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Study of Assessing the Stability of Rwanda’s Power System from big data Based on Power Generation 1

16th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2020 in conjunction with the 13th International Conference on Frontiers of Information technology, applications and Tools, FITAT 2020

作者： Shyirambere, Gilbert Chang, Kuo-Chi Chu, Kai-Chun Wang, Hsiao-Chuan Omer, AbdalazizAltayeb Ibrahim Amesimenu, Governor David Kwabena Chang, Fu-Hsiang Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China School of Information Science and Engineering Fujian University of Technology Fuzhou China Department of Business Management Fujian University of Technology Fuzhou China Institute of Environmental Engineering National Taiwan University Taipei Taiwan College of Mechanical and Electrical Engineering National Taipei University of Technology Taipei Taiwan Department of Business Administration North Borneo University College Sabah Malaysia Department of Tourism Shih-Hsin University Taipei Taiwan

ISBN: (数字)9789813364202

ISBN: (纸本)9789813364196

Rwanda has insufficient of electricity in which the electricity access among its citizens is at 53% equals to 224 MW of power generation. However, even among 53% of electrification, there are still some blackouts and erratic outages in cities during the night when many devices are connected on the system. This blackout and sudden shutdown could make the power system stability of Rwanda to be questionable and it can be so-called unstable. Meanwhile, the Rwanda Government is very ambitious targeting to achieve universal access by 2023/24 in which 52% will be on-grid connected and 48% off-grid. In this study, the current and proposed Rwanda power generation sector, transmission sector, and distribution sector are discussed;general Rwanda energy sources like, hydro, solar, diesel thermal, methane gas, peat are also discussed based on big data. In the end, conclusion and some recommendations have been proposed to be done in order to make stable the power system. For instance, Kalman-filtered solar forecasting approach could be used to predict weather condition every hour so that blackout coming from bad atmosphere could be prevented. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Outages

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Model Degradation Hinders Deep Graph Neural Networks

arXiv

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arXiv 2022年

作者： Zhang, Wentao Sheng, Zeang Yin, Ziqi Jiang, Yuezihan Xia, Yikuan Gao, Jun Yang, Zhi Cui, Bin School of CS & Key Laboratory of High Confidence Software Technologies Peking University China Center for Data Science Peking University National Engineering Laboratory for Big Data Analysis and Applications China Beijing Institute of Technology China

Graph Neural Networks (GNNs) have achieved great success in various graph mining tasks. However, drastic performance degradation is always observed when a GNN is stacked with many layers. As a result, most GNNs only have shallow architectures, which limits their expressive power and exploitation of deep neighborhoods. Most recent studies attribute the performance degradation of deep GNNs to the over-smoothing issue. In this paper, we disentangle the conventional graph convolution operation into two independent operations: Propagation (P) and Transformation (T). Following this, the depth of a GNN can be split into the propagation depth (Dp ) and the transformation depth (Dt ). Through extensive experiments, we find that the major cause for the performance degradation of deep GNNs is the model degradation issue caused by large Dt rather than the over-smoothing issue mainly caused by large Dp. Further, we present Adaptive Initial Residual (AIR), a plug-and-play module compatible with all kinds of GNN architectures, to alleviate the model degradation issue and the over-smoothing issue simultaneously. Experimental results on six real-world datasets demonstrate that GNNs equipped with AIR outperform most GNNs with shallow architectures owing to the benefits of both large Dp and Dt, while the time costs associated with AIR can be ignored. Copyright © 2022, The Authors. All rights reserved.

关键词： Graph neural networks

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EC²Detect: Real-Time Online Video Object Detection in Edge-Cloud Collaborative IoT

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IEEE Internet of Things Journal 2022年第20期9卷 20382-20392页

作者： Siyan Guo Cong Zhao Guiqin Wang Jiaqing Yang Shusen Yang National Engineering Laboratory for Big Data Analytics and the School of Mathematics and Statistics Xi’an Jiaotong University Xi’an China Department of Computing Imperial College London London U.K. National Engineering Laboratory for Big Data Analytics and the School of Computer Science and Technology Xi’an Jiaotong University Xi’an China School of Mathematics and Statistics Xi’an Jiaotong University Xi’an China National Engineering Laboratory for Big Data Analytics and Ministry of Education Key Laboratory for Intelligent Networks and Network Security Xi’an Jiaotong University Xi’an China Industrial Artificial Intelligence Center Pazhou Laboratory Guangzhou China

Video object detection is a fundamental technology of intelligent video analytics for Internet of Things (IoT) applications. However, even with extraordinary detection accuracy, predominating solutions based on deep convolutional neural networks (DCNNs) cannot achieve real-time online object detection on video streams with a low end-to-end (E2E) response latency and therefore cannot be applied to proliferating latency-sensitive IoT applications like autonomous driving requiring large-scale intelligent video analytics. To address this issue, we present EC2Detect, an edge-cloud collaborative real-time online video object detection method. Specifically, we propose a tracking-assisted object detection architecture based on edge-cloud collaboration with keyframe selection, where the accurate but heavy object detection is conducted by the Cloud on sparse keyframes adaptively selected according to their semantic variation, and the lightweight object tracking is used to localize and identify objects in other frames at edge devices. Extensive experiments of our real-world prototype demonstrate that, EC2Detect significantly outperforms state-of-the-art methods in terms of processing speed (up to $4.77\times $ faster), E2E latency (up to $8.12 \times $ lower), and edge-cloud bandwidth occupation ( $17 \times $ lower) with an acceptable mAP, which can effectively support large-scale intelligent video analytics in practice. Source code of EC2Detect is available at https://***/ECCDetect/ECCDetect .

关键词： Object detection Image edge detection Streaming media Internet of Things Collaboration Visual analytics Feature extraction

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Cryptanalysis of an anonymous message authentication scheme for smart grid 13th

Cryptanalysis of an anonymous message authentication scheme ...

引用

13th International Conference on Genetic and Evolutionary Computing, ICGEC 2019

作者： Liang, Xiao-Cong Wu, Tsu-Yang Lee, Yu-Qi Wang, Tao Chen, Chien-Ming Chen, Yeh-Cheng School of Information Science and Engineering Fujian University of Technology Fuzhou350118 China Fujian Provincial Key Lab of Big Data Mining and Applications Fujian University of Technology Fuzhou350118 China National Demonstration Center for Experimental Electronic Information and Electrical Technology Education Fujian University of Technology Fuzhou350118 China College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China Department of Computer Science University of California DavisCA95616 United States

ISBN: (纸本)9789811533075

Authentication schemes are used to authenticate the identity of communication parties and widely applied to several environments. Recently, Wu et al. proposed an anonymous message authentication scheme in smart grid. However, we show that their scheme has several security weaknesses based on the CK adversarial model in this paper. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Authentication

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Molecular epidemiology and phylogenetic analysis of influenza viruses A (H3N2) and B/ Victoria during the COVID-19 pandemic in Guangdong, China

引用

Infectious Diseases of Poverty 2024年第4期13卷 99-100页

作者： Zhiqi Zeng Yong Liu Wenxiang Jin Jingyi Liang Jinbin Chen Ruihan Chen Qianying Li Wenda Guan Lixi Liang Qiubao Wu Yuanfang Lai Xiaoyan Deng Zhengshi Lin Chitin Hon Zifeng Yang State Key Laboratory of Respiratory Disease National Clinical Research Center for Respiratory Disease Guangzhou Institute of Respiratory Health the First Affiliated Hospital of Guangzhou Medical University Guangzhou Guangdong 510180 P.R. China Guangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases KingMed School of Laboratory Medicine Guangzhou Medical University Guangzhou People’s Republic of China Respiratory Disease AI Laboratory on Epidemic Intelligence and Medical Big Data Instrument Applications Faculty of Innovative Engineering Macau University of Science and Technology Macau SAR China Department of Engineering Science Faculty of Innovation Engineering Macau University of Science and Technology Taipa Macau China Guangzhou Laboratory Guangzhou China Kingmed Virology Diagnostic and Translational Center Guangzhou Kingmed Center for Clinical Laboratory Co. Ltd. Guangzhou China

Background Non-pharmaceutical measures and travel restrictions have halted the spread of coronavirus disease 2019(COVID-19)and ***,with COVID-19 restrictions lifted,an unanticipated outbreak of the influ-enza B/Nictoria virus in late 2021 and another influenza H3N2 outbreak in mid-2022 occurred in Guangdong,southern *** mechanism underlying this phenomenon remains *** better prepare for potential influenza out-breaks during COVID-19 pandemic,we studied the molecular epidemiology and phylogenetics of influenza A(H3N2)and BNictoria that circulated during the COVID-19 pandemic in this *** From January 1,2018 to December 31,2022,we collected throat swabs from 173,401 patients in Guang-dong who had acute respiratory tract *** viruses in the samples were tested using reverse tran-scription-polymerase chain reaction,followed by subtype identification and sequencing of hemagglutinin(HA)and neuraminidase(NA)*** and genetic diversity analyses were performed on both genes from 403 samples.A rigorous molecular clock was aligned with the phylogenetic tree to measure the rate of viral evolution and the root-to-tip distance within strains in different years was assessed using regression curve models to determine the *** During the early period of COVID-19 control,various influenza viruses were nearly undetectable in respiratory *** control measures were relaxed in January 2020,the influenza infection rate peaked at 4.94%(39/789)in December 2021,with the influenza B/Victoria accounting for 87.18%(34/39)of the total influenza *** months later,the influenza infection rate again increased and peaked at 11.34%(255/2248)in June 2022;influenza A/H3N2 accounted for 94.51%(241/255)of the total influenza cases in autumn *** diverse geographic distribution of HA genes of B/Nictoria and A/H3N2 had drastically reduced,and most strains originated from *** rate of B/Victoria HA e

关键词： Insidious transmission Influenza COVID-19 control Genetic diversity Evolution

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Study of Low-Cost-Based Smart Home Control Using IoT Powered by Photovoltaic Cells 1

引用

作者： Ahmad, Shoaib Chang, Kuo-Chi Sung, Tien-Wen Chu, Kai-Chun Zhou, Yu-Wen Omer, Abdalaziz Altayeb Ibrahim Amesimenu, Governor David Kwabena Chang, Fu-Hsiang Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China School of Information Science and Engineering Fujian University of Technology Fuzhou China Department of Business Management Fujian University of Technology Fuzhou China College of Mechanical and Electrical Engineering National Taipei University of Technology Taipei Taiwan Department of Business Administration North Borneo University College Kota Kinabalu Sabah Malaysia Department of Tourism Shih-Hsin University Taipei Taiwan

ISBN: (数字)9789813364202

ISBN: (纸本)9789813364196

This research mainly uses the Wi-Fi module (ESP8266) microcontroller to implement the IoT-based smart home system. In this study of smart home system is able to power the circuit by the photovoltaic cell itself and then wirelessly switch to the required load. As technology is expanding every day, mobile, robotics, machines learning are advancing their technology then why our house is an exception. Today’s house moving slowly based on common/human input controlling to smart/IoT-enabled devices to be controlled remotely. Currently, use the existing smart home system technology that is limited to this device only. Because of this, IoT devices are now being applied in various fields, but unfortunately, low cost and simple IoT applications are still insufficient in smart home. However, this study is concerned with the Node MCU (ESP8266) microcontroller used to control the power switches remotely. The users can control witches using web application after authenticating based on low cost and simple IoT application systems;this study has important contributions to the development of smart homes with high price–performance ratio in future. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Microcontrollers

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Dynamic Topic Model for Tracking Topic Evolution and Measuring Popularity of Scientific Literature

Dynamic Topic Model for Tracking Topic Evolution and Measuri...

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IEEE International Conference on data Science in Cyberspace (DSC)

作者： Yezheng Liu Jicheng Wang Yang Qian Yuanchun Jiang Jianshan Sun Yidong Chai School of Management Hefei University of Technology National Engineering Laboratory for Big Data Distribution and Exchange Technologies Key Laboratory of Process Optimization and Intelligent Decision Making Ministry of Education

ISBN: (纸本)9781665418164

With the progress of science and technology, a large number of scientific papers are published every year. Faced with such large data, identifying high-value research and hot research directions has become an interesting and important task. Previous studies focus less on the popularity measurement of research papers. In this paper, we use a dynamic topic model (DTM) for tracking the topic evolution trend and measuring the popularity of research papers based on the topic hotness. To test our model effectiveness, we conduct experiments on 5,964 research papers in the category of management. Our results show that DTM can help to monitor topic evolution and measuring popularity for scientific literature.

关键词： Current measurement Conferences Cyberspace data science Market research data models Time factors

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Optimal Operation of Reservoir Power Generation Based on Improved Grey Wolf Algorithm 6th

Optimal Operation of Reservoir Power Generation Based on Imp...

引用

6th International Conference on Advanced Machine Learning Technologies and applications, AMLTA 2021

作者： Chen, Ran-Fan Chang, Kuo-Chi Chu, Kai-Chun Chang, Fu-Hsiang Wang, Hsiao-Chuan Hsu, Tsui-Lien Liu, Jia-jing Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China School of Information Science and Engineering Fujian University of Technology Fuzhou China School of Management Fujian University of Technology Fuzhou China Department of Tourism Shih-Hsin University Taipei Taiwan Institute of Environmental Engineering National Taiwan University Taipei Taiwan Institute of Construction Engineering and Management National Central University Taoyuan Taiwan College of Mechanical & Electrical Engineering National Taipei University of Technology Taipei Taiwan Department of Business Administration North Borneo University College Sabah Malaysia

ISBN: (纸本)9783030697167

The operation efficiency of the power station mainly depends on power generation. Therefore, under the constraints of water level, water amount, and output of hydropower station, generation flow in each period can be reasonably controlled according to the initial operating conditions of reservoir and inflow runoff, maximize the power generation of cascade power station within the operation cycle. Grey wolf algorithm (GWO) is easy to implement, simple in structure, requires few parameters to be changed, and has a simple operating principle. The gray wolf algorithm’s solution process simulated wolves’ hunting behavior, and the prey was regarded as the optimal global solution. All the candidate solutions were regarded as a gray wolf population. As shown from the above results, the GWOs algorithm has a more vital exploration ability and development ability to optimize single-peak and multi-peak functions better than the other two algorithms. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Reservoirs (water)

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Study of Smart Lifting 3D Garage Design Based on the Low-Cost PLC Control System 6th

Study of Smart Lifting 3D Garage Design Based on the Low-Cos...

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6th International Conference on Advanced Machine Learning Technologies and applications, AMLTA 2021

作者： Zhang, Rongsheng Chang, Kuo-Chi Chu, Kai-Chun Chang, Fu-Hsiang Wang, Hsiao-Chuan Hsu, Tsui-Lien Lin, Yuh-Chung Sung, Tien-Wen Trong-The, Nguyen Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China School of Information Science and Engineering Fujian University of Technology Fuzhou China School of Management Fujian University of Technology Fuzhou China Department of Tourism Shih-Hsin University Taipei Taiwan Institute of Environmental Engineering National Taiwan University Taipei Taiwan Institute of Construction Engineering and Management National Central University Taoyuan Taiwan College of Mechanical and Electrical Engineering National Taipei University of Technology Taipei Taiwan Department of Business Administration North Borneo University College Sabah Malaysia

ISBN: (纸本)9783030697167

As the current computer design level continues to improve, the process equipment and production line management levels are relatively stable. The intelligent and automatic 3D garage-type has shown a diversified development trend. Several garage types are currently in everyday use, including vertical lifting type, vertical lifting type, simple lifting type, horizontal shifting circulation type, channel stacking type, etc. The 3D lifting garage has a simple structure, small floor space, low operating cost, and the most extensive application requirements. However, this study summarizes the application status and development prospects of smart lifting 3D garages first. Then the system analyzes the working principle and mechanical structure characteristics of the smart lifting 3D garage, analyzes the control requirements, and designs the semi-automatic control system of the 3D garage S7–1200—it including the PLC control program and the man-machine interface. Finally, the overall system control effect is verified through simulation. This study meter has superficial operation characteristics, a high degree of automation, fast operation speed, high stability, and has deep development value and application prospects in specific markets. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Automation

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Study of data Repetitive Record Cleaning technology of MES System in High-Tech Process 6th

Study of Data Repetitive Record Cleaning Technology of MES S...

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6th International Conference on Advanced Machine Learning Technologies and applications, AMLTA 2021

作者： Chang, Kuo-Chi Chu, Kai-Chun Lin, Yuh-Chung Chang, Fu-Hsiang Wang, Hsiao-Chuan Hsu, Tsui-Lien Nguyen, Trong-The Sung, Tien-Wen Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China School of Information Science and Engineering Fujian University of Technology Fuzhou China School of Management Fujian University of Technology Fuzhou China Department of Tourism Shih-Hsin University Taipei Taiwan Institute of Environmental Engineering National Taiwan University Taipei Taiwan Institute of Construction Engineering and Management National Central University Taoyuan Taiwan College of Mechanical & Electrical Engineering National Taipei University of Technology Taipei Taiwan Department of Business Administration North Borneo University College Sabah Malaysia

ISBN: (纸本)9783030697167

High-tech industries such as semiconductors have become important pillars of Taiwan’s economy under the raging COVID-19 epidemic. The MES system actively collects and monitors the production materials generated in the manufacturing process and integrates the core business required by the company’s production such as orders, suppliers, property management, production, equipment maintenance, quality control, and other processes to improve the company’s manufacturing process and production efficiency. big data of the process is the foundation of information. Good data quality is the basic condition for effective data analysis applications such as OLAP and data mining. The recursive field matching algorithm uses the recursive structure of the text field. The Sorted-Neighborhood Method (SNM) algorithm cannot solve all the matching records detected by a single keyword. data cleaning is a relatively mature field that expects more breakthroughs and innovations. There is still a lot of room for technological development, but there is still a lot of work to be done, the specific recommendations already provided. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cleaning

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