Halal barcode scanner prototype in android using client side processing with JSON technology

Halal industry has becoming a steady growth industry in Malaysia since people including Muslim and non-Muslim are already alert about this issue due to its hygienic production. However, consumers nowadays are facing few difficulties regarding Halal recognition status as the logo has been duplicated and contacting JAKIM directly via telephone call or browsing web portal is slow and tiring. In certain circumstances, the use of existing technology like Radio-frequency Identification (RFID) is expensive and unaffordable to local communities. Besides, reading the barcode itself will burden consumer as they need to remember all sorts of codes available in stores. Therefore, the usage of Smartphone, barcode scanner and camera will be tested to recognize and split information from a barcode. The results will be analysed by developing Halal Barcode Recognition Status using Android Smartphone by matching the scan barcode to the database. Client server architecture is used to migrate data stored in server database and save to local database. The information will be extracted to recognize its halal status. Based on the testing, the system is capable to recognize the Halal status; however it needs further research for commercial use

A review of artificial intelligence in serious game for public health

Serious games used in public health for purposes including training, learning, prediction, coaching, diagnostic, rehabilitation and supporting. However, the serious game focuses mainly on user experience and graphical application, but less attention on applying artificial intelligence (AI). By enhancing artificial intelligence, it will have the capability to solve issues, especially in the field of public health. This article discussed a review of the use of artificial intelligence in a serious game for public health. The main idea of this paper is to gather all the related articles and create a trend analysis of the use of Artificial Intelligence (AI) in a serious game for public health. The related articles were applied to Artificial intelligence (AI) in the area of decision-making. The final section discussed the new trend and the future of Artificial intelligence using current AI techniques

Pathfinding algorithms in game development

This review paper provides an overview of a pathfinding algorithm for game development which focuses on the algorithms and their contribution to game development. The algorithms were categorised based on their search performance. The aim of this paper is to investigate and provide insights into pathfinding algorithms for game development in the last 10 years. We summarise all pathfinding algorithms and describe their result in terms of performance (time and memory). The result of this paper is metaheuristic techniques have better performance in terms of time and memory compared to heuristic techniques as a pathfinding algorithm

Environmental Degradation in Malaysia's Pahang River Basin and its Relation with River Pollution: Strategic Plan from Assessment to Mitigation using Geo-Informatics

This is an established truth that with the growing world, the environmental degradation process cannot avoid but the technology is a solution to minimize this process. A sustainable development depends on plans, which are design on the strong basis of comprehensive datasets. Under this research studies, the required datasets were generated using remote sensing and GIS system integrated with field GPS surveys. The representations of these datasets further analyzed to ensure the data quality and output results. The objectives of the study were to find out the Pahang River pollution and environmental threats by assessing and analyzing different data layers of topographical, geological, hydrological, land cover, GPS surveys and satellite image. The methodology adopted to achieve the desired goals and to combat the complexity of the hydro-environmental system of Pahang River drawn from the idea to integrate the engineering tools with the geo-informatics techniques. This resultant output of the project enabled to develop a system of system for the existing and future development datasets in different research institutions in Malaysia for the decision makers and researchers. This hydro-environmental system is GIS-based and primarily data driven. However, it also has features, which were included to develop a strategic plan for the assessment of environmental degradation and its mitigation measures by focusing on the concept of sustainable healthy river for future generations and environment friendly development activities in the watershed area of the Pahang River. The planed roadmap for response functions is the salient feature of this research study, which consists of quantitative and qualitative relationships that help to the decision makers to make it understand how changes in the state of environment and river water will take part in the mitigation process for the environment degradation process

Overviews of Uncertainty: Concepts, Categories and Coping Strategies in Decision Making

Uncertainty is not a new issue in decision making. A wrong decision made of a lack of certainty is every decision maker’s nightmare. Although uncertainty is broadly discussed in academic literature, uncertainty has been defined in many definitions, terms and conceptions. Some of the terms often overlap with similar terms from different perspectives. In the light of this, this paper takes the opportunity to explain uncertainty under 3 C’s perspectives; the Concept, the Categories and the Coping Strategies. An overview of uncertainty concepts pro- vides the basis for understanding how it is defined from a particular perspective related to decision support for decision making. The categories of uncertainty are explained based on their characterisation to provide a better understanding. Since there is no fixed way to treat uncertainty, this study takes the opportunity to compile the possible coping strategies in handling uncertainty. As an outcome, the contributions of this study come in two ways. First, this paper provides insights on uncertainty concepts and uncertainty categories that are worthy of being reflected in decision support for decision-making research domains. Second, this paper provides solutions and ideas for potential mix-and-match coping strategies that might be helpful in dealing with uncertainty in decision-making

Potential Data Collections Methods for System Dynamics Modelling: A Brief Overview

System Dynamics (SD) modelling is a highly complex process. Although the SD methodology has been discussed extensively in most breakthroughs and present literature, discussions on data collection methods for SD modelling are not explained in details in most studies. To date, comprehensive descriptions of knowledge extraction for SD modelling is still scarce in the literature either. In an attempt to fill in the gap, three primary groups of data sources proposed by Forrester: (1) mental database, (2) written database and (3) numerical database, were reviewed, including the potential data collections methods for each database by taking into account the advancement of current computer and information technology. The contributions of this paper come in three folds. First, this paper highlights the potential data sources that deserved to be acknowledged and reflected in the SD domain. Second, this paper provides insights into the appropriate mix and match of data collection methods for SD development. Third, this paper provides a practical synthesis of potential data sources and their suitability according to the SD modelling stage, which can serve as modelling practice guidelines

Modeling and simulation of the main metabolism in Escherichia coli and its several single-gene knockout mutants with experimental verification

Peer reviewedPublisher PD

A Comparison of Particle Swarm optimization and Global African Buffalo Optimization

The performance of Particle Swarm Optimization (PSO) brings attention to the field of algorithms when deals with different optimization problems. Due to her simple implementation, small consumption, and very effective in finding a solution in many problems, (PSO) becomes well known to the field of algorithms. In addition, the late proposed algorithms mostly are compared to the well-known algorithm such as PSO. Thus, the Global African Buffalo Optimization (GABO) was proposed lately and yet not been compared to the old well-known algorithms in terms of accuracy and time consumption. However, in this paper, a comparison between Particle Swarm Optimization (PSO) and Global African Buffalo Optimization (GABO) algorithms was performed. Five different nonlinear equations with their upper and lower boundaries values were selected as the test optimization functions problem in addition to PSO was applied to real case study. The experimental results illustrated the differences in the performances of both algorithms toward the optimum solution. At the end of the experiments, the PSO algorithm quickly convergence towards the optimum solution using a few particles and iterations rather than GABO. However, the experimental result showed that PSO achieved good results in all the test cases within a short time. In many cases, PSO and GABO are promising optimization methods

Hand Calibration with Limited Data As The Initial Step Towards System Dynamics Model Validation For COVID-19 Case In Malaysia

This paper presents the manual calibration effort for the System Dynamics (SD) COVID-19 model for Malaysia. This study aims to develop a COVID-19 SD model based on the COVID-19 scenario in Malaysia. The SD model consisted of nine compartments and was adapted based on a standard disease SEIR model using Vensim software. While the development of the model is still ongoing, an initial validation was carried out between ‘Actively Infected’ and the case data gathered from the Malaysia Ministry of Health's official COVID-19 websites. During this period, the parameters were manually adjusted by hand to align the model's output with the actual data. The expected outcome was not easy to achieve, but the result was acceptable. It is important to note that the lack of such strategies may compromise the model’s validity due to uncertainty. This paper also discusses the challenges posed by hand calibration, the lessons learned during this work, and the potential future implications of this work

Statistical modeling for prediction of diabetes in Malaysians

Type II Diabetes Mellitus is one of the silent killer diseases worldwide. According to the World Health Organization, 347 million people are suffering from diabetes throughout the world. To overcome the sharp rise in the disease, various diagnostic or prediction models were developed through various techniques such as artificial intelligence, classification and clustering, pattern recognition and statistical methods. The study led to the related open issues of identifying the need of a relation between the major factors that lead to the development of diabetes. This is possible by investigating the links found between the independent and dependant variables in the dataset. This paper investigates the effect of binary logistic regression applied on a dataset. The results show that the most effective method was the enter method which gave a prediction accuracy of almost 93%