Siti Marhainis Othman
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Siti Marhainis Othman
Official Name
Siti Marhainis, Othman
Alternative Name
Marhainis, Siti
Othman, S. M.
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Scopus Author ID
55210362500
Researcher ID
ABF-6513-2020

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  • Publication
    The ARX and ARMAX Models for thermoelectric cooling on glass windows: A Comparative study
    ( 2022-01-01)
    Mohd Saifizi Saidon
    ;
    Nasrul Amri Mohd Amin
    ;
    Aqilah Che Sulaiman
    ;
    Mohd Rizal Manan
    ;
    Siti Marhainis Othman
    ;
    Wan Azani Wan Mustafa
    ;
    Wahab N.A.
    Thermoelectric cooling (TEC), in particular, can be combined with a heat sink for local cooling, but they can also be integrated into electronic chips for point-to-point cooling. The study aims to develop a dynamic model of a cooling system integrated with TEC for glass window. The main target of this study is to develop a dynamic model of a cooling system integrated with TEC. The black box modelling approach in producing a mathematical model was selected based on the ARMAX and ARX model that corresponds to the actual dynamic state of the cooling system. The best model was finalized based on the best match on curve patterns when comparing the real and estimated models using the system identification tools in MATLAB, and also having the least error. The accuracy of the models was compared and analysed. The results showed that the 4th order of the ARMAX model produced a higher best fitting and standard deviation values of 80.23% and 0.027592 compared to the 4th order of the ARX model of 78.14% and 0.030769 respectively. This system accuracy is almost within the acceptable range for most error calculations in the validation method. Yet, this cooling system integrated with TEC is found more suitable for the 4th order of the ARMAX model when compared to the ARX model due to the noise parameter in the ARMAX model. Nevertheless, the noise order in this system is not dominant, therefore, whenever the noise order of the system in the ARMAX model is high than the second structure (nb), the number of errors is also high. In addition, the ARMAX model is found incapable of achieving the highest fitting due to the losses from the dynamic environment and losses from the TEC itself. Still, the use of this black box model used in this study is a significant variation where system parameters can be identified even offline.
  • Publication
    Automatic Recognition System of Iron Deficiency Anaemia in Human RBC using Machine Learning Techniques
    ( 2023-01-01)
    Siti Nurul Aqmariah Mohd Kanafiah
    ;
    Jusman Y.
    ;
    Shazmin Aniza Abdul Shukor
    ;
    Ibrahim W.N.A.B.W.
    ;
    Nordin S.A.
    ;
    Tohit E.R.B.M.
    ;
    Ali H.B.
    ;
    Nordiana Shariffudin
    ;
    Siti Marhainis Othman
    Iron Deficiency Anaemia (IDA) is the most common blood disorder. According to WHO, 30% of women aged 15-49 years, 37% of pregnant women, as well as 40% of children aged 6-59 months are anaemic globally. Anaemia can cause premature birth and affect mental, physical, and cognitive development, which in turn will lead to birth weight problems and stunted birth. The process of detecting IDA is usually captured based on a thin blood smear utilizing microscopic observation. Nevertheless, this process can be time-consuming. Moreover, it is challenging to identify the difference between IDA and normal red blood cells (RBCs) because the size is similar based on the observation of the human eye. It will cause difficulty in giving drug treatment to patients. A computeraided diagnosis (CAD) method was created to automatically distinguish between IDA and normal RBCs. The processes started with image acquisition, image processing, and recognition. Additionally, a Graphical User Interface (GUI) is also used to display images. In conclusion, recognition was done using the Multilayer Perceptron (MLP) method. The findings indicate that the proposed automated system is effective at distinguishing between IDA as well as normal RBCs, having an accuracy of 97.58% with regard to training and 98% regarding validation utilizing Levenberg-Marquardt (LM) trained MLP.
  • Publication
    Identification of ARX Model for Thermoelectric Cooling on Glass Windows
    ( 2022-01-01)
    Mohd Saifizi Saidon
    ;
    Nasrul Amri Mohd Amin
    ;
    ‘Aqilah Che Sulaiman
    ;
    Mohd Rizal Manan
    ;
    Siti Marhainis Othman
    ;
    Wan Azani Wan Mustafa
    ;
    Arith F.
    Thermoelectric cooling (TEC) is a solid-state heat pump that uses the Peltier effect to dissipate the heat generated by the electronic packaging system. TECs are widely used in aerospace, military, scientific work and industry due to small size, lack of moving parts, and ease of integration. In this study, a cooling system integrated with TEC is developed in a testing area (lecturer’s office) with the aim to reduce the temperature of the hot glass window area due to solar radiation that passes through it. This cooling system used direct TEC, for keeping the cooling temperature on the window to about 26 °C which is equivalent to an air conditioning setting temperature of 26 °C set during the experiment. This work includes experimental and modelling studies conducted on cooling systems integrated with TEC. The main target of this study is to develop a dynamic model of a cooling system integrated with TEC. The black box modelling approach in producing a mathematical model was selected based on the ARX model that corresponds to the actual dynamic state of the cooling system. The best model was finalized based on the best match on curve patterns when comparing the real and estimated models using the system identification tools in MATLAB, and also had the least error. The accuracy of the models was compared and analysed. The results showed that the 4th order of the ARX model produced a higher best fitting and standard deviation values of 78.14% and 0.030769. This system accuracy is almost within the acceptable range for most error calculations in the validation method. In addition, the ARX model is found incapable of achieving the highest fitting due to the losses from the dynamic environment and losses from the TEC itself. Still, the use of this black box model used in this study is a significant variation where system parameters can be identified even offline.
  • Publication
    Characteristic Study of Supercapacitor's Discharging Process Base on BLDC Motor
    ( 2023-01-01)
    Mohd Azri Abd Aziz
    ;
    Mohd Saifizi Saidon
    ;
    Muhammad Izuan Fahmi Romli
    ;
    Siti Marhainis Othman
    ;
    Wan Azani Wan Mustafa
    ;
    Al-Dolaimy F.
    ;
    Alkhayyat A.
    Energy storage has become a key issue for achieving goals connected with increasing the efficiency of both producers and users. In particular, supercapacitors currently seem to be interesting devices for many applications because they can supply high power for a significant amount of time and can be recharged more quickly than electrochemical batteries. Supercapacitors, as similar to conventional capacitors build on two plates separated by a dielectric and an electrolyte, can store more energy than conventional capacitors because they can produce two distinct layers of separated charges between plates, which are typically made of porous, carbon-based materials. The supercapacitors module serves as the power supply for the discharging process as called Energy Storages (ES). The main purpose of this research is to investigate the behaviour and properties of discharged supercapacitors. The design is created using Simulink and includes a circuit schematic and scope label. Using Brushless Direct Current Motor (BLDCM) as a load, study proposed steady state condition and dynamic state condition of BLDCM operation are investigated. With comparison to battery, preliminary finding state that value of SoC and voltage of battery higher but value of current less than supercapacitor in a certain amount of time.
  • Publication
    Temperature control using fuzzy controller for variable speed vapor compression refrigerator system
    ( 2022-01-01)
    Siti Qurrata Ain
    ;
    Mohd Saifizi Saidon
    ;
    Siti Marhainis Othman
    ;
    Aziz A.A.
    ;
    Wan Azani Wan Mustafa
    ;
    Wan Khairunizam Wan Ahmad
    Keeping the cold chain vaccine is crucial to a stable immunisation programme; however, faulty processes may occur more frequently than are often thought in developing nations. This paper discusses the quick and accurate control process for designing fuzzy controllers for variable speed vapor compression refrigerator system. The suggested controller is based on the fuzzy logic intended to improve performance while keeping the cooler’s constant internal temperature and increasing the refrigerator efficiency. Despite the external changes such as the outside temperature change or the volume change in the refrigerator vaccine, the fuzzy logic controller is utilised to maintain the interior temperature. However, a variable speed compressor (VSC) must be used to control the thermophysical characteristics, which dramatically alter the temperature with a small pressure change. In this case, fuzzy rules of the sort developed by Mamdani are used to build up the system. The programming platforms utilised to implement the model include MATLAB, SIMULINK, and Fuzzy Logic Toolbox (FLT). The efficiency of fuzzy logic controller design membership will be compared to ensure that the refrigerator temperature is more accurate and until it achieves the best performance, maintains a temperature of 5°C, and adapts to its surroundings. From the research done, the membership 2 with load shows the near accurate temperature of 5°C with steady-state error ±1.97°C.
  • Publication
    Small metal objects classification based on the deep learning approach
    ( 2024)
    Nur Safariah Inani M. Tahir
    ;
    Masturah Tunnur Mohamad Talib
    ;
    Mohd Hafiz Fazalul Rahiman
    ;
    N. S. Khalid
    ;
    Siti Marhainis Othman
    Classification of small metal objects plays a crucial role in various engineering fields, including manufacturing, robotics, and security. With advancements in deep learning techniques, the use of Convolutional Neural Networks (CNNs) has emerged as a powerful tool for image classification tasks. The methodology begins by collecting diverse datasets consisting of images of small metal objects. The datasets are labelled with corresponding object classes to facilitate supervised learning. Preprocessing techniques like re-sizing, normalization, and augmentation are used to improve the quality and diversity of the datasets. The use of CNNs in classification can be a better option compared to commonly used machine learning approaches. The CNN architecture is designed and trained to learn the distinguishing features of small metal objects. The main objective of this study is to assess the accuracy of this classification and explain how CNNs can enhance classification accuracy. The results of this study also show the effect of the optimizer on the classification process, which changes when different types of optimizers such as RMSprop, Adam, and SGD are used. While some optimizers yield slightly lower accuracy results, the Adam optimizer with the CNN ResNet-50 module proves suitable for use with this dataset, achieving a high classification accuracy of 86%.
  • Publication
    Hand-held shelf life decay detector for non-destructive fruits quality assessment
    ( 2024)
    Nurul Syahirah Khalid
    ;
    Nordiana Shariffudiin
    ;
    Shazmin Aniza Abdul Shukor
    ;
    Humairah Mansor
    ;
    Masturah Tunnur Mohamad Talib
    ;
    Sukhairi Sudin
    ;
    Ismail I. Ibrahim
    ;
    Mohd Zamri Hasan
    ;
    Siti Marhainis Othman
    ;
    N.D.N Dalila
    ;
    M.Thaqif B.N Ashimi
    Perishable food such as fruits have a limited shelf life and can quickly degrade if not properly stored. One method for detecting decay in these foods is the use of ethylene gas. Ethylene is a naturally occurring hormone that is released by fruits as they ripen. By measuring the levels of ethylene in the storage area, it is possible to detect when fruits and vegetables are starting to degrade. This information can then be used to act, such as removing spoiled produce and adjusting storage conditions, to extend the shelf life of the remaining products. By utilizing ethylene gas for early detection of decay, it is possible to improve food safety and reduce food waste. The project aims to utilized ethylene gas from perishable food such as fruits before decay. This project proposed portable or hand-held detection ethylene gas by including temperature and humidity. The sensor will be measuring the level of ethylene gas, temperature and humidity. Next, machine learning method; K-Nearest Neighbour(KNN) were used to evaluate the accuracy of the proposed system. This project, a hand-held decay detector for perishable food products is believed can help to prevent food waste by detecting early signs of spoilage in fruits.
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  • Publication
    Position Tracking Performance with Fine Tune Ziegler-Nichols PID Controller for Electro-Hydraulic Actuator in Aerospace Vehicle Model
    ( 2021-12-01)
    Devendiranath K.
    ;
    Siti Marhainis Othman
    ;
    Sunar N.
    ;
    Hassrizal Hassan Basri
    ;
    Abdul Halim Ismail
    ;
    Mohd Nasir Ayob
    ;
    Azmi M.S.M.
    ;
    Mohd Sani Mohamad Hashim
    Electro-Hydraulic Actuator (EHA) system is a third order non-linear system which is highly suffer from system uncertainties such as Coulomb friction, viscous friction and pump leakage coefficient which makes this system more complicated for the designing of the controller. The Proportional-Integral-Derivative (PID) controller has proposed in this paper to control EHA system and main problem in its application is to tune the parameter to its optimum value. Two different methods are used to tune the PID controller which are trial and error and Ziegler-Nichols method. MATLAB Simulink is used to simulate the system. In order to determine the performance of EHA system for the position tracking. 3 different of external disturbance such as 0N, 5000N and 10000N has been injected into the system. Simulation results show that the Ziegler-Nichols fine tuning method provides the better tracking performance when compared to the trial and error method for every specific disturbance setting. The Ziegler Nichols method provides better disturbance rejection as the performances indexes such as percentage overshoot, settling time and steady state error are not affected by the varying of disturbance.
      1
  • Publication
    Integrating Vision System to a Pick and Place Cartesian Robot
    ( 2021-12-01)
    Tan K.S.
    ;
    Mohd Nasir Ayob
    ;
    Hassrizal Hassan Basri
    ;
    Abdul Halim Ismail
    ;
    Muhamad Safwan Muhamad Azmi
    ;
    Mohd Sani Mohamad Hashim
    ;
    Siti Marhainis Othman
    ;
    Shahriman Abu Bakar
    ;
    Low Y.H.
    Vision aided pick and place cartesian robot is a combination of machine vision system and robotic system. They communicate with each other simultaneously to perform object sorting. In this project, machine vision algorithm for object sorting to solve the problem in failure sorting due to imperfection of images edges and different types of colours is proposed. The image is acquired by a camera and followed by image calibration. Pre-processing of image is performed through these methods, which are HSI colour space transformation, Gaussian filter for image filtering, Otsu's method for image binarization, and Canny edge detection. LabVIEW edge-based geometric matching is selected for template matching. After the vision application analysed the image, electrical signal will send to robotic arm for object sorting if the acquired image is matched with template image. The proposed machine vision algorithm has yielded an accurate template matching score from 800 to 1000 under different disturbances and conditions. This machine vision algorithm provides more customizable parameters for each methods yet improves the accuracy of template matching.
      1
  • Publication
    Optimization of PD Controller based on ARMAX Model for Vapor Compression Refrigeration System using R600a Refrigerant
    ( 2022-01-01)
    Rajaie M.N.
    ;
    Mohd Saifizi Saidon
    ;
    Siti Marhainis Othman
    ;
    Wan Azani Wan Mustafa
    The research undertaken in this paper is to investigates the difference in approaches to the modelling, design and implementation of an adaptive controller tuned using Auto-Regressive Moving-Average Exogenous (ARMAX) 2,1,1 model in an environment simulated in SIMULINK, applied to a variable speed compressor vapor compression refrigeration system running R600a refrigerant. A vapor compression refrigeration system is chosen for this paper research as it’s the most commonly used type of refrigeration system in all over the world, either for domestic, commercial or industrial application. The refrigeration system consists of a condenser, an expansion valve, an evaporator and a compressor which are modified from a fixed speed compressor to a variable speed compressor. The compressor was modified to be able to accommodate the usage of R600a refrigerant. R600a refrigerant has a thermophysical properties which can roughly be define as a slight change in pressure will result in a drastic change in temperature [1]. To be able to control the pressure for R600a with precision, an optimized adaptive controller is required. For the purpose of the simulation, the refrigeration system mathematical model is simplified to a linear polynomials ARMAX model. This is to reduce the complexity of the control design strategies, which in term improve the implementation of the new controller design. The optimization of the adaptive controller design, its simplicity of implementation, speed of convergence and robustness are concluded at the end part of the paper.
      1