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3rd International Conference on Intelligent Systems, Advanced Computing, and Communication, ISACC 2025

作者： Vaghela, Aarzoo Maruf, Padaya Meitei, Naorem Yaipharenba Singh, Laiphrakpam Dolendro National Institute of Technology Department of Computer Science and Engineering Assam Silchar India Indian Institute of Technology NineLabs Electronics & Electrical Engineering Assam Guwahati India

ISBN: (纸本)9798331523893

Traffic congestion poses a significant challenge in urban areas globally, resulting in wasted time, increased fuel consumption, and heightened pollution levels. Traditional traffic light systems often rely on fixed timers, failing to adjust to fluctuating traffic patterns and causing unnecessary delays. To tackle this issue, an adaptive traffic signal timer is designed to dynamically respond to real-time traffic conditions. The proposed system harnesses live camera feeds from traffic junctions and employs object detection techniques to analyze traffic density accurately. The proposed method represents a proactive approach to addressing urban congestion challenges, promising more efficient traffic management and improved commuting experiences for residents and commuters. A comprehensive simulation platform is developed to validate our system's efficacy and facilitate comparative analysis with existing static systems. © 2025 IEEE.

关键词： Vehicle detection

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A Novel Porcelain Fingerprinting Technique

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IEEE Transactions on Emerging Topics in Computing 2025年

作者： Wang, Chengjie Zhang, Yuejun Zhou, Ziyu Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo315211 China

Porcelain, as a significant cultural heritage, embodies the wisdom of human civilization. However, existing anti-counterfeiting and authentication technologies for porcelain are often unreliable and costly. This paper proposes a physical unclonable functions (PUF) design based on crack physical feature extraction for the anti-counterfeiting and authentication of Gold-Wire porcelain. The proposed method generates PUF information by extracting inherent physical deviations in the surface cracks of Gold-Wire porcelain. First, a standard crack extraction process is established using digital image processing to obtain crack information from the porcelain surface. Then, a physical feature extraction model based on the chain code encoding technique and the Delaunay triangulation technique is used to derive the physical feature values from the cracks. Subsequently, a PUF encoding algorithm is designed to convert these physical feature values into a PUF response. Finally, the security and reliability of the designed PUF are evaluated, and a PUF-based porcelain authentication protocol is developed. Experimental results show that the proposed PUF exhibits 50.16% uniqueness and 98.85% reliability, and the PUF data successfully passed the NIST randomness test, demonstrating that the proposed technology can effectively achieve low-cost, high-reliability anti-counterfeiting for commercial porcelain. © 2013 IEEE.

关键词： Porcelain

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An Overview of Web Services, Grid Computing and Grid Services 7th

An Overview of Web Services, Grid Computing and Grid Service...

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7th International Conference on Artificial Intelligence in Renewable Energetic Systems, IC-AIRES 2023

作者： Sara, Rekkal Kahina, Rekkal Department of Computer Science University of Badji Mokhtar Annaba Annaba Algeria Department of Electrical Engineering Salhi Ahmed University Center Naama Naama Algeria

ISBN: (纸本)9783031606311

Over the last few decades, the usefulness of Web services and Grid computing has grown. Their success stems from the fact that they address a wide range of issues pertaining to the management of information systems, the homogenization of data sources, the integration of applications, the exploitation of unused or little used resources, etc. As a result, the research and development activities surrounding them are extremely dynamic. Thus, Web services, Grid computing, and Grid services are explained in this article. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Grid computing

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The Low-Attenuation Endfire Leaky-Wave State on an Optically Transparent Lossy Film

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engineering 2024年第12期43卷 72-80页

作者： Ziheng Zhou Yongjian Zhang Yilin Zheng Ke Chen Yueming Gao Yuehe Ge Yue Li Yijun Feng Zhizhang(David)Chen College of Physics and Information Engineering Fuzhou UniversityFuzhou 350108China Department of Electronic Engineering Tsinghua UniversityBeijing 100084China School of Electronic and Information Engineering Soochow UniversitySoochow 215006China School of Electronic Science and Engineering Nanjing UniversityNanjing 210023China Department of Electrical and Computer Engineering Dalhousie UniversityHalifaxNS B3H 4R2Canada

The development of high-performance optically transparent radio frequency(RF)radiators is limited by the intrinsic loss issue of transparent conductive films(TCFs).Instead of pursuing expensive endeavors to improve the TCFs'electrical properties,this study introduces an innovative approach that leverages leaky-wave mode manipulation to mitigate the TCFs'attenuating effect and maximize the RF *** finding reveals that the precise control of the mode confinement on glass-coated TCFs can create a low-attenuation window for leaky-wave propagation,where the total attenuation caused by TCF dissipation and wave leakage is effectively *** observed low-attenuation leaky-wave state on lossy TCFs originates from the delicate balance between wave leakage and TCF dissipation,attained at a particular glass cladding *** leveraging the substantially extended radiation aperture achieved under suppressed wave attenuation,this study develops an optically transparent antenna with an enhanced endfire realized gain exceeding 15 dBi and a radiation efficiency of 66%,which is validated to offer competitive transmission performance for advancing ubiquitous wireless communication and sensing applications.

关键词： Antennas Endfire radiation Low attenuation Material losses Transparent conductive films

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Intelligent Monitoring and Management of Smart Buildings Using Machine Learning: Optimizing User Behavior and Energy Efficiency

Intelligent Monitoring and Management of Smart Buildings Usi...

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2023 Congress in computer science, computer engineering, and Applied Computing, CSCE 2023

作者： Nijim, Mais Kanumuri, Viswas Albetaineh, Hisham Goyal, Ayosh Texas A&m University-Kingsville Department of Electrical Engineering and Computer Science KingsvilleTX78363 United States

ISBN: (纸本)9798350327595

Smart buildings are a crucial component of smart cities and smart grids, contributing to a more intelligent urban environment. The efficient utilization of energy in buildings is now a significant concern for sustainable societies. Whether they are residential or industrial. Smart buildings consume the majority of the energy produced, but in the context of smart grids, they are also designed to generate energy and help stabilize demand. Even small fluctuations in peak demand can result in substantial budget saving for customers and utilities. In this research, we explore the applicability of machine learning (ML) methods for load forecasting in smart buildings using smart sensor data that infers user behavior. Here, we utilized a smart building dataset encompassing four floors, 51 rooms, and 255 integrated sensors. Each smart building room comprises five types of calculations, including a P IR Sensor that helps to capture motion, a Carbon dioxide concentration sensor to check the purity of air, a Sensor to calculate temperature, a humidity sensor to maintain good conditioning, and a luminosity sensor. By using this data from these sensors, we can optimize and manage the energy saving. To evaluate the prediction performance of the input variables, we used to compare them we use mean squares error, mean absolute error and root mean square error. © 2023 IEEE.

关键词： carbon dioxide sensor Humidity sensor luminosity sensor machine learning PIR sensor

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Detection of Perfect Stealthy Attacks on Cyber-Physical Systems Subject to Measurement Quantizations: A Watermark-Based Strategy

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 114-125页

作者： Yu-Ang Wang Zidong Wang Lei Zou Bo Shen Hongli Dong the College of Information Science and Technology Donghua University the Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of Education IEEE the College of Electrical Engineering and Automation Shandong University of Science and Technology the Department of Computer Science Brunel University London Uxbridge the Sanya Offshore Oil and Gas Research Institute Northeast Petroleum University the Artificial Intelligence Energy Research Institute Northeast Petroleum University Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum University

In this paper, the attack detection problem is investigated for a class of closed-loop systems subjected to unknownbutbounded noises in the presence of stealthy attacks. The measurement outputs from the sensors are quantized before transmission.A specific type of perfect stealthy attack, which meets certain rather stringent conditions, is taken into account. Such attacks could be injected by adversaries into both the sensor-toestimator and controller-to-actuator channels, with the aim of disrupting the normal data flow. For the purpose of defending against these perfect stealthy attacks, a novel scheme based on watermarks is developed. This scheme includes the injection of watermarks(applied to data prior to quantization) and the recovery of data(implemented before the data reaches the estimator).The watermark-based scheme is designed to be both timevarying and hidden from adversaries through incorporating a time-varying and bounded watermark signal. Subsequently, a watermark-based attack detection strategy is proposed which thoroughly considers the characteristics of perfect stealthy attacks,thereby ensuring that an alarm is activated upon the occurrence of such attacks. An example is provided to demonstrate the efficacy of the proposed mechanism for detecting attacks.

关键词： Attack detection cyber-physical systems (CPSs) perfect stealthy attacks watermark-based strategy

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Integrating Temporal Analysis with Hybrid Machine Learning and Deep Learning Models for Enhanced Air Quality Prediction 19

Integrating Temporal Analysis with Hybrid Machine Learning a...

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19th International Conference on Ubiquitous Information Management and Communication, IMCOM 2025

作者： Omer, Muhammad Ali, Sardar Jaffar Raza, Syed M. Le, Duc-Tai Choo, Hyunseung Dept. of Computer Science and Engineering Sungkyunkwan University Suwon Korea Republic of Dept. of AI Systems Engineering Sungkyunkwan University Suwon Korea Republic of James Watt School of Engineering University of Glasgow Glasgow United Kingdom Dept. of Electrical and Computer Engineering Sungkyunkwan University Suwon Korea Republic of

ISBN: (纸本)9798331507817

Air pollution remains a critical issue, adversely affecting public health and the environment. In this study, we utilize the Air Quality index dataset from Kaggle to analyze temporal and seasonal variations of key pollutants, specifically Carbon Monoxide (CO), Nitrogen Oxides (NOx), and Benzene (C6H6 ). Building upon this analysis, we predict Absolute Humidity (AH), a vital meteorological factor influencing pollutant dispersion, using Machine Learning (ML) and Deep Learning (DL) techniques. Three ML techniques, Linear Regression (LR), Random Forest (RF), and Support Vector Regression (SVR), and three DL techniques, Artificial Neural Network (ANN), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM), are employed for predicting AH. The results indicate that while the RF model achieved the lowest Mean Absolute Error (MAE) among ML methods (0.02), the CNN model, despite having an MAE of 0.04, demonstrated statistical superiority through paired t-tests and Wilcoxon signed-rank tests (p © 2025 IEEE.

关键词： Convolutional neural networks

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Analysis of Mobile Sensing Applications for Pandemic Monitoring

Analysis of Mobile Sensing Applications for Pandemic Monitor...

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2023 IEEE International Conference on Electro Information Technology, eIT 2023

作者： Tasnim, Samia Piner, Daniel The University of Toledo Department of Electrical Engineering and Computer Science ToledoOH United States Florida AandM University Department of Computer and Information Sciences TallahasseeFL United States

ISBN: (纸本)9781665493765

Mobile sensing applications are software programs that are written for mobile devices, such as smartphones and tablets, whose collective purpose is to turn the user and the device into a sensor for data collection. These applications require the user's approval to access certain features within the device and its operating system. Mobile sensing systems have a wide variety of applications to provide researchers with real data that they can use to solve problems such as air quality monitoring, contact tracing, medical resource allocation, among others. In this paper, our goal is to analyze different mobile sensing applications (app) that are particularly developed for pandemic monitoring. We classified such apps into two groups, one that performs contact tracing and the other is non-contact tracing applications. We present detailed description of several highly used pandemic monitoring mobile applications, noting pros and cons of each. © 2023 IEEE.

关键词： Coronavirus

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Energy-Efficient Cell-Free Massive MIMO with Wireless Fronthaul 58

Energy-Efficient Cell-Free Massive MIMO with Wireless Fronth...

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58th Asilomar Conference on Signals, Systems and computers, ACSSC 2024

作者： Topal, Ozan Alp Demir, Özlem Tuǧfe Björnson, Emil Cavdar, Cicek Kth Royal Institute of Technology Department of Computer Science Kista Sweden Tobb University of Economics and Technology Department of Electrical-Electronics Engineering Ankara Turkey

ISBN: (纸本)9798350354058

Cell-free massive MIMO improves the fairness among the user equipments (UEs) in the network by distributing many cooperating access points (APs) around the region while connecting them to a centralized cloud-computing unit that coordinates joint transmission/reception. However, the fiber cable deployment for the fronthaul transport network and activating all available antennas at each AP lead to increased deployment cost and power consumption for fronthaul signaling and processing. To overcome these challenges, in this work, we consider wireless fronthaul connections and propose a joint antenna activation and power allocation algorithm to minimize the end-to-end (from radio to cloud) power while satisfying the quality-of-service requirements of the UEs under wireless fronthaul capacity limitations. The results demonstrate that the proposed methodology of deactivating antennas at each AP reduces the power consumption by 50% and 84% compared to the benchmarks based on shutting down APs and minimizing only the transmit power, respectively. © 2024 IEEE.

关键词： Benchmarking

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Physics-Informed Neural Networks for Quantum Wavefunctions

Physics-Informed Neural Networks for Quantum Wavefunctions

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2024 International Conference on computer and Applications, ICCA 2024

作者： Mahmud, Istiak Asthana, Ayush Hoffmann, Mark Abdelhadi, Ahmeb School of Electrical Engineering & Computer Science University of North Dakota ND United States University of North Dakota Department of Chemistry ND United States

ISBN: (纸本)9798350367560

The wave functions and permitted energy levels of quantum systems, which characterize the probability distributions and particle behaviors, are able to be determined via the time-independent Schrodinger equation. Our research study introduces an experimental method of solving the time-independent Schrodinger equation by utilizing Physics-Informed Neural Networks (PINNs) with a customized loss function designed for output waveshape prediction. The technique makes use of PINNs' capacity to directly integrate physical rules into the learning process, assuring that the solutions follow the guiding principles of quantum mechanics. We forecast the associated wavefunctions for different energy levels (n states) and effectively solve the Schrodinger equation for distinct quantum states by using PINNs and a customized loss function. Our findings show that PINNs are a reliable and accurate way to represent the fine features of quantum wavefunctions, and they present a viable substitute for more conventional numerical techniques. This methodology not only improves computer performance but also offers more profound understanding of the behavior of systems in quantum mechanics, which may have implications for material science, nanotechnology, and quantum computing. © 2024 IEEE.

关键词： Schrodinger equation

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