The emergency department (ED) of a hospital is an important unit that deals with time-sensitive and life-threatening medical cases. Rapid treatment and accuracy in diagnosis are considered the main characteristics of excellent operational processes in ED. However, in reality, long waiting time and uncertainty in the diagnosis has affected the quality of ED services. Nonetheless, these problems can be improved by utilising computing technologies that assist medical professionals to make fast and accurate decisions. This paper investigates the issues of under-treatment and uncertainty condition of acute asthma cases in ED. A novel approach, known as the fuzzy logic principle is employed to determine the severity of acute asthma. The fuzzy set theory, known as Fuzzy Rule-based Expert System for Asthma Severity (FRESAS) determination is embedded into the expert system (ES) to assess the severity of asthma among patients in ED. The proposed fuzzy methodology effectively 416 manages the fuzziness of the patient's information data, and determines the 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 tested by the FRESAS development that incorporates expert advice. The system evaluation is performed by using datasets that were extracted from the ED clerking notes from one of the hospitals in Northern Peninsular Malaysia. System evaluation demonstrates that the proposed system performs efficiently in determining the severity of acute asthma. Furthermore, the proposed system offers opportunities for further research on other types of diseases in ED, and improves other hybridisation approaches.

Simulation is one of the most powerful tools available for decision makers to study, analyze and evaluate any design and operation particularly for complex processes and systems. One of the largest application areas for simulation modelling is the manufacturing systems. As such, it is widely applied in manufacturing as a representation of the industrial operation systems allowing the systems to be observed, learnt and tested in a more holistic manner. This paper is based on a preliminary study that demonstrates the application of computer simulation modelling, which is a branch of Operations Research techniques, as a means to identify bottlenecks in order to determine the ideal operating conditions for large scale aircraft composite parts production plant in Malaysia. The model development of the plant under study was built using Arena software.

This paper presents a real case study to determine the optimal tourist route at Langkawi Island. The Langkawi Island was selected as thecase study because normally, tourist travel to this island will drive the rented car as the primary mode of transport. Thus, the aim of this paper is to develop a mathematical model to find an optimal route for tourist to travel to their interesting places around Langkawi Island. In order to solve the problem, Greedy method was applied in this study and MATLAB version 7.8 has been used to get the solution. The result obtained shows that Nearest Greedy Insertion method gives better result compared to the Nearest Greedy method. The minimum value of the route selection gives effect to the cost of travelling. Therefore, from this study, the best route that connect from one interesting place to others place can be suggested to the tourist as guidance. In addition, tourist can save their time and money to visit all interesting places in this study.

No abstract