TY - JOUR A1 - Andjelkovic, Marko A1 - Simevski, Aleksandar A1 - Chen, Junchao A1 - Schrape, Oliver A1 - Stamenkovic, Zoran A1 - Krstić, Miloš A1 - Ilic, Stefan A1 - Ristic, Goran A1 - Jaksic, Aleksandar A1 - Vasovic, Nikola A1 - Duane, Russell A1 - Palma, Alberto J. A1 - Lallena, Antonio M. A1 - Carvajal, Miguel A. T1 - A design concept for radiation hardened RADFET readout system for space applications JF - Microprocessors and microsystems N2 - Instruments for measuring the absorbed dose and dose rate under radiation exposure, known as radiation dosimeters, are indispensable in space missions. They are composed of radiation sensors that generate current or voltage response when exposed to ionizing radiation, and processing electronics for computing the absorbed dose and dose rate. Among a wide range of existing radiation sensors, the Radiation Sensitive Field Effect Transistors (RADFETs) have unique advantages for absorbed dose measurement, and a proven record of successful exploitation in space missions. It has been shown that the RADFETs may be also used for the dose rate monitoring. In that regard, we propose a unique design concept that supports the simultaneous operation of a single RADFET as absorbed dose and dose rate monitor. This enables to reduce the cost of implementation, since the need for other types of radiation sensors can be minimized or eliminated. For processing the RADFET's response we propose a readout system composed of analog signal conditioner (ASC) and a self-adaptive multiprocessing system-on-chip (MPSoC). The soft error rate of MPSoC is monitored in real time with embedded sensors, allowing the autonomous switching between three operating modes (high-performance, de-stress and fault-tolerant), according to the application requirements and radiation conditions. KW - RADFET KW - Radiation hardness KW - Absorbed dose KW - Dose rate KW - Self-adaptive MPSoC Y1 - 2022 U6 - https://doi.org/10.1016/j.micpro.2022.104486 SN - 0141-9331 SN - 1872-9436 VL - 90 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Tran, Son Cao A1 - Pontelli, Enrico A1 - Balduccini, Marcello A1 - Schaub, Torsten T1 - Answer set planning BT - a survey JF - Theory and practice of logic programming N2 - Answer Set Planning refers to the use of Answer Set Programming (ASP) to compute plans, that is, solutions to planning problems, that transform a given state of the world to another state. The development of efficient and scalable answer set solvers has provided a significant boost to the development of ASP-based planning systems. This paper surveys the progress made during the last two and a half decades in the area of answer set planning, from its foundations to its use in challenging planning domains. The survey explores the advantages and disadvantages of answer set planning. It also discusses typical applications of answer set planning and presents a set of challenges for future research. KW - planning KW - knowledge representation and reasoning KW - logic programming Y1 - 2022 U6 - https://doi.org/10.1017/S1471068422000072 SN - 1471-0684 SN - 1475-3081 PB - Cambridge University Press CY - New York ER - TY - JOUR A1 - Steinert, Fritjof A1 - Stabernack, Benno T1 - Architecture of a low latency H.264/AVC video codec for robust ML based image classification how region of interests can minimize the impact of coding artifacts JF - Journal of Signal Processing Systems for Signal, Image, and Video Technology N2 - The use of neural networks is considered as the state of the art in the field of image classification. A large number of different networks are available for this purpose, which, appropriately trained, permit a high level of classification accuracy. Typically, these networks are applied to uncompressed image data, since a corresponding training was also carried out using image data of similar high quality. However, if image data contains image errors, the classification accuracy deteriorates drastically. This applies in particular to coding artifacts which occur due to image and video compression. Typical application scenarios for video compression are narrowband transmission channels for which video coding is required but a subsequent classification is to be carried out on the receiver side. In this paper we present a special H.264/Advanced Video Codec (AVC) based video codec that allows certain regions of a picture to be coded with near constant picture quality in order to allow a reliable classification using neural networks, whereas the remaining image will be coded using constant bit rate. We have combined this feature with the ability to run with lowest latency properties, which is usually also required in remote control applications scenarios. The codec has been implemented as a fully hardwired High Definition video capable hardware architecture which is suitable for Field Programmable Gate Arrays. KW - H.264 KW - Advanced Video Codec (AVC) KW - Low Latency KW - Region of Interest KW - Machine Learning KW - Inference KW - FPGA KW - Hardware accelerator Y1 - 2022 U6 - https://doi.org/10.1007/s11265-021-01727-2 SN - 1939-8018 SN - 1939-8115 VL - 94 IS - 7 SP - 693 EP - 708 PB - Springer CY - New York ER - TY - JOUR A1 - Al Laban, Firas A1 - Reger, Martin A1 - Lucke, Ulrike T1 - Closing the Policy Gap in the Academic Bridge JF - Education sciences N2 - The highly structured nature of the educational sector demands effective policy mechanisms close to the needs of the field. That is why evidence-based policy making, endorsed by the European Commission under Erasmus+ Key Action 3, aims to make an alignment between the domains of policy and practice. Against this background, this article addresses two issues: First, that there is a vertical gap in the translation of higher-level policies to local strategies and regulations. Second, that there is a horizontal gap between educational domains regarding the policy awareness of individual players. This was analyzed in quantitative and qualitative studies with domain experts from the fields of virtual mobility and teacher training. From our findings, we argue that the combination of both gaps puts the academic bridge from secondary to tertiary education at risk, including the associated knowledge proficiency levels. We discuss the role of digitalization in the academic bridge by asking the question: which value does the involved stakeholders expect from educational policies? As a theoretical basis, we rely on the model of value co-creation for and by stakeholders. We describe the used instruments along with the obtained results and proposed benefits. Moreover, we reflect on the methodology applied, and we finally derive recommendations for future academic bridge policies. KW - policy evaluation KW - higher education KW - virtual mobility KW - teacher training Y1 - 2022 U6 - https://doi.org/10.3390/educsci12120930 SN - 2227-7102 VL - 12 IS - 12 PB - MDPI CY - Basel ER - TY - JOUR A1 - Lorenz, Claas A1 - Clemens, Vera Elisabeth A1 - Schrötter, Max A1 - Schnor, Bettina T1 - Continuous verification of network security compliance JF - IEEE transactions on network and service management N2 - Continuous verification of network security compliance is an accepted need. Especially, the analysis of stateful packet filters plays a central role for network security in practice. But the few existing tools which support the analysis of stateful packet filters are based on general applicable formal methods like Satifiability Modulo Theories (SMT) or theorem prover and show runtimes in the order of minutes to hours making them unsuitable for continuous compliance verification. In this work, we address these challenges and present the concept of state shell interweaving to transform a stateful firewall rule set into a stateless rule set. This allows us to reuse any fast domain specific engine from the field of data plane verification tools leveraging smart, very fast, and domain specialized data structures and algorithms including Header Space Analysis (HSA). First, we introduce the formal language FPL that enables a high-level human-understandable specification of the desired state of network security. Second, we demonstrate the instantiation of a compliance process using a verification framework that analyzes the configuration of complex networks and devices - including stateful firewalls - for compliance with FPL policies. Our evaluation results show the scalability of the presented approach for the well known Internet2 and Stanford benchmarks as well as for large firewall rule sets where it outscales state-of-the-art tools by a factor of over 41. KW - Security KW - Tools KW - Network security KW - Engines KW - Benchmark testing; KW - Analytical models KW - Scalability KW - Network KW - security KW - compliance KW - formal KW - verification Y1 - 2021 U6 - https://doi.org/10.1109/TNSM.2021.3130290 SN - 1932-4537 VL - 19 IS - 2 SP - 1729 EP - 1745 PB - Institute of Electrical and Electronics Engineers CY - New York ER - TY - JOUR A1 - Abdelwahab, Ahmed A1 - Landwehr, Niels T1 - Deep Distributional Sequence Embeddings Based on a Wasserstein Loss JF - Neural processing letters N2 - Deep metric learning employs deep neural networks to embed instances into a metric space such that distances between instances of the same class are small and distances between instances from different classes are large. In most existing deep metric learning techniques, the embedding of an instance is given by a feature vector produced by a deep neural network and Euclidean distance or cosine similarity defines distances between these vectors. This paper studies deep distributional embeddings of sequences, where the embedding of a sequence is given by the distribution of learned deep features across the sequence. The motivation for this is to better capture statistical information about the distribution of patterns within the sequence in the embedding. When embeddings are distributions rather than vectors, measuring distances between embeddings involves comparing their respective distributions. The paper therefore proposes a distance metric based on Wasserstein distances between the distributions and a corresponding loss function for metric learning, which leads to a novel end-to-end trainable embedding model. We empirically observe that distributional embeddings outperform standard vector embeddings and that training with the proposed Wasserstein metric outperforms training with other distance functions. KW - Metric learning KW - Sequence embeddings KW - Deep learning Y1 - 2022 U6 - https://doi.org/10.1007/s11063-022-10784-y SN - 1370-4621 SN - 1573-773X PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Michallek, Florian A1 - Genske, Ulrich A1 - Niehues, Stefan Markus A1 - Hamm, Bernd A1 - Jahnke, Paul T1 - Deep learning reconstruction improves radiomics feature stability and discriminative power in abdominal CT imaging BT - a phantom study JF - European Radiology N2 - Objectives To compare image quality of deep learning reconstruction (AiCE) for radiomics feature extraction with filtered back projection (FBP), hybrid iterative reconstruction (AIDR 3D), and model-based iterative reconstruction (FIRST). Methods Effects of image reconstruction on radiomics features were investigated using a phantom that realistically mimicked a 65-year-old patient's abdomen with hepatic metastases. The phantom was scanned at 18 doses from 0.2 to 4 mGy, with 20 repeated scans per dose. Images were reconstructed with FBP, AIDR 3D, FIRST, and AiCE. Ninety-three radiomics features were extracted from 24 regions of interest, which were evenly distributed across three tissue classes: normal liver, metastatic core, and metastatic rim. Features were analyzed in terms of their consistent characterization of tissues within the same image (intraclass correlation coefficient >= 0.75), discriminative power (Kruskal-Wallis test p value < 0.05), and repeatability (overall concordance correlation coefficient >= 0.75). Results The median fraction of consistent features across all doses was 6%, 8%, 6%, and 22% with FBP, AIDR 3D, FIRST, and AiCE, respectively. Adequate discriminative power was achieved by 48%, 82%, 84%, and 92% of features, and 52%, 20%, 17%, and 39% of features were repeatable, respectively. Only 5% of features combined consistency, discriminative power, and repeatability with FBP, AIDR 3D, and FIRST versus 13% with AiCE at doses above 1 mGy and 17% at doses >= 3 mGy. AiCE was the only reconstruction technique that enabled extraction of higher-order features. Conclusions AiCE more than doubled the yield of radiomics features at doses typically used clinically. Inconsistent tissue characterization within CT images contributes significantly to the poor stability of radiomics features. KW - Tomography KW - X-ray computed KW - Phantoms KW - imaging KW - Liver neoplasms KW - Algorithms KW - Reproducibility of results Y1 - 2022 U6 - https://doi.org/10.1007/s00330-022-08592-y SN - 1432-1084 VL - 32 IS - 7 SP - 4587 EP - 4595 PB - Springer CY - New York ER - TY - JOUR A1 - Marco Figuera, Ramiro A1 - Riedel, Christian A1 - Rossi, Angelo Pio A1 - Unnithan, Vikram T1 - Depth to diameter analysis on small simple craters at the lunar south pole - possible implications for ice harboring JF - Remote sensing N2 - In this paper, we present a study comparing the depth to diameter (d/D) ratio of small simple craters (200-1000 m) of an area between -88.5 degrees to -90 degrees latitude at the lunar south pole containing Permanent Shadowed Regions (PSRs) versus craters without PSRs. As PSRs can reach temperatures of 110 K and are capable of harboring volatiles, especially water ice, we analyzed the relationship of depth versus diameter ratios and its possible implications for harboring water ice. Variations in the d/D ratios can also be caused by other processes such as degradation, isostatic adjustment, or differences in surface properties. The conducted d/D ratio analysis suggests that a differentiation between craters containing PSRs versus craters without PSRs occurs. Thus, a possible direct relation between d/D ratio, PSRs, and water ice harboring might exist. Our results suggest that differences in the target's surface properties may explain the obtained results. The resulting d/D ratios of craters with PSRs can help to select target areas for future In-Situ Resource Utilization (ISRU) missions. KW - craters KW - lunar exploration KW - ice harboring Y1 - 2022 U6 - https://doi.org/10.3390/rs14030450 SN - 2072-4292 VL - 14 IS - 3 PB - MDPI CY - Basel ER - TY - JOUR A1 - Möring, Sebastian A1 - Leino, Olli Tapio T1 - Die neoliberale Bedingung von Computerspielen JF - Kontrollmaschinen - zur Dispositivtheorie des Computerspiels Y1 - 2022 SN - 978-3-643-14780-6 SP - 41 EP - 61 PB - LiteraturWissenschaft.de CY - Münster ER - TY - JOUR A1 - Breitenreiter, Anselm A1 - Andjelković, Marko A1 - Schrape, Oliver A1 - Krstić, Miloš T1 - Fast error propagation probability estimates by answer set programming and approximate model counting JF - IEEE Access N2 - We present a method employing Answer Set Programming in combination with Approximate Model Counting for fast and accurate calculation of error propagation probabilities in digital circuits. By an efficient problem encoding, we achieve an input data format similar to a Verilog netlist so that extensive preprocessing is avoided. By a tight interconnection of our application with the underlying solver, we avoid iterating over fault sites and reduce calls to the solver. Several circuits were analyzed with varying numbers of considered cycles and different degrees of approximation. Our experiments show, that the runtime can be reduced by approximation by a factor of 91, whereas the error compared to the exact result is below 1%. KW - Circuit faults KW - Integrated circuit modeling KW - Programming KW - Analytical models KW - Search problems KW - Flip-flops KW - Encoding KW - Answer set programming KW - approximate model counting KW - error propagation KW - radhard design KW - reliability analysis KW - selective fault tolerance KW - single event upsets Y1 - 2022 U6 - https://doi.org/10.1109/ACCESS.2022.3174564 SN - 2169-3536 VL - 10 SP - 51814 EP - 51825 PB - Inst. of Electr. and Electronics Engineers CY - Piscataway ER -