Fazilah Haron

Modeling Groups of Pedestrians in Least Effort Crowd Movements Using Cellular Automata

Groups of pedestrians like family members and friends normally move slower than others and therefore act as a virtual barrier and slow down the crowd. In this paper we present our variation of least effort cellular automata algorithm which also considers the effect of pedestrian groups on crowd movement. The algorithm has been used in small scale movement layer of our multi-agent crowd simulation platform in order to allow more realistic simulations of crowd flows. A simple walkway scenario has been used to test the outcome of the model. Preliminary results of the simulation of the effect of groups are reported in this paper.

Simulating Crowd Movements Using Fine Grid Cellular Automata

Cellular automata models have been extensively used for simulating pedestrian movements. One weakness of this type of models, is the size of the cells which is mostly considered to be of the size of a pedestrian (i.e. 40cm*40cm or near to it). Each pedestrian stands in a single cell and during simulation time steps, transits to neighbouring cells. The size of the cells dictates discrete speed steps for pedestrians and chess like movements. A pedestrian could move one or more cells in a simulation time step or do not move at all. In order to have more smooth movement and different speeds for pedestrians (i.e. from different ages, physical and health status) we propose a finer grid cellular automata. We use this model to build a least effort cellular automata movement algorithm. The algorithm has been used in small scale movement layer of our multi-agent crowd simulation platform in order to allow more realistic simulations of crowd flows. A simple walkway scenario has been used to test the outcome of the model. Results of the simulation are reported in this paper.

Multi-Agent Simulation of Circular Pedestrian Movements Using Cellular Automata

This paper presents a basic multi-layer model of human movement process. A behavior model is used to simulate actions of individual pedestrians while a cellular automata model is used to simulate their small scale movements. A modular platform, which implements the proposed model, is also presented. The platform is being used to simulate different sections of the Muslim holy mosque in Makkah. Preliminary results of the simulation of circular pedestrian movements in a section of the mosque along with the algorithm used are reported.

Time series prediction using adaptive association rules

Grid computing is formed by a large collection of interconnected heterogeneous and distributed system. One of the grid computing purposes is to share computational resources. The efficiency and effectiveness of resource utilization of a grid greatly depend on the scheduler algorithm. The scheduler is able to manage the grid resources more effectively if we able to predict and provide it with the future state of grid resources. Therefore, this paper proposes a model to perform time series prediction using adaptive association rules. This model uses the idea that if a segment of a repeatable time series pattern has occurred, it has the possibility that the following segments of the repeatable pattern appear. Data mining and pattern matching techniques are being applied to mine for repeatable time series patterns. This model has the ability to provide confident level for each prediction it made and perform continuous adaptation. A prototype of this model is being developed and tested with four test cases. These test cases are relatively simple because our work on this time series prediction using adaptive association rules is very much in its early stages. The result from the experiment shows that our model is able to capture repetitive time series patterns and perform prediction using those patterns. However, this model has some drawbacks such as it required high computational power and required large storage.

Architecture of agent-based healthcare intelligent assistant on grid environment

In this paper we present an architecture of agent-based Healthcare Intelligent Assistant on grid environment. The Healthcare Intelligent Assistant is used by the medical practitioners to retrieve and use various existing organizational knowledge to help solve medical cases. We will use case-based format that captures the experiential knowledge of healthcare practitioners [1]. Using grid technologies all resources-knowledge within hospitals can be use by medical practitioner’s across geographically distributed location.

A framework for grid-based neural networks

The usage of neural networks in critical systems is fast approaching the norm. In such systems, the issue of accuracy is of prime importance. Ensemble methods have commonly been used to increase accuracy but at the cost of training time and computational requirements. With the advent of grid computing, it is expected that these problems are solved. This paper proposes a framework in which an ensemble of neural networks is implemented over a grid-based environment.

A Market-Based Scheduler for JXTA-Based Peer-to-Peer Computing System

Peer-to-Peer (P2P) computing is said to be the next wave of computing after client-server and web-based computing. It provides an opportunity to harness a lot of idle peer-resources such as desktop computers across the Internet, for solving large-scale computing applications. Each peer is autonomous and it needs incentive for sustained contribution of its resources to P2P applications. In addition, a flexible and efficient job scheduling is needed to harvest the idle computing power as cheaply and economically as possible.

Crowd Parameter Extraction from Video at the Main Gates of Masjid al-Haram

Gathering information on the large crowd of pilgrims attending Hajj is beneficial for management and safety of the event. Capturing information from videos can provide an effective method to gather different kind of data. However extracting information from such a large crowd is a challenging process. Computer vision allows for capturing of such information without the need for specialized devices or manual marking (labeling). In this paper we will focus on extracting pedestrian information such as speed from a video of Gate 1 (King Abdul Aziz) of Masjid al-Haram. Getting such information is non-trivial for many reasons, one of which is high occlusions. A literature review of the methods used for detection and tracking of human motion is presented. A methodology for the pedestrian parameter extraction is also proposed and the preliminary results of the tests on the algorithms are presented.

Resource Discovery Using PageRank Technique in Grid Environment

The grid deals with large scale and ever-expanding environment which contains million of users and resources. For this reason, resource selection has been a challenging task especially in meeting user’s demand for a quality of service (QoS). A quality of service is the ability to serve a job by providing quality and reliable resource in fulfilling the user’s need. Quality and reliable resource selections naturally yield excellent and quality results. The background of the users and where the resource belongs to are important in determining the quality of a resource. This paper concerns with efficient and quality-based resource discovery using Condor ClassAd and PageRank technique in order to achieve a quality resource matching. The paper discusses how quality of users and resources are determined and considered in the discovery process prior to allocating jobs to resources.

Flexible Security Protocol in Collaborative Editing Environment: An Overview

This paper proposes flexible security protocol for synchronous and asynchronous collaborative editing environment. The flexible security protocol comprises of preventive and corrective measures. The preventive measures ensure user authentication, access control and data confidentiality. The corrective measure includes fault tolerant measures to ensure data integrity.