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The direction of cloud computing for Malaysian education sector in 21st century

AIP Conference Proceedings 2017年第1期1870卷

作者： Jazurainifariza Jaafar M. Nordin A. Rahman M. Fadzil A. Kadir Syadiah Nor Shamsudin Syarilla Iryani A. Saany 1Faculty Informatics and Computing Universiti Sultan Zainal Abidin Tembila Campus 22200 Besut Terengganu Malaysia

In 21st century, technology has turned learning environment into a new way of education to make learning systems more effective and systematic. Nowadays, education institutions are faced many challenges to ensure the teaching and learning process is running smoothly and manageable. Some of challenges in the current education management are lack of integrated systems, high cost of maintenance, difficulty of configuration and deployment as well as complexity of storage provision. Digital learning is an instructional practice that use technology to make learning experience more effective, provides education process more systematic and attractive. Digital learning can be considered as one of the prominent application that implemented under cloud computing environment. Cloud computing is a type of network resources that provides on-demands services where the users can access applications inside it at any location and no time border. It also promises for minimizing the cost of maintenance and provides a flexible of data storage capacity. The aim of this article is to review the definition and types of cloud computing for improving digital learning management as required in the 21st century education. The analysis of digital learning context focused on primary school in Malaysia. Types of cloud applications and services in education sector are also discussed in the article. Finally, gap analysis and direction of cloud computing in education sector for facing the 21st century challenges are suggested.

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Deep learning for EEG-Based preference classification

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AIP Conference Proceedings 2017年第1期1891卷

作者： Jason Teo Chew Lin Hou James Mountstephens 1Faculty of Computing and Informatics Universiti Malaysia Sabah Jalan UMS 88400 Kota Kinabalu Sabah Malaysia

Electroencephalogram (EEG)-based emotion classification is rapidly becoming one of the most intensely studied areas of brain-computer interfacing (BCI). The ability to passively identify yet accurately correlate brainwaves with our immediate emotions opens up truly meaningful and previously unattainable human-computer interactions such as in forensic neuroscience, rehabilitative medicine, affective entertainment and neuro-marketing. One particularly useful yet rarely explored areas of EEG-based emotion classification is preference recognition [1], which is simply the detection of like versus dislike. Within the limited investigations into preference classification, all reported studies were based on musically-induced stimuli except for a single study which used 2D images. The main objective of this study is to apply deep learning, which has been shown to produce state-of-the-art results in diverse hard problems such as in computer vision, natural language processing and audio recognition, to 3D object preference classification over a larger group of test subjects. A cohort of 16 users was shown 60 bracelet-like objects as rotating visual stimuli on a computer display while their preferences and EEGs were recorded. After training a variety of machine learning approaches which included deep neural networks, we then attempted to classify the users’ preferences for the 3D visual stimuli based on their EEGs. Here, we show that that deep learning outperforms a variety of other machine learning classifiers for this EEG-based preference classification task particularly in a highly challenging dataset with large inter- and intra-subject variability.

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Time dependent second grade fluid between two vertical oscillating plates with heat transfer effect

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AIP Conference Proceedings 2017年第1期1823卷

作者： Muhammad Ismail Mohmand Mustafa Bin Mamat Qayyum Shah 1Faculty of Informatics and Computing Universiti Sultan Zainal Abidin UniSZA Malaysia 2Faculty of Informatics and Computing Universiti Sultan Zainal Abidin UniSZA Malaysia 3Faculty of Informatics and Computing Universiti Sultan Zainal Abidin UniSZA Malaysia

In this paper, the flow of unsteady second grade fluid problem is examined between two vertical and oscillating plates. The parallel plates are oscillating. The heat transfer effect is taken on the plates. Optimal Homotopy Asymptotic Method (OHAM) is used for solution. Analytical solution is obtained. Effect of several physical parameters are studied as well as discussed in details.

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An integration of minimum local feature representation methods to recognize large variation of foods

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AIP Conference Proceedings 2017年第1期1891卷

作者： Mohd Norhisham bin Razali Noridayu Manshor Alfian Abdul Halin Norwati Mustapha Razali Yaakob 1Faculty of Computer Science and Information Technology Universiti Putra Malaysia 43300 Serdang Selangor Malaysia 2Faculty of Computing and Informatics Universiti Malaysia Sabah 88400 Kota Kinabalu Sabah Malaysia

Local invariant features have shown to be successful in describing object appearances for image classification tasks. Such features are robust towards occlusion and clutter and are also invariant against scale and orientation changes. This makes them suitable for classification tasks with little inter-class similarity and large intra-class difference. In this paper, we propose an integrated representation of the Speeded-Up Robust Feature (SURF) and Scale Invariant Feature Transform (SIFT) descriptors, using late fusion strategy. The proposed representation is used for food recognition from a dataset of food images with complex appearance variations. The Bag of Features (BOF) approach is employed to enhance the discriminative ability of the local features. Firstly, the individual local features are extracted to construct two kinds of visual vocabularies, representing SURF and SIFT. The visual vocabularies are then concatenated and fed into a Linear Support Vector Machine (SVM) to classify the respective food categories. Experimental results demonstrate impressive overall recognition at 82.38% classification accuracy based on the challenging UEC-Food100 dataset.

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A three-term conjugate gradient method under the strong-Wolfe line search

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AIP Conference Proceedings 2017年第1期1870卷

作者： Wan Khadijah Mohd Rivaie Mustafa Mamat 1Faculty of Informatics and Computing Universiti Sultan Zainal Abidin (UniSZA) Terengganu Malaysia 2Department of Computer Sciences and Mathematics Universiti Teknologi MARA (UiTM) Terengganu Malaysia

Recently, numerous studies have been concerned in conjugate gradient methods for solving large-scale unconstrained optimization method. In this paper, a three-term conjugate gradient method is proposed for unconstrained optimization which always satisfies sufficient descent direction and namely as Three-Term Rivaie-Mustafa-Ismail-Leong (TTRMIL). Under standard conditions, TTRMIL method is proved to be globally convergent under strong-Wolfe line search. Finally, numerical results are provided for the purpose of comparison.

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Time dependent Oldroyd-B liquid film flow over an oscillating and porous vertical plate with the effect of thermal radiation

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AIP Conference Proceedings 2017年第1期1846卷

作者： Muhammad Ismail Mohmand Qayyum Shah Mustafa Bin Mamat Zahir Shah Abdul Samad Khan 1Faculty of Informatics and Computing Universiti Sultan Zainal Abidin UniSZA Malaysia 2Faculty of Informatics and Computing Universiti Sultan Zainal Abidin UniSZA Malaysia 3Faculty of Informatics and Computing Universiti Sultan Zainal Abidin UniSZA Malaysia 4Department of Mathematics Abdul Wali Khan University Mardan Pakistan 5Department of Mathematics Bacha Khan University Charsadda Pakistan

In the current research work, a liquid film flow of Oldroyd-B fluid with internal heat in vertical porous medium in an oscillating belt is being examined in unsteady state. For this phenomenon, by using basic equations of fluid motion we get a mathematical model. The obtained model problem is solved for the exact analytic solutions by Optimal Homotopy Asymptotic Method (OHAM). Velocity, temperature fields with the mass flow-rate and heat transfer rate of the fluid flow at the belt are also calculated. The effect of pertinent parameters like κ1 relaxation time parameter, κ2 retardation time parameter, Λ porosity parameter, R radiation parameter and Pr temperature fields are also deliberated and then are presented graphically.

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Travelling-wave similarity solution for gravity-driven rivulet of a Newtonian fluid with strong surface-tension effect

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AIP Conference Proceedings 2017年第1期1870卷

作者： Siti Sabariah Abas Yazariah Mohd Yatim 1Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Tembila Campus 22200 Besut Terengganu Malaysia 2School of Mathematical Sciences Universiti Sains Malaysia 11800 USM Pulau Pinang Malaysia

Rivulet flows occur in a wide range of practical situations ranging from industrial situation such as coating processes to geophysical situation such as lava flow, and extensive efforts have been made to investigate it. In this study, a lubrication approximation is used to investigate the gravity-driven draining of unsteady, slender, symmetric rivulet of Newtonian fluid down an inclined plane, with strong surface-tension effect. A travelling-wave similarity solution is obtained representing a quartic transverse profile rivulet and that it has a uniform thickness at any position x and time t which widen or narrow according to (x − ct)1/4, where c is a velocity of a rivulet and thicken or thin according to a free parameter F0.

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A new family of Polak-Ribiere-Polyak conjugate gradient method with the strong-Wolfe line search

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AIP Conference Proceedings 2017年第1期1870卷

作者： Nur Hamizah Abdul Ghani Mustafa Mamat Mohd Rivaie 1Faculty of Informatics and Computing Universiti Sultan Zainal Abidin (UniSZA) 21300 Kuala Terengganu Terengganu Malaysia 2Department of Computer Science and Mathematics Universiti Teknologi Mara (UiTM) 21080 Kuala Terengganu Terengganu Malaysia

Conjugate gradient (CG) method is an important technique in unconstrained optimization, due to its effectiveness and low memory requirements. The focus of this paper is to introduce a new CG method for solving large scale unconstrained optimization. Theoretical proofs show that the new method fulfills sufficient descent condition if strong Wolfe-Powell inexact line search is used. Besides, computational results show that our proposed method outperforms to other existing CG methods.

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A new classical conjugate gradient coefficient with exact line search

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AIP Conference Proceedings 2016年第1期1739卷

作者： Norrlaili Shapiee Mohd. Rivaie Mustafa Mamat 1Faculty of Informatics and Computing Universiti Sultan Zainal Abidin (UniSZA) Terengganu Malaysia 2Department of Computer Sciences and Mathematics Universiti Teknologi MARA (UiTM) Terengganu Malaysia

In this paper, we proposed a new classical conjugate gradient method. The global convergence is established using exact line search. Numerical results are presented based on number of iterations and CPU time. This numerical result shows that our method is performs better than classical CG method for a given standard test problems.

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Improved Quasi-Newton method via PSB update for solving systems of nonlinear equations

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AIP Conference Proceedings 2016年第1期1782卷

作者： Mustafa Mamat M. K. Dauda M. Y. Waziri Fadhilah Ahmad Fatma Susilawati Mohamad 1Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Gong Badak Terengganu Malaysia 2Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Gong Badak Terengganu Malaysia 3Department of Mathematical Science Bayero University Kano Nigeria 4Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Gong Badak Terengganu Malaysia 5Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Gong Badak Terengganu Malaysia

The Newton method has some shortcomings which includes computation of the Jacobian matrix which may be difficult or even impossible to compute and solving the Newton system in every iteration. Also, the common setback with some quasi-Newton methods is that they need to compute and store an n × n matrix at each iteration, this is computationally costly for large scale problems. To overcome such drawbacks, an improved Method for solving systems of nonlinear equations via PSB (Powell-Symmetric-Broyden) update is proposed. In the proposed method, the approximate Jacobian inverse Hk of PSB is updated and its efficiency has improved thereby require low memory storage, hence the main aim of this paper. The preliminary numerical results show that the proposed method is practically efficient when applied on some benchmark problems.

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