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9th International Conference on Cyber and IT Service Management, CITSM 2021

作者： Yulfiperius Herawan Hayadi, B. Utami, Risnita Tri Firman Zulkhasyni Pardiansyah, Dedi Universitas Prof. Dr. Hazairin SH Aquaculture Study Program Faculty of Agriculture Bengkulu Indonesia Universitas Prof. Dr. Hazairin SH Informatics Study Program Faculty of Engineering Bengkulu Indonesia

ISBN: (纸本)9781665435482

Geographical Information System is a term in the field of mapping which has a scope of how a system can unify geographic objects and their information. Freshwater fishery is the business of the majority of residents of South Bengkulu Regency covering tilapia and catfish. The solution is to create a web-based Freshwater Fish Pond GIS application using the PHP programming language. Making a database using MySQL, and for geolocation storage using Google Fusion Tables. The web that will be created will later display the GIS Web-based Freshwater Fish Pond Distribution Mapping in South Bengkulu Regency. Each pond will be accompanied by information such as the name of the owner, type of fish, type of pond, and location of the pond. It is known that the number of ponds in 4 villages in 2 districts in South Bengkulu Regency has reached 100 ponds consisting of 80 tilapia fish ponds, 20 catfish ponds. © 2021 IEEE.

关键词： Geographic information systems

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Individual Health Profiling Using Multimodal Sensors on Smart Health Care

Individual Health Profiling Using Multimodal Sensors on Smar...

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International Conference on Telecommunication Systems, Services, and Applications (TSSA)

作者： Vidya Ikawati Didin Saepudin Bambang Susanto Ahmad Munandar Hardy Purnama Nurba Ary Setijadi Prihatmanto Doctoral Program of School of Electrical and Informatics Engineering Institute of Technology Bandung Bandung Indonesia Universitas Sangga Buana Bandung Indonesia Department of Electrical Engineering Faculty of Engineering Universitas Sangga Buana Bandung Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia

Health Service, also referred to as Health Care System, plays a pivotal role in maintaining and enhancing health by preventing illnesses and injuries. In this context, electronic health records are essential for both inpatients and outpatients, serving as a crucial tool for healthcare providers and policymakers. However, the potential of these records extends beyond individual care to support broader health policy and research initiatives. Personal Smart Health Care, an individual-based digital health technology, bridges the gap between personal health management and medical records, enabling comprehensive healthcare improvements. Smart healthcare, driven by technologies like IoT, mobile applications, cloud computing, big data, 5G, artificial intelligence, and biotechnology, offers a holistic approach to healthcare, emphasizing diagnosis, treatment, disease prevention, risk monitoring, and virtual assistance. An intelligent framework for smart healthcare includes four layers: the instrumentation layer, information system layer, business intelligence layer, and gamification layer, each contributing to enhanced patient outcomes, streamlined processes, and improved patient care. The gamification layer incentivizes healthy behaviors and fosters patient engagement, especially in healthcare scenarios. This comprehensive framework underscores the transformative potential of smart healthcare, where technology-driven solutions can revolutionize the healthcare landscape, improving patient care, health management, and the overall well-being of individuals and populations.

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Zero Sequence Current Detection Method of High Impedance Faults Using Distortion Waveform in Distribution Networks

Zero Sequence Current Detection Method of High Impedance Fau...

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IEEE PES Asia-Pacific Power and Energy engineering Conference (APPEEC)

作者： Jiraphat Manmoh Watcharin Srirattanawichaikul Department of Electrical Engineering Faculty of Engineering Chiang Mai University Chiang Mai Thailand Graduate Program in Electrical Engineering Graduate School Chiang Mai University Chiang Mai Thailand Provincial Electricity Authority Bangkok Thailand

ISBN: (数字)9798350318098

ISBN: (纸本)9798350318104

This paper presents high-impedance faults (HIF) detected in distribution networks with distortion zero sequence current detection methods. The simulation model in this paper is performed on a single branch distribution network with a voltage rating of 22kV, and the simulation is divided into two parts. The first part is the creation of HIF in the system by adjusting the distortion of the HIF current according to the principle of the heat-balanced equation of the material. The second part takes the resulting HIF model, which feeds into the established distribution network and detects distortion zero sequence currents occurring. The simulation results clearly depict the current waveform distortion caused by HIF, which can be adjusted. The presence of zero sequence current can indicate the occurrence of HIF in the distribution network.

关键词： Heating systems Surface impedance Surface waves Simulation Distribution networks Voltage Distortion

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Improved Metaheuristics with Machine Learning Enabled Medical Decision Support System

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Computers, Materials & Continua 2022年第11期73卷 2423-2439页

作者： Sara A.Althubiti JoséEscorcia-Gutierrez Margarita Gamarra Roosvel Soto-Diaz Romany F.Mansour Fayadh Alenezi Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Research Center-CIENS Escuela Naval de Suboficiales A.R.C.“Barranquilla”BarranquillaColombia Electronics and Telecommunications Engineering Program Universidad Autónoma del CaribeBarranquilla080001Colombia Departament of Computational Science and Electronic Universidad de la CostaCUCBarranquilla080001Colombia Biomedical Engineering Program Universidad Simón BolívarBarranquilla080001Colombia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga 72511Egypt Department of Electrical Engineering College of EngineeringJouf UniversitySaudi Arabia

Smart healthcare has become a hot research topic due to the contemporary developments of Internet of Things(IoT),sensor technologies,cloud computing,and ***,the latest advances of Artificial Intelligence(AI)tools find helpful for decision-making in innovative healthcare to diagnose several *** Cancer(OC)is a kind of cancer that affects women’s ovaries,and it is tedious to identify OC at the primary stages with a high mortality *** OC data produced by the Internet of Medical Things(IoMT)devices can be utilized to differentiate *** this aspect,this paper introduces a new quantum black widow optimization with a machine learningenabled decision support system(QBWO-MLDSS)for smart *** primary intention of the QBWO-MLDSS technique is to detect and categorize the OC rapidly and ***,the QBWO-MLDSS model involves a Z-score normalization approach to pre-process the *** addition,the QBWO-MLDSS technique derives a QBWO algorithm as a feature selection to derive optimum feature ***,symbiotic organisms search(SOS)with extreme learning machine(ELM)model is applied as a classifier for the detection and classification of ELM model,thereby improving the overall classification *** design of QBWO and SOS for OC detection and classification in the smart healthcare environment shows the study’s *** experimental result analysis of the QBWO-MLDSS model is conducted using a benchmark dataset,and the comparative results reported the enhanced outcomes of the QBWO-MLDSS model over the recent approaches.

关键词： Ovarian cancer decision support system smart healthcare IoMT deep learning feature selection

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Internet of Medical Things: A Bibliometric Analysis of Research Publications from 2018–2022 4th

Internet of Medical Things: A Bibliometric Analysis of Resea...

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4th International Conference on Electronics, Biomedical engineering, and Health Informatics, ICEBEHI 2023

作者： Maulana, Fairuz Iqbal Lestari, Dian Adi, Puput Dani Prasetyo Arifin, Mohammad Nazir Purnomo, Agung Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Faculty of Medicine Universitas Airlangga Surabaya60132 Indonesia Telecommunication Research Center National Research and Innovation Agency Jakarta11480 Indonesia Informatics Engineering Study Program University of Madura Pamekasan Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9789819714629

The field of the Internet of Medical Things (IoMT) is experiencing significant growth as it involves the integration of medical devices and systems with the internet and various digital technologies. This study provides a bibliometric analysis of scholarly articles pertaining to the Internet of Medical Things (IoMT) during the time frame of 2018 to 2022. The analysis is conducted using data sourced from the Scopus database. A total of 1165 documents were identified and analyzed to gain insights into the current state of research in this field. The analysis includes trends in publication output, top authors and institutions, and key research topics. The results of the analysis indicate a steady increase in publication output on IoMT over the past five years, with the highest number of publications in 2022. The top authors in this field were Mohanty, S.P., Kougianos, E., and Pirbhulal, S., while the top institutions were King Saud University, Chinese Academy of Sciences, and University of North Texas. Co-citation analysis revealed that wearable devices, telemedicine, and data analytics were among the key research topics in IoMT. This bibliometric analysis offers useful insights into the present research landscape of the Internet of Medical Things (IoMT) spanning the years 2018 to 2022. The findings can be beneficial for researchers, practitioners, policymakers, and funding agencies in understanding the trends and priorities in this field. The top authors and institutions identified in this analysis can serve as valuable resources for collaboration and staying updated on the latest developments in IoMT. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Digital devices

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Electrochemical Performance of a Water-Based LiFePO4 Cathode for Li-Ion Batteries

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Defect and Diffusion Forum 2022年 417卷 163-168页

作者： Chanhaew, Araya Aranmala, Komsak Darmawan, Luthfi Mursid Nisa, Shofirul Sholikhatun Nurohmah, Anisa Raditya Meethong, Nonglak Materials Science and Nanotechnology Program Department of Physics Faculty of Science Khon Kaen University Muang District Khon Kaen40002 Thailand Department of Chemical Engineering Faculty of Engineering Universitas Sebelas Maret Central Java Surakarta57126 Indonesia Centre of Excellence for Electrical Energy Storage Technology Universitas Sebelas Maret Central Java Surakarta57146 Indonesia Khon Kaen University Muang District Khon Kaen40002 Thailand

Lithium iron phosphate (LiFePO4) has received much attention because it can provide high power density, abundant raw materials, safety, low toxicity, and high thermal stability. In general, the production of LiFePO4 cathode uses Polyvinylidene fluoride (PVDF) as a binder and N-Methyl-2-Pyrrolidone (NMP) as a solvent. These components are expensive, toxic, and can affect the environment. Therefore, to cover this shortcoming, the solvent and binder were replaced in this study. The solvent is replaced with water, which is more environmentally friendly and abundant, while the binder is replaced with water soluble binders. Suitable electrode formulations were investigated to obtain high performance cylindrical typed Li-ion batteries. As a result, Formula B (ratio of LiFePO4: AB: KS6: SBR: CMC = 90: 3: 3: 2.677: 1.333) has the highest specific discharge capacity of 120 mAh/g. The NMP-based cathode can give about 145 mAh/g. Therefore, the water-based cathode LiFePO4 gives a value that is slightly lower the NMP-based formular. © 2022 Trans Tech Publications Ltd, Switzerland.

关键词： Lithium compounds

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Design of big data technology prototype for classification of village status based on village development index involves k-means algorithm to support village ministry Pdtt work programs 2

Design of big data technology prototype for classification o...

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2nd International Conference on Sciences and Technology Applications, ICOSTA 2020

作者： Hasugian, Paska Marto Hutahaean, Harvei Desmon Sinaga, Bosker Sriadhi Silaban, Saronom Informatics Engineering Study Program STMIK Pelita Nusantara Medan Indonesia Computer Science and Informatics Education Study Program Faculty of Engineering Universitas Negeri Medan Medan20221 Indonesia Departement of Chemistry Universitas Negeri Medan Medan20221 Indonesia

Big data technology is the overall technology that can handle the processing associated with analyzing the data to explore the potential that is in it. Some of the uses of big data are based on the biggest data traffic sources, such as social media, financial transactions, public data, censorship data, and company data. The problem found in the accumulation of village status data that has not been utilized in the decision-making process to determine the status of the next village and the absence of an application to process the data stored in the data database so that a tool is developed to analyze the buildup. The results of this study are to produce a prototype design that is Unified Modeling Language (UML) design, Form Design, and Database Design that will be used to develop Big Data Technology in determining the classification of village status based on the Village Build index. © Published under licence by IOP Publishing Ltd.

关键词： Decision making

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Classification Methods for Recognition of Power Quality Disturbances in Distribution Networks Using Artificial Neural Network

Classification Methods for Recognition of Power Quality Dist...

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IEEE PES Asia-Pacific Power and Energy engineering Conference (APPEEC)

作者： Wassanan Buasi Watcharin Srirattanawichaikul Department of Electrical Engineering Faculty of Engineering Chiang Mai University Chiang Mai Thailand Graduate Program in Electrical Engineering Graduate School Chiang Mai University Chiang Mai Thailand Provincial Electricity Authority Bangkok Thailand

ISBN: (数字)9798350318098

ISBN: (纸本)9798350318104

This paper provides the power quality disturbances (PQDs) classification in distribution networks using an artificial neural network (ANN). Various forms of PQDs are considered, including sag, swell, harmonics, flickers, transients, sag with harmonics, and swell with harmonics. The simulation is divided into two parts. The first part is PQDs signals creation and feature extraction using discrete wavelet transform (DWT) and classification by using the dataset from the feature extraction step to be the input of artificial neural network (ANN). The second part is the model testing with the IEEE 9 bus test system with 5 PQDs, which is the most misclassified. The results of the proposed method will be demonstrated using simulation results in MATLAB/Simulink. The results show that the model can classify PQD signals into ten classes. The accuracy of the model is at 99.4%. After testing with the IEEE 9 bus test system, the total accuracy is at 95.6%.

关键词： Accuracy Power quality Artificial neural networks Distribution networks Feature extraction Harmonic analysis Mathematical models

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Review the Utilization of Big Data and K-Means Algorithm in Supporting the Determination of Village Status As Support to the Ministry of Village PDTT 2

Review the Utilization of Big Data and K-Means Algorithm in ...

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2nd International Conference on Sciences and Technology Applications, ICOSTA 2020

Big data refers to big data, fast data processing, diversity of data structures, and data values so that it is not possible to be processed with outdated methods. Big data technology is used in various industrial sectors. Big data technology is the whole technology that can handle Big Data. Some of the uses of big data are based on the largest significant data traffic sources such as social media, financial transactions, public data, sensor data, and corporate data. The same is the case with the status of so many villages in Indonesia, so it is better to use big data for the classification of village status based on the village index build by involving an algorithm process. This research aims to produce a description of the role of big data in supporting activities in a grouping. The method used is a qualitative approach related to data collection based on scientific work with the source of data information needed to study literature techniques from various studies that have been published in national and international journals. A decision is made that big data has been widely used in different circles to facilitate performance and speed up the decision-making process. © Published under licence by IOP Publishing Ltd.

关键词： Data mining

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The Effect of Vehicles Speed on the Performance of VANET Protocol

The Effect of Vehicles Speed on the Performance of VANET Pro...

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Advanced engineering and Technologies (ICONNIC), International Conference on

作者： Osama A. Qasim Dania Mohammed Mahdi Mohammed S. Noori Rabei Raad Ali Christy Atika Sari Eko Hari Rachmawanto Department of Computer Engineering Technology Northern Technical University Mosul Iraq Department of Electrical and Electronics Engineering Uniersiti Tenaga Nasional Selangor Malaysaia Study Program in Informatics Engineering University of Dian Nuswantoro Semarang Indonesia

At present, ad hoc networks are getting a lot of attention, because they have many features that differ from the rest of the networks and because they are technically advanced. In routing protocols, the Vehicular Ad-hoc network (VANET) differ in performance because each protocol has different variables, such as variable density, speed, and traffic scenarios. In this work, we proposed topology-based routing namely Ad hoc On Demand Distance Vector (AODV) protocol. The AODV protocol has been simulated in case of the movement of vehicles at a fixed velocity at 60km/h, and in case of randomly changing the vehicle's locations in the network. There are three parameters used to investigate the performance of the proposed AODV protocol which are packet delivery ratio, and overheads. The Simulation results show a significant decrease from 0.55 to 0.82 in the packet delivery ratio. On the other hand, the performance of the AODV protocol demonstrates effective communication for the VANETs.

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