Fadhilah Ahmad

Development and innovation of multimedia courseware for teaching and learning of KAFA subjects

Nowadays, the development of technology is affecting the educational sector. Courseware is one of the approaches that can be used in teaching and learning process so that it becomes more effective and interesting. This paper demonstrates the process of development of multimedia courseware that can be used for teaching and learning of KAFA subjects. Development of the courseware is to deal with some issues that arise in teaching and learning of KAFA subjects. The courseware is developed based on selected methodology to ensure that it fulfills the teaching and learning objectives. It is integrated with multimedia elements such as graphics, audio and video to make it more attractive to be used by students in their learning process.

Algorithms for extracting adjacency matrix based on formal concept analysis (FCA)

The desire to achieve a holistic representation of Information Retrieval (IR) with the aim for a human-oriented form of representation has spurred the growth of concept-based IR search techniques such as the Semantic Web technology. However, Semantic Web calls for the use of ontologies for many domains. Although meaningful and important, ontology development presents great challenges to the developers especially in terms of conceptual dynamics.. This paper is based on a study that attempts to provide an alternative to ontology lookup for Semantic information retrieval. However, the focus of the paper is on a method proposed to extract adjacency matrix from concepts obtained from the theory of Formal Concept Analysis (FCA) using two consecutive algorithms called the Relatedness Algorithm and Adjacency Matrix Algorithm. Consequently, the adjacency matrices obtained could be used in a similarity measure process based on graph theory. The proposed method offers an alternative to specific domain ontology look-up where results from the measure can further be used in concept-based IR process.

Multiple Criteria Preference Relation by Dominance Relations in Soft Set Theory

This paper presents the applicability of soft set theory for discovering the preference relation in multi-valued information systems. The proposed approach is based on the notion of multi-soft sets. An inclusion of objects into value set of decision class in soft set theory is used to discover the relation between objects based on preference relation. Results from the experiment shows that dominance relation based on soft theory for preference relation is able to produce a finer object classification by eliminating inconsistencies during classification process as opposed to the expert judgement classification.

A Fuzzy TOPSIS with Z-Numbers Approach for Evaluation on Accident at the Construction Site

The construction industry has been identified as one of the most risky industries where involves fatalities accidents. Identifying the causes that lead to the accidents implicates a lot of uncertain and imprecise cases. Z-numbers involve more uncertainties than Fuzzy Sets (FSs). They provide us with additional degree of freedom to represent the uncertainty and fuzziness of the real situations. In this paper, we introduce a Fuzzy TOPSIS (FTOPSIS) with Z-numbers to handle uncertainty in the construction problems. Five criteria and six alternatives are used to evaluate the causes of workers’ accident at the construction sites. Data in form of linguistic variables were collected from three authorised personnel of three agencies. From the analysis, it shows that the FTOPSIS with Z-numbers provides us with an another useful way to handle Fuzzy Multi-Criteria Decision Making (FMCDM) problems in a more intelligent and flexible manner due to the fact that it uses Z-numbers with FTOPSIS.

Improved Quasi-Newton method via PSB update for solving systems of nonlinear equations

The Newton method has some shortcomings which includes computation of the Jacobian matrix which may be difficult or even impossible to compute and solving the Newton system in every iteration. Also, the common setback with some quasi-Newton methods is that they need to compute and store an n × n matrix at each iteration, this is computationally costly for large scale problems. To overcome such drawbacks, an improved Method for solving systems of nonlinear equations via PSB (Powell-Symmetric-Broyden) update is proposed. In the proposed method, the approximate Jacobian inverse Hk of PSB is updated and its efficiency has improved thereby require low memory storage, hence the main aim of this paper. The preliminary numerical results show that the proposed method is practically efficient when applied on some benchmark problems.

Application of Integrated Decision Support Model in Tendering

Tendering is an important issue that requires Decision Support System (DSS) attention as a decision to award tenders to certain competing applications could influence successful completion of a project. This paper presents a framework of DSS for a tendering process based on a combination of single criteria statistical model, weighted model and an extended AHP model known as Guided AHP (GAHP). This hybrid model allows single criteria tender prices which are considered abnormal to be excluded from further detail multicriteria GAHP evaluation. GAHP is proposed to minimize the possibility of inconsistent data entry and to improve evaluation accuracy and flexibility. The use of model integration takes the advantage of their strengths and complements each other’s weaknesses. Finally, a real organizational government tendering application is applied to demonstrate the potential of the proposed framework.