Abd Samad Hasan Basari

Exam timetabling using graph colouring approach

Timetabling at large covering many different types of problems which have their own unique characteristics. In education, the three most common academic timetabling problems are school timetable, university timetable and exam timetable. Exam timetable is crucial but difficult to be done manually due to the complexity of the problem. The main problem includes dual academic calendar, increasing student enrolments and limitations of resources. This study presents a solution method for exam timetable problem in centre for foundation studies and extension education (FOSEE), Multimedia University, Malaysia. The method of solution is a heuristic approach that include graph colouring, cluster heuristic and sequential heuristic.

A New Image Encryption Approach using The Integration of A Shifting Technique and The Aes Algorithm

In this paper, a new image encryption technique is proposed based on the integration of shifted image blocks and basic AES, where the shifted algorithm technique is used to divide the image into blocks. Each block consists of number of pixels, and these blocks are shuffled by using a shift technique that moves the rows and columns of the original image in such a way to produce a shifted image. This shifted image is then used as an input image to the AES algorithm to encrypt the pixels of the shifted image. In order to evaluate the performance, the proposed integration technique and AES algorithm were measured through a series of tests. These tests included a histogram analysis, information entropy, correlation analysis, differential analysis. Experimental results showed that the new integration technique has satisfactory security and is more efficient than using the AES algorithm alone without the shifting algorithm which makes it a good technique for the encryption of multimedia data. The results showed that the histogram of an encrypted image produced a uniform distribution, which is very different from the histogram of the plain image, and the correlation among image pixels was significantly decreased by using the integration technique and a higher entropy was achieved.

An Application of SMS Technology for Customer Service Centre

SMS technology is designed originally as a communication tool between a service provider and its users. However in the last few years this technology has allowed users to communicate among them. The vast growth of mobile technology is also one of the elements that help in utilizing this technology. Users are able to get very fast information anywhere. In order to utilize this technology, CeS-LAP is developed to improve the current services provided by Lembaga Air Perak (LAP). This system is aimed at providing better complaint system, customer information system and expectantly an alternative way for customer to check their unpaid bill.

The Utilization of Template Matching Method for License Plate Recognition: A Case Study in Malaysia

Automatic License plate detection and recognition system is special form of optical character recognition and has been an active research domain in image processing field. However, the accuracy is varied due to different styles of number plates endorsed. Besides, the characters on Malaysia license plate are in one or two lines. Thus, the proposed license plate recognition (LPR) technique of this research is able to achieve the best recognition performance based on Malaysia license plate vehicle registration number characters. This paper presents a study of applying the template matching method for character image recognition. The database of characters and license plate image has been created by collecting images from various type of car. The initial pre-processing involves image enhancement, binarization, filtering and segmenting of license plate. There are 100 license plates that contain 693 characters have been tested, and the result shown that 92.78 % of all characters is correctly recognized. Thus, template matching can be classified as one of the promising algorithm for recognizing Malaysia license plate.

Application of multi-step time series prediction for industrial equipment prognostic

The use of prognostics is critically to be implemented in industrial. This paper presents an application of multi-step time series prediction to support industrial equipment prognostic. An artificial neural network technique with sliding window is considered for the multi-step prediction which is able to predict the series of future equipment condition. The structure of prognostic application is presented. The feasibility of this prediction application was demonstrated by applying real condition monitoring data of industrial equipment.

The Utilisation of Dijkstraâs Algorithm to Assist Evacuation Route in Higher and Close Building

Finding a shortest path in a high rise building during critical incident or evacuation is facing two main issues which are evacuees find difficulties to find the best routes and their behavior makes the process more difficult. These problems are important since it is related to the humans life. By providing the shortest path and control the evacuee behavior, these can lead to successfulness of evacuation. To overcome these issues, two main objectives have been carried on which is initiated by identifying the shortest path algorithm for evacuation. Then follows by design and develop an evacuation preparedness model via shortest path algorithm to choose a suitable exit route to evacuate. Three steps are involved to achieve the objectives. The first step is Building Layout Plan, followed by creating the Visibility Graph and finally implements Dijkstra Algorithm to find the shortest path. Based on the experimental study, the result shows that Dijkstra Algorithm has produced a significant route to exit the building safely. Even though there are other factors need to be considered, this preliminary result has shown a promising outcome which can be extended to improve the robustness of the algorithm. In conclusion, the obtained shortest path is believed can assist evacuee to choose a suitable exit route to evacuate safely.

Preliminary design and development of industrial inspection e-monitoring system

This paper discusses on the initial design and development of industrial inspection e-monitoring system (IIEMS). IIEMS is an intelligent web-based system that monitors defect occurs in the production line. The defect is collected from targeted machines, which are considered as the most critical one. By setting all the related parameters, defects will be logged into the system. Then, the system will send a message through email and personal data assistant (PDA) to the person in charge. An artificial neural network (ANN) will be used to classify the severity of the defect. According to the result, appropriate actions are performed. Throughout this paper, initial analysis, design and development of the system are explained. This includes the requirement analysis, logical and interface design. In the development phase, an early stage of the system development is reported. An overview of the system prototype and some observations based on the initial results are also discussed.

Efficient cluster head selection method to improve the lifetime in wireless sensor networks

In wireless sensor networks (WSNs), environmental event monitoring and tracking systems require efficient routing protocols in order to offer reliable controlling of data traffic. This could help in an efficient utilisation of knowledge obtained from data to provide proper decision under abnormal environment conditions. The efficiency and reliability are the main challenges of routing data in WSNs. LEACH routing protocol is found to provide better performance compared to other protocols due to its hierarchical nature. However, since LEACH is a single-hop protocol, sensors located far from the base station (BS) consume more energy for data transmission and die early, causing a serious reduction in the network performance in terms of lifetime. Moreover, it cannot ensure that sensors have a uniform distribution in the sensing area. In this paper, an improved version of LEACH is presented based on node energy, distance, density, and the use of gravity centre and mass centre for selecting cluster heads (CHs). Simulation results show that the enhanced version is able to improve the network lifetime in comparison with the traditional LEACH protocol. The results confirmed that the proposed enhancement provides a proper decision in selecting CHs in high density areas.

Ant Colony-Dijkstra’s Algorithm for Evacuation Preparedness in High Rise Buildings

The critical tasks during evacuation process is how to find the right ways in order to escape from the danger place to a safe place. In process of finding the right ways, most of the evacuees are panicked. Subsequently, make the process more difficult. With that occurrence, the main objectives of this research study are to identify the suitable shortest path algorithm for evacuation in high rise building, then design and develop an evacuation route via shortest path algorithm in order to obtain an exit route to evacuate by using Optimization and Artificial Intelligence Technique. The objectives that involved are to help the evacuees to find the best routes during evacuation process. Six phases of methods are raised to accomplish the objectives by utilizing the Dijkstra and Ant Colony Optimization Algorithm. The first step is started from the original building layout. Then transform the layout into 2D layout plan. After that, import the matrix data to generate graph theory. Next step is utilizing the both approaches to achieve the shortest path. The preliminary result has shown positive result which can deliver the shortest path to help evacuees.

Enhancement of Nurse Scheduling Steps Using Particle Swarm Optimization

Allocating of working schedule, especially for shift approach is hard to ensure its fairness among them. In the case of nurse scheduling, to set up the time table for each available nurse is time consuming and complicated, which consider many factors including rules, regulation and human factor. Moreover, most nurses are women, which have personnel constraints and maternity leave factors. The undesirable schedule can affect the nurse productivity, social life and the absenteeism can significantly as well affect the patient’s life. This paper aimed to enhance the scheduling process by utilizing the particle swarm optimization in order to generate an intelligent nurse schedule. The result shows that the multiple initial schedules can be generated and can be selected with the lowest cost of constraint violation.