Sabrina Ahmad

Negotiation in the Requirements Elicitation and Analysis Process

Requirements elicitation and analysis is the most crucial process in requirements engineering since it moulds the shape of the desired end product. In dealing with a systems stakeholders in a process to elicit the requirements, conflicts are inevitable. In the initial state, usually, all the stakeholders have a common goal; to build a system. However as an individual, they do have their own perspectives and perceptions. In addition, the stakeholders, either as a representative of end users, a decision maker or a developer, have different concerns, priorities and responsibilities. This paper considers introducing negotiation spiral model with supporting elements in the requirements elicitation and analysis process. Many researches show that negotiation is necessary to handle conflicts in order to gain better requirements. It is believed that the quality of intermediate deliverables like the requirements document is correlated with the quality of the final product. The advantages of implementing negotiation process are well aligned requirements by all the stakeholders, improved system quality, a sound basis for resource estimation and less resource wastage.

A comparative study of feature extraction using PCA and LDA for face recognition

Feature extraction is important in face recognition. This paper presents a comparative study of feature extraction using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) for face recognition. The evaluation parameters for the study are time and accuracy of each method. The experiments were conducted using six datasets of face images with different disturbance. The results showed that LDA is much better than PCA in overall image with various disturbances. While in time taken evaluation, PCA is faster than LDA.

Recognizing Patterns of Music Signals to Songs Classification Using Modified AIS-Based Classifier

Human capabilities of recognizing different type of music and grouping them into categories of genre are so remarkable that experts in music can perform such classification using their hearing senses and logical judgment. For decades now, the scientific community were involved in research to automate the human process of recognizing genre of songs. These efforts would normally imitate the human method of recognizing the music by considering every essential component of the songs from artist voice, melody of the music through to the type of instruments used. As a result, various approaches or mechanisms are introduced and developed to automate the classification process. The results of these studies so far have been remarkable yet can still be improved. The aim of this research is to investigate Artificial Immune System (AIS) domain by focusing on the modified AIS-based classifier to solve this problem where the focuses are the censoring and monitoring modules. In this highlight, stages of music recognition are emphasized where feature extraction, feature selection, and feature classification processes are explained. Comparison of performances between proposed classifier and WEKA application is discussed.

A conceptual model to empower software requirements conflict detection and resolution with rule-based reasoning

It is seldom technical issues which impede the process of eliciting software requirements. The involvement of multiple stakeholders usually leads to conflicts and therefore the need of conflict detection and resolution effort is crucial. This paper presents a conceptual model to further improve current efforts. Hence, this paper forwards an improved conceptual model to assist the conflict detection and resolution effort which extends the model ability and improves overall performance. The significant of the new model is to empower the automation of conflicts detection and its severity level with rule-based reasoning.

The Relevance of Software Requirement Defect Management to Improve Requirements and Product Quality: A Systematic Literature Review

Software is an intangible computer’s component, and their requirements are the greatest challenge to handle but yet the most important. In order to ensure the requirements are in good quality, defect management is one of the promising efforts to adopt. This paper aims to provide a literature review regarding defect management for software requirements and the relevance of the defect management to improve requirements and product quality. The paper is structured based on a systematic literature review method which is constructed from significant questions. The findings on the literatures show that many efforts have been done to improve defect management effort in several stages of software development life cycle. However, the efforts are scarce in the requirement engineering phase. This paper provides a foundation study to pursue research in improving requirements and eventually product quality through defect management.

The effectiveness of gamification technique for higher education students engagement in polytechnic Muadzam Shah Pahang, Malaysia

In recent years, gamification is becoming popular in education development to enrich students experience in classroom. However, there is still lack of awareness among educators and the concern of whether the gamification technique is acceptable by students. This paper presents the effectiveness of gamification technique to improve students’ engagement in Database Design subject at Polytechnic Muadzam Shah Pahang, Malaysia. A framework to implement the gamification technique in higher education is also described. As for the evaluation, an empirical investigation method is adapted and data was collected based on Technology Acceptance Model (TAM) and Student Course Engagement Questionnaire (SCEQ). The evaluation results indicate that the students positively inclined towards gamification caused by the ease of the platform used rather than the benefits that they can obtain from the gamification, concluding that Perceived Ease of Use (PEOU) is a better indicator for students’ attitude towards gamification.

An Enhanced Malay Named Entity Recognition using Combination Approach for Crime Textual Data Analysis

Named Entity Recognition (NER) is one of the tasks in the information extraction. NER is used for extracting and classifying words or entities that belong to the proper noun category in text data such as persons name, location, organization, date and others. As seen in todays generation, social media such as web pages, blogs, Facebook, Twitter, Instagram and online newspapers are among the major contributors to the generation of information. This paper presents an enhanced Malay Named Entity Recognition model using combination fuzzy c-means and K-Nearest Neighbours Algorithm method for crime analysis. The results showed that this combination method could improve the accuracy performance on entity recognition of crime data in Malay. The model is expected to provide a better method in the process of recognizing named entities for text analysis particularly in Malay.