S. R. Kodituwakku

A Model for Web-Intelligence Index to Evaluate the Web Intelligence Capacity of Government Web Sites of Sri Lanka.

Web intelligence can be considered as a subset of Artifi cial Intelligence. It uses existing data in web to produce new data, knowledge and wisdom to support decision making and new predictions for web users. Artificial Intelligence is ever changing and evolving fie ld of computer science and it is extensively used in wide array of web based business applications. Althou gh it is used substantially in web based systems in developed countries, it is not examined whether it is being subs tantially used in Sri Lanka. Every Sri Lankan citizen depends on Public Service more or less throughout his/ her life time and at least more than 3 times: at birth, marriage and death. So providing most of these services to its citizen, Sri Lankan Government uses more or less of its country web portal. Thi s paper presents a model to evaluate web intelligence capability based on weight to key functionalities with respect to web intelligence. The government websites were checked by the proposed criteria to sh ow the potential of using web intelligent technology to provide website based services. The result indicates that the use of web intelligence tec hniques openly and publicly to provide web based services through government web portal to its citizens is not satisfactory. It also indicates that lack of using the technologies pertaining to web intelligence in the public service web hinders the most of the advantages that citizen and government can gain from such technologi cal involvement.

A wheel-based side-view car detection using snake algorithm

Car detection is a challenging research area where the appearance has various changes due to different models, poses, scales, lighting conditions, background, occlusion and various image sizes. Amidst these external challenging factors, car side-views have obvious and consistent characteristics in their structure such as wheels, oblique windows and bumpers, which provide crucial cues for detection. In this paper, we describe a novel side-view car detection technique which constructs an initial contour for the Snake using the detection of wheels. Our approach is subdivided in to three stages: wheel detection, bounding box detection, and segmenting the car from its background. In the first step, we use Hough transformation to detect circles in an image and validate the wheels with a learnt visual vocabulary. In the second step, we construct an initial contour with the aid of the detected wheels and the width-to-height statistics of different types of cars. This initial contour forms the bounding box of the car. In the third step, the Snake algorithm proceeds with the initial contour to fit the boundary closer to the car. Hence, the foreground, car, is separated from the background. We empirically evaluated our method on 100 side-view cars and the testing results shows that this approach has good performance.

An Offline Fuzzy Based Approach for Iris Recognition with Enhanced Feature Detection

Among many biometric identification methods iris recognition is more attractive due to the unique features of the human eye [1]. There are many proposed algorithms for iris recognition. Although all these methods are based on the properties of the iris, they are subject to some limitations. In this research we attempt to develop an algorithm for iris recognition based on Fuzzy logic incorporated with not only the visible properties of the human iris but also considering the iris function. Visible features of the human iris such as pigment related features, features controlling the size of the pupil, visible rare anomalies, pigment frill and Collarette are considered [2]. This paper presents the algorithm we developed to recognize iris. A prototype system developed is also discussed.

Improvements to a complexity metric: CB measure

Controlling the complexity of software applications is an essential part of the software development process as it directly affects maintenance activities such as reusability, understandability, modifiability and testability. However, as stated by Tom DeMarco “You cannot control what you cannot measure”. Thus, over the years many complexity metrics have been proposed with the intention of controlling and minimizing the complexity associated with software. However, majority of these proposed complexity metrics are based on only one aspect of complexity. The CB measure introduced by Chhillar and Bhasin is one metric which relies on a number of complexity factors to decide on the complexity of a program. However, it also has some shortcomings and can be further improved. Thus, this paper attempts to propose some additional complexity factors that the CB measure has not considered, to further improve it. The paper also presents an extensive coverage about the software complexity metrics proposed in the literature.

Ontology Based Information Extraction for Disease Intelligence

Disease Intelligence (DI) is based on the acquisition and aggregation of fragmented knowledge of diseases at multiple sources all over the world to provide valuable information to doctors, researchers and information seeking community. Some diseases have their own characteristics changed rapidly at different places of the world and are reported on documents as unrelated and heterogeneous information which may be going unnoticed and may not be quickly available. This research presents an Ontology based theoretical framework in the context of medical intelligence and country/region. Ontology is designed for storing information about rapidly spreading and changing diseases with incorporating existing disease taxonomies to genetic information of both humans and infectious organisms. It further maps disease symptoms to diseases and drug effects to disease symptoms. The machine understandable disease ontology represented as a website thus allows the drug effects to be evaluated on disease symptoms and exposes genetic involvements in the human diseases. Infectious agents which have no known place in an existing classification but have data on genetics would still be identified as organisms through the intelligence of this system. It will further facilitate researchers on the subject to try out different solutions for curing diseases..

Evaluation of the Use of Web Technology by Government of Sri Lanka to Ensure Food Security for its Citizens

Web technology is one of the key areas in information and communication technology to be used as a powerful tool in ensuring food security which is one of the main issues in Sri Lanka. Web technology involves in communicating and sharing resources in network of computers all over the world. Main focus of food security is to ensure that all people have fair access to sufficient and quality food without endangering the future supply of the same food. In this context, web sites play a vital and major role in achieving food security in Sri Lanka. In this case study, websites pertaining to Sri Lankan government and link with food security were analyzed to find out their impact in achieving the goals of food security using web technologies and how they are being involved in ensuring food security in Sri Lanka. The other objective of this study is to make the Sri Lankan government aware of present situation of those websites in addressing food security related issues and how modern web technologies could be effectively and efficiently used to address those issues. So, the relevant websites were checked against several criteria and scores were used to assess their capabilities to address the concerns of food security. It was found that the amount of emphasis given by these websites to address the issues of food security is not satisfactory. Further, it showed that if these web sites could be improved further, they would generate a powerful impact on ensuring food security in Sri Lanka.

Fuzzy based binary feature profiling for modus operandi analysis

It is a well-known fact that some criminals follow perpetual methods of operations, known as modus operandi (MO) which is commonly used to describe the habits in committing something especially in the context of criminal investigations. These modus operandi are then used in relating criminals to other crimes where the suspect has not yet been recognized. This paper presents a method which is focused on identifying the perpetual modus operandi of criminals by analyzing their previous convictions. The method involves in generating a feature matrix for a particular suspect based on the flow of events. Then, based on the feature matrix, two representative modus operandi are generated: complete modus operandi and dynamic modus operandi. These two representative modus operandi will be compared with the flow of events of the crime in order to investigate and relate a particular criminal. This comparison uses several operations to generate two other outputs: completeness probability and deviation probability. These two outcomes are used as inputs to a fuzzy inference system to generate a score value which is used in providing a measurement for the similarity between the suspect and the crime at hand. The method was evaluated using actual crime data and four other open data sets. Then ROC analysis was performed to justify the validity and the generalizability of the proposed method. In addition, comparison with five other classification algorithms showed that the proposed method performs competitively with other related methods.

Consistency checking of UML class and sequence diagrams

In object-oriented software modeling using the Unified Modeling Language, different aspects of a system are represented by various types of diagrams. UML diagrams represent two different views of a system model. They are static and dynamic views. In this paper we study the dynamic view of Class Diagrams and static view of Sequence Diagrams for checking consistency among them. We assume that the system is specified as a set of Class diagrams and the Sequence Diagrams are drawn using Enterprise Architect. With large and more complex UML models in the software development industry there is a serious issue on inconsistency of such diagrams. In design, evolution presents three issues: Consistency amongst design representations, traceability of a design change in code in order to maintain consistency and versioning of design entities along with versioning of code. As first step we translate UML class and Sequence diagrams into XMI (XML Metadata Interchange) format. We propose an algorithm to check the consistency among these two diagrams. Furthermore show how identify errors and inconsistencies using automated tool.

Data Access Control in Virtual Organisations

Virtual enterprises bring together different companies under one umbrella, and the organizational structure is tailored to the common project rather than reflecting the participating companies’ structure. A virtual organization is also dynamic in nature, as jobs/positions can be created or abolished as the project progresses. Access to information needs to be very flexible in such environment. On one hand, people should have access to all information they need to perform their duties, and those duties may change as time progresses. On the other hand, providing access to data other than needed for a particular job can lead to information overload and also poses a security risk, as it can lead to information leak or accidental modification of data. Role Based Access Control (RBAC) offers a solution to this problem by associating roles with jobs and assigning access privileges to roles.

Finite automation cryptosystem

A new public key cryptosystem is proposed, together with signature capabilities. This system based on the invertibility of finite automata. The security of the system rests on the difficulty of finding inverse automatas and of factoring matrix polynomial over Galois field GF(2).