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检索条件"任意字段=International Conference on Engineering of Reconfigurable Systems and Algorithms"

共 89784 条记录，以下是181-190 订阅

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Method of Tracking Inclined Geosynchronous Orbit Satellite for Satcom on-The-Move Antenna 5

Method of Tracking Inclined Geosynchronous Orbit Satellite f...

引用

5th IEEE international conference on Power, Electronics and Computer Applications, ICPECA 2025

作者： Qin, Chao Guan, Lianwu Gao, Yanbin Zhang, Shuo Huang, Yuanqing Wang, Yihuan College of Intelligent Systems Science and Engineering Harbin Engineering University Harbin China The 54th Research Institute of China Electronics Technology Group Corporation Shijiazhuang China

ISBN: (纸本)9798331533694

The Inclined Geosynchronous Orbit (IGSO) satellite has garnered significant attention for its extensive coverage and high-latitude capabilities. Traditionally, tracking methods rely on Two Line Element (TLE) data for satellite position prediction. To decrease reliance on external TLE data and avoid the complex orbit prediction algorithms, this paper conducts an in-depth analysis of the orbital characteristics of IGSO satellites and the accuracy of TLE-based predictions. A tracking method that employs curve fitting is proposed. Experiment results indicate that the tracking accuracy of this method surpasses 0.1°. © 2025 IEEE.

关键词： Satellite antennas

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Active Cell Balancing

Active Cell Balancing

引用

2025 international conference on Advances in Renewable Energy and Electric Vehicles, AREEV 2025

作者： Joshi, Girisha Bhanupriya, R. Bhuvana Salanki, Bindu S Gowda, Khushi N Nitte Department of Electrical and Electronics Engineering Karnataka 574110 India

ISBN: (纸本)9798331529574

In modern energy storage systems, effective battery management systems (BMS) are essential for optimizing battery performance and longevity. This paper addresses the challenges of manual monitoring of active cell balancing by developing a SOC estimator integrating microcontrollers, sensors, and control algorithms for cell balancing. The system autonomously monitors key parameters such as voltage, temperature, and state of charge (SOC), ensuring safe and efficient operation. It regulates charging and discharging processes, mitigating risks like overcharging, over-discharging, and thermal runaway. The primary goal is to enhance battery performance, longevity, safety, and reliability while minimizing human intervention. By automating monitoring and management, the proposed cell balancing reduces operational complexity and improves efficiency. Its cost-effective hardware and user-friendly interface ensure accessibility and scalability for diverse energy storage applications. This innovative approach streamlines energy management, making it a reliable and practical solution for modern battery systems. © 2025 IEEE.

关键词： State of charge

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A Hybrid Model for Parameter Tuning using SSO and CNN 3

A Hybrid Model for Parameter Tuning using SSO and CNN

引用

3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Patidar, Anil Bandhu, Kailash Chandra Department of Computer Applications Medi-Caps University Indore India Department of Computer Science and Engineering Medi-Caps University Indore India

ISBN: (纸本)9798331527549

Social Spider Optimization (SSO) and Particle Swarm Optimization (PSO) algorithms applied to Intrusion Detection systems (IDS) across small and large datasets. The study aims to evaluate and compare both PSO and SSO and find best optimal parameters in order to improve the accuracy of IDS. Additionally, the SSO algorithm find the best hyperparameter settings which are kernel, filter, padding, learning rate, and stride to achieve optimal results that directly impact IDS security. The evaluation of algorithms in terms of accuracy, precision, recall, F1 score, and AUC score. Results indicate that, on small datasets, PSO comes under overfitting but not SSO. Even on larger datasets, SSO crosses PSO significantly in terms of accuracy. This finding shows the importance of improvement in scalability, efficiency, and robustness of IDS with help of Social Spider Optimization (SSO). © 2025 IEEE.

关键词： Particle swarm optimization (PSO)

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Comparison of Segmentation algorithms for Extraction of Stone from Kidney X-ray Image 4th

Comparison of Segmentation Algorithms for Extraction of Ston...

引用

4th international conference on Smart IoT systems: Innovations and Computing, SSIC 2023

作者： Nisha, N. Dhaka, Vijaypal Singh Sinwar, Deepak Department of Computer and Communication Engineering Manipal University Jaipur Jaipur India Director of School of Computing and Intelligent Systems Department of Computer and Communication Engineering Manipal University Jaipur Jaipur India Department of IoT and Intelligent Systems Manipal University Jaipur Jaipur India

ISBN: (纸本)9789819751990

Healthcare systems are gaining popularity because of the advancement of new technology aiding healthcare professional for diagnosis of disease from medical modalities. The detection and classification of disease using AI and its technologies are active research areas in the last decade. Radiologist usually detects stone from the kidney using different imaging like CT scan, MRI scan, and X-ray. For the detection of stone in kidney X-ray images, various segmentation and classification methods are used. These different classification and segmentation methods are used to reduce errors and time of healthcare professional in diagnosis of stone in X-ray image. In this paper, comparison of different algorithms like thresholding algorithm, contour-based algorithm, deep learning algorithms like U-Net, U-Net++, V-Net, V-Net++, and Transformer Net are used for segmentation of stone from kidney X-ray images. The thorough comparison of different deep learning architectures in diagnosing stone from kidney X-ray images is also made in this paper. Most of the papers work on classification of stone from different medical modalities before segmentation which cause data leakage problem. In this research paper, comparisons of different segmentation algorithms help in achieving higher accuracy and reduce the data leakage problem. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Deep learning

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A Preliminary Study of the Stressed and Drowsy Driving Prediction Models using Semi-Supervised Learning 24

A Preliminary Study of the Stressed and Drowsy Driving Predi...

引用

8th international conference on algorithms, Computing and systems, ICACS 2024

作者： Chui, Kwok Tai Liu, Jiaqi Hung, Kevin Wu, Ho Chun Zhao, Mingbo School of Science and Technology Hong Kong Metropolitan University Hong Kong Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong School of Information Science and Technology Donghua University Shanghai China

ISBN: (纸本)9798400718304

Predicting the occurrence of stressed and drowsy driving provides sufficient time to alert drivers and prevent undesired driving behaviours that result in road traffic accidents. Typically, the predictive machine learning models for stress and drowsy driving are formulated using supervised learning with labelled data. Labelled data are available only in training datasets, where labelling new data becomes infeasible and costly. With the ever-growing quantity of new and unlabelled data, once the model is deployed, unlabelled data quickly dominate the whole data population, and bias toward unlabelled data may increase the error rate of the prediction model. A preliminary study was thus conducted to train the predictive model using semi-supervised learning. We analyze and compare the performance of four algorithms, namely extreme gradient boosting (XGBoost), autoregression (AR), autoregressive integrated moving average (ARIMA), and exponential smoothing (ES). Various portions of unlabeled data were introduced, and more window sizes (in advance intervals) were chosen for the analysis. © 2024 Copyright held by the owner/author(s).

关键词： Self-supervised learning

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Position Determination from CSI Measurements of Multiple UEs under Unaware Environment 16

Position Determination from CSI Measurements of Multiple UEs...

引用

16th international conference on Signal Processing systems, ICSPS 2024

作者： Wang, Chenchen Ma, Yubin Yu, Fangrui Wen, Hao Liu, Weiyu Wan, Qun Nation Key Laboratory on Blind Signal Processing School of Information and Communication Engineering University of Electronic Science and Technology of China Sichuan Chengdu611731 China

ISBN: (纸本)9781510689251

In urban environment, communication signals encompass non-line-of-sight (NLOS) paths that contain environmental information. This paper investigates utilizing NLOS component signal to estimate the environment parameters, and uses these environmental parameters to achieve blind UEs (User Equipment) positioning. Specifically, this paper first analyzes the relationship between environmental parameters and the time of arrival (TOA) of NLOS signals. Second, an algorithm is proposed that utilizes the TOA of one-order NLOS signals in uplink signals between distributed UEs and base stations (BS) to estimate environmental parameters via maximum likelihood estimation. Subsequently, leveraging the obtained environmental parameters, achieving the positioning of blind UEs. Finally, numerical simulations validate the effectiveness of the proposed method. © 2025 SPIE.

关键词： Reflection Non line of sight propagation Mirrors Reconstruction algorithms Environmental sensing Mirror surfaces Point clouds LIDAR Monte Carlo methods Numerical simulations

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A Review on IoT-Enabled Fire Detection and Safety Assurance systems

A Review on IoT-Enabled Fire Detection and Safety Assurance ...

引用

2025 international conference on Multi-Agent systems for Collaborative Intelligence, ICMSCI 2025

作者： Kamal Raj, V. Kaliswaroopan, K. Das, R. Mohan Chennai Institute of Technology Electronics and Communication Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331509828

Traditional fire alarm systems are gradually losing their relevance in the fire safety domain as there is an increasing demand for Fire detection systems than systems that alarm after the incidence of fire. It has become inevitable to develop methodologies that can detect the early signs of fire. This review paper reviews several approaches by different authors. Many technological approaches combine sensors with microcontrollers, GSM devices, and cloud services for monitoring, prompt detection, and effective mitigation of dangers like gas leaks, fires, and harmful releases, in time. Innovations such as machine learning algorithms ensure worker safety are being developed alongside alert systems based on thresholds and requirements, for visualizing data remotely and for analysis purposes. The study also aims to enhance the accuracy of hazard predictions and decrease false alarms by using Machine Learning and Image Processing technologies. This review paper gives an overall view of the role of machine learning methodologies in predicting fire and identifies the best-performing method. The study collectively highlights the significant impact of IoT in reducing risks and enhancing safety measures to safeguard lives and minimize property damage using reliable and cost-effective solutions. © 2025 IEEE.

关键词： Fire alarm systems

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Performance Assessment of Machine Learning Techniques for Mapping Nitrate Contamination using the Water Quality Index 3

Performance Assessment of Machine Learning Techniques for Ma...

引用

3rd international conference on Electronics and Renewable systems, ICEARS 2025

作者： Sivakumar, Vidhya Lakshmi Sundarayamini, K. Simats Saveetha School of Engineering Department of Civil Engineering Chennai India

ISBN: (纸本)9798331509675

Groundwater has played an essential role for both drinking and agriculture purposes but their monitoring methods lead to inadequate spatial coverage and irregular sampling intervals. In this paper, the study incorporates the WQI with machine learning techniques to analyze nitrate contamination in groundwater more accurately to overcome the traditional limitations. The research work has been carried out with limited water quality parameters such as pH, turbidity, DO, and nitrate levels. Samples are collected from five strategically chosen wells from diverse environments such as agricultural, industrial, residential, rural, and coastal areas in the Tiruvallur District of Tamil Nadu, India by providing a comprehensive dataset with the varied hydrogeological and anthropogenic influences over groundwater quality. In the six selected machine learning algorithms, the Random Forest algorithm was able to obtain high predictive accuracy for the nitrate concentrations with R2 = 0.98. The results indicate a significant spatial variability in water quality in which nitrate and turbidity levels are significantly high in wells B and E indicating agricultural and industrial contamination. © 2025 IEEE.

关键词： Groundwater pollution

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Multi-Modal Fusion Algorithm for Ultrasound Imaging Using PMUT Linear Arrays 24

Multi-Modal Fusion Algorithm for Ultrasound Imaging Using PM...

引用

2nd international conference on Artificial Intelligence, systems and Network Security, AISNS 2024

作者： Han, Yanbin Han, Zehang School of Mechanical Engineering and Automation Dalian Polytechnic University Liaoning Dalian China College of Artificial Intelligence Tianjin University of Science and Technology Tianjin China

ISBN: (纸本)9798400711237

Ultrasound CT technology has rapidly developed as a new transmission imaging technique due to its advantages of being unaffected by surrounding tissue interference and high imaging resolution. This paper aims to develop ultrasound reconstruction algorithms based on the designed breast ultrasound CT system. A measurement scheme is proposed for acquiring three-dimensional ultrasound data through the rotational scanning of PMUT linear array sensors. Based on this, a linear trajectory fan beam ultrasound image reconstruction algorithm is derived. By integrating the speed of sound images with B mode images, the tomographic image is obtained that contains both edge information and structural information. Experimental results indicate that the fusion method was more accuracy with improved PSNR and RMSE of 125.8 dB and 0.18, respectively, validating the feasibility and applicability of the ultrasound image reconstruction algorithm. This research provides a theoretical foundation and technical support for comprehensive and reliable screening of breast cancer diagnosis. © 2024 Copyright held by the owner/author(s).

关键词： Ultrasonic imaging

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Research on path planning of intelligent vehicles 4

Research on path planning of intelligent vehicles

引用

2024 4th international conference on Intelligent Traffic systems and Smart City, ITSSC 2024

作者： Yan, Qiyan Liu, Xia Chang, Zhoulin School of Mechanical and Electrical Engineering Guangdong University of Science and Technology Dongguan523083 China

ISBN: (纸本)9781510686304

With the continuous improvement of intelligence and driving safety requirements, accurately sensing the external environment and planning paths reasonably and efficiently has become one of the research hotspots in intelligent vehicles. Based on the study of intelligent vehicle architecture and predictive control schemes, this article focuses on the research of trajectory planning algorithms. This article proposes an improved RRT* algorithm based on the principle of fast random tree algorithm (RRT). This algorithm introduces a bidirectional random tree search strategy to shorten the convergence time and improve computational efficiency;By using redundant point clipping and B-spline curve fitting methods, the algorithm generates relatively smooth paths. Build a narrow channel environment and a multi obstacle environment in MATLAB software environment for simulation verification. The simulation results show that compared to the traditional RRT* algorithm, the improved RRT* algorithm outperforms the traditional RRT* algorithm in terms of planning speed, path length, and number of sampling nodes. © 2025 SPIE.

关键词： MATLAB

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