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检索条件"任意字段=8th IEEE International Conference on Software Engineering and Computer Systems, ICSECS 2023"

共 1532 条记录，以下是411-420 订阅

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Automatic Rain Alert and Protection System for Harvested Crops using IoT 8

Automatic Rain Alert and Protection System for Harvested Cro...

引用

8th international conference on Communication and Electronics systems, ICCES 2023

作者： Varsha, Gudise Satapathy, Ashutosh Harshini, Grandhe Komali, Madala Velagapudi Ramakrishna Siddhartha Engineering College Department of Computer Science and Engineering Andhra Pradesh Vijayawada India

ISBN: (纸本)9798350396638

Agriculture is the backbone of India and low-income Indian states as well, and it generates around 17-18% of India's national income. More than 70% of rural income is generated through agriculture. As the fourth revolution proceeds, technology has been advancing rapidly every day. the agriculture sector is beginning to transform itself by adopting modern agricultural technologies enabled by the Internet of things and artificial intelligence. Starting from a basic sprinkler to the requirement for fertilizer on crops, everything has been significantly changed by these technologies. Protecting crops from torrential rains, which severely reduce soil productivity and crop yield and cause a farmer huge emotional suffering, is one of the problems that needs to be solved. An empirical model was used to provide both automated and manual control to overcome this problem. An Arduino UNO, servo motor, rain sensor, and LED light were utilized to alert farmers and save crops. the purpose of this work is to help farmers and protect crops from the intense rainfall. Within 5 seconds, the crop is protected by the water-resistant film. © 2023 ieee.

关键词： Internet of things

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Group Shared Mobility Platform Activated via Blockchain 8

Group Shared Mobility Platform Activated via Blockchain

引用

8th international conference on Communication and Electronics systems, ICCES 2023

作者： Subramanian, E.K. Rajkumar, M. Poovizhi, T. Mohapatra, Saumendra Kumar Department of Computer Science and Engineering Tamil Nadu Chennai India Vit University School of Information Technology and Engineering Tamil Nadu Vellore India

ISBN: (纸本)9798350396638

Web sharing is a centralized trust system in order to trust users to establish, track, cancel, fare calculate, etc., the service providers. Any malicious activities performed on a centralized server system or vehicle or riders destroy the fairness of the ride and cause the party discomfort. the drivers are assessed by the riders after the ride has been completed. there can be a malicious driver who can claim reimbursement with a fake complaint and give the driver a poor rating. the current system cannot determine the correctness of both parties' objections and delivers the biased outcome of each objection in accordance with the centralized marketing strategies of the company. In order to ensure fair travel, a workaround that can be blocked is presented. the creation, completion, unrest, or abortion of a ride will be published in the block chain booklet so that the peer-to-peer network is available to all participants. this means that the interconnected credibility structure is managed equally at the same time. In Ethereal secure network as well as the KOVAN test network, that have implemented a prototype, and the analysis is included © 2023 ieee.

关键词： Blockchain

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Building an Intelligent Aerial Surveillance System through Deep-learning based Object Detection 8

Building an Intelligent Aerial Surveillance System through D...

引用

8th international conference on Communication and Electronics systems, ICCES 2023

作者： Janakiramiah, B. Bethala, Sitha Ram Chandrika Chereddy, Prasanna Ambi, Geethika Mohan, Challa Prasad V. Potluri Siddhartha Institute of Technology Department of Computer Science and Engineering Andhra Pradesh Vijayawada India

ISBN: (纸本)9798350396638

the article discusses the challenges involved with detection of vehicles with aerial pictures and methods used to overcome these challenges. Aerial images present unique challenges, such as smaller size of vehicles & intricate backgrounds. Traditional approaches such as sliding window and feature extraction have limitations in accurately detecting vehicles in aerial images. Deep learning models like R-CNN, Faster R-CNN, & Mask R-CNN were proposed & demonstrated exceptional performance. However, there remain challenges in their direct application to vehicle detection in aerial images. Modifications were proposed to overcome these challenges, including improvements to region projected network & classifier and the use of instance segmentation in addition to object detection using bounding boxes. the article highlights the need for large aerial picture real-time detection and the importance of accurate vehicle recognition from aerial photographs in various applications, including urban planning and traffic management. © 2023 ieee.

关键词： Antennas

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Alzheimer's Disease Imaging Recognition Based on Improved 3D-ShufflenetV2 Network 1

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

作者： Tao, Xinjie Wei, Lisheng Wang, Qin Anhui Key Laboratory of Electric Drive and Control Anhui Polytechnic University Wuhu241000 China School of Electrical Engineering Anhui Polytechnic University Wuhu241000 China

ISBN: (数字)9789819603138

ISBN: (纸本)9789819603121

To solve the problems of low accuracy, data leakage, and low efficiency in current deep learning based two dimensional Alzheimer's disease (AD) imaging recognition, an improved 3D-ShufflenetV2 network has been proposed. Firstly, the network utilizes 3D convolution to extract spatial continuity information from three dimensional images, enabling the extraction of more brain lesion information. Secondly, a Squeeze-and-Excitation attention mechanism is introduced into the backbone network, recalibrating channel-level feature responses based on global information to enhance the model's focus on important features, thereby enhancing the model's classification performance. Finally, to increase the model's ability to extract global features, a global feature fusion branch has been added to the network structure. Experiments have shown that the improved network is capable of recognizing AD, Mild Cognitive Impairment (MCI), and Cognitively Normal (CN). the classification performance of the modified network model shows significant improvement over the original network, demonstrating its practical value. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Neurodegenerative diseases

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A Novel Deep Information Search Algorithm for Legal Case Text Recommendation System 8

A Novel Deep Information Search Algorithm for Legal Case Tex...

引用

8th international conference on Communication and Electronics systems, ICCES 2023

作者： Wan, Hui Wuhan Business University Department of Information Engineering Hubei Wuhan430056 China

ISBN: (纸本)9798350396638

At present, the need for efficient information search and analysis is essential for the computer-based legal case text analysis systems. For the common methods, their steps are more focused on text pattern analysis, which ignores the deep information of the large case data sets. then, this paper proposes a novel deep information search algorithm for the legal case text recommendation system. the novelties are focused on 3 aspects: (1) the novel deep information search (DIS) algorithm considering the feature model is proposed. (2) the novel text recommendation scenario, the new structural optimal model, is designed. (3) the legal case text features are investigated, and the proposed model is applied to the legal case text datasets to validate the performance. Experimental results show that our method achieves satisfactory results, and different data sizes are considered to test the applicability. © 2023 ieee.

关键词： Recommender systems

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Design and Implementation of AI Machine Vision Inspection System with Multi-Optical Images for OLED Film Manufacturing 8

Design and Implementation of AI Machine Vision Inspection Sy...

引用

8th ieee/ACIS international conference on Big Data, Cloud Computing, and Data Science, BCD 2023

作者： Kim, Tae-Yong Oh, Seongjin Lee, So-Min Lee, Sungkook Hwang, Sangyoon Jeong, Jongpil Sungkyunkwan University Dept. of Smart Factory Convergence Suwon Korea Republic of Sungkyunkwan University Dept. of Culture and Technology Suwon Korea Republic of Sungkyunkwan University Dept. of Mechanical Engineering Suwon Korea Republic of Sungkyunkwan University Dept. of Chemical Engineering Suwon Korea Republic of

ISBN: (纸本)9798350373615

Machine vision technology is one of the main areas of rapid development in the modern world and is becoming increasingly important in various industries. this innovative technology uses the fusion of computer vision and artificial intelligence to process and analyze visual information, enabling the development of automated inspection systems and the automation of processes. In particular, machine vision technology is playing an increasingly important role in OLED film production and quality control. Currently, OLED film production is mainly based on visual inspection, but this method has various problems. It is labor-intensive and relies on humans, which limits the accuracy and consistency of the inspection. It is also difficult to identify defective elements with irregular shapes or sizes. To overcome these issues and revolutionize the field of OLED film production and quality control, we propose an OLED Film Inspection Architecture with Machine vision. this architecture utilizes advanced cameras and sensors to analyze the surface of OLED films in detail and automatically identify defective elements. In addition, by integrating multiple optical systems and AI deep learning algorithms, it can perform accurate inspections under various lighting conditions and detect defects in real time. By utilizing these advanced technologies, quality control and production efficiency can be greatly improved, which is expected to drive innovation in OLED film production. this research provides a high level of technical content and provides a bright outlook for the future of machine vision technology in the industrial field. © 2023 ieee.

关键词： Inspection

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Scheduling Performance Evaluation Framework for ROS 2 Applications 24

Scheduling Performance Evaluation Framework for ROS 2 Applic...

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24th ieee international conference on High Performance Computing and Communications, 8th ieee international conference on Data Science and systems, 20th ieee international conference on Smart City and 8th ieee international conference on Dependability in Sensor, Cloud and Big Data systems and Application, HPCC/DSS/SmartCity/DependSys 2022

作者： Peng, Bo Hasegawa, Atsushi Azumi, Takuya Graduate School of Science and Engineering Saitama University Japan Research Institute of Systems Planning Japan

ISBN: (纸本)9798350319934

Recently, performance analysis research on self-driving software has attracted considerable attention because the development of self-driving software has increased performance needs. ROS 2 is an open-source application framework for robotics. Simultaneously, as the Executor is responsible for scheduling callbacks (the minimal schedulable entity) in ROS 2, the Executor's scheduling performance is one of the most crucial factors affecting the real-time performance of ROS 2. A performance evaluation tool for Executor scheduling is required to evaluate its performance. this paper proposes a tracing and performance analysis framework with instrumentation and tools for ROS 2 Applications, with the visualization of Executor scheduling results and analysis of Executor deadline misses. the proposed framework can help researchers better understand and develop ROS 2 Executor by providing deadline miss analysis of the end-to-end path and the scheduling data. Furthermore, this paper verifies the proposed approach to the Autoware Reference System, which can simulate a real-world scenario to evaluate the performance of Executor. © 2022 ieee.

关键词： Open source software

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Secure Medical Data Management Based on Homomorphic Encryption and Secret Sharing

Secure Medical Data Management Based on Homomorphic Encrypti...

引用

8th ieee international conference on Smart Cloud, SmartCloud 2023

作者： Law, Po Ying Tsai, Chia-Cheng Fok, Tsz Wun Wang, Ching-Ting Chang, Chi-Hsien Chin, Tsung-Yu Liao, Yi-Chen Lee, Jen-Kuang Lin, Chung-Wei Department of Computer Science and Information Engineering Taiwan Department of Electrical Engineering Taiwan Department of Engineering Science and Ocean Engineering Taiwan School of Medicine National Taiwan University Taiwan

ISBN: (纸本)9798350313505

Medical data are highly sensitive and require secure storage systems to protect patients’ privacy. Centralized databases pose significant risks in the context of a breach, since all data are concentrated in a single location. Additionally, privacy concerns often prevent medical institutions from sharing data, hindering potential research breakthroughs. To address these challenges, we propose a novel cloud storage system that utilizes homomorphic encryption and secret sharing. Our approach enables secure cloud storage of medical data and allows for secure data sharing without compromising patients’ privacy. In addition to enhancing confidentiality, our proposed approach also improves data integrity and availability. We implement a proof-of-concept that demonstrates the feasibility of our storage system. ©2023 ieee.

关键词： Cloud storage

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Extended algorithm for current slope estimation in inverter fed synchronous machines 8

Extended algorithm for current slope estimation in inverter ...

引用

Joint 8th international conference on Digital Arts, Media and Technology and 6th ECTI Northern Section conference on Electrical, Electronics, computer and Telecommunications engineering, ECTI DAMT and NCON 2023

作者： Degel, Jan Philipp Haehnlein, Stefan Boschert, Lars Kloeffer, Christian Doppelbauer, Martin Institute of Sustainable Energy Systems University of Applied Science Offenburg Offenburg Germany Institute of Electrical Engineering Karlsruhe Institute of Technology Karlsruhe Germany

ISBN: (纸本)9798350396546

the present work describes an extension of current slope estimation for parameter estimation of permanent magnet synchronous machines operated at inverters. the area of operation for current slope estimation in the individual switching states of the inverter is limited due to measurement noise, bandwidth limitation of the current sensors and the commutation processes of the inverter's switching operations. therefore, a minimum duration of each switching state is necessary, limiting the final area of operation of a robust current slope estimation. this paper presents an extension of existing current slope estimation algorithms resulting in a greater area of operation and a more robust estimation result. © 2023 ieee.

关键词： Parameter estimation

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Skin Disease Detection and Recommendation System using Deep Learning and Cloud Computing 8

Skin Disease Detection and Recommendation System using Deep ...

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8th international conference on Communication and Electronics systems, ICCES 2023

作者： Chowdary, Nama Deepak Inturu, Siddhartha Katta, Jithendra Yashwanth, Chiluka Kanaparthi, Naga Sri Harsha Vardhan Voore, Srinivas Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Vijayawada India

ISBN: (纸本)9798350396638

the main objective of this research is to develop an application based on Deep learning, computer vision and cloud computing that detects the different kinds of skin diseases caused by different types of viruses, Bacteria, Fungus and Environment. this study has also developed and integrated a recommendation system, which recommends the medicines and care taking process for a particular disease. the application also suggests preventive methods for different kinds of skin infections. this study used an ensemble of convolution neural networks (CNN) with generative adversarial network (GAN) and computer vision for construction of the model. Further, Amazon Personalize is used to build recommendation system in the proposed web application. the proposed application detects the disease based on symptoms, pictures, and videos of infected skin area. the application will be helpful for dermatologists and common people to perform early detection and prevention of skin diseases in India. this study also compared the accuracy of ensemble of convolution neural networks (CNN) with GAN and other algorithms like CNN. In comparison of accuracy, this study found that the Ensembles of CNN with GAN give best results for the proposed dataset. © 2023 ieee.

关键词： Generative adversarial networks

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