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High-Speed Visible Light Communication Using Phenothiazine/Dimesitylborane Derivatives as Color Conversion Materials in Semipolar Micro-LED-Based White-Light Systems

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ACS Photonics 2024年第2期11卷 489-497页

作者： Sadhu, Annada Sankar Chen, Li-Yin Pai, Yi-Hua Hsieh, Chung-An Lin, Hao-Wu Chow, Chi-Wai Kuo, Hao-Chung Department of Photonics Institute of Electro-Optical Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Semiconductor Research Center Hon Hai Research Institute Taipei11492 Taiwan College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Department of Materials Science and Engineering National Tsing Hua University Hsinchu30013 Taiwan

Visible light communication (VLC) has emerged as a cutting-edge high-speed communication technology, poised to meet the surging capacity demands of 6G networks. Micro-light-emitting diodes (μLEDs) are considered as the light sources for achieving high-speed VLC, distinguished by their remarkable modulation bandwidths. However, achieving broadband white light emission hinges on the utilization of color-conversion materials with wide emission spectra. The transmission speed of the white-light system is inherently constrained by the characteristics of these color-conversion materials. In this work, we demonstrate CC-MP7 and CC-MP8, two derivatives of phenothiazine/dimesitylborane, as color conversion materials in a semipolar (20-21) micro-LED-based white-light system for high-speed VLC. The color conversion layers possess wide emission spectra, enabling them to achieve excellent color rendering performance when combined with blue micro-LEDs. CCMP7 and CC-MP8 demonstrate rapid photoluminescence decay characteristics, thereby enhancing the modulation bandwidth of the color-conversion layer in the white-light system. The resulting bandwidths achieved by CC-MP7 and CC-MP8 are 210 and 240 MHz, respectively, which represents an approximately 45-fold increase compared to ordinary phosphors. By combining semipolar (20-21) micro-LEDs with CC-MP7 and CC-MP8, the resulting white-light systems exhibit correlated color temperatures of 6860 and 7500 K, CIE coordinates of (0.3009, 0.3577) and (0.2958, 0.3129), and color-rendering indexes of 80 and 85, respectively. Furthermore, both systems offer high bandwidths of 1063 and 1084 MHz with the data rates of 1.72 Gbps and 1.74 Gbps using non-return-to-zero on-off keying (NRZ-OOK) format, respectively, indicating the significant potential of CC-MP7 and CC-MP8 for practical applications in VLC. © 2024 The Authors.

关键词： Bandwidth

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Continuous query-based data trading 24

Continuous query-based data trading

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2024 ACM SIGMETRICS/IFIP Performance Conference on Measurement and Modeling of computer Systems, SIGMETRICS/PERFORMANCE 2024

作者： Cheng, Jin Ding, Ningning Lui, John C.S. Huang, Jianwei School of Science and Engineering Shenzhen Institute of Artificial Intelligence and Robotics for Society The Chinese University of Hong Kong Shenzhen Shenzhen China Department of Electrical and Computer Engineering Northwestern University Evanston United States Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong Hong Kong

ISBN: (纸本)9798400706240

In the era of big data, traditional data trading methods designed for one-time queries on static databases fail to meet the demands of continuous query-based trading on streaming data, often resulting in repeated and inaccurate charges due to neglecting computation sharing in continuous query execution. To address this, we introduce CQTrade, the first trading framework tailored for continuous queries, which incorporates computation sharing across different time windows and queries, enhancing integration with existing trading systems. Our contributions include a theoretical analysis of computation-sharing techniques, the development of a general optimization problem to maximize seller revenue adaptable to various techniques, and the proposal of a branch-and-price algorithm to handle the problem's complexity. Our evaluation shows that the proposed framework improves the success rate of data trading by 12.8% and boosts the seller's revenue by an average of 28.7%, compared to the one-time query-based data trading methods used in the current data market. © 2024 Copyright held by the owner/author(s).

关键词： Integer programming

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Efficient conversion of acoustic vortex using extremely anisotropic metasurface

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Frontiers of physics 2024年第4期19卷 257-264页

作者： Zhanlei Hao Haojie Chen Yuhang Yin Cheng-Wei Qiu Shan Zhu Huanyang Chen Institute of Electromagnetics and Acoustics and Department of Physics College of Physical Science and TechnologyXiamen UniversityXiamen 361005China Department of Electrical and Computer Engineering National University of Singapore4 Engineering Drive 3117583Singapore Department of Mechanical and Electrical Engineering Xiamen UniversityXiamen 361005China Pen-Tung Sah Institute of Micro-Nano Science and Technology Xiamen UniversityXiamen 361005China

Vortex wave and plane wave,as two most fundamental forms of wave propagation,are widely applied in various research ***,there is currently a lack of basic mechanism to enable arbitrary conversion between *** this paper,we propose a new paradigm of extremely anisotropic acoustic metasurface(AM)to achieve the efficient conversion from 2D vortex waves with arbitrary orbital angular momentum(OAM)to plane *** underlying physics of this conversion process is ensured by the symmetry shift of AM medium parameters and the directional compensation of ***,this novel phenomenon is further verified by analytical calculations,numerical demonstrations,and acoustic experiments,and the deflection angle and direction of the converted plane waves are qualitatively and quantitatively confirmed by a simple *** work provides new possibilities for arbitrary manipulation of acoustic vortex,and holds potential applications in acoustic communication and OAM-based devices.

关键词： efficient wave conversion vortex wave plane wave orbital angular momentum acoustic metasurface

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Hybrid attention residual deep convolution learning network for bio medical image analysis

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Journal of Intelligent and Fuzzy Systems 2025年第4期48卷 537-554页

作者： Sundar Raj, A. Naidu, Paruchuri Chandra Babu Sivakumar, S. Senthilkumar, S. Department of Biomedical Engineering E.G.S. Pillay Engineering College Tamilnadu Nagapattinam India Department of Electrical and Electronics Engineering BSA Crescent Institute of Science and Technology Vandalur Tamilnadu Chennai India Department of Computer Science and Engineering Nehru Institute of Engineering and Technology Tamilnadu Coimbatore India Department of Electronics and Communication Engineering E.G.S. Pillay Engineering College Tamilnadu Nagapattinam India

Biomedical image analysis has progressed significantly with the integration of artificial intelligence, presenting new opportunities for early diagnosis and treatment of diseases with high mortality rates, such as skin cancer. This research work introduces a novel Hybrid Attention Residual Deep Convolution Learning (HARDCL) Model designed to enhance the accuracy of skin lesion classification, which is often challenging due to the subtle characteristics of lesions. The HARDCL Network employs an innovative hybrid attention mechanism within a residual learning framework, effectively distinguishing between benign and melanoma skin lesions with a high degree of precision. The encoder-decoder network segments the lesion from dermoscopic images, followed by feature extraction and classification, achieving a maximum accuracy of 97.11%, precision of 98.10%, recall of 98.81%, and an F1-score of 98.45%. This performance surpasses conventional deep learning algorithms such as AlexNet, InceptionV3, and ResNet18, demonstrating the effectiveness of the attention-based features in identifying critical lesion characteristics. However, despite its strengths, the HARDCL Network’s computational intensity and the need for a substantial dataset for optimal training highlight areas for further refinement. The proposed network advances the field of skin cancer diagnostics, offering a robust tool for medical professionals and setting a foundation for future enhancements in automated biomedical image analysis techniques. © 2025 – IOS Press. All rights reserved.

关键词： Deep learning

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Dynamic Payback Period Estimation for Solar Power Plants Through ML Based Solar Power Generation Forecasts

Dynamic Payback Period Estimation for Solar Power Plants Thr...

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2024 International Conference on System, Computation, Automation and Networking, ICSCAN 2024

作者： Singh, Tarun Raj Prajapati, Aryan Himmatlal Kumar, Nishant Indian Institute of Technology Jodhpur Department of Computer Science and Engineering Jodhpur India Indian Institute of Technology Jodhpur Department of Electrical Engineering Jodhpur India

ISBN: (纸本)9798331510022

Substantial capital is required to invest in solar power plants, which puts estimation of the payback period accurately at primary concern for stakeholders. In this paper, we proposed a novel method to estimate the payback period of a 10MW solar power plant through forecasting solar power generation by an optimized XGBoost Machine learning model. We began by forecasting the Global Horizontal Irradiance (GHI) and temperature with a temporal resolution of 1 hour for the upcoming year. Using these forecasted values, the expected power output of a single solar panel with given properties is calculated, which was further scaled for the entire plant to estimate the total power generated for entire year with a resolution of 1 hour. Monthly income from the plant is estimated by considering current electricity prices and the predicted power of each month. Plant investments accounted for various costs, including panels, land acquisition, maintenance, wiring, and equipment, while also considering compound interest on the initial investment (compounded monthly) with monthly loan repayments. By considering different scenarios, we determined the payback period by varying factors such as interest rates, land costs, panel efficiency, and maintenance expenses. Our findings offer offer valuable insights into the financial feasibility and potentiality of solar power plants and demonstrate how these factors influence the payback period of such plants. © 2024 IEEE.

关键词： Decentralized finance

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A Proactive Crowdsourcing Framework for Fake Base Station Detection and Avoidance 15

A Proactive Crowdsourcing Framework for Fake Base Station De...

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15th IEEE Annual Computing and Communication Workshop and Conference, CCWC 2025

作者： Saad, Omar A. Etman, Ahmed A. Abdel-Malek, Mai A. Azab, Mohamed Alexandria University Faculty of Engineering Department of Computer and Communications Engineering Alexandria Egypt The University of Arizona Department of Electrical and Computer Engineering AZ United States Virginia Military Institute Department of Computer and Information Sciences VA United States

ISBN: (纸本)9798331507695

With next-generation communication technologies becoming more integrated into critical infrastructure, securing these networks against sophisticated threats has become paramount. One of the most persistent threats to this communication is the growing presence of fake base stations (FBS). These FBSs are malicious entities that pose as legitimate base stations to intercept, manipulate, or exploit mobile communications, leading to serious privacy breaches. While some existing literature addresses the detection of such malicious entities, detecting FBSs has traditionally been the responsibility of network operators, who rely on tools like signal strength analysis and radio frequency (RF) monitoring to identify unusual patterns or rogue signals. However, these centralized methods often struggle to detect FBSs in complex environments characterized by high mobility, dense urban areas, and sophisticated spoofing techniques. This paper proposes a scalable and pervasive blockchain-based crowd-sourcing mechanism to enable extensive device participation in identifying FBSs. In a fully automated and distributed manner, the proposed platform uses vetted and verified information recorded on the blockchain to identify and report suspicious FBSs in the area. This allows other users to dissociate from these malicious entities automatically. A reputation management system is also employed to ensure the reliability and accountability of participating users. Using qualitative and quantitative evaluations, the proposed approach demonstrated effectiveness and efficiency in achieving all targeted goals. © 2025 IEEE.

关键词： Crowdsourcing

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Multimodal Human Detection using RGB, Thermal and LiDAR modalities for Robotic Perception

Multimodal Human Detection using RGB, Thermal and LiDAR moda...

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IEEE International Conference on Automation Science and engineering (CASE)

作者： Kennedy O. S. Mota Luís Garrote Cristiano Premebida Department of Electrical and Computer Engineering Institute of Systems and Robotics University of Coimbra Portugal

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

People detection is a relevant research topic in artificial perception with wide range of applications from security, surveillance, robotics to autonomous driving. Overcoming challenges in this field involves advanced algorithms, combination of machine learning approaches, as well as the use of sensory data e.g., from cameras and LiDARs. This work addresses the problem of people detection using YOLO, a state-of-the-art object detection method, trained on three distinct data sources LiDAR, RGB (color) and ‘thermal’ (long-wave infra-red) images. The rationale for combining multiple-sensory representation relies on the assumption that each sensor has its own advantages and disadvantages, but together they normally complement each other - specially in real-world conditions. LiDAR contributes to a physically-interpretable mapping of the environment, providing precise information regarding size/dimension and location of the objects, while RGB and thermal provide relevant textural features. The sensors have been calibrated w.r.t. each other thus, allowing the LiDAR’s point-clouds to be projected into the image plane, followed by an up-sampling step, to create dense-depth maps (DM) that enable direct use of the YOLO framework. To support the experiments, a new multi-sensory dataset has been collected using a mobile robot. Besides single-modality models, this paper also explores early and late-fusion strategies. Finally, the new dataset has been made available in a Github repository 1 .

关键词： YOLO Laser radar Machine learning algorithms Surveillance Soft sensors Thermal engineering Robot vision systems Security Mobile robots Software development management

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Multi Agent Coordination Strategy for Collaborative Exploration of GPS-denied Environments

Multi Agent Coordination Strategy for Collaborative Explorat...

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Patel, Akash Kanellakis, Christoforos Nikolakopoulos, George Luleå University of Technology Robotics & Ai Team Department of Computer Electrical and Space Engineering LuleåSE-97187 Sweden

ISBN: (纸本)9798350325706

Autonomous exploration and mapping of unknown subterranean areas using fleet of Micro Aerial Vehicles (MAVs) have achieved great interest in the past decade. The application of such research direction is extended beyond mining industry for example the exploration of potential lava tubes and caves on Mars using Martian MAVs. In this article we present a Collaborative Exploration and Mapping approach for exploration of large scale multi-branched virtual cave environment using multiple MAVs. An important aspect of such approach is to establish a decent collaboration with minimal information exchange among agents such that the exploration area can be maximized by preventing multiple agents covering overlapping parts of the environment. The collaborative exploration approach in this article is based on sharing local traversable frontier points as information among agents such that the each agent can identify the target areas in order to extend global map in an efficient manner. This work proposes a novel baseline collaborative exploration approach for optimal target area selection with a resource constrained MAVs in order to efficiently as well as rapidly explore subterranean environment. Extensive simulations are performed to validate the proposed collaborative strategy in order to establish a multi agent coordinated exploration-coverage mission. © 2023 IEEE.

关键词： Coordinated Exploration Navigation Unmanned Aerial Vehicles

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Dynamic Evolutionary Game-based Modeling,Analysis and Performance Enhancement of Blockchain Channels

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IEEE/CAA Journal of Automatica Sinica 2023年第1期10卷 188-202页

作者： PeiYun Zhang MengChu Zhou ChenXi Li Abdullah Abusorrah IEEE the School of Computer Science Nanjing University of Information Science&TechnologyNanjing 210044China the Helen and John C.Hartmann Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA the School of Computer and Information Anhui Normal UniversityWuhu 241003China the Department of Electrical and Computer Engineering Faculty of Engineeringand Center of Research Excellence in Renewable Energy and Power SystemsKing Abdulaziz UniversityJeddah 21481Saudi Arabia

The recent development of channel technology has promised to reduce the transaction verification time in blockchain *** transactions are transmitted through the channels created by nodes,the nodes need to cooperate with each *** one party refuses to do so,the channel is unstable.A stable channel is thus *** nodes may show uncooperative behavior,they may have a negative impact on the stability of such *** order to address this issue,this work proposes a dynamic evolutionary game model based on node *** model considers various defense strategies'cost and attack success ratio under *** can dynamically adjust their strategies according to the behavior of attackers to achieve their effective *** equilibrium stability of the proposed model can be *** proposed model can be applied to general channel *** is compared with two state-of-the-art blockchain channels:Lightning network and Spirit *** experimental results show that the proposed model can be used to improve a channel's stability and keep it in a good cooperative stable *** its use enables a blockchain to enjoy higher transaction success ratio and lower transaction transmission delay than the use of its two peers.

关键词： Blockchain channel network evolutionary game malicious behavior secure computing stability analysis

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Optimizing NOMA Transmissions to Advance Federated Learning in Vehicular Networks

Optimizing NOMA Transmissions to Advance Federated Learning ...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Chen, Ziru Ni, Zhou Guan, Peiyuan Wang, Lu Cai, Lin X. Hashemi, Morteza Li, Zongzhi Illinois Institute of Technology Department of Electrical and Computer Engineering Chicago United States University of Kansas Department of Electrical Engineering and Computer Science Lawrence United States University of Oslo Department of Informatics Oslo Norway Illinois Institute of Technology Department of Civil Engineering Chicago United States

ISBN: (纸本)9798350351255

Diverse critical data, such as location information and driving patterns, can be collected by IoT devices in vehicular networks to improve driving experiences and road safety. However, drivers are often reluctant to share their data due to privacy concerns. The Federated Vehicular Network (FVN) is a promising technology that tackles these concerns by transmitting model parameters instead of raw data, thereby protecting the privacy of drivers. Nevertheless, the performance of Federated Learning (FL) in a vehicular network depends on the joining ratio, which is restricted by the limited available wireless resources. To address these challenges, this paper proposes to apply Non-Orthogonal Multiple Access (NOMA) to improve the joining ratio in a FVN. Specifically, a vehicle selection and transmission power control algorithm is developed to exploit the power domain differences in the received signal to ensure the maximum number of vehicles capable of joining the FVN. Our simulation results demonstrate that the proposed NOMA-based strategy increases the joining ratio and significantly enhances the performance of the FVN. Index Terms - Federated Vehicular Network, NOMA © 2024 IEEE.

关键词： Data privacy

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