IoT Piggy Bank for Money Saving Habit Instillation

Children nowadays are overwhelming with luxurious things and have only little or even no money concepts where most of the kids just reach out to their parents for buying anything they want. This could be an issue for parents, hence kids should be taught the value of money and knowing that save their own money is important to purchase anything they desired. This project proposed an innovative way to inculcate saving behaviours in children using an IoT Piggy Bank. This goal-directed approach allows children to set their saving goals (values of their desired items) and form a saving habit slowly through their saving routines toward their saving goals. Every saving made by the children will be tracked in a mobile app and a buzzer will be triggered as a reinforcer to alert children when they do not save regularly. The user acceptance testing (UAT) of the proposed prototype has shown the majority of the parents (90%) agreed that the proposed IoT piggy bank is very suitable for children to instil saving habit. Most of the children have reacted positively where they were having lots of fun when trying on the IoT piggy bank and expressed that they would continue to use it for saving in the future

A Semantic Extraction and Analysis for Traffic Density Using Traffic Images: A Critical Review

Population growth in large cities has contributed to the increase in vehicles' number, leading to the traffic congestion problem. Incompetent traffic supervision could squander an inconsiderable number of man-hours and might lead to fatal consequences. Therefore, intelligent traffic surveillance systems have to carry more significant roles in highway monitoring and traffic management system throughout the years. Although vehicle detection and classification methods have evolved rapidly throughout the years, they still lack high-level reasoning. Accurate and precise vehicle recognition and classification are still insufficient to develop an intelligent and reliable traffic system. There is a demand to increase the confidence in image understanding and effectively extract the images conformed to human perception and without human interference. This paper attempts to summarize a review on several methods that semantically extract and analyze traffic density with image processing techniques. Three (3) methods that have been selected to be discussed in this paper are semantic analysis of traffic video using image understanding, mining semantic context details of traffic scene, and integrating vision and language in semantic description of traffic events from image sequences. Each method is discussed thoroughly, and their outstanding issue is deliberated in this paper

Incorporating Unstructured Text in Multi-Layer Perceptron (MLP) Network: Factors Affecting Partner Selection in Pair Programming

The revealed analysis studies on pair programming so far indicate that pair programming has produced affirmative effects on some aspects of students’ performance. In the academic field, the usual practice of pair programming would be pairing the students in line with the programming skills of the students by the respective lecturers. This means, compatibility of the students in terms of their programming skills is the main focus when the pairing was done by the lecturers. Yet, research on elements that the students are looking into when they are given the liberty to decide on their partner in pair programming is lacking. In this study, a multi-layer perceptron (MLP) is developed to predict the preference of opting pair programming over solo programming. The Bayesian Information Criterion was used to select the best features in the prediction. The potential of unstructured text entered by the participants as comments in the questionnaire is incorporated in the MLP model to verify its capabilities towards prediction accuracy, i.e., to verify whether their comments are connected to their preference for pair programming versus solo programming. It was found that, when the students are given the freedom to choose their partner in pair programming, in the context of Malaysia, the students would pay attention to the ethnic criterion. This also suggests that the unstructured texts in the form of comments submitted by the participants in the questionnaire did not contribute to their choices on whether to undertake solo or pair programming

Strengthening Curriculum Sructure of Software Engineering Programme

The rapid development of technology has changed the world with various computer-based inventions and innovations. Education from primary to tertiary level is no exception in facing this change. With the curriculum changes that have begun to introduce courses related to programming at the primary and secondary level, the tertiary level curriculum should also change for quality education. This paper presents a new curriculum structure for the Software Engineering Undergraduate Program at University Malaysia Sarawak (UNIMAS). The current structure of Software Engineering programme does not follow the Malaysian Qualifications Agency (MQA) Programme Standards. The objective of this paper is to develop a new curriculum structure of Bachelor of Software Engineering based on MQA. The processes involved data collection, document analysis, and meeting with industries to restructure the curriculum. As a result, four new courses have been added to the new curriculum structure the Bachelor of Software Engineering programme for improvements. It is hoped that the graduates from this programme will fulfil the job skills and knowledge as required by the current industries

Measurement system analysis for Motorola global software group Malaysia

As measurement of software metrics gradually became a vital process in software engineering, the measurement-derived information has been heavily used as an important source to support decision-making. The reliability of the derived information is subject to the variations in the measurement system which could contribute to information distortion and lead to wrong decisions. This project is to study the existing measurement system adopted by GSG Malaysia to identify the sources of variations and root causes in the system, as well as to improve the measurement system by reducing the variation errors in the measurement mechanisms. The three (3) major elements of measurement system; people, tool and process are examined via a thorough study on the existing relevant documentations, process work flows and measurement mechanism to identify the variations in the system. A respondent’s opinion survey and descriptive statistical analysis are conducted to substantiate the analysis study. The results from the analysis show the major variations errors and errors root causes in the measurement system that are to be solved and improved. The outputs of measurement system analysis are essential sources to improve the quality of the software process and increase the reliability of measurement-derived information. This is to provide better and efficient decisions support system as the organization’s competitive edge to sustain itself in the IT world

A Conceptual Model for Virtual Queuing System to Support Social Distancing

In the early December 2019, Coronavirus Disease 2019 (COVID-19) epidemic outbreak emerged from Wuhan City, Hubei Province, China and spread rapidly to the rest of the world. Globally, IT Professionals were forced to adapt and innovate rapidly in response to the pandemic and have devised a variety of IT solutions to ease peoples’ transitions into the new normal. There are 4 major categories of IT-based COVID-19 solutions, namely contact tracing, quarantine management,symptom monitoring and information provision. However, most of these applications only focus on contact tracing as opposed to preventing the spread of the virus through the enforcement of social distancing. This paper presents a conceptual model for virtual queuing system, MyQueue which allows its users to enter virtual queues by scanning unique QR codes of various premises. It introduces proper process flows and approaches to eliminate waiting in a crowded queue and help support social distancing efforts to reduce the spread of COVID-19

A Semantic Extraction and Analysis for Traffic Density Using Traffic Images: A Critical Review

Population growth in large cities has contributed to the increase in vehicles' number, leading to the traffic congestion problem. Incompetent traffic supervision could squander an inconsiderable number of man-hours and might lead to fatal consequences. Therefore, intelligent traffic surveillance systems have to carry more significant roles in highway monitoring and traffic management system throughout the years. Although vehicle detection and classification methods have evolved rapidly throughout the years, they still lack high-level reasoning. Accurate and precise vehicle recognition and classification are still insufficient to develop an intelligent and reliable traffic system. There is a demand to increase the confidence in image understanding and effectively extract the images conformed to human perception and without human interference. This paper attempts to summarize a review on several methods that semantically extract and analyze traffic density with image processing techniques. Three (3) methods that have been selected to be discussed in this paper are semantic analysis of traffic video using image understanding, mining semantic context details of traffic scene, and integrating vision and language in semantic description of traffic events from image sequences. Each method is discussed thoroughly, and their outstanding issue is deliberated in this paper

Designing a mobile application testing model

In order to ensure that the software developed is at its highest quality, testing should be done all through the software life cycle and should start as early as possible. Therefore, for our previous mobile application development project, V-Model (a software testing model) was adopted as currently there is no specific testing model for mobile application. Unfortunately, we faced with a lot of challenges, similar to the challenges faced by other mobile application project, namely physical factors, network connections, testing equipment, system bug versus mobile device bug and multiple mobile platform and versioning. Even though the main objective is to test the mobile application, mobile application testing cannot be separated from testing on different mobile devices. Although solutions had been proposed to solve a few common mobile application testing challenges, there is still no clear testing model for mobile application. This paper presents the criteria to be considered when designing a testing model for mobile application