Real-time risk assessment plays a vital role in ensuring the safety of autonomous vehicles. This project aims to explore how autonomous vehicles can accurately infer and quantify the potential risks in the uncertain and dynamic real-world environments by using machine learning approaches.

yhng@mmu.edu.my

Wireless indoor localization has garnered significant interest over the last decade due to the increasing demand for location-based services in indoor environments. Owing to the widely fluctuating received signal strength of the wireless signals that arises because of multipath fading, shadowing effects, and attenuation by static or dynamic obstacles, localization techniques often suffer from degraded positioning accuracy. The aim of this project is to design a novel machine learning based wireless localization technique that is capable of achieving high positioning accuracy in dynamic indoor environments.

yhng@mmu.edu.my

The search of avalanche photodiode (APD) operates in linear-mode (below breakdown voltage) or in Geiger-mode (above breakdown voltage) like single photon avalanche diodes (SPADs) attaining the performance of photomultiplier tubes (PMTs) is the ultimate goal. To date, Hg0.7Cd0.3Te and InAs APDs demonstrated internal gain mechanism similar to that of PMT based on single-type carrier multiplication. However, these APDs suffer from inherent material limitations and technological challenges. Thus, it is impetus to search new materials for the enhancement of APDs and SPADs performances, particularly high gain, low noise and short timing jitter essential requirements for real-time quantum imaging and secure communication systems. A potential material free from these challenges is AlAs0.56Sb0.44 lattice matched to InP with a bandgap of 1.63 eV at room temperature. The large disparity of electron and hole ionization coefficient was demonstrated in AlAs0.56Sb0.44 material, in which α > β with the k = β / α value approaching 0.001 for applied electric fields lower than 400 kV/cm. To explain this large difference between the α and β the detailed understanding of AlAs0.56Sb0.44 band structure and electron and hole transport and impact ionization process are required. However, no details of AlAs0.56Sb0.44 band structure has ever been reported in the literature. These insights are keys for designing a high performance APD and single photon avalanche diode (SPAD) based on AlAs0.56Sb0.44 material systems.
In this project, the band structure and electronic properties of AlAs0.56Sb0.44 will be obtained from the first-principles calculations.

dsong@mmu.edu.my

The search for avalanche photodiode (APD) operating in linear-mode or in Geiger-mode, also known as single photon avalanche diode (SPAD), attaining the performance of photomultiplier tubes (PMTs) in terms of high gain, low noise and short timing jitter is the ultimate goal for many applications, especially for second-generation quantum technologies. AlAs0.56Sb0.44 is a potential material with its large disparity of electron (α) and hole (β) ionization coefficient to be exploited for single-type carrier multiplication SPAD. The characteristics of electron and hole high field transport and impact ionization (the internal gain mechanism of avalanche photodiodes) in AlAs0.56Sb0.44 will be investigated using the Monte Carlo particle transport method. The accuracy of the Monte Carlo simulation of electron and hole transport in a semiconductor is only as good as the underlying physical model of electron and hole dynamics (the scattering processes) and kinematics (the electron and hole free flights between scattering). The price one has to pay for a full band Monte Carlo simulation include a very time-consuming computational process and the requirement of a complete knowledge of the physical system under investigation. A Monte Carlo model incorporating an analytically described band structure is the best trade-off for the simulation of high field carrier transport and impact ionization in semiconductors. An Analytical-band Monte Carlo (AMC) model will be developed to simulate the electron and hole transport including impact ionization in AlAs0.56Sb0.44 semiconductor. The AMC model will be advanced for device simulation to predict the possible limit of multiplication gain in linear-mode AlAs0.56Sb0.44-based single photon avalanche diodes based on single-type carrier multiplication.

dsong@mmu.edu.my

Due to the increasing demand of radio spectrum for supporting massive wireless services with heavy traffic, enormous connections and various quality-of-services (QoS) requirements, the management of spectrum is extremely challenging in this new century. Since traditional fixed spectrum allocation policy leads to an inefficient way of spectrum usage, the dynamic spectrum management (DSM) is recommended as one of the promising solution to mitigate the spectrum scarcity problem. Using the machine learning techniques, the model-based schemes in the traditional DSM can be transformed into data-driven approach. Hence, DSM becomes more flexible and efficient. However, there are some challenges to achieve the machine-based DSM schemes such as to differentiate the importance of data of different types in the radio communication and the existing of huge computation overheads during the training process.

Note: Full-time study only. Candidate needs own financial support (or apply for GRA position). Preferably good in Telecommunication and Artificial Intelligence field.

gcchung@mmu.edu.my

Dye-sensitized solar cell (DSSC) is an emerging photovoltaic technology that has garnered considerable interest owing to its numerous attractive features including low cost, ease of fabrication, semi-transparency, light weight and operability under low-light condition. However, the long-term stability issue is the main challenge of DSSC that remain to be tackled in order to realize the commercialization of DSSC. The long-term stability issue can be addressed by a fully solid-state DSSC technology, which is the main goal of this research project here.

kychan@mmu.edu.my

Piezoelectric materials are materials that can turn mechanical stress into electrical charge. Hence, piezoelectric materials are widely used in sensor industry. There are many piezoelectric materials. However, barium titanate is one of the most promising lead-free perovskite-structured materials with high piezoelectric coefficient (149 pC/N) and dielectric constant (100-11000).
Application of nanofibers is widely seen in sensor industry. Barium titanate nanofibers are believed have greater potential than bulk barium titanate. Among the fabrication methods, electrospinning method is the easiest method in fabricating nanofibers. However, the fabrication parameters of electrospinning method must be optimized to produce barium titanate nanofiber with high piezoelectric coefficient and dielectric constant.

yksin@mmu.edu.my

It has been reported in [1] that 700 drowning cases is recorded in Malaysia each year. These cases keep going up due to the lack of public awareness and state-of-the-art rescue facilities used by the rescue team on drowning victims. Having said so, with the recent spike of cases related to COVID-19 pandemic outbreak, it had somehow impacted the perception of humans not to be in close contact with others by maintaining a strict social distance rule [2]. Indirectly, it had contributed to the fear in rescuing a drowning victim with the perception that the victim could be a possible contributor to the COVID-19 virus. To overcome the afore said claims, a feasible immediate proposal is to introduce a state-of-the-art Unmanned – Water Rescue Boat (U-WRB) to safe victims from drowning.

With the urgency of the proposed plan above, there is a need of cheap and readily available local resources for developing the U-WRB. Focusing on Malaysia for an instance, which is geographically located at the equatorial region, is blessed with its high amount of agricultural output throughout the year. According to IndexMundi [3], Malaysia is the second largest oil palm producer in the world after Indonesia. It was reported that 199 Million Tan of oil palm was produced in year 2020. As a result of this, a huge amount of oil palm fibre husks are being abundant from the cultivation of ripen oil palm fruits [4–7]. These husks which contain oil palm fibres are normally used as an insect repellent when they are burnt openly into the atmosphere [8]. This puts a huge amount of oil palm fibres to waste causing serious environmental problems such as greenhouse effect, high readings of Air Pollution Index (API) and forest devastation which can lead to physical disturbance of the ecological behavior of an ecosystem.

To overcome this, the current work is an attempt to explore the possibility of using oil palm fibres as reinforcement elements with polymer matrix to produce a low-cost composite material for developing an Unmanned – Water Rescue Boat (U-WRB). The developed U-WRB will be subjected to different state-of-the-art features as attachments. Examples of the proposed waterproof attachments are emergency light, walkie-talkies, goggles, 360 degrees camera, emergency alarm, oxygen tank, safety jacket, buoy, paddles, emergency beacon, fins and an emergency smoke candle flare. ‘Self-righting’ features will be incorporated to the U-WRB mainly to prevent the boat from overturning or sinking when it is subjected to rough waves. The whole customized U-WRB will be operated by means of a digital remote control by a certified trained lifeguard. The boat will be given a name of ‘Khadijah’s Rescue’ namely to honor the prophet’s wife which took great care of him through the ups and downs of his lifetime.

References

[1] A. Dermawan, “700 drowning cases recorded in Malaysia every year,” News Straits Times. (2017).
[2] Global Report on Drowning: Preventing a Leading Killer by World Health Organization, 2014.
[3] IndexMundi, (2020). (accessed April 20, 2021).
[4] B.F. Yousif, U. Nirmal, Wear and frictional performance of polymeric composites aged in various solutions, Wear. 272 (2011) 97–104.
[5] N.S.. El-Tayeb., B.F. Yousif., The Effect of Oil Palm Fibres As Reinforcement On Tribological Performance of Polyester Composite, Surface Review and Letters, Vol. 14, No. 6 (2007) 1095-1102, (n.d.).
[6] B.F. Yousif. N.S.M. El-Tayeb, High-stress three body abrasive wear of treated and untreated oil palm fibre-reinforced polyester composite, Proc. Inst. Mech. Eng. J:J. Eng. Tribol. 222 (5) 637-646, (2008), (n.d.).
[7] U. Nirmal, J. Hashim, M.M.H. Megat Ahmad, Wear Performance of Oil Palm Seed Fibre-Reinforced Polyester Composite Aged in Brake Fluid Solutions, in: J.P. Davim (Ed.), GREEN AND BIOTRIBOLOGY, De Gruyter, Germany, 2016: pp. 90–115.
[8] U. Nirmal, C.C. Wen, M.Y. Yuhazri, M.H. Amirhafizan, M.M.H. Megat Ahmad, Biocomposite And Synthetic Composites For Automotive Applications, 1st ed., Woodhead Publishing is an imprint of Elsevier, 2020.

Note: Looking for a Master student registered as full time under the Master of Engineering Science in MMU, FET. Allowance may be given if there is sponsorship. The candidate should be highly creative and hardworking with good design and simulation skills. English command should be excellent and participation in Local and International conference is highly encouraged.

nirmal@mmu.edu.my

This project aims to do experimental study of new thermoset composite materials in tribological aspect.

cwchin@mmu.edu.my

This project aims to do experimental study on thermoplastic material in tribological aspect.

cwchin@mmu.edu.my

This project aims to do experimental study on kenal fibre composite material in tribological aspect.

cwchin@mmu.edu.my

Clean water supply is key towards ensuring well-being and quality of life. With the availability of Internet of Things (IoT) technologies, it is possible to acquire sensor data of water quality periodically in real-time. Machine Learning and Deep Learning (DL) algorithms can then be used to monitor and forecast the water quality. Based on the output of this system the authorities can be alerted on possible cases of water pollution, find the root cause and acted on it, so that uninterruptible supply system can be provided.

azlina.aziz@mmu.edu.my

Essentially, the distances between a current vehicle and other vehicles on the same road, whether the other vehicles are at the front, the back, the right or the left of the current vehicle, must be larger than the critical gap, which is the minimum safe distances between them. These distances depend on the speeds, sizes and types of all proximate vehicles and moving objects, which are all moving or located near the current vehicle. The increase in the speeds and sizes of the vehicles generally tend to increase the critical gaps. The speeds of the vehicles also depend on the number of vehicles on the proximate areas of the road. The types of the vehicles or moving objects not only affect the critical gap, but also the speed and the direction of the current vehicle. These constraints also affect the traffic congestion along the road. Vehicles of different types like ambulances, police cars and police motorbikes have different effects on the traffic safety and congestion.

Therefore, investigating the correlation between these constraints is essential in order to give a thorough insight and formulation of the critical gap for reducing the car crash and traffic
congestion.

rosli@mmu.edu.my

A large number of sport videos exists, and generating key highlights or summaries is difficult and time consuming.

This project aim to automatically generate key highlight event or summaries from sport games. Tools such as computer vision, video analysis and deep learning will be used.

hagoh@mmu.edu.my

Wind power has gained interest and investment from the global nations through the last decade due to the issues of climate change and global warming. Wind as renewable energy is leading the projected grow of global renewable energy capacity by 50% from 2020 to 2025. This project involves design and develop a new small scale wind turbine system which is capable of harvesting wind energy at low wind speed regions like Malaysia. The scope of the project will cover the engineering design of the wind turbine system including the generator, prototype fabrication, laboratory and field measurement, and numerical analysis. The experimental investigation methodology will be developed for obtaining its power performance and aerodynamic characteristics at low wind speed conditions, and the results will be verified by the numerical analysis.

Note: Only full-time candidates accepted.

bklim@mmu.edu.my

Two-phase direct immersion cooling method offers superior cooling efficiency for thermal management of the microelectronic devices. The objective of this work is to experimentally investigate the pool boiling heat transfer characteristics from a series of four in-line discrete heat sources mounted in a rectangular enclosure using heat transfer fluid as the working fluid. Simulated chips are to be flush-mounted on one wall of a rectangular channel. The effect of heat transfer fluid and angle of orientation of the enclosure on two-phase heat transfer performance for the simulated multi-chip module will then be investigated. The output from the work helps the thermal design engineers to understand fundamentally the two-phase cooling in electronics and may serve as guideline in the design of pool boiling systems in which the contributed knowledge will be used as a basis for future comparison with studies to be performed on actual circuit boards with complicated geometries.

Note: Only full-time candidates accepted.

bklim@mmu.edu.my

Governments from all over the world including Malaysia are taking great efforts and initiatives to come out with policies and support to the electric vehicles (EVs) in combating the environmental pollution and energy crisis that are partly contributed by the transportation sector. The lithium ion batteries as one of the major energy storage technology development that are aligned with the growth of EVs necessitates an effective battery thermal management (BTM) in order to preserve its performance and lifetime. Immersion cooling is an potential emerging cooling technology to traditional battery cooling methods in which the battery cells are submerged in a liquid coolant for superior thermal contact and homogeneity. This project is about design a liquid immersion cooling system for the battery pack of EVs and investigate the thermal performance of the system. In the work, the cooling system will be modelled in Matlab/Simulink and an experimental work may be designed and setup to verify and validate the data. The project has potential commercialization value and find applications in other fields such as thermal cooling of CPUs and data centers.

Note: Only full-time candidates accepted.

bklim@mmu.edu.my

Micro-hydro systems produce electric power from water. These small water-powered systems can produce up to 15 kW of electrical power, sufficient to provide electricity for a village of almost 100 houses to power lights and small motors. Obviously, this soft energy source, however, doesn’t provide enough power for industrial uses. Micro-hydro systems are important for villages that are near water and do not have electric power.

Perform a theoretical study of microhydro power in Malaysia, and come up with a design and setup of microhydro power system; finally, perform a feasibility study of microhydro power electricity generation in Malaysia.

lim.wee.kuan@mmu.edu.my

Today, people are using solar cookers in many countries around the world. People use solar ovens to cook food and to heat drinking water to kill bacteria and other harmful organisms. Also, solar ovens cook food at low temperatures over long periods of time; this permits people to leave food to cook while they do other things.

Perform a theoretical study of solar food dryers and come up with a prototype.

lim.wee.kuan@mmu.edu.my

The rubber industry has been researching the devulcanization of rubber for many years. The main difficulty in recycling rubber has been devulcanizing the rubber without compromising its desirable properties. The process of devulcanization involves treating rubber in granular form with heat and/or softening agents in order to restore its elastic qualities, in order to enable the rubber to be reused. Several experimental processes have achieved varying degrees of success in the laboratory, but have been less successful when scaled up to commercial production levels. Also, different processes result in different levels of devulcanization: for example, the use of a very fine granulate and a process that produces surface devulcanization will yield a product with some of the desired qualities of unrecycled rubber. In the rubber recycling process, devulcanization begins with the delinking of the sulfur molecules from the rubber molecules, thereby facilitating the formation of new cross-linkages. Two main rubber recycling processes have been developed: the modified oil process and the water-oil process. With each of these processes, oil, and a reclaiming agent are added to the reclaimed rubber powder, which is subjected to high temperature and pressure for a long period (5–12 hours) in special equipment and also requires extensive mechanical post-processing. The reclaimed rubber from these processes has altered properties and is unsuitable for use in many products, including tires. Typically, these various devulcanization processes have failed to result in significant devulcanization, have failed to achieve consistent quality, or have been prohibitively expensive.

lim.wee.kuan@mmu.edu.my

Perform a computational study of the electron, photon, neutron, and positron quantum-mechanical stochastic transport in semiconductors. Design Monte Carlo simulations at various energies for various industrial semiconductor materials. Extrapolate the relevance of the findings to optoelectronics, biotechnology, and medical technology.

lim.wee.kuan@mmu.edu.my

Osmotic (or salinity-gradient) energy generation takes advantage of the osmotic pressure difference between salt and fresh water. If we place a semipermeable membrane (like that in a reverse-osmosis filter) between sealed bodies of salt water and fresh water, the fresh water will gradually travel through the filter by osmosis; exploiting the pressure difference between these two bodies of water, we can extract energy commensurate to the difference in pressure. Osmosis is the diffusion of a solvent through a semipermeable membrane from a region of low solute-concentration to a region of high solute-concentration. The semipermeable membrane is permeable to the solvent, but not to the solute, resulting in a chemical potential difference across the membrane that drives the diffusion; that is, the solvent flows from the side of the membrane where the solution is weaker to the side where it is stronger, until the solution on both sides of the membrane is of the same strength (that is, until the chemical potential is equal on both sides). Mixing of materials with different composition can be used, in principle, in energy production. In fact, the principle of osmotic energy is the exploitation of the entropy of mixing freshwater with saltwater. One of the most important components of osmotic power plant are osmotic membranes, which let water flow through, but does efficiently prevent penetration of saline ions. The membranes help unpressurized water to flow into pressurized seawater without any external mechanical equipment; the membranes work as natural pumps. The pressurized seawater mixed with river water will be conducted into turbine for electricity production. Some of the attractive features of the osmotic energy include the absence of carbon dioxide or other effluents that can adversely affect the environment, renewability, non-periodicity (unlike wind or wave power), and suitability for small or large plants (modularity). Its drawbacks include its current low efficiency, energy-cost sensitivity to membrane cost and efficiency, and vulnerability of membrane to fouling. In fact, one of the obstacles in the development has been, so far, the missing of proper membranes (good water permeability); therefore, pay particular attention to the work of membranes.

Perform a study on osmotic energy, and identify some of its novel applications. Perform some demonstrations or simulations related to the study. Also, come up with a laboratory design and setup of osmotic energy. Perform a theoretical, technological, and feasibility study of osmotic energy implementation; pay particular attention to the membrane and chemical selections, energy storage technology, and power conversion and generation setup. Address the good, the bad, and the ugly aspects of the implementation.

lim.wee.kuan@mmu.edu.my

Municipal solid waste (MSW), also called urban solid waste, is a waste type that includes predominantly household waste (domestic waste) with sometimes the addition of commercial wastes collected by a municipality within a given area. The wastes are in either solid or semisolid form and generally exclude industrial hazardous wastes. Gasification of the waste can be widely used on industrial scales to generate electricity.

Since 1994 Majlis Bandaraya Melaka Bersejarah (MBMB) has been disposing its municipal waste directly to the MBMB sanitary landfill at Krubong; however, this sanitary landfill is scheduled to be terminated soon at the end of the first phase of Krubong Project. The MBMB sanitary landfill receives 750 tons of municipal solid waste daily. Even though, MBMB does not practice landfill gas collection in this sanitary landfill, this open lagoon is for the purpose of waste treatment. During the second phase, MBMB plans to use the collected municipal waste for fuel and energy recovery with gas engine generators, by installing equipment for landfill gas (LFG) collection; also, it plans to use the collected LFG to generate electricity and prevent the emission of methane from the landfill site. In final phase, any excess waste will be buried with water-proof clay, then sand, followed by topsoil; and grass will then be grown on the final layer.

Perform a theoretical, technological, and feasibility study of using municipal waste to generate electricity in Melaka; identify the waste and operation site, energy storage technology, and power conversion & generation setup; examine the gas generated and the related designs of gasifiers or reactors; perform some simulations or programming related to the study; and address the good, the bad, and the ugly aspects of the implementation.

lim.wee.kuan@mmu.edu.my

In fluid mechanics, the cheerios effect is the tendency for small wettable floating objects to attract one another. It is due to surface tension and buoyancy. The same effect governs the behaviour of bubbles on the surface of fizzy drinks. Thus, small wettable objects floating on water tend to coalesce into rafts; in the case of bubbles, such rafts have many solid-like properties. Small wettable objects also tend to be attracted towards the edge of the meniscus. Writing in the American Journal of Physics, Dominic Vella and L. Mahadevan of the Harvard University discuss the cheerios effect and suggest that it may be useful in the study of self-assembly of small structures. The cheerios effect also refers to small objects that repel one another. Vella shows that two small floating items with identical wetting properties can repel one another if the relative density of them is of opposite sign.

Demonstrate the Cheerios effect, and identify its significance and application, and perform some demonstrations or simulations related to the study.

lim.wee.kuan@mmu.edu.my

Perform a theoretical, technological, and feasibility study of atmospheric electricity implementation in Melaka; identify the operation site, energy storage & retrieval technologies, and power conversion and generation setup; perform some simulations or programming related to the study; and address the good, the bad, and the ugly aspects of the implementation. Pay particular attention to the energy storage & retrieval designs and technologies.

lim.wee.kuan@mmu.edu.my

This Master of Engineering Science project is to develop a money detector for the blind people.

Note: Only Bachelor of Electronics / Electrical Engineering  Degree holders are accepted.

wkwong@mmu.edu.my

This Master of Engineering Science project is to develop an omnidirectional car burglar detector for carpark.

Note: Only Bachelor of Electronics/ Electrical Engineering Degree holders are accepted.

wkwong@mmu.edu.my

This project is to develop a 3D Map Plotter Mobile Robot for indoor / tunnel inspection usage.

Note: Only Bachelor of Electrical/ Electrical Engineering degree graduates are accepted. Preferably from the area of robotics.

wkwong@mmu.edu.my

This project is to develop a vision based patrol robot for security purposes during off time.

Note: Only Bachelor of Electrical/ Electrical Engineering degree graduates are accepted. Preferably from the area of robotics.

wkwong@mmu.edu.my

This project is to develop a Sustainable Water Supply System for Household Usage using Electronics, Sensor and AI.

Note: Only graduates from Bachelor’s degree of Electronics/Electrical Engineering are accepted. Preferably good in Electronics Sensor and Control field.

wkwong@mmu.edu.my

Objectives: Drowsy driving is a serious highway safety problem. If drivers could be warned before they became too drowsy to drive safely, some drowsiness-related crashes could be prevented. The presentation of timely warnings, however, depends on reliable detection. To date, the effectiveness of drowsiness detection methods has been limited by their failure to consider individual differences. The present study sought to develop a drowsiness detection model that accommodates the varying individual effects of drowsiness on driving performance.

Methods: Nineteen driving behavior variables and four eye feature variables were measured as participants drove a fixed road course in a high fidelity motion-based driving simulator after having worked an 8-h night shift. During the test, participants were asked to report their drowsiness level using the Karolinska Sleepiness Scale at the midpoint of each of the six rounds through the road course. A multilevel ordered logit (MOL) model, an ordered logit model, and an artificial neural network model were used to determine drowsiness.

Results: The MOL had the highest drowsiness detection accuracy, which shows that consideration of individual differences improves the models’ ability to detect drowsiness. According to the results, percentage of eyelid closure, average pupil diameter, standard deviation of lateral position and steering wheel reversals was the most important of the 23 variables.

Conclusion: The consideration of individual differences on a drowsiness detection model would increase the accuracy of the model’s detection accuracy.

Keywords: Driving behavior; Driving simulator; Drowsiness detection; Eye feature; Multilevel ordered logit model; Non-intrusive.

Note: Only for full-time candidates.

ppem@mmu.edu.my

To design and develop a drone based miniaturize Synthetic Aperture Radar

ykchan@mmu.edu.my

To identify types of drone via synthetic aperture radar (SAR) images. Doppler signature of the drone in SAR images will be used as main feature to differential types of drone.

ykchan@mmu.edu.my

Various types of parameter will study in new PVT system.

ervina.noor@mmu.edu.my

In this project, fibre reinforced hybrid composite crush tubes loaded with nanoparticles will be fabricated. The hybrid composite has a functionally graded structure, and is made of carbon and kevlar fibres. The optimum volume fraction of the nanoparticles, and the effective functionalization of the nanoparticles will be sought after. Optimized and functionalize nanoparticles are expected to enhance their bond with the epoxy matrix, hence maximizing the crush tubes energy absorption in low-speed impact.

ckkok@mmu.edu.my

Micro stir friction welding in the form of butt and/or lap joint to join aluminium and copper is a much sought-after green welding technology. However, due to the inherent incompatibility between the two materials, and the technical challenges related to downscaling of the friction stir welding to mesoscale material thickness (i.e. less than 1mm), the technique has not been proven to be feasible. This project seeks to optimize the welding parameters for a sound stir friction welding of the two materials.

ckkok@mmu.edu.my

One of the main challenges in developing an intelligent and autonomous robot is to be able to plan its navigation path without any human intervention. Both classical path finding algorithms and AI-based approaches will be studied. A mobile robot equipped with LIDAR and camera-based vision system will be used to conduct field test. A new path finding algorithm will be proposed for autonomous navigation in an unknown indoor environment.

vckoo@mmu.edu.my

Electricity consumption and load forecasting have been the most important area of research in recent years. Researchers utilized, machine learning, and deep learning techniques for forecasting electricity consumption data. These studies are done to efficiently and accurately predict future electricity production for supply management in the government and private sector. The electricity forecasting methods could be used to predict a large number of unobserved values found in IoT time-series data sources. These observations could be missed due to network failure,ordevice failure, etc. In this proposal, our aim to develop a framework that will use to predict a large number of missing values in IoT energy consumption time-series data. The framework performs data preprocessing before utilizing the data for forecasting. In the forecasting process, the framework will utilize deep learning long-short term memory LSTM neural network model. This model is frequently used in time-series forecasting in recent years using past observation to predict future values. The LSTM model, using complex time series and showed reduced Mean Absolute Error (MAE) and Root Mean Square Error ( RMSE) for medium to long-range forecasting. The major drawback of the LSTM model needs to learn the scalar weights and biases through the back-propagation learning algorithm to update the neural/cell for the next layer. This process requires large computational time which is not sufficient for real-time monitoring systems. we aim to cover this issue by modifying or maybe use some different learning algorithms that minimize the processing time without sacrificing accuracy. This study also compares the results of our framework with statistical ARIMA and machine learning LS-SVM models. These models were extensively used in past studies for electricity consumption.

jakir.hossen@mmu.edu.my

In Malaysia, Pos Laju introduced EziBoxes for parcel pick-ups at the convenience of the recipients. If you’re not home to receive your Pos Laju parcel when it arrives, you won’t get a note on your gate anymore. You will receive an SMS informing you that your parcel is currently in an EziBox. All you have to do is head over and collect your parcel from their boxes that are accessible 24/7, within 48 hours.

With the same concept, we will extend it to collection and also returning of books from these ‘Eziboxes’ designed especially for library users. Let us call it LibBox (library box).

1. You choose the books you want to borrow. The librarian will find the books and put it inside the LibBox. You get to choose the location of the LibBox. You get an SMS once it is ready for collection.
2. You can also return books through a LibBox.
3. The LibBox is autonomous. It can automatically move on its own from library to its designated location in campus. Locations such as in front of faculty offices or lecture halls.

scchua@mmu.edu.my

Avalanche photodiodes (APDs) are widely used in optical receivers for high-speed communication systems. The material AlGaAsSb have been measured for evaluating its potential as an alternative avalanche material for APDs. The limited data in previous measurements and simulation results for AlInAsSb is the motivation of this research. Since the impact ionization coefficients determine the breakdown voltage and the safe-operating area of APDs, the accuracy in the determination of the impact ionization coefficients in AlInAsSb has been an important issue to design high gain, low noise and high speed device. AlInAsSb APDs has been measured by many researchers. The current issues to be solved
are the presence of multilayers structure, hole injection mechanism and polarization induced charge at the hetero-interface arising from the lattice mismatch and difference in spontaneous polarization between the multiplication regions in APDs.

ahyou@mmu.edu.my

Lithium ion (Li-ion) batteries are widely used in electric and hybrid vehicles, smartphones, computers etc in recent years. With the current challenge, solid polymer electrolytes (SPEs) are chosen as one of the most considerable solutions to solve the security issues for Li-ion batteries because they possess several advantages such as fire resistance, no-leakage, and outstanding stability in electrochemistry. Among all the polymer electrolytes, poly(ethylene oxide) (PEO)-based SPEs have attracted extensive interest for real practical applications.
The main objective of this project is to develop and test a completely working prototype of
LiFeO4/PEO-EC-LiCF3SO3-SiO2/Li cell for commercialization in near future. In this study, PEO-based (PEO-EC-LiCF3SO3-SiO2) SPEs with 2 wt% of SiO2 nanofillers will be prepared and characterized.

ahyou@mmu.edu.my

In this project, functionally graded PLA hollow structures will be 3D printed and subjected to quasi-static axial loading or impact. The aim is to find important aspect of functional gradation that maximizes impact energy absorption, and to relate the fracture modes with the amount of absorbed energy.

ckkok@mmu.edu.my

The objective of this project is to design a powerful tool for early detection of machinery breakdown. It can be achieved through acoustic condition monitoring via airborne sound analysis in conjunction with advanced signal processing and machine learning methods. The Hilbert Huang Transform (HHT) is proposed, as it is an adaptive signal processing technique emerged recently. A deep neural network is proposed for machine learning activity as it is one of the most sophisticated mathematical models to process data in complex ways. The methodology involves collecting extensive data from the real factories involved rotating and moving machineries. This data includes recorded sound signals of various normal and abnormal conditions of the machineries. Few microphones will be used for this purpose. These multicomponent sound signals because of noise in it, will be decomposed into mono component signals using empirical mode decomposition technique (EMD) of HHT. All the necessary features required to train the deep neural network (DNN) will be extracted from these decomposed sound signals using Hilbert transform. These features will be used to train the deep neural network. The trained neural networks will be tested for its classification accuracy for the sound data collected from the same factories. After fine tuning the parameters, the system can be recommended for implementation of factory use.

emerson.raja@mmu.edu.my

This project will involve the fabrication of electrochromic smart window devices based on solid-state electrolytes, which is expected to be deployed as intelligent windows for smart building applications.

kychan@mmu.edu.my

Efficient Optix implementation of GPU propagation ray tracing is desired. However, most previous works focused more on the application aspects and gave little account on the challenges or problems of efficient Optix implementation. Consequently, the learning curve is steep and researchers could unknowingly reinventing the wheel or adopting an inefficient solution. In this project, we will develop a GPU ray tracer for propagation modelling using Optix. In doing so, we strive to lay the ground work for efficient Optix implementation of GPU propagation ray tracing, by uncovering and spelling out the challenges, proposing possible solutions to the challenges, and evaluating their performance in terms of speed, memory, and accuracy.

Note: Full-time only; before 31/12/2021

chteh@mmu.edu.my

The advent of Electric Vehicle (EV) accelerates the trend for designing more and more new sensors and actuators by global automotive sensors manufacturers. On-board automotive sensors powered by means of wires from battery increase car design complexity, adding significant to the car weight and higher cost leading to very complicated sensing architectures and many other problems related to the maintenance and reliability. A new approach for autonomous on-board sensing systems based on the self-powering by means of micro Energy Harvesters (EH) is emerging. While bulk piezoelectric, EH can produce enough power for a few tens of mW, the insufficient power is still a major issue during miniaturizing into micro scale. Contrary to the traditional designs based on cantilever beams which use the bending strain, a novel design is needed to be investigated particularly for the EV application. Because in EV application the EH device will be in direct contact with the driving force and the ambient acceleration amplitudes will be too large for the previously examined cantilever devices. Ubiquitous mechanical vibration in vehicles environment is a key promising source for the MEMS based micro generator for the conversion of the mechanical power into electrical power for the self-powering of vehicles on-board sensing systems. With the development of Micro-Electro-Mechanical-System (MEMS) technology miniaturization feasibility promotes the integration of MEMS based micro Energy Harvesters and ultra-low-power Very Large Scale Integration (VLSI) circuits to form self-powering sensor nodes. In future thrusts of research, it is believed that new geometries and device structures that is apart from cantilever based design, will allow for significant improvements in EH efficiency, eventually granting the realization of truly autonomous MEMS devices. This study will focus to design and fabricate a novel cymbal-type EH device vibration-based MEMS micro EH device that will use tensile stress/strain on the piezoelectric film in order to generate energy together with interface power conversion circuitry. Issues related to the geometric optimization, robustness, reliability of the device, fabrication process including the integration of piezoelectric thin film, structure design for high power density, and CMOS power management circuitry of device will be focused. This is expected to provide the optimal desired dc output power characteristics with high efficiency satisfying all the desired parameters and also maintain an output power that can be used to power EVs sensor networks instead of the conventional batteries.

Note: Full-time only. Candidate needs own financial support.

shabiul.islam@mmu.edu.my

Poor ventilation could have led to airborne transmission of COVID-19 in restaurants. To prevent the spread of the coronavirus, indoor spaces should prevent overcrowding, open windows or doors, and ensure adequate air distribution. To measure how well ventilated a space is, most engineers look at the air change rate—how frequently the air is exchanged with non-contaminated outside air. In the days before Covid-19, most spaces weren’t designed to have high air change rates; they were really used to only limit body odors, the amount of carbon dioxide, and the presence of other chemical or particulate pollutants in indoor spaces. More business owners and building managers are looking to boost the air change rate in their space, either by improving the ventilation (air change rate) or filtration (removing airborne particles). Cooking emissions (in restaurants mostly removed via exhaust hoods) and other volatile compounds can be detrimental to health.

lim.wee.kuan@mmu.edu.my

Devise experimental study and/or numerical modelling to gauge the effectiveness in air filtering, in the use of multuple masks as compared with using a single mask, during a pandemic.

Note: Candidate must have a degree in mechanical engineering.

cptso@mmu.edu.my

Microchannel flow has applications in electronics cooling and others. The thermal effect of an oscillatory surface on a fluid-filled microchannel is lacking in research and is the subject of this project. The investigation uses analytical and/or numerical methods using principles of fluid mechanics and heat transfer.

Note: Candidate must have a degree in mechanical engineering or in applied mathematics.

cptso@mmu.edu.my

There have been concerns about viruses left by the infected, and lingering in the air-conditioning system. This project investigate ways to remove or destroy the viruses through improvement(s) in the air-con ventilation design so that indoor environment can become clean again. The measures could also counter the sick building syndrome.

Note: Candidate must have a degree in mechanical engineering.

cptso@mmu.edu.my

The solar energy is one of the energy sources in green technology. This project investigates the cost-benefit of replacing traditional grid electricity with solar powered electricity, and involves estimation of some details in a proposed change, as applied to a university campus. The methodology is applicable to other building complexes.

Note: Candidate must be trained in mechanical or electrical engineering.

cptso@mmu.edu.my

The processor is the core component of all electronic systems. RISC-V is an open and free instruction set architecture that gaining huge popularity for electronic systems. RISC-V is an open-source Instruction Set Architecture (ISA) which is license-free and royalty-free. The ISA standard is suitable for all levels of computing systems, i.e. from micro-controllers to supercomputers. The RISC-V ecosystem is rapidly growing, ranging from hardware, e.g. various hardware implementations (free as well as commercial) to high-speed Instruction Set Simulators (ISSs). A major industry-proven approach in earlier phases of the design flow is to employ Virtual Prototypes (VPs) of the RISC-V microprocessor. One of the potential works is to design an extensible and configurable high-performance low-power high-speed RISC-V virtual prototype.

wlpang@mmu.edu.my

A eco-friendly red banana peduncle fiber reinforced polymer composites (RBPF) and wood flour are added as a filler (RBWF) were prepared using compression moulding process. These composites were analyzed by testing of properties such as tensile strength, flexural strength, impact strength, and water absorption. Tensile and flexural properties of the composites are verified using ANSYS.

palanisamy.chockalingam@mmu.edu.my

This project aims at developing an imitation bone using biomimetic process and develop a prototype of bone implants using 3D printing. Synthesis nano HAp from natural oyster shells, Egg shells by novel modified chemical precipitation or sol-gel techniques. Similarly, the preparation of nano bio composites has to be carried out through phase inversion techniques. Nano indentation technique is also to be used for finding out the fracture toughness to obtain the exact value closer to that of natural cancellous bone. By using 3D Printing Technology to fabricate the prototype implants for kinematic analysis and tribological behaviors.

palanisamy.chockalingam@mmu.edu.my

This research proposal is aimed to investigate dissimilar joining of sheets of varying thickness (3-8mm) of Cupronickel and Titanium alloys using hybrid laser TIG welding process. These metal joints is expected to be superior in mechanical properties, hardness and corrosion resistance and found suitable for the fabrication of marine components. Optimization of welding parameters and error prediction will be carried out by using Taguchi and adaptive neuro-fuzzy inference system using MATLAB. After High Velocity Oxygen Fuel (HVOF) treatment, it is proposed to conduct mechanical characterizations like Tensile test, Impact test, Vickers hardness test, and bend test and metallurgical characterizations such as FE-SEM, EDAX on the coated and un-coated LTIG weldment.

palanisamy.chockalingam@mmu.edu.my

This project focuses on repurposing EV discarded batteries for various applications that may be more efficient with battery storage system. The project will concentrate more on the performance of those repurposed batteries for selected applications and economical analysis.

gobbi@mmu.edu.my

In the current digital world, Digital twin is an emerging technology. DT is one gaining Importance in manufacturing, to monitor the performance, optimize the progresses, simulate the results and predict the potential errors. A Digital Twin (DT) is a set of computer-generated models that map a physical object into a virtual space. The focus is on the construction of DTs. More specifically, on determining (methodologically) how to design, create and connect physical objects with their virtual counterpart. To explore the problem into several phases: from functional requirement selection and architecture planning to integration and verification of the final (digital) models. Finally, address as well how physical components exchange real-time information with DTs, as well as experimental platforms to build DTs (including protocols and standards).

palanisamy.chockalingam@mmu.edu.my

Wireless communication systems have evolved and offered more smart and advanced systems like ad hoc and sensor-based infrastructure fewer networks. These networks are evaluated with two fundamental parameters including data rate and spectral efficiency. To achieve a high data rate and robust wireless communication, the most significant task is channel equalization at the receiver side. The transmitted data symbols when passing through the wireless channel suffer from various types of impairments, such as fading, Doppler shifts, and Intersymbol Interference (ISI), and degraded the overall network performance. To mitigate channel-related impairments, many channel equalization algorithms have been proposed for communication systems.

gcchung@mmu.edu.my

Deep Eutectic Solvent (DES) is a mixture of a substituted quaternary ammonium salt and a hydrogen bond donor. DES emerges as an alternative to conventional ionic liquids in the area of green chemistry. This project applies experimental and/or numerical approach to investigate the thermophysical properties of DES and its applicability to potential engineering applications.

Note: Only full-time candidate is accepted. Candidate must have a degree in Mechanical or Chemical Engineering.

lim.elaine@mmu.edu.my

Graphene sand composite (GSC) is sand coated with carbon source to form black-colored absorbent to remove substances from the polluted water source. In this project, graphene sand composite will be prepared and experimental investigation will be performed to study the potential of GSC as absorbent for waste water treatment.

Note: Only full-time candidate is accepted. Candidate must have a degree in Mechanical or Chemical Engineering.

lim.elaine@mmu.edu.my

Digital twins have emerged as one of the most promising technologies in the realm of industrial Internet of Things (IoT). By creating a digital replica of a physical entity, industries can predict, monitor, optimize, and analyze their operations in real-time. The solar industry, which is at the forefront of sustainable energy, is no exception. Digital twins for solar plants can provide unparalleled insights into their operations, maintenance, and performance.

The tropical region of Malaysia is marked by unpredictable and inconsistent wind behaviors. These fluctuating wind conditions challenge our traditional understanding and application of wind energy systems. Standard wind turbines, designed primarily for steady and robust wind scenarios, often underperform in such inconsistent wind settings, leading to subpar energy capture. This suggests that the full potential of wind energy in areas like Malaysia remains largely unexplored.

Peer-to-peer (P2P) electricity trading is the next-generation solution to the urgent problems associated with rising electricity demand and promoting the use of renewable energy sources. Such localised networks, however, are highly uncomfortable for prosumers and frequently linked to strategies for load shifting. Another challenge is balancing the supply and demand for electricity in the community. Although there are still challenges facing P2P trade, the decreasing price of
solar panels and improvements in storage device technology, such as vanadium redox flow batteries, offer an alternative viewpoint. This project aims to study the correlation between prosumers’ behaviour in response to different trade prices. These correlations will subsequently be represented by an optimization model on the multi-level storage management system in order to achieve the demand-supply balance.

Note: GRA allowance of RM2000 per month under FRGS

The project involves the design, development and realization of the integrated electrochromic-photovoltaic devices for switchable-energy harvesting smart glass applications.

This project involves the realization of thin film based perovskite solar cells and device characterizations of the solar cells.

This Project involves the development and device performance studies of solid-state electrochromic devices for smart glass applications.

This project involves the design and development, and performance studies of the resistive switching devices for memory device applications.

To design and develop a customized computer vision model to effectively detect and count the number of tree crowns in a Malaysian dipterocarp forest with reliable accuracy via aerial image of tree crowns by UAV.
Key Deliverables:
1) A computer vision model to accurately count tree crowns in aerial images of dense forests
2) Improvement in counting accuracy through customized aerial object detection ML training

ykchan@mmu.edu.my

The international standards on lightning protection risk management is expected to be published by the end of 2024. Much like its preceeding editions, the risk assessment is a rigorous, tedious and cumbersome process involving multiple parameters to be analysed. As the result, consulting engineers and lightning protection solution providers alike would find it challenging to accomplish given the tight project timeline. Hence, this project aims to conduct sensitivity analysis to identify the most significant parameters in the said standards. Comparative analysis against the preceeding editions would also be done to yield invaluable insights on the significant differences brought forth by the upcoming edition. Finally, an assessment tool will be developed.

clsiow@mmu.edu.my

In recent years, collaborative robots (cobots) have gained immense popularity in industrial automation due to their ability to work alongside human operators, improving productivity and safety. To further enhance the capabilities and performance of cobots, the integration of digital twin technology offers great promise. A digital twin is a virtual representation of a physical object or system, and its application in cobots can lead to increased efficiency, predictive maintenance, and optimized performance. This research proposal aims to investigate the potential of using digital twins to augment cobot capabilities and revolutionize the field of collaborative robotics.

Research Objectives: The primary objectives of this research are as follows:
a) To explore how digital twins can be utilized for real-time monitoring, predictive maintenance, and performance optimization of cobots.
b) To evaluate the impact of digital twin integration on cobot performance, efficiency, and safety in industrial settings.

palanisamy.chockalingam@mmu.edu.my

Deep learning has experienced rapid development in recent years. When applied to channel estimation, deep learning does not heavily rely on a precise channel model. In RIS assisted systems, deep learning can be used to estimate the cascaded channel or the individual channels for both the IRS and hybrid RIS. In an IRS-assisted system, deep learning is usually adopted to estimate the cascaded channel. By directly regarding the received pilots at the BS or user side as the input of the neural network, the estimate of cascaded channel can serve as the output of a convolutional neural network. Alternatively, deep learning can be introduced to further enhance the accuracy of LS or LMMSE cascaded channel estimation results. Three practical residual neural networks were adopted to improve the cascaded channel estimation accuracy, whilet he network input was the received pilot matrix. Deep learning-based channel estimation is also preferable in hybrid RIS-assisted systems. For the selection-type hybrid RIS especially, since pilots can be received by a small amount of active units, only the sampled channel on these units can be directly estimated.Then, the full channel can be extrapolated through a residual network. The input ofthe network is the sampled channel, and the output is the full channel. The denoising approach can be further applied here. Considering that the accuracy of the full channel reconstruction from a few observations on the active sensors is limited, a denoising neural network can be employed to refine the channel reconstruction result.

Note:No grants available to date yet

azwan.mahmud@mmu.edu.my

Mobility for individuals with visual impairments is a challenge. Traditional white canes have limitations in detecting obstacles above knee level. This project aims to create an affordable, smart blind stick that can help blind people navigate more effectively.

yksin@mmu.edu.my

In recent research, the focus on metal oxide pH sensors has intensified due to their applications in smart farming and wearable devices. While iridium oxide and ruthenium oxide are promising materials for pH sensors, their large-scale production is costly. In contrast, zinc oxide offers a cost-effective alternative. Zinc oxide is biosafe, non-toxic, and suitable for miniaturization. However, the effects of zinc oxide’s physicochemical properties on pH sensing remain unexplored. Researchers are investigating particle size and surface charge of zinc oxide to enhance sensor sensitivity. The study involves synthesizing aluminum-doped zinc oxide nanoparticles and characterizing their properties. Ultimately, a pH sensor using these nanoparticles aims for sensitivity comparable to iridium oxide and ruthenium oxide.

yksin@mmu.edu.my

As the wireless communication network are advancing into 5G, there are a large of amount of data are shared on the newly developed open source platforms. These data can be employed in developing new services. Among of these, location information of mobile devices is very useful. For instance, the location information can be employed to assist the wireless operators to enhance the network performance. In addition, it provides the location assisted service as well. However, some of the mobile devices may be designed for the limited budget that do not have the GPS capability. Besides, the cellular operators may not have access to the GPS information on the mobile devices. In this project, a novel machine learning based technique is proposed to estimate the location of the mobile devices based on the measurement data that mobiles obtained during every call and session in achieving high accuracy of the location.

jjtiang@mmu.edu.my

A smart antenna design approach is described as selecting the optimum antenna parameters and providing the best geometric dimensions for the demands of antenna performance. Various antenna performance characteristics are examined such as rectangular patch antenna, horn antenna, and helical antenna. The optimal antenna size parameters are determined using a fuzzy inference method. The Mean Square Error (MSE) and MAPE are used to optimize the antenna design. An intelligent machine learning based antenna characterization and geometric parameters prediction model are developed in this project.

jjtiang@mmu.edu.my

IoT-based sensors are vital in the connected technology realm. As IoT is gaining prominence, physical sensors help streamline operations making organizations more productive, massive data collection, and huge implementation.
To streamline sensors data collection, virtual sensors can be implemented. Virtual sensors have the key advantages include improved sensitivity during data capture, almost lossless transmission, and continuous, real-time analysis. Real-time feedback, and data analytics services ensure that processes are active, and are executed optimally.
Project Objective:
a) Feasibility analysis of hybrid virtual-physical IoT sensor for industrial monitoring
b) Methodology of hybrid sensing to investigate the conceptual of integration
c) Research paper of the hybrid sensor systems for industries

Note: Allowance RM3000 per month
Postgraduate Master’s Fees Included

Engineering drawings are crucial for various engineering disciplines, providing detailed instructions for design, assembly, and maintenance. Given the frequent revisions these drawings undergo, accurately detecting and analyzing changes is essential. Traditional manual methods for change detection are not only time-consuming but also prone to errors. This research aims to address this issue by developing an automated system leveraging visual cues to detect and analyze changes in engineering drawings. The primary objectives include investigating existing methods, developing a visual cue-based algorithm, implementing it into a functional prototype, and evaluating its performance against traditional and existing automated methods. The methodology involves data collection of various engineering drawings, preprocessing to standardize formats and enhance image quality, and algorithm development to identify and extract visual features like lines, shapes, and text. Feature matching and machine learning techniques will be employed for change detection and classification. A prototype system will be developed, integrating the algorithm with a user-friendly interface for visualizing changes and providing analytical tools. The system’s performance will be evaluated on a dataset of engineering drawings, measuring accuracy, precision, recall, and processing time, alongside user studies to assess usability compared to manual methods. This research is expected to produce a robust algorithm and a functional prototype demonstrating its capabilities, offering significant improvements in efficiency and accuracy of change detection in engineering drawings. The outcomes will benefit industries reliant on precise documentation, contributing to advancements in visual content analysis and engineering process automation. The research timeline spans a year, with the initial months dedicated to literature review and data collection, followed by preprocessing, algorithm development, prototype implementation, testing, evaluation, and concluding with documentation and thesis writing. This study will compile a comprehensive list of references from academic papers, books, and industry reports on relevant topics. The successful implementation of this research will not only streamline the process of change detection in engineering drawings but also pave the way for future innovations in visual content analysis and automated engineering solutions.

fazly.salleh.abas@mmu.edu.my

Engineering and technical drawings are essential for documenting design and assembly processes in various industries. As these drawings undergo frequent revisions, there is a critical need for an efficient version tracking and register system to manage changes accurately. Traditional methods for tracking changes are often manual and error-prone, leading to inefficiencies and potential discrepancies. This research proposes the development of an automated system utilizing image analytics to track and register versions of technical drawings. The primary objectives are to investigate existing techniques, develop an image analytics-based algorithm for version tracking, implement this algorithm into a functional system, and evaluate its effectiveness compared to traditional methods. The methodology involves collecting a diverse set of technical drawings, preprocessing to ensure consistency in format and quality, and developing an algorithm to identify and analyze changes between versions. The algorithm will leverage advanced image processing techniques to detect modifications in visual features such as lines, shapes, and annotations. A prototype system will be created, integrating the algorithm with a user interface designed to visualize version changes and manage a register of drawing versions. The system’s performance will be evaluated on various technical drawing datasets, focusing on metrics such as accuracy, processing time, and user satisfaction. This research aims to deliver a robust system that enhances the efficiency and reliability of version tracking in technical drawings, benefiting industries reliant on precise documentation and change management. The outcomes will contribute to advancements in image analytics and automation in technical documentation processes. The research timeline spans one year, starting with a literature review and data collection, followed by algorithm development, system implementation, testing, evaluation, and concluding with documentation and thesis writing. This study will reference relevant academic papers, books, and industry reports, ensuring a comprehensive understanding of the field. The successful completion of this research will provide a valuable tool for managing technical drawing versions, promoting accuracy and efficiency in engineering and related fields.

fazly.salleh.abas@mmu.edu.my

This project focus on the implementation and development of RISC-V bare-metal for smart farming application. Bare-metal development inclusive of using C language to assembly and machine code. And further to optimization and validation of RISC-V core in RTL level.

Note: Only graduates from Bachelor’s degree of Electronics Engineering or Computer Engineering are accepted.

cllee@mmu.edu.my

Existing research in path navigation utilizes various techniques like LIDAR and sensor-based navigation, which are reliable but expensive and limited in range. Machine learning approaches can struggle in dynamic environments due to their reliance on pre-defined maps. While deep learning shows promise for obstacle detection and path generation, existing methods often perform full image segmentation, which is computationally expensive for real-time applications. This research proposes a novel solution: a selective image segmentation approach using deep learning. This will focus on identifying key features crucial for navigation, addressing the limitations of computational cost and offering a more robust solution for path navigation in dynamic environments.

Note: Full-time candidate only. Registration by September 2024.

hidayati.aziz@mmu.edu.my

yusoff@mmu.edu.my

yusoff@mmu.edu.my

mardeni.roslee@mmu.edu.my

jakir.hossen@mmu.edu.my

mardeni.roslee@mmu.edu.my

hezerul@mmu.edu.my

ykchan@mmu.edu.my

t.bhuvaneswari@mmu.edu.my

emerson.raja@mmu.edu.my

hidayati.aziz@mmu.edu.my