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International Conference on Applied Soft Computing and Communication Networks, ACN 2023

作者： Hasan, Mohammed Zaki Alabady, Salah Abdulghani Salleh, Mohd Fadzli Mohd Computer Networks Department College of Computer Science and Mathematics University of Mosul Mosul Iraq Computer Engineering Department College of Engineering University of Mosul Mosul Iraq School of Electrical and Electronic Engineering Universiti Sains Malaysia Seri Ampangan Pulau Pinang Nibong Tebal14300 Malaysia

ISBN: (纸本)9789819720033

Energy efficiency in sensor networks is a critical concern, as sensors are often resource-constrained devices with limited battery power. Maximizing energy efficiency is essential to prolonging the network’s lifetime, reducing maintenance costs, and enabling long-term monitoring and data collection in various Internet of Things (IoT) applications. Collaborative beamforming involves multiple sensors that coordinate their signal transmission to be focused on a specific direction. However, sensors may have various energy budget limitations to achieve beamformed signal transmission in a specific direction of the sink. In this paper, we developed a power control approach of beamforming transmission to prolong the lifetime of sensors by organizing the collaborative sensors into clusters. The proposed algorithm is based on the K-means clustering algorithm, which groups these collaborative sensors into clusters based on their residual energy information (REI). REI is changed among collaborative sensors to communicate with each other within a cluster. Therefore, each of these collaborative sensors adjusts its transmission power level to achieve balance in making decisions and facilitate collaboration between sensors in the inner cluster. Simulation results demonstrate that the proposed algorithm requires significantly low overhead and computational complexity in terms of prolonging the lifetime of the collaborative sensor cluster as compared to alternative power control algorithm that balances the energy consumption of the entire network. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Wireless sensor networks

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Near-sensor computing-assisted simultaneous viral antigen and antibody detection via integrated label-free biosensors with microfluidics

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InfoMat 2023年第10期5卷 80-95页

作者： Byungjoon Bae Yongmin Baek Jeongyong Yang Heesung Lee Charana S.S.Sonnadara Sangeun Jung Minseong Park Doeon Lee Sihwan Kim Gaurav Giri Sahil Shah Geonwook Yoo William APetri Kyusang Lee Department of Electrical and Computer Engineering University of VirginiaCharlottesvilleVirginiaUSA School of Electronic Engineering Soongsil UniversitySeoulRepublic of Korea Department of Electrical and Computer Engineering University of MarylandCollege ParkMarylandUSA Department of Chemical Engineering University of VirginiaCharlottesvilleVirginiaUSA Division of Infectious Diseases and International Health Department of MedicineSchool of MedicineUniversity of VirginiaCharlottesvilleVirginiaUSA Department of Material Science and Engineering University of VirginiaCharlottesvilleVirginiaUSA Department of Intelligent Semiconductors Soongsil UniversitySeoulRepublic of Korea

Precise diagnosis and immunity to viruses,such as severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)and Middle East respiratory syndrome coronavirus(MERS-CoV)is achieved by the detection of the viral antigens and/or corresponding antibodies,***,a widely used antigen detection methods,such as polymerase chain reaction(PCR),are complex,expensive,and time-consuming Furthermore,the antibody test that detects an asymptomatic infection and immunity is usually performed separately and exhibits relatively low *** achieve a simplified,rapid,and accurate diagnosis,we have demonstrated an indium gallium zinc oxide(IGZO)-based biosensor field-effect transistor(bio-FET)that can simultaneously detect spike proteins and antibodies with a limit of detection(LOD)of 1 pg mL–1 and 200 ng mL–1,respectively using a single assay in less than 20 min by integrat-ing microfluidic channels and artificial neural networks(ANNs).The near-sensor ANN-aided classification provides high diagnosis accuracy(>93%)with significantly reduced processing time(0.62%)and energy consumption(5.64%)compared to the software-based *** believe that the development of rapid and accurate diagnosis system for the viral antigens and antibodies detec-tion will play a crucial role in preventing global viral outbreaks.

关键词： artificial intelligence biosensor edge-computing integration microfluidic

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Explaining Machine Learning Based Speed Anomaly Detection System Using eXplainable Artificial Intelligence 1

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13th International Conference on Information Systems and Advanced Technologies, ICISAT 2023

作者： Idris, Hussaini Aliyu Ahmad, Aminu Diginsa, Muhammad Umar Aliyu, Buhari Muhammad, Adamu Yahaya, Abdulgaffar Abubakar Suleiman, Sabiu Usman Alexandria Egypt School of Computer Science and Engineering Central South University Hunan Changsha China Department of Computer Engineering Technology Bilyaminu Usman Polytechnic Hadejia Hadejia Nigeria Department of Computer Science Jigawa State Polytechnic Dutse Jigawa Nigeria Department of Electrical Electronics Engineering Jigawa State Polytechnic Dutse Jigawa Nigeria Department of Computer Science Mewar University Gangarar Chittorgarh Rajasthan India

ISBN: (数字)9783031605949

ISBN: (纸本)9783031605932

The goal of combating road accidents through the application of advanced communication and network technologies in transportation system called intelligent transportation system (ITS) has recorded a remarkable success. Nevertheless, the complex nature of the ITS makes cyberattacks a major concern even with cryptographic techniques employed for authentication of users, as they cannot prevent attacks from authenticated users (insider attackers). To solve this problem, several data-centric approaches for anomaly detection using machine learning (ML) are proposed by the research community. However, those approaches are limited in interpretability and explainability due to the complexity of some ML algorithms and black-box nature of neural networks which makes threat intelligence and analysis difficult. In this paper, we proposed an eXplainable artificial intelligence (XAI)-based speed anomaly detection system using trusted vehicles method with more than 99% accuracy, precision, recall and F1-Score where Shapley Additive exPlanation (SHAP) is further employed to explain the predictions made by the models. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Machine learning

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Concierge: Towards Accuracy-Driven Bandwidth Allocation for Video Analytics Applications in Edge Network 8

Concierge: Towards Accuracy-Driven Bandwidth Allocation for ...

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8th IEEE International Conference on Edge Computing and Communications, EDGE 2024

作者： Huang, Yuyang Zharfan, Faishal Hendrawan, Hendrawan Gunawi, Haryadi S. Jiang, Junchen University of Chicago Department of Computer Science Chicago United States Bandung Institute of Technology School of Electrical Engineering and Informatics Bandung Indonesia

ISBN: (纸本)9798350368499

When performing inference on sensor data, edge video analytics applications may not always need high-fidelity data, since important information may not appear all the time. Consequently, each edge AI application's bandwidth demand is highly dynamic. Thus, a shared edge system should dynamically allocate more bandwidth to the applications in need to reach high accuracy at each moment. However, previous bandwidth allocators are ill-suited because they are agnostic to the timevarying impact of bandwidth on each application's *** short paper explores a new accuracy-driven approach to bandwidth allocation, which periodically re-allocates bandwidth across edge AI applications based on the sensitivity of each application's accuracy to its bandwidth share. To examine its practical benefit and technical challenges, we present a concrete accuracy-driven bandwidth allocator called ConciERGE, which exposes a simple yet efficient interface to estimate each application's sensitivity to a small change in its bandwidth *** run CONCIERGE on state-of-the-art video-analytics applications with real video streams and show its early promise in greatly improving the inference accuracy of video analytics. © 2024 IEEE.

关键词： Bandwidth

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Photonic orbital angular momentum with controllable orientation

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National science Review 2022年第7期9卷 56-62页

作者： Chenhao Wan Jian Chen Andy Chong Qiwen Zhan School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology School of Optical and Electronic Information Huazhong University of Science and Technology Department of Electro-Optics and Photonics University of Dayton Department of Physics University of Dayton

Vortices are whirling disturbances,commonly found in nature,ranging from tremendously small scales in Bose-Einstein condensations to cosmologically colossal scales in spiral *** optical vortex,generally associated with a spiral phase,can carry orbital angular momentum(OAM).The optical OAM can either be in the longitudinal direction if the spiral phase twists in the spatial domain or in the transverse direction if the phase rotates in the spatiotemporal *** this article,we demonstrate the intersection of spatiotemporal vortices and spatial vortices in a wave *** a result of this intersection,the wave packet hosts a tilted OAM that provides an additional degree of freedom to the applications that harness the OAM of photons.

关键词： orbital angular momentum spatiotemporal vortex spatial vortex spiral phase

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Trust Assessment Model for Visual Image-Based Human-Robot Interaction Under Known and Unknown Threats 16th

Trust Assessment Model for Visual Image-Based Human-Robot I...

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16th International Conference on Social robotics, ICSR + BioMed 2024

作者： Li, Heqing Li, Xinde Liu, Erfeng Ge, Shuzhi Sam School of Cyber Science and Engineering Southeast University Nanjing China School of Automation Southeast University Nanjing China Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore

ISBN: (纸本)9789819789627

Visual imagery is a critical perceptual source in human-robot interaction (HRI), extensively applied in various domains such as robotic navigation, target detection, and task planning. Aerial robots, also known as UAVs, are the typical representatives of teleoperation robots. The substantial distance between humans and remotely operated robots, coupled with the dynamic and open environments these robots navigate, exposes image-based HRI to significant security risks from both known and unknown threats. The trustworthiness of data sources is a fundamental prerequisite for ensuring the security of HRI systems. However, the multidimensionality of trust factors and the uncertainty of trust evidence have constrained its practical application. To advance this field, we have innovatively proposed a trust evaluation scheme based on multidimensional evidence fusion within the Belief Functions (BFs) framework. This scheme constructs an adaptive trust evaluation model capable of addressing both known and unknown threats. For known threats, we developed coarse-grained multidimensional trust elements and employed multiple lightweight SVM submodels to construct Basic Belief Assignments (BBAs), thereby achieving direct trust modeling and enabling rapid trust evaluation of images. Conversely, for unknown threats, we utilized pretrained models to establish fine-grained multidimensional trust elements, implementing indirect trust modeling through trust recommendation, thus facilitating indirect trust evaluation of images. We further combined direct and indirect trust to derive a overall trust assessment of the images, achieving adaptive dynamic trust evaluation in image-based HRI. Additionally, to more accurately represent image trustworthiness, we introduced a BBAs weighted fusion method, which aids in more rational trust aggregation. To validate the efficacy of our proposed method, we conducted experiments on a real aerial image dataset. The results demonstrate that our approach ef

关键词： Human robot interaction

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On the Convergence of Finite Element Domain Decomposition Methods for Discontinuous Subdomain Interfaces

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IEEE Transactions on Antennas and Propagation 2025年第6期73卷 4122-4127页

作者： Xin, Xi-Min Gao, Hong-Wei Wang, Shu Jian Lim, Qi Peng, Zhen Beijing Institute of Technology School of Integrated Circuits and Electronics Beijing100081 China Beijing Institute of Technology School of Cyberspace Science and Technology Beijing100081 China The University of New Mexico Applied Electromagnetics Group Department of Electrical and Computer Engineering AlbuquerqueNM87131 United States NVIDIA Corporation Santa ClaraCA95050 United States University of Illinois at Urbana–Champaign Department of Electrical and Computer Engineering UrbanaIL61801 United States

In this communication, we propose a finite element domain decomposition method (FE-DDM) with Robin-type transmission conditions (TCs) at discontinuous subdomain interfaces. By definition, these discontinuous interfaces refer to impedance surfaces where electromagnetic (EM) fields exhibit discontinuities, which are common in applications of metamaterials/metasurfaces, frequency-selective surfaces, or thin dielectric layer approximation. Through a detailed convergence study, we propose an optimized set of parameters in the TC. The proposed TC provides convergence for both propagating and evanescent EM waves across subdomain interfaces and is valid for all resistivity values. Numerical experiments are supplied to validate our theoretical analysis, demonstrating the convergence and accuracy of our proposed work. © 1963-2012 IEEE.

关键词： Electromagnetic wave transmission

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Microgrid digital twins: concepts and their controlling through multi-agent systems

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International Journal of High Performance Systems Architecture 2023年第4期11卷 225-236页

作者： Negi, Gaurav Singh Mishra, Anupama Gupta, Mukul Kumar Saxena, Nitin Kumar Saini, DilipKumar Jang Bahadur Joshi, Kapil Electrical and Electronics Engineering Uttaranchal Institute of Technology Uttaranchal University Dehradun248007 India Department of Computer Science and Engineering Himalayan School of Science and Technology Swami Rama Himalayan University Uttarakhand Dehradun248140 India School of Engineering University of Petroleum and Energy Studies Dehradun248006 India Department of Electronics & Instrumentation Engineering MJP Rohilkhand University UP Bareilly243006 India Electrical and Electronics Engineering KIET Group of Institutions Ghaziabad201206 India Electrical and Computer Engineering University of Denver Denver80210 United States Department of Computer Science and Engineering School of Engineering and Technology Pimpri Chinchwad University Pune411044 India Department of CSE Uttaranchal Institute of Technology Uttaranchal University Dehradun248007 India

Real-time grid analysis is made possible by the electric digital twin grid, which combines history and present data to convey system status and project future circumstances. Cooperative smart agents that can solve problems bigger than one agent's scope make up a multi-agent system (MAS). A micro-grid digital twin (MGDT) uses real-time data interchange and high-fidelity models to simulate a microgrid’s operation. Hybrid energy storage systems are managed by agents who maximise renewable resources and minimise expenses. Microgrids combine sensing, control, and intelligence technology in utility networks. Plant management, communication protocols, and power system operations are all made easier with MAS-based control. For dependable microgrid operation, dispersed energy resources are coordinated by MAS. In order to handle complexity and improve resilience and control of the energy system, this study investigates the application of MAS in microgrid control. Energy management and agent communication in microgrids are the main topics of MAS research. Integrating microgrid digital twins with MAS holds promise for advancing energy systems. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Multi agent systems

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Optimization of Intelligent Classroom based on CAD Multi-Valued Color Image Segmentation Algorithm

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computer-Aided Design and Applications 2023年第S3期20卷 16-28页

作者： Wang, Nanlan Li, Jianqi Balaji, Prasanalakshmi Vaiyapuri, Thavavel Verma, Amit School of Computer and Electrical Engineering Hunan university of Arts and Science Hunan Changde415000 China International Education Center Philippine Christian University Manila1772 Philippines Department of Computer Science King Khalid University Saudi Arabia Department of Computer Sciences College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz University Saudi Arabia Department of CSE University Centre for Research & Development Chandigarh University Punjab Mohali140413 India

In order to solve the problem that the efficiency of smart classroom is not high enough, a multi valued color image segmentation algorithm based on CAD is proposed to optimize the smart classroom. This paper explores the notion of smart education as well as a conceptual framework to enable children to receive excellent education and to spark their interest through creative learning. Firstly, CAD software is used to improve software design efficiency and optimize product technology;Secondly, the core technology of the smart classroom is improved by using the national value color image segmentation algorithm, and compared with the smart classroom without the multi value color image segmentation algorithm;Finally, the utilization efficiency of the improved smart classroom is counted. It is proved that the smart classroom based on CAD multi valued color image segmentation algorithm can give greater play to the role of smart classroom, reduce the teaching pressure of teachers by 20% and improve the learning efficiency of students by 20%. The intelligent classroom has a higher degree of informatization and more powerful functions, which is of great help to promote classroom communication and improve communication efficiency. The smart classroom is easier to run and adapt thanks to the optimization of the CAD multi threshold color picture segmentation algorithm, which considerably improves the system's work efficiency and capability. However, the smart classroom also has its own shortcomings, which are mainly reflected in the high investment cost, the complex design of the system and the high maintenance cost in the later stage. With the optimization of CAD multi valued color image segmentation algorithm, the smart classroom is easier to operate and adjust, which greatly enhances the work efficiency and ability of the system. © 2023 CAD Solutions, LLC.

关键词： computer aided design

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PrivShape: Extracting Shapes in Time Series under User-Level Local Differential Privacy 40

PrivShape: Extracting Shapes in Time Series under User-Level...

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40th IEEE International Conference on Data engineering, ICDE 2024

作者： Mao, Yulian Ye, Qingqing Hu, Haibo Wang, Qi Huang, Kai Southern University of Science and Technology Department of Computer Science and Engineering China The Hong Kong Polytechnic University Department of Electrical and Electronic Engineering Hong Kong Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology China School of Computer Science and Engineering Macau University of Science and Technology China

ISBN: (纸本)9798350317152

Time series have numerous applications in finance, healthcare, IoT, and smart city. In many of these applications, time series typically contain personal data, so privacy infringement may occur if they are released directly to the public. Recently, local differential privacy (LDP) has emerged as the state-of-the-art approach to protecting data privacy. However, existing works on LDP-based collections cannot preserve the shape of time series. A recent work, PatternLDP, attempts to address this problem, but it can only protect a finite group of elements in a time series due to ?-event level privacy guarantee. In this paper, we propose PrivShape, a trie-based mechanism under user-level LDP to protect all elements. PrivShape first transforms a time series to reduce its length, and then adopts trie-expansion and two-level refinement to improve utility. By extensive experiments on real-world datasets, we demonstrate that PrivShape outperforms PatternLDP when adapted for offline use, and can effectively extract frequent shapes. © 2024 IEEE.

关键词： Time series

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