Dinesh Kumar Saini

Integrating EduLearn learning content management system (LCMS) with cooperating learning object repositories (LORs) in a peer to peer (P2P) architectural framework

An attempt is made to integrate the EduLearn Learning Content Management System (LCMS) components with comparable Learning Objects Repository (LORs), specified in Peer to Peer (P2P) architecture to provide a better framework for sharing Learning Objects. Learning Content Designers need to be able to access a suitable learning object. For this the Learning Object needs to reside in an LOR which has the capacity to cater quickly to the needs of the Learning Content Designer. Reuse of a Learning Object is possible only if it is available easily and it is designed in a standard format. Such a reusable learning object (RLO) has the ability of being reused in different learning contexts and for various objectives. We have proposed a new framework for more efficient e-learning environment by using P2P architecture and Semantic Overlay Network. This will help in efficient management of LCMS components and improve the performance of LCMS through the RLO. Our framework authenticates Learning Object Repositories and provides a better load balance for the framework using P2P technology.

Testing polymorphism in object oriented systems for improving software quality

With object-oriented approaches, testing should center on objects, classes, generic classes and super classes, inheritance and polymorphism, instead of subprograms. In object-oriented software test, the feature of inheritance and polymorphism produces the new obstacle during dynamic testing. Polymorphism becomes a problem in dealing with object-oriented software testing. In this paper various issues and problems that are associated with testing polymorphic behavior of objects in object oriented systems is discussed. I propose a testers perspective method to assess the polymorphism in design stage. This way it also provides useful information for developer to probe into the fault that is hidden from test in early stage. Thus it will help in improving the quality of object oriented software.

Class Level Test Case Generation in Object Oriented Software Testing

Object-oriented programming consists of several different levels of abstraction, namely, the algorithmic level, class level, cluster level, and system level. In this article, we discuss a testing technique to generate test cases at class level for object-oriented programs. The formal object oriented class specification is used to develop a test model. This test model is based on finite state machine specification. The class specification and the test model is analyzed to select a set of test data for each method of the class, and finally the test cases can be generated using other testing techniques like finite-state testing or data-flow testing.

Enhanced inquiry method for malicious object identification

This paper proposes a new technique for malicious object detec-tion and identification. The technique is based on a concept of vi-rus inquiry. The inquiry is an activity that is performed by the malicious object during its initiation. The malicious object uses this activity to ensure its uniqueness in memory. The inquiry can be regarded as a common behavior of malicious object such as viruses. The proposed system is designed using the concept of Ob-ject Oriented Programming (OOP) that treats the operating system, user program, and virus as objects. It is constructed of three ele-mentary objects that perform their activities depending on two da-tabases.

Credibility of digital content in a healthcare collaborative community.

With the increased number of new diseases that are appearing in the world, such as swine flu [influenza A(H1N1)], and the increased awareness of the importance of sharing medical ideas, information, experience, knowledge, and research results, there is an urgent demand for a collaboration framework. Such a framework depends on deploying, discovering, and using digital content. This inevitably leads to the generation of large amounts of digital content from different healthcare users, which requires massive resources to process, store, and retrieve them. Moreover, the digital content currently suffers from a lack of credibility, which is vital in healthcare applications. Thus, this chapter discusses briefly how grid computing can boost Web 2.0 communities. In addition, the chapter discusses a proposed scenario for offering a way of measuring the credibility of the published digital content.

Cloud Computing and Accident Handling Systems

An attempt is made to study the current issues of the cloud computing solutions for the life critical systemcar accident systems in the Gulf region. Gulf region has high death rate because of car accidents and there is little or no proper accident handling facilities in the region. This Research paper includes the review of development in the field of cloud computing in the service industries which provide some assistance to the accident handling systems including the hospitals and the drivers using latest technologies such as Mobile computing, SaaS, Cloud Computing etc..

E-assessment for e-learning

The aim of the paper is to analyse the concept of e-assessment in the e-learning domain. Current knowledge explosion and needs of learning pose new challenges in the assessment techniques and traditional assessment methods have their own limitations. In this paper comparison of traditional assessment and e-assessment is carried out. The respective effectiveness of each method e-assessment and e-learning for the learner based on learner profiles and learning desired learning outcomes is done in the paper. It is helping learners to achieve the required level of learning outcomes. The mapping between the e-assessment and the learning outcome is an issue that needs to be addressed. Another concern is the lack of proper tools and guidelines for e-assessment, especially issues related to subjective assessments. Popular learning platforms like Moodle and Blackboard do not support core learning skills, critical thinking ability or any method to assess them. Quality and validity of e-assessment issues are also addressed in the paper.

Emerging information technology and contemporary challenging R & D problems in the area of learning: An artificial intelligence approach

Access to information and electronic resources is a main hurdle faced by e-learners. In addition, it is difficult to find learning materials that best suit students needs while tutors need to find an automatic way for receiving feedback from students. Therefore, the development of efficient new procedures to better guide students for selecting suitable learning materials is becoming a challenging factor in the e-Learning environment.

Business Intelligence Design Model (BIDM) for University

ABSTRACT Information and knowledge are the backbone of any organization’s development because they are used in decision making processes. In addition, the management level of any organization is looking forward to ensure the quality and the effectiveness of the work performances depending on the knowledge to make the right decisions. But by the increased amount of information produced by the organizations the decision making processes becomes more complex and needs lots of time to be taken. Therefore, they have to upgrade their work and the way of decision making processes by using new technologies like the Business Intelligence (BI). BI can help the organizations to make the best use of information and creating a knowledge base which supports the decision making processes. Therefore, the universities as any organizations are looking forward to improve their work performances to keep pace with the world’s development and manage the increase of the volume of the information needed for the decision making process. Therefore, this research paper is to introduce a Business Intelligence Design Model (BIDM). BIDM is a model that is going to help university to use the business intelligence systems to produce the reports which achieve the accuracy, reliability and the effectiveness to support the decision making processes.

Environmental Scrutinizing System based on Soft Computing Technique

Artificial intelligent techniques are very much needed to design the environmental monitoring systems. These systems must be smart enough so that all the decisions taken by the system must be accurate. Soft Computing (SC) it is a set of computational methods that attempt to determine satisfactory approximate solutions to find a model for real-world problems. It based on various techniques such as Artificial Neural Networks, Fuzzy Logic and Genetic Algorithms. The aim of this paper is to implement a soft computing technique which is artificial neural network based on Self-Organizing Feature Map (SOFM). SOFM model for monitoring and collecting of the data are real-time and static datasets acquired through pollution monitoring sensors and stations. In the environmental monitoring systems the ultimate requirement is to establish controls for the sensor based data acquisition systems and need interactive and dynamic reporting services. SOFM techniques are used for data analysis and processing. The processed data is used for control system which even feeds to the alarming systems.