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A Survey on Recent Applications of Artificial Intelligence and Optimization for Smart Grids in Smart Manufacturing

Energies 2023年第22期16卷 7660-7660页

作者： Hsu, Chao-Chung Jiang, Bi-Hai Lin, Chun-Cheng Department of Industrial Engineering and Management National Yang Ming Chiao Tung University Hsinchu300 Taiwan International Master Program in Smart Manufacturing and Applied Information Science National Chin-Yi University of Technology Taichung411 Taiwan

To enable highly automated manufacturing and net-zero carbon emissions, manufacturers have invested heavily in smart manufacturing. Sustainable and smart manufacturing involves improving the efficiency and environmental sustainability of various manufacturing operations such as resource allocation, data collecting and monitoring, and process control. Recently, a lot of artificial intelligence and optimization applications based on smart grid systems have improved the energy usage efficiency in various manufacturing operations. Therefore, this survey collects recent works on applications of artificial intelligence and optimization for smart grids in smart manufacturing and analyzes their features, requirements, and challenges. In addition, potential trends and further challenges for the integration of smart grids with renewable energies for smart manufacturing, applications of 5G and B5G (beyond 5G) technologies in the SG system, and next-generation smart manufacturing systems are discussed to provide references for further research. © 2023 by the authors.

关键词： Smart power grids

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Characterization of Nanocomposite Membrane Based Bacterial Cellulose Made of Pineapple Waste Reinforced by Graphite Nanoplatelets

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Journal of Renewable Materials 2022年第9期10卷 2465-2475页

作者： Heru Suryanto Bili Darnanto Susilo Jibril Maulana Aminnudin Uun Yanuhar Surjani Wonorahardjo Husni Wahyu Wijaya Abu Saad Ansari Center of Excellence for Cellulose Composite(CECCom) Department of Mechanical EngineeringUniversitas Negeri MalangMalang65145Indonesia Centre of Advanced Material for Renewable Energy(CAMRY) Universitas Negeri MalangMalang65145Indonesia Master Program of Mechanical Engineering Faculty of EngineeringUniversitas Negeri MalangMalang65145Indonesia Department of Aquatic Resources Management Faculty of Fisheries and Marine SciencesBrawijaya UniversityMalang65145Indonesia Department of Chemistry Faculty of Mathematics and Natural SciencesUniversitas Negeri MalangMalang65145Indonesia Department of Materials Science&Engineering Incheon National UniversityIncheon464-742South Korea

Waste is the main problem for the *** waste for various useful applications has a benefit for the *** work has been studied for handling pineapple peel waste to make composite film bacterial cellulose nanocomposite membrane(BCNM)with addition graphite nanoplatelet(GNP).The concentration of GNP in the membrane influence the membrane *** bacterial cellulose(BC)pellicle was synthesized by using media from pineapple peel waste *** pellicle is cleaned with water and NaOH solution to be free from *** is synthesized through the mechanical disintegration *** results of disintegration using high pressure homogenizer at 150 bar and five ***/GNP is synthesized with varying addition of GNP of 2.5,5.0,10 and 100 wt%of dry bacterial nanocellulose(BNC).The BC and GNP solution were dried in an oven for 14 h at 80℃.BCNM morphology was observed using *** is dispersed and distributed in the BC matrix as *** analysis shows many peaks of BNC less pronounced with increasing of *** higher concentration of GNP,the rougher of *** optimum tensile strength of BCNM was achieved after addition GNP of 2.5 wt%.

关键词： Bacterial nanocellulose graphite nanoplatelet membrane nanocomposite pineapple waste

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Evaluating AI-Induced Anxiety and Technical Blindness in Healthcare Professionals

Evaluating AI-Induced Anxiety and Technical Blindness in Hea...

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Creative Communication and Innovative Technology (ICCIT), IEEE

作者： Michael Christian Ratlan Pardede Kurnadi Gularso Suryo Wibowo Oktafalia Marisa Muzammil Sunarno Dept. of Management University of Bunda Mulia Jakarta Indonesia Master of Management University of Bunda Mulia Jakarta Indonesia Dept. of Medical Profession Study Program Krida Wacana Christian University Jakarta Indonesia Dept. of Business Management School Dept. of Business Undergraduate Program Bina Nusantara University Bekasi Indonesia Dept. of Mechanical Engineering University of Tama Jagakarsa Jakarta Indonesia

ISBN: (数字)9798350367492

ISBN: (纸本)9798350367508

The widespread implementation of artificial intelligence (AI) in various industries, including healthcare, provides significant benefits but raises concerns. Notably, apprehensions about AI generating issues, experiencing malfunctions, and hindering work extend to fears of replacing medical professional positions. This research aims to quantitatively assess the impact of anxiety forms, specifically social, technical blindness and AI configuration, on job replacement anxiety among medical doctors. A pre-test approach was employed to gather data from 38 doctors in Jakarta who regularly interact with AI in their daily work. The study used PLS-SEM structural modelling with SmartPLS 3.0 as the analysis tool. Findings indicate that both social and technical blindness and AI configuration significantly influence job replacement anxiety. Additionally, the study reveals that elements within the AI configuration interact with social-technical blindness, and the AI setup effectively mitigates its impact on job replacement anxiety. These anxieties notably affect medical professionals’ fears of being replaced in their current roles. Previous research shows that anxiety about AI among healthcare personnel is persistent. However, this worry can be reduced or eliminated through continuous awareness, education, and understanding of AI’s purpose and limitations. This study aims to provide medical practitioners with a comprehensive understanding of AI constraints and the aspects requiring direct doctor involvement.

关键词： Training Industries Ethics Anxiety disorders Psychology Medical services Blindness Personnel Artificial intelligence Guidelines

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Quality Assessment Support System for Alarm Prioritization in Pharmaceutical Plant Operations 8

Quality Assessment Support System for Alarm Prioritization i...

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8th IEEE International Conference on Industrial engineering and Applications, ICIEA 2021

作者： Agapito, Arjay M. Prasetyo, Yogi Tri Persada, Satria Fadil Perwira Redi, A.A.N. School of Industrial Engineering and Service Engineering Management Mapua University Manila1002 Philippines Institut Teknologi Sepuluh November Kampus Its Sukolilo Department of Business Management Surabaya60111 Indonesia BINUS-Graduate Program-Master of Industrial Engineering Bina Nusantara University Industrial Engineering Department Jakarta11480 Indonesia

ISBN: (纸本)9781665428958

Pharmaceutical manufacturing is distinct as it has a number of quality standards being met to make sure that the products are effective and safe. Alarms help to make sure that critical parameters stay on a specific range and quality attributes are met. In this study, quality HAZOP is used for alarm prioritization that helps a simulated pharmaceutical process maintain acceptable alarm rates that will allow operators respond better on process upsets. It was seen in the simulation that a decrease in average alarm rates and peak alarm rates upon employing this method. In this way, quality HAZOP can also be used to train operators to respond quickly and better, especially on novel processes being developed. © 2021 IEEE.

关键词： Drug products plants

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Sadewa satellite remote sensing data to Manggarai 1-hour water level machine learning model 8

Sadewa satellite remote sensing data to Manggarai 1-hour wat...

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8th International Conference on Advanced Informatics: Concepts, Theory, and Application, ICAICTA 2021

作者： Valerian, Jonathan Raditya Rohmat, Faizal Kardhana, Hadi Kusuma, Muhammad Syahril Badri Yatsrib, Muhammad Institut Teknologi Bandung Master of Water Resources Management Faculty of Civil and Environmental Engineering Bandung Indonesia Institut Teknologi Bandung Water Resources Research Group Faculty of Civil and Environmental Engineering Bandung Indonesia Institut Teknologi Bandung Water Resources Engineering and Management Study Program Faculty of Civil and Environmental Engineering Bandung Indonesia

ISBN: (纸本)9781665417433

The Manggarai Water Gate is a measurement point strategically located to measure Jakarta's flooding magnitude that keeps increasing from year to year. The 2015s gate capacity improvement underscores this importance. This paper applies a machine learning model that utilizes an atmospheric approach to predict the Manggarai water level as output. In the process, optimization is done by comparing three spatial input sizes and performing a sensitivity analysis of the input variables. Using a simple recurrent sequence, the model can predict the water level with a coefficient of determination (R2) reaching 0.7 using 18-hour recurrent data. This study can be used as the basis for further development that can take satellite data lead time advantage that is crucial for the early warning system. © 2021 IEEE.

关键词： Water levels

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A Genetic Algorithm to Optimize Cargo Stability in Container Transportation 11

A Genetic Algorithm to Optimize Cargo Stability in Container...

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11th IEEE Global Conference on Consumer Electronics, GCCE 2022

作者： Hsieh, Chi-Jung Wu, Kuang-Sung Wu, Tin-Yu Tey, Fu Jie Chen, Yi-Kai Ho, Jye Yi National Ilan University Department of Computer Science and Information Engineering Ilan County Taiwan National Ilan University Master Program of E-Learning for Multimedia and Network Communications Yilan Taiwan National Pingtung University of Science and Technology Department of Management Information Systems Pingtung County Taiwan National Taiwan University of Science and Technology Department of Electrical Engineering Taipei Taiwan

ISBN: (纸本)9781665492324

In the era of the global village, frequent cross-border trade in goods has made container transportation a significant part in delivery of cargo. However, rollover accidents of container trucks often occur because of tall truck height, improper cargo stowage or crooked roads. Therefore, how to find the optimal center of gravity (CG) of the packed cargo remains an issue that the transportation industry should not neglect. To optimize cargo stability and reduce the incidence of rollovers, this paper proposes a genetic algorithm that scores the cargo stacking process to find the best CG of the cargo based on the CG of the vehicle. According to the deviation angle and the point closest to the best CG, we can Figure out the optimal cargo stacking method. © 2022 IEEE.

关键词： Genetic algorithms

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Spatiotemporal Analysis of Meteorological Drought Using Standardized Precipitation Index (SPI) in Gabiley Region, Somaliland

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Journal of Geoscience and Environment Protection 2023年第5期11卷 47-59页

作者： Abdisamad Abib Omar Jie-Lun Chiang Bashir Hassan Daud Department of Tropical Agriculture and International Cooperation National Pingtung University Science and Technology Taiwan Department of Soil and Water Conservation National Pingtung University Science and Technology Taiwan College of Engineering International Master Program on Natural Hazards Mitigation and Management National Cheng Kung University Taiwan

Drought is a common natural disaster worldwide, with varying durations, severity levels, and spatial extents. This study aimed to model the spatiotemporal variation of meteorological drought events in the Gabiley region of Somaliland. The study utilized primary data collected from the meteorological station in Gabiley and CHIRPS (Climate Hazards Group InfraRed Precipitation with Station) data to develop the standardized precipitation index (SPI) at a 3-month timescale. The results of the study revealed that the study area was characterized by drought and received inadequate precipitation, resulting in catastrophic droughts that negatively impacted the socioeconomic situation of the community. Mild-to-severe meteorological drought events occurred every two to three years, with the most severe droughts occurring in 1998, 2002, 2009, 2015, and 2017. Specifically, the year 2015 experienced the most severe meteorological drought in the region during the studied period. The predominant type of drought was a mild year in the study area. The SPI was found to potentially identify meteorological drought, making it a useful tool for policymakers as they develop drought adaptation and mitigation policies. This study provides valuable information that can benefit local authorities and policymakers in creating drought mitigation and adaptation strategies in the Gabiley region.

关键词： Meteorological Drought SPI CHRIPS Rainfall Gabiley

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Overview of Bearing Fault Diagnosis Based on Deep Learning

Overview of Bearing Fault Diagnosis Based on Deep Learning

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Electronic Communications, Internet of Things and Big Data (ICEIB), International Conference on

作者： Xue-Ling Zou Kai-Xu Han Wei Chien Xin-Yan Gan Liu-Yue Shi School of Electric and Information Engineering Beibu Gulf University Qinzhou China School of Information Management and Master’s Program Lunghwa University of Science and Technology Taoyuan City Taiwan Guangxi University of Chinese Medicine Nanning China

Deep learning has excellent learning and feature classification abilities, extracting features in massive, multi-source, and high-dimensional measurement data. It also diagnoses and generalizes models without relying on manual intervention. Thus, it is widely used in equipment fault diagnosis. We introduce the common models of deep learning: deep confidence network, convolutional neural network, and automatic encoder. Using deep learning, the fault diagnosis of rolling bearings is executed, and the result provides the basis for future development.

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Application of factor analysis method to support the users acceptance model of ERP systems implementation 4

Application of factor analysis method to support the users a...

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4th International Conference on Combinatorics, Graph Theory, and Network Topology, ICCGANT 2020

作者： Sardjono, W. Sudirwan, J. Priatna, W. Putra, G.R. Information Systems Management Department BINUS Graduate Program Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia School of Information Systems Department BINUS Undergraduate Program Bina Nusantara University Jakarta11480 Indonesia Informatics Engineering Engineering Bhayangkara University Jakarta Raya Indonesia Computer Science Study Program Faculty of Mathematics and Natural Sciences Pakuan University Bogor Indonesia

An e-Commerce company has been using an Enterprise Resource Planning (ERP) system for several years, but is still constrained in its implementation, this is reflected in the number of issue/change request tickets submitted by users who have not been able to reach ideal conditions. To overcome this problem, we need an appropriate reference model, the ERP system user acceptance model in companies. The study conducted factors that influence the level of acceptance of SAP ERP users in the XYZ group to then determine a model that is able to explain practically the level of ERP system user acceptance, which in turn can produce concrete proposals to increase ERP system user acceptance. Research is quantitative descriptive using factor analysis and regression analysis methods. The research method uses a questionnaire with a total of 107 valid respondents coming from 8 company names under the XYZ group in 6 Southeast Asian countries. The conclusion of the study is that there are 24 indicators and 4 factors that influence user acceptance of the SAP ERP system. These four factors are the low contribution of the ERP system, the quality of ERP systems and data, the development of ERP systems, and also the low quality of ERP system supporters. It is hoped that by optimizing the value of the 4 factors, the XYZ group can increase user acceptance of the SAP ERP system so that the system can provide benefits expected by the company to be competitive advantage. © 2021 Published under licence by IOP Publishing Ltd.

关键词： Factor analysis

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Influence of programming Robot Learning Mode Based on Conceptual Mapping on College Students' Computational Thinking 3

Influence of Programming Robot Learning Mode Based on Concep...

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3rd IEEE Eurasia Conference on IOT, Communication and engineering, ECICE 2021

作者： Chen, Bing-Hong Chen, Ling-Hsiu Chen, Chih-Cheng Chen, Chih-Hung Chaoyang University of Technology Department of Information Management 41349 Taiwan Control Engineering Feng Chia University Department of Automatic 40724 Taiwan National Taichung University of Education Master Program of Professional Teacher 403454 Taiwan

ISBN: (纸本)9781665445160

As the information age has progressed, computational thinking ability to solve problems has become an indispensable way of life in life. Many scholars believe that the process of solving problems will be more logical if they have computational thinking ability. At the same time, scholars believe that a good learning method improves learners' intrinsic motivation. Therefore, in this research, we try to use conceptual mapping so that students can construct knowledge when composing their own images, as the focus of this learning model and computational thinking is the thinking process and the two coincide. This research intends to introduce the traditional programming robot course into conceptual mapping and measure whether there are differences in computational thinking tendencies, problem-solving tendencies, and intrinsic motivations between students who use conceptual mapping and those who do not use it. The students in the experimental group with conceptual mapping activities developed computational thinking skills during the program robotics course. The students in the control group first watched the computational thinking explanation video to explain the computational thinking skills to the students, and then taught in the traditional programming robotics course. © 2021 IEEE.

关键词： Students

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