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TAPEMAN: Towards an Optimal Data Gathering Mechanism in Wireless Sensor Networks

Chinese Journal of Electronics 2023年第4期19卷 594-598页

作者： Yu Gu Yusheng Ji Hongyang Chen Baohua Zhao Department of Computer Science University of Science and Technology of China Hefei China State Key Laboratory of Networking and Switching Technology Beijing China Information Systems Architecture Science Research Division NII Tokyo Japan Institute of Industrial Science University of Tokyo Tokyo Japan

In this paper, we study the lifetime optimization problem using a mobile sink node in a storage-constrained wireless sensor network, and propose an optimal data gathering mechanism named (TAPEMAN) which runs in three steps: first a tight upper bound of the network lifetime is derived through analysis of energy consumption, then we generate a Traveling salesman problem (TSP) solution based on a 2-approximation $O(n^{2})$ algorithm. A judgment will be made about whether this solution is optimal. If the answer is yes, TAPEMAN terminates. If not, a novel data diffusion scheme is used to distribute data to neighboring nodes, in order to avoid data leaking. We prove that under some reasonable assumptions, our algorithm can achieve this upperbound. Simulation results demonstrate the efficiency of our proposed solution and substantiate the importance of using sink mobility for energy-constrained sensor networks.

关键词： Wireless communication Wireless sensor networks Energy consumption Upper bound Simulation Traveling salesman problems Delays

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Using Mobile Sinks in WSN: Computational Complexity and a Theoretical Bound

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Chinese Journal of Electronics 2023年第1期20卷 147-150页

In this paper, we study the lifetime optimization problem in wireless sensor networks using mobile sink nodes. This problem is inherently difficult since we need to consider both sink scheduling and data routing. Through a simple case study we develop a novel notation named the Placement pattern (PP) to bound traffic patterns with candidate locations. This significantly decreases the number of elements needed to be scheduled. Based on the PP, we mathematically formulate this optimization problem as a Mixed-integer non-linear programming (MINLP), which is very tough and time consuming to solve. By proving that the problem is NP-complete, we point out that instead of seeking an optimal algorithm, heuristic algorithms, especially those with performance guarantee, would be much more desirable to develop. Furthermore, in order to help identify performance gains of heuristic algorithms proposed in the future, we develop a Linear programming (LP) formulation which serves as an upper bound by adopting a reformulation and relaxation technique.

关键词： Wireless sensor networks Upper bound Heuristic algorithms Traffic control Programming Performance gain Routing

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Sex Difference in Atrial Fibrillation Recurrence After Catheter Ablation

Sex Difference in Atrial Fibrillation Recurrence After Cathe...

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International Conference on Awareness science and technology (iCAST)

作者： Xue Zhou Xin Zhu Tianhui Li Keijiro Nakamura Ming Huang Division of Information Systems University of Aizu Aizu-Wakamatsu Japan Division of Cardiovascular Medicine Toho University Ohashi Medical Center Tokyo Japan Graduate School of Science and Technology Nara Institute of Science and Technology Ikoma Japan

Atrial fibrillation (AF) is a common sustained arrhythmia associated with increased risks of cardiovascular and renal diseases and adverse clinical outcomes, including mortality. Catheter ablation is an established method to restore sinus rhythm, but AF recurrence remains high. The impact of sex differences on recurrence after catheter ablation is poorly understood. This study investigated sex differences in AF recurrence using a propensity score matched cohort. A multiple imputation method, "Generates Multivariate Imputations by Chained Equations," addressed missing variables. Univariate Cox proportional hazards regression analysis identified variables significantly associated with AF recurrence (p < 0.05). Propensity score matching created a matched cohort with sex as the dependent variable and significant variables as independent variables. The study included 507 AF patients (143 females, 364 males), with 147 experiencing AF recurrence. Recurrence rates did not significantly differ between females and males (33.6% vs. 27.2%, p = 0.189). After 1:1 matching, 232 patients (116 females, 116 males) were included. AF recurrence was higher in females than males (33.6% vs. 12.9%, p < 0.001). The recurrence-free curves of females and males differed significantly (p < 0.001). Females had a higher risk of AF recurrence than males (hazard ratio: 2.70, 95% confidence interval: 1.49-4.90, p = 0.001).This study highlights the importance of considering sex disparities in AF management and treatment strategies to improve patient outcomes and personalize care.

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Shield-U: Safeguarding Traffic Sign Recognition Against Perturbation Attacks 23

Shield-U: Safeguarding Traffic Sign Recognition Against Pert...

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23rd IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2024

作者： Xu, Shengmin Sun, Jianfei Cao, Hangcheng Gao, Yulan He, Ziyang Wu, Cong Fujian Normal University College of Computer and Cyber Security China Singapore Management University School of Computing and Information Systems Singapore City University of Hong Kong Department of Computer Science Hong Kong Kth Royal Institute of Technology Division of Information Science and Engineering Sweden Zhengzhou University School of Cyber Science and Engineering China Nanyang Technological University School of Computer Science and Engineering Singapore

Traffic sign recognition systems are crucial for the navigation and situation awareness of autonomous vehicles. They leverage deep learning technologies to swiftly and accurately identify traffic signs, even in the most challenging traffic environments. However, security researchers have uncovered a critical vulnerability in these systems: learning-based TSRs are particularly susceptible to physical-world perturbation attacks. Through subtle modifications (i.e., attaching well-designed patches on traffic signs), attackers can deceive the recognition system into making erroneous judgments, which can further lead to serious traffic accidents. Although several defense mechanisms have been proposed to enhance the security of sign recognition systems, these solutions generally target only specific types of malicious perturbations and thus lack robustness. To address this issue, we present a robust defense mechanism named Shield-U, which restores traffic sign images contaminated by physical patch perturbations, providing credible data for the recognition model. In the process of implementing Shield-U, we first design a feature difference-aware perturbation generator that outputs potential sign contamination patterns. Incorporating generated perturbations during the training phase enables our restoration model to gain sufficient understanding of diverse perturbation types, thus enhancing its ability to repair various perturbed signs. Following this, we build an attention-driven restoration network to repair sign images. Finally, we evaluate the effectiveness of Shield-U using widely used sign recognition models and public datasets. The results demonstrate that our defense mechanism excels in resisting potential perturbations, increasing the average sign recognition accuracy by 50.4%. © 2024 IEEE.

关键词： defense mechanism perturbation attack public transportation safety Traffic sign recognition

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Efficient Coordination and Synchronization of Multi-Robot systems Under Recurring Linear Temporal Logic

arXiv

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arXiv 2025年

作者： Peron, Davide Fernandez-Ayala, Victor Nan Vlahakis, Eleftherios E. Dimarogonas, Dimos V. Department of Information Engineering University of Padova Padova35122 Italy Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm10044 Sweden

We consider multi-robot systems under recurring tasks formalized as linear temporal logic (LTL) specifications. To solve the planning problem efficiently, we propose a bottom-up approach combining offline plan synthesis with online coordination, dynamically adjusting plans via real-time communication. To address action delays, we introduce a synchronization mechanism ensuring coordinated task execution, leading to a multi-agent coordination and synchronization framework that is adaptable to a wide range of multi-robot applications. The software package is developed in Python and ROS2 for broad deployment. We validate our findings through lab experiments involving nine robots showing enhanced adaptability compared to previous methods. Additionally, we conduct simulations with up to ninety agents to demonstrate the reduced computational complexity and the scalability features of our work. © 2025, CC BY.

关键词： Multipurpose robots

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Optimized Precoding for MU-MIMO With Fronthaul Quantization

arXiv

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arXiv 2022年

作者： Khorsandmanesh, Yasaman Björnson, Emil Jaldén, Joakim The Division of Communication Systems KTH Royal Institute of Technology Stockholm Sweden The Division of Information Science and Engineering KTH Royal Institute of Technology Stockholm Sweden

One of the first widespread uses of multi-user multiple-input multiple-output (MU-MIMO) is in 5G networks, where each base station has an advanced antenna system (AAS) that is connected to the baseband unit (BBU) with a capacity-constrained fronthaul. In the AAS configuration, multiple passive antenna elements and radio units are integrated into a single box. This paper considers precoded downlink transmission over a single-cell MU-MIMO system. We study optimized linear precoding for AAS with a limited-capacity fronthaul, which requires the precoding matrix to be quantized. We propose a new precoding design that is aware of the fronthaul quantization and minimizes the mean-squared error at the receiver side. We compute the precoding matrix using a sphere decoding (SD) approach. We also propose a heuristic low-complexity approach to quantized precoding. This heuristic is computationally efficient enough for massive MIMO systems. The numerical results show that our proposed precoding significantly outperforms quantization-unaware precoding and other previous approaches in terms of the sum rate. The performance loss for our heuristic method compared to quantization-aware precoding is insignificant considering the complexity reduction, which makes the heuristic method feasible for real-time applications. We consider both perfect and imperfect channel state information. Copyright © 2022, The Authors. All rights reserved.

关键词： 5G mobile communication systems

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Carbon-Aware Computing in a Network of Data Centers: A Hierarchical Game-Theoretic Approach

Carbon-Aware Computing in a Network of Data Centers: A Hiera...

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European Control Conference (ECC)

作者： Enno Breukelman Sophie Hall Giuseppe Belgioioso Florian Dörfler Division of Decision and Control Systems KTH Royal Institute of Technology School of Electrical Engineering and Computer Science Stockholm Sweden Department of Electrical Engineering and Information Technology Automatic Control Laboratory ETH Zurich Zürich Switzerland

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

Over the past decade, the continuous surge in cloud computing demand has intensified data center workloads, leading to significant carbon emissions and driving the need for improving their efficiency and sustainability. This paper focuses on the optimal allocation problem of batch compute loads with temporal and spatial flexibility across a global network of data centers. We propose a bilevel game-theoretic solution approach that captures the inherent hierarchical relationship between supervisory control objectives, such as carbon reduction and peak shaving, and operational objectives, such as priority-aware scheduling. Numerical simulations with real carbon intensity data demonstrate that the proposed approach success-fully reduces carbon emissions while simultaneously ensuring operational reliability and priority-aware scheduling.

关键词： Data centers Processor scheduling Computational modeling Carbon dioxide Games Supervisory control Resource management

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Enhancing Older Adults’ Gesture Typing Experience Using the T9 Keyboard on Small Touchscreen Devices

arXiv

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arXiv 2023年

作者： Kuang, Emily Chen, Ruihuan Fan, Mingming Golisano College of Computing and Information Sciences Rochester Institute of Technology United States School of Information Rochester Institute of Technology United States Computational Media and Arts Thrust The Hong Kong University of Science and Technology Guangzhou China Division of Integrative Systems and Design Department of Computer Science and Engineering The Hong Kong University of Science and Technology China

Older adults increasingly adopt small-screen devices, but limited motor dexterity hinders their ability to type effectively. While a 9-key (T9) keyboard allocates larger space to each key, it is shared by multiple consecutive letters. Consequently, users must interrupt their gestures when typing consecutive letters, leading to inefficiencies and poor user experience. Thus, we proposed a novel keyboard that leverages the currently unused key 1 to duplicate letters from the previous key, allowing the entry of consecutive letters without interruptions. A user study with 12 older adults showed that it significantly outperformed the T9 with wiggle gesture in typing speed, KSPC, insertion errors, and deletes per word while achieving comparable performance as the conventional T9. Repeating the typing tasks with 12 young adults found that the advantages of the novel T9 were consistent or enhanced. We also provide error analysis and design considerations for improving gesture typing on T9 for older adults. © 2023, CC BY-NC-ND.

关键词： Touch screens

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An Integrated Observer Framework Based Mechanical Parameters Identification for Adaptive Control of Permanent Magnet Synchronous Motor

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Complex System Modeling and Simulation 2022年第4期2卷 354-367页

作者： Zhong Liao Zhaohua Liu Lei Chen Mingyang Lyu Dian Wang Faming Wu Zhengheng Wang Hualiang Wei the School of Information and Electrical Engineering Hunan University of Science and TechnologyXiangtan 411201China the Wind Power Business Division CRRC Zhuzhou Institute Co.Ltd.Zhuzhou 412001China. the Department of Automatic Control and Systems Engineering University of SheffieldSheffieldS13JDUK.

An integrated observer framework based mechanical parameters identification approach for adaptive control of permanent magnet synchronous motors is proposed in this ***,an integrated observer framework is established for mechanical parameters’estimation,which consists of an extended sliding mode observer(ESMO)and a Luenberger *** at minimizing the influence of parameters coupling,the viscous friction and the moment of inertia are obtained by ESMO and the load torque is identified by Luenberger observer *** obtaining estimates of the mechanical parameters,the optimal proportional integral(PI)parameters of the speed-loop are determined according to third-order best design *** a result,the controller can adjust the PI parameters in real time according to the parameter changes to realize the adaptive control of the ***,the disturbance is compensated according to the ***,the experiments were carried out on simulation platform,and the experimental results validated the reliability of parameter identification and the efficiency of the adaptive control strategy presented in this paper.

关键词： parameter identification permanent magnet synchronous motor adaptive control extended sliding mode observer Luenberger observer

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Pre-trained Convolutional Neural Networks and Otsu’s Multi-level Thresholding based Alzheimer’s Classification

Pre-trained Convolutional Neural Networks and Otsu’s Multi-...

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Advances in Computing, Communication and Applied Informatics (ACCAI), International Conference on

作者： Nivedhitha Mahendran P M Durai Raj Vincent Duraimurugan Samiayya Venkatesan Rajinikanth Department of Networking and Communications School of Computing Technologies SRM Institute of Science and Technology Kattankulathur Chennai India School of Computer Science and Engineering and Information Systems Vellore Institute of Technology Vellore India Department of Information Technology St. Joseph’s College of Engineering Chennai India Department of Computer Science and Engineering Saveetha School of Engineering Division of Research and Innovation SIMATS Chennai India

ISBN: (数字)9798350389449

ISBN: (纸本)9798350389456

Disorders affecting the brain and the nerves that supply the entire body are referred to as neurological diseases. Changes in the brain’s chemistry, structure, or electrical system can cause a variety of symptoms. Alzheimer’s disease (AD), a degenerative neurological condition that impairs cognitive function, is one example of this type of illness. The most prevalent type of dementia for which there is no effective treatment. Early detection and treatment, however, may help the patient’s lifestyle and reduce symptoms. Brain imaging techniques, including MRI, CT, PET, and others, are widely used to diagnose neurological problems. It has been discovered that the Artificial Intelligence based approaches, such as the deep learning algorithms and machine learning algorithms work well for assessing these photos and provide improved accuracy for identifying AD. In this paper, we classified AD and Control cases using four different Convolutional Neural Networks (CNN) versions. Additionally, in order to increase the accuracy of AD’s classification, we have segmented the images using Otsu’s thresholding technique. The outcomes demonstrate that, both before and after thresholding was implemented, the CNN AlexNet offers a significant improvement over the other deep learning models.

关键词： Neurological diseases Deep learning Thresholding (Imaging) Machine learning algorithms Magnetic resonance imaging Computed tomography Computational modeling

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