Displaying all 16 publications

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  1. Yap, H.J., Tan, C.H., Sivadas, C.S., Wan, W.L., Taha, Z., Chang, S.W.
    Movement Health & Exercise, 2018;7(2):39-52.
    MyJurnal
    Virtual Reality (VR) is a technology that makes use of computer graphics,
    algorithms and special hardware to simulate the real world in real time. There
    are four main elements required to make a VR system a success, namely
    virtual world, immersion, sensory feedback and interactivity. The virtual
    world created must be as real as possible. Users should have a sense of
    immersion in the virtual world. Position tracking is usually incorporated into
    a VR system for visual, sound and force feedback on the users and the virtual
    objects in the VR world must be interact-able with the users. VR has proven
    to be effective in training and widely used in many areas, for example medical
    surgery, dental treatment, psychology treatment for phobia, engineering
    design, maintenance and repair, sports and many more. By implementing VR
    technology in training, users are able to reduce the training cost and time. VR
    training is also safer for users, as harsh environments can be simulated despite
    the environment and/or human factors. On the other hand, the physical
    facilities and infrastructures of the track cycling are very costly. In track
    cycling, the game field, known as a velodrome, requires a large space of area.
    It requires a huge budget and professional manpower to maintain these
    facilities. Therefore, the proposed spatial immersive track cycling simulator
    is invented to overcome these issues. The aim of this study is to simulate the
    velodrome track cycling in VR environment and synchronize with a 6 degreeof-freedom
    motion platform. The simulator is aimed to be low cost and
    minimal space requirement compared to actual velodrome. A trainee who
    undergoes VR track cycling simulator training wears a head-mounted-display (HMD) to visualize the VR environment. An actual bike will be mounted on
    the 6-DOF motion platform, which the platform will synchronize with the VR
    environment to simulate the track condition for the training purposes. An
    encoder is placed at the bicycle wheel to feedback the moving speed and
    synchronize the visualize feedback to the HMD.
  2. Dawal SZ, Taha Z
    J Hum Ergol (Tokyo), 2004 Dec;33(1-2):19-27.
    PMID: 17402505 DOI: 10.11183/jhe1972.33.19
    A survey was conducted to investigate the relationship between job satisfaction and job factors that affect work design in two automotives manufacturing companies in Malaysia. A set of multiple choices questionnaires was developed and data were collected by interviewing the employees at the production plant. Hundred and seventy male subjects between the ages of 18 to 40 years with the mean age of 26.8 and SD of 5.3 years and mean work experience of 6.5 and SD of 4.9 years took part in the survey. The survey focused on job factors, i.e. skill variety, task identity, task significance, autonomy and feedback. The results support the previous findings that job factors are significantly correlated to job satisfaction. Furthermore, it also highlights the significant influence of age, work experience and marital status.
  3. Dawal SZ, Taha Z
    Int J Occup Saf Ergon, 2006;12(3):267-80.
    PMID: 16984786
    A methodology was developed for diagnosing industrial work, which includes questionnaire, observation, measurements, data collection and statistical analysis. A survey was conducted to investigate the relationship between job satisfaction and factors that affect work design in 2 automotives manufacturing companies in Malaysia. A basic work design model was proposed. The aim of this model was to determine the factors that influence employees' perception towards their work. A set of multiple-choice questionnaires was developed and data was collected by interviewing employees at a production plant. The survey focused on job and environmental factors. The results supported the proposed model and showed that job and environmental factors were significantly related to job satisfaction. They highlighted the significant influence of age, work experience and marital status on job satisfaction. Further, environmental factors, especially the surroundings, context dependence and the building's function, also had a significant impact on job satisfaction.
  4. Dawal SZ, Taha Z
    J Hum Ergol (Tokyo), 2007 Dec;36(2):63-8.
    PMID: 18572797 DOI: 10.11183/jhe1972.36.2_63
    A methodology is developed in diagnosing the effect of job organizational factors on job satisfaction in two automotive industries in Malaysia. One hundred and seventy male subjects of age 18-40 years with the mean age of 26.8 and standard deviation (SD) of 5.3 years and the mean work experience of 6.5 years and SD of 4.9 years took part in the study. Five job organizational factors were tested in the study including job rotation, work method, training, problem solving and goal setting. A job organization questionnaire was designed and was based on respondents' perception in relation to job satisfaction. The results showed that job organization factors were significantly related to job satisfaction. Job rotation, work method, training and goal setting showed strong correlation with job satisfaction while problem solving had intermediate correlation in the first automotive industry. On the other hand, most job organization factors showed intermediate correlation with job satisfaction in the second automotive industry except the training factor which had low correlation with job satisfaction. These results highlight that job rotation, work methods, problem solving and goal setting are outstanding factors in the study of job satisfaction for automotive industries.
  5. Tahriri F, Dawal SZ, Taha Z
    ScientificWorldJournal, 2014;2014:505207.
    PMID: 24982962 DOI: 10.1155/2014/505207
    A new multiobjective dynamic fuzzy genetic algorithm is applied to solve a fuzzy mixed-model assembly line sequencing problem in which the primary goals are to minimize the total make-span and minimize the setup number simultaneously. Trapezoidal fuzzy numbers are implemented for variables such as operation and travelling time in order to generate results with higher accuracy and representative of real-case data. An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA) is proposed in order to solve this optimization model. In establishing the FAGA, five dynamic fuzzy parameter controllers are devised in which fuzzy expert experience controller (FEEC) is integrated with automatic learning dynamic fuzzy controller (ALDFC) technique. The enhanced algorithm dynamically adjusts the population size, number of generations, tournament candidate, crossover rate, and mutation rate compared with using fixed control parameters. The main idea is to improve the performance and effectiveness of existing GAs by dynamic adjustment and control of the five parameters. Verification and validation of the dynamic fuzzy GA are carried out by developing test-beds and testing using a multiobjective fuzzy mixed production assembly line sequencing optimization problem. The simulation results highlight that the performance and efficacy of the proposed novel optimization algorithm are more efficient than the performance of the standard genetic algorithm in mixed assembly line sequencing model.
  6. Zadry HR, Dawal SZ, Taha Z
    Int J Occup Saf Ergon, 2011;17(4):373-84.
    PMID: 22152503
    A study was conducted to investigate the effects of repetitive light tasks of low and high precision on upper limb muscles and brain activities. Surface electromyography (EMG) and electroencephalography (EEG) were used to measure the muscle and brain activity of 10 subjects. The results show that the root-mean-square (RMS) and mean power frquency (MPF) of the muscle activity and the mean power of the EEG alpha bands were higher on the high-precision task than on the low-precision one. There was also a high and significant correlation between upper limb muscle and brain activity during the tasks. The longer the time and the more precise the task, the more the subjects become fatigued both physically and mentally. Thus, these results could be potentially useful in managing fatigue, especially fatique related to muscle and mental workload.
  7. Zadry HR, Dawal SZ, Taha Z
    Int J Occup Saf Ergon, 2016 Sep;22(3):374-83.
    PMID: 27053140 DOI: 10.1080/10803548.2016.1150094
    This study was conducted to develop muscle and mental activities on repetitive precision tasks. A laboratory experiment was used to address the objectives. Surface electromyography was used to measure muscle activities from eight upper limb muscles, while electroencephalography recorded mental activities from six channels. Fourteen university students participated in the study. The results show that muscle and mental activities increase for all tasks, indicating the occurrence of muscle and mental fatigue. A linear relationship between muscle activity, mental activity and time was found while subjects were performing the task. Thus, models were developed using those variables. The models were found valid after validation using other students' and workers' data. Findings from this study can contribute as a reference for future studies investigating muscle and mental activity and can be applied in industry as guidelines to manage muscle and mental fatigue, especially to manage job schedules and rotation.
  8. Liu K, Wang H, Xiao J, Taha Z
    Comput Intell Neurosci, 2015;2015:158478.
    PMID: 25866500 DOI: 10.1155/2015/158478
    The purpose of this research is to analyse the relationship between nonlinear dynamic character and individuals' standing balance by the largest Lyapunov exponent, which is regarded as a metric for assessing standing balance. According to previous study, the largest Lyapunov exponent from centre of pressure time series could not well quantify the human balance ability. In this research, two improvements were made. Firstly, an external stimulus was applied to feet in the form of continuous horizontal sinusoidal motion by a moving platform. Secondly, a multiaccelerometer subsystem was adopted. Twenty healthy volunteers participated in this experiment. A new metric, coordinated largest Lyapunov exponent was proposed, which reflected the relationship of body segments by integrating multidimensional largest Lyapunov exponent values. By using this metric in actual standing performance under sinusoidal stimulus, an obvious relationship between the new metric and the actual balance ability was found in the majority of the subjects. These results show that the sinusoidal stimulus can make human balance characteristics more obvious, which is beneficial to assess balance, and balance is determined by the ability of coordinating all body segments.
  9. Taha Z, Jomoah IM, Zadry HR
    J Hum Ergol (Tokyo), 2009 Jun;38(1):27-32.
    PMID: 20034316 DOI: 10.11183/jhe.38.27
    This study presents a comparison of the anthropometric characteristics of 241 Malaysian and 646 Saudi Arabian males aged 20 to 30 years. The mean values, standard deviation (SD), and 5th and 95th percentile values of 26 measurements and 22 proportions of each group were given. The results showed that there were significant differences in a number of body dimensions between these populations, except for eye height and elbow height (standing) and height, eye height, shoulder height, and elbow height (sitting). These results are important for the ergonomic design of workstations, personal protective equipment, tools, interface systems and furniture: The presented data may be useful for providing a safer, more productive and user-friendly workplace for Malaysian and Saudi Arabian populations.
  10. Yap HJ, Taha Z, Dawal SZ, Chang SW
    PLoS One, 2014;9(10):e109692.
    PMID: 25360663 DOI: 10.1371/journal.pone.0109692
    Traditional robotic work cell design and programming are considered inefficient and outdated in current industrial and market demands. In this research, virtual reality (VR) technology is used to improve human-robot interface, whereby complicated commands or programming knowledge is not required. The proposed solution, known as VR-based Programming of a Robotic Work Cell (VR-Rocell), consists of two sub-programmes, which are VR-Robotic Work Cell Layout (VR-RoWL) and VR-based Robot Teaching System (VR-RoT). VR-RoWL is developed to assign the layout design for an industrial robotic work cell, whereby VR-RoT is developed to overcome safety issues and lack of trained personnel in robot programming. Simple and user-friendly interfaces are designed for inexperienced users to generate robot commands without damaging the robot or interrupting the production line. The user is able to attempt numerous times to attain an optimum solution. A case study is conducted in the Robotics Laboratory to assemble an electronics casing and it is found that the output models are compatible with commercial software without loss of information. Furthermore, the generated KUKA commands are workable when loaded into a commercial simulator. The operation of the actual robotic work cell shows that the errors may be due to the dynamics of the KUKA robot rather than the accuracy of the generated programme. Therefore, it is concluded that the virtual reality based solution approach can be implemented in an industrial robotic work cell.
  11. Samrat NH, Bin Ahmad N, Choudhury IA, Bin Taha Z
    ScientificWorldJournal, 2014;2014:436376.
    PMID: 24892049 DOI: 10.1155/2014/436376
    Today, the whole world faces a great challenge to overcome the environmental problems related to global energy production. Most of the islands throughout the world depend on fossil fuel importation with respect to energy production. Recent development and research on green energy sources can assure sustainable power supply for the islands. But unpredictable nature and high dependency on weather conditions are the main limitations of renewable energy sources. To overcome this drawback, different renewable sources and converters need to be integrated with each other. This paper proposes a standalone hybrid photovoltaic- (PV-) wave energy conversion system with energy storage. In the proposed hybrid system, control of the bidirectional buck-boost DC-DC converter (BBDC) is used to maintain the constant dc-link voltage. It also accumulates the excess hybrid power in the battery bank and supplies this power to the system load during the shortage of hybrid power. A three-phase complex vector control scheme voltage source inverter (VSI) is used to control the load side voltage in terms of the frequency and voltage amplitude. Based on the simulation results obtained from Matlab/Simulink, it has been found that the overall hybrid framework is capable of working under the variable weather and load conditions.
  12. Samrat NH, Ahmad N, Choudhury IA, Taha Z
    PLoS One, 2015;10(6):e0130678.
    PMID: 26121032 DOI: 10.1371/journal.pone.0130678
    Energy is one of the most important factors in the socioeconomic development of a country. In a developing country like Malaysia, the development of islands is mostly related to the availability of electric power. Power generated by renewable energy sources has recently become one of the most promising solutions for the electrification of islands and remote rural areas. But high dependency on weather conditions and the unpredictable nature of these renewable energy sources are the main drawbacks. To overcome this weakness, different green energy sources and power electronic converters need to be integrated with each other. This study presents a battery storage hybrid standalone photovoltaic-wind energy power supply system. In the proposed standalone hybrid system, a DC-DC buck-boost bidirectional converter controller is used to accumulates the surplus hybrid power in the battery bank and supplies this power to the load during the hybrid power shortage by maintaining the constant dc-link voltage. A three-phase voltage source inverter complex vector control scheme is used to control the load side voltage in terms of the voltage amplitude and frequency. Based on the simulation results obtained from MATLAB/Simulink, it has been found that the overall hybrid framework is capable of working under variable weather and load conditions.
  13. Hasan M, Hanafiah MM, Alhilfy IHH, Aeyad Taha Z
    PeerJ, 2021;9:e10614.
    PMID: 33520446 DOI: 10.7717/peerj.10614
    Background: Laser applications in agriculture have recently gained much interest due to improved plant characteristics following laser treatment before the sowing of seeds. In this study, maize seeds were exposed to different levels of laser treatment prior to sowing to improve their field performance. The aim of this study is to evaluate the impact of pre-sowing laser photobiomodulation on the field emergence and growth of treated maize seeds.

    Methods: The maize seeds were first photobiomodulated with two lasers: 1) a helium-neon (He-Ne) red laser (632.8 nm), and 2) a neodymium-doped yttrium aluminum garnet (Nd:YAG) green laser (532 nm). Following three replications of randomized complete block design (RCBD), four irradiation treatments were applied (45 s, 65 s, 85 s, and 105 s) at two power intensities (2 mW/cm2 and 4 mW/cm2).

    Results: Based on the results, maize seeds pretreated with a green laser and 2 mW/cm2 power intensity for 105 s exhibited the highest rate of seed emergence (96%) compared to the untreated control seeds with a lower seed emergence rate (62.5%). Furthermore, maize seeds treated with a red laser for 45 s showed an increased vigor index compared to the other treatment options and the control (P 

  14. Sudheer S, Taha Z, Manickam S, Ali A, Cheng PG
    Fungal Biol, 2018 05;122(5):293-301.
    PMID: 29665955 DOI: 10.1016/j.funbio.2018.01.007
    Following the importance of antler-type fruiting bodies of Ganoderma lucidum, in this study, the impact of main growth parameters such as ventilation and light on the development of antler-type fruiting bodies has been investigated together with the determination of physico-chemical properties of antler fruiting bodies. For this, the primordia bags of G. lucidum were kept under controlled ventilation to adjust the CO2 produced by the mushrooms owing to its respiration under light and dark conditions. The bioactive compounds such as phenolics, flavonoids, water-soluble polysaccharides and ganoderic acid showed a two-fold increase in the antler-type fruiting bodies as compared to normal kidney-shaped fruiting bodies. It is assumed from this study that the antler type fruiting bodies are developed due to restricted ventilation which causes an increase in the level of CO2 gas in the air as a result of respiration of mushroom. The shape and colour of antler fruiting bodies again dependent on the light provided in the growth chamber. This study also proves that with the manipulation of light and ventilation antler-type fruiting bodies of G. lucidum could be developed with higher quantity of bioactive compounds and with higher antioxidant potential.
  15. Muazu Musa R, P P Abdul Majeed A, Taha Z, Chang SW, Ab Nasir AF, Abdullah MR
    PLoS One, 2019;14(1):e0209638.
    PMID: 30605456 DOI: 10.1371/journal.pone.0209638
    k-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. However, the application of k-NN for prediction and classification in specific sport is still in its infancy. The present study classified and predicted high and low potential archers from a set of physical fitness variables trained on a variation of k-NN algorithms and logistic regression. 50 youth archers with the mean age and standard deviation of (17.0 ± 0.56) years drawn from various archery programmes completed a one end archery shooting score test. Standard fitness measurements of the handgrip, vertical jump, standing broad jump, static balance, upper muscle strength and the core muscle strength were conducted. Multiple linear regression was utilised to ascertain the significant variables that affect the shooting score. It was demonstrated from the analysis that core muscle strength and vertical jump were statistically significant. Hierarchical agglomerative cluster analysis (HACA) was used to cluster the archers based on the significant variables identified. k-NN model variations, i.e., fine, medium, coarse, cosine, cubic and weighted functions as well as logistic regression, were trained based on the significant performance variables. The HACA clustered the archers into high potential archers (HPA) and low potential archers (LPA). The weighted k-NN outperformed all the tested models at itdemonstrated reasonably good classification on the evaluated indicators with an accuracy of 82.5 ± 4.75% for the prediction of the HPA and the LPA. Moreover, the performance of the classifiers was further investigated against fresh data, which also indicates the efficacy of the weighted k-NN model. These findings could be valuable to coaches and sports managers to recognise high potential archers from a combination of the selected few physical fitness performance indicators identified which would subsequently save cost, time and energy for a talent identification programme.
  16. Taha Z, Musa RM, P P Abdul Majeed A, Alim MM, Abdullah MR
    Hum Mov Sci, 2018 Feb;57:184-193.
    PMID: 29248809 DOI: 10.1016/j.humov.2017.12.008
    Support Vector Machine (SVM) has been shown to be an effective learning algorithm for classification and prediction. However, the application of SVM for prediction and classification in specific sport has rarely been used to quantify/discriminate low and high-performance athletes. The present study classified and predicted high and low-potential archers from a set of fitness and motor ability variables trained on different SVMs kernel algorithms. 50 youth archers with the mean age and standard deviation of 17.0 ± 0.6 years drawn from various archery programmes completed a six arrows shooting score test. Standard fitness and ability measurements namely hand grip, vertical jump, standing broad jump, static balance, upper muscle strength and the core muscle strength were also recorded. Hierarchical agglomerative cluster analysis (HACA) was used to cluster the archers based on the performance variables tested. SVM models with linear, quadratic, cubic, fine RBF, medium RBF, as well as the coarse RBF kernel functions, were trained based on the measured performance variables. The HACA clustered the archers into high-potential archers (HPA) and low-potential archers (LPA), respectively. The linear, quadratic, cubic, as well as the medium RBF kernel functions models, demonstrated reasonably excellent classification accuracy of 97.5% and 2.5% error rate for the prediction of the HPA and the LPA. The findings of this investigation can be valuable to coaches and sports managers to recognise high potential athletes from a combination of the selected few measured fitness and motor ability performance variables examined which would consequently save cost, time and effort during talent identification programme.
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