chechking Y1 - 1999 SN - 0-7695-0390-X ; 0-7695-0391-8 ER - TY - BOOK A1 - Sogomonyan, Egor S. A1 - Marienfeld, Daniel A1 - Ocheretnij, V. A1 - Gössel, Michael T1 - A new self-checking sum-bit duplicated carry-select adder T3 - Preprint / Universität Potsdam, Institut für Informatik Y1 - 2003 SN - 0946-7580 VL - 2003, 5 PB - Univ. CY - Potsdam ER - TY - JOUR A1 - Sogomonyan, Egor S. A1 - Singh, Adit D. A1 - Gössel, Michael T1 - A multi-mode scannable memory element for high test application efficiency and delay testing Y1 - 1999 ER - TY - BOOK A1 - Wu, K. A1 - Karri, R. A1 - Kuznetsov, Grigory A1 - Gössel, Michael T1 - Low Cost Concurrent Error Detection for the Advanced Encryption Standart T3 - Preprint / Universität Potsdam, Institut für Informatik Y1 - 2003 SN - 0946-7580 VL - 2003, 8 PB - Univ. CY - Potsdam ER - TY - JOUR A1 - Ocheretnij, Vitalij A1 - Gössel, Michael A1 - Sogomonyan, Egor S. A1 - Marienfeld, Daniel T1 - Modulo p=3 checking for a carry select adder N2 - In this paper a self-checking carry select adder is proposed. The duplicated adder blocks which are inherent to a carry select adder without error detection are checked modulo 3. Compared to a carry select adder without error detection the delay of the MSB of the sum of the proposed adder does not increase. Compared to a self-checking duplicated carry select adder the area is reduced by 20%. No restrictions are imposed on the design of the adder blocks Y1 - 2006 UR - http://www.springerlink.com/content/100286 U6 - https://doi.org/10.1007/s10836-006-6260-8 ER - TY - JOUR A1 - Otscheretnij, Vitalij A1 - Saposhnikov, Vl. V. A1 - Saposhnikov, V. V. A1 - Gössel, Michael T1 - Fault-tolerant self-dual circuits Y1 - 1999 ER - TY - JOUR A1 - Saposhnikov, Vl. V. V. V. A1 - Moshanin, Vl. A1 - Saposhnikov, V. V. A1 - Gössel, Michael T1 - Experimental results for self-dual multi-output combinational circuits Y1 - 1999 ER - TY - JOUR A1 - Saposhnikov, Vl. V. A1 - Ocheretnij, V. A1 - Saposhnikov, V. V. A1 - Gössel, Michael T1 - Modified TMR-system with reduced hardware overhead Y1 - 1999 ER - TY - JOUR A1 - Gössel, Michael A1 - Sogomonyan, Egor S. T1 - New totally self-checking ripple and carry look-ahead adders Y1 - 1999 ER - TY - JOUR A1 - Gössel, Michael T1 - A new method of redundancy addition for circuit optimization JF - Preprint / Universität Potsdam, Institut für Informatik Y1 - 1999 SN - 0946-7580 VL - 1999, 08 PB - Univ. CY - Potsdam ER - TY - JOUR A1 - Bogue, Ted A1 - Jürgensen, Helmut A1 - Gössel, Michael T1 - Design of cover circuits for monitoring the output of a MISR Y1 - 1994 SN - 0-8186-6307-3 , 0-8186-6306-5 ER - TY - JOUR A1 - Saposhnikov, Vl. V. A1 - Dimitriev, Alexej A1 - Gössel, Michael A1 - Saposhnikov, Va. V. T1 - Self-dual parity checking - a new method for on-line testing Y1 - 1996 ER - TY - JOUR A1 - Gössel, Michael A1 - Sogomonyan, Egor S. T1 - Code disjoint self-parity combinational circuits for self-testing, concurrent fault detection and parity scan design Y1 - 1994 ER - TY - JOUR A1 - Kundu, S. A1 - Sogomonyan, Egor S. A1 - Gössel, Michael A1 - Tarnick, Steffen T1 - Self-checking comparator with one periodiv output Y1 - 1996 ER - TY - JOUR A1 - Hartje, Hendrik A1 - Sogomonyan, Egor S. A1 - Gössel, Michael T1 - Code disjoint circuits for partity codes Y1 - 1997 ER -