Mohamed Mydin Hj M.Abdul Kader
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Preferred name
Mohamed Mydin Hj M.Abdul Kader
Official Name
Mohamed Mydin , Hj M.Abdul Kader
Alternative Name
Kader, M. M.A.
Abdul Kader, M. Mohamed Mydin
Mohamed, M. M.A.K.
Abdul Kader, Mohamed Mydin M.
Kader, M. M.M.A.
Main Affiliation
Scopus Author ID
57202264868
Researcher ID
CYH-3060-2022

Research Output

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  • Publication
    Methylene blue dye adsorption by using deep eutectic solvent pre-treated wood chips
    ( 2022-11-18)
    Muhammad Masrur Jamil
    ;
    Ahmad Anas Nagoor Gunny
    ;
    Mohd Sharizan Md Sarip
    ;
    Mohd Faizal Ab Jalil
    ;
    Mohamed Mydin Hj M.Abdul Kader
    ;
    Mohamed Syazwan Osman
    ;
    Zulkarnain Mohamed Idris
    Adsorption of Methylene Blue using biomass or bioproduct of industries has received major attention by the researcher and industries. In this study, wood chips treated using deep eutectic solvents (DES) was used for adsorption of methylene blue. The surface and pores of this wood chips were analyzed by using scanning electron microscope (SEM). One Factor At a Time (OFAT) method was carried out to study the effect of contact time and biomass dosage on adsorption efficiency. Evaluation of pretreated wood chips biosorption, isotherms and kinetics were also studied.. Wood chips treated with DES changes the surface area and the pores of wood chips and improved the adsorption process efficiency. Freundlich isotherm and pseudo-second show correlation coefficient of R2, 0.9591 and 0.9999 respectively. Wood chips treated using deep eutectic solvents demonstrate a great potential as a cheap biosorbent for the removal of methylene blue by looking at the isotherm and kinetic studies.
  • Publication
    Urban Farming Growth Monitoring System Using Artificial Neural Network (ANN) and Internet of Things (IOT)
    ( 2025-01-01)
    Mohamed Mydin Hj M.Abdul Kader
    ;
    Muhammad Naufal Mansor
    ;
    Wan Azani Wan Mustafa
    ;
    Zol Bahri Razali
    ;
    Ahmad Anas Nagoor Gunny
    ;
    Samsul Setumin
    ;
    Muhammad Khusairi Osman
    ;
    Mohaiyedin Idris
    ;
    Akbar M.F.
    ;
    Premavathy Kunasakaran
    ;
    Muhammad Zubir Zainol
    ;
    Nor Syamina Sharifful Mizam
    As an introduction to this project, the growth-related traits, such as above-ground biomass and leaf area, are critical indicators to characterize the growth of indoor lettuce plants. Currently, non-destructive methods for estimating growth-related traits are subject to limitations in that the methods are susceptible to noise and heavily rely on manually designed features. It is also one of the problem statements in this project. Based on this project the next problem is manual control of nutrients may cause quality issues to the lettuce plant. If the nutrient supply is too much or less, it will disturb the growth of the lettuce plant either the lettuce plant is dead or stunted. This project is about urban farming growth monitoring system using Artificial Neural Network (ANN) and Internet of Things (IoT). In this project, a method for monitoring the growth of indoor lettuce plants was proposed by using digital images and an ANN using Deep Learning Architecture. DLA is mostly developed by the software of MATLAB or Python to insert and run the coding. DLA is mostly used for image detection, pattern recognition, and natural language processing through the graph for Neural Network. Next, the Internet of Things (IoT) is a medium to store images of indoor lettuce plant growth into the Cloud (Google Drive). Furthermore, it takes indoor lettuce plant images as the input, an ANN was trained to learn the relationship between images and the corresponding growth-related traits with other fixed parameters. The pH level parameters were controlled by other fixed parameters to take the images of indoor lettuce plant growth. The parameters used in this project are temperature and humidity. This helps to compare the results of Artificial Neural Network (ANN), widely adopted methods were also used. Concisely, this project is expected to develop the Deep Learning Architecture using an Artificial Neural Network (ANN) with digital images as a robust tool for the monitoring of the growth of indoor lettuce plants every 30 minutes per day. Generally, focused on an urban farming growth monitoring system using Artificial Neural Network (ANN) and the Internet of Things (IoT).
  • Publication
    Automotive Mechanical Vehicle Starter
    ( 2021-12-01)
    Mohamed Mydin Hj M.Abdul Kader
    ;
    Zol Bahri Razali
    ;
    Wan Azani Wan Mustafa
    ;
    Syahrul Affandi Saidi
    ;
    Ahmad Anas Nagoor Gunny
    ;
    Samsul Setumin
    ;
    Muhammad Khusairi Osman
    ;
    Idris M.
    ;
    Akbar M.F.
    ;
    Sarbini M.A.A.
    ;
    Mizam N.S.S.
    This research is used to crank start automotive vehicle. There are many different system used in order to start-up vehicles using electric starter, in the time of battery low-power or totally drained. The purpose of this research is to help the driver to get out of this difficulty. Nowadays there are many people that have experienced such a bad moment, where they are stranded at road side due to malfunction starter in their car because of battery problem. Most of the vehicle electric starter failure is because of battery corrosion or battery undercharged. The importance of this research is to solve this problem. Starter is a vital part of the vehicle, without it no automotive vehicles able to operate. These starters will rotate an internal-combustion engine to initiate the engine's operation under its own power. Starters also can be malfunction too due to corroded electrical connections or an undercharged battery. This system can be used to solve this problem. This system used human energy by using mechanical parts in order to produce electrical power. In order to produce electrical current, workforce will be applied by rotating the wheel that already linked by belt and from that rotations will trigger a magnetic force and it will produce an electrical current and supply it into battery. This system is divided into two development; hardware development and software development. The hardware development involved, mechanical device which is used and electrical device such as monitor. For software development, Fritzing is used to construct circuit.