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检索条件"任意字段=7th International Conference on Computing in Engineering and Technology, ICCET 2022"

共 10988 条记录，以下是191-200 订阅

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Research on Remote Sensing Image Classification Algorithm Based on EfficientNet 7

Research on Remote Sensing Image Classification Algorithm Ba...

引用

7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Yin, Hang Yang, Chengyi Lu, Jiayi Xi'an University of Science and Technology School of Computer Science and Technology Xi'an China Harbin University of Science and Technology School of Computer Science and Technology Harbin China Beijing University of Chemical Technology School of Mechanical and Electrical Engineering Beijing China

ISBN: (纸本)9781665478571

Accurate classification of remote sensing images is important in remote sensing applications. In order to verify the efficiency and accuracy of efficientnet algorithm in remote sensing image classification, this paper classifies the UCMerced LandUse dataset based on EfficientNet. the experimental results show that compared with VGGNet, ResNet and MobileNet, the EfficientNet network introduces composite parameters and scales depth, width and resolution at the same time. the accuracy of EfficientV2-s in the verification set is 16.5%, 5.2%, 1.8% and 1.7% higher than that of VGG, MobileNetV2, ResNet34 and EfficientNet-b0, which shows the efficiency and accuracy of EfficientNet network in remote sensing image classification data set. © 2022 IEEE.

关键词： Efficiency

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SVM-based Fault Detection Method for Air Conditioners in EMU Train 7

SVM-based Fault Detection Method for Air Conditioners in EMU...

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7th international conference on Data Science and Information technology, DSIT 2024

作者： Wei, Rongjiao Pan, Chao Wei, Pu An, Yangyang Zhu, Hao Wang, Mulan Nanjing Institute of Technology School of Communications and Information Engineering Nanjing China China Railway Shanghai Group Co. Ltd. Nanjing EMU Depot Nanjing China Nanjing Institute of Technology Jiangsu Key Laboratory of Advanced Numerical Control Technology Nanjing China

ISBN: (纸本)9798350384093

In this paper, we introduce and experimentally demonstrate a fault detection method for the air conditioner in the EMU train, which usually generates abnormal sounds when the faults occur. the technique utilizes the Support Vector Machine (SVM) to recognize the time-frequency characteristics of the sound generated by the air conditioner, which is extracted using the short-time Fourier transform (STFT). In addition, a detection system is built for the experiment, in which an FPGA and an embedded system are employed for sound acquisition and acoustic signal process, respectively. the penalty factor of the SVM model is optimized and accuracy of 0.977 is achieved. Our method will improve the efficiency and accuracy of fault detection for the air conditioner in the EMU train. © 2024 IEEE.

关键词： Support vector machines

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Methodology Metadata-driven Knowledge Production Charac-teristics Identification by Knowledge Retrieval and Mining 7

Methodology Metadata-driven Knowledge Production Charac-teri...

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7th international conference on Data Science and Information technology, DSIT 2024

作者： Xu, Hao Ge, Linlin Zhang, Yan Jin, Zhenqiang Wang, Mulan Feng, Ke Kang, Zhenyuan Nanjing Institute of Technology School of Management Engineering Nanjing China Nanjing University School of Information Management Nanjing China Nanjing Institute of Technology School of Electrical Power Engineering Shen Guorong College Nanjing China Jiangsu Power Transmission & Transformation Co. Ltd Nanjing China

ISBN: (纸本)9798350384093

the progress of science, technology, and innovation is greatly aided by the advancement, improvement, and use of methodology. Our work developed a Characteristic Recognition Algorithm based on text mining to extract methodology metadata from full-text documents and identify characteristics that are methodologically driven by time trend, dissemination speed, and co-drive. A sample of 5564 publications from the economic and management (E&M) discipline were chosen, from which 9,995 methodological metadata were extracted and classified into 4 categories: model, software & tool (S&T), data, and method & theory (M&T). the co-occurrence trait was revealed using the social network approach. Results indicate that over the past 20 years, the methodology's usage rate has increased, reaching 78.49% in 2019 alone. While S&T, model, and data have slowed down, M&T has the highest usage rate, which is reflected in a continually rising diffusion feature. the outcomes of knowledge creation in E&M exhibit the features of multi-methodology that is frequently driven, including M&T (hypotheses, questionnaire surveys), data (China Statistical Yearbook, wind, and CSMAR), model (double difference and logit), and S&T (SPSS, Amos, LISREL). the process of defining characteristics of approach metadata-driven knowledge production will be applied to different areas as a preliminary investigation, as well as used as training material for the automatic extraction of large-scale corpora. © 2024 IEEE.

关键词： Intelligent computing Knowledge Production Characteristics Knowledge Retrieval and Mining Methodology Driven Social Network Analysis

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Implementation of Cloud computing in Higher Education: A Bibliographic Analysis 7

Implementation of Cloud Computing in Higher Education: A Bib...

引用

7th international conference on Intelligent computing and Control Systems, ICICCS 2023

作者： Samanta, Soham Pasayat, Ajit Kumar Kalinga Institute of Industrial Technology School of Computer Engineering Bhubaneswar India

ISBN: (纸本)9798350397253

A network of remote servers is implemented by cloud computing, which is placed on the internet to safeguard, access, manage, and process data instead of on a local server. Cloud computing is currently a very in-demand service as it provides various benefits like huge computational power, cost cutting of services, enhanced performance, scalability, stability, and availability. In this review work 442 research papers on implementation/adoption of cloud computing in the field of higher education were explored using the bibliometric analysis and reviews of numerous studies were incorporated. these results demonstrate that during the past few years, there has been an increase in interest in cloud computing research, which has provided an improved understanding of the application or implementation or adaptation of cloud computing in the sphere of higher education. this report will give researchers, students, publishers, and experts information about the present cloud computing deployment trend in the higher education sector. © 2023 IEEE.

关键词： Cloud computing

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Development of Green computing through Power Management in Wireless Networks using Machine Learning 7

Development of Green Computing through Power Management in W...

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7th international conference on Inventive Computation Technologies, ICICT 2024

作者： Raja, S.R. Arya, Hemlata Ramya, D. Sivakumar, S. Arigela, Arun Kumar Venu, Nookala Saveetha Deemed University SIMATS Saveetha College of Liberal Arts And Science Department of Computer Science Chennai India Department of Computer Science & Engineering Madhya Pradesh Gwalior India Sathyabama Institute of Science And Technology Electrical And Electronics Engineering Rajiv Gandhi Salai Chennai India Vel Tech Rangarajan Dr. Sagunthala R And D Institute of Science And Technology Department of Electrical And Electronics Engineering Chennai Tamilnadu Avadi600062 India Department of Csit Telangana Hyderabad India Centre For IoT Madhya Pradesh Gwalior474 005 India

ISBN: (纸本)9798350359299

this study investigates the use of Support Vector Machines (SVM), Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN) to improve power utilization in green data centers. the study examines each model's individual capabilities in addressing key concerns about energy efficiency and sustainability. SVM is extremely accurate in workload prediction and resource allocation, whereas CNN excels in real-time monitoring and cooling system efficiency. RNN contributes by anticipating fluctuations in energy use and adapting to dynamic workload changes over time. the research uses ten hypothetical trials to demonstrate the models' consistent performance across multiple measures. these results suggest that SVM, CNN, and RNN have transformative potential in the development of flexible, efficient, and sustainable green data centers. the study adds to the larger discussion about green computing by emphasizing the role of powerful machine learning models in shaping the future of ecologically responsible data center operations. © 2024 IEEE.

关键词： Support vector machines

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Jamming Waveform Designed in Focused Energy Delivery for Precision Electronic Warfare Scenario 7

Jamming Waveform Designed in Focused Energy Delivery for Pre...

引用

7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Zhang, Kedi Wang, Jing Zhou, Qingsong Zhang, Jianyun National University of Defense Technology College of Electronic Engineering Hefei China National University of Defense Technology College of Computer Changsha China

ISBN: (纸本)9781665478571

Precision electronic warfare (PREW) is an application to solve many problems that are difficult to solve with current electronic warfare methods. However, the current issues related to designing jamming waveforms suitable for ultra-sparse used in PREW scenarios are still worthy of further study. this paper addresses this problem by employing sequential cone programming (SCP) in convex optimization techniques to design constant-modulus jamming waveforms suitable for the PREW scenarios. In a standard PREW scenario, the spatial energy focusing effect of the waveforms generated by the proposed algorithm is verified. the waveforms designed by the proposed algorithm based on the verification results are more suitable for the PREW scenario deployment than the previous method. © 2022 IEEE.

关键词： Convex optimization

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Factors Affecting the Short-Form Video Consumption on Social Media Platforms 9

Factors Affecting the Short-Form Video Consumption on Social...

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Joint 9th international conference on Digital Arts, Media and technology with 7th ECTI Northern Section conference on Electrical, Electronics, Computer and Telecommunications engineering, ECTI DAMT and NCON 2024

作者： May, Shin thant Siddoo, Veeraporn Prince of Songkla University College of Computing Phuket Campus Phuket Thailand

ISBN: (纸本)9798350318241

this paper aims to examine the various factors that influence the consumption of short-form video on social media platforms. the examination includes both internal and external factors affecting user engagement. the study integrated the technology Acceptance Model (TAM) and the Uses and Gratifications theory (UGT). the research approach employed was a systematic literature review, wherein data were obtained from several databases spanning the years 2018 to 2023. there were 13 articles that matched the search criteria. there are five internal factors that explain the customers' motivation and twenty-eight external factors that explain the utilization of technology. this paper propose that future investigations should encompass a broader range of business domains and use other theoretical frameworks to better understand short-form video consumption's behavior. © 2024 IEEE.

关键词： Social networking (online)

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Iterative partial computation offloading algorithm for LEO satellite edge computing served by MEO satellite 24

Iterative partial computation offloading algorithm for LEO s...

引用

2024 7th international conference on Computer Information Science and Artificial Intelligence, CISAI 2024

作者： Wang, Jin Zhang, Guoting Bai, Zhen Guo, Yinchun Yang, Yang Beijing Institute of Tracking and Telecommunications Technology Beijing China Shanghai Aerospace Electronic Technology Institute Shanghai China School of Electronics and Information Engineering Beihang University Beijing China

ISBN: (纸本)9798400707254

this paper studies the energy-efficient optimization problem for low earth orbit (LEO) satellite edge computing served by medium earth orbit (MEO) satellite when partial computation offloading strategy is adopted. An optimization model with the goal of minimizing the total energy consumption of LEO satellites is established, with constraints of task tolerable delay, transmit power, and CPU-cycle frequency, forming a challenging mixed-integer and nonlinear problem. Based on the non-convexity of the optimization problem and the coupling variables, the problem is decomposed into three manageable subproblems as local computing subproblem, task offloading subproblem, and resource allocation subproblem, which are solved using analytical method, convex optimization, and Lagrange dual decomposition method, respectively. Based on the solution of the subproblems, alternative iterations are performed to converge to the optimal value. the simulation results show that when using the partial computation offloading optimization algorithm, the total energy consumption required for LEO satellites is significantly lower than that of local computing and full offloading strategies. © 2024 Copyright held by the owner/author(s).

关键词： Computation offloading

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Drowsiness Detection for Drivers using IoT 7

Drowsiness Detection for Drivers using IoT

引用

7th international conference on computing Methodologies and Communication, ICCMC 2023

作者： Saranya, S.S. Kavitha, M.N. Sivasenthil, M. Koushik, K. Ashwin, M. Computer Science and Engineering Kongu Engineering College Erode India Bachelor of Science Information Systems Kongu Engineering College Erode India

ISBN: (纸本)9781665464086

the challenges existing sleep monitoring system generate alarm sounds notification to the drivers when they are drowsy. they used computer vision method in that recognized face to detect drivers not eye. these are the current technology tenser flow, Keras etc. While driving there with a lot of noise in the surrounding, the drivers can easily divert from sleep. Alert the drivers by message to take some rest for sometimes is useless while driving driver don't use the mobile then it is not possible to see message. To overcome this problem, the proposed system helps to prevent driver drowsiness. then set a vibrate motor under a driver seat. It does not affect the driver in any manner. By using vibrate methodology, it can help the driver awake from the sleep these are tools used in this project raspberry pi, pi camera, and vibration motor. Video can store the live recordings in external storage. Even though a network issue can prevent data from being stored if the car is in a hilly area, external storage is provided here to record video. Rotary encoder will measure steering wheel. the car will automatically switch off if the steering radius is not consistent. © 2023 IEEE.

关键词： Digital storage

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Research on Target Video Simulation and Simulation technology Based on Shipborne three-coordinate Radar System 7

Research on Target Video Simulation and Simulation Technolog...

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7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Fang, Fengtang Zhang, Zhen Xing, Yupeng Han, Lei Xu, Yue Cssc Systems Engineering Research Institute Beijing100094 China

ISBN: (纸本)9781665478571

We propose a method for generating video simulation of shipborne three-coordinate radar. First, the research work is carried out on the shipboard three-coordinate radar system, a radar video simulation device is designed to simulate the generation of radar video, and the target echo video block is analyzed. the calculation and drawing methods are based on the K-distributed sea clutter model to simulate the clutter background environment. Finally, the application effect is verified based on the radar video simulation device. © 2022 IEEE.

关键词： Ships

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