Muhammad Aizat Abu Bakar
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Preferred name
Muhammad Aizat Abu Bakar
Official Name
Muhammad Aizat , Abu Bakar
Alternative Name
Bakar, M. A.A.
Bakar, Muhammad Aizat Abu
Bakar, M. A.Abu
Bin Abu Bakar, Muhammad Aizat
Main Affiliation
Scopus Author ID
57190940268
Researcher ID
EMX-4423-2022

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  • Publication
    The effects of interactional justice and OCB on burnout: Empirical evidences among housemen in Malaysia public hospital
    ( 2021-05-03)
    Sulaiman M.K.
    ;
    Ummi Naiemah Saraih
    ;
    Sakdan M.F.
    ;
    Aminudin Anuar
    ;
    Muhammad Aizat Abu Bakar
    ;
    Muhammad Nur Aiman Uda
    ;
    Asyraf Hakimi Abu Bakar
    This study investigates the effect of interactional justice (IJ) and organizational citizenship behaviour (OCB) on burnout (BO) among housemen in Malaysia Public Hospital. This study involve 15 urban hospital in Malaysia. Quantitative method was used in the study to analyse the questionnaire. The questionnaire will distribute to the 800 housemen in 15 urban public hospital in Malaysia. The questionnaire will analyze by using PLS-SEM statistical tool. From the analyze the hypothesis are accepted and significant. The IJ and OCB can reduce the value of BO among housemen in public hospital. The information based on this study will be a valuable guide to the Ministry of Health (MoH) in and decrease the level of burnout among housemen in Malaysia. The hospital management also can use the information based on the study to upgrade the policy and standard operating procedure (SOP) towards the management of the housemen. Also, this study can be the basis to help the Malaysian housemen to identify the causes of burnout and improve their perspectives upon this issue. Not only that, knowing the dimensions of burnout and its causes can create a positive vibe in the medical environment, particularly among the ministry, hospital management, housemen, and patients.
  • Publication
    Fabrication of mandible fracture plate by indirect additive manufacturing
    ( 2017-10-29)
    Muhammad Aizat Abu Bakar
    ;
    Shah Fenner Khan Mohamad Khan
    Bone fracture is a serious skeletal injury due to accidents and fragility of the bones at a certain age. In order to accelerate fracture healing process, fracture bone plate is use to hold the fracture segment for more stability. The purpose of this study is to fabricate mandibular fracture plate by using indirect additive manufacturing methods in order to reduce time taken during bending and shaping the fracture fixation plate that conform to the anatomy of the fractured bone site. The design and analysis of the plates are performed using CATIA and ANSYS software. The 3D-CAD data were sent to an additive manufacturing machine (fused filament fabricated) to generate master pattern using PLA and the mould were fabricated using Plaster of Paris. A melt ZAMAK 3 was poured directly into the moulds, and left it until completely harden. 3point bending test was performed on the prototype plate using universal testing machine. Stress-strain curve shows the graph exhibited a linear relationship of stress-strain up to a strain value of 0.001. Specimens give a maximum yielding stress and then break before the conventional deflection. Since the maximum flexural stress and the breaking stress are far apart with a plateau stating at strain value of 0.003mm/mm in most specimens, the specimen's failure types are considered plastic failure mode. The average thickness and width are 1.65mm and 2.18mm respectively. The flexural modulus and flexural strength are 189.5GPa and 518.1MPa, respectively.
  • Publication
    IoT-based Carbon Monoxide (CO) Real-Time Warning System Application in Vehicles
    ( 2021-12-01)
    Kamarudin A.A.A.
    ;
    Nurul Syahirah Khalid
    ;
    Ibrahim I.I.
    ;
    Muhammad Aizat Abu Bakar
    ;
    Mahadi M.Z.
    ;
    Shukor S.A.A.
    ;
    Sukhairi Sudin
    ;
    Hasan M.Z.
    ;
    Mansor H.
    The project is about develop a system and application for detect the presence of Carbon Monoxide(CO) in car, since recently there are many cases of drowning while sleeping in car due to inhaling CO. The build system are able to detect the presence of CO and provide warning about level of CO to the users. It uses Blynk application to monitors level of CO inside the vehicle, MQ-9 gas sensor as the input sensor, ESP 8266 as medium to send data to the application via IoT-based and the level concentration of CO is displayed on the LCD in real-time displayed. For the output, it has 3 different condition based on the level concentration of CO. This project has been testing in six different situation. Based on the result, ambience air and in car with open window situation have lowest of CO level. Meanwhile, the highest of CO level is detect in smoke that are produced from fuel combustion of the car exhaust at distance 5 cm. Additionally, Principal Component Analysis (PCA) is used to analysed the ability of this system in clustering for each situation. As a result, PCA have clearly clustering data for every situation with the value of PC1 is 71.82% and PC2 is 28.18%, hence it is verified that the build system is able to applied in detecting the presence of CO. This project is believed able in helping to reduce the numbers of cases people drowning while sleeping due to inhaling CO in the car.
  • Publication
    Development of portable electronic nose for monitoring the atmospheric hazards in confined space
    ( 2018)
    Muhammad Aizat Abu Bakar
    This thesis discussed the development of electronic nose (e-nose) for monitoring the atmospheric hazards in a confined space. A confined space is large enough for workers to enter and perform work. It has a limited means of entry or exit and is not designed for continuous occupancy. It can contribute towards atmospheric hazards accidents that threaten the worker safety and industry progress. The most critical atmospheric hazards are too high or low oxygen in the atmosphere or atmospheres that contain flammable or toxic gases. Current technology to monitor the atmospheric hazards is applied before entering confined spaces called pre-entry by using a gas detector. This study aims to develop an instrument to assist workers during pre-entry for atmosphere testing. E-nose is the integration between hardware and software that can identify and classify different concentrations of gases in an air sample using pattern recognition techniques. The developed instrument using specific sensor arrays which were identified based on main hazardous gasses effective value. The temperature and humidity rates are also measured. The instrument utilizes multivariate statistical analysis that is Principal Component Analysis (PCA) for discriminate the different concentrations of gases. The Support Vector Machine (SVM) and Artificial Neural Network (ANN) that is Radial Basis Function (RBF) Network are used to classify the acquired data from the air sample. This will increase the instrument capability while the portability will minimize the size and operational complexity as well as increase user friendliness. The instrument was successfully developed, tested and calibrated using fixed concentrations of gases samples. The results proved that the developed instrument is able to discriminate an air sample using PCA with total variation for 99.42%, while the classifier success rate for SVM and RBF Network indicates at 99.28% for train performance and 98.33% for test performance. This will contribute significantly to acquiring a new and alternative method of using the instrument for monitoring the atmospheric hazards in confined space. This will ensure the safety of workers during work progress in a confined space.
  • Publication
    Transient stability for IEEE 14 bus power system using power world simulator
    ( 2020-01-07)
    Aminudin Anuar
    ;
    Wahab M.A.A.
    ;
    Syahrun Nizam Md Arshad @ Hashim
    ;
    Muhammad Izuan Fahmi Romli
    ;
    Asyraf Hakimi Abu Bakar
    ;
    Muhammad Aizat Abu Bakar
    Nowadays, demand for electricity is increasing every single day. This is due to the deep requirements in current economy. Generating electricity is an important element to ensuring a system operates in good condition and not being affected. At the same time, some problems have arisen as a phenomenon of transient stability. Hence, analysis needs to be done to control energy stability in rivalling current demand. Power system stability can be further divided into 3 sub-analysis starting with rotor angle stability which is the ability of synchronous machines of an interconnected power system to remain in synchronism after being subjected to a disturbance, voltage stability which is the ability of a power system to maintain steady voltages at all buses in the system after being subjected to a disturbance and also frequency stability which the ability of a power system to maintain steady frequency following a severe system disturbance resulting in a significant imbalance between generation and load. This analysis is used the IEEE Bus System 14 and analyzed using Power World Simulator (PWS) software. The variations in power angle, bus voltage and system frequency were studied with the help of three-phase balanced fault. Fast fault clearing times were analysed for a three-phase balanced fault in order to re-establish the stability of the system. Furthermore, impact of fault location on system was also computed to observe whether it affected the stability of the systems.
  • Publication
    2D LiDAR Based Reinforcement Learning for Multi-Target Path Planning in Unknown Environment
    ( 2023-01-01)
    Abdalmanan N.
    ;
    Kamarulzaman Kamarudin
    ;
    Muhammad Aizat Abu Bakar
    ;
    Mohd Hafiz Fazalul Rahiman
    ;
    Ammar Zakaria
    ;
    Syed Muhammad Mamduh Syed Zakaria
    ;
    Latifah Munirah Kamarudin
    Global path planning techniques have been widely employed in solving path planning problems, however they have been found to be unsuitable for unknown environments. Contrarily, the traditional Q-learning method, which is a common reinforcement learning approach for local path planning, is unable to complete the task for multiple targets. To address these limitations, this paper proposes a modified Q-learning method, called Vector Field Histogram based Q-learning (VFH-QL) utilized the VFH information in state space representation and reward function, based on a 2D LiDAR sensor. We compared the performance of our proposed method with the classical Q-learning method (CQL) through training experiments that were conducted in a simulated environment with a size of 400 square pixels, representing a 20-meter square map. The environment contained static obstacles and a single mobile robot. Two experiments were conducted: experiment A involved path planning for a single target, while experiment B involved path planning for multiple targets. The results of experiment A showed that VFH-QL method had 87.06% less training time and 99.98% better obstacle avoidance compared to CQL. In experiment B, VFH-QL method was found to have an average training time that was 95.69% less than that of the CQL method and 83.99% better path quality. The VFH-QL method was then evaluated using a benchmark dataset. The results indicated that the VFH-QL exhibited superior path quality, with efficiency of 94.89% and improvements of 96.91% and 96.69% over CQL and SARSA in the task of path planning for multiple targets in unknown environments.
      1  24
  • Publication
    Home automation system for security and temperature control using microcontroller based with smartphone applications
    ( 2021-05-03)
    Muhammad Aizat Abu Bakar
    ;
    Fazreen Mohd Yusoff
    ;
    Aminudin Anuar
    ;
    Muhammad Nur Aiman Uda
    ;
    Asyraf Hakimi Abu Bakar
    ;
    Muhammad Nur Afnan Uda
    ;
    Mohamed K. Sulaiman
    In Malaysia, the El-Nino phenomenon happen in 2016 was caused the used of home appliances increasing including air-conditioner, fan and air cooler which are used frequently compared to other appliances. This report presents prototype development System for Security and Temperature Control using Microcontroller Based with Smartphone Application. The system has beneficial to reduce human labour besides energy saving and designed for special purposes which can easily maintain the temperature in sorrounding home. The system used several sensors for input parts including LM35 for temperature sensor and Passive Infra-Red (PIR) sensor for motion detector. For security system, the Radio-frequency Identification (RFID) has been used as security input user identification. A microcontroller arduino uno type is used as the system brain in the process part. In outputs part, servo motor has been used as door application while Light-Emitting Diode (LED) and buzzer as indicators when RFID is in use. A smartphone application is implemented in the system which allows the user to control a device remotely including home appliances through Bluetooth module. All data will display in Liquid Crystal Display (LCD) as user reference.
      3
  • Publication
    2D LiDAR based reinforcement learning for Multi-Target path planning in unknown environment
    ( 2023)
    Nasr Abdalmanan
    ;
    Kamarulzaman Kamarudin
    ;
    Muhammad Aizat Abu Bakar
    ;
    Mohd Hafiz Fazalul Rahiman
    ;
    Ammar Zakaria
    ;
    Syed Muhammad Mamduh Syed Zakaria
    ;
    Latifah Munirah Kamarudin
    Global path planning techniques have been widely employed in solving path planning problems, however they have been found to be unsuitable for unknown environments. Contrarily, the traditional Q-learning method, which is a common reinforcement learning approach for local path planning, is unable to complete the task for multiple targets. To address these limitations, this paper proposes a modified Q-learning method, called Vector Field Histogram based Q-learning (VFH-QL) utilized the VFH information in state space representation and reward function, based on a 2D LiDAR sensor. We compared the performance of our proposed method with the classical Q-learning method (CQL) through training experiments that were conducted in a simulated environment with a size of 400 square pixels, representing a 20-meter square map. The environment contained static obstacles and a single mobile robot. Two experiments were conducted: experiment A involved path planning for a single target, while experiment B involved path planning for multiple targets. The results of experiment A showed that VFH-QL method had 87.06% less training time and 99.98% better obstacle avoidance compared to CQL. In experiment B, VFH-QL method was found to have an average training time that was 95.69% less than that of the CQL method and 83.99% better path quality. The VFH-QL method was then evaluated using a benchmark dataset. The results indicated that the VFH-QL exhibited superior path quality, with efficiency of 94.89% and improvements of 96.91% and 96.69% over CQL and SARSA in the task of path planning for multiple targets in unknown environments.
      2  23
  • Publication
    Real-time vision-based hand gesture to text interpreter by using artificial intelligence with augmented reality element
    ( 2024-03-07)
    Rosnazri M.H.
    ;
    Mohd Rizal Manan
    ;
    Rosnazri Ali
    ;
    Baseemah Mat Jalaluddin
    ;
    Aimi Salihah Abdul Nasir
    ;
    Muhammad Aizat Abu Bakar
    ;
    Zamri N.F.
    ;
    Rahmat M.A.
    ;
    Zamzuri M.A.
    ;
    Azmi M.A.A.
    Real-time Vision-based Hand Gesture to Text Interpreter by Using Artificial Intelligence with Augmented Reality Element is a device that can interpret sign language to text in real-time. This communicator used a machine learning approach with a slight touch of deep learning elements, which are OpenCV, MediaPipe, and TensorFlow algorithms. Those algorithms have been used to differentiate the hand from other objects, detect the movement and coordinate of hands and perform imagery data analysis to produce output instantly in real-time. The camera will detect the user's hand movement, and the output will be produced on an LCD monitor. This project has been developed by using Python programming language. 13,000 of ASL's alphabets and 5,000 of ASL's number imagery datasets have been collected and trained by using cloud platforms which are Google Teachable Machine and Google Colab. The training process produced 99.85% of accuracy for the alphabets and 100% accuracy for the number. Finally, the constructed machine learning algorithm able to display alphabets and numbers on an LCD monitor by performing ASL's alphabet and number hand gesture in real-time. The performance of the prototype has been analyzed and experimented by two users at plain and noise background with different determined distances.
      2  24
  • Publication
    Electronic Nose Testing for Confined Space Application Utilizes Principal Component Analysis and Support Vector Machine
    ( 2020-12-18)
    Muhammad Aizat Abu Bakar
    ;
    Abu Hassan Abdullah
    ;
    Wan Azani Wan Mustafa
    ;
    Zol Bahri Razali
    ;
    Syahrul Affandi Saidi
    ;
    Mohamed Mydin Hj M.Abdul Kader
    ;
    Aman M.N.S.B.S.
    A confined space has a limited space for entry and exit but it is large enough for workers to enter and perform work inside. It is not designed for continuous occupancy because it can contribute atmospheric hazards accidents that threaten the worker safety and industry progress. In this work, we reported the testing an instrument to assist workers for atmosphere testing during pre-entry. An electronic nose (e-nose) using specific sensor arrays is the integration between hardware and software that able to sense different concentrations of gases in an air sample using pattern recognition techniques. The instrument utilizes multivariate statistical analysis which is Principal Component Analysis (PCA) for discriminate the different concentrations of gases and the Support Vector Machine (SVM) to classify the acquired data from the air sample. The instrument was successfully tested using diesel, gasoline, petrol and thinner. The results show that the instrument able to discriminate an air sample using PCA with total variation for 99.94%, while the classifier success rate for SVM indicates at 98.21% for train performance and 95.83% for test performance. This will contribute significantly to acquiring a new and alternative method of using the instrument for monitoring the atmospheric hazards in confined space to ensure the safety of workers during work progress in a confined space.
      3  27