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arXiv 2024年

作者： Liu, Shuai Wu, Bo-Han Huang, Jeffrey Zhang, Zheshen Department of Electrical Engineering and Computer Science The University of Michigan Ann ArborMI48109 United States Research Laboratory of Electronics Massachusetts Institute of Technology CambridgeMA02139 United States

Bound states in the continuum (BIC) holds significant promise in manipulating electromagnetic fields and reducing losses in optical structures, leading to advancements in both fundamental research and practical applications. Despite their observation in various optical systems, the behavior of BIC in whispering-gallery-modes (WGMs) optical microcavities, essential components of photonic integrated chips, has yet to be thoroughly explored. In this study, we propose and experimentally identify a robust mechanism for generating quasi-BIC in a single deformed microcavity. By introducing boundary deformations, we construct stable unidirectional radiation channels as leaking continuum shared by different resonant modes and experimentally verify their external strong mode coupling. This results in drastically suppressed leaking loss of one originally long-lived resonance, manifested as more than a 3-fold enhancement of its quality (Q) factor, while the other short-lived resonance becomes more lossy, demonstrating the formation of Friedrich-Wintgen quasi-BICs as corroborated by both the theoretical model and the experimental data. This research will provide a practical approach to enhance the Q factor of optical microcavities, opening up potential applications in the area of deformed microcavities, nonlinear optics, quantum optics, and integrated photonics. © 2024, CC BY.

关键词： Quantum optics

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Data Driven Traffic Density Monitoring: A UAV and ResNet50 Deep Learning Framework

Data Driven Traffic Density Monitoring: A UAV and ResNet50 D...

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International Colloquium on Signal Processing & Its Applications, CSPA

作者： Saddaf Rubab Fida Hussain Dahri Ghulam E Mustafa Abro Nooritawati Md Tahir Muhammad Javed Department of Computer Engineering College of Computing and Informatics University of Sharjah Sharjah United Arab Emirates School of Computer Science and Engineering Southeast University Nanjing China Interdisciplinary Research Centre for Aviation and Space Exploration King Fahd University of Petroleum and Minerals (KFUPM) Saudi Arabia School of Electrical Engineering College of Engineering Universiti Teknologi MARA Shah Alam Selangor Malaysia Department of Cybersecurity International information Technology University Alamty Kazakhstan Department of Computer Science and Technology College of Computer Science Donghua University Shanghai China

ISBN: (数字)9798331522193

ISBN: (纸本)9798331522209

Urban traffic congestion necessitates innovative monitoring and control solutions. This study leverages UAV footage and deep learning techniques to classify and analyze traffic density levels autonomously. By employing a pre-trained ResN et50 model enhanced with additional layers, the research optimizes traffic density classification using UAV-captured data. A custom dataset of traffic scenarios in Dammam, Saudi Arabia, was developed, incorporating diverse conditions through advanced normalization and data augmentation techniques to improve resilience and robustness. The modified ResN et50 model demonstrated high classification accuracy across varied traffic scenarios, validating its reliability and scalability for real-world applications. Key findings include the superior adaptability of UAV-based monitoring for real-time urban traffic assessment and the enhanced classification precision achieved through model optimization. This research underscores the potential of integrating UAV technology with deep learning to advance urban traffic management and foster more efficient urban planning strategies.

关键词： Deep learning Scalability Heuristic algorithms Urban planning Autonomous aerial vehicles Real-time systems Monitoring Traffic congestion Resilience Residual neural networks

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Natural Human Skin‑Inspired Wearable and Breathable Nanofiber‑based Sensors with Excellent Thermal Management Functionality

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Advanced Fiber Materials 2024年第6期6卷 1955-1968页

作者： Peng Wang Xiaodan Li Guifen Sun Guoqing Wang Qing Han Chuizhou Meng Zhonghe Wei Yang Li School of Mechanical Engineering University of JinanJinan 250022China School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China State Key Laboratory for Reliability and Intelligence of Electrical Equipment Engineering Research Center of Ministry of Education for Intelligent Rehabilitation Device and Detection TechnologyHebei Key Laboratory of Smart Sensing and Human‑Robot InteractionSchool of Mechanical EngineeringHebei University of TechnologyTianjin 300401China Shandong Provincial Key Laboratory of Network‑Based Intelligent Computing School of Information Science and EngineeringUniversity of JinanJinan 250022China Network Information Center Department of Computer ScienceQilu University of Technology(Shandong Academy of Sciences)Jinan 250353China School of Integrated Circuits Shandong UniversityJinan 250101China

Wearable sensors have been rapidly developed for application in various human monitoring ***,the wearing comfort and thermal properties of these devices have been largely ignored,and these characteristics urgently need to be ***,we develop a wearable and breathable nanofiber-based sensor with excellent thermal management functionality based on passive heat preservation and active Joule heating *** multifunctional device consists of a micropatterned carbon nanotube(CNT)/thermoplastic polyurethane(TPU)nanofiber electrode,a microporous ionic aerogel electrolyte and a microstructured Ag/TPU nanofiber *** to the presence of a supercapacitive sensing mechanism and the appli-cation of microstructuration,the sensor shows excellent sensing performance,with a sensitivity of 24.62 ***,due to the overall porous structure and hydrophobicity of TPU,the sensor shows good breathability(62 mm/s)and water repellency,with a water contact angle of 151.2°.In addition,effective passive heat preservation is achieved by combining CNTs with high solar absorption rates(85%)as the top layer facing the outside,aerogel with a low thermal conductivity(0.063 W m-1 k-1)as the middle layer for thermal insulation,and Ag with a high infrared reflectance rate as the bottom layer facing the *** warming,this material yields a higher temperature than ***,the active Joule heat-ing effect is realized by applying current through the bottom resistive electrode,which can quickly increase the temperature to supply controlled warming on *** proposed wearable and breathable sensor with tunable thermal properties is promising for monitoring and heat therapy applications in cold environments.

关键词： Wearable sensor Breathable Personal thermal management Electrospun nanofibers Joule heating

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Leveraging Group Secret Sharing Technology for FD-RAN: A Lightweight AKA Mechanism

Leveraging Group Secret Sharing Technology for FD-RAN: A Lig...

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IEEE Conference on Vehicular Technology (VTC)

作者： Ning Wang Jiacheng Chen Jianbing Ni Liquan Chen Haibo Zhou School of Cyber Science and Engineering Southeast University Nanjing China Department of Strategic and Advanced Interdisciplinary Research Peng Cheng Laboratory Shenzhen China Department of Electrical and Computer Engineering Queen's University Kingston ON Canada School of Electronic Science and Engineering Nanjing University Nanjing China

ISBN: (数字)9798350387414

ISBN: (纸本)9798350387421

With rapid advances in communication technology, a new access architecture of fully decoupled radio access network (FD-RAN) has been proposed. FD-RAN completely decouples the base station (BS) into uplink data base station (UBS), downlink data base station (DBS), and control base station (CBS). Different BSs handle the uplink and downlink data of the user plane, as well as control signaling, and facilitate communication needs through multi-BS cooperation. To ensure the security of multi-BS cooperation and user access, it becomes imperative to conduct key negotiations among multiple parties. However, as the number of simultaneously accessed BSs increases, the existing access security mechanism imposes excessive overhead in FD-RAN, compromising both access security and efficiency. Additionally, it becomes susceptible to distributed denial of service (DDoS) attacks launched by potential attackers. This paper introduces a lightweight authentication and key agreement (AKA) protocol based on secret value ( $m_{i},\ n_{i}$ ) sharing technology to negotiate multi-BS group communication keys, which ensures access security in FD-RAN. By leveraging interpolation polynomial and multi-party key negotiation, the proposed protocol achieves efficient and cost-effective key negotiation on both the user and BS sides, which mitigates the risk of man-in-the-middle (MitM) and DDoS attacks. Security analysis and further evaluation show that the proposed scheme can resist various known attacks, and guarantee the computational and communication efficiency of key negotiation within the FD-RAN context.

关键词： Base stations Vehicular and wireless technologies Interpolation Protocols Resists Downlink Denial-of-service attack

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Clustering Interval and Triangular Granular Data: Modeling, Execution, and Assessment

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IEEE Transactions on Neural Networks and Learning Systems 2024年第6期36卷 10000-10014页

作者： Yiming Tang Wenbin Wu Witold Pedrycz Jianwei Gao Xianghui Hu Zhaohong Deng Rui Chen Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information Hefei University of Technology Hefei China Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada School of Computer and Information Hefei University of Technology Hefei China Faculty of Automatic Control Electronics and Computer Science Silesian University of Tecghnology Gliwice Poland Research Center of Performance and Productivity Analysis Istinye University Istanbul TÃrkiye School of Computer Science and Engineering Southeast University Nanjing China School of Artificial Intelligence and Computer Jiangnan University Wuxi Jiangsu China

In current granular clustering algorithms, numeric representatives were selected by users or an ordinary strategy, which seemed simple; meanwhile, weight settings for granular data could not adequately express their structural characteristics. Aiming at these problems, in this study, a new scheme called a granular weighted kernel fuzzy clustering (GWKFC) algorithm is put forward. We propose the representative selection and granularity generation (RSGG) algorithm enlightened by the density peak clustering (DPC) algorithm. We build interval and triangular granular data on the strength of numeric representatives obtained by RSGG under the principle of justifiable granularity (PJG), in which we establish some combinations of functions and boundary constraints and prove their properties. Furthermore, we present a novel distance formula via the kernel function for granular data and design new weights to affect the coverage and specificity of granular data. In addition, based upon these factors, we come up with the GWKFC algorithm of granular clustering, and its performance with different granularity is assessed. To sum up, a macro framework involving granular modeling, granular clustering, and assessment has been set up. Lastly, the GWKFC algorithm and ten other granular clustering algorithms are compared by experiments on some artificial and UCI datasets together with datasets with large data or those of high dimensionality. It is found that the GWKFC algorithm can provide better granular clustering results by contrast with other algorithms. The originality is embodied as follows. First, we improve the previous density radius and present the RSGG algorithm to acquire numeric representatives. Second, we propose a new strategy to determine granular data boundaries and further obtain novel weights enlightened by the idea of volume. Lastly, we employ the kernel function to calculate the distance between granular data, which has a stronger spatial division ability than the pr

关键词： Clustering algorithms Data models Computational modeling Numerical models Kernel Phase change materials Granular computing Uncertainty Fuzzy sets Noise

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On Verifying Entropic Vectors with Distributions Generated by Neural Networks

On Verifying Entropic Vectors with Distributions Generated b...

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IEEE (first ITW conference of the year) Information Theory Workshop (ITW)

作者： Shuhao Zhang Nan Liu Wei Kang Haim Permuter School of Information Science and Engineering Southeast University Nanjing China National Mobile Communications Research Laboratory Southeast University Nanjing China Department of Electrical and Computer Engineering Ben-Gurion University of the Negev Beersheba Israel

ISBN: (数字)9798350348934

ISBN: (纸本)9798350348941

This paper proposes a novel algorithm to verify entropic vectors with probability mass functions parametrized and generated by neural networks. Given a target vector, we minimize the normalized distance by training a neural network, which reveals the entropic nature of the target, with the underlying distribution obtained accordingly. Empirical results demonstrate improved normalized distances and convergence performances compared with prior works. We also conduct optimizations of Ingleton score and Ingleton violation index, where a new lower bound of Ingleton violation index is obtained. An inner bound of the almost entropic region with four random variables is constructed with the proposed method, presenting the current best inner bound measured by the volume ratio.

关键词： Training Lower bound Volume measurement Current measurement Neural networks Vectors Random variables Indexes Optimization Information theory

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Controllable multi-level switching of optical phase change materials via microheater temperature profile engineering

Controllable multi-level switching of optical phase change m...

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CLEO: science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Sun, Hongyi Lian, Chuanyu Vásquez-Aza, Francis Huang, Yi-Siou Vitale, Steven A. Takeuchi, Ichiro Hu, Juejun Youngblood, Nathan Pavlidis, Georges Ríos Ocampo, Carlos A. Department of Materials Science & Engineering University of Maryland College ParkMD20742 United States Institute for Research in Electronics and Applied Physics University of Maryland College ParkMD20742 United States Department of Mechanical Engineering University of Connecticut StorrsCT06269 United States Advanced Materials and Microsystems Group MIT Lincoln Laboratory LexingtonMA02139 United States Quantum Materials Center Department of Physics University of Maryland College ParkMD20742 United States Department of Materials Science & Engineering MIT CambridgeMA02139 United States Electrical & Computer Engineering Department The University of Pittsburgh PittsburghPA15213 United States

We demonstrate doped-silicon-on-insulator microheaters with triangle-like temperature profiles. Such devices control the hotspot size and temperature and, thus, the area that undergoes amorphization or crystallization in optical phase-change materials, leading to controllable multilevel, nonvolatile response. © Optica Publishing Group 2024

关键词： Amorphization

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Clustering-Based Resource Management for Consumer Cost Optimization in IoT Edge computing Environments

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IEEE Transactions on Consumer Electronics 2024年 1-1页

作者： Denden, Mohsen Jemmali, Mahdi Boulila, Wadii Soni, Mukesh Khan, Faheem Ahmad, Jawad Department of Computer and Information Technologies College of Telecommunication and Information CTI Riyadh Saudi Arabia Department of Computer Science College of Computing and Informatics University of Sharjah Sharjah UAE Robotics and Internet-of-Things Laboratory Prince Sultan University Riyadh Saudi Arabia Department of CSE University Centre for Research and Development Chandigarh University Mohali Punjab- India Department of Computer Engineering Gachon University Seongnam-si South Korea School of Computing Engineering and the Built Environment Edinburgh Napier University U.K

Edge computing emerges as a pivotal model in the era of next-generation consumer electronics and the emerging challenges of multimodal data-driven decision-making. Specifically, edge computing offers an open computing architecture for the vast and diverse consumer multimodal data generated by mobile computing and Internet of Things (IoT) technologies. While edge computing is instrumental in optimizing latency and bandwidth control in processing consumer multimodal data, the viability of employing edge resources is complicated by high service costs and the complexities of managing multimodal data diversity. This study introduces an innovative optimization method for distributing multimodal data on edge storage, considering both the I/O (input/output) speed and the overall distribution cost. The core part of our approach is the deployment of intelligent algorithms that ensure equitable data distribution across storage servers, thus eliminating unused space and reducing extra costs. Given the complexity of this NP-hard (non-deterministic polynomial-time) challenge, our study reveals a unique model incorporating an edge-broker component in combination with novel algorithms. The proposed algorithms aim to harmonize data distribution and reduce resource allocation expenses in a multimodal edge environment. Our proposed approach achieves excellent results, highlighting the efficacy of the proposed algorithms in several parameters such as makespan, cost, multimodal data security, and total processing time. Empirical tests reveal that the BCA (Best Clustering Algorithm) performs best, achieving a minimum load balancing rate of 92.2%, an average variance of 0.04, and an average run time of 0.56 seconds. IEEE

关键词： Edge computing

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MIMO Beamforming and Signal Modulation Design for Federated Learning Optimization

MIMO Beamforming and Signal Modulation Design for Federated ...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Nuocheng Yang Sihua Wang Mingzhe Chen Cong Shen Changchuan Yin Christopher G. Brinton Beijing Laboratory of Advanced Information Network Beijing University of Posts and Telecommunications Beijing China Department of Electrical and Computer Engineering Institute for Data Science and Computing University of Miami Coral Gables FL USA Charles L. Brown Department of Electrical and Computer Engineering University of Virginia Charlottesville VA USA School of Electrical and Computer Engineering Purdue University West Lafayette IN USA

In this paper, we consider the optimization of federated learning (FL) over a realistic wireless multiple-input multiple-output (MIMO) communication system with digital modulation and over-the-air computation (AirComp). In such a system, MIMO devices transmit their locally trained FL models to a parameter server (PS) using beamforming to maximize the number of devices scheduled for transmission. AirComp enables efficient wireless model aggregation by the PS in bandwidth-limited settings. However, wireless channel fading can produce distortions in AirComp-based FL. To tackle this challenge, we develop a novel aggregation scheme that combines digital modulation with AirComp to mitigate wireless fading while ensuring communication efficiency. We formulate this as a joint transmit-receive beamforming design optimization problem which dynamically adjusts the beamforming matrices to minimize the FL training loss with transmission errors. To solve this problem based on limited information at the PS, we employ an artificial neural network (ANN) to estimate the local FL models of all devices. Then, we derive a closed-form optimal design of the transmit and receive beamforming matrices based on predicted FL models. Numerical evaluations validate the advantages of the proposed methodology in terms of model training performance compared with baselines.

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A Probabilistic Public-Key Encryption with Ensuring Data Integrity in Cloud computing

A Probabilistic Public-Key Encryption with Ensuring Data Int...

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International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO)

作者： Mostefa Kara Konstantinos Karampidis Giorgos Papadourakis Abdelkader Laouid Muath AlShaikh LIAP Laboratory University of El Oued El Oued El Oued Algeria Department of Electrical and Computer Engineering Hellenic Mediterranean University Greece Computer Science Department College of Computing and Informatics Saudi Electronic University Riyadh KSA

researchers are working hard to face various challenges in the fast-moving field of network security and data exchange. When it comes to encryption techniques, efforts vary to address multiple issues such as computational speed, data size requirements, application scope, etc. that are driven by the purposes of collecting and sharing sensitive data that must be stored and processed securely. This paper proposes an efficient asymmetric cryptosystem that bases on the multiplication of plaintext by a variable public key. The origin of this key is constant, but for each encryption, a random number must be added to it. Therefore, a new public key each time is generated; in other words, a simulation of a one-time pad system. For each message, the sender generates a new secret twin of the public key; The receiver can decrypt all messages encrypted by different twins with a single private key. The proposed probabilistic scheme is linear coding and hence is lightweight, easy to execute, and practical in many areas. We consider the cloud to be an untrusted part that tries to disclose data when decoded by systems, the proposed method provides the additive homomorphic property and ensures data integrity when a homomorphic operation is performed by the cloud; thus, we realize verifiable partial homomorphic encryption.

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