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49. Jahrestagung der Gesellschaft fur Informatik: 50 Jahre Gesellschaft fur Informatik - Informatik fur Gesellschaft, INFORMATIK 2019 - 49th Annual Meeting of the German Informatics Society: 50 years of the German Informatics Society - computer science for Society, INFORMATICS 2019

作者： Müller, Robert Schmitt, Corinna Kaiser, Daniel Waldvogel, Marcel Department of Computer and Information Science Distributed Systems Laboratory Universität Konstanz Konstanz78457 Germany Research Institute Code Universität der Bundeswehr München Werner-Heisenberg-Weg 39 Neubiberg85577 Germany Security and Networking Research Group Netlab Maison du Nombre 6 University of Luxembourg Avenue de la Fonte Esch-sur-Alzette4364 Luxembourg

ISBN: (纸本)9783885796886

Integrating Internet of Things (IoT) devices into an existing network is a nightmare. Minimalistic, unfriendly user interfaces, if any;badly chosen security methods, most notably the defaults;lack of long term security;and bugs or misconAgurations are plentiful. As a result, an increasing number of owners operate unsecure devices. Our investigations into the root causes of the problems resulted in the development of Home CertiAcate Authority (HomeCA). HomeCAincludes a comprehensive set of secure, vendor-independent interoperable practices based on existing protocols and open standards. HomeCA avoids most of the current pitfalls in network integration by design. Long-term protocol security, permission management, and secure usage combined with simpliAed device integration and secure key updates on ownership acquisition pave the way toward scalable, federated IoT security. © 2019 Gesellschaft fur Informatik (GI). All rights reserved.

关键词： Network security

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Geo-Cloudlet: Time and Power Efficient Geospatial Query Resolution using Cloudlet

Geo-Cloudlet: Time and Power Efficient Geospatial Query Reso...

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International Conference on Advanced Computing, ICAC

作者： Jaydeep Das Anwesha Mukherjee Soumya K. Ghosh Rajkumar Buyya Advanced Technology Development Centre Indian Institute of Technology Kharagpur West Bengal India Department of Computer Science Mahishadal Raj College Purba Medinipur West Bengal India Department of Computer Science and Engineering Indian Institute of Technology Kharagpur West Bengal India Cloud Computing and Distributed Systems (CLOUDS) Lab School of Computing and Information Systems The University of Melbourne VIC Australia

ISBN: (数字)9781728152868

ISBN: (纸本)9781728152875

Geospatial data analysis is an emerging area of research today due to the potential to enable varied location-aware services. The existing centralized cloud-based analysis becomes time and computing-intensive for huge amount of geospatial data processing. This paper addresses the challenge of time and power-efficiency in QoS-aware geospatial query resolution. We propose a cloudlet based hierarchical paradigm, namely Geo-Cloudlet, where the cloudlets contain the geospatial data of the districts. The state and national level geospatial data are stored inside the state cloud and country cloud respectively. The query resolution is performed by either the cloudlet or by the state cloud or country cloud depending upon the geographical region related to the query. The experimental analysis illustrates that the proposed architecture Geo-Cloudlet reduces the latency up to 61.3% and power consumption up to 61.1% over the use of only remote cloud servers for geospatial query resolution.

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Automated Classification of Airborne Pollen using Neural Networks

Automated Classification of Airborne Pollen using Neural Net...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Julian Schiele Fabian Rabe Maximilian Schmitt Manuel Glaser Franziska Häring Jens O. Brunner Bernhard Bauer Björn Schuller Claudia Traidl-Hoffmann Athanasios Damialis Chair of Health Care Operations / Health Information Management Faculty of Business and Economics University Center of Health Sciences at Klinikum Augsburg (UNIKA-T) Chair of Software Methodologies for Distributed Systems Faculty of Computer Science University of Augsburg ZD.B Chair of Embedded Intelligence for Health Care and Wellbeing Faculty of Computer Science University of Augsburg Chair and Institute of Environmental Medicine UNIKA-T Technical University of Munich and Helmholtz Zentrum München

Pollen allergies are considered as a global epidemic nowadays, as they influence more than a quarter of the worldwide population, with this percentage expected to rapidly increase because of ongoing climate change. To date, alerts on high-risk allergenic pollen exposure have been provided only via forecasting models and conventional monitoring methods that are laborious. The aim of this study is to develop and evaluate our own pollen classification model based on deep neural networks. Airborne allergenic pollen have been monitored in Augsburg, Bavaria, Germany, since 2015, using a novel automatic Bio-Aerosol Analyzer (BAA 500, Hund GmbH). The automatic classification system is compared and evaluated against our own, newly developed algorithm. Our model achieves an unweighted average precision of 83.0 % and an unweighted average recall of 77.1 % across 15 classes of pollen taxa. Automatic, real-time information on concentrations of airborne allergenic pollen will significantly contribute to the implementation of timely, personalized management of allergies in the future. It is already clear that new methods and sophisticated models have to be developed so as to successfully switch to novel operational pollen monitoring techniques serving the above need.

关键词： Monitoring Training Neural networks Atmospheric modeling Biological system modeling Respiratory system Neurons

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Genomic map of the functionally extinct northern white rhinoceros (Ceratotherium simum cottoni)

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Proceedings of the National Academy of sciences of the United States of America 2025年第20期122卷 e2401207122页

作者： Wang, Gaojianyong Korody, Marisa L. Brändl, Björn Hernandez-Toro, Camilo Jose Rohrandt, Christian Hong, Karl Pang, Andy Wing Chun Lee, Joyce Migliorelli, Giovanna Stanke, Mario Ford, Sarah M. Pollmann, Iris Houck, Marlys L. Lewin, Harris A. Lear, Teri L. Ryder, Oliver A. Meissner, Alexander Loring, Jeanne F. Müller, Franz-Josef Department of Genome Regulation Max Planck Institute for Molecular Genetics 14195 Berlin Germany Department of Psychiatry and Psychotherapy Christian-Albrechts Universität Kiel 24105 Germany Zentrum für Integrative Psychiatrie University Hospital Schleswig-Holstein Kiel 24105 Germany San Diego Zoo Wildlife Alliance Escondido 92027 CA United States Institute for Communications Technologies and Embedded Systems Kiel University of Applied Sciences Kiel 24149 Germany Bionano Genomics Inc San Diego CA 92121 Institute of Mathematics and Computer Science Center for Functional Genomics of Microbes University of Greifswald Germany Department of Ecology and Evolutionary Biology University of California CA 95060 Santa Cruz Argentina The Genome Center University of California Davis CA 95616 Department of Evolution and Ecology University of California Davis CA 95616 John Muir Institute for the Environment University of California Davis CA 95616 Gluck Equine Research Center Department of Veterinary Science University of Kentucky Lexington United States Scripps Research La Jolla CA 92037 Italy

The northern white rhinoceros (NWR;Ceratotherium simum cottoni) is functionally extinct, with only two nonreproductive females alive. Efforts to rescue the NWR from its inevitable demise have inspired the exploration of unconventional conservation methods, including the development of induced pluripotent stem cells (iPSCs) for the in vitro generation of artificial gametes. The integrity of iPSC genomes is critical for in vitro gametogenesis to be used for assisted reproductive technologies using NWR iPSCs. We generated a chromosome-level NWR reference genome that meets or exceeds the metrics proposed by the Vertebrate Genome Project, using complementary sequencing and mapping methods. The genome represents 40 autosomes, an X and a partially resolved Y chromosome, and the mitochondrial genome. Using comparative FISH mapping, we confirmed a general gene order conservation between the NWR and horse genomes. We aligned the NWR genome with that of the southern white rhinoceros (SWR;Ceratotherium simum simum), a population that has been physically separated from the NWR for tens of thousands of years, and we found that the two subspecies are very similar on the chromosome level. Comparing long-read data from NWR iPSC lines and the fibroblast cultures used for reprogramming, we identified copy number variations that were likely to have been introduced during in vitro iPSC expansion. The NWR reference genome allows for efficient, rapid, and accurate assessment of the genomic integrity of iPSC lines to direct their differentiation. This will assist in strategies to rescue the NWR through extraordinary measures like cloning and the generation of embryos from iPSC-derived gametes.

关键词： genome assembly genome integrity iPSC northern white rhinoceros southern white rhinoceros

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Automated design of error-resilient and hardware-efficient deep neural networks

arXiv

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arXiv 2019年

作者： Schorn, Christoph Elsken, Thomas Vogel, Sebastian Runge, Armin Guntoro, Andre Ascheid, Gerd Department of Dependable Connected Systems Bosch Corporate Research Renningen Germany Institute for Communication Technologies and Embedded Systems RWTH Aachen University Aachen Germany Bosch Center for Artificial Intelligence Renningen Germany Department of Computer Science University of Freiburg Freiburg im Breisgau Germany

Applying deep neural networks (DNNs) in mobile and safety-critical systems, such as autonomous vehicles, demands a reliable and efficient execution on hardware. Optimized dedicated hardware accelerators are being developed to achieve this. However, the design of efficient and reliable hardware has become increasingly difficult, due to the increased complexity of modern integrated circuit technology and its sensitivity against hardware faults, such as random bit-flips. It is thus desirable to exploit optimization potential for error resilience and efficiency also at the algorithmic side, e.g. by optimizing the architecture of the DNN. Since there are numerous design choices for the architecture of DNNs, with partially opposing effects on the preferred characteristics (such as small error rates at low latency), multi-objective optimization strategies are necessary. In this paper, we develop an evolutionary optimization technique for the automated design of hardware-optimized DNN architectures. For this purpose, we derive a set of easily computable objective functions, which enable the fast evaluation of DNN architectures with respect to their hardware efficiency and error resilience solely based on the network topology. We observe a strong correlation between predicted error resilience and actual measurements obtained from fault injection simulations. Furthermore, we analyze two different quantization schemes for efficient DNN computation and find significant differences regarding their effect on error resilience. Copyright © 2019, The Authors. All rights reserved.

关键词： Multiobjective optimization

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Towards Self-Explainable Cyber-Physical systems

Towards Self-Explainable Cyber-Physical Systems

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ACM/IEEE International Conference on Model Driven Engineering Languages and systems Companion

作者： Mathias Blumreiter Joel Greenyer Francisco Javier Chiyah Garcia Verena Klos Maike Schwammberger Christoph Sommer Andreas Vogelsang Andreas Wortmann Institute for Software Systems Hamburg University of Technology Software Engineering Group Leibniz Universitat Hannover Heriot-Watt University Software and Embedded Systems Engineering Technische Universitat Berlin Department of Computing Science University of Oldenburg Heinz Nixdorf Institute and Dept. of Computer Science Paderborn University Automated Systems Engineering Technologies Technische Universitat Berlin Software Engineering RWTH Aachen University

ISBN: (纸本)9781728151267

With the increasing complexity of Cyber-Physical systems, their behavior and decisions become increasingly difficult to understand and comprehend for users and other stakeholders. Our vision is to build self-explainable systems that can, at run-time, answer questions about the system's past, current, and future behavior. As hitherto no design methodology or reference framework exists for building such systems, we propose the Monitor, Analyze, Build, Explain (MAB-EX) framework for building self-explainable systems that leverage requirements- and explainability models at run-time. The basic idea of MAB-EX is to first Monitor and Analyze a certain behavior of a system, then Build an explanation from explanation models and convey this EXplanation in a suitable way to a stakeholder. We also take into account that new explanations can be learned, by updating the explanation models, should new and yet un-explainable behavior be detected by the system.

关键词： Explainability Self-adaptive systems Cyber-physical systems Adaptive systems Cyber-physical systems MONITOR Runtime Buildings

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An energy-aware resource provisioning scheme for real-time applications in a cloud data center

An energy-aware resource provisioning scheme for real-time a...

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作者： Faragardi, Hamid Reza Dehnavi, Saeid Nolte, Thomas Kargahi, Mehdi Fahringer, Thomas School of Innovation Design and Engineering Mälardalen University Västerås Sweden Distributed and Parallel Systems Group Institute of Computer Science Innsbruck University Innsbruck Austria School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Tehran Iran

Based on a pay-as-you-go model, cloud computing provides the possibility of hosting pervasive applications from both academic and business domains. However, data centers hosting cloud applications consume huge amounts of electrical energy, contributing to high operational costs and large carbon footprints to the environment. Energy-aware resource provisioning is an effective solution to diminish the energy consumption of cloud data centers. Recently, a growing trend has emerged, where cloud technology is used to run periodic real-time applications such as multimedia, telecommunication, video gaming, and industrial applications. In order for a real-time application to be able to use cloud services, cloud providers have to be able to provide timing guarantees. In this paper, we introduce an energy-aware resource provisioning mechanism for cloud data centers, which are capable of serving real-time periodic tasks following the Software as a Service model. The proposed method is compared against an energy-aware version of the RT-OpenStack. RT-OpenStack is a recently proposed approach to provide a time-predictable version of OpenStack. The experimental results manifest that our proposed resource provisioning method outperforms energy-aware version of the RT-OpenStack by 16.01%, 25.45%, and 25.45% in terms of energy consumption, number of used servers, and average utilization of used servers, respectively. Moreover, from the scalability perspective, the preference of the proposed method for large-scale data centers is more considerable. Copyright © 2018 John Wiley & Sons, Ltd.

关键词： Ant colony optimization

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Towards self-explainable cyber-physical systems

arXiv

引用

arXiv 2019年

作者： Blumreiter, Mathias Greenyer, Joel Garcia, Francisco Javier Chiyah Klös, Verena Schwammberger, Maike Sommer, Christoph Vogelsang, Andreas Wortmannz, Andreas Institute for Software Systems Hamburg University of Technology Software Engineering Group Leibniz Universität Hannover Germany Heriot-Watt University Software and Embedded Systems Engineering Technische Universität Berlin Germany Department of Computing Science University of Oldenburg Heinz Nixdorf Institute Dept. of Computer Science Paderborn University Automated Systems Engineering Technologies Technische Universität Berlin Germany Software Engineering RWTH Aachen University

With the increasing complexity of Cyber-Physical systems, their behavior and decisions become increasingly difficult to understand and comprehend for users and other stakeholders. Our vision is to build self-explainable systems that can, at run-time, answer questions about the system's past, current, and future behavior. As hitherto no design methodology or reference framework exists for building such systems, we propose the Monitor, Analyze, Build, Explain (MAB-EX) framework for building self-explainable systems that leverage requirements- A nd explainability models at run-time. The basic idea of MAB-EX is to first Monitor and Analyze a certain behavior of a system, then Build an explanation from explanation models and convey this EXplanation in a suitable way to a stakeholder. We also take into account that new explanations can be learned, by updating the explanation models, should new and yet unexplainable behavior be detected by the system. Copyright © 2019, The Authors. All rights reserved.

关键词： embedded systems

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Context-dependent multimodal communication in human-robot collaboration

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Procedia CIRP 2018年 72卷 15-20页

作者： Csaba Kardos Zsolt Kemény András Kovács Balázs E. Pataki József Váncza EPIC Center of Excellence in Production Informatics and Control Institute for Computer Science and Control Hungarian Academy of Sciences Department of Manufacturing Science and Technology Budapest University of Technology and Economics Department of Distributed Systems Institute for Computer Science and Control Hungarian Academy of Sciences

In the dynamic environment of human-robot collaboration, a key for boosting the efficiency of human workers is supporting them with context-dependent work instructions, delivered via communication modalities that suit the actual context. Workers, in turn, should be supported in controlling the robot or other components of the production system by using the most convenient modality, thus lifting the limitations of traditional interfaces as push buttons installed at fixed locations. We introduce a workflow for context-dependent multimodal communication in a collaborative work environment and present its implementation in a Human-Machine Interface Controller system.

关键词： human-robot collaboration worker information systems multi-modal communication

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A Chance Constrained Optimal Reserve Scheduling Approach for Economic Dispatch Considering Wind Penetration

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IEEE/CAA Journal of Automatica Sinica 2017年第2期4卷 186-194页

作者： Yufei Tang Chao Luo Jun Yang Haibo He IEEE Department of Computer & Electrical Engineering and Computer Science and the Institute for Sensing and Embedded Network Systems EngineeringFlorida Atlantic University School of Electrical Engineering Wuhan University Department of Electrical Computer and Biomedical EngineeringUniversity of Rhode Island

The volatile wind power generation brings a full spectrum of problems to power system operation and management, ranging from transient system frequency fluctuation to steady state supply and demand balancing issue. In this paper, a novel wind integrated power system day-ahead economic dispatch model, with the consideration of generation and reserve cost is modelled and investigated. The proposed problem is first formulated as a chance constrained stochastic nonlinear programming U+0028 CCSNLP U+0029, and then transformed into a deterministic nonlinear programming U+0028 NLP U+0029. To tackle this NLP problem, a three-stage framework consists of particle swarm optimization U+0028 PSO U+0029, sequential quadratic programming U+0028 SQP U+0029 and Monte Carlo simulation U+0028 MCS U+0029 is proposed. The PSO is employed to heuristically search the line power flow limits, which are used by the SQP as constraints to solve the NLP problem. Then the solution from SQP is verified on benchmark system by using MCS. Finally, the verified results are feedback to the PSO as fitness value to update the particles. Simulation study on IEEE 30-bus system with wind power penetration is carried out, and the results demonstrate that the proposed dispatch model could be effectively solved by the proposed three-stage approach. © 2017 Chinese Association of Automation.

关键词： Constrained optimization Economics Electric load flow Electric power generation Intelligent systems Monte Carlo methods Nonlinear programming Optimization Particle swarm optimization (PSO) Problem solving Quadratic programming Scheduling Stochastic systems Wind power

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