bluuebunny/crossref_metadata_2025 huggingface dataset:
Silhouette index for determining optimal k-means clustering on images in different color models
Authors: Rasid Mamat Abd , Susilawati Mohamed Fatma , Afendee Mohamed Mohamad , Mohd Rawi Norkhairani , Isa Awang Mohd
Published: May 2018

Clustering process is an essential part of the image processing. Its aim to group the data according to having the same attributes or similarities of the images. Consequently, determining the number of the optimum clusters or the best (well-clustered) for the image in different color models is very crucial. This is because the cluster validation is fundamental in the process of clustering and it reflects the split between clusters. In this study, the k-means algorithm was used on three colors model: CIE Lab, RGB and HSV and the clustering process made up to k clusters. Next, the Silhouette Index (SI) is used to the cluster validation process, and this value is range between 0 to 1 and the greater value of SI illustrates the best of cluster separation. The results from several experiments show that the best cluster separation occurs when k=2 and the value of average SI is inversely proportional to the number of k cluster for all color model. The result shows in HSV color model the average SI decreased 14.11% from k = 2 to k = 8, 11.1% in HSV color model and 16.7% in CIE Lab color model. Comparisons are also made for the three color models and generally the best cluster separation is found within HSV, followed by the RGB and CIE Lab color models.
Onmyouji: Gesture-based virtual reality game
Authors: Weng Chou Ka , Quek Albert , Hong Yew Hui
Published: May 2018

With the emergence of Virtual Reality (VR), user’s senses are taken into consideration in achieving a natural and intuitive human-computer interaction (HCI) as well for a more effective data interaction. The conventional keyboard and mouse interface and control methods of VR no longer sufficiently handles the richness of the information and facilitate intuitive user interaction in the virtual environment. There are alternative controllers such as motion controller used in the game, but this burden users for having them to hold a controller during gameplay. Hand gestures are a powerful tool for communication among humans. Hand gestures recognition has the potential to achieve the naturalness and intuitiveness for HCI. Here, we have proposed a VR game implemented a set of simple gestures with Leap Motion controller named Onmyouji. Onmyouji emphasizes on the VR experience provided with utilizing hand gestures to move and cast attack as the player control. A set of gestures are designed to fulfill the naturalness and intuitiveness of controls in the game. By qualitative user evaluation on a target interest group, most of the participants evaluated positively on the intuitive gestures and gameplay. For the overall game experience, all participants rated 4 and 5 out of 5 scores.
Filling Sharp Features on Corner of Triangular Mesh by using Enhanced Advancing Front Mesh (EAFM) method
Authors: Awang Noorehan , Wirza Rahmat Rahmita , Suhaiza Sulaiman Puteri , Jaafar Azmi , Seng Beng Ng
Published: May 2018

Repairing an incomplete polygon mesh constitutes a primary difficulty in 3D model construction, especially in the computer graphics area. The objective of hole-filling methods is to keep surfaces smoothly and continually filled at hole boundaries while conforming with the shapes. The Advancing Front Mesh (AFM) method was normally used to fill simple holes. However, there has not been much implementation of AFM in handling sharp features. In this paper, we use an  AFM method to fill a holes on sharp features. The Enhanced Advancing Front Mesh (EAFM) method was introduced when there was a conflict during triangle creation. The results of the study show that the presented method can effectively improve the AFM method, while preserving the geometric features and details of the original mesh.
Development of Spatial Distribution Model using GIS to Identify Social Support Index Among Drug-Abuse Inmates
Authors: Mohamad Mahadzirah , Khairul Amri Kamarudin Mohd , Juahir Hafizan , Azman Mat Ali Nor , Karim Fazida , Badarilah Nurhikmah , Muhammad Norhilmi , Syaakir Mohd Ridzuan Muhammad
Published: May 2018

This study was to identify the spatial distribution of Social Support Index (SSI) among drug-abuse inmates throughout Peninsular Malaysia. Factor Analysis (FA) and Discriminant Analysis (DA) were applied to analyses the level of social support (SS) among drug-abuse inmates and develop the spatial model using Geographic Information System (GIS). Five significant index categories were generated from FA: excellent, good, moderate, low and poor Quality of Life Index (QoLi) and the nine of SS variables are expected to be derived from family, friends and other social factor. DA showed each category differed from others in terms of different compositions, stepwise backward and forward modes gave 99.75% correct classification. GIS analysis show the distribution of SSI categorized on family and friends factor were moderately for where the prisoners came. Besides that, Perlis classified as low-level index and Melaka as high-level index of other social factor. The distribution model of SSI in moderately-level showed Jelebu, Sungai Petani, Pengkalan Chepa and Simpang Renggang as the better SS factor to quality of life compared to the Penor, Pahang. The procedures of FA, DA and GIS were used in this study proved the source apportionment of SS and QoLi among drug-abuse inmates in Peninsular Malaysian prisons.
Determination of Filtration and Purification System for Flood Water Filter
Authors: Aini Kamarudin Nurul , Khairul Amri Kamarudin Mohd , Umar Rosalan , Rahman Hassan Abdul , Lananan Fathurrahman , . Sunardi
Published: May 2018

Water is one of the basic needs which essential to life but cannot take it easy, it becomes more concern when a flood, there is plenty of dirty water than clean water, and the sources of the water are not approved to use. There are many kinds of waterborne pathogens which can donate diseases also death if not treating the water well before use. The treatment can be utilized based on the size of the microorganism. By identifying the size of the smallest bacteria will make easier to find the filtration based on the size of filter pores and other processes to ensure all the bacteria is removed and the water safe to use. Even there are many kinds of bacteria or microorganisms in the contaminated water, but the pathogens need to deal. The water will become clean and safe to use when the colour is clear and there is any pathogenic microorganism in there. This study is to ensure water is clean from pathogen after the flood water is filtered by know for sure the organism’s size and to overcome the lack of clean water problem during the flood and others purpose.
Spatial Model of Sky Brightness Magnitude in KUSZA Observatory, UniSZA
Authors: Umar Roslan , Jannah Awang Wardatul , Nadhirah Berzanji Siti , Farhana Abd Majed Nur , Khairul Amri Kamarudin Mohd , Garba Abdullahi Musa
Published: May 2018

Light pollution is the by-product of anthropogenic activities result from the increases in advanced economic and urbanization. Light pollution limits the ability to view the night sky by astronomers, on biodiversity, and ecosystems. This technology nowadays has led us to increase the convenient method to observe the brightness of night sky to determine how much the night sky polluted by artificial light. The study used SQM device and monitored the sky brightness of the KUSZA Observatory in Merang, Setiu, Terengganu, Malaysia. The results obtained were used to compare with the results obtained by simulation data generated from Earth Observation Group (EOG) of National Oceanic and Atmospheric Administration (NOAA), National Geophysical Data Center. It is the first world atlas of the artificial night sky brightness using GIS Interpolation tools. The result showed that the Kusza Observatory Merang is still appropriate to be the place of observation of celestial objects to either optical or radio astronomers. Hence, we recommended that through the data obtained from Defense Meteorological Satellite Program (DMSP) satellites, the value of sky brightness from all over the world can be used to make further analysis and to increase the precision of data recorded through observations. This study provides a clear view mapping of the accessing the sky condition using Geographic Information System (GIS) analysis in the study area.
Study on Dimensional Stability of Particleboard Made Using Glutardialdehyde Modified Corn Starch as the Binder at Various Relative Humidity
Authors: Hazim Mohamad Amini Mohd , Hashim Rokiah , Syuhada Sulaiman Nurul , Mohamed Mazlan , Najmi Masri Mohmad , Ahmad Sobri Sharizal , Izaida Ibrahim Nor
Published: May 2018

The objective of the study was to evaluate the dimensional stability of experimental particleboard panels made from rubberwood (Hevea brasiliensis) using modified starch as binder. Panels were manufactured using 15% corn starch modified with glutardialdehyde and 13% modified starch with 2% Urea Formaldehyde resin as improvement. The particleboards were tested for their dimensional stability towards moisture. Results found that the 2% replacement of modified starch with urea formaldehyde resin showed a little increased in dimensional stability compared to using glutardialdehyde modified corn starch only as the binder. Therefore, this study indicated that combination of modified corn starch and urea formaldehyde resin can have a potential to be used as an improved binder to produce particleboard panels with accepted properties.
Fungal Resistance of Particleboard Made Using Glutardialdehyde Modified Corn Starch as the Binder with the Aid of Urea Formaldehyde Resin
Authors: Hazim Mohamad Amini Mohd , Hashim Rokiah , Syuhada  Sulaiman Nurul , Sulaiman Othman , Bashree Abu Bakar Mohamed , Mohamed Mazlan , Rahman Rozyanty
Published: May 2018

Particleboard is a popular wood composite made using mixtures of wood particles and resin, binder or adhesives, pressed at high temperature to cured. Despite its popularity, formaldehyde-based adhesives used in the formulations lead to cancerous effect as the formaldehyde fumes released from the unreacted chemicals travel into human lungs. Therefore this study tries to reduce the utilization of formaldehyde-based resin by replacement of a significant portion of the binder with glutardialdehyde modified corn starch as the binder. However, this practice could lower the durability of the particleboards against biological attack. Therefore, this study evaluates the fungal resistance of the particleboard panels. Panels were manufactured using 83:15:2 ratio of wood, corn starch-modified with glutardialdehyde and formaldehyde resin, respectively, as an improvement. Four types of wood-degrading fungal were chosen including Trametes versicolor, Formitopsis palustris, Schizophyllum commune and Pycnoporus sangineus. Some of the particleboard showed a little increased in fungal resistance when 2% urea formaldehyde was added, compared to using glutardialdehyde modified corn starch and starch only as the binder. Nine out of twelve samples showed a decrement in fungal degradation by using glutardialdehyde modified starch as the binder. Meanwhile, 6 out of 12 samples showed higher fungal resistance after additional of 2% urea formaldehyde in the binder formulation. Based on the results, combination of modified corn starch and urea formaldehyde resin could have a potential to be used in particleboard making without reducing the initial resistance towards fungal attack.
Integrated Interface Development Environment using STEP Universal Data Structure
Authors: M.S. Tg Sulaiman T , B. Mohamed S , Minhat M , S. Mohamed A , R. Mohamed A
Published: May 2018

Nowadays modern manufacturing demands advanced computer controller, having higher input language and less proprietary vendor dependencies. STEP stands for Standard for the Exchange of Product model data is the next generation of data model between CAD/CAM and CNC system. STEP is still under research and development all around the world. This paper describes the design, development and testing of an integrated Interface development environment for STEP file using Universal Data Structure, which aims to provide support for machining operation.  The system also aims to provide function of reading and extracting the relevant information associated with the machining data and to write the G-Code file. The sample of machined block is designed from 3D CAD modeler which consisted of features need to be machined from a blank workpiece and saved in the STEP file format. The validation process will be done using the simulation in the Mach3 software.
Innovation and Skills Workers of Mechanical Engineer to Design Smart Flush
Authors: Omar Ali Saifuddin bin Wan Ismail W , Binti Hamzah Noraini , Bin Jusoh Khalid
Published: May 2018

Smart Flush is an innovative product in mechanical engineering. All the skilled workers need to      improve the quality of product that would be manufacture. The three objectives of this study are as  follows: (i) to design automatic water level control based on electrical conductivity of the water; (ii) to improve the supply of water into the water tank as well as avoiding any accessing water; and (iii) to provide easy installation and maintenance. 5W + 1H concept are used to solve the problem. The     existing water level for toilet flushing system employs mechanical method, which is commonly expose to mechanical failure. This research introduces the notion of water level controlling within the context of electrical conductivity of the water. System design integrates the electrical and electronic based   water level sensing and couple with solenoids shut off valve in a wired environment. The system equipment is lower power consumption, equipment only work when the water level changes, usually is in a waiting state. Smart Flush approach would help in reducing water overflow and low water pressure in the piping system. Maintaining water level inside the toilet pump system is an essential aspect in order to avoid waste of water due to overflow.
Performance Comparison of Neural Network Training Algorithms for Modeling Customer Churn Prediction
Authors: Khalid Awang Mohd , Ridwan Ismail Mohammad , Makhtar Mokhairi , Nordin A Rahman M , Rasid Mamat Abd
Published: May 2018

Predicting customer churn has become the priority of every telecommunication service provider as the market  is becoming more saturated and competitive. This paper presents a comparison of neural network learning algorithms for customer churn prediction.  The data set used to train and test the neural network algorithms was provided by one of the leading telecommunication company in Malaysia. The Multilayer Perceptron (MLP) networks are trained using nine (9) types of learning algorithms, which are Levenberg Marquardt backpropagation (trainlm), BFGS Quasi-Newton backpropagation (trainbfg), Conjugate Gradient backpropagation with Fletcher-Reeves Updates (traincgf), Conjugate Gradient backpropagation with Polak-Ribiere Updates (traincgp), Conjugate Gradient backpropagation with Powell-Beale Restarts (traincgb), Scaled Conjugate Gradient backpropagation (trainscg), One Step Secant backpropagation (trainoss), Bayesian Regularization backpropagation (trainbr), and Resilient backpropagation (trainrp). The performance of the Neural Network is measured based on the prediction accuracy of the learning and testing phases. LM learning algorithm is found to be the optimum model of a neural network model consisting of fourteen input units, one hidden node and one output node. The best result of the experiment indicated that this model is able to produce the performance accuracy of 94.82%.
Travelling-Wave Similarity Solution for Gravity-Driven Rivulet of a Non-Newtonian Fluid
Authors: Sabariah Abas Siti , Mohd Yatim Yazariah , . .
Published: May 2018

Unsteady travelling-wave similarity solution describing the flow of a slender symmetric rivulet of non-Newtonian power-law fluid down an inclined plane is obtained. The flow is driven by gravity with strong surface-tension effect. The solution predicts that at any time  and position , the rivulet widens or narrows according to , where  is velocity of a rivulet, and the film thickens or thins according to a free parameter , independent of power-law index . The rivulet also has a quartic transverse profile which always has a global maximum at its symmetrical axis.
A hybrid model of ordinal ranking-based clustering using G+Rank K-Means
Authors: Suhailan S , Abdul Samad S , Burhanuddin M A , Makhtar M
Published: May 2018

K-Means is a clustering technique that maps object features onto multidimensional coordinates and groups them based on location closeness. However, measuring closest distance can be doubtful when ranking representation of ordinal scale objects are not considered. Thus, distribution of objects in a cluster may violate ranking representation. For example, a same-rank object may be grouped into different clusters. To address this issue, an enhanced of K-Means algorithm is proposed to achieve better and meaningful result of ranking-based clustering. It is based on integration of ranking algorithm that sort objects into ranking list which also representing object closeness based on its nearby location. A new additional step in K-Means is proposed in reassigning unaligned K-Means nearest objects using ranking attribute that eventually accelerates the clustering process. AHP ranking algorithm is integrated into K-Means in achieving a ranking-based cluster. This enhancement was evaluated on three ordinal datasets covering 67 Java programs, 92 students’ marks on computer architecture subject and 456 EUFA’s football club coefficient ranking list. The results show that by integrating ranking algorithm in K-Means as proposed in G+Rank K-Means, a rank cluster representation has been successfully achieved. The purity value that represents the correctness against certain group classification has also increased.
A Decision Tree Based Recommender System for Backpackers Accommodations
Authors: Mat Amin Maizan , Yep Ai Lan Jannifer , Makhtar Mokhairi , Rasid Mamat Abd
Published: May 2018

Backpackers often travel for a longer period of time, have their own budgets and requirements on accommodations. The existing systems do not offer personalized recommendation criteria and some proposed inefficient recommender system (RS) for users. Moreover, other than information searching from websites and bloggers, only limited systems were specifically designed for backpackers’ accommodations recommender system. An observation and online survey was conducted to get the information from backpackers regarding their preferences while looking for the accommodations. Fifty (50) respondents were involved in the survey and the data have been analyzed and were classified to build a decision tree. The decision tree model then implemented in the Backpackers’ accommodations Recommender System (BRS). BRS offers a convenient way and solution for backpackers by including decision tree technique in the system to suggest best accommodations suit to backpacker’s preferences.
Image Pre-Processing Algorithm for Ficus deltoidea Jack (Moraceae) Varietal Recognition: A Repeated Perpendicular Line Scanning Approach
Authors: Fakhri Ab. Nasir Ahmad , Nordin A Rahman M , Mat Nashriyah , Rasid Mamat A , Shahrizan Abdul Ghani Ahmad
Published: May 2018

Image pre-processing task is always the first crucial step in plant species recognition system which is responsible to keep precision of feature measurement process. Some of researchers have developed the image pre-processing algorithm to remove petiole section. However, the algorithm was developed using semi-automatic algorithm which is strongly believed to give an inaccurate feature measurement. In this paper, a new technique of automatic petiole section removal is proposed based on repeated perpendicular petiole length scanning concept. Four phases of petiole removal technique involved are: i) binary image enhancement, ii) boundary binary image contour tracing, iii) petiole section scanning, and iv) optimal image size retaining and cropping. The experiments are conducted using six varieties of Ficus deltoidea Jack (Moraceae) leaves. The experimental results indicate that the segmentation results are acceptably good since the digital leaf images have less than 1% of segmentation errors on several ground truth images.
Design and Implementation of Data-at-Rest Encryption for Hadoop
Authors: Hanisah Kamaruzaman Siti , Nor Shuhadah Wan Nik Wan , Afendee Mohamed Mohamad , Mohamad Zarina
Published: May 2018

The manuscript should contain an abstract. The security aspects in Cloud computing is paramount in order to ensure high quality of Service Level Agreement (SLA) to the cloud computing customers. This issue is more apparent when very large amount of data is involved in this emerging computing environment. Hadoop is an open source software framework that supports large data sets storage and processing in a distributed computing environment and well-known implementation of Map Reduce. Map Reduce is one common programming model to process and handle a large amount of data, specifically in big data analysis. Further, Hadoop Distributed File System (HDFS) is a distributed, scalable and portable file system that is written in java for Hadoop framework. However, the main problem is that the data at rest is not secure where intruders can steal or converts the data stored in this computing environment. Therefore, the AES encryption algorithm has been implemented in HDFS to ensure the security of data stored in HDFS. It is shown that the implementation of AES encryption algorithm is capable to secure data stored in HDFS to some extent.
Wireless Network Traffic Analysis and Troubleshooting using Raspberry Pi
Authors: Nur Haziq Mohd Safri Mohamad , Nor Shuhadah Wan Nik Wan , Mohamad Zarina , Mohamad Mumtazimah
Published: May 2018

In the past five decades, computer network has kept up growing with the increases of its complexity. In such situation, the management, monitoring and maintenance of such computer network requires special attention to ensure optimal network access capability is achieved. Wireless network traffic analysis is a process of recording, studying and analyzing packets in wireless network for network performance analysis purposes. In some cases, the quality of network access performance can be very low without knowing the actual problem. Therefore, in this paper, the performance of wireless network traffic is proposed to be analyzed by using a Raspberry Pi which further able to send an alert to network admin to lessen the downtime. Raspberry Pi is a low cost, a small and portable size of a computer board that can be used to plug-in to monitor, keyboard, mouse, pen drive, etc. In this project, a MyTraceroute (MTR) program is installed on the Raspberry Pi to capture the IP of the Access Point (AP) and show packets loss percentage in the network. The results will be saved in the form of text file and sent to network admin by using email. The solution proposed in this paper is able to support solution to a problem on efficient monitoring, managing and maintaining wireless network traffics.
A Student Performance Prediction Model Using Data Mining Technique
Authors: Abdul Razak Rohaila , Omar Mazni , Ahmad Mazida
Published: May 2018

Predicting performance is very significant in the education world nowadays. This paper will describe the process of doing a prediction of student performance by using data mining technique. 257 data sets were taken from the student of semester 6 KPTM that involved four (4) academic programs which are Diploma in Computer System and Networking, Diploma in Information Technology, Diploma in Business Management and Diploma in Accountancy. Knowledge Discovery in Database (KDD) was used as a guide to the process of finding and extracting a knowledge from the dataset. A decision tree and linear regression were used to analyze the dataset based on variables selected. The variables used are Gender, Financing, SPM, GPASem1, GPASem2, GPASem3, GPASem4, GPASem5 and CGPA as a dependent variable. The result from this indicate the significant variable that contribute most to the students’ performance. Based on the analysis, the decision tree shows that GPASem1 has a strong significant to the CGPA final semester of the student and the prediction accuracy is 82%. The linear regression shows that the GPA for each semester has a highly significant with the dependent variable with 96.2% prediction accuracy. By having this information, the management of KPTM can make a plan to ensure that the student can maintain a good result and at the same time to make a strategic plans for those without a good result.
Current Issues in Ciphertext Policy-Attribute Based Scheme for Cloud Computing: A Survey
Authors: Muhammad Norhidayah , Mohamad Zain Jasni , Mohamad Mumtazimah
Published: May 2018

The use of cloud computing has increased exponentially in data resources storage over the past few years. Cloud storage reduces the overall costs of server maintenance, whereby companies only pay for the resources they actually use in the cloud storage. Despite this, security concerns in cloud computing must be a top priority. One of the common encryption methods in cloud security is Attribute Based Encryption (ABE). ABE contains two types, namely, Ciphertext Policy-Attribute Based Encryption (CP-ABE) and Key Policy- Attribute based Encryption (KP-ABE). CP-ABE is better than KP-ABE, especially in reduplication issues and fine-grained access. However, issues in CP_ABE need further improvement. Improvement for the CP-ABE scheme has been growing rapidly since 2010 to date, and five main issues need improvement. This paper reviews the proposed CP-ABE schemes during the past three years.  These schemes focus on solving the five issues identified inherent in the CP-ABE scheme.
Filter-Based Gene Selection Method for Tissues Classification on Large Scale Gene Expression Data
Authors: Kabir Ahmad Farzana , Yusof Yuhanis , Yusoff Nooraini
Published: May 2018

DNA microarray technology is a current innovative tool that has offers a new perspective to look sight into cellular systems and measure a large scale of gene expressions at once. Regardless the novel invention of DNA microarray, most of its results relies on the computational intelligence power, which is used to interpret the large number of data. At present, interpreting large scale of gene expression data remain a thought-provoking issue due to their innate nature of “high dimensional low sample size”. Microarray data mainly involved thousands of genes, n in a very small size sample, p. In addition, this data are often overwhelmed, over fitting and confused by the complexity of data analysis. Due to the nature of this microarray data, it is also common that a large number of genes may not be informative for classification purposes. For such a reason, many studies have used feature selection methods to select significant genes that present the maximum discriminative power between cancerous and normal tissues. In this study, we aim to investigate and compare the effectiveness of these four popular filter gene selection methods namely Signal-to-Noise ratio (SNR), Fisher Criterion (FC), Information Gain (IG) and t-Test in selecting informative genes that can distinguish cancer and normal tissues. Two common classifiers, Support Vector Machine (SVM) and Decision Tree (C4.5) are used to train the selected genes. These gene selection methods are tested on three large scales of gene expression datasets, namely breast cancer dataset, colon dataset, and lung dataset. This study has discovered that IG and SNR are more suitable to be used with SVM while IG fit for C4.5. In a colon dataset, SVM has achieved a specificity of 86% with SNR while and 80% for IG. In contract, C4.5 has obtained a specificity of 78% for IG on the identical dataset. These results indicate that SVM performed slightly better with IG pre-processed data compare to C4.5 on the same dataset.
Challenges of event detection from social media streams
Authors: Zubair Al-Dyani Wafa , Hussein Yahya Adnan , Kabir Ahmad Farzana
Published: May 2018

The area of Event Detection (ED) has attracted researchers' attention over the last few years because of the wide use of social media.  Many studies have examined the problem of ED in various social media platforms, like Twitter, Facebook, YouTube, etc. The ED task for social networks involves many issues, including the processing of huge volumes of data with a high level of noise, data collection and privacy issues, etc.  Hence, this article discusses and presents the wide range of challenges encountered in the ED process from unstructured text data for the most popular Social Networks (SNs), such as Facebook and Twitter. The main goal is to aid the researchers to understand the main challenges and to discuss the future directions in the ED area.
Repairable Queue with Non-exponential Interarrival Time and Variable Breakdown Rates
Authors: Siew Khew Koh , Ching Herny Chin , Yi Fei Tan , Ah Hin Pooi , Yong Kheng Goh , Min Cherng Lee , Tan Ching Ng
Published: May 2018

This paper considers a single server queue in which the service time is exponentially distributed and the service station may breakdown according to a Poisson process with the rates γ and γ' in busy period and idle period respectively. Repair will be performed immediately following a breakdown. The repair time is assumed to have an exponential distribution. Let g(t) and G(t) be the probability density function and the cumulative distribution function of the interarrival time respectively. When t tends to infinity, the rate of g(t)/[1 – G(t)] will tend to a constant. A set of equations will be derived for the probabilities of the queue length and the states of the arrival, repair and service processes when the queue is in a stationary state. By solving these equations, numerical results for the stationary queue length distribution can be obtained.
Filling Simple Holes of Triangular Mesh by using Enhanced Advancing Front Mesh (EAFM) method
Authors: Awang Noorehan , Wirza Rahmat Rahmita , Suhaiza Sulaiman Puteri , Jaafar Azmi , Seng Beng Ng
Published: May 2018

Triangular meshes are extensively used to represent 3D models. Some surfaces cannot be digitised due to various reasons such as inadequacy of the scanner, and this generally occurs for glossy, hollow surfaces and dark-coloured surfaces. This cause triangular meshes to contain holes and it becomes difficult for numerous successive operations such as model prototyping, model rebuilding, and finite element analysis. Hence, it is necessary to fill these holes in a practical manner. In this paper, the Enhanced Advancing Front Mesh (EAFM) method was introduced for recovering missing simple holes in an object. The first step in this research was to extract the feature vertices around a hole on a 3D test data function. Then the Advancing Front Mesh (AFM) method was used to fill the holes. When conflicts occurred during construction of the triangle, the EAFM method was introduced to enhance the method. The results of the study show that the enhanced method is simple, efficient and suitable for dealing with simple hole problems.
Surface deformation on thermocapillary convection in a binary fluid with internal heat generation and temperature dependent viscosity
Authors: Hafizah Zainal Abidin Nurul , Fadzillah Mohd Mokhtar Nor , Zarifah Abdul Hamid Nur , Abdul Majid Zanariah
Published: May 2018

The effects of temperature dependent viscosity and internal heat generation on the onset of steady Bénard-Marangoni convection in a horizontal binary fluid layer heated from below is investigated theoretically. The upper free surface is assumed to be deformable and the lower boundary is considered to be rigid and perfectly insulated to temperature perturbations. The asymptotic solution of the long wavelength is obtained using regular perturbation method with wave number as a perturbation parameter. It is found that the surface deformation of a binary fluid layer enhances the onset of thermocapillary convection while increasing the value of internal heat generation and temperature dependent viscosity will destabilize the binary fluid layer system.
Finite element analysis of heat sink in term of thermal and temperature distribution with different chip power input
Authors: Mohamed Mazlan , Nazri Omar Mohd , Shaiful Ashrul Ishak Mohamad , Rahman Rozyanty , Fahmi Mohd Roslan Muhamad , Nur Hafiz Shaidan Muhammad , Ismael Rizman Zairi
Published: May 2018

This paper presents the simulation of heat sink by using Workbench 18.0 Software to simulate the temperature distribution at different chip power input. 3D model of heat sink is generated using Design Modeler using the same dimension with experimental setup. The study was made for a heat sink mounted on the power source (Chip) under different types of chip powers. The results are presented in terms of temperature distribution when chip powers have been increased from 1 W to 10 W. The temperature distribution is been observed and it was found that the temperature distribution of the heat sink has lower temperature when power source at 1 W and increase significantly when the power source rise up to 10 W. The increase the temperature of heat sink is from 30.8ºC up to 96.2ºC estimated to be 212% the increase of temperature. The simulation also been verify by using different time step use during the simulation and using grid independency test to ensure the simulation result is accurate.
Estimating the unemployment rate using least square and conjugate gradient methods
Authors: Syarafina Mohamed Nur , Mamat Mustafa , Rivaie Mohd , Hamizah Abdul Ghani Nur , Zull Norhaslinda , Syoid Syazni
Published: May 2018

Unemployment rate is one of the major issues among Malaysian citizens. The unemployment rate indicates the percentage of the total workforce who are actively seeking employment and currently unemployed. In this paper, a data of unemployment rate of a state in Malaysia from year 2000 until 2015 is collected. The statistics data is extracted by Labour Force Survey Malaysia (LFSM) which was conducted monthly by using household approach targeted to working ages between 15 to 64 years old. An estimation data for year 2016 can be forecasted by using discrete least square method of numerical analysis and conjugate gradient method in unconstrained optimization. These methods have been chosen based on its simplicity and accuracy. The calculations are based on linear and quadratic models for each the method together with their errors. Results showed that the conjugate gradient method is comparable with the least square method.
Numerical solution of hybrid method for third grade flow due to variable accelerated plate in a rotating frame
Authors: Mahadi Shafaruniza , Abdul Aziz Zainal , Su Hoe Yeak , Salah Faisal , Suraya Md Nasrudin Farah
Published: May 2018

The aim of this article is to obtain numerical solution for incompressible unsteady flow for third grade fluid induced by variable accelerated plate. Numerical solution is obtained by using Hybrid method which combine between finite difference method (FDM) and asymptotic interpolation method. The influence of difference values of material constant parameters on the velocity flow fluid are discussed and shown graphically.
An integration of fuzzy TOPSIS and fuzzy logic for multi-criteria decision making problems
Authors: Fitria Jumarni Ratih , Zamri Nurnadiah
Published: May 2018

Multi-Criteria Decision Making (MCDM) is a decision-making methods, which it is able to find a unique agreement from number of experts by evaluating the uncertain judgment among them. Several fuzzy logic based approaches have been employed in MCDM to handle the linguistic uncertainties and hesitancy. However, there is still a need to handle high level of uncertainties that exists in decision making problems. Thus, the purpose of this paper is to introduce the new concept namely fuzzy TOPSIS and fuzzy logic based MCDM. The proposed concepts aims to handle the high levels of uncertainties which exists due to the varying experts’ judgments and the vagueness of the appraisal. The proposed method utilized fuzzy logic rule-base in determining the alternatives and criteria for decision matrix. Then, in the aggregation phase, the min operator is used to compute the firing strength for each rule. The feasibility and applicability of the proposed methods are illustrated with an example. This new concept is seen be able to handle intangibles and less cumbersome in mathematical calculations.
Rainfall frequency analysis using LH-moments approach: A case of Kemaman Station, Malaysia
Authors: Amani Zakaria Zahrahtul , Moath Ali Suleiman Jarah , Mohamad Mumtazimah
Published: May 2018

Statistical analysis of extreme events is often carried out to obtain the probability distribution of floods data and then predict the occurrence of floods for a significant return period. L-moments approach is known as the most popular approach in frequency analysis. This paper discusses comparison of the L-moments method with higher order moments (LH-moments) method. LH-moment, a generalization of L-moment, which is proposed based on the linear combinations of higher-order statistics has been used to characterize the upper part of distributions and larger events in flood data. It is observed from a comparative study that the results of the analysis of observed data and the diagram based on the K3D-II distribution using LH-moments method is more efficient and reasonable than the L-moments method for estimating data of the upper part of the distribution events.
Development of café web-based system using priority scheduling approach
Authors: Ghazali Fatimah , Ismail Rohana , Hariz Hasni Mohamad
Published: May 2018

Manual food ordering system requires on many employees to handle ordering process. It can be dull and disorganized, and can end up with data irregularity for generating sales report. Moreover, the total time taken for food preparations is longer.  Therefore, the café web based system is developed using priority scheduling algorithm to reduce the duration in ordering process, handling and preparing bulk and concurrent order, and at the same time minimizing the cost of handling employees. The priority scheduling algorithm is based on Control Processing Unit scheduling algorithm where it has a priority to execute tasks in waiting queue. The system is implemented at UniSZA’s café where it will be used by café owner and UniSZA students. This system is developed based on three-tier architecture. The JSP, JavaScript, Java and MySQL have been employed to improve manual ordering management. Initially, the preliminary testing shows that the priority scheduling algorithm has a potential to exchange the traditional ordering system.
Preserving songket through sustainable packaging design
Authors: Ziratul Aqma Norzaman Nor
Published: May 2018

To date, we have never come across any significant study conducted on the Songket packaging design. Most available research findings focus on the motifs and how it is applicable to the contemporary world. Songket packaging design has not evolved parallel to the rapid growth of Songket textile design. From the observation done, today, most of the Songket especially sampin packaging design relies on conventional packaging and other reliable for preserving its quality in long term storage. This research aim to test out the applicability design special for storing sampin.
The impact of customer integration on manufacturing firms sustainable performance
Authors: Ghozali Hassan Mohamad , Abindin Rahimi , Nordin Norani
Published: May 2018

This paper examined the impact of customers’ integration on the three dimensions of sustainability performance (environmental, economic and social) among manufacturing firms. The rationale for undertaking this study is based on the fact that many manufacturing firms, most especially within Malaysia have yet to adopt green supply chain management (GSCM) concept in their business operation, with GSCM recently emerging to ensure that firms comply with regulations for environmental protection. Even the few firms that have implemented this concept do not integrate their customers in the chain, which has led to the creation of an unhealthy culture. Although there are few prior studies that have investigated customers' integration on manufacturing firms’ sustainable performance, they have largely focused on sustainable performance only in terms of environmental dimension, excluding the economic and social dimensions. In this study, quantitative method was used for collecting data from 107 ISO14001 certified manufacturing companies in Malaysia. The statistical package for social science (SPSS) version 20.0 was used to analyze the data. The study findings indicate that customer integration has a positive and significant relationship with sustainable performance. Therefore, the study argues the need for customer integration to ensure a vibrant business organization performance.
The moderating effect of environmental regulation and policy on the relationship between continuous process improvement and organizational performance: An empirical analysis
Authors: Ghozali Hassan Mohamad , Diekola Akanmu Muslim , Yusni Bahaudin Ahmad
Published: May 2018

There have been inconsistencies in the implementation of TQM practices in the Malaysian Food and Beverage Companies and this has led to low sales and less competitive advantage in the industry. This study therefore aimed to investigate the moderating effects of environmental regulation and policy on the relationship between continuous process improvement and organizational performance. A Partial Least Square Structural Equation Modeling (PLS-SEM) was used to estimate the relationship among the above variables in the context of Malaysian Food and Beverage Companies. The results of this study revealed that continuous process improvement has always been a significant predictor of organizational performance by following the regulations and policy related to environment. The results confirmed that environmental regulation and policy moderates the relationship between continuous process improvement and organizational performance. The integration of strategies and practices will help organizations to enhance their performance through implementation of the suggested constructs in this study. The study also supported the premises of the contingency theory and the institutional theory by reaffirming the importance of the supportive environmental regulation and policy for any successful strategic implementation
Solving examination timetabling problem in UniSZA using ant colony optimization
Authors: Firdaus Khair Ahmad , Makhtar Mokhairi , Mazlan Munirah , Afendee Mohamed Mohamad , Nordin Abdul Rahman Mohd
Published: May 2018

At all educational institutions, timetabling is a conventional problem that has always caused numerous difficulties and demands that need to be satisfied. For the examination timetabling problem, those matters can be defined as complexity in scheduling exam events or non-deterministic polynomial hard problems (NP-hard problems). In this study, the latest approach using an ant colony optimisation (ACO) which is the ant system (AS) is presented to find an effective solution for dealing with university exam timetabling problems. This application is believed to be an impressive solution that can be used to eliminate various types of problems for the purpose of optimising the scheduling management system and minimising the number of conflicts. The key of this feature is to simplify and find shorter paths based on index pheromone updating (occurrence matrix). With appropriate algorithm and using efficient techniques, the schedule and assignation allocation can be improved. The approach is applied according to the data set instance that has been gathered. Therefore, performance evaluation and result are used to formulate the proposed approach. This is to determine whether it is reliable and efficient in managing feasible final exam timetables for further use.
Analyzing performance of classifiers for medical datasets
Authors: Rosly Rosaida , Makhtar Mokhairi , Khalid Awang Mohd , Isa Awang Mohd , Nordin Abdul Rahman Mohd
Published: May 2018

This paper analyses the performance of classification models using single classification and combination of ensemble method, which are Breast Cancer Wisconsin and Hepatitis data sets as training datasets. This paper presents a comparison of different classifiers based on a 10-fold cross validation using a data mining tool. In this experiment, various classifiers are implemented including three popular ensemble methods which are boosting, bagging and stacking for the combination. The result shows that for the classification of the Breast Cancer Wisconsin data set, the single classification of Naïve Bayes (NB) and a combination of bagging+NB algorithm displayed the highest accuracy at the same percentage (97.51%) compared to other combinations of ensemble classifiers. For the classification of the Hepatitisdata set, the result showed that the combination of stacking+Multi-Layer Perception (MLP) algorithm achieved a higher accuracy at 86.25%. By using the ensemble classifiers, the result may be improved. In future, a multi-classifier approach will be proposed by introducing a fusion at the classification level between these classifiers to obtain classification with higher accuracies.
Ant colony optimisation for solving university course timetabling problems
Authors: Mazlan Munirah , Makhtar Mokhairi , Firdaus Khair Ahmad Khairi Ahmad , Afendee Mohamed Mohamad , Nordin Abdul Rahman Mohd
Published: May 2018

Course timetabling is one of the most important activities faced by any educational institution. Furthermore, the course timetabling process is time-consuming and tiresome as it needs to be prepared for each regular semester. This paper aims to apply the Ant Colony Optimisation (ACO) method to solve the course timetabling problem. This approach is to optimise the properties of the course requirement and minimise various conflicts for the time slot assignation. This method is based on the life of the ant colony in generating automatic timetabling according to the properties (pheromones) such as time, student, lecturer and room, besides satisfying the constraints. The implementation of this method is to find an effective and better solution for university course timetabling. The result and performance evaluation is used to determine whether it is reliable in providing the feasible timetable.
Usability testing on game interface design using video-based behavior analysis
Authors: Ahmad Ibrahim , Abdullasim Nazreen , Mohd Suaib Norhaida
Published: May 2018

The objective of this study is to quantitatively incorporate user observation into usability evaluation of game interface design. In this study, an experiment was conducted to monitor and record users' behavior using built in video-cam. The experiment was done after the user play “A Garuda” game. All the character movement controlled by user were captured and recorded for comparative analysis. There were about 20 people involved as a subject for this experiment. The data from video recordings were coded with Noldus Observer XT in order to find usage patterns and thus to gather quantitative data for analyzing the GUI effectiveness, efficiency and satisfaction. The result of user's interaction towards the design of game's GUI able to give additional information for the game designer to develop a better responsive game toward its usability. The effect of user's control and emotion that can be seen from user's face will give the information needed to be considered in game development. Previous studies mostly focusing on evaluating the usability with performance measures by only looking at task results. Thus, at the end of this study, a method is proposed by incorporating user observation into usability evaluation of game design interfaces.