Shamsul Mohamad

Development of INPLANS: An analysis on Students’ Performance Using Neuro-Fuzzy

This paper presents a simulation of Neuro-Fuzzy application for analysing studentspsila performance based on their CPA and GPA. The analysis is an extension of our previous study, which was called an analysis on studentpsilas performance using fuzzy systems. The main function of this analysis is to support the development of intelligent planning system (INPLANS) using fuzzy systems, neural networks, and genetic algorithms which will be used by the academic advisory domain in educational institutions by evaluating and predicting studentspsila performance as well as comparing the results with the previous study. The neuro-fuzzy model is connectionist feed-forward architecture with five layers of neurons and four connections. The system has been tested for 26 cases of studentspsila results. The results show that the studentspsila performances have improved significantly compared to the prediction of the same case using fuzzy systems.

Simulating group formation and behaviour in dense crowd

This paper presents a technique to simulate large groups in a dense crowd, where the groups can change their formation, and continuously avoid collision with other individual agents and groups, but still try to keep their collective behaviour until they reach their destination. To achieve this, we use the leader-follower model where the leader determines the group path while other members, driven by the modified social force model (SFM), follow the leader, maintaining the group formation. We also use density of agents in the travelling direction as the criteria to determine the appropriate formation type. Our proposed technique is easily compatible with individual agents driven by the existing SFM at moderate costs.

Development of Pusat Pengajian Diploma Industrial Training Online System (PiTOS): A Step Forward

This paper describes the design and implementation of the Pusat Pengajian Diploma Industrial Training Online System (PiTOS), which was designed to be a user friendly, generic, web-based system to ease accessibility to all vital information related to students’ industrial training in a more organized and efficient way in a paperless environment. The solution we developed is a web application, written using PHP and utilizes the MySQL as the database management system.

Silence removal from isolated Malay words using framing and windowing method

The most important domain in digital signal processing is speech signal processing. This is because a variety of noise signals could degrade the original speech signal and make it unclear to user. This project contributes to the literature by developing a program to remove silence from the original speech signal using framing and windowing method. Eight subjects from different gender and age have been asked to utter four Malay words and their voices are recorded to evaluate the effectiveness of the developed program. The results reveal that the program can be used effectively for removing silence.The most important domain in digital signal processing is speech signal processing. This is because a variety of noise signals could degrade the original speech signal and make it unclear to user. This project contributes to the literature by developing a program to remove silence from the original speech signal using framing and windowing method. Eight subjects from different gender and age have been asked to utter four Malay words and their voices are recorded to evaluate the effectiveness of the developed program. The results reveal that the program can be used effectively for removing silence.

Intelligent Agent Simulator in Massive Crowd

Received Mar 3, 2018 Revised Apr 11, 2018 Accepted Apr 21, 2018 Paintball has gained a huge popularity in Malaysia with growing number of tournaments organized nationwide. Currently, Ideal Pro Event, one of the paintball organizer found difficulties to pair a suitable opponent to against one another in a tournament. This is largely due to the manual matchmaking method that only randomly matches one team with another. Consequently, it is crucial to ensure a balanced tournament bracket where eventual winners and losers not facing one another in the very first round. This study proposes an intelligent matchmaking using Particle Swarm Optimization (PSO) and tournament management system for paintball organizers. PSO is a swarm intelligence algorithm that optimizes problems by gradually improving its current solutions, therefore countenancing the tournament bracket to be continually improved until the best is produced. Indirectly, through the development of the system, it is consider as an intelligence business idea since it able to save time and enhance the company productivity. This algorithm has been tested using 3 size of population; 100, 1000 and 10,000. As a result, the speed of convergence is consistent and has not been affected through big population.N. N. S. Abdul Rahman, N.M. Saad, A. R. Abdullah, M. R. M. Hassan, M. S. S. M. Basir, N. S. M. Noor 1,2,4,6Faculty of Electronic and Computer Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia 2,3Center for Robotics and Industrial Automation, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia 3,5Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, MalaysiaLight rail transit (LRT), or fast tram is urban public transport using rolling stock similar to a tramway, but operating at a higher capacity, and often on an exclusive right-of-way. Indonesia as one of developing countries has been developed the LRT in two cities of Indonesia, Palembang and Jakarta. There are opinions toward the development of LRT, negative and positive opinions. To reveal the level of LRT development acceptance, this research uses machine learning approach to analyze the data which is gathered through social media. By conducting this paper, the data is modeled and classified in order to analyze the social sentiment towards the LRT development.Mohamad, S., Nasir, F.M., Sunar, M.S., Isa, K., Hanifa, R.M., Shah, S.M., Ribuan, M.N., Ahmad, A. 1,4,6,7,8Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Johor, Malaysia 1,2,3UTM-IRDA Digital Media Centre, Media and Game Innovation Centre of Excellence, Universiti Teknologi Malaysia, Johor, Malaysia 1,2,3Faculty of Computing, Universiti Teknologi Malaysia, Johor, Malaysia 5Centre for Diploma Studies, Universiti Tun Hussein Onn Malaysia, Johor, Malaysia 6Research Centre for Applied Electromagnetics, Universiti Tun Hussein Onn Malaysia, Johor, MalaysiaReceived Jan 31, 2018 Revised Apr 21, 2018 Accepted Apr 30, 2018 Bluetooth is an emerging mobile ad-hoc network that accredits wireless communication to connect various short range devices. A single hop network called piconet is the basic communication topology of bluetooth which allows only eight active devices for communication among them seven are active slaves controlled by one master. Multiple piconets are interconnected through a common node, known as Relay, to form a massive network called as Scatternet. It is obvious that the performance of Scatternet scheduling is highly dependent and directly proportionate with the performance of the Relay node. In contrary, by reducing the number of Relays, it may lead to poor performance, since every Relay has to perform and support several piconet connections. The primary focus of this study is to observe the performance metrics that affects the inter-piconet scheduling since the Relay node’s role is like switch between multiple piconets. In this paper, we address and analyze the performance issues to be taken into consideration for efficient data flow in Scatternet based on Relay node.

Malay speech recognition for different ethnic speakers : An exploratory study

Speech technology has become an alternative medium of communication. It could help those on smart wheelchair to use their voice to ease their movements from one location to another. However, most of the speech technology that has been developed is based on the English language and limited for other languages. This project contributes to the literature by developing a program on speech technology for Malay speech recognition using Visual C# to determine the quality of the program in advancing the state-of-the-art. The developed program has been tested using the speech by 13 subjects from different ethnic backgrounds to evaluate its quality and limitations. Results indicate that the voice, including the volume, accent and word emphasis to be important elements in influencing the quality of recognition.

Making decision for the next step in dense crowd simulation using support vector machines

This paper presents a method to optimize the travel time of an intelligent agent finding its way through a simulated dense crowd by using Support Vector Machines (SVMs). While prior studies have used Social Force Model (SFM) for crowd simulation, a limitation of the model is that it does not allow the agent to make decision in getting to a specific point in a dense crowd in the shortest time possible. The next step refers to the temporary position before a final destination is reached and identifying a suitable next step in a dense crowd is challenging as there are many other moving agents that might block the path. Hence, to avoid formulating the decision of the agents next step to proceed to a target point in an explicit manner, we therefore resort to SVMs whereby the position and velocity of the nearby agents are used as the feature vectors and the next step position as the class label. The training data is trained a priori with feature vectors and class labels supplied by human subjects. In order to produce a higher accuracy of training model, the training data is duplicated by permutation process. During the simulation, we used SFM and multiple SVM training models to control the motion of the intelligent agent. The results of the simulation indicated that the combination of SFM+SVMs enabled the intelligent agent to reach the final destination faster than using SFM on its own.