Sunday, June 16, 2019

 
These articles have been peer-reviewed and accepted for publication in JICT, but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the JICT standard. Additionally, titles, authors, abstracts and keywords may change before publication.
 

 
FORMANT CHARACTERISTICS OF MALAY VOWELS OF PERLIS, KELANTAN AND TERENGGANU 
Nursuriati Jamil, Izzad Ramli & Norizah Ardi
 
Abstract
The pronunciation of Malay vowels is taught by referring to the International Phonetic Association transcription sound chart. The documentation of pronunciation is done by describing and distinguishing the vowel’s sound through impressionistic. In the last five years, several initiatives were done to quantify the standard Malay vowels pronunciation using formant frequencies. However, only one work was found to measure Malay vowels using formant frequencies for Kedah district. Some of the findings, however, were contradicting as the spoken vowels are extracted from a read speech which may not represent the natural dialect. Therefore, this paper investigated the Malay vowels variations of three districts (Perlis, Kelantan, and Terengganu) using spontaneous speeches acquired in natural settings. Eight (8) Malay vowels were collected from local males and females residing in Perlis, Kelantan, and Terengganu. Four formant frequencies were measured from the vowels extracted from the spontaneous speeches of the locals. Further analysis of the first and second formant show that the Malay vowels of Terengganu and Kelantan has a broader range of formants and are located in approximately the same position in the mouth.However, the vowels of the Perlis dialects are closely positioned in a narrower mouth space. A Malay vowel diagram is also plotted that can be used for future reference in research and educational tool for language learning. Finally, Kelantan and Terengganu dialects are shown to be very similar based on the first and second formants.
 
Keywords: Malay dialect, vowel diagram, formant frequencies, vowel recognition.

 
A SYSTEMATIC MAPPING STUDY ON CLOUD-BASED MOBILE APPLICATION TESTING
Badamasi Imam Ya’u, Norsaremah Salleh, Azlin Nordin, Ali A. Alwan, Norbik Bashah Idris & Hafiza Abas
 
Abstract
Mobile applications and devices play significant roles in boosting a global business, which encompasses various domain such as health, education, bank, transport, to mention a few. They become indispensable tools for everyday activities, thus these applications are developed in a very large quantity with a diverse features and platforms. This brings about new set of difficulties and security challenges. To address this problem and ensure quality and security of these applications, a rigorous and systematic testing especially, using a cloud-based environment is required. Using a systematic mapping study (SMS) method is significant in reporting empirical studies that address issues cloud-based mobile application testing. This paper presents a total of 23 primary studies that investigate a cloud based mobile application testing and the effect of a Testing as a Service (TaaS). Majority of these studies (56.5%) contribute to literature with a number of framework proposals. We discover that most of the studies (60.9%) focus on Android applications and usually supporting one type of mobile app testing. In addition, despite a plethora of services offered by TaaS, majority of the studies (52.2%) fail to focus on TaaS. The results of this SMS identify a clear gap: 1) lack of general and scalable approaches to support diverse types of mobile apps testing for applications using various platforms and 2) lack of evaluation methods such as case study to validate the proposed approaches.
 
Keywords: Cloud-based mobile application testing, systematic mapping, testing-as-a-service.

 
A FUZZY RULE-BASED EXPERT SYSTEM FOR ASTHMA SEVERITY IDENTIFICATION IN EMERGENCY DEPARTMENT
Nurul Atikah Mohd Sharif, Norazura Ahmad, Nazihah Ahmad, Wan Laailatul Hanim Mat Desa, Khaled Mohamed Helmy,  Wei Chern Ang & Ida Zaliza Zainol Abidin
 
Abstract
An emergency department (ED) of a hospital is a critical unit that deals with time-sensitive and life-threatening cases. Rapid treatment and accuracy in diagnosis are considered as main characteristics for excellent operational processes in EDs. However, in reality, long waiting time and uncertainty of diagnosis may affect the quality of ED services. This situation could be improved by utilising computing technologies to assist medical professionals in making fast and accurate decisions. This article is devoted to the issues of under-treatment and uncertainty condition of acute asthma cases in ED. A novel approach known as the fuzzy logic principle is used to determine the severity of acute asthma. The fuzzy set theory is embedded into the expert system (ES) to assess the severity of asthma among patients in ED, which known as Fuzzy Rule-based Expert System for Asthma Severity (FRESAS) determination. The proposed fuzzy methodology effectively deals with the fuzziness of the patient information data and subjective judgment of medical practitioners’ level on eight criteria assessed in severity determination. Knowledge acquisition and representation, fuzzification, fuzzy inference engine, and defuzzification are the processes that pass through the FRESAS development which involves expert advice. System evaluation is performed using dataset extracted from ED’s clerking note from one of the hospitals in Northern Peninsular Malaysia. System evaluation demonstrated that the proposed system could work efficiently in determining the severity of acute asthma and offers extension research for other types of disease in ED as well as improves other hybridisation approaches.
 
Keywords: Emergency department, acute asthma, fuzzy rule-based.

 
VARIATION ON THE NUMBER OF HIDDEN NODES THROUGH MULTILAYER PERCEPTRON NETWORKS TO PREDICT THE CYCLE TIME
Ahmad Afif Ahmarofi, Razamin Ramli, Norhaslinda Zainal Abidin, Jastini Mohd Jamil & Izwan Nizal Shaharanee
 
Abstract
Multilayer perceptron network (MLP) has a better prediction performance compared to other networks since the structure of MLP is suitable for training process in solving prediction problem. However, to the best of our knowledge, there is no rule of thumb in determining the number of hidden nodes within the MLP structure. Researchers normally test with various numbers of hidden nodes to obtain the lowest square error value for optimal prediction result since none of the approaches is claimed as the best practice. Thus, the aim of this paper is to determine the best MLP network by varying the number of hidden nodes of the developed network in predicting the cycle time for producing a new audio product at a production line. The networks are trained and validated through 100 sets of production lots from a selected audio manufacturer. As a result, the 3-2-1 MLP network is the best network based on the lowest square error value compared to the 3-1-1 and 3-3-1 networks. Consequently, the 3-2-1 predicted the best cycle time of 5 seconds to produce a new audio product. Hence, the prediction result can guide production planners to manage the assembly process at the production line smoothly.
 
Keywords: Artificial neural networks,multilayer perceptron, hidden node, cycle time, production line. 

 
BAYESIAN NETWORK OF TRAFFIC ACCIDENTS IN MALAYSIA
Zamira Hasanah Zamzuri, Akmalia Shabadin & Siti Zaharah Ishak
 
Abstract
Exploring the cause and effect of hazardous events such as traffic accident is vital to the society. Statistical analyses have been a great help in terms of understanding and making inference on the cause-effect analysis and also predicting the occurrence of the accident in the future. One of the issues that could not be handled by the conventional way of statistical modelling is the interrelationships exist between the variables in the data set. With the advent of technology and the wide application of machine learning algorithm, this goal can be achieved through the Bayesian network analysis, in which it is a directed acyclic probabilistic graphical model. By using Hill Climb (HC) and Tabu algorithms, the structure of the data was learnt and their relationship is estimated through the conditional probability based on the Bayes’ theorem. We found that that weather does impact on the accident occurred through the lighting condition and the traffic system. It is also learnt that fatality accidents have a higher likelihood to occur in head-on, turn over and out of control accidents. The use of Bayesian network allows for the probability queries which is very important estimates needed as we want to know what is the risk that we face given the information that we have in hand.
 
Keywords: Bayesian network, HC algorithm, Tabu algorithm, traffic accidents.

 
CONTEXT ONTOLOGY IN MOBILE APPLICATIONS
Farhanah Atiqah Norki, Radziah Mohamad & Noraini Ibrahim
 
Abstract
Mobile applications are expected to receive context input such as location, speech, and network from different context providers. Since context can be considered as knowledge, a formal method is needed to capture this knowledge. There is less work on ontology model that could be reused to model a new context ontology for Android mobile application. Therefore, this study proposed an ontology specifically for Android mobile application, COCCC, to formalize context knowledge present within it. METHONTOLOGY method was used to create COCCC ontology as it offers intermediate representation in the form of concepts. The concepts from the context ontology were extracted from various resources, sorted and categorized based on the types and functions for standardization purposes. Survey was given to five domain experts for evaluation of COCCC ontology in terms of its usability. Data from these experts were analysed and the results have confirmed that the proposed context ontology is usable to Android mobile application developers.
 
Keywords: Context ontology, knowledge representation, mobile application, ontology.

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