@book{MeinelSack2012, author = {Meinel, Christoph and Sack, Harald}, title = {Internetworking : technische Grundlagen und Anwendungen}, publisher = {Springer-Verlag Berlin Heidelberg}, address = {Berlin, Heidelberg}, isbn = {978-3-540-92939-0}, doi = {10.1007/978-3-540-92940-6}, pages = {978 S.}, year = {2012}, language = {de} } @phdthesis{Ghasemzadeh2005, author = {Ghasemzadeh, Mohammad}, title = {A new algorithm for the quantified satisfiability problem, based on zero-suppressed binary decision diagrams and memoization}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-6378}, school = {Universit{\"a}t Potsdam}, year = {2005}, abstract = {Quantified Boolean formulas (QBFs) play an important role in theoretical computer science. QBF extends propositional logic in such a way that many advanced forms of reasoning can be easily formulated and evaluated. In this dissertation we present our ZQSAT, which is an algorithm for evaluating quantified Boolean formulas. ZQSAT is based on ZBDD: Zero-Suppressed Binary Decision Diagram , which is a variant of BDD, and an adopted version of the DPLL algorithm. It has been implemented in C using the CUDD: Colorado University Decision Diagram package. The capability of ZBDDs in storing sets of subsets efficiently enabled us to store the clauses of a QBF very compactly and let us to embed the notion of memoization to the DPLL algorithm. These points led us to implement the search algorithm in such a way that we could store and reuse the results of all previously solved subformulas with a little overheads. ZQSAT can solve some sets of standard QBF benchmark problems (known to be hard for DPLL based algorithms) faster than the best existing solvers. In addition to prenex-CNF, ZQSAT accepts prenex-NNF formulas. We show and prove how this capability can be exponentially beneficial.}, subject = {Bin{\"a}res Entscheidungsdiagramm}, language = {en} } @phdthesis{Linckels2008, author = {Linckels, Serge}, title = {An e-librarian service : supporting explorative learning by a description logics based semantic retrieval tool}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-17452}, school = {Universit{\"a}t Potsdam}, year = {2008}, abstract = {Although educational content in electronic form is increasing dramatically, its usage in an educational environment is poor, mainly due to the fact that there is too much of (unreliable) redundant, and not relevant information. Finding appropriate answers is a rather difficult task being reliant on the user filtering of the pertinent information from the noise. Turning knowledge bases like the online tele-TASK archive into useful educational resources requires identifying correct, reliable, and "machine-understandable" information, as well as developing simple but efficient search tools with the ability to reason over this information. Our vision is to create an E-Librarian Service, which is able to retrieve multimedia resources from a knowledge base in a more efficient way than by browsing through an index, or by using a simple keyword search. In our E-Librarian Service, the user can enter his question in a very simple and human way; in natural language (NL). Our premise is that more pertinent results would be retrieved if the search engine understood the sense of the user's query. The returned results are then logical consequences of an inference rather than of keyword matchings. Our E-Librarian Service does not return the answer to the user's question, but it retrieves the most pertinent document(s), in which the user finds the answer to his/her question. Among all the documents that have some common information with the user query, our E-Librarian Service identifies the most pertinent match(es), keeping in mind that the user expects an exhaustive answer while preferring a concise answer with only little or no information overhead. Also, our E-Librarian Service always proposes a solution to the user, even if the system concludes that there is no exhaustive answer. Our E-Librarian Service was implemented prototypically in three different educational tools. A first prototype is CHESt (Computer History Expert System); it has a knowledge base with 300 multimedia clips that cover the main events in computer history. A second prototype is MatES (Mathematics Expert System); it has a knowledge base with 115 clips that cover the topic of fractions in mathematics for secondary school w.r.t. the official school programme. All clips were recorded mainly by pupils. The third and most advanced prototype is the "Lecture Butler's E-Librarain Service"; it has a Web service interface to respect a service oriented architecture (SOA), and was developed in the context of the Web-University project at the Hasso-Plattner-Institute (HPI). Two major experiments in an educational environment - at the Lyc{\´e}e Technique Esch/Alzette in Luxembourg - were made to test the pertinence and reliability of our E-Librarian Service as a complement to traditional courses. The first experiment (in 2005) was made with CHESt in different classes, and covered a single lesson. The second experiment (in 2006) covered a period of 6 weeks of intensive use of MatES in one class. There was no classical mathematics lesson where the teacher gave explanations, but the students had to learn in an autonomous and exploratory way. They had to ask questions to the E-Librarian Service just the way they would if there was a human teacher.}, subject = {Terminologische Logik}, language = {en} } @phdthesis{Huang2006, author = {Huang, Wanjun}, title = {Temporary binding for dynamic middleware construction and web services composition}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-7672}, school = {Universit{\"a}t Potsdam}, year = {2006}, abstract = {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.}, subject = {Middleware}, language = {en} } @inproceedings{DennertMoellerGarmannKujathetal.2016, author = {Dennert-M{\"o}ller, Elisabeth and Garmann, Robert and Kujath, Bertold and Zscheyge, Oliver and Weicker, Karsten and B{\"o}hne, Sebastian and Knobelsdorf, Maria and Kreitz, Christoph and Steen, Alexander and Wisniewski, Max and Benzm{\"u}ller, Christoph and Gebhardt, Kai and Ehlenz, Matthias and Bergner, Nadine and Schroeder, Ulrik}, title = {Hochschuldidaktik der Informatik}, editor = {Schwill, Andreas and Lucke, Ulrike}, publisher = {Universit{\"a}tsverlag Potsdam}, address = {Potsdam}, isbn = {978-3-86956-376-3}, issn = {1868-0844}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-93511}, pages = {102}, year = {2016}, abstract = {Die 7. Fachtagung f{\"u}r Hochschuldidaktik, die 2016 erneut mit der DeLFI E-Learning Fachtagung Informatik stattfand, setzte das erfolgreiche Modell einer Tagung fort, die sich mit hochschuldidaktischen Fragen und der Gestaltung von Studieng{\"a}ngen der Informatik besch{\"a}ftigt. Thema der Tagung waren alle Fragen, die sich der Vermittlung von Informatikgegenst{\"a}nden im Hochschulbereich widmen. Dazu geh{\"o}rten u.a.: • fachdidaktische Konzepte der Vermittlung einzelner Informatikgegenst{\"a}nde • methodische L{\"o}sungen, wie spezielle Lehr- und Lernformen, Durchf{\"u}hrungskonzepte • empirische Ergebnisse und Vergleichsstudien • E-Learning-Ans{\"a}tze, wenn sie ein erkennbares didaktisches Konzept verfolgen • Studienkonzepte und Curricula, organisatorische Fragen, wie Gewinnung von Studierenden, Studieneingangsphase, Abbrecher. Die Fachtagung widmete sich ausgew{\"a}hlten Fragestellungen dieses Themenkomplexes, die durch Vortr{\"a}ge ausgewiesener Experten, durch eingereichte Beitr{\"a}ge und durch Pr{\"a}sentationen und Poster intensiv behandelt wurden. Unser besonderer Dank gilt dem Programmkomitee und den hier nicht genannten Helfern f{\"u}r ihren Einsatz bei der Vorbereitung und Durchf{\"u}hrung der Tagung.}, language = {de} } @phdthesis{Menzel2011, author = {Menzel, Michael}, title = {Model-driven security in service-oriented architectures : leveraging security patterns to transform high-level security requirements to technical policies}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-59058}, school = {Universit{\"a}t Potsdam}, year = {2011}, abstract = {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.}, language = {en} } @misc{KliemeTietzMeinel2018, author = {Klieme, Eric and Tietz, Christian and Meinel, Christoph}, title = {Beware of SMOMBIES}, series = {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)}, journal = {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)}, publisher = {IEEE}, address = {New York}, isbn = {978-1-5386-4387-7}, issn = {2324-9013}, doi = {10.1109/TrustCom/BigDataSE.2018.00096}, pages = {651 -- 660}, year = {2018}, abstract = {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.}, language = {en} } @article{ThienenNoweskiMeineletal.2012, author = {Thienen, Julia von and Noweski, Christine and Meinel, Christoph and Lang, Sabine and Nicolai, Claudia and Bartz, Andreas}, title = {What can design thinking learn from behavior group theraphy?}, isbn = {978-3-642-31990-7}, year = {2012}, language = {en} } @misc{MeinelSack2004, author = {Meinel, Christoph and Sack, Harald}, title = {WWW : Kommunikation, Internetworking, Web-Technologien}, publisher = {Springer}, address = {Berlin}, isbn = {3-540-44276-6}, issn = {1439-5428}, pages = {1179 S.}, year = {2004}, language = {de} } @book{MeinelSack2009, author = {Meinel, Christoph and Sack, Harald}, title = {Digitale Kommunikation : Vernetzen, Multimedia, Sicherheit}, series = {Media Press}, journal = {Media Press}, publisher = {Springer-Verlag Berlin Heidelberg}, address = {Berlin, Heidelberg}, isbn = {978-3-540-92922-2}, issn = {1439-3107}, doi = {10.1007/978-3-540-92923-9}, pages = {422 S.}, year = {2009}, language = {de} } @misc{AlhosseiniAlmodarresiYasinBinTareafNajafietal.2019, author = {Alhosseini Almodarresi Yasin, Seyed Ali and Bin Tareaf, Raad and Najafi, Pejman and Meinel, Christoph}, title = {Detect me if you can}, series = {Companion Proceedings of The 2019 World Wide Web Conference}, journal = {Companion Proceedings of The 2019 World Wide Web Conference}, publisher = {Association for Computing Machinery}, address = {New York}, isbn = {978-1-4503-6675-5}, doi = {10.1145/3308560.3316504}, pages = {148 -- 153}, year = {2019}, abstract = {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.}, language = {en} } @article{LindbergMeinelWagner2011, author = {Lindberg, Tilmann and Meinel, Christoph and Wagner, Ralf}, title = {Design thinking : a fruitful concept for IT development?}, isbn = {978-3-642-13756-3}, year = {2011}, language = {en} } @article{MeinelKlotz2006, author = {Meinel, Christoph and Klotz, Volker}, title = {The first 10 years of the ECCC digital library}, doi = {10.1145/1107458.1107484}, year = {2006}, language = {en} } @article{GruenewaldMeinel2015, author = {Gr{\"u}newald, Franka and Meinel, Christoph}, title = {Implementation and Evaluation of Digital E-Lecture Annotation in Learning Groups to Foster Active Learning}, series = {IEEE transactions on learning technologies}, volume = {8}, journal = {IEEE transactions on learning technologies}, number = {3}, publisher = {Inst. of Electr. and Electronics Engineers}, address = {Los Alamitos}, issn = {1939-1382}, doi = {10.1109/TLT.2015.2396042}, pages = {286 -- 298}, year = {2015}, abstract = {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.}, language = {en} } @phdthesis{Schnjakin2014, author = {Schnjakin, Maxim}, title = {Cloud-RAID}, pages = {137}, year = {2014}, language = {de} } @phdthesis{Saleh2016, author = {Saleh, Eyad}, title = {Securing Multi-tenant SaaS Environments}, school = {Universit{\"a}t Potsdam}, pages = {108}, year = {2016}, abstract = {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.}, language = {en} } @article{MeinelWang2006, author = {Meinel, Christoph and Wang, Long}, title = {Building content clusters based on modelling page pairs}, doi = {10.1007/11610113_85}, year = {2006}, abstract = {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}, language = {en} } @phdthesis{SadrAzodi2015, author = {Sadr-Azodi, Amir Shahab}, title = {Towards Real-time SIEM-based Network monitoring and Intrusion Detection through Advanced Event Normalization}, school = {Universit{\"a}t Potsdam}, pages = {144}, year = {2015}, language = {en} } @phdthesis{Gericke2014, author = {Gericke, Lutz}, title = {Tele-Board - Supporting and analyzing creative collaboration in synchronous and asynchronous scenario}, pages = {186}, year = {2014}, language = {en} } @article{JobstKoeppenLindbergetal.2012, author = {Jobst, Birgit and K{\"o}ppen, Eva and Lindberg, Tilmann and Moritz, Josephine and Rhinow, Holger and Meinel, Christoph}, title = {The faith-factor in design thinking : creative confidence through education at the design thinking schools Potsdam and Standford?}, isbn = {978-3-642-31990-7}, year = {2012}, language = {en} } @article{NoweskiScheerBuettneretal.2012, author = {Noweski, Christine and Scheer, Andrea and B{\"u}ttner, Nadja and Thienen, Julia von and Erdmann, Johannes and Meinel, Christoph}, title = {Towards a paradigm shift in education practice : developing twenty-first century skills with design thinking}, isbn = {978-3-642-31990-7}, year = {2012}, language = {en} } @article{GumiennyGerickeWenzeletal.2012, author = {Gumienny, Raja and Gericke, Lutz and Wenzel, Matthias and Meinel, Christoph}, title = {Tele-board in use : applying aq digital whiteboard system in different situations and setups}, isbn = {978-3-642-31990-7}, year = {2012}, language = {en} } @article{ThienenNoweskiRauthetal.2012, author = {Thienen, Julia von and Noweski, Christine and Rauth, Ingo and Meinel, Christoph and Lange, Sabine}, title = {If you want to know who are, tell me where you are : the importance of places}, year = {2012}, language = {en} } @article{MeinelLeifer2012, author = {Meinel, Christoph and Leifer, Larry}, title = {Design thinking research}, isbn = {978-3-642-31990-7}, year = {2012}, language = {en} } @book{LinckelsMeinel2011, author = {Linckels, Serge and Meinel, Christoph}, title = {E-Librarian service : user-friendly semantic search in digital libraries}, publisher = {Springer-Verlag Berlin Heidelberg}, address = {Berlin, Heidelberg}, isbn = {978-3-642-17742-2}, doi = {10.1007/978-3-642-17743-9}, pages = {212 S.}, year = {2011}, language = {en} } @article{MeinelLeifer2011, author = {Meinel, Christoph and Leifer, Larry}, title = {Design thinking research}, isbn = {978-3-642-13756-3}, year = {2011}, language = {en} } @misc{OPUS4-33848, title = {Design thinking : understand - improve - apply}, editor = {Plattner, Hasso and Meinel, Christoph and Leifer, Larry}, publisher = {Springer-Verlag Berlin Heidelberg}, address = {Berlin, Heidelberg}, isbn = {978-3-642-13756-3}, pages = {236 S.}, year = {2011}, language = {en} } @article{GumiennyMeinelGerickeetal.2011, author = {Gumienny, Raja and Meinel, Christoph and Gericke, Lutz and Quasthoff, Matthias and LoBue, Peter and Willems, Christian}, title = {Tele-board : enabling efficient collaboration in digital design spaces across time and distance}, isbn = {978-3-642-13756-3}, year = {2011}, language = {en} } @article{ThienenNoweskiMeineletal.2011, author = {Thienen, Julia von and Noweski, Christine and Meinel, Christoph and Rauth, Ingo}, title = {The co-evolution of theory and practice in design thinking - or - "Mind the oddness trap!"}, isbn = {978-3-642-13756-3}, year = {2011}, language = {en} } @article{LindbergKoeppenRauthetal.2012, author = {Lindberg, Tilmann and K{\"o}ppen, Eva and Rauth, Ingo and Meinel, Christoph}, title = {On the perection, adoption and Implementation of design thinking in the IT industry}, year = {2012}, language = {en} } @article{GerickeGumiennyMeinel2012, author = {Gericke, Lutz and Gumienny, Raja and Meinel, Christoph}, title = {Tele-board : folow the traces of your design process history}, year = {2012}, language = {en} } @article{MeinelLeifer2012, author = {Meinel, Christoph and Leifer, Larry}, title = {Design thinking research}, year = {2012}, language = {en} } @book{OPUS4-33866, title = {Dsign thinking research : studying co-creation in practice}, editor = {Plattner, Hasso and Meinel, Christoph and Leifer, Larry}, publisher = {Springer Berlin Heidelberg}, address = {Berlin, Heidelberg}, isbn = {978-3-642-21642-8}, doi = {10.1007/978-3-642-21643-5}, pages = {277 S.}, year = {2012}, language = {en} } @phdthesis{AlSaffar2016, author = {Al-Saffar, Loay Talib Ahmed}, title = {Analysing prerequisites, expectations, apprehensions, and attitudes of university students studying Computer science}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-98437}, school = {Universit{\"a}t Potsdam}, pages = {xii, 131}, year = {2016}, abstract = {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.}, language = {en} } @article{Broeker2015, author = {Br{\"o}ker, Kathrin}, title = {Unterst{\"u}tzung Informatik-Studierender durch ein Lernzentrum}, series = {HDI 2014 : Gestalten von {\"U}berg{\"a}ngen}, volume = {2015}, journal = {HDI 2014 : Gestalten von {\"U}berg{\"a}ngen}, number = {9}, editor = {Schubert, Sigrid and Schwill, Andreas}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-84754}, pages = {189 -- 197}, year = {2015}, abstract = {In diesem Papier wird das Konzept eines Lernzentrums f{\"u}r die Informatik (LZI) an der Universit{\"a}t Paderborn vorgestellt. Ausgehend von den fachspezifischen Schwierigkeiten der Informatik Studierenden werden die Angebote des LZIs erl{\"a}utert, die sich {\"u}ber die vier Bereiche Individuelle Beratung und Betreuung, „Offener Lernraum", Workshops und Lehrveranstaltungen sowie Forschung erstrecken. Eine erste Evaluation mittels Feedbackb{\"o}gen zeigt, dass das Angebot bei den Studierenden positiv aufgenommen wird. Zuk{\"u}nftig soll das Angebot des LZIs weiter ausgebaut und verbessert werden. Ausgangsbasis dazu sind weitere Studien.}, language = {de} } @phdthesis{Prasse2016, author = {Prasse, Paul}, title = {Pattern recognition for computer security}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-100251}, school = {Universit{\"a}t Potsdam}, pages = {VI, 75}, year = {2016}, abstract = {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.}, language = {en} } @phdthesis{Videla2014, author = {Videla, Santiago}, title = {Reasoning on the response of logical signaling networks with answer set programming}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-71890}, school = {Universit{\"a}t Potsdam}, year = {2014}, abstract = {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.}, language = {en} } @phdthesis{Haider2013, author = {Haider, Peter}, title = {Prediction with Mixture Models}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-69617}, school = {Universit{\"a}t Potsdam}, year = {2013}, abstract = {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.}, language = {en} } @phdthesis{Dick2016, author = {Dick, Uwe}, title = {Discriminative Classification Models for Internet Security}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-102593}, school = {Universit{\"a}t Potsdam}, pages = {x, 57}, year = {2016}, abstract = {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.}, language = {en} } @phdthesis{AlAreqi2017, author = {Al-Areqi, Samih Taha Mohammed}, title = {Semantics-based automatic geospatial service composition}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-402616}, school = {Universit{\"a}t Potsdam}, pages = {xvi, 163}, year = {2017}, abstract = {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.}, language = {en} } @phdthesis{Glander2012, author = {Glander, Tassilo}, title = {Multi-scale representations of virtual 3D city models}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-64117}, school = {Universit{\"a}t Potsdam}, year = {2012}, abstract = {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 B{\´e}zier 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.}, language = {en} } @phdthesis{Seibel2012, author = {Seibel, Andreas}, title = {Traceability and model management with executable and dynamic hierarchical megamodels}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-64222}, school = {Universit{\"a}t Potsdam}, year = {2012}, abstract = {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.}, language = {en} } @phdthesis{Polyvyanyy2012, author = {Polyvyanyy, Artem}, title = {Structuring process models}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-59024}, school = {Universit{\"a}t Potsdam}, year = {2012}, abstract = {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.}, language = {en} } @phdthesis{Middelanis2023, author = {Middelanis, Robin}, title = {Global response to local extremes—a storyline approach on economic loss propagation from weather extremes}, doi = {10.25932/publishup-61112}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-611127}, school = {Universit{\"a}t Potsdam}, pages = {vii, 237}, year = {2023}, abstract = {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.}, language = {en} } @article{MiddelanisWillnerOttoetal.2021, author = {Middelanis, Robin and Willner, Sven N. and Otto, Christian and Kuhla, Kilian and Quante, Lennart and Levermann, Anders}, title = {Wave-like global economic ripple response to Hurricane Sandy}, series = {Environmental research letters : ERL / Institute of Physics}, volume = {16}, journal = {Environmental research letters : ERL / Institute of Physics}, number = {12}, publisher = {IOP Publ. Ltd.}, address = {Bristol}, issn = {1748-9326}, doi = {10.1088/1748-9326/ac39c0}, pages = {11}, year = {2021}, abstract = {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.}, language = {en} } @article{QuanteWillnerMiddelanisetal.2021, author = {Quante, Lennart and Willner, Sven N. and Middelanis, Robin and Levermann, Anders}, title = {Regions of intensification of extreme snowfall under future warming}, series = {Scientific reports}, volume = {11}, journal = {Scientific reports}, number = {1}, publisher = {Macmillan Publishers Limited, part of Springer Nature}, address = {Berlin}, issn = {2045-2322}, doi = {10.1038/s41598-021-95979-4}, pages = {9}, year = {2021}, abstract = {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.}, language = {en} } @phdthesis{Makowski2021, author = {Makowski, Silvia}, title = {Discriminative Models for Biometric Identification using Micro- and Macro-Movements of the Eyes}, school = {Universit{\"a}t Potsdam}, pages = {xi, 91}, year = {2021}, abstract = {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.}, language = {en} } @article{SchirrmannLandwehrGiebeletal.2021, author = {Schirrmann, Michael and Landwehr, Niels and Giebel, Antje and Garz, Andreas and Dammer, Karl-Heinz}, title = {Early detection of stripe rust in winter wheat using deep residual neural networks}, series = {Frontiers in plant science : FPLS}, volume = {12}, journal = {Frontiers in plant science : FPLS}, publisher = {Frontiers Media}, address = {Lausanne}, issn = {1664-462X}, doi = {10.3389/fpls.2021.469689}, pages = {14}, year = {2021}, abstract = {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.}, language = {en} } @article{ThonLandwehrDeRaedt2011, author = {Thon, Ingo and Landwehr, Niels and De Raedt, Luc}, title = {Stochastic relational processes efficient inference and applications}, series = {Machine learning}, volume = {82}, journal = {Machine learning}, number = {2}, publisher = {Springer}, address = {Dordrecht}, issn = {0885-6125}, doi = {10.1007/s10994-010-5213-8}, pages = {239 -- 272}, year = {2011}, abstract = {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.}, language = {en} } @article{CiliaLandwehrPasserini2011, author = {Cilia, Elisa and Landwehr, Niels and Passerini, Andrea}, title = {Relational feature mining with hierarchical multitask kFOIL}, series = {Fundamenta informaticae}, volume = {113}, journal = {Fundamenta informaticae}, number = {2}, publisher = {IOS Press}, address = {Amsterdam}, issn = {0169-2968}, doi = {10.3233/FI-2011-604}, pages = {151 -- 177}, year = {2011}, abstract = {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.}, language = {en} }