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2nd International Conference on Advanced Data and Information engineering, DaEng 2015

作者： Mohd, Wan Maseri Wan Beg, A.H. Herawan, Tutut Noraziah, Ahmad Chiroma, Haruna Faculty of Computer Systems & Software Engineering University Malaysia Pahang Lebuhraya Tun Razak Gambang KuantanPahang26300 Malaysia

ISBN: (纸本)9789811317972

K-Means is one of the popular methods for generating clusters. It is very well-known and commonly used for its convenience and fastness. The main disadvantage of these criteria is that user should specify the number of cluster in enhance. As a repetitive clustering strategy, a K-Means criterion is very delicate to the preliminary beginning circumstances. In this paper, has been proposed a clustering strategy known as Multi-dimensional K-Means clustering criteria. This algorithm auto generates preliminary k (the preferred variety of cluster) without asking input from the user. It also used a novel strategy of establishing the preliminary centroids. The experiment of the proposed strategy has been conducted using synthetic data, which is taken form LIyod’s K-means experiments. The algorithm is suited for higher education for calculating the student’s CGPA and extracurricular activities with graphs. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Data mining

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Balancing energy consumption in limited power grid with active front-end and three phase dual active bridge system

Balancing energy consumption in limited power grid with acti...

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Compatibility in Power Electronics (CPE)

作者： Konstantin Vorobev Ryszard Strzelecki Nikolai Poliakov School of Computer Technologies and Control Faculty of Control Systems and Robotics ITMO University Saint-Petersburg Russia Faculty of Electrical and Control Engineering Gdańsk University of Technology Gdańsk Poland

ISBN: (数字)9781728142180

ISBN: (纸本)9781728142197

Paper deals with simulation analysis of bidirectional power converters system for charging station of electric vehicle in condition of limited power source in city infrastructure. In case of incapability to provide additional power supply through the grid by virtue of historical, architectural and economic reasons it is possible to solve this issue by implementation of mobile battery-powered supply source. The proposed bidirectional power converters system for consist of three-phase dual active bridge two-directional converter and active front end. Bidirectional power converters system operation modes considered in the paper include transmission of energy from both the battery station, and grid and the joint power supply with battery and grid.

关键词： Batteries Power supplies Switches Urban areas Power grids Bridges

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Optimize Performance Load Balancing Techniques Using Binary Vote Assignment Grid Quorum (BVAGQ): A Systematic Review 2nd

Optimize Performance Load Balancing Techniques Using Binary ...

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2nd International Conference on Advanced Data and Information engineering, DaEng 2015

作者： Fairuzullah, A. Noraziah, Ahmad Arshah, Ruzaini Abdullah Herawan, Tutut Faculty of Computer Systems & Software Engineering University Malaysia Pahang Gambang KuantanPahang26300 Malaysia Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur50603 Malaysia

ISBN: (纸本)9789811317972

This paper present load balancing technique in a heterogeneous environment allows the usage for geographically widely distributed and multi-owner resources to solve large-level application, usage of load balancing algorithms was important to keep maintaining the balance of workload between emerged infrastructures like grid. This replication generally referred as mechanism to improve availability and performance in distributed databases especially handling fragmented database replication becomes demanding issue. Intended in this paper we address various kinds of load balancing algorithms for the heterogeneous network like grid, especially Binary Vote Assignment Grid Quorum (BVAGQ) and to identify various metric and gaps between them. Many load balancing algorithms are already implemented which work against various issues like heterogeneity, scalability, etc. Different load balancing algorithms for the grid environment work on various metrics such as make span, time, average resource utilization rate, communication overhead, reliability, stability, and fault tolerance. However the aim is to find improved query response time and overall throughput as compared to other scheme. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Fault tolerance

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A New Approach to Secure and Manage Load Balancing of the Distributed Database Using SQL Firewall 2nd

A New Approach to Secure and Manage Load Balancing of the Di...

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2nd International Conference on Advanced Data and Information engineering, DaEng 2015

作者： Fairuzullah, A. Noraziah, Ahmad Mohd, Wan Maseri Wan Herawan, Tutut Faculty of Computer Systems & Software Engineering University Malaysia Pahang Gambang KuantanPahang26300 Malaysia Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur50603 Malaysia

ISBN: (纸本)9789811317972

This paper is the current approach database security of organization need layers of security around their data, with each layer protecting a specific area. The current trend of security attack is targeting any valuable data stored in a database such as financial data and student mark, including data theft, data modification or replay and data disruption. To understand how the system works, the system setting and the weaknesses of Enterprise Distributed Database. This paper is about the design and development to secure database access, a framework based on packet and content filtering on IP address, port and SQL statement. And simulate the framework and design database security framework. We address how to build the outcome of this is to reduce the risk of data manipulation and reduce the impact of internal threat and malicious insiders. The result shows that the proposed method succeeded in meeting those aspects of information security. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Security of data

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A Time Effect based Collaborative Filtering Approach for User Preference Statistics and Recommendation 2

A Time Effect based Collaborative Filtering Approach for Use...

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2019 2nd International Conference on computer Information Science and Artificial Intelligence, CISAI 2019

作者： Chen, Yuxi Zhang, Xiaotong Zhao, Qing Akhtar, Faheem School of Statistics and Mathematics Country Central University of Finance and Economics Beijing100081 China Harpur College of Arts and Sciences Binghamton University-SUNY New York13902 United States Faculty of Information Technology Beijing University of Technology Beijing100124 China Department of Computer Science Vrije Universiteit Amsterdam1081 HV Netherlands School of Software Engineering Beijing University of Technology Beijing Engineering Research Center for IoT Software and Systems Beijing100124 China Department of Computer Science Sukkur IBA University Sukkur65200 Pakistan

With the rapid development of the information technologies in the financial field, extracting meaningful information from a massive amount of data is hugely significant for efficient business decision making. The recommendation system is an intelligent system that applies historical knowledge of users to infer their preferences and make a personalized recommendation. However, it suffers from the problem of time effect of user's behaviour, which means a user's interests may change over time. To overcome this problem, we propose a time effect based collaborative filtering approach to adaptively statistics the change of user preferences. Firstly, Item-based collaborative filtering is used to calculate rating similarity between items. Since an Item-based collaborative filtering algorithm doesn't consider the time effect;next, the time decay function is proposed to statistics the change of user interests. Experimental results show that the proposed scheme retained higher accuracy compare to traditional collaborative filtering method. © Published under licence by IOP Publishing Ltd.

关键词： Collaborative filtering

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arXiv

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arXiv 2019年

作者： Netisopakul, Ponrudee Wohlgenannt, Gerhard Pulich, Aleksei Bangkok Thailand Faculty of Software Engineering and Computer Systems Itmo University St. Petersburg Russia

Distributional semantics in the form of word embeddings are an essential ingredient to many modern natural language processing systems. The quantification of semantic similarity between words can be used to evaluate the ability of a system to perform semantic interpretation. To this end, a number of word similarity datasets have been created for the English language over the last decades. For Thai language few such resources are available. In this work, we create three Thai word similarity datasets by translating and re-rating the popular WordSim-353, SimLex-999 and SemEval-2017-Task-2 datasets. The three datasets contain 1852 word pairs in total and have different characteristics in terms of difficulty, domain coverage, and notion of similarity (relatedness vs. similarity). These features help to gain a broader picture of the properties of an evaluated word embedding model. We include baseline evaluations with existing Thai embedding models, and identify the high ratio of out-of-vocabulary words as one of the biggest challenges. All datasets, evaluation results, and a tool for easy evaluation of new Thai embedding models are available to the NLP community online. Copyright © 2019, The Authors. All rights reserved.

关键词： Embeddings

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E-learning Model for Students' Satisfaction in Higher Education Universities: Review Paper

E-learning Model for Students' Satisfaction in Higher Educat...

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2019 International Conference on Fourth Industrial Revolution, ICFIR 2019

作者： Tawafak, Ragad M Romli, Awanis B.T. Arshah, Ruzaini Bin Abdullah Faculty of Computer Systems and Software Engineering University Malaysia Pahang Kuantan Pahang26300 Malaysia Faculty of Information Technology Department AlBuraimi University College Buraimi Oman

ISBN: (纸本)9781728114781

The number of internet users with E-Learning models offered in high educational institutions has increased rapidly with the beginning of this century. However, with the increment in number of higher education in the universities, the learner needs more flexibility to attend lesions and easy participate in communication. Therefore, E-Learning is one of the ways provide an accessibility and flexibility to more learners to overcome the far distance of locations or different cultures or timing management for achieving student satisfaction. This paper aims to analyze the current studies on benefits of E-Learning of student satisfaction on the technologies applied and type of blended learning used in learning process to get better qualified learners and to improve the student learning outcomes. The method based on showing different types of E-Learning strategies and the way that allowed learners and faculties to communicate using the common communication models. The finding of this paper shows analytical studies results and their positive evidence with student satisfaction on E-Learning models. © 2019 IEEE.

关键词： E-learning

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The personification of the user’s interface: classification vs. Clusterization of users of online courses 12

The personification of the user’s interface: classification...

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12th International Scientific and Practical Conference on Environment. Technology. Resources

作者： Matrosova, Nataliia D. Shtennikov, Dmitry G. Faculty of Software Engineering and Computer Systems Saint-Petersburg National Research University of Information Technologies Mechanics and Optics Saint-Petersburg Russia

Researchers compared the classification and the clusterization of users of online course for the personification of the users’ information system interface. When interacting with control and information systems, users may manifest individual features, including implicit characteristics that may affect one’s results within the system. At the same time due to information system building peculiarities one of the most comprehensive statistics can be collected via e-learning systems. When using a course, the user leaves a wide trail of activity that may contain different information depending on the learning environment structure. Online blended learning courses draw the researcher’s attention to the impact of digital teaching models on students as well as its ability to adjust distant learning courses to individual students’ needs and differences. Information personalization is a highly relevant content presentation at the most individual level. Therefore, the task of personalization is to show users information that meets their needs and interests. Personalization gives the opportunity to focus on points that have real value for users. © 2019 Nataliia D. Matrosova, Dmitry G. Shtennikov.

关键词： Machine learning

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BG-GAN: Generative AI Enable Representing Brain Structure-Function Connections for Alzheimer’s Disease

arXiv

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arXiv 2023年

作者： Zhou, Tong Ding, Chen Jing, Changhong Liu, Feng Hung, Kevin Pham, Hieu Mahmud, Mufti Lyu, Zhihan Qiao, Sibo Wang, Shuqiang Tsang, Kim-Fung The Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China University of Chinese Academy of Sciences Beijing100864 China The Department of Systems and Enterprises Stevens Institute of Technology United States School of Science and Technology Hong Kong Metropolitan University Hong Kong College of Engineering and Computer Science VinUni-Illinois Smart Health Center VinUniversity Viet Nam Department of Information and Computer Science SDAIA-KFUPM Joint Research Center for AI Interdisciplinary Research Center for Biosystems and Machines King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia Department of Game Design Faculty of Arts Uppsala University Sweden The School of Software Tiangong University Tianjin300387 China

The relationship between brain structure and function is critical for revealing the pathogenesis of brain disorders, including Alzheimer’s disease (AD). However, mapping brain structure to function connections is a very challenging task. In this work, a bidirectional graph generative adversarial network (BG-GAN) is proposed to represent brain structure-function connections. Specifically, by designing a module incorporating inner graph convolution network (InnerGCN), the generators of BG-GAN can employ features of direct and indirect brain regions to learn the mapping function between the structural domain and the functional domain. Besides, a new module named Balancer is designed to counterpoise the optimization between generators and discriminators. By introducing the Balancer into BG-GAN, both the structural generator and functional generator can not only alleviate the issue of mode collapse but also learn complementarity of structural and functional features. Experimental results using Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset show that both generated structure and function connections can improve the identification accuracy of AD. The experimental findings suggest that the relationship between brain structure and function is not a complete one-to-one correspondence. They also suggest that brain structure is the basis of brain function, and the strong structural connections are majorly accompanied by strong functional connections. Copyright © 2023, The Authors. All rights reserved.

关键词： Neurodegenerative diseases

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IEEE ICCI*CC Series in Year 20: Latest Advances in Cognitive Computing (Plenary Panel Report-II) 20

IEEE ICCI*CC Series in Year 20: Latest Advances in Cognitive...

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20th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2021

作者： Kinsner, Witold Zhu, Haibin Baciu, George Luo, Guiming Rubio, Fernando Sui, Jie Huang, Runhe Hiraishi, Hironori Peng, Jun Chen, Liang Univ. of Manitoba FI2CICC Dept of ECE Winnipeg Canada Nipissing University FI2CICC ON Canada Hong Kong Polytechnic University FI2CICC Dept. of Computing Hong Kong Tsinghua University FI2CICC Software Institute Beijing China Complutense Univ. of Madrid FI2CICC Dept. of Computer Systems and Computation Spain Aberdeen University FI2CICC Aberdeen United Kingdom Hosei University FI2CICC Faculty of Computer and Information Sciences Japan Ashikaga University Faculty of Engineering Tochigi326-8558 Japan Chongqing Univ. of Science and Technology FI2CICC School of AI Chongqing China Univ. of Northern British Columbia Dept. of Computer Science BC Canada

ISBN: (纸本)9781665421195

Cognitive Computing (CC) is a contemporary field of fundamental intelligence theories and general AI technologies triggered by the transdisciplinary development in intelligence, computer, brain, knowledge, cognitive, robotic, and cybernetic sciences for engineering implementations. This paper presents a summary of the plenary panel (Part II) on the theoretical foundations of CI/CC and recent breakthroughs in AI engineering reported in the 20th IEEE International ICCI*CC Conference (ICCI*CC'21). The latest advances in CI and CC towards general AI are presented by twenty-Two distinguished panelists. Strategic AI engineering applications in CI, CC, and cognitive systems are elaborated for abstract intelligence, cognitive robots, autonomous systems, intelligent vehicles, and safety-And-mission-critical systems. © 2021 IEEE.

关键词： Cognitive systems

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