Wednesday, November 30, 2022

Noor Huzaimi@Karimah Mohd Noor, Shahrul Azman Mohd Noah & Mohd Juzaiddin Ab Aziz
Mohammad Raquibul Hossain & Mohd Tahir Ismail
Ashwindran Naidu Sanderasagran, Azizuddin Abd Aziz & Daing Mohamad Nafiz Daing Idris
Norliza Katuk, Ku Ruhana Ku-Mahamud, Nur Haryani Zakaria & Ayad Mohammed Jabbar

Shamini Raja Kumaran, Mohd Shahizan Othman & Lizawati Mi Yusuf
School of Computing, Universiti Teknologi Malaysia, Malaysia; shahizan,
Missing values are a huge constraint in microarray technologies towards improving and identifying disease-causing genes. Estimating missing values is an undeniable scenario faced by field experts. The imputation method is an effective way to impute the proper values to proceed with the next process in microarray technology. Missing value imputation methods may increase the classification accuracy. Although these methods might predict the values, classification accuracy rates prove the ability of the methods to identify the missing values in gene expression data. In this study, a novel method, Optimised Hybrid of Fuzzy C-Means and Majority Vote (opt-FCMMV), was proposed to identify the missing values in the data. Using the Majority Vote (MV) and optimisation through Particle Swarm Optimisation (PSO), this study predicted missing values in the data to form more informative and solid data. In order to verify the effectiveness of opt-FCMMV, several experiments were carried out on two publicly available microarray datasets (i.e. Ovary and Lung Cancer) under three missing value mechanisms with five different percentage values in the biomedical domain using Support Vector Machine (SVM) classifier. The experimental results showed that the proposed method functioned efficiently by showcasing the highest accuracy rate as compared to the one without imputations, with imputation by Fuzzy C-Means (FCM), and imputation by Fuzzy C-Means with Majority Vote (FCMMV). For example, the accuracy rates for Ovary Cancer data with 5% missing values were 64.0% for no imputation, 81.8% (FCM), 90.0% (FCMMV), and 93.7% (opt-FCMMV). Such an outcome indicates that the opt-FCMMV may also be applied in different domains in order to prepare the dataset for various data mining tasks.
Keywords: Fuzzy C-means, majority vote, missing values, microarray data, data optimisation.
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Yoanes Bandung & Joshua Tanuraharja
School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Indonesia;
Quality of Service provisioning for real-time multimedia applications is largely determined by a network’s available bandwidth. Until now, there is no standard method for estimating bandwidth on wireless networks. Therefore, in this study, a mathematical model called Modified Passive Available Bandwidth Estimation (MPABE) was developed to estimate the available bandwidth passively on a Distributed Coordination Function (DCF) wireless network on the IEEE 802.11 protocol. The mathematical model developed was a modification of three existing mathematical models, namely Available Bandwidth Estimation (ABE), Cognitive Passive Estimation of Available Bandwidth V2 (cPEAB-V2), and Passive Available Bandwidth Estimation (PABE). The proposed mathematical model gave emphasis on what will be faced to estimate available bandwidth and will help in building strategies to estimate available bandwidth on IEEE 802.11. The developed mathematical model consisted of idle period synchronisation between sender and receiver, the overhead probability occurring in the Medium Access Control (MAC) layer, as well as the successful packet transmission probability. Successful packet transmission was influenced by three variables, namely the packet collision probability caused by a number of neighbouring nodes, the packet collision probability caused by traffic from hidden nodes, and the packet error probability. The proposed mathematical model was tested by comparing it with other relevant mathematical models. The performance of the four mathematical models was compared with the actual bandwidth. Using a series of experiments that have been performed, it was found that the proposed mathematical model is approximately 26% more accurate than ABE, 36% more accurate than cPEABV2, and 32% more accurate than PABE.
Keywords: Available bandwidth estimation, distributed coordination function, IEEE 802.11, hidden nodes.
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1Noor Huzaimi@Karimah Mohd Noor, 2Shahrul Azman Mohd Noah & 2Mohd Juzaiddin Ab Aziz
1Faculty of Computing, Universiti Malaysia Pahang, Malaysia
2Faculty of Information Science & Technology, Universiti Kebangsaan Malaysia, Malaysia; shahrul,
Anaphor candidate determination is an important process in anaphora resolution (AR) systems. There are several types of anaphor, one of which is pronominal anaphor. Pronominal anaphor is an anaphor that involves pronouns. In some of the cases, certain pronouns can be used without referring to any situation or entity in a text, and this phenomenon is known as pleonastic. In the case of the Malay language, it usually occurs for the pronoun nya. The pleonastic that exists in every text causes a severe problem to the anaphora resolution systems. The process to determine the pleonastic nya is not the same as identifying the pleonastic ‘it’ in the English language, where the syntactic pattern could not be used because the structure of nya comes at the end of a word. As an alternative, semantic classes are used to identify the pleonastic itself and the anaphoric nya. In this paper, the automatic semantic tag was used to determine the type of nya, which at the same time could determine nya as an anaphor candidate. The new algorithms and MalayAR architecture were proposed. The results of the F-measure showed the detection of clitic nya as a separate word achieved a perfect 100% result. In comparison, the clitic nya as a pleonastic achieved 88%, clitic nya referring to humans achieved 94%, and clitic nya referring to non-humans achieved 63%. The results showed that the proposed algorithms were acceptable to solve the issue of the clitic nya as pleonastic, human referral as well as non-human referral.
Keywords: Anaphora resolution, natural language processing, Malay anaphora resolution, anaphor candidate determination.
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1Mohammad Raquibul Hossain & 2Mohd Tahir Ismail
1Department of Applied Mathematics, Noakhali Science and Technology University, Bangladesh.
2School of Mathematical Sciences, Universiti Sains Malaysia, Malaysia.;
Forecasting is a challenging task as time series data exhibit many features that cannot be captured by a single model. Therefore, many researchers have proposed various hybrid models in order to accommodate these features to improve forecasting results. This work proposed a hybrid method between Empirical Mode Decomposition (EMD) and Theta methods by considering better forecasting potentiality. Both EMD and Theta are efficient methods in their own ground of tasks for decomposition and forecasting, respectively. Combining them to obtain a better synergic outcome deserves consideration. EMD decomposed the training data from each of the five Financial Times Stock Exchange 100 Index (FTSE 100 Index) companies’ stock price time series data into Intrinsic Mode Functions (IMF) and residue. Then, the Theta method forecasted each decomposed subseries. Considering different forecast horizons, the effectiveness of this hybridisation was evaluated through values of conventional error measures found for test data and forecast data, which were obtained by adding forecast results for all component counterparts extracted from the EMD process. This study found that the proposed method produced better forecast accuracy than the other three classic methods and the hybrid EMD-ARIMA models.
Keywords: Forecasting stock price, empirical mode decomposition, intrinsic mode functions, theta method, time series.
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Ashwindran Naidu Sanderasagran, Azizuddin Abd Aziz & Daing Mohamad Nafiz Daing Idris
Faculty of Mechanical and Automotive Engineering Technology, Universiti Malaysia Pahang, Malaysia.; azizuddin,
The behaviour of fluid flow is a complex paradigm for cognitive interpretation and visualisation. Engineers need to visualise the behaviour mechanics of flow field response in order to enhance the cognitive ability in problem solving. Therefore, mixed reality related technology is the solution for enhanced virtual interactive learning environment. However, there are limited augmented reality platforms on fluid flow interactive learning. Therefore, an interactive education application is proposed for students and engineers to interact and understand the complex flow behaviour pattern subjected to elementary geometry body relative to external flow. This paper presented the technical development of a real-time flow response visualisation augmented reality application for computational fluid dynamics application. It was developed with the assistance of several applications such as Unity, Vuforia, and Android. Particle system modules available in the Unity engine were used to create a two-dimensional flow stream domain. The flow visualisation and interaction were limited to two-dimensional and the numerical fluid continuum response was not analysed. The physical flow response pattern of three simple geometry bodies was validated against ANSYS simulated results based on visual empirical observation. The particle size and number of particles emitted were adjusted in order to emulate the physical representation of fluid flow. Colour contour was set to change according to fluid velocity. Visual validation indicated trivial dissimilarities between FLUENT generated results and flow response exhibited by the proposed augmented reality application.
Keywords: Augmented reality, computational fluid dynamics, image target, Vuforia, Unity engine, particle system.
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1Norliza Katuk, 1Ku Ruhana Ku-Mahamud, 1Nur Haryani Zakaria & 1,2Ayad Mohammed Jabbar
1School of Computing, Universiti Utara Malaysia, Malaysia
2College of Arts and Sciences, Shatt Al-Arab University, Iraq
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Citations have been an acceptable journal performance metric used by many indexing databases for inclusion and discontinuation of journals in their list. Therefore, editorial teams must maintain their journal performance by increasing article citations for continuous content indexing in the databases. With this aim in hand, this study intended to assist the editorial team of the Journal of Information and Communication Technology (JICT) in increasing the performance and impact of the journal. Currently, the journal has suffered from low citation count, which may jeopardise its sustainability. Past studies in library science suggested a positive correlation between keywords and citations. Therefore, keyword and topic analyses could be a solution to address the issue of journal citation. This article described a scientometric analysis of emerging topics in general computer science, the Scopus subject area for which JICT is indexed. This study extracted bibliometric data of the top 10% journals in the subject area to create a dataset of 5,546 articles. The results of the study suggested ten emerging topics in computer science that can be considered by the journal editorial team in selecting articles and a list of highly used keywords in articles published in 2019 and 2020 (as of 15 April 2020). The outcome of this study might be considered by the JICT editorial team and other journals in general computer science that suffer from a similar issue.
Keywords: Scientometrics, scientometric analysis, bibliometrics, citation analysis, research trends.
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