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Enhancing Anxiety Prediction: Leveraging Machine Learning with Functional Design Metrics

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Enhancing Anxiety Prediction: Leveraging Machine Learning wi...

International Conference on Electrical engineering, Computing science and Automatic Control (CCE)

作者： Abqa Javed Sahar Ajmal Taliah Tajammal Muhammad Aslam Martinez-Enriquez A. M. Usman Sadiq Sheikh Department of Computer Science University of Engineering and Technology Lahore Pakistan Department of Software Engineering National University of Computer and Emerging Sciences Pakistan Department of Computer Science and Information Technology Virtual University of Pakistan Lahore Pakistan Department of Computer Science CINVESTAV-IPN D.F. Mexico Clinical Fellow in Respiratory Medicine Bronglais General Hospital UK

ISBN: (数字)9798350377545

ISBN: (纸本)9798350377552

关键词： Measurement Training Accuracy Systematics ISO Standards Anxiety disorders Machine learning Throughput Standards Resilience

6G Wireless Communications: From Far-field Beam Steering to Near-field Beam Focusing

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arXiv 2022年

作者： Zhang, Haiyang Shlezinger, Nir Guidi, Francesco Dardari, Davide Eldar, Yonina C. The School of Communication and Information Engineering Nanjing University of Posts and Telecommunications China The School of Electrical and Computer Engineering Ben-Gurion University Israel Electronics Telecommunications and Information Technologies from Ecole Polytechnique Paris-Tech France Computer Science Specialty The University of Bologna Italy IEIIT-CNR Italy The University of Bologna WiLAB-CNIT Italy The Department of Math and Computer Science Weizmann Institute of Science Israel The Center for Biomedical Engineering and Signal Processing The Israel Academy of Sciences and Humanities IEEE Fellow EURASIP Fellow

6G networks will be required to support higher data rates, improved energy efficiency, lower latency, and more diverse users compared with 5G systems. To meet these requirements, electrically extremely large-scale antenna arrays are envisioned to be key physical-layer technologies. As a consequence, it is expected that some portion of future 6G wireless communications may take place in the radiating near-field (Fresnel) region, in addition to the far-field operation as in current wireless technologies. In this article, we discuss the opportunities and challenges that arise in radiating near-field communications. We begin by discussing the key physical characteristics of near-field communications, where the standard plane-wave propagation assumption no longer holds, and clarifying its implication on the modelling of wireless channels. Then, we elaborate on the ability to leverage spherical wavefronts via beam focusing, highlighting its advantages for 6G systems. We point out several appealing application scenarios which, with proper design, can benefit from near-field operation, including interference mitigation in multi-user communications, accurate localization and focused sensing, as well as wireless power transfer with minimal energy pollution. We conclude by discussing some of the design challenges and research directions that are yet to be explored to fully harness the potential of near-field operation. Copyright © 2022, The Authors. All rights reserved.

关键词： Antenna arrays

Quantum Linear System Solvers: A Survey of Algorithms and Applications

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arXiv 2024年

作者： Morales, Mauro E.S. Pira, Lirandë Schleich, Philipp Koor, Kelvin Costa, Pedro C.S. An, Dong Aspuru-Guzik, Alán Lin, Lin Rebentrost, Patrick Berry, Dominic W. Joint Center for Quantum Information and Computer Science University of Maryland United States Centre for Quantum Software and Information University of Technology Sydney Australia Centre for Quantum Technologies National University of Singapore Singapore Department of Computer Science University of Toronto Canada Vector Institute for Artificial Intelligence Toronto Canada ContinoQuantum Sydney Australia Beijing International Center for Mathematical Research Peking University Beijing China Department of Chemistry University of Toronto Canada Canadian Institute for Advanced Research Toronto Canada Acceleration Consortium Toronto Canada Department of Chemical Engineering & Applied Chemistry University of Toronto Toronto Canada Department of Materials Science & Engineering University of Toronto Toronto Canada Lebovic Fellow Canadian Institute for Advanced Research Toronto Canada Department of Mathematics University of California Berkeley United States Applied Mathematics and Computational Research Division Lawrence Berkeley National Laboratory Berkeley United States Department of Computer Science National University of Singapore Singapore School of Mathematical and Physical Sciences Macquarie University Sydney Australia

Solving linear systems of equations plays a fundamental role in numerous computational problems from different fields of science. The widespread use of numerical methods to solve these systems motivates investigating the feasibility of solving linear systems problems using quantum computers. In this work, we provide a survey of the main advances in quantum linear systems algorithms, together with some applications. We summarize and analyze the main ideas behind some of the algorithms for the quantum linear systems problem in the literature. The analysis begins by examining the Harrow-Hassidim-Lloyd (HHL) solver. We note its limitations and reliance on computationally expensive quantum methods, then highlight subsequent research efforts which aimed to address these limitations and optimize runtime efficiency and precision via various paradigms. We focus in particular on the post-HHL enhancements which have paved the way towards optimal lower bounds with respect to error tolerance and condition number. By doing so, we propose a taxonomy that categorizes these studies. Furthermore, by contextualizing these developments within the broader landscape of quantum computing, we explore the foundational work that have inspired and informed their development, as well as subsequent refinements. Finally, we discuss the potential applications of these algorithms in differential equations, quantum machine learning, and many-body physics. © 2024, CC BY.

关键词： Quantum computers

White-Box evaluation of fingerprint recognition systems

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arXiv 2020年

作者： Grosz, Steven A. Engelsma, Joshua J. Jain, Anil K. Life Fellow IEEE United States Department of Computer Science and Engineering Michigan State University East LansingMI48824 United States

Typical evaluations of fingerprint recognition systems consist of end-to-end black-box evaluations, which assess performance in terms of overall identification or authentication accuracy. However, these black-box tests of system performance do not reveal insights into the performance of the individual modules, including image acquisition, feature extraction, and matching. On the other hand, white-box evaluations, the topic of this paper, measure the individual performance of each constituent module in isolation. While a few studies have conducted white-box evaluations of the fingerprint reader, feature extractor, and matching components, no existing study has provided a full system, white-box analysis of the uncertainty introduced at each stage of a fingerprint recognition system. In this work, we extend previous white-box evaluations of fingerprint recognition system components and provide a unified, in-depth analysis of fingerprint recognition system performance based on the aggregated white-box evaluation results. In particular, we analyze the uncertainty introduced at each stage of the fingerprint recognition system due to adverse capture conditions (i.e., varying illumination, moisture, and pressure) at the time of acquisition. Our experiments show that a system that performs better overall, in terms of black-box recognition performance, does not necessarily perform best at each module in the fingerprint recognition system pipeline, which can only be seen with white-box analysis of each sub-module. Findings such as these enable researchers to better focus their efforts in improving fingerprint recognition systems. Copyright © 2020, The Authors. All rights reserved.

关键词： Uncertainty analysis

Invariance Principles and Observability in Switched Systems with an Application in Consensus

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arXiv 2020年

作者： Lee, Ti-Chung Tan, Ying Su, Youfeng Mareels, Iven IEEE IEEE Fellow IEEE Department of Electrical Engineering Minghsin University of Science and Technology Hsin-Hsing Road Hsin-Fong Hsinchu Taiwan Department of Electrical and Electronic Engineering University of Melbourne VIC3010 Australia College of Mathematics and Computer Science Fuzhou University Fuzhou350116 China IBM Research Australia 60 City Road South BankVIC3006 Australia

Using any nonnegative function with a nonpositive derivative along trajectories to define a virtual output, the classic LaSalle invariance principle can be extended to switched nonlinear time-varying (NLTV) systems, by considering the weak observability (WO) associated with this output. WO is what the output informs about the limiting behavior of state trajectories (hidden in the zero locus of the output). In the context of switched NLTV systems, WO can be explored using the recently established framework of limiting zeroing-output solutions. Adding to this, an extension of the integral invariance principle for switched NLTV systems with a new method to guarantee uniform global attractivity of a closed set (without assuming uniform Lyapunov stability or dwell-time conditions) is proposed. By way of illustrating the proposed method, a leaderless consensus problem for nonholonomic mobile robots with a switching communication topology is addressed, yielding a new control strategy and a new convergence result. Copyright © 2020, The Authors. All rights reserved.

关键词： Observability

An Efficient Robust Lightweight Remote User Authentication Protocol using Extended Chaotic Maps

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An Efficient Robust Lightweight Remote User Authentication P...

International Conference on computer, Information and Telecommunication Systems (CITS)

作者： Chandrashekhar Meshram Mohammad S. Obaidat Akshaykumar Meshram Deppartment of Post Graduation Studies and Research in Mathematics Jayawanti Haksar Government Post Graduation College College of Chhindwara University Betul M.P. India Fellow of IEEE and Fellow of SCS College of Computing and Informatics University of Sharjah UAE King Abdullah II School of Information Technology The University of Jordan Jordan University of Science and Technology Bejing Bejing China Department of Applied Mathematics Yeshwantrao Chavan College of Engineering Nagpur M.S. India

ISBN: (数字)9781728165448

ISBN: (纸本)9781728165455

Rapid development in networking and mobile technology has resulted in new networking hypotheses such as the Internet of Things, enabling clients to link via different devices to an unsafe public communication channel and access remote server services and data. Remote user authentication process and key agreement process for wireless, and IoT communications therefore have become more challenging. In the present study, we propose an efficient robust lightweight remote user authentication protocol using extended chaotic maps. The presented protocol is secure against various attacks.

关键词： Authentication Protocols Chaotic communication Servers Smart cards Password Cryptography

G-softmax: Improving Intra-class Compactness and Inter-class Separability of Features

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arXiv 2019年

作者： Luo, Yan Wong, Yongkang Kankanhalli, Mohan Zhao, Qi IEEE Fellow IEEE Department of Computer Science and Engineering University of Minnesota MinneapolisMN55455 United States School of Computing National University of Singapore Singapore117417 Singapore

Intra-class compactness and inter-class separability are crucial indicators to measure the effectiveness of a model to produce discriminative features, where intra-class compactness indicates how close the features with the same label are to each other and inter-class separability indicates how far away the features with different labels are. In this work, we investigate intra-class compactness and inter-class separability of features learned by convolutional networks and propose a Gaussian-based softmax (G-softmax) function that can effectively improve intra-class compactness and inter-class separability. The proposed function is simple to implement and can easily replace the softmax function. We evaluate the proposed G-softmax function on classification datasets (i.e., CIFAR-10, CIFAR-100, and Tiny ImageNet) and on multi-label classification datasets (i.e., MS COCO and NUS-WIDE). The experimental results show that the proposed G-softmax function improves the state-of-the-art models across all evaluated datasets. In addition, analysis of the intra-class compactness and inter-class separability demonstrates the advantages of the proposed function over the softmax function, which is consistent with the performance improvement. More importantly, we observe that high intra-class compactness and inter-class separability are linearly correlated to average precision on MS COCO and NUS-WIDE. This implies that improvement of intra-class compactness and inter-class separability would lead to improvement of average precision. Copyright © 2019, The Authors. All rights reserved.

关键词： Classification (of information)

Self-Awareness for Autonomous Systems

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PROCEEDINGS OF THE ieee 2020年第7期108卷 971-975页

作者： Dutt, Nikil Regazzoni, Carlo S. Rinner, Bernhard Yao, Xin Nikil Dutt (Fellow IEEE) received the Ph.D. degree from the University of Illinois at Urbana–Champaign Champaign IL USA in 1989.""He is currently a Distinguished Professor of computer science (CS) cognitive sciences and electrical engineering and computer sciences (EECS) with the University of California at Irvine Irvine CA USA. He is a coauthor of seven books. His research interests include embedded systems electronic design automation (EDA) computer architecture distributed systems healthcare Internet of Things (IoT) and brain-inspired architectures and computing.""Dr. Dutt is a Fellow of ACM. He was a recipient of the IFIP Silver Core Award. He has received numerous best paper awards. He serves as the Steering Committee Chair of the IEEE/ACM Embedded Systems Week (ESWEEK). He is also on the steering organizing and program committees of several premier EDA and embedded system design conferences and workshops. He has served on the Editorial Boards for the IEEE Transactions on Very Large Scale Integration (VLSI) Systems and the ACM Transactions on Embedded Computing Systems and also previously served as the Editor-in-Chief (EiC) for the ACM Transactions on Design Automation of Electronic Systems. He served on the Advisory Boards of the IEEE Embedded Systems Letters the ACM Special Interest Group on Embedded Systems the ACM Special Interest Group on Design Automationt and the ACM Transactions on Embedded Computing Systems. Carlo S. Regazzoni (Senior Member IEEE) received the M.S. and Ph.D. degrees in electronic and telecommunications engineering from the University of Genoa Genoa Italy in 1987 and 1992 respectively.""He is currently a Full Professor of cognitive telecommunications systems with the Department of Electrical Electronics and Telecommunication Engineering and Naval Architecture (DITEN) University of Genoa and a Co-Ordinator of the Joint Doctorate on Interactive and Cognitive Environments (JDICE) international Ph.D. course started initially as EU Erasmus Mundus Project and

Autonomous systems are able to make decisions and potentially take actions without direct human intervention, which requires some knowledge about the system and its environment as well as goal-oriented reasoning. In computer systems, one can derive such behavior from the concept of a rational agent with autonomy (“control over its own actions”), reactivity (“react to events from the environment”), proactivity (“act on its own initiative”), and sociality (“interact with other agents”) as fundamental properties \n[1]\n. Autonomous systems will undoubtedly pervade into our everyday lives, and we will find them in a variety of domains and applications including robotics, transportation, health care, communications, and entertainment to name a few. \nThe articles in this month’s special issue cover concepts and fundamentals, architectures and techniques, and applications and case studies in the exciting area of self-awareness in autonomous systems.

关键词： Special issues and sections Autonomous systems Self-aware Robot sensing systems Computational modeling

Energy efficient system architecture for wireless wearable biomedical sensors

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Energy efficient system architecture for wireless wearable b...

Custom Integrated Circuits Conference (CICC)

作者： Yong Lian IEEE and Fellow of Academy of Engineering Singapore Department of Electrical Engineering and Computer Science Lassonde School of Engineering York University President-Elect IEEE Circuits and Systems Society Member IEEE Fellow Committee

Wearable biomedical sensors are necessary for future healthcare. Novel ultra low power system architecture is a must for zero-powered devices. Innovations in energy harvesting is the key to success. Flexible circuit a... 详细信息

关键词： Wireless sensor networks Wireless communication Biosensors Energy efficiency Systems architecture Electrical engineering computer science