@phdthesis{Bazhenova2018,
  author    = {Bazhenova, Ekaterina},
  title     = {Discovery of Decision Models Complementary to Process Models},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-410020},
  school      = {Universit{\"a}t Potsdam},
  year      = {2018},
  abstract  = {Business process management is an acknowledged asset for running an organization in a productive and sustainable way. One of the most important aspects of business process management, occurring on a daily basis at all levels, is decision making. In recent years, a number of decision management frameworks have appeared in addition to existing business process management systems. More recently, Decision Model and Notation (DMN) was developed by the OMG consortium with the aim of complementing the widely used Business Process Model and Notation (BPMN). One of the reasons for the emergence of DMN is the increasing interest in the evolving paradigm known as the separation of concerns. This paradigm states that modeling decisions complementary to processes reduces process complexity by externalizing decision logic from process models and importing it into a dedicated decision model. Such an approach increases the agility of model design and execution. This provides organizations with the flexibility to adapt to the ever increasing rapid and dynamic changes in the business ecosystem. The research gap, identified by us, is that the separation of concerns, recommended by DMN, prescribes the externalization of the decision logic of process models in one or more separate decision models, but it does not specify this can be achieved. The goal of this thesis is to overcome the presented gap by developing a framework for discovering decision models in a semi-automated way from information about existing process decision making. Thus, in this thesis we develop methodologies to extract decision models from: (1) control flow and data of process models that exist in enterprises; and (2) from event logs recorded by enterprise information systems, encapsulating day-to-day operations. Furthermore, we provide an extension of the methodologies to discover decision models from event logs enriched with fuzziness, a tool dealing with partial knowledge of the process execution information. All the proposed techniques are implemented and evaluated in case studies using real-life and synthetic process models and event logs. The evaluation of these case studies shows that the proposed methodologies provide valid and accurate output decision models that can serve as blueprints for executing decisions complementary to process models. Thus, these methodologies have applicability in the real world and they can be used, for example, for compliance checks, among other uses, which could improve the organization's decision making and hence it's overall performance.},
  language  = {en}
}
@phdthesis{Buschmann2018,
  author    = {Buschmann, Stefan},
  title     = {A software framework for GPU-based geo-temporal visualization techniques},
  doi       = {10.25932/publishup-44340},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-443406},
  school      = {Universit{\"a}t Potsdam},
  pages     = {viii, 99},
  year      = {2018},
  abstract  = {R{\"a}umlich-zeitliche Daten sind Daten, welche sowohl einen Raum- als auch einen Zeitbezug aufweisen. So k{\"o}nnen beispielsweise Zeitreihen von Geodaten, thematische Karten die sich {\"u}ber die Zeit ver{\"a}ndern, oder Bewegungsaufzeichnungen von sich bewegenden Objekten als r{\"a}umlich-zeitliche Daten aufgefasst werden. In der heutigen automatisierten Welt gibt es eine wachsende Anzahl von Datenquellen, die best{\"a}ndig r{\"a}umlich-zeitliche Daten generieren. Hierzu geh{\"o}ren beispielsweise Verkehrs{\"u}berwachungssysteme, die Bewegungsdaten von Menschen oder Fahrzeugen aufzeichnen, Fernerkundungssysteme, welche regelm{\"a}ßig unsere Umgebung scannen und digitale Abbilder wie z.B. Stadt- und Landschaftsmodelle erzeugen, sowie Sensornetzwerke in unterschiedlichsten Anwendungsgebieten, wie z.B. der Logistik, der Verhaltensforschung von Tieren, oder der Klimaforschung. Zur Analyse r{\"a}umlich-zeitlicher Daten werden neben der automatischen Analyse mittels statistischer Methoden und Data-Mining auch explorative Methoden angewendet, welche auf der interaktiven Visualisierung der Daten beruhen. Diese Methode der Analyse basiert darauf, dass Anwender in Form interaktiver Visualisierung die Daten explorieren k{\"o}nnen, wodurch die menschliche Wahrnehmung sowie das Wissen der User genutzt werden, um Muster zu erkennen und dadurch einen Einblick in die Daten zu erlangen. Diese Arbeit beschreibt ein Software-Framework f{\"u}r die Visualisierung r{\"a}umlich-zeitlicher Daten, welches GPU-basierte Techniken beinhaltet, um eine interaktive Visualisierung und Exploration großer r{\"a}umlich-zeitlicher Datens{\"a}tze zu erm{\"o}glichen. Die entwickelten Techniken umfassen Datenhaltung, Prozessierung und Rendering und erm{\"o}glichen es, große Datenmengen in Echtzeit zu prozessieren und zu visualisieren. Die Hauptbeitr{\"a}ge der Arbeit umfassen: - Konzept und Implementierung einer GPU-zentrierten Visualisierungspipeline. Die beschriebenen Techniken basieren auf dem Konzept einer GPU-zentrierten Visualisierungspipeline, in welcher alle Stufen -- Prozessierung,Mapping, Rendering -- auf der GPU ausgef{\"u}hrt werden. Bei diesem Konzept werden die r{\"a}umlich-zeitlichen Daten direkt im GPU-Speicher abgelegt. W{\"a}hrend des Rendering-Prozesses werden dann mittels Shader-Programmen die Daten prozessiert, gefiltert, ein Mapping auf visuelle Attribute vorgenommen, und schließlich die Geometrien f{\"u}r die Visualisierung erzeugt. Datenprozessierung, Filtering und Mapping k{\"o}nnen daher in Echtzeit ausgef{\"u}hrt werden. Dies erm{\"o}glicht es Usern, die Mapping-Parameter sowie den gesamten Visualisierungsprozess interaktiv zu steuern und zu kontrollieren. - Interaktive Visualisierung attributierter 3D-Trajektorien. Es wurde eine Visualisierungsmethode f{\"u}r die interaktive Exploration einer großen Anzahl von 3D Bewegungstrajektorien entwickelt. Die Trajektorien werden dabei innerhalb einer virtuellen geographischen Umgebung in Form von einfachen Geometrien, wie Linien, B{\"a}ndern, Kugeln oder R{\"o}hren dargestellt. Durch interaktives Mapping k{\"o}nnen Attributwerte der Trajektorien oder einzelner Messpunkte auf visuelle Eigenschaften abgebildet werden. Hierzu stehen Form, H{\"o}he, Gr{\"o}ße, Farbe, Textur, sowie Animation zur Verf{\"u}gung. Mithilfe dieses dynamischen Mappings wurden außerdem verschiedene Visualisierungsmethoden implementiert, wie z.B. eine Focus+Context-Visualisierung von Trajektorien mithilfe von interaktiven Dichtekarten, sowie einer Space-Time-Cube-Visualisierung zur Darstellung des zeitlichen Ablaufs einzelner Bewegungen. - Interaktive Visualisierung geographischer Netzwerke. Es wurde eine Visualisierungsmethode zur interaktiven Exploration geo-referenzierter Netzwerke entwickelt, welche die Visualisierung von Netzwerken mit einer großen Anzahl von Knoten und Kanten erm{\"o}glicht. Um die Analyse von Netzwerken verschiedener Gr{\"o}ßen und in unterschiedlichen Kontexten zu erm{\"o}glichen, stehen mehrere virtuelle geographische Umgebungen zur Verf{\"u}gung, wie bspw. ein virtueller 3D-Globus, als auch 2D-Karten mit unterschiedlichen geographischen Projektionen. Zur interaktiven Analyse dieser Netzwerke stehen interaktive Tools wie Filterung, Mapping und Selektion zur Verf{\"u}gung. Des weiteren wurden Visualisierungsmethoden f{\"u}r verschiedene Arten von Netzwerken, wie z.B. 3D-Netzwerke und zeitlich ver{\"a}nderliche Netzwerke, implementiert. Zur Demonstration des Konzeptes wurden interaktive Tools f{\"u}r zwei unterschiedliche Anwendungsf{\"a}lle entwickelt. Das erste beinhaltet die Visualisierung attributierter 3D-Trajektorien, welche die Bewegungen von Flugzeugen um einen Flughafen beschreiben. Es erm{\"o}glicht Nutzern, die Trajektorien von ankommenden und startenden Flugzeugen {\"u}ber den Zeitraum eines Monats interaktiv zu explorieren und zu analysieren. Durch Verwendung der interaktiven Visualisierungsmethoden f{\"u}r 3D-Trajektorien und interaktiven Dichtekarten k{\"o}nnen Einblicke in die Daten gewonnen werden, wie beispielsweise h{\"a}ufig genutzte Flugkorridore, typische sowie untypische Bewegungsmuster, oder ungew{\"o}hnliche Vorkommnisse wie Fehlanfl{\"u}ge. Der zweite Anwendungsfall beinhaltet die Visualisierung von Klimanetzwerken, welche geographischen Netzwerken in der Klimaforschung darstellen. Klimanetzwerke repr{\"a}sentieren die Dynamiken im Klimasystem durch eine Netzwerkstruktur, die die statistische Beziehungen zwischen Orten beschreiben. Das entwickelte Tool erm{\"o}glicht es Analysten, diese großen Netzwerke interaktiv zu explorieren und dadurch die Struktur des Netzwerks zu analysieren und mit den geographischen Daten in Beziehung zu setzen. Interaktive Filterung und Selektion erm{\"o}glichen es, Muster in den Daten zu identifizieren, und so bspw. Cluster in der Netzwerkstruktur oder Str{\"o}mungsmuster zu erkennen.},
  language  = {en}
}
@phdthesis{Cheng2018,
  author    = {Cheng, Lung-Pan},
  title     = {Human actuation},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-418371},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xiv, 85},
  year      = {2018},
  abstract  = {Ever since the conception of the virtual reality headset in 1968, many researchers have argued that the next step in virtual reality is to allow users to not only see and hear, but also feel virtual worlds. One approach is to use mechanical equipment to provide haptic feedback, e.g., robotic arms, exoskeletons and motion platforms. However, the size and the weight of such mechanical equipment tends to be proportional to its target's size and weight, i.e., providing human-scale haptic feedback requires human-scale equipment, often restricting them to arcades and lab environments. The key idea behind this dissertation is to bypass mechanical equipment by instead leveraging human muscle power. We thus create software systems that orchestrate humans in doing such mechanical labor—this is what we call human actuation. A potential benefit of such systems is that humans are more generic, flexible, and versatile than machines. This brings a wide range of haptic feedback to modern virtual reality systems. We start with a proof-of-concept system—Haptic Turk, focusing on delivering motion experiences just like a motion platform. All Haptic Turk setups consist of a user who is supported by one or more human actuators. The user enjoys an interactive motion simulation such as a hang glider experience, but the motion is generated by those human actuators who manually lift, tilt, and push the user's limbs or torso. To get the timing and force right, timed motion instructions in a format familiar from rhythm games are generated by the system. Next, we extend the concept of human actuation from 3-DoF to 6-DoF virtual reality where users have the freedom to walk around. TurkDeck tackles this problem by orchestrating a group of human actuators to reconfigure a set of passive props on the fly while the user is progressing in the virtual environment. TurkDeck schedules human actuators by their distances from the user, and instructs them to reconfigure the props to the right place on the right time using laser projection and voice output. Our studies in Haptic Turk and TurkDeck showed that human actuators enjoyed the experience but not as much as users. To eliminate the need of dedicated human actuators, Mutual Turk makes everyone a user by exchanging mechanical actuation between two or more users. Mutual Turk's main functionality is that it orchestrates the users so as to actuate props at just the right moment and with just the right force to produce the correct feedback in each other's experience. Finally, we further eliminate the need of another user, making human actuation applicable to single-user experiences. iTurk makes the user constantly reconfigure and animate otherwise passive props. This allows iTurk to provide virtual worlds with constantly varying or even animated haptic effects, even though the only animate entity present in the system is the user. Our demo experience features one example each of iTurk's two main types of props, i.e., reconfigurable props (the foldable board from TurkDeck) and animated props (the pendulum). We conclude this dissertation by summarizing the findings of our explorations and pointing out future directions. We discuss the development of human actuation compare to traditional machine actuation, the possibility of combining human and machine actuators and interaction models that involve more human actuators.},
  language  = {en}
}
@phdthesis{Gruetze2018,
  author    = {Gr{\"u}tze, Toni},
  title     = {Adding value to text with user-generated content},
  school      = {Universit{\"a}t Potsdam},
  pages     = {ii, 114},
  year      = {2018},
  abstract  = {In recent years, the ever-growing amount of documents on the Web as well as in closed systems for private or business contexts led to a considerable increase of valuable textual information about topics, events, and entities. It is a truism that the majority of information (i.e., business-relevant data) is only available in unstructured textual form. The text mining research field comprises various practice areas that have the common goal of harvesting high-quality information from textual data. These information help addressing users' information needs. In this thesis, we utilize the knowledge represented in user-generated content (UGC) originating from various social media services to improve text mining results. These social media platforms provide a plethora of information with varying focuses. In many cases, an essential feature of such platforms is to share relevant content with a peer group. Thus, the data exchanged in these communities tend to be focused on the interests of the user base. The popularity of social media services is growing continuously and the inherent knowledge is available to be utilized. We show that this knowledge can be used for three different tasks. Initially, we demonstrate that when searching persons with ambiguous names, the information from Wikipedia can be bootstrapped to group web search results according to the individuals occurring in the documents. We introduce two models and different means to handle persons missing in the UGC source. We show that the proposed approaches outperform traditional algorithms for search result clustering. Secondly, we discuss how the categorization of texts according to continuously changing community-generated folksonomies helps users to identify new information related to their interests. We specifically target temporal changes in the UGC and show how they influence the quality of different tag recommendation approaches. Finally, we introduce an algorithm to attempt the entity linking problem, a necessity for harvesting entity knowledge from large text collections. The goal is the linkage of mentions within the documents with their real-world entities. A major focus lies on the efficient derivation of coherent links. For each of the contributions, we provide a wide range of experiments on various text corpora as well as different sources of UGC. The evaluation shows the added value that the usage of these sources provides and confirms the appropriateness of leveraging user-generated content to serve different information needs.},
  language  = {en}
}
@phdthesis{Herzberg2018,
  author    = {Herzberg, Nico},
  title     = {Integrating events into non-automated business process environments},
  school      = {Universit{\"a}t Potsdam},
  pages     = {243},
  year      = {2018},
  language  = {en}
}
@phdthesis{Ion2018,
  author    = {Ion, Alexandra},
  title     = {Metamaterial devices},
  doi       = {10.25932/publishup-42986},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-429861},
  school      = {Universit{\"a}t Potsdam},
  pages     = {x, 173},
  year      = {2018},
  abstract  = {Digital fabrication machines such as 3D printers excel at producing arbitrary shapes, such as for decorative objects. In recent years, researchers started to engineer not only the outer shape of objects, but also their internal microstructure. Such objects, typically based on 3D cell grids, are known as metamaterials. Metamaterials have been used to create materials that, e.g., change their volume, or have variable compliance. While metamaterials were initially understood as materials, we propose to think of them as devices. We argue that thinking of metamaterials as devices enables us to create internal structures that offer functionalities to implement an input-process-output model without electronics, but purely within the material's internal structure. In this thesis, we investigate three aspects of such metamaterial devices that implement parts of the input-process-output model: (1) materials that process analog inputs by implementing mechanisms based on their microstructure, (2) that process digital signals by embedding mechanical computation into the object's microstructure, and (3) interactive metamaterial objects that output to the user by changing their outside to interact with their environment. The input to our metamaterial devices is provided directly by the users interacting with the device by means of physically pushing the metamaterial, e.g., turning a handle, pushing a button, etc. The design of such intricate microstructures, which enable the functionality of metamaterial devices, is not obvious. The complexity of the design arises from the fact that not only a suitable cell geometry is necessary, but that additionally cells need to play together in a well-defined way. To support users in creating such microstructures, we research and implement interactive design tools. These tools allow experts to freely edit their materials, while supporting novice users by auto-generating cells assemblies from high-level input. Our tools implement easy-to-use interactions like brushing, interactively simulate the cell structures' deformation directly in the editor, and export the geometry as a 3D-printable file. Our goal is to foster more research and innovation on metamaterial devices by allowing the broader public to contribute.},
  language  = {en}
}
@phdthesis{Jaeger2018,
  author    = {Jaeger, David},
  title     = {Enabling Big Data security analytics for advanced network attack detection},
  doi       = {10.25932/publishup-43571},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-435713},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XVII, 201, XXXIII},
  year      = {2018},
  abstract  = {The last years have shown an increasing sophistication of attacks against enterprises. Traditional security solutions like firewalls, anti-virus systems and generally Intrusion Detection Systems (IDSs) are no longer sufficient to protect an enterprise against these advanced attacks. One popular approach to tackle this issue is to collect and analyze events generated across the IT landscape of an enterprise. This task is achieved by the utilization of Security Information and Event Management (SIEM) systems. However, the majority of the currently existing SIEM solutions is not capable of handling the massive volume of data and the diversity of event representations. Even if these solutions can collect the data at a central place, they are neither able to extract all relevant information from the events nor correlate events across various sources. Hence, only rather simple attacks are detected, whereas complex attacks, consisting of multiple stages, remain undetected. Undoubtedly, security operators of large enterprises are faced with a typical Big Data problem. In this thesis, we propose and implement a prototypical SIEM system named Real-Time Event Analysis and Monitoring System (REAMS) that addresses the Big Data challenges of event data with common paradigms, such as data normalization, multi-threading, in-memory storage, and distributed processing. In particular, a mostly stream-based event processing workflow is proposed that collects, normalizes, persists and analyzes events in near real-time. In this regard, we have made various contributions in the SIEM context. First, we propose a high-performance normalization algorithm that is highly parallelized across threads and distributed across nodes. Second, we are persisting into an in-memory database for fast querying and correlation in the context of attack detection. Third, we propose various analysis layers, such as anomaly- and signature-based detection, that run on top of the normalized and correlated events. As a result, we demonstrate our capabilities to detect previously known as well as unknown attack patterns. Lastly, we have investigated the integration of cyber threat intelligence (CTI) into the analytical process, for instance, for correlating monitored user accounts with previously collected public identity leaks to identify possible compromised user accounts. In summary, we show that a SIEM system can indeed monitor a large enterprise environment with a massive load of incoming events. As a result, complex attacks spanning across the whole network can be uncovered and mitigated, which is an advancement in comparison to existing SIEM systems on the market.},
  language  = {en}
}
@phdthesis{Klimke2018,
  author    = {Klimke, Jan},
  title     = {Web-based provisioning and application of large-scale virtual 3D city models},
  doi       = {10.25932/publishup-42805},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-428053},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xiii, 141},
  year      = {2018},
  abstract  = {Virtual 3D city models represent and integrate a variety of spatial data and georeferenced data related to urban areas. With the help of improved remote-sensing technology, official 3D cadastral data, open data or geodata crowdsourcing, the quantity and availability of such data are constantly expanding and its quality is ever improving for many major cities and metropolitan regions. There are numerous fields of applications for such data, including city planning and development, environmental analysis and simulation, disaster and risk management, navigation systems, and interactive city maps. The dissemination and the interactive use of virtual 3D city models represent key technical functionality required by nearly all corresponding systems, services, and applications. The size and complexity of virtual 3D city models, their management, their handling, and especially their visualization represent challenging tasks. For example, mobile applications can hardly handle these models due to their massive data volume and data heterogeneity. Therefore, the efficient usage of all computational resources (e.g., storage, processing power, main memory, and graphics hardware, etc.) is a key requirement for software engineering in this field. Common approaches are based on complex clients that require the 3D model data (e.g., 3D meshes and 2D textures) to be transferred to them and that then render those received 3D models. However, these applications have to implement most stages of the visualization pipeline on client side. Thus, as high-quality 3D rendering processes strongly depend on locally available computer graphics resources, software engineering faces the challenge of building robust cross-platform client implementations. Web-based provisioning aims at providing a service-oriented software architecture that consists of tailored functional components for building web-based and mobile applications that manage and visualize virtual 3D city models. This thesis presents corresponding concepts and techniques for web-based provisioning of virtual 3D city models. In particular, it introduces services that allow us to efficiently build applications for virtual 3D city models based on a fine-grained service concept. The thesis covers five main areas: 1. A Service-Based Concept for Image-Based Provisioning of Virtual 3D City Models It creates a frame for a broad range of services related to the rendering and image-based dissemination of virtual 3D city models. 2. 3D Rendering Service for Virtual 3D City Models This service provides efficient, high-quality 3D rendering functionality for virtual 3D city models. In particular, it copes with requirements such as standardized data formats, massive model texturing, detailed 3D geometry, access to associated feature data, and non-assumed frame-to-frame coherence for parallel service requests. In addition, it supports thematic and artistic styling based on an expandable graphics effects library. 3. Layered Map Service for Virtual 3D City Models It generates a map-like representation of virtual 3D city models using an oblique view. It provides high visual quality, fast initial loading times, simple map-based interaction and feature data access. Based on a configurable client framework, mobile and web-based applications for virtual 3D city models can be created easily. 4. Video Service for Virtual 3D City Models It creates and synthesizes videos from virtual 3D city models. Without requiring client-side 3D rendering capabilities, users can create camera paths by a map-based user interface, configure scene contents, styling, image overlays, text overlays, and their transitions. The service significantly reduces the manual effort typically required to produce such videos. The videos can automatically be updated when the underlying data changes. 5. Service-Based Camera Interaction It supports task-based 3D camera interactions, which can be integrated seamlessly into service-based visualization applications. It is demonstrated how to build such web-based interactive applications for virtual 3D city models using this camera service. These contributions provide a framework for design, implementation, and deployment of future web-based applications, systems, and services for virtual 3D city models. The approach shows how to decompose the complex, monolithic functionality of current 3D geovisualization systems into independently designed, implemented, and operated service- oriented units. In that sense, this thesis also contributes to microservice architectures for 3D geovisualization systems—a key challenge of today's IT systems engineering to build scalable IT solutions.},
  language  = {en}
}
@phdthesis{Kruse2018,
  author    = {Kruse, Sebastian},
  title     = {Scalable data profiling},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-412521},
  school      = {Universit{\"a}t Potsdam},
  pages     = {ii, 156},
  year      = {2018},
  abstract  = {Data profiling is the act of extracting structural metadata from datasets. Structural metadata, such as data dependencies and statistics, can support data management operations, such as data integration and data cleaning. Data management often is the most time-consuming activity in any data-related project. Its support is extremely valuable in our data-driven world, so that more time can be spent on the actual utilization of the data, e. g., building analytical models. In most scenarios, however, structural metadata is not given and must be extracted first. Therefore, efficient data profiling methods are highly desirable. Data profiling is a computationally expensive problem; in fact, most dependency discovery problems entail search spaces that grow exponentially in the number of attributes. To this end, this thesis introduces novel discovery algorithms for various types of data dependencies - namely inclusion dependencies, conditional inclusion dependencies, partial functional dependencies, and partial unique column combinations - that considerably improve over state-of-the-art algorithms in terms of efficiency and that scale to datasets that cannot be processed by existing algorithms. The key to those improvements are not only algorithmic innovations, such as novel pruning rules or traversal strategies, but also algorithm designs tailored for distributed execution. While distributed data profiling has been mostly neglected by previous works, it is a logical consequence on the face of recent hardware trends and the computational hardness of dependency discovery. To demonstrate the utility of data profiling for data management, this thesis furthermore presents Metacrate, a database for structural metadata. Its salient features are its flexible data model, the capability to integrate various kinds of structural metadata, and its rich metadata analytics library. We show how to perform a data anamnesis of unknown, complex datasets based on this technology. In particular, we describe in detail how to reconstruct the schemata and assess their quality as part of the data anamnesis. The data profiling algorithms and Metacrate have been carefully implemented, integrated with the Metanome data profiling tool, and are available as free software. In that way, we intend to allow for easy repeatability of our research results and also provide them for actual usage in real-world data-related projects.},
  language  = {en}
}
@phdthesis{Lopes2018,
  author    = {Lopes, Pedro},
  title     = {Interactive Systems Based on Electrical Muscle Stimulation},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-421165},
  school      = {Universit{\"a}t Potsdam},
  pages     = {171},
  year      = {2018},
  abstract  = {How can interactive devices connect with users in the most immediate and intimate way? This question has driven interactive computing for decades. Throughout the last decades, we witnessed how mobile devices moved computing into users' pockets, and recently, wearables put computing in constant physical contact with the user's skin. In both cases moving the devices closer to users allowed devices to sense more of the user, and thus act more personal. The main question that drives our research is: what is the next logical step? Some researchers argue that the next generation of interactive devices will move past the user's skin and be directly implanted inside the user's body. This has already happened in that we have pacemakers, insulin pumps, etc. However, we argue that what we see is not devices moving towards the inside of the user's body, but rather towards the body's biological "interface" they need to address in order to perform their function. To implement our vision, we created a set of devices that intentionally borrow parts of the user's body for input and output, rather than adding more technology to the body. In this dissertation we present one specific flavor of such devices, i.e., devices that borrow the user's muscles. We engineered I/O devices that interact with the user by reading and controlling muscle activity. To achieve the latter, our devices are based on medical-grade signal generators and electrodes attached to the user's skin that send electrical impulses to the user's muscles; these impulses then cause the user's muscles to contract. While electrical muscle stimulation (EMS) devices have been used to regenerate lost motor functions in rehabilitation medicine since the 1960s, in this dissertation, we propose a new perspective: EMS as a means for creating interactive systems. We start by presenting seven prototypes of interactive devices that we have created to illustrate several benefits of EMS. These devices form two main categories: (1) Devices that allow users eyes-free access to information by means of their proprioceptive sense, such as the value of a variable in a computer system, a tool, or a plot; (2) Devices that increase immersion in virtual reality by simulating large forces, such as wind, physical impact, or walls and heavy objects. Then, we analyze the potential of EMS to build interactive systems that miniaturize well and discuss how they leverage our proprioceptive sense as an I/O modality. We proceed by laying out the benefits and disadvantages of both EMS and mechanical haptic devices, such as exoskeletons. We conclude by sketching an outline for future research on EMS by listing open technical, ethical and philosophical questions that we left unanswered.},
  language  = {en}
}
@phdthesis{Pufahl2018,
  author    = {Pufahl, Luise},
  title     = {Modeling and executing batch activities in business processes},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-408013},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xix, 163},
  year      = {2018},
  abstract  = {Business process automation improves organizations' efficiency to perform work. Therefore, a business process is first documented as a process model which then serves as blueprint for a number of process instances representing the execution of specific business cases. In existing business process management systems, process instances run independently from each other. However, in practice, instances are also collected in groups at certain process activities for a combined execution to improve the process performance. Currently, this so-called batch processing is executed manually or supported by external software. Only few research proposals exist to explicitly represent and execute batch processing needs in business process models. These works also lack a comprehensive understanding of requirements. This thesis addresses the described issues by providing a basic concept, called batch activity. It allows an explicit representation of batch processing configurations in process models and provides a corresponding execution semantics, thereby easing automation. The batch activity groups different process instances based on their data context and can synchronize their execution over one or as well multiple process activities. The concept is conceived based on a requirements analysis considering existing literature on batch processing from different domains and industry examples. Further, this thesis provides two extensions: First, a flexible batch configuration concept, based on event processing techniques, is introduced to allow run time adaptations of batch configurations. Second, a concept for collecting and batching activity instances of multiple different process models is given. Thereby, the batch configuration is centrally defined, independently of the process models, which is especially beneficial for organizations with large process model collections. This thesis provides a technical evaluation as well as a validation of the presented concepts. A prototypical implementation in an existing open-source BPMS shows that with a few extensions, batch processing is enabled. Further, it demonstrates that the consolidated view of several work items in one user form can improve work efficiency. The validation, in which the batch activity concept is applied to different use cases in a simulated environment, implies cost-savings for business processes when a suitable batch configuration is used. For the validation, an extensible business process simulator was developed. It enables process designers to study the influence of a batch activity in a process with regards to its performance.},
  language  = {en}
}
@phdthesis{Richter2018,
  author    = {Richter, Rico},
  title     = {Concepts and techniques for processing and rendering of massive 3D point clouds},
  doi       = {10.25932/publishup-42330},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-423304},
  school      = {Universit{\"a}t Potsdam},
  pages     = {v, 131},
  year      = {2018},
  abstract  = {Remote sensing technology, such as airborne, mobile, or terrestrial laser scanning, and photogrammetric techniques, are fundamental approaches for efficient, automatic creation of digital representations of spatial environments. For example, they allow us to generate 3D point clouds of landscapes, cities, infrastructure networks, and sites. As essential and universal category of geodata, 3D point clouds are used and processed by a growing number of applications, services, and systems such as in the domains of urban planning, landscape architecture, environmental monitoring, disaster management, virtual geographic environments as well as for spatial analysis and simulation. While the acquisition processes for 3D point clouds become more and more reliable and widely-used, applications and systems are faced with more and more 3D point cloud data. In addition, 3D point clouds, by their very nature, are raw data, i.e., they do not contain any structural or semantics information. Many processing strategies common to GIS such as deriving polygon-based 3D models generally do not scale for billions of points. GIS typically reduce data density and precision of 3D point clouds to cope with the sheer amount of data, but that results in a significant loss of valuable information at the same time. This thesis proposes concepts and techniques designed to efficiently store and process massive 3D point clouds. To this end, object-class segmentation approaches are presented to attribute semantics to 3D point clouds, used, for example, to identify building, vegetation, and ground structures and, thus, to enable processing, analyzing, and visualizing 3D point clouds in a more effective and efficient way. Similarly, change detection and updating strategies for 3D point clouds are introduced that allow for reducing storage requirements and incrementally updating 3D point cloud databases. In addition, this thesis presents out-of-core, real-time rendering techniques used to interactively explore 3D point clouds and related analysis results. All techniques have been implemented based on specialized spatial data structures, out-of-core algorithms, and GPU-based processing schemas to cope with massive 3D point clouds having billions of points. All proposed techniques have been evaluated and demonstrated their applicability to the field of geospatial applications and systems, in particular for tasks such as classification, processing, and visualization. Case studies for 3D point clouds of entire cities with up to 80 billion points show that the presented approaches open up new ways to manage and apply large-scale, dense, and time-variant 3D point clouds as required by a rapidly growing number of applications and systems.},
  language  = {en}
}
@phdthesis{Sapegin2018,
  author    = {Sapegin, Andrey},
  title     = {High-Speed Security Log Analytics Using Hybrid Outlier Detection},
  doi       = {10.25932/publishup-42611},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-426118},
  school      = {Universit{\"a}t Potsdam},
  pages     = {162},
  year      = {2018},
  abstract  = {The rapid development and integration of Information Technologies over the last decades influenced all areas of our life, including the business world. Yet not only the modern enterprises become digitalised, but also security and criminal threats move into the digital sphere. To withstand these threats, modern companies must be aware of all activities within their computer networks. The keystone for such continuous security monitoring is a Security Information and Event Management (SIEM) system that collects and processes all security-related log messages from the entire enterprise network. However, digital transformations and technologies, such as network virtualisation and widespread usage of mobile communications, lead to a constantly increasing number of monitored devices and systems. As a result, the amount of data that has to be processed by a SIEM system is increasing rapidly. Besides that, in-depth security analysis of the captured data requires the application of rather sophisticated outlier detection algorithms that have a high computational complexity. Existing outlier detection methods often suffer from performance issues and are not directly applicable for high-speed and high-volume analysis of heterogeneous security-related events, which becomes a major challenge for modern SIEM systems nowadays. This thesis provides a number of solutions for the mentioned challenges. First, it proposes a new SIEM system architecture for high-speed processing of security events, implementing parallel, in-memory and in-database processing principles. The proposed architecture also utilises the most efficient log format for high-speed data normalisation. Next, the thesis offers several novel high-speed outlier detection methods, including generic Hybrid Outlier Detection that can efficiently be used for Big Data analysis. Finally, the special User Behaviour Outlier Detection is proposed for better threat detection and analysis of particular user behaviour cases. The proposed architecture and methods were evaluated in terms of both performance and accuracy, as well as compared with classical architecture and existing algorithms. These evaluations were performed on multiple data sets, including simulated data, well-known public intrusion detection data set, and real data from the large multinational enterprise. The evaluation results have proved the high performance and efficacy of the developed methods. All concepts proposed in this thesis were integrated into the prototype of the SIEM system, capable of high-speed analysis of Big Security Data, which makes this integrated SIEM platform highly relevant for modern enterprise security applications.},
  language  = {en}
}
@phdthesis{Vogel2018,
  author    = {Vogel, Thomas},
  title     = {Model-driven engineering of self-adaptive software},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-409755},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xvi, 357},
  year      = {2018},
  abstract  = {The development of self-adaptive software requires the engineering of an adaptation engine that controls the underlying adaptable software by a feedback loop. State-of-the-art approaches prescribe the feedback loop in terms of numbers, how the activities (e.g., monitor, analyze, plan, and execute (MAPE)) and the knowledge are structured to a feedback loop, and the type of knowledge. Moreover, the feedback loop is usually hidden in the implementation or framework and therefore not visible in the architectural design. Additionally, an adaptation engine often employs runtime models that either represent the adaptable software or capture strategic knowledge such as reconfiguration strategies. State-of-the-art approaches do not systematically address the interplay of such runtime models, which would otherwise allow developers to freely design the entire feedback loop. This thesis presents ExecUtable RuntimE MegAmodels (EUREMA), an integrated model-driven engineering (MDE) solution that rigorously uses models for engineering feedback loops. EUREMA provides a domain-specific modeling language to specify and an interpreter to execute feedback loops. The language allows developers to freely design a feedback loop concerning the activities and runtime models (knowledge) as well as the number of feedback loops. It further supports structuring the feedback loops in the adaptation engine that follows a layered architectural style. Thus, EUREMA makes the feedback loops explicit in the design and enables developers to reason about design decisions. To address the interplay of runtime models, we propose the concept of a runtime megamodel, which is a runtime model that contains other runtime models as well as activities (e.g., MAPE) working on the contained models. This concept is the underlying principle of EUREMA. The resulting EUREMA (mega)models are kept alive at runtime and they are directly executed by the EUREMA interpreter to run the feedback loops. Interpretation provides the flexibility to dynamically adapt a feedback loop. In this context, EUREMA supports engineering self-adaptive software in which feedback loops run independently or in a coordinated fashion within the same layer as well as on top of each other in different layers of the adaptation engine. Moreover, we consider preliminary means to evolve self-adaptive software by providing a maintenance interface to the adaptation engine. This thesis discusses in detail EUREMA by applying it to different scenarios such as single, multiple, and stacked feedback loops for self-repairing and self-optimizing the mRUBiS application. Moreover, it investigates the design and expressiveness of EUREMA, reports on experiments with a running system (mRUBiS) and with alternative solutions, and assesses EUREMA with respect to quality attributes such as performance and scalability. The conducted evaluation provides evidence that EUREMA as an integrated and open MDE approach for engineering self-adaptive software seamlessly integrates the development and runtime environments using the same formalism to specify and execute feedback loops, supports the dynamic adaptation of feedback loops in layered architectures, and achieves an efficient execution of feedback loops by leveraging incrementality.},
  language  = {en}
}