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Indonesia Malaysia Research Consortium Seminar 2018, IMRCS 2018

作者： Muqtadiroh, Feby Artwodini Herdiyanti, Anisah Wicaksono, Indra Usagawa, Tsuyoshi Department of Information Systems - ITS Indonesia Graduate School of Science and Technology Faculty of Engineering Faculty of Advanced Science and Technologoy Kumamoto University Japan

E-learning is an internet-based learning program. It has been adopted in Institut Teknologi Sepuluh Nopember (ITS) since 2006, and called SAHRE-ITS. It is managed by Directorate of Academic Affairs in ITS. Despite quite long adoption in ITS, there are still a number of problems to confront. One of them is lack of intent of the lecturers as the main and vital users to adopt e-learning continuously. The research was to identify factors affecting the continuance intention of lecturers to adopt SHARE-ITS using some model: expectation - confirmation model (ECM), technology acceptance model (TAM), theory of planned behaviour (TPB), and FLOW theory. The variables used comprised 10 variables, i.e.: perceived usefulness, perceived ease of use, attitude, perceived enjoyment, concentration, subjective norm, perceived behavioural control, confirmation, satisfaction, and continuance intention. The results of the research indicate some factors affecting the continuance intention of the lecturers to use SHARE-ITS and suggest some recommendations for strengthening those factors. This research showed the factors of lecture's satisfaction and perceived usefulness to SHAREITS positively and significantly affected the continuance intention to use SHARE-ITS. The factor of perceived ease of use among the lecturers positively and significantly affected the perceived usefulness among the lecturer towards SHARE-ITS. Those three factors were essential to consider as they affected the continued intention the lecturers to use SHARE-ITS. In addition, it is identified that the factor of perceived enjoyment in using SHARE-ITS by the lecturers positively and significantly affected their attitude in using SHARE-ITS. Accordingly, the researchers addressed recommendation within the contexts of service rendered by the administrator of SHARE-ITS, data integration, SHARE-ITS menu and navigation designs. © 2019 IOP Publishing Ltd. All rights reserved.

关键词： E-learning

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A Framework for Skin Cancer Prediction Using CNN Ensembles 2

A Framework for Skin Cancer Prediction Using CNN Ensembles

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2nd International Conference on Advancements in Smart, Secure and Intelligent Computing, ASSIC 2024

作者： Samushonga, Wieslaw Kumar, Rakesh Gupta, Meenu Obaid, Ahmed J. Chandigarh University Department of Computer Science and Engineering Punjab Gharuan India University of Kufa Faculty of Computer Science and Mathematics Najaf Iraq Technical Engineering College Al-Ayen University Department of Computer Technical Engineering Thi-Qar Iraq

ISBN: (纸本)9798350370188

Skin cancer is among the deadliest diseases engulfing the world. The early detection of this disease may provide a great relief to the patients and healthcare systems worldwide. Recently, Machine Learning (ML)-based detection techniques have become popular in early skin cancer prediction. This paper comprehensively presents an overview of the latest research in the field of skin cancer prediction using ML techniques, especially the use of Convolutional Neural Networks (CNN) for the said purpose. Various methodologies employed in the past have been discussed along with the outcomes achieved, limitations, and advantages of these predictive models. A detailed review of the latest key references in the area is also discussed. At the end, a way of achieving ensemble using CNN methods for skin care has also been discussed, which we will implement in the next phase of our research. © 2024 IEEE.

关键词： Diseases

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1983 Design of Angle-controlled Current Source Inverter-Fed Induction Motor Drive

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IEEE Transactions on Industry Applications 1984年第4期IA-20卷 1104-1105页

作者： Krishnan, R. Lindsay, James F. Stefanovic, Victor R. Gould Research Center Rolling Meadows Faculty of Engineering and Computer Science Concordia University Industrial Power Conversion Systems Department Industry Applications Society

The current source inverter-fed induction motor drive (hereafter referred to as CSIM drive) is one of the widely used drives in the industry. Of the many strategies employed for the control of CSIM drive, angle control is the simplest scheme to incorporate the aspect of “frequency compensation,” thus paving the way for a fast response CSIM drive. A step-by-step design of the angle-controlled CSIM drive is described. A systematic design of inner current loop, slip speed loop, outer speed loop, and frequency compensation loop is given. The design incorporates a linear relationship between the reference input and output of electromagnetic torque and a strategy to obtain maximum torque per ampere. The commutation delay in the current source inverter is taken care of in the design of the frequency compensator. Experimental results are given in support of the design procedure. Copyright © 1984 by The Institute of Electrical and Electronics Engineers, Inc.

关键词： Induction motor drives Educational institutions Electrical equipment industry Electrical engineering Power electronics Frequency Torque Electronics industry Motor drives Education

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Crack identification using extended IsoGeometric analysis and particle swarm optimization 7th

Crack identification using extended IsoGeometric analysis an...

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7th International Conference on Fracture Fatigue and Wear, FFW 2018

作者： Khatir, Samir Wahab, Magd Abdel Benaissa, Brahim Köppen, Mario Department of Electrical Energy Metals Mechanical Constructions and Systems Faculty of Engineering and Architecture Ghent University Ghent Belgium Graduate School of Life Science and Systems Engineering Kyushu Institute of Technology Kitakyushu Japan Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Kitakyushu Japan

ISBN: (纸本)9789811304101

The eXtended isogeometric analysis (X-IGA) combined with Particle swarm optimization (PSO) is used for crack identification in twodimensional linear elastic problems based on inverse problem. The application of fracture mechanics test under mode II loading is performed. The X-IGA possesses the advantages of the combination between eXtended Finite Element Method (X-FEM) and the Isogeometric Analysis (IGA). The objective function minimizes the gap between the calculated and measured displacements. Convergence studies at various positions of crack on the plate are calculated and the results shows that the proposed technique can detect damage with minimum accuracy 95% for the position and maximum accuracy 98%. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Inverse problem PSO and crack identification and plate 2D XIGA

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Bayesian networks application for representation and structure learning of gene regulatory networks

Bayesian networks application for representation and structu...

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2009 12th International Conference on computer and Information Technology, ICCIT 2009

作者： Ristevski, Blagoj Loskovska, Suzana Department of Information Systems Management Faculty of Administration and Information Systems Management St. Kliment Ohridski University Bitola Macedonia Department of Computer Science and Computer Engineering Faculty of Electrical Engineering and Information Technologies Ss. Cyril and Methodius University Skopje Macedonia

ISBN: (纸本)9781424462841

The cell functions and development are regulated by complex networks of genes, proteins and other components by means of their mutual interactions. These networks are called gene regulatory networks (GRNs). GRNs are used to reveal the fundamental gene regulatory mechanisms, to determine the reasons for many diseases and interactions between drugs and their targets. The introduction of experimental technologies such as microarrays, ChIP-chip which combines chromatin immunoprecipitation (ChIP) with microarrays and ChIP-Seq which combines ChIP with DNA sequencing, has provided a large number of available datasets related to gene expression and transcription factors (TFs) and their interactions. These datasets are basis for further analysis to reveal the gene regulation mechanisms. Many models have been applied to represent gene regulatory networks. We have used the dynamic Bayesian network model which is able to cope with missing data and can include a prior knowledge about transcription factors and their activation/inhibition of corresponding genes. We describe the obtained results and survey the common structure learning algorithms for learning of GRN's structure. We tested the obtained GRN for test datasets with different sizes and in the paper describe obtained dependencies between the ratio of Bayesian score and BIC and dataset size. ©2009 IEEE.

关键词： Bayesian networks

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Enhancing the Heart Disease Classification Using Multi-level Perceptron and Principal Component Analysis 1

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International Conference on Advanced engineering, Technology and Applications, ICAETA 2024

作者： Jaiswal, Vanshika Gupta, Sanyam Gupta, Shilpa Kumar, Deepika Hameed, Alaa Ali Department of Computer Science and Engineering JIMS Engineering Management Technical Campus U.P. Greater Noida India Department of Computer Science and Engineering Bharati Vidyapeeth’s College of Engineering New Delhi India Department of Computer Engineering Faculty of Engineering and Natural Sciences Istinye University Istanbul34396 Turkey

ISBN: (数字)9783031709241

ISBN: (纸本)9783031709234

The ability to detect cardiac disease early is vital to saving lives. Heart attacks are one of the leading reasons for high death rates worldwide due to the high cost of identifying cardiac disorders, which is crucial to the healthcare industry, as well as the shortage of human and logistical resources. In order to find the best machine learning algorithm for early-stage heart disease prediction, a model is presented in this study. In order to train and evaluate the model based on the data for efficient decision-making, machine learning techniques are utilized. The goal of this research is to combine Principal Component Analysis and Multilevel Perceptron model to propose an updated diagnosis and classification model based on machine learning (ML) for predicting heart failure and heart disease detection. Using cutting-edge techniques and foundational classifiers like Support Vector machines, Random forests, and K-Nearest Neighbors, an empirical evaluation of the suggested methodology was carried out with accuracy, precision, recall, and F1-score serving as the evaluation criteria. The proposed method has shown the maximum accuracy of 95.1%. This innovative approach not only streamlines the diagnostic process but also offers personalized medical assistance, facilitating early detection and intervention in heart disease, thereby optimizing healthcare delivery and improving patient outcomes. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Support vector machines

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Reducing the search space in ontology alignment using clustering techniques and topic identification 2015

Reducing the search space in ontology alignment using cluste...

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8th International Conference on Knowledge Capture, K-CAP 2015

作者： Chiatti, Agnese Dragisic, Zlatan Cerquitelli, Tania Lambrix, Patrick Department of Control and Computer Engineering Politecnico di Torino Italy Computer Science Swedish E-Science Research Center Linköping University Sweden

ISBN: (纸本)9781450338493

One of the current challenges in ontology alignment is scal- ability and one technique to deal with this issue is to reduce the search space for the generation of mapping suggestions. In this paper we develop a method to prune that search space by using clustering techniques and topic identification. Fur- ther, we provide experiments showing that we are able to generate partitions that allow for high quality alignments with a highly reduced effort for computation and validation of mapping suggestions for the parts of the ontologies in the partition. Other techniques will still be needed for finding mappings that are not in the partition. © 2015 ACM.

关键词： Mapping

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Battery Monitoring System on IoT-Based Smart Micro Grid 4

Battery Monitoring System on IoT-Based Smart Micro Grid

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4th International Conference on Electronic and Electrical engineering and Intelligent System, ICE3IS 2024

作者： Iksan, Nur Widodo, Djoko Adi Djuniadi, Djuniadi Putri, Riana Defi Mahadji Suryanto, Agus Udayanti, Erika Devi Universitas Negeri Semarang Faculty of Engineering Department of Electrical Engineering Indonesia Universitas Dian Nuswantoro Faculty of Computer Science Department of Information System Indonesia

ISBN: (纸本)9798350378368

The use of batteries as an energy storage medium has a very important role in the installation of renewable energy power plants, such as photovoltaics to overcome intermittency in photovoltaics and to maintain stable power quality. In this study, the installation of solar plants that was used as the research object was a smart micro grid that integrates photovoltaic electrical energy sources with the Utility electricity network for residential scale. The battery monitoring system is used to manage the performance of existing batteries on the electricity grid through analysis of the battery's electrical values such as current, voltage, power and energy, so that it can function optimally in storing electrical energy and supplying electricity to users. Internet of things (IoT) technology is used to provide easy transfer of data obtained through the process of data acquisition to data visualization provided to be accessed by users in real time. This research aims to develop an IoT-based battery monitoring system. The development carried out focuses on the data acquisition process, the data transfer process using IoT technology, the process of analyzing and visualizing data on the IoT cloud and remote access to users. © 2024 IEEE.

关键词： Battery IoT Monitoring Smart Micro Grid

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A hybrid PSO_Fuzzy_PID controller for gas turbine speed control

International Journal of Control and Automation

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International Journal of control and Automation 2013年第1期6卷 13-24页

作者： Mansourabad, Azadeh Mansouri Beheshti, Mohammad Taghi Hamidi Simab, Mohsen Department of Technical and Engineering International Campus-Kish Island Tehran University Kish Iran Faculty of Electrical and Computer Engineering Tarbiat Modares University Tehran Iran Department of Electrical Engineering Science and Research Branch Islamic Azad University Fars Iran

In this paper, a hybrid PSO_Fuzzy_PID controller is designed for speed control of a gas turbine. The aim of the controller is to maintain the turbine speed and the exhaust temperaturein a desired interval during startup and operating condition. Here, different parts of the fuzzy controller such as fuzzification, rule base, inference engine, defuzzification, and particle swarm optimization (PSO) algorithm are presented. computer simulations of the controller andgas turbine based on Matlab / simulink simulation platform are performed to investigate the effectiveness of the proposed algorithm. The performance of the proposed algorithm is evaluated during startup and operating condition of the gas turbine. Simulation results well show that the response of the PSO_Fuzzy_PID controller is effectively improved compared with other controllers. The characteristics of the step response such as rise time, settling time and overshootare considerably decreased, and the value of the steady state error is minimized.

关键词： Fuzzy control

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Implementation of GPSR protocol with various mobility models in VANET Scenario 1

Implementation of GPSR protocol with various mobility models...

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1st International Conference on Mechatronics and Artificial Intelligence, ICMAI 2021

作者： Raheja, K. Mahajan, M. Goel, A. Department of Computer Science and Engineering SGT University Gurugram India Faculty of Engineering and Technology SGT University Gurugram India School of Computing Science and Engineering Galgotias University India

In Vehicular Ad hoc Networks (VANET), topology varies very frequently because vehicles move in high speed. VANET is deployed on road. In GPSR Protocol, as the data packets are forwarded depending upon on the beacon information sent by neighboring nodes, which contain the location of neighbors. Hence nodes move in mobile nature as they change their positions. Mobile pattern of node is reflected by Mobility Models, as they characterize the movement of users who are mobile on the road, with respect to their direction, velocity and location over a period of time. Mobility models are practiced in implementation of protocols and the pattern by which the mobility models reflect real world practices of vehicles on the roads. Using simple pattern randomly, graph constrained mobility models are common practices while doing research. These models donot describe mobility of vehicles in realistic manner. For instance while accelerating and decelerating in the presence of nearby vehicles, these situations greatly affect the Network performance. Selecting the mobility model which is realistic one is the main focus of this paper. To address the challenges such as high mobility of vehicle nodes on the road and random topology, VANET needs a suitable mobility model to obtain improved Packet Delivery Ratio, Throughput, End to End Delay etc. This paper first implements the GPSR Protocol and then GPSR is analyzed by applying different mobility models such as Random Way Point, Gauss Markov, Manhattan Grid, Reference Point Group and Random direction. Results are analyzed by taking the following parameters: Routing overhead, Throughput, PDR and End to End Delivery. The implementation is carried out using NS - 2.35 and Bonmotion is used to create mobility models. © Published under licence by IOP Publishing Ltd.

关键词： Vehicular ad hoc networks

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