Grant Details: UBD/RSCH/1.3/FICBF(b)/2020/011 Due to the recent environmental concerns and long-term challenges in energy security, the Global energy scenarios are shifting more towards sustainable and renewable energy resources. As rightly reported by the International Renewable Energy Association (IRENA), renewable energy technologies are fast becoming cost effective and soon can compete with the traditional energy options. Brunei has planned to increase the use of cleaner energy technologies by contributing 10 percent or 954 GWh of renewable energy in its power generation mix by 2035. Out of the available renewable options, solar is the most promising one for Brunei, for example, the daily average solar installation is around 5kWh per day [Energy and Industry Department of Prime Ministerâ€™s office (2016]. Though solar energy is an abundant resource, for optimally designing and successfully managing solar power projects, its availability in different time scales are to be analysed and understood in a local context. The objectives of the proposed project is to develop such design and management tools by applying machine learning and deep learning algorithm. In the first part of the project, a tool for estimating the power produced by different commercial PV systems under the varying solar insolation at a prospective site will be developed. This machine learning model will highly be relevant for designing solar power systems under Bruneian environments as it is based on the long term performance data from the Tenaga Suria PV project. Further, a system for forecasting the power developed by the solar PV plants in different time scales will also be developed and tested. Such forecasting system will be useful in the power dispatch and management of the solar systems installed in Brunei. Apart from the scientific contributions through publications and scientific networking, the project is also expected to equip UBD to support the national vision of supplementing the energy base with renewable and sustainable energy resources.
The effect of ageing on biometric systems and particularly its impact on face recognition systems is a challenging area for research. Face ageing in humans is the result of multi-dimensional process of physical, physiological, and social change, which affects considerably the appearance of a human face. Being biological tissue in nature, facial biometric trait undergoes significant changes as a person ages. Ageing-related appearance variation due to bone growth normally occurs throughout childhood and puberty, whereas skin-related effects principally appear in older subjects. Looking from the face recognition point of view, ageing of the face images of the same person brings confusion which degrades the system performance dramatically. In many practical systems (e.g., passport control, etc.), the time intervals between two acquired images can lead up to several years. The ageing factor is very significant in face images. In comparison to other facial variation (pose, illumination, etc.), adaption to template ageing deserves a dedicated treatment of its own, since ageing is a lifelong process. Ageing also bring gradual changes in the data distribution over time, thus causing performance loss as a result of template becoming outdated. These factors indicate that template ageing process is very similar to the concept drift theory, based on the fact that real-worlds concepts change with the time resulting in underlying data distribution to change. When compared with other source of variation in face images, ageing variations is specific to a given individual. It can occur slowly and is affected significantly by other factors. The appearance of a human face is affected considerably by the ageing process.
Recently, a technology-based bio-inspired has shown a gradually impact on human life. This project aims to study a flying behavior of bat as a preliminary study on the unmanned aerial vehicle (UAV) for video aerial monitoring in Brunei. The ultimate goal for this long-term research study e.g. for monitoring bush fire in Brunei. The objective of this project is to model the kinematics of sophisticated bat flapping behavior using SolidWorks. The bat flapping-wing design project starts by investigating bat flying behavior in an indoor tunnel designed by internship Virginia Tech University students. The bat flying behavior will be captured by high-speed cameras installed inside the tunnel. According to this video camera recording, a detail of a bat flapping wing mechanism will be sketched. A four-bar-linkage mechanism will be used to model the bat flapping-wing movement. Once all parts are designed, the part will be printed using a 3D printer and will be building a prototype.
Over 2.2 million people per year require surgery to repair critical bone defects resulting from accidents, diseases, and trauma. The people with a bone fracture are usually undergoing with two times surgery, one for bone repair to attach the metal implant and another one is for removing the metal implant from the body after the bone has been recovered. This second surgery may psychologically inconvenient for the patient because of pain or required an additional cost. Due to this reason, an absorbable metal implant is necessary. The implant has certain desired structural/mechanical properties and a desire to minimize the toxicity effect against the human body. With the development of material science engineering, absorbable metal implants are currently being developed in decades. The objective is one the metal implant attached to the body, it is not necessary to remove the metal implant from the body because it can absorb to the body by a chemical reaction and biological process. The research mainly focuses on the measurement of biomedical materials corrosion inside the body. Where this will affect directly for the health for the human. The present invention related to the field of bio-medical implants made of biodegradable material could be advantageous for a temporary application, such as mechanical support during bone healing. After completion of the healing process, the implant should be removed to avoid long-term side effects.
In recent years, the development of advanced manufacturing technology has been continuously pushed towards a higher demand for specification due to a need for better and more consistent product quality, reduced product cost and shorter manufacturing process. The advancement of the manufacturing process equipped with an intelligent method opens possibilities to answer the existing challenges. To date, the surface quality monitoring of abrasive processes such as grinding and polishing relies on a visual inspection and is typically conducted in offline mode once the entire process completed. The surface quality measurements such as thickness, surface roughness, and material removal rate require a considerable amount of time and skilled operators, because of the repetitive process (de-mounting and mounting) of the component/work coupon to the fixture. This research will develop a real-time monitoring method for the abrasive process by connecting sensor, robot and DAQ device in the hardware setup; and embed a deep learning method into the system integration. A convolutional neural network (CNN) will be used in this research to predict the surface quality parameter. The prediction result of CNN will be connected to the robot to provide a decision on whether the current process is operating in normal mode. If the process is running abnormally, the process parameters will adaptively be altered based on the decision input from the CNN method. This real-time monitoring and the adaptive mechanism will maintain the quality of the component with reduced overall manufacturing time.
Globally, there is a growing concern on air pollution and its impact on health and the environment. To date, World Health Organization (WHO) reported that there are 4.2 million deaths every year due to exposure to ambient (outdoor) air pollution. They also reported that 91% of the worldâ€™s population lives in places with air quality exceeding WHO guideline limits. The project aims to predict air quality and occurrence of haze in Brunei Darussalam.
This work investigates an additive manufacturing route of producing functional net shaped parts from pre-alloyed magnetic shape-memory alloy powders e.g. Ni-Mn-Ga and TiNi. Shape memory alloy powders that will be used in this investigation will be produced by ball milling (BM) method. Additive manufacturing via Direct Metal Laser Melting (DMLM) will be used in this research due to the reason that it removes the need of post-printing sintering and the possibility to obtain complex shaped parts from the shape memory alloys. The fourth-dimension (4D) is created by the predictable change in 3D printed part configuration over time as the result of shape-memory functionality. DMLM will be proved successful in producing net shaped porous structures (spring-like, 3-D hierarchical lattice structures, etc. with good mechanical strength. It is intended to produce parts with porosities ~25% by using powders with distinct morphologies. The printed parts undergo reversible martensitic transformation during heating and cooling, which is a prerequisite for the shape-memory behavior. Thermo-magneto-mechanical trained 3D printed parts obtained from ball milled alloy powders will be expected to produce reversible magnetic-field-induced strains (MFISs) of up to 0.01% â€“ 1% for energy harvesting applications and proper sealing behavior for aeronautical applications.
Abstract: Problems with water quality normally link with increased pollutants as a result of human activities. River has constant interaction with its physical environment as well as the climate and human factors. There are two categories of water pollution sources: point and non-point sources. Point source pollution is due to direct discharge from waste water treatment and industrial plants, whereas non-point sources that come from other sources and locations (e.g. residential area). Brunei has 4 major rivers with Brunei Muara district being the most populated district. Hence Brunei river in Brunei Muara district could well be affected with pollutants. Hence it is the focus of this research project to focus on non-point pollution along the residential area of Brunei river and its impact on water quality.
Abstract: Membrane fouling is a major impediment to membrane efficiency and it results in the reduction of membrane performance. Despite the vast efforts to reduce the effect of membrane fouling by improving membrane properties, optimizing operating conditions and pre-treatment of feed water, fouling is unavoidable. Improved hydrodynamic conditions such as manipulating shear rates on membrane surfaces, improved design of the membrane systems, and induced flow instabilities are other useful methods in overcoming membrane fouling and concentration polarization. These methods would be further studied using both experimental and computational methods in a circular cross flow membrane filtration.
Abstract: In 2010, it was reported that BND3.9 million had been allocated to clean up Sungai Brunei. As of 2015, Brunei has not yet been able to control its non-point source of pollution, which carries around 30 to 40 per cent of total pollutant load. The main objectives of the project are to develop IoT systems to monitor the water quality of Sungai Brunei and its tributaries, and to propose mitigation measures to minimize the impact of non-point source of pollution in Sungai Brunei. In order to address these issues, four main tributaries which eventually leads to Sungai Brunei are investigated: Sungai Kedayan, Sungai Menglait, Sungai Tungkadeh, and Sungai Rimba. These areas are heavily associated with steady increase in population growth and economic development which indirectly affecting the overall water quality along these rivers. Each river will have its own proposed sites where IoT systems will be placed and monitored directly. The multi-disiplinary research project will require: measurement of water quality parameters such as pH, temperature, turbidity, conductivity, dissolved oxygen and fecal coliform, development of IoT systems such as sensors, and offer constant real-time online monitoring as feedback to users. This research project will be a subsidiary to our initial project proposal (FIC Research Grant applied) on â€œnon-point pollution and its impact on water quality of Sungai Bruneiâ€. With results gathered from IoT systems and manual data gathering and analyses (from initial project proposal: non-point pollution and its impact on water quality of Sungai Brunei), it is hoped that Sungai Brunei and its tributaries will have its reliable water quality monitoring systems and can assist goverment agencies such as Jastre in proposing preventive measures to preserve the water quality of our Sungai Brunei for the present and future generations. This work will hence add value to the Environmental Impact Assessment (EIA) work at Sungai Brunei.
Brunei has the potential to generate value-added products, chemicals, fuels and energy from biomass or wastes from industries via biomass conversion processes such as gasification and pyrolysis. The concept of biorefinery is the integration of processes which is comparable to petroleum refinery, but instead it uses biomass as its feedstock and has the potential to diversify the economy away from oil and gas. Rice husk, rice straw, grasses, invasive species (eg: Acacia) and microalgae/macroalgae species are a few of many potential candidates of biomass feedstock. However, the selection of biomass feedstock and their characterisation is an essential pre-requisite step to find out whether the material is suitable for conversion. The generated biomass products have to also undergo characterisation to assess their viability towards potential usage in various industrial applications such as energy (biofuels), agriculture and bio-based chemicals. This particular research area is vast, and processes may include a combination of: i) Feedstock pre-treatment; ii) Thermochemical processes such as pyrolysis, gasification and combustion; iii) The incorporation of catalyst such as zeolites, metal-oxides or natural minerals into the processes; iv) Potential separation of selected chemicals/gases
The objective of this project is to design and improve the biomass pyrolysis system, particularly the reactor and feeding unit. Students are required to review the existing system in laboratory, pilot plants and industries, particularly on biomass conversion systems; compare and make several design concepts to suit the requirement. A simple prototype is expected which shall be incorporated onto our existing pyrolysis/gasification system unit. Knowledge on CAD software such as Solidwork is essential.
Photonic crystal fibers (PCFs) are a kind of optical fibers that use photonic crystals to form the cladding around the core. Photonic crystals are low-loss periodic dielectric medium constructed using a periodic array of microscopic air holes that run along the entire fiber length. PCF-based sensors are advantageous over standard optical fiber sensors in many aspects. They not only have great design flexibility but also their holey internal structure can be filled with analyte so that a controlled interaction can take place between propagating light and the analyte sample. This greatly enhances the sensitivity of fiber optic sensors as well as opens up a new direction for making advanced portable sensors. PCF sensors have a wide range of applications. Measurement of different physical parameters like temperature, pressure, strain, twist, torsion, curvature, bend, electromagnetic field, gas and refractive index are a few of them. The research and entrepreneurial communities are interested in this topic due to multiple applications of these sensors in various fields, including civil engineering and the aeronautical and automotive industries. The objective of this project is to develop PCFs for sensing any of the aforementioned physical parameters in the optical and terahertz regimes. This shall be achieved through design, simulation, fabrication and characterisation.
Nanophotonics is an exciting new field of nano-science that deals with the interaction of light with matter on a nanometer size scale. It is a field in which photonics merges with nanoscience and nanotechnology, providing challenges for fundamental research and creating opportunities for new technologies and applications. Nanotechnologies can be exploited by incorporating nano-features into optical fibers to achieve manipulation of light in ways not possible with conventional optical fiber waveguiding techniques. This additional functionality offers great potential of fiber-based nanotechnology for applications in communications, optical computation and medical technology for optical waveguides.
Rapid developments in Photonic Crystal Fibers (PCFs) driven by novel engineering techniques continue to push the limits of optical fiber technology and its applications. This major advancement in PCFs is essentially due to its high design flexibility and geometrical economy. PCFs are the very useful for white light generation. A white light source is usually understood to be a light source generating white light in the visible range of the electromagnetic spectrum. i.e., with a white perception for the human eye. Some typical types of white light sources are incandescent lamps, gas discharge lamps, fluorescent lamps, Light Emitting Diode (LED), and laser based RGB sources. Important properties of white light sources include the colour temperature, colour rendering index, luminous efficacy, temporal coherence, spatial coherence, operation lifetime, radiant flux, and its ability to operate continuously. Many white light sources are required for various lighting applications (indoor and outdoor), where one often needs to generate a substantial luminous flux over extended times. The energy efficiency, largely determined by the luminous efficacy, is then particularly important. Moreover, the attractive properties of PCFs include high nonlinearity, high birefringence, endlessly single mode, and large mode area, etc. These properties make PCFs natural candidates for supercontinuum generation. Efficient supercontinuum generation relies on an endlessly single mode nonlinear medium with tailored dispersion and nonlinearity â€“ essentially a highly nonlinear PCFs. The applications of white light source in illumination such as signs, traffic signals, decorative and architectural lighting, and automobile daylight running lights and brake lights. Other applications of white light source include photography, spectroscopy, and colorimetry. The advantages of white light sources are many, such as their low maintenance cost, tuneability, compact size and robustness, but they also have environmentally important features such as longevity, high energy efficiency and not containing any environmentally harmful substances. The successful application of white light sources will be provided significant economic and environmental benefits.
Microalgae has been considered as 3rd generation biofuel sources from last decade owing to its excellent capability of CO2 capture and sequestration, water treatment, prolific growth rate and enormous energy content. Although energy research on microalgae has spread throughout the world, there is very limited to no initiative experimental studies has been performed particularly in Brunei, given into consideration that the weather in Brunei is quite suitable for growing microalgae. The conditions include adequate rainfall, average temperature of 28 Í¦C and presence of direct sunlight throughout whole year. The research work will examine the bio-energy potential of native blue-green microalgae consortium. The local species of microalgae will be collected and energy properties will be characterized. Proximate analysis comprises of moisture content, calorific value, volatile matter, ash content and ultimate analysis (C, H, O, N, S) will be demostrated through standard ASTM method. Based on the outcome of microalgae biomass characterization, the study will endeavour to blend the biomass with other type of popular bio-energy producing biomass and generate heat by combustion. The Microalgae is aimed to be as a new source of potential bioenergy feedstock for heat and electricity generation, minimizing atmospheric GHG and supplementary options to excessive fossil fuel applications in Brunei.
The conjunction of biomass gasification with solid oxide fuel cells (SOFCs) is a promising and forthcoming possibility for electricity and heat cogeneration along with profound environmental and socioeconomic benefits. This is in-line with one of the strategies to achieve GDP target of 63% contibution from the non oil and gas sector, i.e. innovation technology and creative industry. Solid oxide fuel cells (SOFC) are in the commercialization phase and, therefore, would be interesting to integrate with biomass gasification technologies to have a single and highly efficient system; combining the benefits of each system to establish a new technology. Biomass fuelled integrated SOFC system is one of the key energy technologies of the future since it combines the merits of renewable energy sources and hydrogen energy systems. Together with an integrated gasification plant that gasifies wood chips in a two-step gasification process, electricity and heat will be produced in an environmentally friendly way. The produced heat will be used for water purification. This is a novel technique to produce electricity and driniking water, and lots of space to do research and development.
Supercapacitor is an energy storage device that attempts to combine the high power density of a capacitor with the high energy density of a battery. Conventional supercapacitors use carbon based electrodes, mostly graphite. In recent years, alternatives such as carbon nanotubes, graphene, and other nanostructured materials have been considered to construct supercapacitor electrodes.
There are many ceramics that has been investigated as potential anode materials and many of which are perovskite-type structures. Recently, double perovskites with the general formula A2BB/O6 have also been reported to be good anode materials.Changing of the A and B-site cations has strong effect not only on its structural and electrochemical properties but also on the performance in fuel cell applications. Many compositions have already been studied and many more is on-going to find the best composition. Huang et al.  reported that the double perovskite Sr2MgMoO6-Î´ has been an excellent anode as it yielded high power density and has high sulfur tolerance. Bernuy LÏŒpez et al. shows high redox and 1200 Â°C under 5% H2/Ar reducing and stability and up to 1000 Â°C under 5% H2/N2 conditions. However, recent work done by Bi et al. shows that the material possessed very poor intrinsic catalytic activity for oxidation of both H2 and CH4 in the absence of Pt mesh/paste as current collector. On the other hand, Vasala et al. has investigated the effects of W and Nb substitution on active element Mo in the structure and electrical properties. Niobium compounds are well known to show an excellent catalytic activity for different reactions, being used as active catalysts for methane oxidation. To our knowledge, no work has been done on the double perovskite material Sr2FeNbO6-Î´ as an anode in the application of solid oxide fuel cell. Fe and Ti ions are stable cations and have good stability of the perovskite structure against reduction. . Y.-H. Huang, R. I. Dass, Z.-L. Xing, and J. B. Goodenough, â€œDouble Perovskites as Anode Materials for Solid-Oxide Fuel Cells,â€ Sci. , vol. 312, no. 5771, pp. 254â€“257, Apr. 2006.
Grant Details: UBD/RSCH/1.3/FICBF(b)/2018/001: Internet of Things for Residential Monitoring System (BND$20,000) Statistic has shown that water and electricity usages in Brunei is among the highest in the region. This is despite the fact that globally, over 1 billion people across the globe are not receiving clean water. Normally, treated â€˜tapâ€™ water contains about 300+ chemicals and pollutants; even after treatment mainly due to pathogens gaining access to the system. This is made worst by industries; contaminating the water sources such as rivers, seas etc. The main objective of this project is to develop suitable IoT systems for water and electricity monitoring in terms of water-usage, electricity usage, flow and quality. By employing data analytics, it shall be able to detect abnormalities; leakages and quality changes, and raise alarms to house-owners/authorities. The multi-disciplinary project requires the identification of important parameters for water-quality control and electricity, development of IoT systems such as sensors and communication link, development of analytical tool, as well as the development of interface to provide feedback to users. It is envisaged that the project would produce affordable but effective tools which would assist house-owners in controlling their water-usage and quality as well as electricity usage, authorities for detections of leakages and preventions of contaminants as well as other relevant agencies
Brunei is blessed with a wide variety of plants in its wild forest; with some endemic plant only found locally, having impressive medicinal properties. Researchers at Institute of Biological and Environmental Research (IBER), UBD have been studying different varieties of endemic plant from different perspective: growth conditions, medicinal properties, etc., and they are interested in engaging with the engineering faculty to design and prototype a system that is able to monitor different parameters related to the plant as well as feedback mechanism to maintain optimal growth conditions. As such, only students interested in combining engineering with agriculture need to apply. It is expected that the system shall constitute of sensors, actuators, communication device, data storage capability and data analytic capability; depending on the requirements from the potential uses. Subsequently, the student is expected to design, prototype and test the design. Different parameters such as soil moisture, temperature, humidity, etc. are expected to be monitored and kept in a database to produce time-series data for off-line analysis. The system may be extended to feedback system with analytic capability. As an end product, the student is expected to produce a system that is capable to be used by researchers for monitoring as well as for their experiments to find optimal growth conditions of different species of plant.
Generally, we relies on GPS location tracking for our orientation; despite its low accuracy and dependency on actually receiving enough GPS signals to enable location detection. There is, indeed, many circumstances that we may not be able to receive enough GPS signals. The purpose of this project is to design and prototype a low-cost system with reasonable accuracy that is able to give us our coordinates. For the project, the student is expected to do a thorough literature review of the different methods that may be used for location detection under different circumstances. General user requirements shall then be dictated to the student, for the design, prototype and testing of the system. It is expected that different systems be tested in terms of accuracy and power requirements; to satisfy different needs of different possible users.
The clamshell can be utilized in hydroxyapatite (HAp) synthesis due to the presence of high CaCO3 content. Since the characterization and composition of HAp is comparable to human skeletal and dental structure, HAp has been widely used as bone filler, orthopedic implants coating, drug carrier and other biomedical applications. The common method for HAp synthesis such as chemical precipitation, hydrothermal and chemical vapor have not reported a good control on the morphology of HAp because the processes of nucleation, crystal growth and agglomeration are not well investigated. This research project is aimed to optimize ultrasonication method in synthesizing HAp with the hypothesis that this method can influence seeding, direct the crystal growth as well as agglomeration of the compound structure. The HAp composite will be characterized using Thermogravimetric Analysis (TGA), powder X-Ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), Dynamic Light Scattering (DLS) and Scanning Electron Microscopy (SEM) to investigate the morphology, structural and functionalization of the material. The HAp produced will also be tested in biocompatibility with osteoblast cells since the progress of nontoxic nanoparticles and biocompatible has been of interest in recent years to find new material that can support the growth of bone cells.
People around the world participate in many different sports activities for various reasons ranging from personal satisfaction, stress reliever, relaxation and for keeping fit. However, sports is one of the major causes of injuries, which can lead to possible sprains on body parts, disability and even death in severe cases. The most common sports-related injury is ankle sprain. Inadequate treatment of repeated ankle sprains can lead to chronic ankle instability and possibly arthritis in later years. Apart from researches on effective treatment, prevention of ankle sprain injury is also equally, if not, more important. Amongst the many active researches in the field of prevention mechanisms, the design and fabrication of intelligent wearable anti-sprain system is envisioned to help in the foot and ankle biomechanics. This project aims to design, develop and fabricate wearable anti-sprain system which may be attached to relevant parts of the ankle, to detect incorrect landing postures and provide corrective mechanism to prevent such injuries that happen in any sports-related activities. As such, the project shall delve into understanding the reflex mechanisms that happen prior and during ankle sprain, designing suitable sensors, processing unit as well as feedback mechanism. It is envisaged that the device may be embedded in the clothing of athletes (e.g. in a pair of sport legging), and as such, minimally invasive.
While many studies in the literature assumed a similar value for the glucose diffusivity in both water and cell culture media (CCM), Suhaimi et al hypothesized the difference in the composition and hydrodynamic properties of both media should give different respective diffusivities. The results shown have proven the hypothesis to be correct. The glucose diffusivity in CCM has been found to be significantly reduced than the one in water due to CCM having a larger dynamic viscosity than water. Another reason may be due to the presence of extra components and therefore the difference in fluid properties of CCM. Although the result from this research does not exclusively apply to all other biological media/cultures since the variation in composition of media may imply a different diffusivity value, it does highlight the danger of assuming glucose diffusivity in CCM as equal to that in water. Similar to the self-diffusivity of glucose in CCM, the effective diffusivity for tissue engineering (TE) materials imbibed in CCM has also been found to be significantly smaller than those in water which is contrary to what have been generally assumed in the previous studies. This further proves that the presence of extra components is a contributing factor to a difference in the effective diffusivity value. Lactic acid is an example of a metabolic waste product produced by cells. As similar to the vascular system in vivo, we should mimic the system in such a way that the diffusion of lactate acid within the scaffold is also monitored. In this way, it may complete the biochemical communication and especially useful in developing a mathematical model that can simulate real situations.
There are mainly two types of networks, one is Internet and other is telecommunication network. IoT devices connect using one of these existing networks. IoT help towards the goal of the smart city, the smart nation, the smart vehicle, and others using data collection. This project proposes to run an experiment of multiple autonomous driving vehicles in two scenarios (i) ADV trained with sensor and image data i.e. without GAN (ii) ADV trained with data generated through GAN model. A real-world application to improve GAN model is proposed
AlexNet, DenseNet, Vgg, and Inception etc are few deep neural network models with a large number of layers. The gradient over the weights on input washes out with an increasing number of layers, however, accuracy improves. Each layer features are input to subsequent layers so to preserve the information extraction. What could be the optimum number of layers for each state-of-the-art datasets to improve the accuracy? Is it always possible to go for more layers? A solution for the optimum number of layers is to be explored in the project
Malay language, the language of Brunei Darussalam uses the same character set as of the English language. A project wherein data is to be formed and establish a BLEU score for Malay to the English language translation system is to explore. There are projects like- Adversarial text generation, Anomaly text sequence detection is to be studied in the context of Malay language