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arXiv 2022年

作者： Borras, Hendrik Klein, Bernhard Fröning, Holger Computing Systems Group Institute of Computer Engineering Heidelberg University Germany

Deep neural networks are extremely successful in various applications, however they exhibit high computational demands and energy consumption. This is exacerbated by stuttering technology scaling, prompting the need for novel approaches to handle increasingly complex neural architectures. At the same time, alternative computing technologies such as analog computing, which promise groundbreaking improvements in energy efficiency, are inevitably fraught with noise and inaccurate calculations. Such noisy computations are more energy efficient, and, given a fixed power budget, also more time efficient. However, like any kind of unsafe optimization, they require countermeasures to ensure functionally correct results. This work considers noisy computations in an abstract form, and gears to understand the implications of such noise on the accuracy of neural network classifiers as an exemplary workload. We propose a methodology called Walking Noise which injects layer-specific noise to measure the robustness and to provide insights on the learning dynamics. In more detail, we investigate the implications of additive, multiplicative and mixed noise for different classification tasks and model architectures. While noisy training significantly increases robustness for all noise types, we observe in particular that it results in increased weight magnitudes and thus inherently improves the signal-to-noise ratio for additive noise injection. Contrarily, training with multiplicative noise can lead to a form of self-binarization of the model parameters, leading to extreme robustness. We conclude with a discussion of the use of this methodology in practice, among others, discussing its use for tailored multi-execution in noisy environments. Copyright © 2022, The Authors. All rights reserved.

关键词： Energy efficiency

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Geometric Parameterized Macromodel of Uniaxial Capacitance Accelerometer Based on Modal Superposition 16

Geometric Parameterized Macromodel of Uniaxial Capacitance A...

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16th IEEE International Scientific and Technical Conference Actual Problems of Electronic Instrument engineering, APEIE 2023

作者： Gridchin, Aleksandr V. Koleda, Aleksei N. Barbin, Evgenii S. Nesterenko, Tamara G. Kolchuzhin, Vladimir A. Department of Semiconductor Devices and Microelectronics Novosibirsk State Technical University Novosibirsk Russia Department of Electronic Engineering National Research Tomsk Polytechnic University Tomsk Russia Laboratory of Intelligent Computer Systems Tomsk State University of Control Systems and Radioelectronics Tomsk Russia Advanced Cellular Group Qorvo Munich GmbH Munich Germany

ISBN: (纸本)9798350330885

The paper presents a piecewise geometric parameterization method and a parametric analysis of uniaxial capacitance accelerometer using a reduced model formulated on the modal superposition method. The extraction of parameters for the macromodel such as modal frequencies, modal masses, modal stiffnesses, strain energy, and capacitances are described. The reduced model consists of the two modes: torsion mode, and transversal mode, three electrodes in the electrostatic domain, and eight master nodes in the geometrical domain located at the edges of the plate. The generation of the discrete macromodels is executed using commercial software. The thickness of the plate has been selected as a design parameter. Linear piecewise interpolation is used for macromodel parameterization which have been done inside VHDL-AMS code. The accelerometer's dynamic response simulated using of parametrized macromodel considering the mechanical contact phenomena and the nonlinear electrostatic interaction are presented and discussed. The developed approach can be applied for fast system level simulations in view of the variation of the geometric parameters. © 2023 IEEE.

关键词： Capacitance

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Security-centric ranking algorithm and two privacy scores to mitigate intrusive apps

Security-centric ranking algorithm and two privacy scores to...

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作者： Mohsen, Fadi Abdelhaq, Hamed Bisgin, Halil Information Systems Group Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence University of Groningen Groningen Netherlands Computer Science Apprenticeship An-Najah National University Nablus Palestine Computer Science Engineering and Physics University of Michigan-Flint FlintMI United States

Smartphone users are constantly facing the risks of losing their private information to third-party mobile applications. Studies have revealed that the vast majority of users either do not pay attention to privacy or unable to comprehend privacy messages. Developers though have exploited this fact by asking users to grant their apps an enormous number of permissions. In this article, we propose and evaluate a new security-centric ranking algorithm built on top of the Elasticsearch engine to help users evade such apps. The algorithm calculates an intrusiveness score for an app based on its requested permissions, received system actions, and users' privacy preferences. As such, we further propose a new approach to capture these preferences. We evaluate the ranking algorithm using a million Android applications, contextual data and APK files, that we collect from the Google Play store. The results show that the scoring and reranking steps add minor overhead. Moreover, participants of the user studies gave positive feedback for the ranking algorithm and the privacy preferences solicitation approach. These results suggest that our proposed system would definitely protect the privacy of mobile users and pushes developers into requesting least amount of privileges. Still, there are many risks that endanger the users' privacy. © 2021 The Authors. Concurrency and Computation: Practice and Experience published by John Wiley & Sons Ltd.

关键词： Android (operating system)

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Robotic fish:Opening a new era of underwater detection

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The Innovation 2025年第3期6卷 13-14页

作者： Dongfang Li Suet To Zhicheng Xu Guanghong Liu Rob Law Edmond Q.Wu Limin Zhu State Key Laboratory of Ultraprecision Machining Technology Department of Industrial and Systems EngineeringThe Hong Kong Polytechnic UniversityHong Kong 999077China School of Electrical Engineering and Automation Fuzhou UniversityFujian 350108China China Electronics Technology Group Corporation Information Science Research InstituteBeijing 100086China School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China Asia-Pacific Academy of Economics and Management Faculty of Business AdministrationUniversity of MacaoMacao 999078China Department of Computer Science and Engineering Shanghai JiaoTong UniversityShanghai 200240China

Escalating competition within aquatic environments,particularly in oceans,underscores the imperative for innovative solutions in underwater *** solutions necessitate the development of intelligent underwater equipment,with robotic fish emerging as a promising contender.1 Leveraging advancements in robotics and artificial intelligence,robotic fish offer a suite of advantages that position them as transformative assets in underwater exploration and *** fish are autonomous robots designed based on biomimetics principles that mimic the appearance of fish and can autonomously swim and perform specific tasks in water.

关键词： robotic fish intelligent underwater equipmentwith autonomous robots underwater detection oceans artificial intelligencerobotic fish aquatic environments innovative solutions

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Generic and scalable multi-layered architecture for Digital Twin implementation in industrial processes: Mineral Processing case study 23

Generic and scalable multi-layered architecture for Digital ...

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Proceedings of the 2023 7th International Conference on Advances in Artificial Intelligence

作者： Oussama Hasidi El Hassan Abdelwahed Aimad Qazdar Moulay Abdellah El Alaoui-Chrifi Intissar Benzakour Rachida Chahid Ahmed Bendaouia François Bourzeix Computer Science Departement Computer Systems Engineering Laboratory Cadi Ayyad University Morocco and Analytics Lab Mohammed VI Polytechnic University Morocco Computer Science Departement Computer Systems Engineering Laboratory Cadi Ayyad University Morocco ESTIDMA Laboratory Ibn Zohr University Morocco R&D and Engineering center Reminex Managem Group Morocco Computer Science Departement Computer Systems Engineering Laboratory Cadi Ayyad University Morocco and SEIA Departement MAScIR Morocco Analytics Lab Mohammed VI Polytechnic University Morocco

ISBN: (纸本)9798400708985

Digitalization is crucial for achieving product quality, cost reduction, and timely delivery in manufacturing. With the rise of Industry 4.0, Digital Twin technology has gained popularity, enabling real-time monitoring, predictive maintenance, process optimization, and assumption testing. Manufacturing Digital Twins utilize digital models to represent physical processes, facilitating continuous simulation, interaction, correction, and optimization for autonomous control. However, implementing Digital Twins can be challenging due to diverse data requirements and multiple services. This paper proposes a scalable, service-oriented multi-layered architecture for developing Digital Twins in mineral processing, which can be adapted to other manufacturing systems. The paper provides an overview of Digital Twins, their data-centric workflow, and industrial applications. Additionally, a case study on implementing a Digital Twin for the froth flotation process in the mining industry is presented based on the proposed architecture.

关键词： Digital Twin Implementation Industry 4.0 Multi-layered Architecture Optimisation Predictive model Real time control and monitoring

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A Novel Hybrid Clustering Based Transmission Protocol for Wireless Body Area Networks

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computers, Materials & Continua 2021年第11期69卷 2459-2473页

作者： Neelam Sharma Harshita Chadha Karan Singh B.M.Singh Nitish Pathak Research Scholar Computer Science and EngineeringUttarakhand Technical University(UTU)DehradunIndia Computer Science and Engineering Maharaja Agrasen Institute of TechnologyNew DelhiIndia School of Computer&Systems Sciences Jawaharlal Nehru University(JNU)DelhiIndia College of Engineering Roorkee UTUDehradunIndia Department of Information Technology KIET Group of InstitutionsGhaziabadIndia

Wireless sensor networks are a collection of intelligent sensor devices that are connected to one another and have the capability to exchange information packets amongst *** recent years,this field of research has become increasingly popular due to the host of useful applications it can potentially serve.A deep analysis of the concepts associated with this domain reveals that the two main problems that are to be tackled here are throughput enhancement and network security *** present article takes on one of these two issues namely the throughput *** the purpose of improving network productivity,a hybrid clustering based packet propagation protocol has been *** protocol makes use of not only clustering mechanisms of machine learning but also utilizes the traditional forwarding function approach to arrive at an optimum *** result of the simulation is a novel transmission protocol which significantly enhances network productivity and increases throughput value.

关键词： Forwarding function wireless sensor networks WSNs WBANs energy characteristics clustering hybrid mechanism dissipated energy network stability

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Optimization Techniques in University Timetabling Problem:Constraints,Methodologies,Benchmarks,and Open Issues

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computers, Materials & Continua 2023年第3期74卷 6461-6484页

作者： Abeer Bashab Ashraf Osman Ibrahim Ibrahim Abakar Tarigo Hashem Karan Aggarwal Fadhil Mukhlif Fuad A.Ghaleb Abdelzahir Abdelmaboud Faculty of Computer Science&Information Technology Alzaiem Alazhari University13311KhartoumSudan Faculty Computing and Informatics Universiti Malaysia SabahKota Kinabalu88400SabahMalaysia Department of Computer Science University of SharjahSharjah27272United Arab Emirates Electronic and Communication Engineering Department Maharishi Markandeshwar Deemed to be UniversityMullanaAmbala133207HaryanaIndia Information Assurance and Security Research Group(IASRG) School of ComputingFaculty of EngineeringUniversiti Teknologi Malaysia81310JohorMalaysia Department of Information Systems King Khaled UniversityMuhayel61913AseerSaudi Arabia

University timetabling problems are a yearly challenging task and are faced repeatedly each *** problems are considered nonpolynomial time(NP)and combinatorial optimization problems(COP),which means that they can be solved through optimization algorithms to produce the aspired optimal *** techniques have been used to solve university timetabling problems,and most of them use optimization *** paper provides a comprehensive review of the most recent studies dealing with concepts,methodologies,optimization,benchmarks,and open issues of university timetabling *** comprehensive review starts by presenting the essence of university timetabling as NP-COP,defining and clarifying the two formed classes of university timetabling:University Course Timetabling and University Examination Timetabling,illustrating the adopted algorithms for solving such a problem,elaborating the university timetabling constraints to be considered achieving the optimal timetable,and explaining how to analyze and measure the performance of the optimization algorithms by demonstrating the commonly used benchmark datasets for the *** is noted that meta-heuristic methodologies are widely used in the ***,recently,multi-objective optimization has been increasingly used in solving such a problem that can identify robust university timetabling ***,trends and future directions in university timetabling problems are *** paper provides good information for students,researchers,and specialists interested in this area of *** challenges and possibilities for future research prospects are also explored.

关键词： University timetabling timetabling approaches meta-heuristics combinatorial optimization

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BitMoD: Bit-serial Mixture-of-Datatype LLM Acceleration

arXiv

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arXiv 2024年

作者： Chen, Yuzong AbouElhamayed, Ahmed F. Dai, Xilai Wang, Yang Andronic, Marta Constantinides, George A. Abdelfattah, Mohamed S. Computer Systems Lab Cornell University United States Systems and Networking Research Group Microsoft Research United States Department of Electrical and Electronic Engineering Imperial College London United Kingdom

Large language models (LLMs) have demonstrated remarkable performance across various machine learning tasks. Yet the substantial memory footprint of LLMs significantly hinders their deployment. In this paper, we improve the accessibility of LLMs through BitMoD1, an algorithm-hardware co-design solution that enables efficient LLM acceleration at low weight precision. On the algorithm side, BitMoD introduces fine-grained data type adaptation that uses a different numerical data type to quantize a group of (e.g., 128) weights. Through the careful design of these new data types, BitMoD is able to quantize LLM weights to very low precision (e.g., 4 bits and 3 bits) while maintaining high accuracy. On the hardware side, BitMoD employs a bit-serial processing element to easily support multiple numerical precisions and data types;our hardware design includes two key innovations: First, it employs a unified representation to process different weight data types, thus reducing the hardware cost. Second, it adopts a bit-serial dequantization unit to rescale the per-group partial sum with minimal hardware overhead. Our evaluation on six representative LLMs demonstrates that BitMoD significantly outperforms state-of-the-art LLM quantization and acceleration methods. For discriminative tasks, BitMoD can quantize LLM weights to 4-bit with © 2024, CC BY-NC-ND.

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Towards adaptive trajectories for mixed autonomous and human-operated ships

arXiv

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arXiv 2024年

作者： Pianini, Danilo Tomforde, Sven Department of Computer Science and Engineering Alma Mater Studiorum Università di Bologna Cesena Italy Intelligent Systems Group Kiel University Kiel Germany

We are witnessing the rise of autonomous cars, which will likely revolutionize the way we travel. Arguably, the maritime domain lags behind, as ships operate on many more degrees of freedom (thus, a much larger search space): there is less physical infrastructure, and rules are less consistent and constraining than what is found on roads. The problem is further complicated by the inevitable co-existence of autonomous and human-operated ships: the latter may take unpredictable decisions, which require adjustments on the autonomous ones. Finally, the problem is inherently decentralised, there is no central authority, and communication means can be very diverse in terms of communication distance and performance, mandating special care on which information is shared and how. In this work, we elaborate on the challenges of trajectory prediction and adaptation for mixed autonomous and human-operated ships, and we propose initial ideas on potential approaches to address them. Copyright © 2024, The Authors. All rights reserved.

关键词： Decentralized control

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Towards Threat Modelling of IoT Context-Sharing Platforms

arXiv

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arXiv 2024年

作者： Goudarzi, Mohammad Shaghaghi, Arash Finn, Simon Stiller, Burkhard Jha, Sanjay School of Computer Science and Engineering UNSW Sydney Australia Australia Communication Systems Group Department of Informatics University of Zurich Switzerland Cisco United States

The Internet of Things (IoT) involves complex, interconnected systems and devices that depend on context-sharing platforms for interoperability and information exchange. These platforms are, therefore, critical components of real-world IoT deployments, making their security essential to ensure the resilience and reliability of these "systems of systems." In this paper, we take the first steps toward systematically and comprehensively addressing the security of IoT context-sharing platforms. We propose a framework for threat modelling and security analysis of a generic IoT context-sharing solution, employing the MITRE ATT&CK framework. Through an evaluation of various industry-funded projects and academic research, we identify significant security challenges in the design of IoT context-sharing platforms. Our threat modelling provides an in-depth analysis of the techniques and sub-techniques adversaries may use to exploit these systems, offering valuable insights for future research aimed at developing resilient solutions. Additionally, we have developed an open-source threat analysis tool that incorporates our detailed threat modelling, which can be used to evaluate and enhance the security of existing context-sharing platforms. Copyright © 2024, The Authors. All rights reserved.

关键词： Cloud platforms

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