@misc{HempelKoseskaNikoloskietal.2017,
  author    = {Hempel, Sabrina and Koseska, Aneta and Nikoloski, Zoran and Kurths, J{\"u}rgen},
  title     = {Unraveling gene regulatory networks from time-resolved gene expression data},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-400924},
  pages     = {26},
  year      = {2017},
  abstract  = {Background: Inferring regulatory interactions between genes from transcriptomics time-resolved data, yielding reverse engineered gene regulatory networks, is of paramount importance to systems biology and bioinformatics studies. Accurate methods to address this problem can ultimately provide a deeper insight into the complexity, behavior, and functions of the underlying biological systems. However, the large number of interacting genes coupled with short and often noisy time-resolved read-outs of the system renders the reverse engineering a challenging task. Therefore, the development and assessment of methods which are computationally efficient, robust against noise, applicable to short time series data, and preferably capable of reconstructing the directionality of the regulatory interactions remains a pressing research problem with valuable applications. Results: Here we perform the largest systematic analysis of a set of similarity measures and scoring schemes within the scope of the relevance network approach which are commonly used for gene regulatory network reconstruction from time series data. In addition, we define and analyze several novel measures and schemes which are particularly suitable for short transcriptomics time series. We also compare the considered 21 measures and 6 scoring schemes according to their ability to correctly reconstruct such networks from short time series data by calculating summary statistics based on the corresponding specificity and sensitivity. Our results demonstrate that rank and symbol based measures have the highest performance in inferring regulatory interactions. In addition, the proposed scoring scheme by asymmetric weighting has shown to be valuable in reducing the number of false positive interactions. On the other hand, Granger causality as well as information-theoretic measures, frequently used in inference of regulatory networks, show low performance on the short time series analyzed in this study. Conclusions: Our study is intended to serve as a guide for choosing a particular combination of similarity measures and scoring schemes suitable for reconstruction of gene regulatory networks from short time series data. We show that further improvement of algorithms for reverse engineering can be obtained if one considers measures that are rooted in the study of symbolic dynamics or ranks, in contrast to the application of common similarity measures which do not consider the temporal character of the employed data. Moreover, we establish that the asymmetric weighting scoring scheme together with symbol based measures (for low noise level) and rank based measures (for high noise level) are the most suitable choices.},
  language  = {en}
}
@phdthesis{Felgentreff2017,
  author    = {Felgentreff, Tim},
  title     = {The Design and Implementation of Object-Constraint Programming},
  school      = {Universit{\"a}t Potsdam},
  pages     = {183},
  year      = {2017},
  language  = {en}
}
@book{SchneiderLambersOrejas2017,
  author    = {Schneider, Sven and Lambers, Leen and Orejas, Fernando},
  title     = {Symbolic model generation for graph properties},
  number    = {115},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-396-1},
  issn      = {1613-5652},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-103171},
  publisher      = {Universit{\"a}t Potsdam},
  pages     = {48},
  year      = {2017},
  abstract  = {Graphs are ubiquitous in Computer Science. For this reason, in many areas, it is very important to have the means to express and reason about graph properties. In particular, we want to be able to check automatically if a given graph property is satisfiable. Actually, in most application scenarios it is desirable to be able to explore graphs satisfying the graph property if they exist or even to get a complete and compact overview of the graphs satisfying the graph property. We show that the tableau-based reasoning method for graph properties as introduced by Lambers and Orejas paves the way for a symbolic model generation algorithm for graph properties. Graph properties are formulated in a dedicated logic making use of graphs and graph morphisms, which is equivalent to firstorder logic on graphs as introduced by Courcelle. Our parallelizable algorithm gradually generates a finite set of so-called symbolic models, where each symbolic model describes a set of finite graphs (i.e., finite models) satisfying the graph property. The set of symbolic models jointly describes all finite models for the graph property (complete) and does not describe any finite graph violating the graph property (sound). Moreover, no symbolic model is already covered by another one (compact). Finally, the algorithm is able to generate from each symbolic model a minimal finite model immediately and allows for an exploration of further finite models. The algorithm is implemented in the new tool AutoGraph.},
  language  = {en}
}
@book{NiephausFelgentreffHirschfeld2017,
  author    = {Niephaus, Fabio and Felgentreff, Tim and Hirschfeld, Robert},
  title     = {Squimera},
  number    = {120},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-422-7},
  doi       = {10.25932/publishup-40338},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-403387},
  publisher      = {Universit{\"a}t Potsdam},
  pages     = {92},
  year      = {2017},
  abstract  = {Programmierwerkzeuge, die verschiedene Programmiersprachen unterst{\"u}tzen und sich konsistent bedienen lassen, sind hilfreich f{\"u}r Softwareentwickler, weil diese sich nicht erst mit neuen Werkzeugen vertraut machen m{\"u}ssen, wenn sie in einer neuen Sprache entwickeln wollen. Außerdem ist es n{\"u}tzlich, verschiedene Programmiersprachen in einer Anwendung kombinieren zu k{\"o}nnen, da Entwickler dann Softwareframeworks und -bibliotheken nicht in der jeweiligen Sprache nachbauen m{\"u}ssen und stattdessen bestehende Software wiederverwenden k{\"o}nnen. Dennoch haben Entwickler eine sehr große Auswahl, wenn sie nach Werkzeugen suchen, die teilweise zudem speziell nur f{\"u}r eine Sprache ausgelegt sind. Einige integrierte Entwicklungsumgebungen unterst{\"u}tzen verschiedene Programmiersprachen, k{\"o}nnen aber h{\"a}ufig keine konsistente Bedienung ihrer Werkzeuge gew{\"a}hrleisten, da die jeweiligen Ausf{\"u}hrungsumgebungen der Sprachen zu verschieden sind. Dar{\"u}ber hinaus gibt es bereits Mechansimen, die es erlauben, Programme aus anderen Sprachen in einem Programm wiederzuverwenden. Dazu werden h{\"a}ufig das Betriebssystem oder eine Netzwerkverbindung verwendet. Programmierwerkzeuge unterst{\"u}tzen jedoch h{\"a}ufig eine solche Indirektion nicht und sind deshalb nur eingeschr{\"a}nkt nutzbar bei beispielsweise Debugging Szenarien. In dieser Arbeit stellen wir einen neuartigen Ansatz vor, der das Programmiererlebnis in Bezug auf das Arbeiten mit mehreren dynamischen Programmiersprachen verbessern soll. Dazu verwenden wir die Werkzeuge einer Smalltalk Programmierumgebung wieder und entwickeln eine virtuelle Ausf{\"u}hrungsumgebung, die verschiedene Sprachen gleichermaßen unterst{\"u}tzt. Der auf unserem Ansatz basierende Prototyp Squimera demonstriert, dass es m{\"o}glich ist, Programmierwerkzeuge in der Art wiederzuverwenden, sodass sie sich f{\"u}r verschiedene Programmiersprachen gleich verhalten und somit die Arbeit f{\"u}r Entwickler vereinfachen. Außerdem erm{\"o}glicht Squimera einfaches Wiederverwenden und dar{\"u}ber hinaus das Verschmischen von in unterschiedlichen Sprachen geschriebenen Softwarebibliotheken und -frameworks und erlaubt dabei zus{\"a}tzlich Debugging {\"u}ber mehrere Sprachen hinweg.},
  language  = {en}
}
@phdthesis{Neuhaus2017,
  author    = {Neuhaus, Christian},
  title     = {Sicherheitsmechanismen f{\"u}r dienstbasierte Softwaresysteme},
  school      = {Universit{\"a}t Potsdam},
  pages     = {183},
  year      = {2017},
  language  = {de}
}
@book{KlauckMaschlerTausche2017,
  author    = {Klauck, Stefan and Maschler, Fabian and Tausche, Karsten},
  title     = {Proceedings of the Fourth HPI Cloud Symposium "Operating the Cloud" 2016},
  number    = {117},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-401-2},
  issn      = {1613-5652},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-394513},
  publisher      = {Universit{\"a}t Potsdam},
  pages     = {32},
  year      = {2017},
  abstract  = {Every year, the Hasso Plattner Institute (HPI) invites guests from industry and academia to a collaborative scientific workshop on the topic Every year, the Hasso Plattner Institute (HPI) invites guests from industry and academia to a collaborative scientific workshop on the topic "Operating the Cloud". Our goal is to provide a forum for the exchange of knowledge and experience between industry and academia. Co-located with the event is the HPI's Future SOC Lab day, which offers an additional attractive and conducive environment for scientific and industry related discussions. "Operating the Cloud" aims to be a platform for productive interactions of innovative ideas, visions, and upcoming technologies in the field of cloud operation and administration. On the occasion of this symposium we called for submissions of research papers and practitioner's reports. A compilation of the research papers realized during the fourth HPI cloud symposium "Operating the Cloud" 2016 are published in this proceedings. We thank the authors for exciting presentations and insights into their current work and research. Moreover, we look forward to more interesting submissions for the upcoming symposium later in the year. Every year, the Hasso Plattner Institute (HPI) invites guests from industry and academia to a collaborative scientific workshop on the topic "Operating the Cloud". Our goal is to provide a forum for the exchange of knowledge and experience between industry and academia. Co-located with the event is the HPI's Future SOC Lab day, which offers an additional attractive and conducive environment for scientific and industry related discussions. "Operating the Cloud" aims to be a platform for productive interactions of innovative ideas, visions, and upcoming technologies in the field of cloud operation and administration.},
  language  = {en}
}
@book{MaximovaGieseKrause2017,
  author    = {Maximova, Maria and Giese, Holger and Krause, Christian},
  title     = {Probabilistic timed graph transformation systems},
  number    = {118},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-405-0},
  issn      = {1613-5652},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-397055},
  publisher      = {Universit{\"a}t Potsdam},
  pages     = {34},
  year      = {2017},
  abstract  = {Today, software has become an intrinsic part of complex distributed embedded real-time systems. The next generation of embedded real-time systems will interconnect the today unconnected systems via complex software parts and the service-oriented paradigm. Therefore besides timed behavior and probabilistic behaviour also structure dynamics, where the architecture can be subject to changes at run-time, e.g. when dynamic binding of service end-points is employed or complex collaborations are established dynamically, is required. However, a modeling and analysis approach that combines all these necessary aspects does not exist so far. To fill the identified gap, we propose Probabilistic Timed Graph Transformation Systems (PTGTSs) as a high-level description language that supports all the necessary aspects of structure dynamics, timed behavior, and probabilistic behavior. We introduce the formal model of PTGTSs in this paper and present a mapping of models with finite state spaces to probabilistic timed automata (PTA) that allows to use the PRISM model checker to analyze PTGTS models with respect to PTCTL properties.},
  language  = {en}
}
@phdthesis{Meier2017,
  author    = {Meier, Sebastian},
  title     = {Personal Big Data},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-406696},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xxiv, 133},
  year      = {2017},
  abstract  = {Many users of cloud-based services are concerned about questions of data privacy. At the same time, they want to benefit from smart data-driven services, which require insight into a person's individual behaviour. The modus operandi of user modelling is that data is sent to a remote server where the model is constructed and merged with other users' data. This thesis proposes selective cloud computing, an alternative approach, in which the user model is constructed on the client-side and only an abstracted generalised version of the model is shared with the remote services. In order to demonstrate the applicability of this approach, the thesis builds an exemplary client-side user modelling technique. As this thesis is carried out in the area of Geoinformatics and spatio-temporal data is particularly sensitive, the application domain for this experiment is the analysis and prediction of a user's spatio-temporal behaviour. The user modelling technique is grounded in an innovative conceptual model, which builds upon spatial network theory combined with time-geography. The spatio-temporal constraints of time-geography are applied to the network structure in order to create individual spatio-temporal action spaces. This concept is translated into a novel algorithmic user modelling approach which is solely driven by the user's own spatio-temporal trajectory data that is generated by the user's smartphone. While modern smartphones offer a rich variety of sensory data, this thesis only makes use of spatio-temporal trajectory data, enriched by activity classification, as the input and foundation for the algorithmic model. The algorithmic model consists of three basal components: locations (vertices), trips (edges), and clusters (neighbourhoods). After preprocessing the incoming trajectory data in order to identify locations, user feedback is used to train an artificial neural network to learn temporal patterns for certain location types (e.g. work, home, bus stop, etc.). This Artificial Neural Network (ANN) is used to automatically detect future location types by their spatio-temporal patterns. The same is done in order to predict the duration of stay at a certain location. Experiments revealed that neural nets were the most successful statistical and machine learning tool to detect those patterns. The location type identification algorithm reached an accuracy of 87.69\%, the duration prediction on binned data was less successful and deviated by an average of 0.69 bins. A challenge for the location type classification, as well as for the subsequent components, was the imbalance of trips and connections as well as the low accuracy of the trajectory data. The imbalance is grounded in the fact that most users exhibit strong habitual patterns (e.g. home > work), while other patterns are rather rare by comparison. The accuracy problem derives from the energy-saving location sampling mode, which creates less accurate results. Those locations are then used to build a network that represents the user's spatio-temporal behaviour. An initial untrained ANN to predict movement on the network only reached 46\% average accuracy. Only lowering the number of included edges, focusing on more common trips, increased the performance. In order to further improve the algorithm, the spatial trajectories were introduced into the predictions. To overcome the accuracy problem, trips between locations were clustered into so-called spatial corridors, which were intersected with the user's current trajectory. The resulting intersected trips were ranked through a k-nearest-neighbour algorithm. This increased the performance to 56\%. In a final step, a combination of a network and spatial clustering algorithm was built in order to create clusters, therein reducing the variety of possible trips. By only predicting the destination cluster instead of the exact location, it is possible to increase the performance to 75\% including all classes. A final set of components shows in two exemplary ways how to deduce additional inferences from the underlying spatio-temporal data. The first example presents a novel concept for predicting the 'potential memorisation index' for a certain location. The index is based on a cognitive model which derives the index from the user's activity data in that area. The second example embeds each location in its urban fabric and thereby enriches its cluster's metadata by further describing the temporal-semantic activity in an area (e.g. going to restaurants at noon). The success of the client-side classification and prediction approach, despite the challenges of inaccurate and imbalanced data, supports the claimed benefits of the client-side modelling concept. Since modern data-driven services at some point do need to receive user data, the thesis' computational model concludes with a concept for applying generalisation to semantic, temporal, and spatial data before sharing it with the remote service in order to comply with the overall goal to improve data privacy. In this context, the potentials of ensemble training (in regards to ANNs) are discussed in order to highlight the potential of only sharing the trained ANN instead of the raw input data. While the results of our evaluation support the assets of the proposed framework, there are two important downsides of our approach compared to server-side modelling. First, both of these server-side advantages are rooted in the server's access to multiple users' data. This allows a remote service to predict spatio-in the user-specific data, which represents the second downside. While minor classes will likely be minor classes in a bigger dataset as well, for each class, there will still be more variety than in the user-specific dataset. The author emphasises that the approach presented in this work holds the potential to change the privacy paradigm in modern data-driven services. Finding combinations of client- and server-side modelling could prove a promising new path for data-driven innovation. Beyond the technological perspective, throughout the thesis the author also offers a critical view on the data- and technology-driven development of this work. By introducing the client-side modelling with user-specific artificial neural networks, users generate their own algorithm. Those user-specific algorithms are influenced less by generalised biases or developers' prejudices. Therefore, the user develops a more diverse and individual perspective through his or her user model. This concept picks up the idea of critical cartography, which questions the status quo of how space is perceived and represented.},
  language  = {en}
}
@article{ChujfiLaRocheMeinel2017,
  author    = {Chujfi-La-Roche, Salim and Meinel, Christoph},
  title     = {Matching cognitively sympathetic individual styles to develop collective intelligence in digital communities},
  series = {AI \& society : the journal of human-centred systems and machine intelligence},
  volume    = {35},
  journal   = {AI \& society : the journal of human-centred systems and machine intelligence},
  number    = {1},
  publisher = {Springer},
  address   = {New York},
  issn      = {0951-5666},
  doi       = {10.1007/s00146-017-0780-x},
  pages     = {5 -- 15},
  year      = {2017},
  abstract  = {Creation, collection and retention of knowledge in digital communities is an activity that currently requires being explicitly targeted as a secure method of keeping intellectual capital growing in the digital era. In particular, we consider it relevant to analyze and evaluate the empathetic cognitive personalities and behaviors that individuals now have with the change from face-to-face communication (F2F) to computer-mediated communication (CMC) online. This document proposes a cyber-humanistic approach to enhance the traditional SECI knowledge management model. A cognitive perception is added to its cyclical process following design thinking interaction, exemplary for improvement of the method in which knowledge is continuously created, converted and shared. In building a cognitive-centered model, we specifically focus on the effective identification and response to cognitive stimulation of individuals, as they are the intellectual generators and multiplicators of knowledge in the online environment. Our target is to identify how geographically distributed-digital-organizations should align the individual's cognitive abilities to promote iteration and improve interaction as a reliable stimulant of collective intelligence. The new model focuses on analyzing the four different stages of knowledge processing, where individuals with sympathetic cognitive personalities can significantly boost knowledge creation in a virtual social system. For organizations, this means that multidisciplinary individuals can maximize their extensive potential, by externalizing their knowledge in the correct stage of the knowledge creation process, and by collaborating with their appropriate sympathetically cognitive remote peers.},
  language  = {en}
}
@book{TietzPelchenMeineletal.2017,
  author    = {Tietz, Christian and Pelchen, Chris and Meinel, Christoph and Schnjakin, Maxim},
  title     = {Management Digitaler Identit{\"a}ten},
  number    = {114},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-395-4},
  issn      = {1613-5652},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-103164},
  publisher      = {Universit{\"a}t Potsdam},
  pages     = {65},
  year      = {2017},
  abstract  = {Um den zunehmenden Diebstahl digitaler Identit{\"a}ten zu bek{\"a}mpfen, gibt es bereits mehr als ein Dutzend Technologien. Sie sind, vor allem bei der Authentifizierung per Passwort, mit spezifischen Nachteilen behaftet, haben andererseits aber auch jeweils besondere Vorteile. Wie solche Kommunikationsstandards und -Protokolle wirkungsvoll miteinander kombiniert werden k{\"o}nnen, um dadurch mehr Sicherheit zu erreichen, haben die Autoren dieser Studie analysiert. Sie sprechen sich f{\"u}r neuartige Identit{\"a}tsmanagement-Systeme aus, die sich flexibel auf verschiedene Rollen eines einzelnen Nutzers einstellen k{\"o}nnen und bequemer zu nutzen sind als bisherige Verfahren. Als ersten Schritt auf dem Weg hin zu einer solchen Identit{\"a}tsmanagement-Plattform beschreiben sie die M{\"o}glichkeiten einer Analyse, die sich auf das individuelle Verhalten eines Nutzers oder einer Sache st{\"u}tzt. Ausgewertet werden dabei Sensordaten mobiler Ger{\"a}te, welche die Nutzer h{\"a}ufig bei sich tragen und umfassend einsetzen, also z.B. internetf{\"a}hige Mobiltelefone, Fitness-Tracker und Smart Watches. Die Wissenschaftler beschreiben, wie solche Kleincomputer allein z.B. anhand der Analyse von Bewegungsmustern, Positionsund Netzverbindungsdaten kontinuierlich ein „Vertrauens-Niveau" errechnen k{\"o}nnen. Mit diesem ermittelten „Trust Level" kann jedes Ger{\"a}t st{\"a}ndig die Wahrscheinlichkeit angeben, mit der sein aktueller Benutzer auch der tats{\"a}chliche Besitzer ist, dessen typische Verhaltensmuster es genauestens „kennt". Wenn der aktuelle Wert des Vertrauens-Niveaus (nicht aber die biometrischen Einzeldaten) an eine externe Instanz wie einen Identit{\"a}tsprovider {\"u}bermittelt wird, kann dieser das Trust Level allen Diensten bereitstellen, welche der Anwender nutzt und dar{\"u}ber informieren will. Jeder Dienst ist in der Lage, selbst festzulegen, von welchem Vertrauens-Niveau an er einen Nutzer als authentifiziert ansieht. Erf{\"a}hrt er von einem unter das Limit gesunkenen Trust Level, kann der Identit{\"a}tsprovider seine Nutzung und die anderer Services verweigern. Die besonderen Vorteile dieses Identit{\"a}tsmanagement-Ansatzes liegen darin, dass er keine spezifische und teure Hardware ben{\"o}tigt, um spezifische Daten auszuwerten, sondern lediglich Smartphones und so genannte Wearables. Selbst Dinge wie Maschinen, die Daten {\"u}ber ihr eigenes Verhalten per Sensor-Chip ins Internet funken, k{\"o}nnen einbezogen werden. Die Daten werden kontinuierlich im Hintergrund erhoben, ohne dass sich jemand darum k{\"u}mmern muss. Sie sind nur f{\"u}r die Berechnung eines Wahrscheinlichkeits-Messwerts von Belang und verlassen niemals das Ger{\"a}t. Meldet sich ein Internetnutzer bei einem Dienst an, muss er sich nicht zun{\"a}chst an ein vorher festgelegtes Geheimnis - z.B. ein Passwort - erinnern, sondern braucht nur die Weitergabe seines aktuellen Vertrauens-Wertes mit einem „OK" freizugeben. {\"A}ndert sich das Nutzungsverhalten - etwa durch andere Bewegungen oder andere Orte des Einloggens ins Internet als die {\"u}blichen - wird dies schnell erkannt. Unbefugten kann dann sofort der Zugang zum Smartphone oder zu Internetdiensten gesperrt werden. K{\"u}nftig kann die Auswertung von Verhaltens-Faktoren noch erweitert werden, indem z.B. Routinen an Werktagen, an Wochenenden oder im Urlaub erfasst werden. Der Vergleich mit den live erhobenen Daten zeigt dann an, ob das Verhalten in das {\"u}bliche Muster passt, der Benutzer also mit h{\"o}chster Wahrscheinlichkeit auch der ausgewiesene Besitzer des Ger{\"a}ts ist. {\"U}ber die Techniken des Managements digitaler Identit{\"a}ten und die damit verbundenen Herausforderungen gibt diese Studie einen umfassenden {\"U}berblick. Sie beschreibt zun{\"a}chst, welche Arten von Angriffen es gibt, durch die digitale Identit{\"a}ten gestohlen werden k{\"o}nnen. Sodann werden die unterschiedlichen Verfahren von Identit{\"a}tsnachweisen vorgestellt. Schließlich liefert die Studie noch eine zusammenfassende {\"U}bersicht {\"u}ber die 15 wichtigsten Protokolle und technischen Standards f{\"u}r die Kommunikation zwischen den drei beteiligten Akteuren: Service Provider/Dienstanbieter, Identit{\"a}tsprovider und Nutzer. Abschließend wird aktuelle Forschung des Hasso-Plattner-Instituts zum Identit{\"a}tsmanagement vorgestellt.},
  language  = {de}
}