Amran Ahmed

Analysis the Condition of RazakSAT Based on Attitude Sensor of Atttitude Determination System Data

Attitude determination system (ADS) is a process to control the orientation of the satellite to make sure that the orientation is relative to inertial references frame such as Earth. ADS is consists of mathematical algorithm and sensor as a references measurement to determine attitude of satellite. Since RazakSAT in the orbit, the sensor such as sun sensor, magnetometer and gyroscopes are used to control angular rotation and prevent high spin rates that can damage the satellite. This paper presents the analysis on sensor of attitude determination system based on RazakSAT data. Matlab was used to analyze the X,Y and Z axis of the sensor to determine the condition of the satellite.

Association between socioeconomic status and obesity among 12-year-old Malaysian adolescents

The epidemic of obesity in developed countries is commonly associated with poor dietary habit and sedentary lifestyle. However, other determinants, including education background and family income, may contribute towards the problem especially in developing countries. This study aimed to determine the influence of socioeconomic status (SES) on obesity among 12-year-old school adolescents in Terengganu, Malaysia. Body weight and height were measured and BMI was categorised based on WHO z-score cut-off points. Information was obtained from self-reported questionnaire on parents’ education background, family income and occupation. A total of 3,798 school adolescents aged 12 years (44% boys and 56% girls) were recruited. There was no significant difference in BMI status between boys and girls, or between rural and urban participants. There were significant differences between BMI categories and gender, household income and SES level within rural areas. In the urban areas, significant differences were found between BMI categories and gender, parents’ occupational and educational level, household income and size, and SES level. A logistic regression model found several SES factors to be predictors of obesity in this population, namely, gender, household size, father’s occupation level, household income level and SES level. Each component of SES has been significantly associated with the BMI category of school adolescents, particularly in the urban areas. This suggests the requirement of multifaceted approaches, including the role of family, society and authorities, in the effort to curtail adolescent obesity.

A Modified Boltzmann Machine for Solving Distribution System Expansion Planning in Malaysia

Received Jan 19, 2018 Revised Apr 28, 2018 Accepted Jun 14, 2018 Nowadays, Aspect-Oriented Programming (AOP) paradigm is getting more popularity in the field of software development. But testing an AspectOriented Software System (AOSS) is not well matured. Therefore, many researchers have been focusing on testing an AOSS. Moreover, the literature indicates that very few papers have devoted to literature survey but still there is need to study in depth of various testing techniques used for AOSS. Therefore, in this paper, a comprehensive study of existing various testing techniques for AOSS have been conducted and present a comparative analysis result of various testing techniques based on various parameters.Received Apr 8, 2018 Revised Jun 9, 2018 Accepted Jun 23, 2018 This paper proposes an effective technique to solve Distribution System Expansion Planning (DSEP) problem by using the artificial neural network. The proposed technique will be formulated by using mean-variance analysis (MVA) approach in the form of mixed-integer quadratic programming problem. It consists of two layers neural network which combine Hopfield network and Boltzmann machine (BM) in upper and lower layer respectively named as Modified BM. The originality of the proposed technique is it will delete the unit of the second layer, which is not selected in the first layer in its execution. Then, the second layer is restructured using the selected units. Due to this feature, the proposed technique will improve time consuming and accuracy of solution. Referring to the case study demonstrated in this paper, the significance outputs obtained are the improvement in computational time and accuracy of solution provided. As the solution provided various of options, the proposed technique will help decision makers in solving DSEP problem. As a result, the performance of strategic investment planning in DSEP certainly enhanced.Internet Protocol version 6 (IPv6) is a next-generation internet protocol that is devised to replace its predecessor, the IPv4. With the benefit of ample address space, flexible header extensions and its many specific features, IPv6 is the future of the Internet and Internetworking. A significant advantage of IPv6 is its capabilities in the domain of security and mobility, where it scores in comparison with its predecessor. One of the many features specific to IPv6, such as the mandatory IPsec messaging or address auto-configuration, is the Neighbor Discovery Protocol (NDP). Even though the concept of security is more pronounced in the IPv6 protocols, there still exist loopholes. These loopholes when exploited target the foundation of the Internetworking. The extensive applications of NDP make it even more necessary to identify and address these gaps to ensure network security. Hence, this paper investigates such loopholes in the applications of NDP in creating a network and analyzes the process of the denial-of-service attacks that endanger the safety of an established network. Also, the paper proposes a new method to mitigate Denial-of-Service (DoS) in network mobility of IPv6 networks. This proposed approach is a hybrid of existing solutions and is capable of overcoming the significant disadvantages of these methods. Also, the paper discusses the comparative analysis among the various existing solutions and illustrates the effect of the proposed method in MIPv6 security.Received Jun 1, 2018 Revised Jul 10, 2018 Accepted Jul 25, 2018 Big Data is a new technology and architecture. It can work on a very large volume of a variety of data with high-velocity, discovery, and/or analysis. Big Data is about the fast-growing sources of data such as web logics, Sensor networks, Social media, Internet text and documents, Internet pages, Search Index data, scientific research. Big data also formally introduces a complex range of analysis. Big data can evaluate mixed data (structured and unstructured) from multiple sources. As there are some security issues in big data which are no longer solved using the hashing techniques on large amount of data, this paper shows an idea of new approach of designing a Knox‟ified Hadoop cluster.

Formulation of noise isolation index for evaluating the interior acoustics level in vehicle cabin

This article proposes noise isolation index to assess the acoustical comfort level in the interior vehicle cabin. The noise isolation index is developed, validated, and compared for three local compact cars, namely, Axia, Myvi, and Viva which are most widely used vehicles in Malaysia and have not been yet studied. Toward this end, the interior and exterior sound signals are recorded on both stationary and non-stationary (highway, pavement, and urban) conditions and the trends of sound quality loudness (sone) and sharpness (acum) with respect to sound pressure level (Pa) are observed. The findings of this study indicate that the noise isolation index results are literally influenced by factors including type of road surface, engine transmissions, and vehicle design characteristics. The proposed index can be successfully extended by automotive researchers to assess the interior vehicle noise and can be significant factor in vehicle manufacturing process.

Influence of School Location within Districts of Terengganu on Body Weight Status among School Adolescents

Rapid development in the urbanisation process is linked to a shift in dietary intake and lifestyle. The locality may also determine the differences in socio-demographic and environmental factors related to nutrition between the rural and urban populations. The present study aimed to determine prevalence of obesity and to compare the body weight status on body weight status among school adolescents aged 10 to 17 years within districts of Terengganu. A cross sectional survey involving school adolescents aged 10 to 17 years from all government school in seven districts in Terengganu were carried out. Anthropometrics data were obtained from National Fitness Standard (SEGAK) assessment which was uploaded into specific developed database Health Monitoring System (HEMS) and BMI were classified using WHO BMI-for-age zscore. A total of 62,567 school adolescents were involved in this study. Girls had significantly higher BMI than boys in age groups of 13 to 15 and 16 to 17 years old. There were significant differences in mean BMI between rural and urban school locations school adolescents in all age groups (P <0.001) among boys and girls. Significant differences were also found between rural and urban school location in 10 to 12 years old in Dungun and Marang, whilst Kemaman and Kuala Terengganu districts had significant difference between rural and urban in 16 to 17 years old age group. Marang had the highest obesity prevalence within urban 15.3% school location whilst rural school location within Kuala Terengganu had the highest prevalence of obesity (14.1%). The obesity prevalence increased substantially regardless of school locations International Journal of Academic Research in Business and Social Sciences 2017, Vol. 7, No. 6

Data Mining Techniques for Classification of Childhood Obesity Among Year 6 School Children

Today, data mining is broadly applied in many fields, including healthcare and medical fields. Obesity problem among children is one of the issues commonly explored using data mining techniques. In this paper, the classification of childhood obesity among year six school children from two districts in Terengganu, Malaysia is discussed. The data were collected from two main sources; a Standard Kecergasan Fizikal Kebangsaan untuk Murid Sekolah Malaysia/National Physical Fitness Standard for Malaysian School Children (SEGAK) Assessment Program and a set of distributed questionnaire. From the collected data, 4,245 complete data sets were promptly analyzed. The data preprocessing and feature selection were implemented to the data sets. The classification techniques, namely Bayesian Network, Decision Tree, Neural Networks and Support Vector Machine (SVM) were implemented and compared on the data sets. This paper presents the evaluation of several feature selection methods based on different classifiers.

A review on the major sources of the interior sound vibration and riding comfort in vehicles

Vehicle interior comfort is a crucial criteria that is considered by the perspective costumer when purchasing a new vehicle. Meanwhile, automotive industries face the challenges for producing vehicles with better design criteria that meet the expectations of costumers and eventually promote higher competitive advantages in areas of acoustic performance, cost effectiveness, product weight, and global competitive market. This review presents the major sources that influence the generation of noise and vibration in the interior part of the vehicles. It also demonstrates the relative methods that are used to assess the interior acoustics and vibration and further improve the riding comfort. This study is of a particular importance for acoustical researchers and automobile engineers, where it brings about suggestions and fundamentals that can contribute to acoustical comfort in vehicles.

A study on correlation between ECI and satellite’s velocity based on RazakSAT data

This paper presents the analyzed on Earth Centered Inertial (ECI) of Attitude Determination System (ADS) and satellite velocity data of RazakSAT by using analysis method. ADS are one sub-system in satellite as function to control the orientation of satellite relative with inertial references frame. ECI is one of inertial references frame of RazakSAT with three dimension axis. ECI and velocity of satellite data of RazakSAT are analyzed with normality test by using Minitab software. The results show ECI and velocity data of RazakSAT are non-normal distribution, and correlation between ECI and satellite velocity is ellipse shape.

A double layer neural network for solving mixed-integer quadratic optimization problems

The main aim of this paper is to propose a double layer neural network (DLNN) for solving a class of mixed-integer quadratic optimization problems. It is proven that the DLNN is globally stable in the sense of Lyapunov and the output of the proposed neural network converged globally to an optimal solution. Compared with conventional Boltzmann Machine (BM) neural networks, the proposed neural network has a very small model size owing to its double layer structure. Furthermore, an application to power system showed that DLNN is effective. Numerical results shows that the DLNN is reduced by up to one-fifth compared to BM neural networks.

Structural Learning of Boltzmann Machine and its Application

In order to solve a problem efficiently, we propose the structural learning of Boltzmann machine. The proposed method enables us to solve the problem defined in terms of mixed integer quadratic programming. In this research, an analysis is performed by using the concepts of the reliability and risks of units evaluated using a variance-covariance matrix and also the effect and expanses of replacement are measured. Mean-variance analysis is formulated as a mathematical programming with two objectives to minimize the risk and maximize the expected return. Finally, we employ a Boltzmann machine to solve the mean-variance analysis efficiently. At the end, the result of our method was exemplified. This method enables us to obtain a more effective selection of results and enhanced the effectiveness of the decision making process.