Noraida Abdul Ghani

A Discrete Event Simulation Model for Evaluating the Performances of an M/G/C/C State Dependent Queuing System

M/G/C/C state dependent queuing networks consider service rates as a function of the number of residing entities (e.g., pedestrians, vehicles, and products). However, modeling such dynamic rates is not supported in modern Discrete Simulation System (DES) software. We designed an approach to cater this limitation and used it to construct the M/G/C/C state-dependent queuing model in Arena software. Using the model, we have evaluated and analyzed the impacts of various arrival rates to the throughput, the blocking probability, the expected service time and the expected number of entities in a complex network topology. Results indicated that there is a range of arrival rates for each network where the simulation results fluctuate drastically across replications and this causes the simulation results and analytical results exhibit discrepancies. Detail results that show how tally the simulation results and the analytical results in both abstract and graphical forms and some scientific justifications for these have been documented and discussed.

Modelling Pedestrian Travel Time and the Design of Facilities: A Queuing Approach

Pedestrian movements are the consequence of several complex and stochastic facts. The modelling of pedestrian movements and the ability to predict the travel time are useful for evaluating the performance of a pedestrian facility. However, only a few studies can be found that incorporate the design of the facility, local pedestrian body dimensions, the delay experienced by the pedestrians, and level of service to the pedestrian movements. In this paper, a queuing based analytical model is developed as a function of relevant determinants and functional factors to predict the travel time on pedestrian facilities. The model can be used to assess the overall serving rate or performance of a facility layout and correlate it to the level of service that is possible to provide the pedestrians. It has also the ability to provide a clear suggestion on the designing and sizing of pedestrian facilities. The model is empirically validated and is found to be a robust tool to understand how well a particular walking facility makes possible comfort and convenient pedestrian movements. The sensitivity analysis is also performed to see the impact of some crucial parameters of the developed model on the performance of pedestrian facilities.

A framework for emergency department capacity planning using system dynamics approach and the theory of constraints philosophies

Patient waiting time and service delivery problems characterize health care services and are more acute in an emergency department (ED).With more patients needing care and fewer resources to care for them, ED that operates at or above capacity is inevitable. This paper is a review of work-in-progress of a study being conducted in a government hospital in Penang, Malaysia.This paper proposes a hybrid of System Dynamics (SD) approach and the Theory of Constraints (TOC) in solving health capacity planning. The potential combination of these methods will be reviewed that is hoped to reveal the synergy between the established methods in addressing the health capacity planning options for the long-term future.

The Video Conferencing Learning Environment in Distance Education: A Study of the Interaction Pattern

This article reports on the study undertaken to elucidate the pattern of interactions in the Video Conferencing Learning Environment (VCLE) used as a course delivery mechanism in distance learning. The study involved transcribing the recorded course delivery sessions conducted in the VCLE for three undergraduate Physics courses. The model of interaction used in this study was based on the Oliver & McLoughlin [5] interaction model consisting of five interactive dimensions, namely, the social, procedural, expository, explanatory and cognitive dimensions across five combinations of dialogue exchanges between teachers, students and the class as a whole. The results revealed that there were high frequencies of two-way exchanges between teachers and students in the expository, explanatory and cognitive interactive dimensions. The implication of these findings in terms of the quality of knowledge construction and high level student understanding of the course contents will be discussed and elaborated.

Managing resource capacity using hybrid simulation

Due to the diversity of patient flows and interdependency of the emergency department (ED) with other units in hospital, the use of analytical models seems not practical for ED modeling. One effective approach to study the dynamic complexity of ED problems is by developing a computer simulation model that could be used to understand the structure and behavior of the system. Attempts to build a holistic model using DES only will be too complex while if only using SD will lack the detailed characteristics of the system. This paper discusses the combination of DES and SD in order to get a better representation of the actual system than using either modeling paradigm solely. The model is developed using AnyLogic software that will enable us to study patient flows and the complex interactions among hospital resources for ED operations. Results from the model show that patients’ length of stay is influenced by laboratories turnaround time, bed occupancy rate and ward admission rate.

Analysis of MCLP, Q-MALP, and MQ-MALP with Travel Time Uncertainty Using Monte Carlo Simulation

This paper compares the application of the Monte Carlo simulation in incorporating travel time uncertainties in ambulance location problem using three models: Maximum Covering Location Problem (MCLP), Queuing Maximum Availability Location Problem (Q-MALP), and Multiserver Queuing Maximum Availability Location Problem (MQ-MALP). A heuristic method is developed to site the ambulances. The models are applied to the 33-node problem representing Austin, Texas, and the 55-node problem. For the 33-node problem, the results show that the servers are less spatially distributed in Q-MALP and MQ-MALP when the uncertainty of server availability is considered using either the independent or dependent travel time. On the other hand, for the 55-node problem, the spatial distribution of the servers obtained by locating a server to the highest hit node location is more dispersed in MCLP and Q-MALP. The implications of the new model for the ambulance services system design are discussed as well as the limitations of the modeling approach.

Bayesian network model of crowd emotion and negative behavior

The effects of overcrowding have become a major concern for event organizers. One aspect of this concern has been the idea that overcrowding can enhance the occurrence of serious incidents during events. As one of the largest Muslim religious gathering attended by pilgrims from all over the world, Hajj has become extremely overcrowded with many incidents being reported. The purpose of this study is to analyze the nature of human emotion and negative behavior resulting from overcrowding during Hajj events from data gathered in Malaysian Hajj Experience Survey in 2013. The sample comprised of 147 Malaysian pilgrims (70 males and 77 females). Utilizing a probabilistic model called Bayesian network, this paper models the dependence structure between different emotions and negative behaviors of pilgrims in the crowd. The model included the following variables of emotion: negative, negative comfortable, positive, positive comfortable and positive spiritual and variables of negative behaviors; aggressive and hazardous acts. The study demonstrated that emotions of negative, negative comfortable, positive spiritual and positive emotion have a direct influence on aggressive behavior whereas emotion of negative comfortable, positive spiritual and positive have a direct influence on hazardous acts behavior. The sensitivity analysis showed that a low level of negative and negative comfortable emotions leads to a lower level of aggressive and hazardous behavior. Findings of the study can be further improved to identify the exact cause and risk factors of crowd-related incidents in preventing crowd disasters during the mass gathering events.

Modeling Emergency Department Using a Hybrid Simulation Approach

Within hospital, emergency department is one of the most important unit that involves complex patient movement flow and detailed operational activities. As an integrated system, the efficiency of emergency department depends on its interaction between inter-departmental units and intra-departmental elements. Over the years, with the rapid development of computer technology, there has been a rising trend of using simulation modeling to improve healthcare operations. Discrete-event simulation (DES) has become a popular and effective decision-making tool for modeling the stochastic operational activities in a system. However for a whole system approach, system dynamics (SD) has advantages over DES. SD does not require vast data and is able to capture the interdependency relations between different units in an integrated system. Both approaches have strengths and weaknesses that may support and complement each other. An integrated model of both approaches will provide a realistic view of a complex system. This chapter provides an overview of the hybrid simulation modeling applications to emergency department.

Understanding the dynamic effects of returning patients toward emergency department density

This paper presents the development of a dynamic hypothesis for the effect of returning patients to the emergency department (ED). A logical tree from the Theory of Constraint known as Current Reality Tree was used to identify the key variables. Then, a hypothetical framework portraying the interrelated variables and its influencing relationships was developed using causal loop diagrams (CLD). The conceptual framework was designed as the basis for the development of a system dynamics model.This paper presents the development of a dynamic hypothesis for the effect of returning patients to the emergency department (ED). A logical tree from the Theory of Constraint known as Current Reality Tree was used to identify the key variables. Then, a hypothetical framework portraying the interrelated variables and its influencing relationships was developed using causal loop diagrams (CLD). The conceptual framework was designed as the basis for the development of a system dynamics model.

A fuzzy Bayesian network approach to quantify the human behaviour during an evacuation

Bayesian Network (BN) has been regarded as a successful representation of inter-relationship of factors affecting human behavior during an emergency. This paper is an extension of earlier work of quantifying the variables involved in the BN model of human behavior during an evacuation using a well-known direct probability elicitation technique. To overcome judgment bias and reduce the expert’s burden in providing precise probability values, a new approach for the elicitation technique is required. This study proposes a new fuzzy BN approach for quantifying human behavior during an evacuation. Three major phases of methodology are involved, namely 1) development of qualitative model representing human factors during an evacuation, 2) quantification of BN model using fuzzy probability and 3) inferencing and interpreting the BN result. A case study of three inter-dependencies of human evacuation factors such as danger assessment ability, information about the threat and stressful conditions are used to illus...