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IEEE Transactions on Industrial Cyber-Physical Systems 2024年 2卷 615-625页

作者： Lien, Shao-Yu Tseng, Chih-Cheng Hung, Wei-Cheng Tsai, Cheng-You Liu, Ting-Yu Deng, Der-Jiunn Lin, Yuan-Chun Lin, Shih-Cheng Chang, Chia-Chan Chang, Sheng-Fuh Institute of Intelligent Systems National Yang Ming Chiao Tung University Tainan711010 Taiwan Department of Electrical Engineering National Ilan University Ilan260007 Taiwan Department of Computer Science and Information Engineering National Chung Cheng University Chiayi621301 Taiwan Department of Computer Science and Information Engineering National Changhua University of Education Changhua50074 Taiwan Department of Electrical Engineering National Chung Cheng University Chiayi621301 Taiwan

The reconfigurable intelligent surface (RIS) steering reflective beam directions toward a target mobile user equipment (UE) has been a promising technology for coverage enhancement and physical-layer (PHY) security to avoid signal eavesdroppers and jammers. However, tracking and predicting the moving trajectory of UE demand significant computing burdens unaffordable to the RIS. Performing beam steering computations on the radio access network (RAN) intelligent controller in the open RAN (O-RAN) architecture therefore emerges as a revolutionary paradigm. In this paper, we propose a PHY-secured beam steering design based on a pre-processing-based Kalman filter algorithm. Through a pre-processing phase to derive the radiation feature, the proposed design accurately tracks the position of the mobile UE and quickly recovers the position search while position tracking fails. Through practical field-try experiments, we justify the capability of O-RAN RIC-empowered RIS for PHY security. © 2013 IEEE.

关键词： Radio access networks

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A proactive load balanced handoff scheme for vehicular ad-hoc networks

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International Journal of Vehicle Information and Communication Systems 2023年第4期8卷 345-362页

作者： Madli, Rajeshwari Varaprasad, G. Department of Computer Science and Engineering B.M.S. College of Engineering Bengaluru Karnataka Bangalore India

The embracement of the wireless technology by the automobile industry has led to novel research interests in the field of Vehicular Ad-hoc Networks (VANETs). In addition to ad-hoc mode, a VANET supports infrastructure mode of communication, which provides access to internet services such as Hyper Text Transfer Protocol (HTTP), Voice over Internet Protocol (VoIP) and File Transfer Protocol (FTP), through access points known as Road Side Units (RSU). Vehicles can benefit from these services when associated with an RSU. However, because of uneven distribution and high mobility of vehicles, some RSUs are overloaded, resulting in network congestion and affecting the packet delivery ratio and throughput. This paper proposes a proactive load-balanced handoff scheme, in which vehicles evade overloaded RSUs and choose an RSU based on signal strength, network load and service reliability. Simulation results indicate that vehicles using the load-balanced handoff method, experience a higher packet delivery ratio and throughput. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Vehicular ad hoc networks

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Real-time Steering Control algorithm based on Lane Segmentation image using Monocular view for Map-less Driving

Real-time Steering Control algorithm based on Lane Segmentat...

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2023 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2023

作者： Lee, Si Woo Lee, Jinsun Hong, HyeongKeun Jeon, Jae Wook Sungkyunkwan University Department of Computer Science and Engineering Suwon Korea Republic of Sungkyunkwan University Department of Electrical and Computer Engineering Suwon Korea Republic of

ISBN: (纸本)9798350344318

Growing interest in integrating in-vehicle data processing and artificial intelligence (AI) has significantly improved performance. This improvement extends to technologies like object detection, with rapid progress, and pixel-based segmentation research in various directions. While research on steering value processing using AI models is ongoing, model-centric studies continue to garner attention. This paper discusses a framework for obtaining lane gradients using instance segmentation techniques among segmentation methods. It emphasizes the development of image processing independent of control systems or single-model limitations, proposes a service-oriented methodology for better management and development, and outlines the utilization of pre-trained instance segmentation models. © 2023 IEEE.

关键词： Object detection

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Design of an RF-CMOS Switched-Capacitor Power Amplifier for NB-IoT RF Transceivers

Design of an RF-CMOS Switched-Capacitor Power Amplifier for ...

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2023 International Young Engineers Forum in electrical and computer engineering, YEF-ECE 2023

作者： Santos, Ana Isabel Pedro Oliveira, Joao NOVA School of Science and Technology Department of Electrical and Computer Engineering Caparica Portugal Centre of Technology and Systems CTS-UNINOVA Department of Electrical and Computer Engineering Caparica Portugal

ISBN: (纸本)9798350300420

The paper presents the implementation of a Switched Capacitor Power Amplifier (SCPA) to be integrated into a Narrowband Internet of Things (NB-IoT) Transceiver. The SCPA is designed to operate at a frequency of 0.9GHz and aiming the maximum output power allowed by the standard of 23dBm. All the blocks within the SCPA were developed using RF components of a standard 130nm CMOS process, with a 1.2V/2.4V supply voltage. Results show that the SCPA is able to produce a maximum output power of 15.61dBm with a maximum Power-Added Efficiency (PAE) of 26.52% and a Total Harmonic Distortion (THD) of 0.68%. The measured HD2 and HD3 are-70.23dBc and-43.41dBc, respectively. Additional Process, Voltage and Temperature (PVT) corners and Monte Carlo simulations indicate the SCPA operates properly when subject to different conditions and mismatches. Besides the SCPA, a 16 QAM modulation stage is designed in VerilogA in order to evaluate the performance of the RF PA when a sequence of symbols is transmitted. © 2023 IEEE.

关键词： Power amplifiers

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Leveraging Large Language Models to Identify the Values Behind Arguments 2nd

Leveraging Large Language Models to Identify the Values Be...

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2nd International Workshop on Value engineering in Artificial Intelligence, VALE 2024

作者： Senthilkumar, Rithik Appachi Homayounirad, Amir Siebert, Luciano Cavalcante Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft Netherlands

ISBN: (纸本)9783031854620

Human values capture what people and societies perceive as desirable, transcend specific situations and serve as guiding principles for action. People’s value systems motivate their positions on issues concerning the economy, society and politics among others, influencing the arguments they make. Identifying the values behind arguments can therefore help us find common ground in discourse and uncover the core reasons behind disagreements. Transformer-based large language models (LLMs) have exhibited remarkable performance across language generation and analysis. However, leveraging LLMs in sociotechnical systems that assist with discourse and argumentation necessitates systematically evaluating their ability to analyse and identify the values behind arguments, an under-explored research direction. Using a multi-level human value taxonomy inspired by the Schwartz Theory of Basic Human Values, we present a systematic and critical evaluation of GPT-3.5-turbo in human value identification from a dataset of multi-cultural arguments, across the zero-shot, few-shot and chain-of-thought prompting strategies, carrying forward from prior research on this task which leveraged a fine-tuned BERT model. We observe that prompting strategies exhibit performance levels close to, but still behind fine-tuning for value classification. We also detail some challenges associated with value classification with LLMs, offering potential directions for future research. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Human Values Large Language Models Prompting

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Quantum Inspired DC Optimal Power Flow Under Frequency Constraint

Quantum Inspired DC Optimal Power Flow Under Frequency Const...

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2025 IEEE Texas Power and Energy Conference, TPEC 2025

作者： Magar, Madan Rana Nguyen, Nga University of Wyoming Electrical Engineering and Computer Science LaramieWY82071 United States

ISBN: (纸本)9798331541125

This study uses quantum-inspired techniques to ad-dress the DC optimal power flow problem considering frequency constraints. Although numerous analytical and data-driven meth-ods have been developed to solve DC-OPF under stability security constraints, this problem has never been addressed in the context of quantum computing. This paper proposed a novel algorithm based on quantum computing principles that improves both the accuracy and efficiency of solving DC-OPF solutions while dealing with the complexity of frequency stability requirements. This method simplifies the frequency security constraint by converting it into an inertia constraint, incorporating all variables from the frequency deviation equation. This transformed constraint is then integrated into the DC-OPF model. This method will be tested on the IEEE 14 bus system using the IBM qiskit simulation tool. The alternate direction method of multipliers is used as a quantum optimization technique and validates the results against classical methods. Our findings show that this quantum-inspired approach effectively optimizes power flow and maintains frequency stability, indicating its significant potential to enhance modern power systems for more resilient and efficient energy management. © 2025 IEEE.

关键词： Quantum computers

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ScanSavant: Malware Detection for Android Applications with Explainable AI

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2024年第19期18卷 171-181页

作者： Navaneethan, S. Udhaya Kumar, S. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Tamil Nadu Chennai India

Mobile devices face SQL injection, malware, and web-based threats. Current solutions lack real-time detection. This paper introduces an Android app with advanced algorithms for real-time threat scanning. During testing, our application detected 94% of SQL injection attempts, outperforming the 86% average detection rate in similar studies. For malware analysis, it achieved a 97% detection accuracy on a dataset of infected files, higher than the industry standard of 93%. Additionally, our app can detect 85 malware variants and assign 15 attributes (***.8, ***, ***, ***, ***, ***, ***-2017-0143, ***, ***, Backdoor. DarkComet, ***, ***, ***, ***32. Necurs, and ***) to some malwares, providing detailed analysis for better threat management. The application effectively scans both EXE and APK files, ensuring com-prehensive protection. When assessing website links, the application identified security risks with 96% accuracy, demonstrating its capability in managing web-based threats. This app detects SQL injections, analyses malware, and assesses website security, bolstering cyber defence with user-friendly features and top-notch threat mitigation. © 2024, International Federation of engineering Education Societies (IFEES). All rights reserved.

关键词： Android malware

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Solar Irradiance Forecasting Using Deep Learning: Impact of Hyperparameter Optimization

Solar Irradiance Forecasting Using Deep Learning: Impact of ...

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2025 IEEE Texas Power and Energy Conference, TPEC 2025

作者： Humagain, Sanjeeb Nguyen, Nga University of Wyoming Electrical Engineering and Computer Science LaramieWY82071 United States

ISBN: (纸本)9798331541125

The balance of supply and demand is pivotal in ensuring efficient and reliable power grid utilization. With the growth of demand, the integration of renewable energy resources (RERs) into the power grid is increasing phenomenally. Because of the random nature of RERs, the power grid is vulnerable to frequency and voltage stability issues. Enhancing the performance of generation forecasts is one of the efficient ways to deal with these issues. An accurate generation forecast will facilitate better planning to reduce the impacts caused by the unpredictable nature of RERS. Implementing deep learning (DL) methods in forecasting is becoming more popular as it has been proven to generate forecasts with high accuracy. This paper implements a DL method for solar irradiance forecasting using hyperparameter optimization (HPO). Solcast dataset is utilized to validate the efficacy of the proposed method. The model performance with activation functions, rectified linear unit, Leaky ReLu, and exponential linear unit with and without HPO is compared. Additionally, Bayesian and random search optimization methods are implemented, and their accuracy is also compared. The result shows the significant enhancement of the model performance after HPO, proving its importance in deep learning applications. Finally, the activation function and the optimization method based on accuracy and time of execution are suggested. © 2025 IEEE.

关键词： Solar irradiance

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Sum-Difference Analysis Based Design for Third-Order Sparse Arrays 2

Sum-Difference Analysis Based Design for Third-Order Sparse ...

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2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024

作者： Guo, Haodong Chen, Hua Liu, Wei Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo China The Hong Kong Polytechnic University Department of Electrical and Electronic Engineering Hong Kong

ISBN: (纸本)9798331515669

Recently, third-order cumulants (TOCs) as a non-conventional odd-order statistics, has been introduced to direction-of-arrival (DOA) estimation with the third-order nested array (TONA), which significantly increases the number of uniform degrees-of-freedom (uDOFs) and can even be comparable to the fourth-order cumulant approach. In this paper, through analysis of the second-order sum-difference co-array, a third-order sparse linear array (SLA) design scheme suitable for TOCs is proposed, which can extend the commonly used second-order SLAs to the third-order. By selecting an appropriate generator array, the derived third-order SLA has far more uDOFs than the existing TONA, greatly improving its DOA estimation accuracy. © 2024 IEEE.

关键词： Direction of arrival

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Position: AI/ML Influencers Have a Place in the Academic Process 41

Position: AI/ML Influencers Have a Place in the Academic Pro...

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41st International Conference on Machine Learning, ICML 2024

作者： Weissburg, Iain Xie Arora, Mehir Wang, Xinyi Pan, Liangming Wang, William Yang Department of Electrical and Computer Engineering University of California Santa Barbara United States Department of Computer Science University of California Santa Barbara United States

As the number of accepted papers at AI and ML conferences reaches into the thousands, it has become unclear how researchers access and read research publications. In this paper, we investigate the role of social media influencers in enhancing the visibility of machine learning research, particularly the citation counts of papers they share. We have compiled a comprehensive dataset of over 8,000 papers, spanning tweets from December 2018 to October 2023, alongside controls precisely matched by 9 key covariates. Our statistical and causal inference analysis reveals a significant increase in citations for papers endorsed by these influencers, with median citation counts 2-3 times higher than those of the control group. Additionally, the study delves into the geographic, gender, and institutional diversity of highlighted authors. Given these findings, we advocate for a responsible approach to curation, encouraging influencers to uphold the journalistic standard that includes showcasing diverse research topics, authors, and institutions. Copyright 2024 by the author(s)

关键词： Adversarial machine learning

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