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IEEE Conference on systems, Process & Control (ICSPC)

作者： Anis Farihan Mat Raffei Hishammuddin Asmuni Rohayanti Hassan Razib M. Othman Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Lebuhraya Tun Razak Kampung Melayu Gambang Gambang Pahang Malaysia Faculty of Computing N28A Universiti Teknologi Malaysia Johor Bahru Johor Malaysia

ISBN: (纸本)9781538663288;9781538663271

The low resolution iris images in non-cooperative environment has resultant in failure to determine the eye center, limbic and pupillary boundary of the iris segmentation. Hence, a combination with periocular area is suggested to improve the accuracy of the recognition system. However, the existing periocular features extraction methods to extract the texture features can be easily affected by a background complication and depends on image size and orientation. Although some of the existing studies have combined the texture and colour features to increase the accuracy of periocular recognition, still, the method of colour feature extraction is limited to spatial information and quantization effects. This paper presents the analysis of texture and colour based features of periocular for low resolution colour iris images. Two datasets: UBIRIS.v2 and UBIPr are used and the proposed method provides robust discriminative structure features and sufficient spatial information which has increased the discriminating power.

关键词： Feature extraction Image color analysis Image resolution Iris recognition Histograms Conferences Process control

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Handling constraints in combinatorial interaction testing in the presence of multi objective particle swarm and multithreading

arXiv

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arXiv 2018年

作者： Ahmed, Bestoun S. Gambardella, Luca M. Afzal, Wasif Zamli, Kamal Z. Manno-LuganoCH-6928 Switzerland Department of Computer Science Faculty of Electrical Engineering Czech Technical University Karlovo nam. 13 Praha 2121 35 Czech Republic School of Innovation Design and Engineering Mlardalen University Sweden Faculty of Computer Systems and Software Engineering University Malaysia Pahang Gambang Malaysia

Context: Combinatorial testing strategies have lately received a lot of attention as a result of their diverse applications. In its simple form, a combinatorial strategy can reduce several input parameters (configurations) of a system into a small set based on their interaction (or combination). In practice, the input configurations of software systems are subjected to constraints, especially in case of highly configurable systems. To implement this feature within a strategy, many difficulties arise for construction. While there are many combinatorial interaction testing strategies nowadays, few of them support constraints. Objective: This paper presents a new strategy, to construct combinatorial interaction test suites in the presence of constraints. Method: The design and algorithms are provided in detail. To overcome the multi-judgement criteria for an optimal solution, the multi-objective particle swarm optimisation and multithreading are used. The strategy and its associated algorithms are evaluated extensively using different benchmarks and comparisons. Results: Our results are promising as the evaluation results showed the efficiency and performance of each algorithm in the strategy. The benchmarking results also showed that the strategy can generate constrained test suites efficiently as compared to state-of-the-art strategies. Conclusion:The proposed strategy can form a new way for constructing of constrained combinatorial interaction test suites. The strategy can form a new and effective base for future implementations. Copyright © 2018, The Authors. All rights reserved.

关键词： Multiobjective optimization

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A Hybrid Q-Learning Sine-Cosine-based Strategy for Addressing the Combinatorial Test Suite Minimization Problem

arXiv

引用

arXiv 2018年

作者： Zamli, Kamal Z. Din, Fakhrud Ahmed, Bestoun S. Bures, Miroslav IBM Centre of Excellence Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Lebuhraya Tun Razak Kuantan Pahang Darul Makmur 26300 Malaysia Department of Computer Science Faculty of Electrical Engineering Czech Technical University Karlovo nam. 13 Praha 2121 35 Czech Republic

The sine-cosine algorithm (SCA) is a new population-based meta-heuristic algorithm. In addition to exploiting sine and cosine functions to perform local and global searches (hence the name sine-cosine), the SCA introduces several random and adaptive parameters to facilitate the search process. Although it shows promising results, the search process of the SCA is vulnerable to local minima/maxima due to the adoption of a fixed switch probability and the bounded magnitude of the sine and cosine functions (from-1 to 1). In this paper, we propose a new hybrid Q-learning sine-cosine-based strategy, called the Q-learning sine-cosine algorithm (QLSCA). Within the QLSCA, we eliminate the switching probability. Instead, we rely on the Q-learning algorithm (based on the penalty and reward mechanism) to dynamically iden-tify the best operation during runtime. Additionally, we integrate two new operations (Lvy ight motion and crossover) into the QLSCA to facilitate jumping out of local minima/maxima and enhance the solution diversity. To assess its performance, we adopt the QLSCA for the combinatorial test suite minimization problem. Experimental results reveal that the QLSCA is sta-tistically superior with regard to test suite size reduction compared to recent state-of-the-art strategies, including the original SCA, the particle swarm test generator (PSTG), adaptive particle swarm optimization (APSO) and the cuckoo search strategy (CS) at the 95% confidence level. However, con-cerning the comparison with discrete particle swarm optimization (DPSO), there is no significant difference in performance at the 95% confidence level. On a positive note, the QLSCA statistically outperforms the DPSO in certain configurations at the 90% confidence level. Copyright © 2018, The Authors. All rights reserved.

关键词： Cosine transforms

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Factors influencing the continuous use of cloud computing services in organization level 17

Factors influencing the continuous use of cloud computing se...

引用

2017 International Conference on Advances in Image Processing, ICAIP 2017

作者： Al-Sharafi, Mohammed A. Arshah, Ruzaini Abdullah Abu-Shanab, Emad A. Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Lebuhraya Tun Razak Gambang Kuantan26300 Malaysia Accounting and Information Systems College of Business and Economics Qatar University Doha Qatar

ISBN: (纸本)9781450352956

The primary purpose of carrying out this research work is to identify the crucial factors that influence the continuous use of cloud computing services in organizations. To achieve this identified objective, this research work carried out a comprehensive literature review on cloud computing services' adoption at the organizational level, particularly emphasizing the factors that define the prolonged adoption of cloud computing services. The factors identified, served as a guide required by organizations for completely safe and effective cloud computing service and their use in businesses. This research adopts the criteria of Wymer and Regan as a basis for this study. A total of 53 factors were obtained from prior studies on the cloud computing services' adoption. Results obtained during the cause of study revealed that the most crucial factors affecting the continuous use of cloud computing services in organizations are as follows: Relative advantage;Complexity: Perceived security and privacy;Compatibility;Top manager's support;Cost reduction;Competitive pressure;IT readiness;Firm size;Vendor support;Regulations and Government policy;Trialability;Perceived reliability;Perceived availability;Uncertainty and Perceived Trust. © 2017 Association for Computing Machinery.

关键词： Cost reduction

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Preface

引用

CEUR Workshop Proceedings 2022年 3091卷

作者： Kovalev, Igor Semenkin, Eugene Schwenker, Friedhelm Shaidurov, Vladimir Ganchev, Todor Škraba, Andrej Stanimirović, Predrag Kolehmainen, Mikko Kronberger, Gabriel Affenzeller, Michael Brester, Christina Ryzhikov, Ivan Kazakovtsev, Lev Sopov, Evgenii Semenkina, Maria Akhmedova, Shakhnaz Stanovov, Vladimir Krasnoyarsk Regional Science and Technology City Hall Department of Computer Science of Siberian Federal University Krasnoyarsk Russia Siberian Institute of Applied System Analysis named after A.N. Antamoshkin The Department ofsystem analysis and operations research of Reshetnev University Krasnoyarsk Russia Institute of Neural Information Processing Ulm University Ulm Germany The Institute of Computational Modeling SB RAS Krasnoyarsk Russia Technical University of Varna Varna Bulgaria University of Maribor UM Faculty of Organizational Sciences Cybernetics and Decision Support Systems Laboratory Slovenia Department of Computer Science Niš Serbia Department of Environmental and Biological Sciences Environmental Informatics University of Eastern Finland Kuopio Finland University of Applied Sciences Upper Austria Hagenberg Austria Department of Software Engineering School of Informatics Communications and Media University of Applied Sciences Upper Austria Hagenberg Austria University of Eastern Finland UEF · Department of Environmental Science Kuopio Finland The Department of Systems Analysis Reshetnev University of Science and Technology Krasnoyarsk Russia Siberian Institute of Applied System Analysis Krasnoyarsk Russia University of Applied Sciences Upper Austria and Softwarepark Hagenberg Austria Reshetnev Siberian States University of Science and Technology Siberian Institute of Applied System Analysis Krasnoyarsk Russia SibSAU · Institute of computer science and telecommunications Krasnoyarsk Russia

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Enhancement the video quality forwarding Using Receiver-Based Approach(URBA) in Vehicular Ad-Hoc Network

Enhancement the video quality forwarding Using Receiver-Base...

引用

2017 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications, ICRAMET 2017

作者： Hammood, Omar A. Kahar, Mohd Nizam Mohmad Mohammed, Muamer N. Faculty of Computer Systems and Software Engineering University Malaysia Pahang Pahang Malaysia IBM Center of Excellence University Malaysia Pahang Pahang Malaysia Department of Computer Sciences Bayan University Erbil Iraq

ISBN: (纸本)9781538638491

In Vehicular Ad-hoc Networks (VANETs), data routing is a major problem because of its quick change in topology and vehicular high mobility. VANETs are ad hoc wireless mobile networks which play important role in commercial applications and safety of public vehicular communications. The routing protocols that base on vehicular position are attracting much interest because of the availability and advancement of devices equipped with GPS. A major problem with VANETs is the frequent disruptions in the path of vehicles due to the high mobility of the participating vehicles. This can lead to the breaking of established links and result in low throughput, delay in service delivery, less overhead as well as low rate of delivery. In this paper, Using Receiver-Based Approach (URBA) is proposed. The proposed approach (URBA) compared to VANET, incorporates a potential receiver-based strategy which is traditionally better in performance and might achieve less delay in service delivery with a higher rate of delivery. © 2017 IEEE.

关键词： Vehicular ad hoc networks

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A Flexible Keyphrase Extraction Technique for Academic Literature

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Procedia computer Science 2018年 135卷 553-563页

作者： Gollam Rabby Saiful Azad “ Mufti Mahmud Kamal Z. Zamli Mohammed Mostafizur Rahman Faculty of Computer Systems & Software Engineering University Malaysia Pahang Gambang Kuantan Malaysia IBM Centre of Excellence Gambang Kuantan Malaysia Department of Computing and Technology Nottingham Trent University Nottingham United Kingdom Department of Mathematics American International University - Bangladesh (AIUB) Dhaka Bangladesh

A keyphrase extraction technique endeavors to extract quality keyphrases from a given document, which provide a high-level summary of that document. Except statistical keyphrase extraction approaches, all other approaches are either domain-dependent or require a sufficient amount of training data, which are rare at present. Therefore, in this paper, a new tree-based automatic keyphrase extraction technique is proposed, which is domain-independent and employs nominal statistical knowledge; but no train data are required. The proposed technique extracts a quality keyphrase through forming a tree from a candidate keyphrase; and later, it is expanded or shrunk or remained in the same state depending on other similar candidate keyphrases. At the end, keyphrases are extracted from the resultant trees based on a value, µ (which is the Maturity Index (MI) of a node in the tree), which enables flexibility in this process. A small µ value would yield many and/or lengthy keyphrases (greedy approach); whereas, a large µ value would yield lower and/or abbreviated keyphrases (conservative approach). Thereby, a user can extract his/her desired-level of keyphrases through tuning µ value. The effectiveness of the proposed technique is evaluated on an actual corpus, and compared with Rapid Automatic Keyphrase Extraction (RAKE) technique.

关键词： Candidate keyphrase keyphrase automatic keyphrase extraction technique tree data structure

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Application of High Conductive Nanoparticles to Enhance the Thermal and Mechanical Properties of Wood Composite

引用

Materials Today: Proceedings 2018年第1期5卷 3143-3149页

作者： Arun Gupta Anuj Kumar K.V. Sharma Ritu Gupta Centre for Biocomposite and Innovative Materials (CBIM) Faculty of Chemical and Natural Resources Engineering University Malaysia Pahang 26300 Kuantan Pahang Malaysia Department of Building Structures Faculty of Civil Engineering Czech Technical University in Parague Czech Republic Department of Mechanical Engineering University Teknologi Petronas 32610 Seri Iskandar Perak Darul Ridzuan Malaysia Department of Computer Systems and Software Engineering University Malaysia Pahang 26300 Kuantan Pahang Malaysia

In the present work three different types of Nanofillers such as multiwalled carbon Nanotubes (CNTSs), aluminum oxide Nanoparticles and Nanosize activated charcoal were mixed with urea formaldehyde (UF) resin and used in the preparation of medium density fiberboard (MDF). The fillers has improved heat transfer during hot pressing and achieved proper curing due to enhanced thermos-physical properties of wood fibers. To improve the dispersion of Nanofillers into UF matrix, high speed mechanical stirring and ultrasonic treatments were used. The CNTSs were oxidized with nitric acid and the functional groups formed on its surface improved the dispersion and interaction with UF matrix. The mixing of CNTSs and Aluminum oxide with UF resin have reduced the curing time due to enhanced thermal conductivity of MDF matrix. The heat transfer during hot pressing of MDF improved significantly with the addition of CNTSs and Al 2 O 3 Nanoparticle. The activated charcoal did not show much effect on heat transfer. The curing rate of UF resin improved with all the three Nanofillers, as the activation energy of UF curing decreases. The physical and mechanical properties of MDF have improved significantly with CNTSs and Al2O3 Nanoparticle. The activated charcoal has significantly decreased the formaldehyde emission of MDF.

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Collaborative Filtering Similarity Measures: Revisiting

Collaborative Filtering Similarity Measures: Revisiting

引用

作者： Hael Al-bashiri Mansoor Abdullateef Abdulgabber Awanis Romli Fadhl Hujainah Faculty of Computer Systems & Software Engineering Universiti Malaysia Pahang

This paper discussed the most commonly used similarity measures in Collaborative Filtering(CF) recommender system. In addition, the author introduced some recommendations related to CF system quality improvement which should be considered in the process of formulating similarity measure that may lead to alleviating the issue of data sparsity and some existing measures shortcomings. Generally, CF approach is one of the most widely used and most successful methods for the recommendation system, such as e-commerce. CF system introduced items to the user based on his/her previous ratings and the ratings of his/her neighbors. Therefore, the most important stage in CF system is locating the successful neighbor. Nevertheless, the sparsity of data is the major issue faced by the memory-based CF. The reason behind this is that many of the users rated a few number of items from the huge number of available items. This has encouraged many researchers to provide solutions. One of these solutions was by proposing or updating similarities measures take in considerations the global information preference, all ratings provided by users, the size of common ratings, and so on. In this work, the researcher discussed these measures alongside with their limitations. In addition, the researcher also listed some advices that are important in the process of locating successful neighbors, which may help researchers to improve the quality of CF system.

关键词： Recommendation System Collaborative Filtering Similarity Measurer

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Preface

引用

CEUR Workshop Proceedings 2022年 3304卷

作者： Jia, Weijia Yin, Jian Hu, Shaolin Peng, Shaoliang Niu, Shaozhang Srinivasa Rao, P.C. Lu, Yao Mirsaeidi, Sohrab Cao, Bin Wu, Yilin Wang, Xingbo Subramaniyam, Kannimuthu Boddu, Raja Sarath Kumar Li, Zhonghua Tao, Qian Zhang, Lei Li, Yi Ding, Deqing Wang, Dahan Zhang, Ziyan AlShawabkeh, Mahmoud Aslam, Muhammad Dib, Omar Sahibuddin, Shamsul Bin Wagh, Sanjeev J. Pardalos, Panos M. Al-Sammarraie, Najeeb Abbas Liu, Linfeng Kong, Jin-Heung Borrego, Carlos Tahir, Sabeen Wu, Zhiheng Li, Jiongcheng Xu, Yong Xie, Zhi Wang, Jiahai Cai, Hongmin Yang, Yuedong Qin, Xiaolin Beijing Normal University Zhuhai China Sun Yat-sen University China Guangdong University of Petrochemical Technology China Hunan University China Beijing University of Posts and Telecommunications China India Beijing Jiaotong University China Hebei University of Technology China Guangdong University of Education China Foshan University China Karpagam College of Engineering India Lenora College of Engineerin India Yat-sen University Guangdong High Performance Computing Society China South China University of Technology China Henan University China Wenzhou University China National University of Defense Technology China Xiamen University of Technology China Hainan Tropical Ocean University China Guangxi Normal University for Nationalities China Wuhan University China Wenzhou-Kean University China School of Software Engineering Universiti Teknologi Malaysia Information Technology Government College of Engineering Karad India Department of Industrial & Systems Engineering University of Florida United States Al-Madinah International University Faculty of Computer and Information Technology Malaysia School of Computer Science and Technology Nanjing University of Posts and Telecommunications China School of Computer and Information Engineering Kwangwoon University Korea Republic of Departament Enginyeria of Information Comunicacions Autonomous University of Barcelona Spain Information Technology Department King AbdulAziz University Jeddah Saudi Arabia Institute of Manufacturing GDAS China Guangdong Planning and Designing Institute of Telecommunications Co. Ltd China Guangzhou Institutes of Biomedicine and Health Chinese Academy of Sciences China Cheng Du Information Technology of Chinese Academy of Sciences Co. Ltd China

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