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2019 International Conference on Advanced Science and engineering, ICOASE 2019

作者： Sayaydeha, Osama Nayel Al Mohammad, Mohammad Falah Faculty of Computer Systems Software Engineering Universiti Malaysia Pahang Gambang Pahang26300 Malaysia

ISBN: (纸本)9781538693438

Parkinson's disease is a dangerous disease that attacks the nervous system and affects it negatively over time. Early diagnosis of this disease is necessary for identifying the most appropriate treatment for preventing the disease from worsening. It can be diagnosed by examining the symptoms of the patient. Recently, researchers have used voice disorders to diagnose Parkinson's disease by extracting attributes from audio recordings of affected people and using classification techniques to provide accurate diagnoses. In this paper, an enhanced fuzzy minmax neural network with the OneR attribute evaluator (EFMM-OneR) is proposed as a hybrid model for diagnosing Parkinson's disease. The proposed model consists of two stages: In the first stage, feature selection is used to identify and remove irrelevant, redundant, or noisy features from the provided dataset. In the second stage, the enhanced fuzzy min-max (EFMM) neural network is used for the classification process. The results demonstrated the ability of the EFMM-OneR model to improve the classification accuracy as compared to other classifiers from the literature. © 2019 IEEE.

关键词： Fuzzy neural networks

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E-learning prospect on improving academic performance in Omani Universities

E-learning prospect on improving academic performance in Oma...

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International Conference on Green engineering Technology and Applied Computing 2019, IConGETech2 019 and International Conference on Applied Computing 2019, ICAC 2019

作者： Tawafak, Ragad M. Romli, Awanis Abdullah Arshah, Ruzaini Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Pahang Kuantan26300 Malaysia

This paper will discuss the impact of E-Learning prospect on the improvement of learner academic performance of Oman universities. The study explains the needs to expand working on E-Learning models and continue use of face to face traditional educational process. The real problem faced education is a need for several applications and technologies to improve their outputs and improve on teacher-student prospect. This paper aims to present an expanded review of different E-learning models to evaluate the prospect of their academic performance. The method of this paper divided into two phases. In the first phase, including the analysis of different technologies and most used tools affected in the educational process to measure the acceptance of learning outcomes. The Second phase, show the testing and validation of learner prospect of E-Learning to enhance the learning process and improve the academic performance. © 2019 Published under licence by IOP Publishing Ltd.

关键词： E-learning

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A Descriptive Study towards Green Computing Practice Application for Data Centers in IT Based Industries

A Descriptive Study towards Green Computing Practice Applica...

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2017 Malaysian Technical Universities Conference on engineering and Technology, MUCET 2017

作者： Anthony, Bokolo Abdul Majid, Mazlina Romli, Awanis Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Gambang Pahang26300 Malaysia

The progressive upsurge in demand for processing and computing power has led to a subsequent upsurge in data center carbon emissions, cost incurred, unethical waste management, depletion of natural resources and high energy utilization. This raises the issue of the sustainability attainment in data centers of Information Technology (IT) based industries. Green computing practice can be applied to facilitate sustainability attainment as IT based industries utilizes data centers to provide services to staffs, practitioners and end users. But it is a known fact that enterprise servers utilize huge quantity of energy and incur other expenditures in cooling operations and it is difficult to address the needs of accuracy and efficiency in data centers while yet encouraging a greener application practice alongside cost reduction. Thus this research study focus on the practice application of Green computing in data centers which houses servers and as such presents the Green computing life cycle strategies and best practices to be practiced for better management in data centers in IT based industries. Data was collected through questionnaire from 133 respondents in industries that currently operate their in-house data centers. The analysed data was used to verify the Green computing life cycle strategies presented in this study. Findings from the data shows that each of the life cycles strategies is significant in assisting IT based industries apply Green computing practices in their data centers. This study would be of interest to knowledge and data management practitioners as well as environmental manager and academicians in deploying Green data centers in their organizations. © The Authors, published by EDP Sciences, 2018.

关键词： Green computing

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Review of Access Control Mechanisms in Cloud Computing

Review of Access Control Mechanisms in Cloud Computing

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International PostGraduate Conference on Applied Science and Physics 2017, GRASP 2017

作者： Rizwan Ghori, Muhammad Ali Ahmed, Abdulghani Faculty of Computer Systems and Software Engineering University of Malaysia Pahang Gambang Campus Kuantan Malaysia

Cloud Computing is an evolving technology in the field of IT. People are using this technology vastly as it reduces the storage and other services burden of the users as they use the services provided by the cloud. There are many advantages related to this technology like unlimited storage, cost effectiveness but lacking the strong authentication process. Many researchers are working on the security issue of cloud like user confidentiality, integrity and authenticity etc. However, in this paper we have reviewed and discussed several papers that are related to the authentication in cloud environment. Moreover, after studying different authentication system made by the researchers, we have critically analysed them and found advantages and disadvantages along with some suggestions for the future work. © Published under licence by IOP Publishing Ltd.

关键词： Cost effectiveness

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VANET Routing Protocols: Review, Implementation and Analysis

VANET Routing Protocols: Review, Implementation and Analysis

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International PostGraduate Conference on Applied Science and Physics 2017, GRASP 2017

作者： Rizwan Ghori, Muhammad Safa Sadiq, Ali Ghani, Abdul Faculty of Computer Systems and Software Engineering University of Malaysia Pahang Gambang Campus Kuantan Malaysia

Wireless technology is developing very fast. Most of the researchers are working in the field of wireless communication. VANET is an evolving technology in the field of wireless communication and with the advancement it will contribute more to the smart transportation system in days to come. VANET gives a communication framework that has enhanced the traffic service and helped in reducing the road accidents. Data sharing in this system is time sensitive and require quick and vigorous network connection forming. VANET is serving the said purposes but there are some issues and challenges like efficient handling of fast handovers for video streaming applications. Therefore, in this paper we have reviewed and discussed several studies related to the routing protocols to judge which one is the best for video applications in VANET. Moreover, after studying different systems made by the researchers, we have critically analyzed them and found advantages and disadvantages for the future works. Also, simulation is performed to check the delays and throughput comparisons between the routing protocols. Furthermore, with the experiments we have proven that the AODV performance is better than the other ad-hoc protocols in VANET environment. © Published under licence by IOP Publishing Ltd.

关键词： Routing protocols

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Learning cuckoo search strategy for t-way test generation 1

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1st International Conference on Computing, Analytics and Networks, ICAN 2017

作者： Nasser, Abdullah B. Alsewari, Abdulrahman Zamli, Kamal Z. Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang KuantanPahang26300 Malaysia

ISBN: (数字)9789811307553

ISBN: (纸本)9789811307546

The performance of meta-heuristic algorithms highly depends on their exploitation and exploration techniques. In the past 30 years, many meta-heuristic algorithms have been developed which adopts different exploitation and exploration techniques. Several studies reported that the hybrid of meta-heuristics algorithms often perform better than its corresponding original algorithm. This paper presents a new hybrid algorithm;called Learning Cuckoo Search (LCS) strategy based on the integration student phase from Teaching Learning based Optimization (TLBO) Algorithm. To evaluate the developed algorithm, we use the problem of t-way test generation as our case study. The experiment results show that LCS has better performance as compared as to the original Cuckoo Search as well many other existing strategies. © 2018, The Author(s).

关键词： Heuristic algorithms

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An analytical study evaluating the applicability of a developed innovative E-Sourcing system for automobile based firm

An analytical study evaluating the applicability of a develo...

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2018 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies, 3ICT 2018

作者： Anthony, Bokolo Majid, Mazlina Abdul Romli, Awanis Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Gambang Pahang26300 Malaysia

ISBN: (纸本)9781538692073

Automobile based firms involve enterprises that deal with the sale of cars products from different manufactures. Hence, over the years several studies have contributed to e-businesses, but at the moment there are fewer studies that have contributed to improving e-sourcing operation in automobile based firms. Therefore, this paper aims to develop an innovative e-sourcing system for automobile based firms based on Model View Control (MVC) architecture to facilitate procurement operation among consumers and sales staffs. The developed system aims to lessen the labor of sales staff thus decreasing manual task carried out. Additionally, the proposed tool substitutes the manual approach by facilitating administration in the form of automating automobile data. The tool also aids in managing and retaining of clients' data. Furthermore, the developed tool facilitate customers in viewing catalog of new automobile products and ordering new automobile products from several automobile manufacturers such as Toyota, Honda, Nissan etc., whenever they want to without visiting the company. Additionally, the developed innovative e-sourcing system was evaluated using questionnaire data to validate the applicability of tool in maintaining automobile products order between the customer and sales staff based on data from 50 respondents. Hence, statistical analysis was employed to examine the dataset utilizing Microsoft Excel. Results from the analyzed data reveal that the developed innovative e-sourcing system is applicable in supporting sales of automobile based products. © 2018 IEEE.

关键词： Sales

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Textile web defect inspection by feature analysis method

Textile web defect inspection by feature analysis method

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2nd International Conference on Innovative Computing, Information and Control, ICICIC 2007

作者： Musa, Zalili Kadir, Tuty Asmawaty Abdul Bakar, Rohani Abu Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang 25000 Kuantan Pahang Malaysia

ISBN: (纸本)0769528821

Nowadays in the textile industry are still used a human naked eyes to detect any kinds of defect on textile webs. The problems occurred when a human has their own limitations on different kind of perceptions in identifying a defect. In this paper, we intend to propose an object classification using a standard deviation value for classifying the defect on textile webs. First we describe the method of image segmentation that we applied in this study which is based on statistical technique. Further, we focus on the features analysis where we divide it into two phases;(1) learning phase and (2) analysis phase. Finally, we have been tested our propose algorithm into 5 (five) different types of textile webs with 500 images for each type of webs. We figure out that this method is suitable for distort and small defect as in textile webs. The details of results from our testing phases will be discussed at the end of this paper. © 2007 IEEE.

关键词： Defects

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A component-oriented programming for embedded mobile robot software

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International Journal of Advanced Robotic systems 2007年第3期4卷 371-380页

作者： Jawawi, Dayang N. A. Mamat, Rosbi Deris, Safaai Department of Software Engineering Faculty of Computer Science and Information Systems Universiti Teknologi Malaysia 81310 UTM Skudai Malaysia Department of Mechatronics and Robotics Engineering Faculty of Electrical Engineering Universiti Teknologi Malaysia 81310 UTM Skudai Malaysia

Applying software reuse to many Embedded Real-Time (ERT) systems poses significant challenges to industrial software processes due to the resource-constrained and real-time requirements of the systems. Autonomous Mobile Robot (AMR) system is a class of ERT systems, hence, inherits the challenge of applying software reuse in general ERT systems. Furthermore, software reuse in AMR systems is challenged by the diversities in terms of robot physical size and shape, environmental interaction and implementation platform. Thus, it is envisioned that component-based software engineering will be the suitable way to promote software reuse in AMR systems with consideration to general requirements to be self-contained, platform-independent and real-time predictable. A framework for component-oriented programming for AMR software development using PECOS component model is proposed in this paper. The main features of this framework are: (1) use graphical representation for components definition and composition;(2) target C language for optimal code generation with resource-constrained micro-controller;and (3) minimal requirement for run-time support. Real-time implementation indicates that, the PECOS component model together with the proposed framework is suitable for resource constrained embedded AMR systems software development.

关键词： Mobile robots

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Time-intervals-related pattern selection for continuous event prediction

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Pattern Recognition 2025年 168卷

作者： Nevo Itzhak Szymon Jaroszewicz Robert Moskovitch Software and Information Systems Engineering Ben-Gurion University of the Negev Beer Sheva Israel Institute of Computer Science Polish Academy of Sciences Warsaw Poland Faculty of Mathematics and Information Science Warsaw University of Technology Warsaw Poland

Symbolic time intervals (STIs) are used in different domains to represent real-life events with varying durations, like traffic light timing or medical treatments. Multivariate temporal data may include STIs and event-driven or manual measurements, such as traffic accidents or blood tests. This study proposes temporal abstraction to uniformly represent such heterogeneous multivariate temporal data (time point values, instantaneous events, or time intervals) using STIs and to develop a model to continuously predict events of interest. We introduce the use of multiple TIRPs that end with an event of interest for continuous prediction while using multiple TIRP instance completion predictors simultaneously. Since often there are dozens of discovered patterns, in this paper, we introduce novel discriminative pattern-selection metrics, such as the differences in the frequencies or duration between the entities ( e.g. , patients) having or not having the event of interest. The proposed methods achieved an average improvement of 5% AUROC over LSTM-FCN, the best-performing baseline, out of the evaluated baseline models (RawXGB, Resnet, LSTM-FCN, and ROCKET) that were applied to the raw medical and non-medical datasets. The proposed continuous event prediction method has the potential for broad real-world and real-time applicability in diverse domains with heterogeneous multivariate temporal data, such as early panic attack prediction using wearable devices or early complication prediction in intensive care unit patients.

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