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2021 International Symposium on Networks, computers and Communications, ISNCC 2021

作者： Abid, Aymen Khediri, Salim El Moulahi, Tarek Cheour, Rym Kachouri, Abdennaceur Computer And Embedded Systems Lab National Engineering School Sfax Tunisia College Of Computer Department Of Infomration Technology Gabes Tunisia Advanced Fluid Dynamics Energetics And Evironment Lab National Engineering School Sfax Tunisia

ISBN: (纸本)9780738113166

The target of a Wireless Sensor Network (WSN) designer is to improve the robustness of the network while taking into account constraints such as verifying the detection of anomalies. Preventing anomalies can be assured by data analysis via outliers identification as it strongly affects decision-making in the case of smart-home, e-health and other high-risk applications. In this paper, we study some families of outliers and we propose to detect data anomalies using K Nearest Neighbours (KNN) and Voting techniques by a benchmark suitable to be a simulation for a smart-house. In order to evaluate the dependability, some performance metrics are analyzed such as data rate detection, precision, specificity and accuracy. Performance results are in the order of 100% detection rate with reduced false alarm and fast response time compared to some other existing ones. © 2021 IEEE.

关键词： Wireless sensor networks

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Vision-based fall detection and prevention for the elderly people: A review ongoing research 5

Vision-based fall detection and prevention for the elderly p...

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5th International Conference on Intelligent Computing in Data Sciences, ICDS 2021

作者： Guendoul, Oumaima Hamd, Ait Abdelali Youness, Tabii Rachid, Oulad Haj Thami Omar, Bourja Mohammed v University ADMIR Lab National School of Computer Science and Systems Analysis ENSIAS Rabat10000 Morocco MAScIR Embedded Systems and Artificial Intelligence Department Rabat10000 Morocco

ISBN: (纸本)9781665442381

Falls are the most leading cause of accidental injury deaths worldwide, therefore, it poses a real challenge for the prevention of life-threatening conditions in geriatrics. The most damaged community is the ever-growing aging population. For this reason, there are considerable demands to distinguish a dangerous posture such as fall in real-time. Here we provide a literature review of conducted work on elderly fall detection and prediction mentioning the main methods to recognize human posture including computer vision-based and wearable sensor-based. We approached these perspectives: sensor fusion, Datasets, approaches proposition. In conclusion, our survey summarizes the progress achieved in the five past years to help the researchers in this field to spot areas where further effort would be beneficial and innovative. © 2021 IEEE.

关键词： computer vision

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Training Adversarially Robust Sparse Networks via Bayesian Connectivity Sampling 38

Training Adversarially Robust Sparse Networks via Bayesian C...

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38th International Conference on Machine Learning, ICML 2021

作者： Özdenizci, Ozan Legenstein, Robert Graz University of Technology Institute of Theoretical Computer Science Graz Austria Silicon Austria Labs TU Graz - SAL Dependable Embedded Systems Lab Graz Austria

ISBN: (纸本)9781713845065

Deep neural networks have been shown to be susceptible to adversarial attacks. This lack of adversarial robustness is even more pronounced when models are compressed in order to meet hardware limitations. Hence, if adversarial robustness is an issue, training of sparsely connected networks necessitates considering adversarially robust sparse learning. Motivated by the efficient and stable computational function of the brain in the presence of a highly dynamic synaptic connectivity structure, we propose an intrinsically sparse rewiring approach to train neural networks with state-of-the-art robust learning objectives under high sparsity. Importantly, in contrast to previously proposed pruning techniques, our approach satisfies global connectivity constraints throughout robust optimization, i.e., it does not require dense pre-training followed by pruning. Based on a Bayesian posterior sampling principle, a network rewiring process simultaneously learns the sparse connectivity structure and the robustness-accuracy trade-off based on the adversarial learning objective. Although our networks are sparsely connected throughout the whole training process, our experimental benchmark evaluations show that their performance is superior to recently proposed robustness-aware network pruning methods which start from densely connected networks. Copyright © 2021 by the author(s)

关键词： Deep neural networks

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A GPU-accelerated particle filter with pixel-level likelihood

A GPU-accelerated particle filter with pixel-level likelihoo...

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13th International Fall Workshop Vision, Modeling, and Visualization 2008, VMV 2008

作者： Lenz, Claus Panin, Giorgio Knoll, Alois Robotics and Embedded Systems Lab. Computer Science Department Technische Universität München Boltzmannstrasse 3 85748 Garching bei München Germany

ISBN: (纸本)9781586039219

We present in this paper a GPU-accelerated particle filter based on pixel-level segmentation and matching, for real-time object tracking. The proposed method achieves real-time perfomance, while computing for each particle the corresponding filled model silhouette through the rendering engine of the graphics card, and comparing it with the underlying binary map of the segmentation preprocess. With the proposed approach, a better precision and generality is obtained with respect to related feature-level likelihoods such as color histograms, while keeping low computational requirements.

关键词： Graphics processing unit

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Secure bisimulation for interactive systems 15th

Secure bisimulation for interactive systems

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15th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2015

作者： Liu, Guanjun Jiang, Changjun Department of Computer Science Tongji University Shanghai201804 China Key Lab of the Ministry of Education for Embedded Systems and Services Computing Tongji University Shanghai201804 China

ISBN: (纸本)9783319271361

In real applications, many systems have the same functions but their securities are different due to different security policies. We find that different security policies can affect the interacting behavior of a system, which exactly is the reason why a good policy can strengthen the security. In other words, two interactive systems with different security policies are not of an equivalent behavior although their functions are identical. However, the classic (weak) bisimulation theory draws an opposite conclusion that their behaviors are equivalent. The notion of (weak) bisimulation is not suitable for these security-oriented interactive systems since it does not consider a security policy while the security policy can affect their interacting behaviors. This paper proposes the concept of secure bisimulation in order to solve the above problem. Based on secure bisimulation, we furthermore define a binary relation ≥SL to compare the levels of different security policies. We prove that ≥SL is a partial order but not a total one. © Springer International Publishing Switzerland 2015.

关键词： Petri nets

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A Multi-view Deep Convolutional Neural Network for Reduction of False Positive Findings in Breast Cancer Screening

A Multi-view Deep Convolutional Neural Network for Reduction...

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International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)

作者： Nouha Derbel Hedi Tmar Adel Mahfoudhi Computer & Embedded Systems Lab University of Sfax Sfax Tunisia

ISBN: (数字)9781728175133

ISBN: (纸本)9781728175140

Screening mammography is commonly the only imaging exam allowing early-stage detection of breast cancer. The early detection is, in fact, associated with a decreased breast cancer mortality rate amongst women. However, false positive recall is one of the main limitations of screening practices and it is often associated with unnecessary workups and biopsies. To tackle this issue and improve the medical image classification performance in order to carry out a screening/diagnosis task, we propose to use a multi-view deep convolutional neural network - the proposed network can extract discriminative features from Cranial Caudal (CC) and Medio-Lateral Oblique (MLO) views for each breast of a patient (a set of four images). We experiment it on an augmented-data based subset selected from the open Digital Database for Screening Mammography (DDSM) using 5400 images. We show how the proposed method can lead to a better performance than the state-of-the-art ones, especially in terms of prediction accuracy and false positive rate reduction. In fact, The results show statistically significant reduction in false findings without increasing false negative cases. Our method achieves a specificity rate of 98% and an accuracy rate of 98.88%. Index Terms-Mammography, Breast cancer diagnosis, False positive findings, Deep learning, Multi-view deep convolutional neural network.

关键词： Breast cancer Training Mammography Task analysis Biomedical imaging Biopsy Linear programming

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On transitioning from PID to ADRC in thermal power plants

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Control Theory and Technology 2021年第1期19卷 3-18页

作者： Zhenlong Wu Zhiqiang Gao Donghai Li YangQuan Chen Yanhong Liu School of Electrical Engineering Zhengzhou UniversityZhengzhou 450001HenanChina Department of Electrical and Computer Engineering Cleveland State UniversityClevelandOH 44115USA State Key Lab of Power Systems Department of Energy and Power EngineeringTsinghua UniversityBeijing 100084China Mechatronics Embedded Systems and Automation(MESA)LabDepartment of Mechanical EngineeringSchool of EngineeringUniversity of CaliforniaMercedCA 95343USA

This paper focuscs on the recent progress in the adoption of active disturbance rejection control(ADRC)in thermal pro-cesses as a viable alternative to proportional-_integral-derivative(PID),especially in coa-fired power *** profound interpretation of this paradigm shift,with backward compatibility,is discussed in detail.A few fundamental issues associated with ADRC's applications in thermal processes are discussed,such as implementation,tuning,and the structural *** and case studies are presented,encompassing coal-fired power plants,gas turbines and nuclear power plants,as well as highlighting results of field *** discussed are future research opportunities brought by ADRC's entry as the baseline control technology in thermal processes.

关键词： Active disturbance rejection control(ADRC) Proportional-integral-derivative(PID) Thermal processes Coal-fired power plant Field applications

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Deep learning based cyber bullying early detection using distributed denial of service flow

Deep learning based cyber bullying early detection using dis...

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作者： Zaib, Muhammad Hassan Bashir, Faisal Qureshi, Kashif Naseer Kausar, Sumaira Rizwan, Muhammad Jeon, Gwanggil Department of Computer Science Bahria University Islamabad Pakistan Lab Bahria University Islamabad Pakistan Department of Embedded Systems Engineering Incheon National University Incheon Korea Republic of

Cyber-bullying has been on the rise especially after the explosive widespread of various cyber-attacks. Various types of techniques have been used to tackle cyber-bullying. These techniques focused primarily on data traffic for monitoring malicious activities. This research proposes a methodology where we can detect early Denial of service (DoS) and Distributed Denial of Service (DDoS) attacks. First, we formulate the problem in a practical scenario by comparing flow and non-flow-based datasets using Mann Whitney U statistical test. Flow and non-flow-based datasets and Artificial Neural Network (ANN) and Support Vector Machine (SVM) is used for classification. To keep original features, we use variance, correlation, ½ quartile method to eliminate the unimportant features. The forward selection wrapper method for feature selection is used to find out the best features. To validate the proposed methodology, we take multiple DoS and DDoS single flow and validate it on 10%, 20%, 30%, 40%, and 50%. For validation, the experimental results show + 90% accuracy on the early 10% flow. © 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Network security

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Performance characterization of itanium®2-based montecito processor

Performance characterization of itanium®2-based montecito p...

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SPEC Benchmark Workshop 2009: computer Performance Evaluation and Benchmarking

作者： Desai, Darshan Hoflehner, Gerolf F. Kejariwal, Arun Lavery, Daniel M. Nicolau, Alexandru Veidenbaum, Alexander V. McNairy, Cameron Center for Embedded Computer Systems University of California Irvine CA 92697 United States Intel Compiler Lab Intel Corporation Santa Clara CA 95050 United States

This paper presents the performance characteristics of the Intel &reg2 Itanium&reg2 2-based Montecito processor and compares its performance to the previous generation Madison processor. Measurements on both a... 详细信息

ISBN: (纸本)3540937986

This paper presents the performance characteristics of the Intel ®2 Itanium®2 2-based Montecito processor and compares its performance to the previous generation Madison processor. Measurements on both are done using the industry-standard SPEC CPU2006 benchmarks. The benchmarks were compiled using the Intel Fortran/C++ optimizing compiler and run using the reference data sets. We analyze a large set of processor parameters such as cache misses, TLB misses, branch prediction, bus transactions, resource and data stalls and instruction frequencies. Montecito achieves 1.14 and 1.16 higher (geometric mean) IPC on integer and floating-point applications. We believe that the results and analysis presented in this paper can potentially guide future IA-64 compiler and architectural research. ©Springer-Verlag Berlin Heidelberg 2009.

关键词： Digital arithmetic

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SystemC simulation framework of protocol processing architectures for IPv6 routing

SystemC simulation framework of protocol processing architec...

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International Symposium on Signals, Circuits and systems (ISSCS)

作者： D. Truscan S. Virtanen J. Lilius Embedded Systems Lab Turku Centre for Computer Science Turku Finland

In this paper, we present our use of SystemC to simulate IPv6 router architecture on our TTA based protocol processor. Our approach makes it easy to verify the correct functionality and to identify performances bottlenecks in the architecture within a short time frame. All this is done prior to proceeding to synthesize the processor into hardware.

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