Search

Relieving urban traffic congestion has always been an urgent call in a dynamic traffic network. The objective of this research is to control the traffic flow within a traffic network consists of multiple signalized intersections with traffic ramp. The massive traffic network problem is dealt through Q-learning actuated traffic signalization (QLTS), where the traffic phases will be monitored as immediate actions can be taken during congestion to minimize the number of vehicles in queue. QLTS is tested under two cases and has better performance than common fixed-time traffic signalization (FTS). When dealing with the ramp flow, QLTS has flexibility to change the traffic signals according to the traffic conditions and necessity.

This work aims to explore the potential to minimize traffic congestion using a non-deterministic algorithm. Conventionally, the deterministic algorithm such as fuzzy logic was proposed as the computational algorithm to compute the optimum traffic signal timing for minimizing vehicles in queue and travel delay. However, it is very difficult to define the suitable number of fuzzy rules that are able to cover the all possibilities of traffic flow changes since the natural traffic flow behavior is dynamic. Besides, the inherent deterministic behavior limits the algorithm to explore the solution space in searching for the optimum traffic solution. In other words, the deterministic algorithm will not provide other solution with the same input. Therefore, genetic algorithm, a non-deterministic algorithm, is proposed to optimize the traffic signalization. A benchmarked 3×3 grid traffic network is developed as the testbed to examine the robustness of the proposed GA. Each intersection is integrated with a GA based signal controller or known as agent to form a multi-agent system. Each agent has the autonomy in controlling their own traffic intersection and they will share their local traffic information to their downstream intersections. The performance of the proposed GA is compared with the conventional fuzzy logic. The simulation results show the proposed GA improves the performance about 6.6 % in minimizing vehicles in queue and travel delay as compared to the conventional fuzzy logic.

This paper presents a metaheuristic-based temperature controller for an exothermic batch process. Developing a suitable temperature controller for an exothermic process is a challenging task because large amount of heat is released rapidly during the process. The exothermic behavior will further increase the reaction rate and cause more heat to be liberated. As the result, the improper temperature control might cause the reaction becomes unstable and consequently poses safety concern to the plant personnel and equipment. The conventional non-metaheuristic-based controller, such as fuzzy logic requires empirical data or knowledge about the total amount heat released while developing its fuzzy rules and membership functions for precision control. However, the detailed kinetic model of the heat released is unable to be obtained since there are several unobservable parameters during the process, such as the energy held in the reactor and jacket walls. Therefore, particle swarm optimization algorithm (PSO) is proposed as the controller to maintain the reactor temperature at the desired trajectory by manipulating the inlet jacket fluid temperature and flow rate. The simulation results show the proposed PSO produces better performances in terms of minimizing fluctuation in control actions and overshooting as compared with the conventional fuzzy logic controller.

Vehicles have become a daily needs for all of us and it is normal that every family is having at least one vehicle at their home. This leads to the increased of accidents and vehicular ad hoc network (VANET) is an approach invented to tackle with this problem. In order to study the algorithm in VANET, a mobility simulator is needed for simulation. SUMO is proved to be a good simulation tool for VANET while MATLAB is good for future algorithm development. To develop a good simulation platform, modification on SUMO files are necessary. This paper discusses on the steps for creating a left-hand traffic (LHT) simulation file that is suitable to be used in Malaysia. Most of the hard work in creating LHT simulation is to modify the road connection and traffic light files. This paper also showed the results of the simulation after SUMO files modification. It is recommended that user make a good decision in deciding the map for simulation. Smaller map is easier to modify, while maintaining the same map for the whole VANET development can prevent a start over on the SUMO files modification process.

The emerging of the intelligent transportation system especially in the research area of traffic surveillance and solving traffic congestions, become notably crucial for traffic operators in the aim of achieving efficient vehicle flow. However, behavioural manoeuvres that describe the pattern of vehicles movements and change of the vehicle flow are not sufficiently modeled based on the conventional inductive-loop traffic sensors. These behavioural manoeuvres are useful for interpreting the indepth study of traffic pattern in a traffic network. Hence, with the advancement of the available vehicle tracking system, vehicle trajectory dataset is selected as suitable candidate input for the traffic pattern extraction. The implementation of k-means and fuzzy c-means (FCM) clustering algorithm for vehicle flow analyzing task is served as focus in this paper. Similarity function based on Longest Common Subsequence (LCSS) is implemented to measure the similarity among the trajectories before clustering is performed. Rand Index (RI) is computed to evaluate the clustering performance of two sets trajectories with two different traffic scenes by comparing the simulated clustering result with the ground-truth result.

This work aims to minimize average delay for signalized traffic network along Jalan UMS under oversaturated condition using decentralized genetic algorithm (DGA). Relieving traffic network is a key challenge for a nation for improving its socio-economic systems and welfare to society. Control the traffic signal timing becomes a cost effective solution to reduce congestion since the space constraint limits the authority to build more infrastructures in city. Regrettably, most of the current traffic signal control systems are not yet optimized. They are preset based on historical traffic data; thus they are inadequate to cope with the dynamic changes in real traffic scenario. Therefore, this work proposes DGA to optimize the traffic network signal for reducing average delay during the morning peak hour. A comprehensive traffic model based on Public Works Department, Malaysia has been developed as the platform. The average delay experienced by vehicles to traverse the crossed intersection during morning peak hour is used as the performance metric to evaluate performances of the proposed algorithm. Simulation results show developed DGA is able to reduce the average network delay by optimizing the traffic signal.

The effects of perforated plates with different percentage of perforation affecting the sound absorption coefficient of coir fibre acoustic panels were investigated. Two types of perforated plates of 6.93 and 19.24% perforation were combined with the similar coir fibre layer. Acoustic tests for measuring the sound absorption were conducted in the reverberation room according to the ISO 354:2003 standard. The based coir fibre panel showed to possess good sound absorption characteristics from intermediate to high frequency range (800-2000 Hz). Perforated plates (6.93 and 19.24%) with coir fibre panel were found to achieve maximum sound absorption coefficients of 0.77 and 0.63 at 2000 Hz, respectively. As frequency increased to 4000 Hz, the sound absorption coefficient for the higher percentage perforation produced a higher sound absorption coefficient value.

This work aims to minimize average delay for an urban signalized intersection under oversaturated condition using genetic algorithm (GA). Relieving urban traffic congestion is an urgent call for traffic engineering. The effectiveness of traffic signalization is one of the key solutions to reduce congestion, but regrettably the current traffic signal control system is not fully optimized for handling oversaturated condition. Therefore, this work proposes GA to optimize traffic signals for reducing average delay at a signalized crossed intersection under oversaturated condition. A comprehensive traffic model based on Public Works Department, Malaysia has been developed as the platform. The average delay experienced by vehicles to traverse the crossed intersection is used as the performance metric to evaluate performances of the proposed algorithm. Simulation results show GA is able to control the traffic signals for minimizing the average delay to 55 sec/veh or equivalent to level of service (LOS) D.

Continuous increased of on-road vehicles has also increased the possibility of accidents, most of it caused by human errors. Hence, a solution has been proposed, which is to make vehicles more intelligent through research on vehicular ad hoc networks (VANETs). Currently, simulation on VANETs has been widely studied. It is known that networking and mobility component are required to form a VANET. In this paper, mobility component is focused and discussed. A few mobility simulators have been introduced with some citations of related works for each of the simulators. MATLAB and Simulation of Urban Mobility (SUMO) are further used for VANET simulation respectively. At the same time, TraCI4Matlab, an Application Programming Interface (API) developed in MATLAB that allows communication between any applications written in MATLAB and SUMO simulator is also discussed.

Relieving traffic congestion is an urgent call for traffic engineering. Although various adaptive control strategies have been reported in literature to reduce the travel delay, most of them are not tested under oversaturated condition, where the traffic demand is higher than the road capacity. Therefore, this work proposes genetic algorithm (GA) to optimize the traffic signals for reducing the average delay at the at-grade crossed intersection under oversaturated condition. A comprehensive traffic model has been developed as the testbed. The average delay experienced by every vehicle to traverse the intersection is taken as performance metric to evaluate the performances of the formulated GA. The simulation results show the formulated GA is able to optimize the traffic signals and minimize the average delay of the intersection to 55.2 sec or equivalent to level-of-service (LOS) D.

Traffic data obtained from surveillance system has been vital for traffic operators to monitor the traffic flow at a traffic intersection. However, detailed information of the traffic flow such as the behavioural manoeuvres is not sufficiently provided by the inductive-loop traffic detectors. Thus, vehicles trajectory dataset is selected as traffic data input in traffic simulation for modelling the traffic flow. In this paper, clustering on the vehicle trajectory dataset is simulated to group the data via similarity function based on Longest Common Subsequence (LCSS). To evaluate the clustering result, Rand Index (RI) is implemented to compare the simulated result with the ground-truth result.

This study investigates and characterizes the impact damage of woven E-glass Fibre Reinforced Polymer (GFRP) composite under drop weight impact event. The experimental tests are performed according to ASTM standards (D7136/D 7136M-05 and D5687/D 5687M-05) utilizing a blunt conical impactor and drop weight testing rig. Four groups of specimens have been utilized for the impact event with various drop height. The event resulted in a series of linear damage growth that is proportional to the absorbed impact energy. From the micrographic observation, the specimen damage is found to form cross shape cracking on the front surface or known as effect of orientation of delamination.

Post fracture analysis is an important methodology to provide enormous important physical insights to the failure mechanisms of a material. The novelty of micrographic approach or technique for linear-elastic fracture characterization of a metallic solid in particular has adopted material forensic techniques for post fracture evaluation through microscopic measurement of crack initiation zone using the Infinite Focus Microscope (IFM) and the Scanning Electron Microscope (SEM). The IFM has been utilized to analyze the surface roughness profile of the critical fractured surfaces and identify the transition crack initiation zone to develop over a small region of crack increment of about 17 microns. Alternatively, the high magnification SEM could also measure the band width or the incremental crack length at initiation to about 10 microns, in addition to the capability to reveal the microstructures of the crack; namely river patterns and the feather marks, which appear as trademarks leftover due to cleavage linear-elastic fracture. © Asian Network for Scientific Information.

The development of an efficient traffic flow monitoring system has been the main focus for many researchers working in the field. Due to the rapid development in urbanization, the complexity of traffic intersections provides challenges for researchers to detect the underlying traffic scenes. With the emerging video based surveillance system, vehicle trajectory can be extracted for observation and prediction via behavioral pattern learning. Prior to the learning, clustering of the extracted vehicle trajectory data is performed to group the data based on similarity measures. In this paper, the implementation of clustering algorithm on the trajectory data is analyzed and issues concerning the trajectory clustering are discussed.

Relieving urban traffic congestion has always been an urgent call in a dynamic traffic network. The objective of this research is to control the traffic flow within a traffic network consists of multiple signalized intersections with traffic ramp. The massive traffic network problem is dealt through Q-learning actuated traffic signalization (QLTS), where the traffic phases will be monitored so that immediate actions can be taken when congestion is happening to minimize the number of vehicles in queue. QLTS has better performance than the existing common fixed-time traffic signalization (FTS) in dealing with the ramp flow due to its flexibility in changing the traffic signal with accordance to the traffic conditions and necessity.

Traffic jam has become a common scene nowadays, due to the rapid increase of road users in the past few years. To solve this problem, the design of traffic control is required. Traffic control parameter can be determined from the traffic flow behavior of the traffic intersection. Currently, most of the traffic control system in Malaysia is using Webster Model, which its green time duration is pre-determined by collecting the data from the traffic intersection. Most of the waiting time at the intersection is wasted due to the constant green time duration. The aim of this paper is to optimize the average waiting time of a traffic intersection via a developed Fuzzy Logic traffic control system. Traffic light simulator hardware is built to deal with the difficulties of working in a real environment and to investigate the performance of the traffic control system. Conventional traffic control system, Webster Model and the Fuzzy Logic controller will be applied into the traffic signal simulator in order to investigate their performance.

An experimental investigation of the seawater effect on the degradation of GFRP composite material with respect to water absorption was conducted. The GFRP specimens were exposed to seawater and weather environment. Water absorption analysis was conducted to investigate the moisture uptake and degradation of woven GFRP. The woven GFRP percentage weight gain due to moisture uptake were 0, 0.253, 0.513, 0.752, 0.732, 0.752, and 0.997 % of the initial weight, after 1, 2, 3, 5, 8, 48, and 168 immersion hours. Degradation of GFRP was also found to correlate to the corrosion and uptake of seawater at the fibre/matrix interface.

Resin MUF yang boleh larut dalam air digunakan dengan meluas sebagai bahan pelekat dalam industri kayu, teknologi salutan, industri kertas dan merupakan bahan utama dalam penghasilan barangan dapur plastik. Sifat resin yang berbeza diperlukan dalam aplikasi yang berlainan. Sifat–sifat resin ini dipengaruhi oleh beberapa faktor iaitu nisbah mol antara formaldehid dengan melamina/urea pada setiap peringkat tindak balas dan bilangan peringkat tindak balas di mana sebatian amino ditindak balaskan. Sifat–sifat resin yang penting ialah kestabilan resin, kelarutan dalam air yang tinggi dan tempoh pengerasan yang pendek. Kajian lepas telah menghasilkan resin MUF dengan sifat–sifat ini, walau bagaimanapun ia tidak mempunyai kandungan melamina dan urea yang mencukupi, untuk menyeimbangi kos dan prestasi. Selain itu haba juga diperlukan untuk membantu memendekkan tempoh pengerasan resin. Dalam kajian ini, kesan perubahan formula ke atas sifat–sifat resin seperti kestabilan resin, kelarutan dalam dan tempoh pengerasan pada suhu bilik dikaji. Keputusan menunjukkan bahawa kestabilan resin meningkat apabila bilangan peringkat tindak balas dan kandungan melamina meningkat. Walau bagaimanapun tempoh pengerasan turut dipanjangkan. Formula ini mempunyai kandungan melamina dan urea yang mencukupi, di mana ia berkos rendah berbanding resin melamina-formaldehid (MF), tapi dengan prestasi yang baik. Kata kunci: Melamina-urea-formaldehid (MUF); urea; melamina; formaldehid MUF resin is widely used as an adhesive in wood industries, coating technology, paper industries and a main material in kitchenware production. In different application, various MUF resin properties are required. The MUF resin properties are affected by several factors, for example mole ratio of formaldehyde to melamine/urea at each reaction stage and number of reaction stages where the amino compounds are reacted. Previous researches have developed MUF resin with these properties, however the formulation lack sufficient amount of melamine or urea to balance the cost and performance. Furthermore, shorter curing period could only be obtained with the help of external heat. In this research, effects of formula variation on resin properties such as resin storage stability, solubility in water and curing period at room temperature are investigated. The results showed that in 3-reaction stage of MUF resin process, the ratio of formaldehyde to urea/melamine in each reaction stage has caused significant increases in MUF resin curing period, solubility in water and resin storage stability. These formulations contains sufficient amount of melamine and urea, which lowered the cost and yet maintaining good performance as compared to melamine–formaldehyde (MF) resin. Key words: Melamine-urea-formaldehyde (MUF); urea; melamine; formaldehyde

The aim of this research is to simplify an existing model (model-1) of solar flux radiation containing many parameters as compared to a new mathematical model (model-2) using just two independent variables, time and roof's angle of inclination. The impact of the solar radiation on the surface of the roof in Sabah (state of Malaysia) has been examined under different orientations and slopes by means of model-1 at different time of the day. Furthermore, the data of solar flux radiation computed using model-1 has been explored to develop the model-2 from which the correlation coefficient of 0.87 was achieved using regression analysis. It has been proven statistically using the t-test that the difference between the existing model-1 and the proposed model-2 is not significant. The new mathematical model-2 developed can be applied for a double-pitched roof at any given orientation in the area of Sabah only, where the slope of the roof and the local time have to be taken from 0 to 75 degrees and from 7 hrs to 17 hrs, respectively. Additionally, the method used in the derivation of this new model can also be employed for other states of Malaysia as well as other countries. From a technical point of view, the architects or designers can use the proposed model for a quick estimation of solar flux radiation, to identify the type of insulations to be applied under the roof or above the ceiling, as well as the size area of the natural ventilation and the decision-making on the thermal system to be employed, either as an active or a passive cooling system. Copyright © 2008 The Berkeley Electronic Press.

This paper reports on the fracture behavior of a hard wood known as Selanga Batu (Shorea spp) with different structure under tensile stress at various strain rates (10-100mm/min). It was found that the structure had significant effect on the modulus of elasticity and yield strength of the wood. Wood with high percentage of ray parenchyma exhibited lower modulus of elasticity and yield strength. Ray parenchyma in wood acted as the weakest plane for crack to propagate in a step-wise manner. However, large variation found in test results make it not possible to evaluate whether the strain rate affects the ultimate strength and the fracture strain. Since the values of the modulus of elasticity obtained at a given strain rate had very small variation, the effect of strain rate on the modulus of elasticity and yield strength could be examined. It was found that the strain rate did not affect the modulus of elasticity and the yield strength of the wood.