Knowledge acquisition and dissemination for emergency situation

Emergency situation is highly uncertain, dynamic, time pressure in making decisions and involves multi organizations and multi jurisdiction level. This paper presents a conceptual architecture that can be used by emergency response task force in assisting the victims of the disaster. Flood disaster is used as a case study. The architecture describes the knowledge and communication for flood emergency response management

New improvement in digital forensic Standard Operating Procedure (SOP)

In today’s digital forensic investigation, there are hundreds of specific and unique application software packages and hardware device that could be used in the investigation. Even with all this yet there are quite number of failure in SOP that being practiced by the current digital forensic investigator.In this research paper an improved SOP is being proposed. This proposed SOP will be flexible rather than being limited to a particular process of an investigation

Computational Recognition-Primed Decision Model Based on Temporal Data Mining Approach in a Multiagent Environment for Reservoir Flood Control Decision

In an emergency, decisions have to be made fast and accurate. Each decision has an influence to the safety of the public and properties. Due to the time pressure of the situation, a rapid decision model is required which will increase the speed of responding to an emergency situation. The decision model must be able produce accurate decisions due to the unpredictability and uncertainty of the situation that develops. This study is an initiative towards developing a computational model for emergency decision-making. The characteristics of an emergency environment resembles naturalistic decision-making environment. Among the properties of this environment is time pressure, urgent, unpredictable, high uncertainty, high stakes, usually involved multiple players and experienced decision-maker. In a situation such as this, experience and able to recognize a similar situation with the past is essential. This recognitional strategy helps reduce time taken in making decisions by comparing to previous decision patterns. Gary Klein introduced such a model called Recognition-prime decision (RPD) to describe experienced decision makers thinking processes. For a computer system, the computational model should be able to learn from experience and recognize a similar situation. The 'learning from experience' requirement resembles a computational intelligence procedure called data mining. It can provide an autonomous decision-making capability that can facilitate shorter response time in decision-making. Emergency situation has special characteristics where events are usually an effect of a cause after some considerable delay. Hence the situation is time dependent and strictly time: ordered. Therefore the data mining approach need to be able to handle this time factor. This thesis, explored the feasibility of using temporal data mining approach to support computational RPD model to be used in a naturalistic situation. Flood emergency is taken as domain to be studied due to its common occurrences in Malaysia. Reservoir flood control at Timah Tasoh dam in the State of Perlis is taken as case to test the model developed. Real operation data were used to validate the model. A multiagent system was also designed, prototype implemented and tested to also provide autonomous and proactive capability to the emergency warning system. Agent based approach and temporal data mining provide faster response to impending emergency situation. Performance of the model was measured against real operation data from 1998 to 2002 and was found to predict with more that 90% accuracy with less than 10% false alarm

Artificial immune system agent model

The Artificial Immune Systems (AIS) is a biologically inspired techniques that emulates a natural system, in particular the vertebrate immune system, in order to develop computational tools for solving engineering problems.Immunity-based technique emerge as a new branch of artificial intelligence (AI).The human biological immune system has become the source of inspiration for developing intelligent problem-solving techniques.The powerful information processing capabilities of the human system, such as feature extraction, pattern extraction, learning, memory and its distributive nature provide rich metaphors for its artificial counterpart. Hence, the goal of this study is to develop an Artificial Immune System (AIS) model using agent approach for incremental learning.The main issue handled was how to integrate a multiagent system into an AIS application.This model proposed was simulated using cases for the performance measurement.The step by step activities performed in developing the agent based AIS model can be a guideline in developing an AIS application. Besides that, the simulation of the AIS model can be further enhanced to be used for teaching and learning purposes

Requirements analysis method for extracting-transformation-loading (ETL) in data warehouse systems

The data warehouse (DW) system design involves several tasks such as defining the DW schemas and the ETL processes specifications, and these have been extensively studied and practiced for many years.The problems in heterogeneous data integration are still far from being resolved due to the complexity of ETL processes and the fundamental problems of data conflicts in information sharing environments.The understanding of an early phase of DW development is essential in properly tackling the complexity of ETL processes.The method to analyses the DW requirements from the abstract level (e.g. goal, sub-goal, stakeholder, dependency) toward the specification of ETL processes (e.g. extracting, filtering, conversion) are important in order to manage the complexity of the ETL processes design (e.g. semantic heterogeneity problems). However, current approaches that are based on existing software requirement approach still have limitations on translating the business semantics for DW requirements toward the ETL processes specifications.Moreover, the understanding of goal in the perspective of the organization and decision makers are important to ensure the semantic of DW requirements can be properly determined, organized, and implemented by the ETL processes. Therefore, the proposed method will utilize the ontology with goal-driven approach in analyzing the requirements of ETL processes

pSPADE: Mining sequential pattern using personalized support threshold value

As the web log data is considered as complex and temporal, applying Sequential Pattern Mining technique becomes a challenging task.The min sup threshold issue is highlighted - as a pattern is considered as frequent if it meets the specified min sup.If the min sup is high, few patterns are discovered else the mining process will be longer if too many patterns generated using low min sup. The format of web log data that creates consecutive occurring pages has made it difficult to generate frequent sequences. Also, as each user’ behaviour is unique; using one min sup value for all users may affect the pattern generation. This research introduced a personalized minimum support threshold for each web users using their Median item access (support) value to curb this problem.The pSPADE performance was the highest on the discovery of user’s origin and also interesting pattern discovery attribute

Integrated model for organizational transformation in business process reengineering

This paper presents a pilot study implementing business process engineering where integrated model was used for business transformation analysis. Business process reengineering is a process that contributes to organizational transformation which will redesign the business processes and management to achieve dramatic improvement in business performance. A model that can bridge the gap between business and technical view is needed in the reengineering processes such that it can be easily translated from both business and technical perspective. This study demonstrate the feasibility of using model as technique in generating reengineering solution for organizational transformation in a human resource department of a wholesale company. Evaluation by users including the human resource officer shows a high satisfaction and improvement in the prototype representing new work processes develop using Lotus Notes

ETL processes specifications generation through goal-ontology approach

The common design-related problems for extract, transform, load (ETL) processes are far away from being resolved due to the variation and ambiguity of user requirements and the complexity of ETL operations.These were the fundamental issues of data conflicts in heterogeneous information sharing environments.Current approaches are based on existing software requirement methods that have limitations on reconciliation of the user semantics toward the modeling of the DW. This will prolong the process to generate the ETL processes specifications accordingly.The solution in this paper is focused on the requirement analysis method for designing the ETL processes. The method - RAMEPs (Requirement Analysis Method for ETL Processes) was developed to support the design of ETL processes by analyzing and producing the DW requirements in perspectives of organization, decision-makers, and developers.The ETL processes are modeled and designed by capturing DW schemas and data sources integration and transformation. The validation of RAMEPs emphasizes on the correctness of the goal-oriented and ontology requirement model, and was validated by using compliant tools that support both these approaches.The correctness of RAMEPs was evaluated in three real case studies of Student Affairs System, Gas Utility System, and Graduate Entrepreneur System.These case studies were used to illustrate how the RAMEPs method was implemented in generating the ETL processes specifications

NEW IMPROVEMENT IN DIGITAL FORENSIC STANDARD OPERATING PROCEDURE (SOP)

ABSTRACT. In today's digital forensic investigation, there are hundreds of specific and unique application software packages and hardware device that could be used in the investigation .Even with all this yet there are quite number of failure in SOP that being practiced by the current digital forensic investigator .In this research paper an improved SOP is being proposed. This proposed SOP will be flexible rather than being limited to a particular process of an investigation