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- Hasso-Plattner-Institut für Digital Engineering gGmbH (30) (remove)
Prof. Fink wird zum einen auf die industriell schon lange genutzten natürlichen Polymere wie Cellulose, Stärke und Lignin eingehen, zum anderen auf neue Entwicklungen bei biobasierten Kunststoffen. Von besonderer Bedeutung ist dabei die Aufklärung von Zusammenhängen zwischen Prozessparametern, Strukturen und Eigenschaften.
E-commerce marketplaces are highly dynamic with constant competition. While this competition is challenging for many merchants, it also provides plenty of opportunities, e.g., by allowing them to automatically adjust prices in order to react to changing market situations. For practitioners however, testing automated pricing strategies is time-consuming and potentially hazardously when done in production. Researchers, on the other side, struggle to study how pricing strategies interact under heavy competition. As a consequence, we built an open continuous time framework to simulate dynamic pricing competition called Price Wars. The microservice-based architecture provides a scalable platform for large competitions with dozens of merchants and a large random stream of consumers. Our platform stores each event in a distributed log. This allows to provide different performance measures enabling users to compare profit and revenue of various repricing strategies in real-time. For researchers, price trajectories are shown which ease evaluating mutual price reactions of competing strategies. Furthermore, merchants can access historical marketplace data and apply machine learning. By providing a set of customizable, artificial merchants, users can easily simulate both simple rule-based strategies as well as sophisticated data-driven strategies using demand learning to optimize their pricing strategies.
Mixed-projection treemaps
(2017)
This paper presents a novel technique for combining 2D and 2.5D treemaps using multi-perspective views to leverage the advantages of both treemap types. It enables a new form of overview+detail visualization for tree-structured data and contributes new concepts for real-time rendering of and interaction with treemaps. The technique operates by tilting the graphical elements representing inner nodes using affine transformations and animated state transitions. We explain how to mix orthogonal and perspective projections within a single treemap. Finally, we show application examples that benefit from the reduced interaction overhead.
In this extended abstract, we will analyze the current challenges for the envisioned Self-Adaptive CPS. In addition, we will outline our results to approach these challenges with SMARTSOS [10] a generic approach based on extensions of graph transformation systems employing open and adaptive collaborations and models at runtime for trustworthy self-adaptation, self-organization, and evolution of the individual systems and the system-of-systems level taking the independent development, operation, management, and evolution of these systems into account.
Cost models play an important role for the efficient implementation of software systems. These models can be embedded in operating systems and execution environments to optimize execution at run time. Even though non-uniform memory access (NUMA) architectures are dominating today's server landscape, there is still a lack of parallel cost models that represent NUMA system sufficiently. Therefore, the existing NUMA models are analyzed, and a two-step performance assessment strategy is proposed that incorporates low-level hardware counters as performance indicators. To support the two-step strategy, multiple tools are developed, all accumulating and enriching specific hardware event counter information, to explore, measure, and visualize these low-overhead performance indicators. The tools are showcased and discussed alongside specific experiments in the realm of performance assessment.
As virtualization drives the automation of networking, the validation of security properties becomes more and more challenging eventually ruling out manual inspections. While formal verification in Software Defined Networks is provided by comprehensive tools with high speed reverification capabilities like NetPlumber for instance, the presence of middlebox functionality like firewalls is not considered. Also, they lack the ability to handle dynamic protocol elements like IPv6 extension header chains. In this work, we provide suitable modeling abstractions to enable both - the inclusion of firewalls and dynamic protocol elements. We exemplarily model the Linux ip6tables/netfilter packet filter and also provide abstractions for an application layer gateway. Finally, we present a prototype of our formal verification system FaVe.
Embedded smart home
(2017)
The popularity of MOOCs has increased considerably in the last years. A typical MOOC course consists of video content, self tests after a video and homework, which is normally in multiple choice format. After solving this homeworks for every week of a MOOC, the final exam certificate can be issued when the student has reached a sufficient score. There are also some attempts to include practical tasks, such as programming, in MOOCs for grading. Nevertheless, until now there is no known possibility to teach embedded system programming in a MOOC course where the programming can be done in a remote lab and where grading of the tasks is additionally possible. This embedded programming includes communication over GPIO pins to control LEDs and measure sensor values. We started a MOOC course called "Embedded Smart Home" as a pilot to prove the concept to teach real hardware programming in a MOOC environment under real life MOOC conditions with over 6000 students. Furthermore, also students with real hardware have the possibility to program on their own real hardware and grade their results in the MOOC course. Finally, we evaluate our approach and analyze the student acceptance of this approach to offer a course on embedded programming. We also analyze the hardware usage and working time of students solving tasks to find out if real hardware programming is an advantage and motivating achievement to support students learning success.
Selection of initial points, the number of clusters and finding proper clusters centers are still the main challenge in clustering processes. In this paper, we suggest genetic algorithm based method which searches several solution spaces simultaneously. The solution spaces are population groups consisting of elements with similar structure. Elements in a group have the same size, while elements in different groups are of different sizes. The proposed algorithm processes the population in groups of chromosomes with one gene, two genes to k genes. These genes hold corresponding information about the cluster centers. In the proposed method, the crossover and mutation operators can accept parents with different sizes; this can lead to versatility in population and information transfer among sub-populations. We implemented the proposed method and evaluated its performance against some random datasets and the Ruspini dataset as well. The experimental results show that the proposed method could effectively determine the appropriate number of clusters and recognize their centers. Overall this research implies that using heterogeneous population in the genetic algorithm can lead to better results.
The identification of vulnerabilities relies on detailed information about the target infrastructure. The gathering of the necessary information is a crucial step that requires an intensive scanning or mature expertise and knowledge about the system even though the information was already available in a different context. In this paper we propose a new method to detect vulnerabilities that reuses the existing information and eliminates the necessity of a comprehensive scan of the target system. Since our approach is able to identify vulnerabilities without the additional effort of a scan, we are able to increase the overall performance of the detection. Because of the reuse and the removal of the active testing procedures, our approach could be classified as a passive vulnerability detection. We will explain the approach and illustrate the additional possibility to increase the security awareness of users. Therefore, we applied the approach on an experimental setup and extracted security relevant information from web logs.
This paper discusses a new approach for designing and deploying Security-as-a-Service (SecaaS) applications using cloud native design patterns. Current SecaaS approaches do not efficiently handle the increasing threats to computer systems and applications. For example, requests for security assessments drastically increase after a high-risk security vulnerability is disclosed. In such scenarios, SecaaS applications are unable to dynamically scale to serve requests. A root cause of this challenge is employment of architectures not specifically fitted to cloud environments. Cloud native design patterns resolve this challenge by enabling certain properties e.g. massive scalability and resiliency via the combination of microservice patterns and cloud-focused design patterns. However adopting these patterns is a complex process, during which several security issues are introduced. In this work, we investigate these security issues, we redesign and deploy a monolithic SecaaS application using cloud native design patterns while considering appropriate, layered security counter-measures i.e. at the application and cloud networking layer. Our prototype implementation out-performs traditional, monolithic applications with an average Scanner Time of 6 minutes, without compromising security. Our approach can be employed for designing secure, scalable and performant SecaaS applications that effectively handle unexpected increase in security assessment requests.
Massive Open Online Courses (MOOCs) have left their mark on the face of education during the recent years. At the Hasso Plattner Institute (HPI) in Potsdam, Germany, we are actively developing a MOOC platform, which provides our research with a plethora of e-learning topics, such as learning analytics, automated assessment, peer assessment, team-work, online proctoring, and gamification. We run several instances of this platform. On openHPI, we provide our own courses from within the HPI context. Further instances are openSAP, openWHO, and mooc.HOUSE, which is the smallest of these platforms, targeting customers with a less extensive course portfolio. In 2013, we started to work on the gamification of our platform. By now, we have implemented about two thirds of the features that we initially have evaluated as useful for our purposes. About a year ago we activated the implemented gamification features on mooc.HOUSE. Before activating the features on openHPI as well, we examined, and re-evaluated our initial considerations based on the data we collected so far and the changes in other contexts of our platforms.
The rapid digitalization of the Facility Management (FM) sector has increased the demand for mobile, interactive analytics approaches concerning the operational state of a building. These approaches provide the key to increasing stakeholder engagement associated with Operation and Maintenance (O&M) procedures of living and working areas, buildings, and other built environment spaces. We present a generic and fast approach to process and analyze given 3D point clouds of typical indoor office spaces to create corresponding up-to-date approximations of classified segments and object-based 3D models that can be used to analyze, record and highlight changes of spatial configurations. The approach is based on machine-learning methods used to classify the scanned 3D point cloud data using 2D images. This approach can be used to primarily track changes of objects over time for comparison, allowing for routine classification, and presentation of results used for decision making. We specifically focus on classification, segmentation, and reconstruction of multiple different object types in a 3D point-cloud scene. We present our current research and describe the implementation of these technologies as a web-based application using a services-oriented methodology.
DualPanto
(2018)
We present a new haptic device that enables blind users to continuously track the absolute position of moving objects in spatial virtual environments, as is the case in sports or shooter games. Users interact with DualPanto by operating the me handle with one hand and by holding on to the it handle with the other hand. Each handle is connected to a pantograph haptic input/output device. The key feature is that the two handles are spatially registered with respect to each other. When guiding their avatar through a virtual world using the me handle, spatial registration enables users to track moving objects by having the device guide the output hand. This allows blind players of a 1-on-1 soccer game to race for the ball or evade an opponent; it allows blind players of a shooter game to aim at an opponent and dodge shots. In our user study, blind participants reported very high enjoyment when using the device to play (6.5/7).
Bridging the Gap
(2019)
The recent restructuring of the electricity grid (i.e., smart grid) introduces a number of challenges for today's large-scale computing systems. To operate reliable and efficient, computing systems must adhere not only to technical limits (i.e., thermal constraints) but they must also reduce operating costs, for example, by increasing their energy efficiency. Efforts to improve the energy efficiency, however, are often hampered by inflexible software components that hardly adapt to underlying hardware characteristics. In this paper, we propose an approach to bridge the gap between inflexible software and heterogeneous hardware architectures. Our proposal introduces adaptive software components that dynamically adapt to heterogeneous processing units (i.e., accelerators) during runtime to improve the energy efficiency of computing systems.
Mise-Unseen
(2019)
Creating or arranging objects at runtime is needed in many virtual reality applications, but such changes are noticed when they occur inside the user's field of view. We present Mise-Unseen, a software system that applies such scene changes covertly inside the user's field of view. Mise-Unseen leverages gaze tracking to create models of user attention, intention, and spatial memory to determine if and when to inject a change. We present seven applications of Mise-Unseen to unnoticeably modify the scene within view (i) to hide that task difficulty is adapted to the user, (ii) to adapt the experience to the user's preferences, (iii) to time the use of low fidelity effects, (iv) to detect user choice for passive haptics even when lacking physical props, (v) to sustain physical locomotion despite a lack of physical space, (vi) to reduce motion sickness during virtual locomotion, and (vii) to verify user understanding during story progression. We evaluated Mise-Unseen and our applications in a user study with 15 participants and find that while gaze data indeed supports obfuscating changes inside the field of view, a change is rendered unnoticeably by using gaze in combination with common masking techniques.
Editorial
(2019)
Interactive Close-Up Rendering for Detail plus Overview Visualization of 3D Digital Terrain Models
(2019)
This paper presents an interactive rendering technique for detail+overview visualization of 3D digital terrain models using interactive close-ups. A close-up is an alternative presentation of input data varying with respect to geometrical scale, mapping, appearance, as well as Level-of-Detail (LOD) and Level-of-Abstraction (LOA) used. The presented 3D close-up approach enables in-situ comparison of multiple Regionof-Interests (ROIs) simultaneously. We describe a GPU-based rendering technique for the image-synthesis of multiple close-ups in real-time.
The availability of detailed virtual 3D building models including representations of indoor elements, allows for a wide number of applications requiring effective exploration and navigation functionality. Depending on the application context, users should be enabled to focus on specific Objects-of-Interests (OOIs) or important building elements. This requires approaches to filtering building parts as well as techniques to visualize important building objects and their relations. For it, this paper explores the application and combination of interactive rendering techniques as well as their semanticallydriven configuration in the context of 3D indoor models.
A fundamental task in 3D geovisualization and GIS applications is the visualization of vector data that can represent features such as transportation networks or land use coverage. Mapping or draping vector data represented by geometric primitives (e.g., polylines or polygons) to 3D digital elevation or 3D digital terrain models is a challenging task. We present an interactive GPU-based approach that performs geometry-based draping of vector data on per-frame basis using an image-based representation of a 3D digital elevation or terrain model only.
Industry 4.0 and the Internet of Things are recent developments that have lead to the creation of new kinds of manufacturing data. Linking this new kind of sensor data to traditional business information is crucial for enterprises to take advantage of the data’s full potential. In this paper, we present a demo which allows experiencing this data integration, both vertically between technical and business contexts and horizontally along the value chain. The tool simulates a manufacturing company, continuously producing both business and sensor data, and supports issuing ad-hoc queries that answer specific questions related to the business. In order to adapt to different environments, users can configure sensor characteristics to their needs.