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Performance analysis of heterogeneous database management system (DBMS) synchronization using message digest 5

AIP Conference Proceedings 2020年第1期2291卷

作者： Ayu Helinda Zuhar Musliyana Desita Ria Yusian TB Mahendar Dwipayana Julinawati Suanda Atikah Nor Johari 1Department of Engineering Informatics Faculty of Computer Science Ubudiyah Indonesia University Acheh Indonesia 2Department of Information System Faculty of Computer Science Ubudiyah Indonesia University Acheh Indonesia 3Center of Excellence Geopolymer & Green technology (CEGeoGTech) Universiti Malaysia Perlis Perlis Malaysia

Currently, the Database Management system (DBMS) keeps growing and is available on various platforms. The use of various types of DBMS in a system can cause problems with limitations in the synchronization process because each DBMS only provides synchronization methods for similar DMBS. Previous research has examined heterogeneous database synchronization algorithms on mobile devices using the Message Digest 5 (MD5) method. The process of synchronization with this method is done by comparing the hash values of each record data in the source table with the data hash values in the destination table. If a different hash value is obtained, the synchronization process is based on the type of transaction that has been determined. Based on the principle of work, this algorithm requires a long synchronization time for large-scale databases because it has to check the hash values of each data record. This study examined the performance analysis of the DBMS synchronization method using MD5. The testing was performed by observing the parameters of execution time of synchronization ptocess for the MySQL DBMS and PostgreSQL types. The results showed that the execution time of the MD5 synchronization process was proportional to the number of data records that need to be synchronized. This is because the hashing process that must be done on every data record and synchronization mechanism requires all data to be sent to check and compare the hash values of each data record in the destination synchronization database even though the data has not changed.

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Implementation of Data Mining to Classify the Consumer's Complaints of Electricity Usage Based on Consumer's Locations Using Clustering Method 1

Implementation of Data Mining to Classify the Consumer's Com...

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1st Workshop on Environmental science, Society, and Technology, WESTECH 2018

作者： Pardede, A.M.H. Sembiring, Yusdiana Br Iskandar, Akbar Pitasari, Dyah Retno Sriadhi, S. Rianita, Dian Arifin, Muhammad Ririhena, Mersy Yoslin Siregar, Nurintan Asyiah Supriyono Sari, Ayu Esteka Tondo, Simson Zarlis, Muhammad Winarno, Edy Tulus STMIK Kaputama Sumatera Utara Binjai Indonesia Department of Informatics STMIK AKBA Makassar Indonesia Department of Law Universitas Halmahera Tobelo Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Department of Public Administrations Universitas Lancang Kuning Indonesia Department of Information System Faculty of Engineering Universitas Muria Kudus Indonesia Department of Accounting Universitas Halmahera Indonesia Department of Management STIE Labuhanbatu Sumatera Utara Indonesia Department of Information System Universitas Muria Kudus Kudus Indonesia Department of Management STIE Sakti Alam Kerinci Jambi Indonesia Department of Public Administration Universitas Halmahera Tobelo Indonesia Department of Computer Science Universitas Sumatera Utara Medan Indonesia Faculty of Information Technology Universitas Stikubank Semarang Indonesia Department of Mathematics Universitas Sumatera Utara Medan Indonesia

Data collected by PLN staff on customer's complaints in the usage of electricity are very huge and accumulate. Previously, there was no information about these kinds of complaints in all sub-districts included inside the company, PT. PLN Binjai. On the other hand, each year company experienced problems to classify all complaints in order to obtain customers with information to later be used as a basis for making policy/decision. Data mining used clustering method and K-Means algorithm to classify the data so that important information is obtained from customer's complaints on the electricity usage, using variable: types of complaints, power using by consumer and consumer's region. Data was analyzed using Matlab to produce cluster centers and obtained a relationship between variables obtained with groups with high number of complaints. Results revealed that from 500 customers who have complained, cluster 1 had 218 complaints namely NT Fuse Putus with power used was 1300 watt and was located in Binjai. © Published under licence by IOP Publishing Ltd.

关键词： Data mining

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Analysis of possibilities of alleviating repercussions caused by large disturbances in the power system

Analysis of possibilities of alleviating repercussions cause...

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Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion, MEDPOWER 2018

作者： Noskov, Robert Petrovic, Ivica Glavaš, Hrvoje Šljivac, Damir Baric, Tomislav Croatian Transmission System Operator Ltd. Vukovarska cesta 217 Osijek31000 Croatia Faculty of Electrical Engineering Computer Science and Information Technology Osijek Ulica Kneza Trpimira 2b Osijek31000 Croatia

ISBN: (纸本)9781839531330

Various EU regulations have established rules for accessing the electricity exchange grid in order to ensure proper functioning of the electricity market while maintaining a proper level of system security. system security depends on the technical capabilities of its components to withstand disturbances and to help prevent serious interruptions or to re-establish system operation after a breakdown occurs. This paper generally gives a theoretical and practical overview of measures for the automatized protection against voltage disruption and reduction of the active or reactive load of lines or transformers in the subsystem PrP Osijek. In addition to automatic protection, measures of excluding certain elements of the grid will be shown, as well as functions for blocking/activating the regulation of grid elements in order to reduce active and reactive loads of lines or transformers. The analysis gives the effect of some measurements on a real transmission grid model. The model had to be adjusted with the grid state and load requirements that anticipated various unfavourable scenarios, which could cause the power system to break down. © 2018 Institution of engineering and Technology. All rights reserved.

关键词： Electric power transmission networks

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Development of a Hand-Up Request Motion Model Based on Analysis of Hand-Up Motion Between Humans

Development of a Hand-Up Request Motion Model Based on Analy...

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IEEE International Conference on Robotic Computing (IRC)

作者： Shunsuke Ota Toshiyuki Yasuda Mitsuru Jindai Yoshihiro Sejima Graduate School of Science and Engineering University of Toyama Toyama Japan Faculty of Computer Science and System Engineering Okayama Prefectural University Okayama Japan

Robots are expected to work in fields involving direct interaction with human. However, in order to work in these fields, the robot has to be accepted favorably by humans. Therefore, these robots need to start communication smoothly. In the previous research, hand-up response motion of robot has been discussed. The effectiveness of this model was demonstrated by experiments using a hand-up robot system that employed the developed model. On the other hand, robots should also be able to generate active hand-up motion in order to promote its embodied interaction with humans. However, request side of hand-up greeting interaction of robot has not been discussed. Therefore, in this paper, a hand-up request motion model was proposed for generation of hand-up greeting with voice greeting with human. Initially, hand-up greeting between mutual human is measured and analyzed. Based on the motion characteristics obtained from the analysis result, a hand-up request motion model in which a robot requests hand-up greeting with voice greeting from human is proposed. The effectiveness of the developed request motion model is demonstrated through sensory evaluation experiments.

关键词： Robot sensing systems Mathematical model Robot kinematics Elbow Motion measurement Analytical models

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Learning a no-reference quality assessment model of enhanced images with big data

arXiv

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arXiv 2019年

作者： Gu, Ke Tao, Dacheng Qiao, Junfei Lin, Weisi Beijing Key Laboratory of Computational Intelligence and Intelligent System BJUT Faculty of Information Technology Beijing University of Technology Beijing100124 China School of Information Technologies Faculty of Engineering and Information Technologies University of Sydney J12/318 Cleveland St DarlingtonNSW2008 Australia School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore

In this paper we investigate into the problem of image quality assessment (IQA) and enhancement via machine learning. This issue has long attracted a wide range of attention in computational intelligence and image processing communities, since, for many practical applications, e.g. object detection and recognition, raw images are usually needed to be appropriately enhanced to raise the visual quality (e.g. visibility and contrast). In fact, proper enhancement can noticeably improve the quality of input images, even better than originally captured images which are generally thought to be of the best quality. In this work, we present two most important contributions. The first contribution is to develop a new no-reference (NR) IQA model. Given an image, our quality measure first extracts 17 features through analysis of contrast, sharpness, brightness and more, and then yields a measre of visual quality using a regression module, which is learned with big-data training samples that are much bigger than the size of relevant image datasets. Results of experiments on nine datasets validate the superiority and efficiency of our blind metric compared with typical state-of-theart full-, reduced- and no-reference IQA methods. The second contribution is that a robust image enhancement framework is established based on quality optimization. For an input image, by the guidance of the proposed NR-IQA measure, we conduct histogram modification to successively rectify image brightness and contrast to a proper level. Thorough tests demonstrate that our framework can well enhance natural images, low-contrast images, low-light images and dehazed images. The source code will be released at https://***/site/guke198701/publications. Copyright © 2019, The Authors. All rights reserved.

关键词： Image enhancement

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Preface

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CEUR Workshop Proceedings 2021年 2899卷

作者： Kovalev, Igor Semenkin, Eugene Gulyaev, Yuri Barakaev, Nusratilla Shaidurov, Vladimir Škraba, Andrej Tsarev, Roman Legalov, Alexander Saramud, Mikhail Grosspietsch, Karl-Erwin Stupina, Alena Department of Computer Science Siberian Federal University Krasnoyarsk Russia Department of system analysis and operations research of Reshetnev University Krasnoyarsk Russia International and Russian Union of Scientific and Engineering Associations Moscow Russia Rector of Bukhara Engineering Technological Institute Bukhara Uzbekistan Institute of Computational Modeling SB RAS Krasnoyarsk Russia University of Maribor UM Faculty of Organizational Sciences - Cybernetics and Decision Support Systems Laboratory Slovenia Department of Informatics Siberian Federal University Krasnoyarsk Russia Faculty of Computer Science School of Software Engineering HSE University Moscow Russia Department of Informatics Siberian Federal University Krasnoyarsk Russia European Organization for Information and Microelectronics Germany The Siberian Federal University Krasnoyarsk Russia

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OpenKBP-Opt: An international and reproducible evaluation of 76 knowledge-based planning pipelines

arXiv

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arXiv 2022年

作者： Babier, Aaron Mahmood, Rafid Zhang, Binghao Alves, Victor G.L. Barragán-Montero, Ana Maria Beaudry, Joel Cardenas, Carlos E. Chang, Yankui Chen, Zijie Chun, Jaehee Diaz, Kelly Eraso, Harold David Faustmann, Erik Gaj, Sibaji Gay, Skylar Gronberg, Mary Guo, Bingqi He, Junjun Heilemann, Gerd Hira, Sanchit Huang, Yuliang Ji, Fuxin Jiang, Dashan Giraldo, Jean Carlo Jimenez Lee, Hoyeon Lian, Jun Liu, Shuolin Liu, Keng-Chi Marrugo, José Miki, Kentaro Nakamura, Kunio Netherton, Tucker Nguyen, Dan Nourzadeh, Hamidreza Osman, Alexander F.I. Peng, Zhao Muñoz, José Darío Quinto Ramsl, Christian Rhee, Dong Joo Rodriguez, Juan David Shan, Hongming Siebers, Jeffrey V. Soomro, Mumtaz H. Sun, Kay Hoyos, Andrés Usuga Valderrama, Carlos Verbeek, Rob Wang, Enpei Willems, Siri Wu, Qi Xu, Xuanang Yang, Sen Yuan, Lulin Zhu, Simeng Zimmermann, Lukas Moore, Kevin L. Purdie, Thomas G. McNiven, Andrea L. Chan, Timothy C.Y. Department Of Mechanical And Industrial Engineering University Of Toronto TorontoON Canada Vector Institute TorontoON Canada Department Of Radiation Oncology University Of Virginia Health System CharlottesvilleVA United States Department Of Molecular Imaging Radiation Oncology UCLouvain Louvain-la-Neuve Belgium Department Of Radiation Oncology Memorial Sloan Kettering Cancer Center New YorkNY United States Department Of Radiation Oncology The University Of Alabama At Birmingham BirminghamAL United States Department Of Engineering And Applied Physics University Of Science And Technology Of China Hefei China Shenying Medical Technology Co. Ltd. Guangdong Shenzhen China Department Of Radiation Oncology Yonsei University Seoul Korea Republic of Department Of Physics National University Of Colombia Medellín Colombia Atominstitut Vienna University Of Technology Vienna Austria Department Of Biomedical Engineering Cleveland Clinic ClevelandOH United States Department Of Radiation Physics The University Of Texas MD Anderson Cancer Center HoustonTX United States Department Of Biomedical Engineering Shanghai Jiao Tong University Shanghai China Department Of Radiation Oncology Medical University Of Vienna Vienna Austria Department Of Biomedical Engineering Johns Hopkins University BaltimoreMD United States Department Of Radiation Oncology Peking University Cancer Hospital And Institute Beijing China Department Of Electrical Engineering And Automation Anhui University Hefei China Department Of Radiation Oncology Massachusetts General Hospital BostonMA United States Department Of Radiation Oncology University Of North Carolina At Chapel Hill Chapel HillNC United States Department Of Medical Imaging Taiwan AI Labs Taipei Taiwan Department Of Biomedical And Health Sciences Hiroshima University Hiroshima Japan Laboratory Department Of Radiation Oncology The University Of Texas Southwestern Medical Center DallasTX United States Department Of Radiatio

We establish an open framework for developing plan optimization models for knowledge-based planning (KBP) in radiotherapy. Our framework includes reference plans for 100 patients with head-and-neck cancer and high-quality dose predictions from 19 KBP models that were developed by different research groups during the OpenKBP Grand Challenge. The dose predictions were input to four optimization models to form 76 unique KBP pipelines that generated 7600 plans. The predictions and plans were compared to the reference plans via: dose score, which is the average mean absolute voxel-by-voxel difference in dose a model achieved;the deviation in dosevolume histogram (DVH) criterion;and the frequency of clinical planning criteria satisfaction. We also performed a theoretical investigation to justify our dose mimicking models. The range in rank order correlation of the dose score between predictions and their KBP pipelines was 0.50 to 0.62, which indicates that the quality of the predictions is generally positively correlated with the quality of the plans. Additionally, compared to the input predictions, the KBPgenerated plans performed significantly better (P © 2022, CC BY.

关键词： Forecasting

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Indonesian License Plate Detection Using Morphological Operation

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IOP Conference Series: Materials science and engineering 2020年第1期797卷

作者： Y P Pasrun M Muchtar A N Basyarah Noorhasanah Department of Information System Faculty of Information Technology Sembilanbelas November Kolaka University South East Sulawesi Indonesia Kolaka 93517 Department of Informatics Engineering Faculty of Engineering Halu Oleo University South East Sulawesi Indonesia Kendari 93132 Department of Computer Science Faculty of Mathematics and Natural Science Halu Oleo University South East Sulawesi Indonesia Kendari 93132

Technological developments have enabled the use of vehicle number plate recognition in various fields such as parking systems, e-toll payments, handling motor vehicle theft cases, traffic violations and so on. Vehicle number plate characteristics in each country have characteristics that are not the same. Each country has a standard numbering system in its writing method, colour, language and size of the license plate, so that to take the research standards for license plate numbers from other countries is not effective. Special research is needed in accordance with the format of the number plate used by the country, in this case Indonesia. This research applies simple method, morphological operations in detecting vehicle plates in Indonesia. Morphological results will be segmented to get the image of the plate character separately. The test results show that the method applied can provide a maximum accuracy of up to 100% on taking plate images with a distance of 1.5 meters.

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Short term electric load forecast with artificial neural networks

arXiv

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arXiv 2018年

作者： Cristian, Vasar Iosif, Szeidert Ioan, Filip Gabriela, Prostean Department of Control System Engineering Politehnica' University from Timisoara Faculty of Automation and Computer Science Timisoara300223 Romania

This paper presents issues regarding short term electric load forecasting using feedforward and Elman recurrent neural networks. The study cases were developed using measured data representing electrical energy consume from Banat area. There were considered 35 different types of structure for both feedforward and recurrent network cases. For each type of neural network structure were performed many trainings and best solution was selected. The issue of forecasting the load on short term is essential in the effective energetic consume management in an open market environment. Copyright © 2007 IFAC Copyright © 2018, The Authors. All rights reserved.

关键词： Electric load forecasting

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Weather Data Analysis Using Hadoop: Applications and Challenges

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IOP Conference Series: Materials science and engineering 2019年第1期551卷

作者： Mohammed Adam Ibrahim Fakherldin Khalid Adam Noor Akma Abu Bakar Mazlina Abdul Majid Faculty of Computer Science and Information Systems Jazan University Faculty of Electric and Electronic Engineering Universiti Malaysia Pahang Faculty of Computer System & Software Engineering Universiti Malaysia Pahang

Weather data is very crucial in every aspect of human daily life. It plays an important role in many sectors such as agriculture, tourism, government planning, industry and so on. Weather has a variety of parameters like temperature, pressure, humidity and wind speed. The meteorological department deployed sensors for each weather parameter at different geographical locations to collect data. This data is stored mostly in the unstructured format. Thus, a big amount of data has been collected and archived. Therefore, storage and processing of this big data for accurate weather prediction is a huge challenge. Hadoop an apache product it used to support big data sets in a distributed environment. Hadoop has greatest advantages over scalable and fault-tolerant distributed processing technologies. This paper explains a system that uses the historical weather data of a region and apply the MapReduce and Hadoop techniques to analysis these historical data.

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