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

作者： Paul, Soumyadip Chakraborty, Sarit Government College of Engg. & Ceramic Technology Dept. Of Information Technology WB Kolkata 700010 India Government College of Engineering and Leather Technology Dept. of Computer Science and Engineering WB Kolkata 700106 India

ISBN: (纸本)9798331523893

Quantum technology offers a transformative approach to solving complex computational challenges in decentralized systems, particularly in blockchain transaction scheduling. Efficient transaction scheduling is critical in distributed ledger systems, which often face challenges like dynamic transaction loads. This work proposes a novel approach namely Hybrid Quantum Approximate Optimization Algorithm (HQAOA) which combines Multi-Agent QAOA (MA-QAOA) and Adaptive Layer QAOA (AL-QAOA) to provide a robust solution to such issues. HQAOA leverages a decentralized optimization framework where multiple agents, each representing a node in the network, optimize local transaction scheduling while considering global constraints. Additionally, HQAOA adapts to varying transaction loads by dynamically adjusting the number of quantum layers for each agent, ensuring computational efficiency under different conditions. Such dynamic layer adjustment mechanisms mitigate the adverse effects of quantum noise and ensures optimal performance in scenarios with fluctuating transaction loads. In contrast to traditional QAOA, which struggles with noise and scaling issues, HQAOA provides improved performance by balancing the complexity of the problem with available quantum resources. Experimental results signify the future potential of HQAOA to outperform QAOA, particularly in noisy environments and irregular transaction conditions. This work demonstrates the potential of HQAOA to optimize blockchain transaction scheduling in decentralized systems. © 2025 IEEE.

关键词： AL-QAOA Blockchain HQAOA MA-QAOA Quantum computing

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Investigating the Impact of Chunk Time on Video Streaming Performance in TCP-based Networks 29

Investigating the Impact of Chunk Time on Video Streaming Pe...

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29th International Computer Conference, Computer Society of Iran, CSICC 2025

作者： Chatri, Yeganeh Akbari, Behzad Goudarzi, Pejman Dept. of Computer and Electronic Engineering Tarbiat Modares University Tehran Iran Dept. of Information Technology ICT Research Institute Tehran Iran

ISBN: (纸本)9798331523114

The exponential increase in video traffic on the Internet has generated a heightened demand for efficient video streaming solutions. HTTP Adaptive Streaming (HAS) has emerged as a viable strategy, facilitating dynamic quality adaptation in response to fluctuating network conditions. In HAS, media content is segmented into short time intervals, with each segment encoded in multiple bitrate-resolution combinations known as representations. This framework enables users to choose the most appropriate representation according to their current network connectivity. To enhance the selection of bit rates and elevate the Quality of Experience (QoE), it is crucial to conduct a precise assessment of network conditions. This research investigated the impact of chunk time on video streaming performance in TCP-based networks. Analyzing the effects of chunk time on both QoE and throughput, our findings indicate that similar to the adaptive nature of video representations that depend on network conditions, chunk time must also be adaptive. It is essential that the chunk time is tailored to the specific network environment, necessitating an adaptive chunk-time strategy for each resolution to ensure optimal streaming performance. © 2025 IEEE.

关键词： Chunk Time HTTP adaptive streaming QoE

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Live Audio Recognition and Text Conversion System 2

Live Audio Recognition and Text Conversion System

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2nd International Conference on Computational Intelligence, Communication technology and Networking, CICTN 2025

作者： Sharma, Pratyaksha Gupta, Sumita Bhavya, Boddu Asmitha Sharma, Khushi Dhir, Saru Gambhir, Sapna Department of Computer Science & Engineering Amity School of Engineering & Technology Amity University UP India Department of Information Technology Amity School of Engineering & Technology Amity University UP India Dept. of Computer Science College of Engineering and Computing George Mason University United States

ISBN: (纸本)9798331530389

With the advancement of technologies, different methods are currently being used for converting spoken language into text. These systems offer a hands-free alternative to traditional input methods, especially for individuals with physical disabilities or those requiring efficient documentation of spoken content. The goal of this study is to review recent advancements in this field and highlight gaps in current research, with a focus on accuracy, language adaptability, ease of use, and the integration of various technologies. We also suggest future directions for enhancing and developing this technology further. © 2025 IEEE.

关键词： Hidden Markov models

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Bird Repeller Using Opencv

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Procedia Computer Science 2025年 252卷 975-984页

作者： M. Upendra T. Anuradha L. Prakash Dept. of Information Technology Velagapudi Ramakrishna Siddhartha Engineering College Vijayawada India

This research addresses one of the major problems in agriculture that farmers are currently facing: birds causing significant crop damage in agricultural fields. To reduce this damage, a person’s presence is often required in the farm field to repel the birds. To eliminate this need and automate the repellent system, the project aims to develop a bird repellent device using computer vision techniques to detect and repel birds from fields. Existing work lags behind in using effective algorithms and developing hardware. Object detection algorithms like the Haar Cascade Classifier and YOLOv8 are used; YOLOv8 is a powerful object detection algorithm, and it is chosen as the primary algorithm for its accuracy and speed in detecting birds. A hardware device is developed using a Raspberry Pi with a Pi camera and a Bluetooth speaker. Upon detecting birds in the farm fields through the Pi camera, distress calls are produced through the Bluetooth speakers to repel the birds.

关键词： Computer Vision Cascade Classifier Open CV Distress Call image detection Raspberry pi pi camera YOLO Bird Repellent

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Comprehensive Analysis of Fruit Variety Classification: Techniques, Challenges, and Application

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Procedia Computer Science 2025年 258卷 223-232页

作者： Kedar Sawant Ajitha Shenoy K B Smitha Pai Rudresh D. Shirwaikar Manipal Institute of Technology Dept. of Information and Communication Technology Manipal Karnataka India Department of Information Technology Shree Rayeshwar Institute of Engineering and Information Technology Goa India

Fruit variety classification is a crucial aspect in agricultural processes and supply chain management, influencing market competitiveness, and consumer satisfaction. This paper provides a comprehensive review of various fruit variety classification techniques utilizing machine learning (ML) methodologies, highlighting the motivations driving research in this domain and the challenges that researchers and practitioner’s encounter. The capabilities of ML algorithms and deep learning (DL) models have facilitated significant advancements in fruit classification accuracy. Motivated by the growing demand globally for fruits and their varieties and the need to optimize resources utilized in agriculture, researchers have focused on developing ML-driven classification systems capable of automating fruit sorting, grading, maturity estimation, and quality control processes. DL particularly has ability to learn complex representations from images, among which the primary architecture is the convolutional neural network (CNN) for applications related to image classification. Based on the extensive literature survey conducted, its observed that utilization of CNN for fruit variety classification has immensely increased generating outstanding results using “from-scratch” or “pretrained” model for transfer learning, however it often struggles with limited datasets, leading to poor generalization, and difficulty in handling variations in fruit appearance due to lighting, orientation, or ripeness. Besides this, the paper presents frameworks, model design, and one practical application on the use of CNN for fruit variety classification.

关键词： Fruit Variety Classification Deep Learning Machine Learning CNN

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Edge Node Load Balancing Using Game Theoretic Approaches 5

Edge Node Load Balancing Using Game Theoretic Approaches

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5th International Conference on Emerging Systems and Intelligent Computing, ESIC 2025

作者： Haldar, Rajdeep Rooj, Saptadip Sharma, Neeraj Das, Ritambhar Mandal, Arnab Bandyopadhyay, Anjan Dept. of Information Technology Bhubaneswar India Lovely Professional University School of Computer Science and Engineering Jalandhar India School of Computer Engineering Bhubaneswar India

ISBN: (纸本)9798331522100

This paper explores the application of game theoretic approaches to load balancing across edge nodes within distributed computing systems. Focusing on a non-cooperative game model, we aim to enhance system efficiency by strategically optimizing resource allocation and load distribution among autonomous edge nodes. Initial simulations demonstrate that our approach not only addresses the inherent complexities of edge environments but also outperforms traditional load balancing mechanisms in terms of both operational efficiency and system responsiveness. © 2025 IEEE.

关键词： Edge computing

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Automated Wind Turbine Inspection and Structural Damage Detection Using YOLOv5s

Automated Wind Turbine Inspection and Structural Damage Dete...

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Interdisciplinary Approaches in technology and Management for Social Innovation (IATMSI), IEEE Conference on

作者： Vishwajeet Karpe Rushikesh Gaikwad Om Gole Prasad Gore Riddhi Mirajkar Nitin Sawalkar Dept. of Information Technology Vishwakarma Institute of Information Technology Pune India Dept. of Civil Engineering Vishwakarma Institute of Information Technology Pune India

ISBN: (数字)9798331521691

ISBN: (纸本)9798331521707

An automated damage detection method based on deep learning for wind turbine blades uses the YOLOv5 framework, which is object detection that is quite fast and relatively accurate for detecting objects and localization instances of damage in images. Source data has been a curated collection dataset of wind turbine images with annotated regions of damage; thus, a model was trained from Roboflow. This uses transfer learning in which the model is started with pre-trained YOLOv5s weights and further fine-tunes it over the specific dataset. It also fits well into the nature of the data-set including the number of classes of damage. The training process, therefore, is optimizing the model parameters to achieve the minimization of differences between predicted bounding boxes and the available ground-truth annotations. Standard metrics for object detection are used in the evaluation of the model: precision, recall, mean Average Precision (mAP), and F1-score. Qualitative assessment is also carried through as a visual check on the predictions that the model would produce on unseen images, validating its use in real conditions. It contributes to developing an automated and efficient system concerning structural health monitoring of wind turbines and enables maintenance at the appropriate time, thus decreasing down times.

关键词： YOLO Training Visualization Technological innovation Transfer learning Predictive models Minimization Wind turbines Monitoring Standards

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Specialization Meets Flexibility: A Heterogeneous Architecture for High-Efficiency, High-Flexibility AR/VR Processing 23

Specialization Meets Flexibility: A Heterogeneous Architectu...

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Proceedings of the 60th Annual ACM/IEEE Design Automation Conference

作者： Arpan Suravi Prasad Luca Benini Francesco Conti Dept. of Information Technology and Electrical Engineering ETH Zürich Switzerland Dept. of Information Technology and Electrical Engineering ETH Zürich Switzerland and Dept. of Electrical Electronic and Information Engineering University of Bologna Italy Dept. of Electrical Electronic and Information Engineering University of Bologna Italy

ISBN: (纸本)9798350323481

Emerging AR-VR applications execute complex heterogeneous workloads, mixing Deep-Learning(DL) and Digital-Signal-Processing(DSP) tasks, on SoCs embedded in the frame of eyeglasses, with implied tight power and area constraints, especially in the case of AR. We propose ArchiMEDES, an open-source heterogeneous-SoC platform with a programmable cluster of RISC-V cores coupled with a configurable DNN engine (NEureka) targeting AR/VR workloads. ArchiMEDES features a low-overhead Heterogeneous Cluster Interconnect(HCI) to enable fast RISC-V/NEureka cooperation on a shared tightly coupled data memory (TCDM). We show post-layout results targeting 22nm technology; ArchiMEDES shows a peak combined performance of up to 1.19 TOPS and an efficiency of up to 10.6 TOPS/W. Hardware-Software cooperation in ArchiMEDES enables a 5.5× speedup in an AR-VR gaze tracking case study, compared to a non-cooperative single-RISC-V + Accelerator system.

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Drive Stabilization of Multi-Degree-of-Freedom Maglev Planar Motor Based on Closed Loop System Identification

Drive Stabilization of Multi-Degree-of-Freedom Maglev Planar...

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2025 IEEE International Conference on Mechatronics, ICM 2025

作者： Nakata, Keigo Ohnishi, Wataru Koseki, Takafumi Nakamura, Yuichiro Takahashi, Kenji Sekiguchi, Hiroyuki The University of Tokyo Dept. of Electrical Engineering and Information systems Tokyo Japan Advanced Technology R&D Center Mitsubishi Electric Corporation Hyogo Japan

ISBN: (纸本)9798331533892

Magnetic levitation planar motor can move at high speed and with high accuracy, and prevent vibration and noise because of no friction. This technology leads to the application of a transport system that requires high-speed and high-precision movement. However, the design of appropriate control algorithms is essential to achieve stability and high-speed, high-precision control of the maglev planar motor. In this research, we stabilized a maglev planar motor on the basis of system identification. Initially, we designed a whole control system for the movement of the maglev planar motor. Furthermore, we conducted system identification and verified that the maglev planar motor works with the designed control system and evaluated its motion performance. Through experiments, it was confirmed that accurate motion control was possible. This research is expected to be a basis for improving control performance soon. © 2025 IEEE.

关键词： Degrees of freedom (mechanics)

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Amplitude Stabilization of Frequency-Tunable Biquad Digital Oscillator Using Zero-Input Response Analysis

Amplitude Stabilization of Frequency-Tunable Biquad Digital ...

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2024 International Conference on Photonics Solutions, ICPS 2024

作者： Chivapreecha, Sorawat Suwannawach, Piyapan Sato, Tomoaki School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok10520 Thailand Dept. of Management Information Hokusei Gakuen Univ. Sapporo Japan

ISBN: (数字)9781510688308

ISBN: (纸本)9781510688292

This paper presents an analysis of the biquad digital oscillator, which leads to design improvements in the online oscillating frequency adjustment capabilities. The requirements for signal generation in a digital oscillator without input comprise the initial conditions as well as the coefficients, which are constants. The coefficient of biquad oscillator can be modified to be a tuning parameter for changing the oscillating frequency by the users. Although the frequency of the oscillating signal can be changed as desired, however, while the system is operating, the inconsistency of the changed coefficient with the initial conditions that emerge from the retained prior states causes the signal amplitude to lose its stability. The zero-input response of a system could be theoretically examined to identify and understand this behavior. Moreover, the issue of amplitude stabilization can be looked into and resolved with the use of the zero-input response analysis develop to an improvement, which results in maintaining the amplitude of the oscillating signal after the frequency change. © 2025 SPIE.

关键词： Circuit oscillations

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