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30th IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS 2024

作者： Kang, Woosung Lee, Jinkyu Lee, Youngmoon Oh, Sangeun Lee, Kilho Chwa, Hoon Sung DGIST Dept. of Electrical Engineering and Computer Science Korea Republic of Dept. of Computer Science and Engineering Korea Republic of Hanyang University Dept. of Robotics Korea Republic of Ajou University Department of Software and Computer Engineering Korea Republic of School of AI Convergence Soongsil University Korea Republic of

ISBN: (纸本)9798350358414

The increasing complexity and memory demands of Deep Neural Networks (DNNs) for real-Time systems pose new significant challenges, one of which is the GPU memory capacity bottleneck, where the limited physical memory inside GPUs impedes the deployment of sophisticated DNN models. This paper presents, to the best of our knowledge, the first study of addressing the GPU memory bottleneck issues, while simultaneously ensuring the timely inference of multiple DNN tasks. We propose RT-Swap, a real-Time memory management framework, that enables transparent and efficient swap scheduling of memory objects, employing the relatively larger CPU memory to extend the available GPU memory capacity, without compromising timing guarantees. We have implemented RT-Swap on top of representative machine-learning frameworks, demonstrating its effectiveness in making significantly more DNN task sets schedulable at least 72% over existing approaches even when the task sets demand up to 96.2% more memory than the GPU's physical capacity. © 2024 IEEE.

关键词： Deep neural networks

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Using Ant Colony Optimised Algorithms for Shortest Path Exploration by Robots 2

Using Ant Colony Optimised Algorithms for Shortest Path Expl...

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2nd IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2024

作者： Singh, Aashdeep Dhawan, Sakshi Verma, Jyoti Singh, Gurpreet Kaur, Amanpreet Dept. of Computer Science & Engineering Punjab Rajpura India Dept. of Computer Application Punjab Rajpura India Chitkara University Institute of Engineering & Technology Dept. of Computer Science & Engineering Punjab Rajpura India

ISBN: (纸本)9798350360523

In the realm of robotics and autonomous systems, efficient path planning is a critical aspect for optimizing resource utilization and achieving mission objectives. This study explores the application of Ant Colony Optimized (ACO) algorithms to enhance the efficiency of robots in navigating and exploring unknown environments. Inspired by the foraging behavior of ants, ACO algorithms are employed to find the shortest paths by leveraging pheromone communication and decentralized decision-making. Ant Colony Optimization is then introduced as a bio-inspired solution to address these challenges. The experimental results demonstrate the capability of the ACO algorithm to efficiently explore complex environments, adapt to changes in the surroundings, and converge to optimal paths. Insights gained from these analyses contribute to the refinement of the ACO algorithm for diverse robotic applications. The findings of this research have practical implications for the development of autonomous robots operating in real-world scenarios, such as search and rescue missions, environmental monitoring, and surveillance. This study provides a valuable foundation for the integration of bio-inspired algorithms in robotics, advancing the state-of-the-art in autonomous exploration and path planning. © 2024 IEEE.

关键词： Motion planning

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Adaptive Central Acceleration With Variance Control for Robust Federated Optimization in Ubiquitous Intelligence

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IEEE Internet of Things Journal 2025年第12期12卷 21379-21393页

作者： Zhao, Lei Lu, Wu-Sheng Cai, Lin University of Victoria Dept. of Electrical and Computer Engineering VictoriaBCV8P 5C2 Canada

Federated Learning (FL) in Intelligent Internet of Things (IIoT) environments faces critical challenges, including sparse client participation, non-IID local data distributions, and unreliable communication, which lead to slow convergence and high variance in global updates. To address these issues, we propose Adaptive Central Federated Momentum Optimization (ACFMO), an optimization framework that enhances FL efficiency and stability under constrained participation. ACFMO integrates an adaptive central acceleration mechanism that dynamically adjusts momentum updates based on real-time client availability, preventing instability and ensuring smoother global model updates. Additionally, a variance-controlled local updating strategy refines client contributions, mitigating high variance caused by infrequent and heterogeneous updates. Extensive experiments across diverse FL scenarios demonstrate that ACFMO significantly accelerates convergence, reduces communication overhead, and improves model stability compared to state-of-the-art FL methods, making it particularly well-suited for real-world IIoT deployments where network and computational resources are constrained. © 2025 IEEE.

关键词： Federated learning

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Parallelized 0/1 Knapsack Algorithm Optimization in CPU-GPU-Based Heterogeneous System with Algorithm-based Fault Tolerance 18

Parallelized 0/1 Knapsack Algorithm Optimization in CPU-GPU-...

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18th International Conference on Ubiquitous Information Management and Communication, IMCOM 2024

作者： Abid, Marzan Binte Shaha, Shuvo Kabir, Upama Arefin, Md. Fahim University of Dhaka Dept. of Computer Science and Engineering Bangladesh

ISBN: (纸本)9798350331011

A heterogeneous high-performance computing (HPC) system is an aggregation of CPUs and GPUs through high-speed interconnection. As graphics processing units (GPUs) can conduct rapid mathematical and vector operations due to their hardware properties, GPU-based heterogeneous systems can optimize algorithms that show data parallelism. Since the dynamic programming (DP) solution of the 0/1 knapsack algorithm is inherently data-parallel, this paper optimized the algorithm to maximize the advantages of a GPU-based parallel environment. Furthermore, this research identified that the algorithm was well suited to four distinct GPU-launch approaches. Among them, the "single-cell calculation by single thread with a single kernel launch"approach outperforms others by reducing the complexity from O(n∗w) to O(n). Besides, these HPC systems are susceptible to the slightest of errors. Checkpoint recovery (CP/R) is the most commonly used fault tolerance and recovery system, which suffers from huge checkpoint and recovery overhead. To reduce this overhead in CPU-GPU-based heterogeneous systems, an algorithm-based fault tolerance (ABFT) technique has been proposed for a particular class of algorithm: 0/1 knapsack. The experimental results verify the feasibility of the proposed ABFT technique and demonstrate that the system can recover from failures with minimal overhead. © 2024 IEEE.

关键词： Graphics processing unit

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Electromagnetic Near-Field Codebook Design for General Antenna Arrays 58

Electromagnetic Near-Field Codebook Design for General Anten...

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

作者： Castellanos, Miguel Rodrigo Heath, Robert W. University of Tennessee Dept. of Electrical Engineering and Computer Science KnoxvilleTN37966 United States University of California San Diego Dept. of Electrical and Computer Engineering La Jolla CA92093 United States

ISBN: (纸本)9798350354058

Precoding codebooks facilitate efficient channel state information acquisition in high-dimensional MIMO systems. Most codebook designs, however, are agnostic to the antenna array composition and the underlying gain pattern profiles. We leverage an electromagnetic characterization of the antenna array manifold to generalize the codebook design problem. Specifically, we formulate the codebook design problem in a manner that incorporates polarization, near-field propagation and the antenna array characteristics. Our proposed approach is also flexible enough to adapt to different antenna types and even to heterogenous arrays. Our numerical results demonstrate that the electromagnetic-based codebooks achieve higher beamforming gains than approaches that neglect antenna effects. © 2024 IEEE.

关键词： Channel state information

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A Novel Approach for Recognizing Real-Time American Sign Language (ASL) Using the Hand Landmark Distance and Machine Learning Algorithms 9

A Novel Approach for Recognizing Real-Time American Sign Lan...

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9th IEEE International Women in engineering (WIE) Conference on electrical and computer engineering, WIECON-ECE 2023

作者： Ahmed, Shahan Kar, Sumit Kumar Basak, Sarnali North South University Dept. of Electrical and Computer Engineering Dhaka Bangladesh Jahangirnagar University Dept. of Computer Science and Engineering Savar Bangladesh

ISBN: (纸本)9798350319651

Several sign language recognition techniques and models have been prevalent to ease the communication gap between people with hearing disabilities and people who don't understand sign language. The proposed model is a vision-based approach aims to find a better system to recognize sign gestures using the distance between hand landmarks. This process doesn't rely on complex image processing techniques, making it robust towards challenging lighting conditions, noisy backgrounds, and image resolution. To accurately detect 26 American Sign Language (ASL) letters, the model only extracts 12 features. As a result, it can recognize the letters more rapidly than the traditional image-based method and can be trained with lesser computational resources. Therefore, low-configured devices can likewise utilize the method described in this paper. Despite a number of sign language recognition methods are currently in widespread use, the inability of those models to handle the orientation of some specific letter combinations (D, G, U, H, I, and J) has a severe effect on their overall effectiveness. This proposed algorithm, added with features 11 and 12, can solve the anomalies in the orientation of similar pair alphabets. Therefore, the four most popular algorithms, Naive Bayes, Support Vector Machine (SVM), Random Forest, and K-Nearest Neighbors (KNN), have been used to predict the letters of the American Sign Language alphabet. Regardless of the algorithm employed, the model was highly efficient because of the carefully curated dataset, which included attributes directly related to the ASL alphabet signs. SVM demonstrated the best accuracy among these algorithms, outperformina the others by 97 %. © 2023 IEEE.

关键词： Support vector machines

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Demystifying PDFs: Emerging AI for text generation and operation on PDF 4

Demystifying PDFs: Emerging AI for text generation and opera...

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4th IEEE Asian Conference on Innovation in Technology, ASIANCON 2024

作者： Sharma, Ashish Baveja, Mannu Kanikicherla, Suhaj Kaushik, Devansh Sharma, Yashuman Jessica, Jessica Chandigarh University Dept of Electrical Engineering Mohali India Chandigarh University Dept. of Computer Science Mohali India

ISBN: (纸本)9798350354218

AI is considered as most disruptive language and revolutionized various sectors with its ability analyze data with its large language model. incapability of other AI to read PDF and accept prompt and do text generation using their large language *** work is based on proposing a new technique to integrate it into current AI. It will eliminate the need manual work of copy pasting Portable Document Format data to AI for prompt. In this can rely on Technologies Like Optical character recognition for reading images to text but challenging part is Portable Document Format to image and then image to text. this work is advancement of Optical character recognition which can eliminate the drawback of already existing technology. © 2024 IEEE.

关键词： Optical character recognition

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INTELLIGENT MANAGEMENT OF INTEGRATED ENERGY SYSTEMS IN REMOTE MARITIME ENVIRONMENTS UTILIZING FUZZY MODES 14

INTELLIGENT MANAGEMENT OF INTEGRATED ENERGY SYSTEMS IN REMOT...

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14th Mediterranean Conference on Power Generation Transmission, Distribution and Energy Conversion, MEDPOWER 2024

作者： Alamaniotis, Miltiadis Fevgas, Athanasios Dept. of Electrical and Computer Engineering University of Texas at San Antonio San AntonioTX United States Dept. of Electrical and Computer Engineering University of Thessaly Volos Greece

ISBN: (纸本)9781837242689

This paper explores isolated maritime environments equipped with an integrated energy system (IET) to fulfil the energy requirements of nearby communities. These environments are presumed to lack grid access but possess a connection point for a floating energy source capable of supplying consistent electricity for a limited duration. The study introduces a novel management system for the efficient operation of IES in such environments, utilizing an innovative multi-mode approach. Specifically, the system includes several management modes, each employing a distinct management strategy for the IET. These modes are implemented using fuzzy logic tools, with a core of IF/THEN control rules that enable flexible and rapid decision-making. The fundamental concept is that the use of modes in decision-making inherently prioritizes specific operational objectives and consumption needs based on current conditions. The proposed system comprises three modes and is tested through a series of simulated scenarios. Results indicate that the IET can provide flexible energy management that adapts to dynamic conditions, outperforming a single-strategy system. © The Institution of engineering & Technology 2024.

关键词： Fuzzy logic

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Smart Attendance Management System Using Face Recognition 1

Smart Attendance Management System Using Face Recognition

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1st International Conference on Advances in computer science, electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Rawat, Shivam Goyal, Shweta Rawat, Nikita Graphic Era Hill University Dept. Computer Science & Engineering Dehradun India Graphic Era deemed to be University Dept. of Electrical Engineering Dehradun India

ISBN: (纸本)9798331518578

Managing attendance in educational institutions is often a time-consuming and error-prone task, with traditional methods like roll calls or sign-in sheets being inefficient and susceptible to proxy attendance. This paper presents a Smart Attendance Management System that leverages facial recognition technology to automate the attendance process. By using cameras to capture images of students, the system recognizes their faces and marks their attendance in real time. Developed in Python, the system employs the K-Nearest Neighbours (KNN) algorithm for accurate face recognition. Once attendance is recorded, it is stored in a CSV file and can be visualized using the flask web application. The proposed system significantly reduces manual effort, ensures accuracy, and operates efficiently in real-time environments. © 2025 IEEE.

关键词： Nearest neighbor search

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COMPARING WSN PERFORMANCE: TRADITIONAL VS. SDN APPROACH

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: electrical engineering and computer science 2024年第4期86卷 81-94页

作者： Hamad, Diyar Jamal Yalda, Khirota Gorgees Okumus, Ibrahim Taner Tapus, Nicolae Faculty of Automatic Control and Computer Science University of Science and Technology POLITEHNICA Bucharest Soran Technical college Erbil Polytechnic University Erbil Iraq Computer Engineering Kahramanmaras Sutcu Imam University Kahramanmaras Turkey Dept. of Computer Science University of Science and Technology POLITEHNICA Bucharest Romania

The proliferation of Wireless Sensor Networks (WSN) in various applications has necessitated the exploration of network architectures that can ensure efficient, scalable, and reliable communication. This study presents a comparative performance evaluation of traditional networking paradigms and Software-Defined Networking (SDN)-based architectures within WSN. Utilizing the Floodlight SDN controller and Mininet-WiFi emulator, we conducted a series of experiments across three different network topologies, varying the number of hosts and access points. The performance metrics focused on are average latency, packet loss percentage, and throughput. The results demonstrate a considerable improvement in all measured parameters under the SDN-based environment compared to the traditional setup. Specifically, SDN environments consistently showcased lower latency, minimal packet loss, and higher throughput, with the most notable difference observed in smaller network configurations. The findings suggest that SDN, with its centralized control plane, can significantly enhance the performance of WSNs, particularly in scenarios demanding rapid scalability and dynamic traffic management. This study underscores the potential of SDN architectures in optimizing WSN operations and lays the groundwork for future research in this domain. © 2024, Politechnica university of Bucharest. All rights reserved.

关键词： Floodlighting

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