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Industry 4.0: Discovering Scientific Trends through a Bibliometric Analysis 1

引用

8th international conference on Information and Communication technology for Intelligent Systems, ICTIS 2024

作者： Ventayen, Randy Joy M. International Accreditation Office Pangasinan State University Pangasinan Philippines

ISBN: (数字)9789819758104

ISBN: (纸本)9789819758098

the emergence of revolutionary Industry 4.0 in manufacturing businesses has become a significant area of interest. this research paper examines the current state of knowledge and advancements in the field of Industry 4.0. To achieve this, the authors utilized the PRISMA method to analyze and identify published research studies from the Scopus database. the study found a total of 14,435 documents published on this topic between 2011 and 2021. Articles were found to be the most common type of publication, with Engineering being the predominant subject theme. the most influential source of publications in this area was the conference proceedings, specifically Procedia Computer Science by Elsevier. Additionally, Erwin Rauch, affiliated with the Free University of Bozen-Bolzano in Italy, emerged as the most influential researcher. the analysis also revealed that Germany, Italy, India, and the United States were the countries with the most prolific authors in this field. In conclusion, the research indicates that Industry 4.0 has undergone substantial scientific development and significantly impacted the global manufacturing industry by improving industrial processes. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Bibliographies

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Evaluating Keyphrase Extraction Methods for Clustering Influenza-Related Scientific Papers 8

Evaluating Keyphrase Extraction Methods for Clustering Influ...

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8th international Iranian conference on Signal Processing and Intelligent Systems, ICSPIS 2022

作者： Forghani, Majid Firstkov, Artyom Alyannezhadi, Mohammad. M. Forghani, Kazem Krasovskii Institute of Mathematics & Mechanics Mathematical Programming Lab. Yekaterinburg Russia University of Science and Technology of Mazandaran Department of Science Behshahr Iran Iran University of Science and Technology Computer Science Department Tehran Iran

ISBN: (纸本)9781665476232

the number of annual scientific publications is growing year by year, which has led to the accumulation and formation of large databases. this increases the complexity of the search for relevant articles. Modern search engines leverage keyphrases to improve the performance of search results. Keyphrases (or keywords) are a set of single or multi-word expressions which provide a very compact summary of contents and describe the overall topic of a document. Implementation of keyphrase extraction can be varied for specific-domain databases. this motivated us to evaluate these methods on a database of influenza scientific literature. In this work, we considered 9 well known methods for extracting keyphrases. Our preliminary results show txhat graph-based methods which employ topics outperform others using our database. We also determined that influenza-related papers can be grouped into three general topics: public health & medical care;molecular biology & immunology;and phylogenetic & epidemiological studies. © 2022 IEEE.

关键词： database systems

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Elevating database Performance: Current Caching and Prefetching Strategies for Online databases in Nigeria 8th

Elevating Database Performance: Current Caching and Prefetch...

引用

8th international Visual Informatics conference, IVIC 2023

作者： Kehinde, Olatunji Austine Zulkifli, Zahidah Surin, Ely Salwana Mat Junurham, Nur Leyni Nilam Putri Mahmud, Murni Department of Library and Information Science Kulliyyah of Information and Communication Technology International Islamic University Malaysia Kuala Lumpur Malaysia Department of Information Systems Kulliyyah of Information and Communication Technology International Islamic University Malaysia Kuala Lumpur Malaysia Institute of Visual Informatics Universiti Kebangsaan Malaysia Bangi Malaysia

ISBN: (纸本)9789819973385

this study investigated caching and prefetching techniques to improve data access performance in online databases, considering factors like data popularity, access patterns, and cache coherence. the research design adopted for this study was the descriptive survey. the population comprised of 1387 undergraduates computer science students in public tertiary institutions in Ekiti State. Simple random sampling technique was adopted to select 150 computer science students from three public tertiary institutions in the study area. the instrument used for data collection was a structured 4 Likert type questionnaire. the questionnaire was distributed to the respondents to find out the effectiveness of caching and prefetching techniques on online database. the instrument was both face and content validated by two experts from department of computer science in Bamidele Olumilua University of Education Science and technology, Ikere-Ekiti, Ekiti State. the reliability of the instrument was ensured using Pearson Product Moment Correlation formula which yielded a coefficient of 0.97. the data collected were analyzed using descriptive statistics such as mean and standard deviation. the result showed that the current caching and prefetching techniques employed in online databases are highly effective;the different access patterns have effect on the effectiveness of caching and prefetching techniques in online databases and there are impacts of cache coherence mechanisms on the efficiency of caching and prefetching techniques in online databases. It was therefore recommended that the inclusion of caching and prefetching in curriculum is important across all educational level in Nigeria. In addition, caching and perfecting has come under fire for focusing mostly on computer science. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Engineering education

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Novel topology identification method for distribution network based on graph database 8

Novel topology identification method for distribution networ...

引用

8th international conference on Energy System, Electricity, and Power, ESEP 2023

作者： Zhu, Tianyi Wang, Shunjiang Cui, Jia Wang, Tong Wang, Wenzhi Han, Ni Li, Chaoran Electric Power Research Institute State Grid Liaoning Electric Power Company Limited Shenyang110002 China State Grid Liaoning Electric Power Company Limited Shenyang110002 China School of Electrical Engineering Shenyang University of Technology Shenyang110870 China

ISBN: (数字)9781510679801

ISBN: (纸本)9781510679795

In the power system, the distribution network is an important infrastructure for safeguarding people's livelihood and the last link for serving residential users. Its safe and stable operation greatly affects the quality and reliability of users' electricity consumption. With the continuous promotion of the smart grid strategy, the power system measurement technology is constantly improved, which provides new ideas for distribution network topology identification, and also makes it possible to accurately estimate the impedance parameters of distribution lines. In this paper, a topology identification method is proposed based on distribution network data analysis. Firstly, the voltage fluctuation principle of load nodes in the distribution network is introduced, which provides a theoretical basis for the extraction of feature data. Secondly, for the three-phase unbalance phenomenon existing in the medium voltage distribution network, an imputation method for the outlet voltage of distribution transformers is proposed. the distribution network is equivalently modeled according to the degree of similarity between the characteristic data of each distribution transformer. thirdly, the equivalent network is cut by using the standardized cutting method in the spectral clustering analysis method to get the correspondence between distribution transformers and feeders. And the topology reconstruction method of distribution network based on mutual information and maximum spanning tree algorithm is tested. © 2024 SPIE.

关键词： Clustering algorithms

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Research on multi-type demand response user profile based on improved k-means clustering algorithm 8

Research on multi-type demand response user profile based on...

引用

8th international conference on Energy System, Electricity, and Power, ESEP 2023

作者： Jiang, Mengmeng Qi, Yuliang Zhang, Hui Lin, JunHao Guo, Chunjie Wei, Shanshan Gao, Hui Shandong Inspur Database Technology Co. 1036 Langchao Road Shandong Jinan250101 China State Grid Shandong Integrated Energy Services Co. Ltd. 1 Shengping Street Shandong Jinan250001 China

ISBN: (数字)9781510679801

ISBN: (纸本)9781510679795

the customer power load has the characteristics of complex and irregular use. therefore, in order to meet the demand response scheduling requirements, cluster analysis should be carried out according to the user load characteristics. To solve the above problems, this paper proposes a multi-type demand response user portrait research method based on improved k-means clustering algorithm. Firstly, the improved k-means clustering algorithm is used to analyze the user's electricity consumption data, study the user's electricity consumption behavior, and classify the user. then, considering the dynamic elastic adjustment coefficient, the price-based demand response model is constructed. Finally, select the demand response characteristic index, construct the demand response characteristic evaluation system and establish the user demand response portrait. the validity of the model is verified by analyzing the energy use data of a park in Shandong Province. the example analysis shows that the method used in this paper can effectively reflect the acceptability of demand response of different types of users under different electricity prices. © 2024 SPIE.

关键词： Cluster analysis

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Comprehensive Study on Machine Learning Applications for Heart Disease Risk Prediction 8

Comprehensive Study on Machine Learning Applications for Hea...

引用

8th international conference on Digital Technologies in Education, Science and Industry, DTESI 2023

作者： Adiat, Lashyn Altaibek, Aizhan Nurtas, Marat Altayeva, Aigerim International Information Technology University Manas St. 34/1 Almaty050000 Kazakhstan Institute of Ionosphere Gardening community IONOSPHERE 117 Almaty050020 Kazakhstan Al-Farabi Kazakh National University al-Farabi Avenue 71 Almaty050040 Kazakhstan

this research investigates an analytical approach to machine learning applications for cardiovascular disease (CVD) risk prediction on a publicly accessible database. the dataset contains crucial information about patients' individual characteristics, such as age, blood pressure, ECG at rest, heart rate, and four types of chest pain. the purpose of this research is to choose the most suitable model for heart attack analysis. Descriptive analytics and exploratory data analysis based on various factors were done to predict risk by employing machine learning algorithms and techniques, including k-nearest neighbours, logistic regression, support vector machines (SVM) and random forests. the research involves thorough data analysis and rigorous model training processes. © 2023 Copyright for this paper by its authors.

关键词： Blood pressure

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Qsync: extending Simplified SMR Protocol with Partial Network Partition Tolerance 25

Qsync: Extending Simplified SMR Protocol with Partial Networ...

引用

8th international conference on High Performance Computing in Asia-Pacific Region, HPC Asia 2025

作者： Kida, Aoi Kawashima, Hideyuki Keio University Fujisawa Japan

ISBN: (纸本)9798400713354

State Machine Replication (SMR) is a fundamental replication technique for building fault-tolerant distributed systems, ensuring consistency across multiple nodes. SMR protocol has been widely adopted in systems that require high availability and strong consistency. Rabia is an SMR protocol that prioritizes simplicity of implementation using a randomized consensus algorithm. Our analysis reveals a vulnerability in the Rabia protocol. When partial network partitioning faults occur, an improper client request distribution leads to inconsistent queue states across replica nodes. these inconsistent states cause Rabia-based distributed systems to enter a livelock state that prevents any meaningful progress, effectively rendering the system inoperative. this paper proposes Qsync, a lightweight enhancement to the Rabia protocol that provides tolerance to partial network partitioning through efficient queue state synchronization mechanisms while preserving its core simplicity. To evaluate the effectiveness of Qsync, we conducted experiments with various partial network partitioning scenarios on small-scale clusters where Rabia-based systems would typically be deployed. Where the original Rabia-based system's throughput drops to zero, the system with Qsync maintains operational continuity. © 2025 Copyright held by the owner/author(s).

关键词： Fault tolerant computer systems

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Fogmotic: Applying Osmotic Data Services to improve database Operations on SmartCity Environments 8

Fogmotic: Applying Osmotic Data Services to improve Database...

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8th IEEE international Smart Cities conference, ISC2 2022

作者： Souza, Arthur Cacho, Nelio Batista, thais Federal University of Rio Grande Do Norte Natal Brazil

ISBN: (数字)9781665485616

ISBN: (纸本)9781665485616

the increase in the computing capabilities of Edge devices made it possible to distribute the processing contracted in the Cloud, leveraging the emergence of Edge Computing and Fog Computing. Fog's improved processing of data obtained by Edge quickly progressed from simple cleaning and categorization to more refined and contextually related information. thus, there is a growing need for persistent storage at the Fog/Edge level, especially in facing the scenarios present in Osmotic Computing. With this context in mind, our work presents a solution for data persistence between the various levels of Edge/Fog/Cloud. Going further, we introduce Fogmotic, a database as a Service platform that focuses on distribution, synchronization, reliability, efficiency, and data migration at the Edge/Fog/Cloud levels. Finally, we present an experimental evaluation of the reading, writing, and sync rate performance obtained by Fogmotic. © 2022 IEEE.

关键词： Fog

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8th international conference on Soft Computing: theories and Applications, SoCTA 2023

8th International Conference on Soft Computing: Theories and...

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8th international conference on Soft Computing: theories and Applications, SoCTA 2023

ISBN: (纸本)9789811998577

the proceedings contain 80 papers. the special focus in this conference is on Soft Computing: theories and Applications. the topics include: Machine Learning: An Analytical Approach for Pattern Detection in Diabetes;a Dynamic Weighted Federated Learning for Android Malware Classification;entropy Measure for the Linguistic q-Rung Orthopair Fuzzy Set;empirical Analysis of Unsupervised Link Prediction Algorithms in Weighted Networks;detection of Fraudulent Credit Card Transactions Using Deep Neural Network;recommendation System and Its Techniques in Machine Learning: A Survey;approximation of Signal Belongs to W′(Lp, ξ(t) ) Class by Generalized Nörlund-Cesáro Product Means;dignet: A Deep Learning-Based Efficient Digit Recognition System;implementation of Artificial Neural Network for Demanufacturing Operation in the Rail Industry;Voice Command Automation System (VCAS) for Controlling Electrical Devices Using Arduino;turing Machines Behind the Horizon: Modeling Black Hole Interiors as Transfinite Limited Turing Machines;a Review on Deep Learning-Enabled Healthcare Prediction Technique: An Emerging Digital Governance Approach;evaluation of Deep Learning Technique on Working Model of Self-driving Car—A Review;analysis of the Distractions in Youth Due to Social Media and the Effects on their Concentration Abilities;the Intervention of technology in Education Under Isolation: Intuitions from Covid;analysis of Bao-Zhou-Chen-Liu’s Hybrid Chaotic System;identification of Skin Lesion with Adaptive Tasmanian Devil Optimization-Based Transfer Learning;Synchronization of MLS Chaotic System Using Sliding Mode Control Technique;performance Analysis of User Behavior Pattern Mining Using Web Log database for User Identification;diversified Recommendation Generation Using Graph Convolution Neural Network;an Imperfect Production System for Non-instantaneous Deteriorating Goods with Preservation technology Under Cap-and-Trade Policy;Human Activity Recognition Using a Hybrid Dilated CNN a

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Framework for Developing Modeling Parameters of FRP—Retrofitted Reinforced Concrete Shear Walls 8th

Framework for Developing Modeling Parameters of FRP—Retrofi...

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8th international conference on Advanced Composite Materials in Bridges and Structures, ACMBS 2021

作者： Dukes, Jazalyn Sattar, Siamak National Institute of Standards and Technology GaithersburgMD United States

ISBN: (纸本)9783031096310

Aging buildings and ever evolving design codes imply the need of implementing retrofit techniques to ensure the safety and functionality of buildings under current operating loads as well as extreme hazard events. Fiber reinforced polymer (FRP) composites are being implemented in practice to retrofit existing buildings as a popular retrofit system because of their high strength, lightweight properties, minimal profile, and versatile application. there are standards that help the engineer implement an FRP retrofit of a building (e.g., ACI 440.2R). However, the current performance-based seismic design standards such as ASCE/SEI 41-17 do not provide guidance on modeling parameters and acceptance criteria of reinforced concrete retrofitted components including beams, columns, and shear walls. this study develops a database of experimental tests of FRP retrofitted reinforced concrete (RC) shear walls, which contains over 200 test specimens from test programs performed across the globe. the database is organized to present the most important parameters and details in an accessible format. the database is an essential means to fill in missing gaps of information for the practicing engineer by analyzing the responses of the walls and determining backbone curves and modeling parameters relevant to retrofitted shear walls. © 2023, Canadian Society for Civil Engineering.

关键词： database systems

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