Prototype of Automated Vehicle Window Using the Detection of Raindrop Sensor

This project presents prototype of vehicle window using the detection of raindrop sensor in order to reduce heat trapped in the prototype. This project will investigate the effectiveness of heat dissipation at different opening gap of power window. The climate seasons are almost the same throughout all year. Temperature are uniformly high throughout the year, it can range up to 33℃ and drop as low as 23℃. Meanwhile, the mean annual rainfall of Malaysia is approximately 2540mm. Since high number of houses in Malaysia does not have garage to park their vehicle inside, the temperature of the car cabin can reach a high temperature when the weather is hot. The rise in temperature in the vehicle cabin is caused by the ultraviolet ray from the sun that passes through the window and windscreen of the vehicle. The amount of ultraviolet ray passing through can be reduced by tinting the window but it is not effective. The propose mechanism for the prototype of vehicle window to reduce the interior cabin temperature. Finally, evaluate the effectiveness of the prototype vehicle window mechanism in reducing the interior cabin temperature. Studies will be conducted to investigate the factors of increasing temperature inside the car cabin. A prototype of vehicle window will be built to propose the mechanism. To evaluate the effectiveness of the prototype vehicle window mechanism in reducing the interior temperature is done by conducting 2 experiments. By doing this project, the prototype has proven that the implementation of automated power window to dissipate heat is effective with the use of raindrop sensor

A review: Use of evolutionary algorithm for optimisation of machining parameters

Optimisation of machining parameters is crucial to ensure higher productivity and optimum outcomes in machining processes. By optimising machining parameters, a particular machining process can produce better machining outcomes within equivalent resources. This paper reviews past studies to achieve the desired outputs; minimum surface roughness (SR), highest material removal rate (MRR), lowest production cost, and the shortest production time of machining processes and various optimisation attempts in terms of varying parameters that affect the outcomes. The review deliberates the optimisation methods employed and analyses the performance discussing the relevant parameters that must have been considered by past researchers. To date, most studies have been focusing on optimising conventional machining processes such as turning, milling, and drilling. Optimisation works have been performed parametrically, experimentally, and numerically, where discrete variations of the parameters are investigated, while others are remained constant. Lately, evolutionary algorithm, statistical approaches such as genetic algorithm (GA), particle swarm optimisation (PSO), and cuckoo search algorithm (CSA) have been utilised in simultaneous optimisation of the parameters of the desired outputs and its great potential in optimising machining processes is recognisable

Extrapancreatic actions of incretin-based therapies on bone in diabetes mellitus

Diabetes mellitus is correlated with modifications in bone microarchitectural and mechanical strength, leading to increased bone fragility. The incretin hormones, with a classical effect to increase insulin secretion following food ingestion, are now postulated to have important direct effects on bone. As such, glucose-dependent insulinotropic polypeptide (GIP) has dual actions on bone cells; enhancing bone�forming activity of osteoblasts and suppressing bone resorption by osteoclasts. The sister incretin of GIP, glucagon-like peptide-1 (GLP-1), is also suspected to directly influence bone health in a beneficial manner, although mechanism are less clear at present. The physiological actions of incretins are attenuated by dipeptidyl peptidase (DPP-4) activity and it is speculated that introduction of DPP-4 inhibitor may also positively affect quality of the skeleton. As such, this thesis evaluates the potential beneficial effects of a DPP-4 resistant GIP analogue, namely [D-Ala2 ]GIP, on osteoblastic-derived, SaOS-2 cells, and also preliminary in vivo studies on the impact of genetic deficiencies of GIPRs and GLP-1Rs on bone mineral density and content. Further studies characterised the beneficial effects of incretin-based therapies on metabolic control, bone microstructure and bone mechanical integrity in animal models of pharmacologically-, genetically- and environmentally-induced diabetes. GIP and related stable analogue increased bone-forming biomarkers in SaOS-2 cells and importantly, [D-Ala2 ]GIP was shown to be more potent than native GIP. Knockout mouse studies revealed that both GIPR and GLP-1R signaling are important for optimum bone mass. All diabetic mouse models displayed reduced bone mass, altered bone micromorphology and impairment of bone mechanical strength, similar to the human situation, confirming their appropriateness. The incretin-based therapeutics, [D-Ala2 ]GIP and Liraglutide, in streptozotocin-diabetic significantly increased bone matrix properties, indicating recovery of bone strength at the tissue level. The beneficial effects of administration of [D-Ala2 ]GIP�oxyntomodulin on bone health in db/db mice were more prominent as the Oxm analogue did not only improve bone strength at tissue level, but also at whole-bone level. These modifications were independent of metabolic status. Twice-daily Exendin-4 therapy improved glycaemic control and increased work required to resist bone fracture in high-fat fed mice. It was also established that Sitagliptin had neutral effects on bone microstructure and mechanical strength in high-fat mice. In summary, these data demonstrate the negative impact of diabetes mellitus on normal skeleton development and bone quality. Moreover, this thesis highlights the growing potential of incretin-based therapies for ameliorating bone defects and improving the increased fragility fracture risk associated with diabete

Effect of seeding time on the formation of gold nanoplates

Metallic nanostructures, such as gold, is very sensitive to the dielectric environment of the materials due to strong dependency of plasmon on shapes and sizes. Thus, its unique properties are very good and can be used as sensing material in plasmonic sensor. This paper reports a study on the surface density on the formation of gold nanoplates with variation of seeding time. The gold nanoplates have been grown on a quartz substrate using seed mediated growth method. In this study, the seeding time was varied from one to three hours and labelled as MP1, MP2 and MP3. The XRD analysis shows two peaks of the diffraction angle occurs at the plane (111) in position ~ 38.2º and plane (200) at ~ 44.20º. Through variation of the seeding time, the optimum surface density is 61.8 % with a total of 43.7 % of the nanoplates shape from sample MP2. The optical absorption spectrum of the sample shows two resonance peaks, ~ 550 nm and 660 nm, which are corresponding to the transverse surface plasmon resonance (t-SPR) and the longitudinal surface plasmon resonance (l-SPR) respectively. Thus, in this study, it is found that the seeding time affected the growth of the gold nanostructures with optimum seeding time of two hours. Longer seeding time caused the growth of stacking nanogold and it is not suitable to be used in sensing application because of its broad and wider optical spectrum

Sustainable assessment in manufacturing company

Knowledge of sustainability concepts and the application of sustainability assessment in Malaysian industries are rather limited. A practical approach towards understanding sustainability concepts and its advantages is by conducting sustainability assessment. Sustainability assessment should consider the three pillars of sustainability via the environment, economic and social. The objectives of the study were to perform sustainability assessment on a popular power tool by determining its sustainability score and to propose improvement to increase the sustainability score. Sustainability assessment was performed using the Math Lab fuzzy logic toolbox. The sub element for environment were solid waste and global warming, whereas for economic, the sub element were cost, quality, technology and process. Finally for social sub element it was the social performance. Outcomes of this study demonstrate the integration between fuzzy logic and sustainability assessment yield the sustainability score for a popular power tool. Methods for improving the sustainability score of the chosen product were also proposed. Finally, some recommendations for future studies were proposed

Effect of Reynolds number on the wake of a Next-Generation High-Speed Train using CFD analysis

Improvement to the next-generation high-speed train (NG-HST) is ongoing particularly in achieving a higher operating speed. Consequently, the aerodynamic effect of the train will be more critical as it affects the development of a wake flow characterized by complex and unsteady structures. Although the effect of Reynolds number (Re) on aerodynamic forces is negligible, its effect on the wake of NG-HSTs is unknown. In this study, the Re ranging from 7.42 × 105 to 1.62 × 106 was used to examine the characteristics of vortex structures, streamline distributions, velocity characteristics, and pressure characteristics in the wake region of an NG-HST. The Delayed Detached Eddy Simulation (DDES) is used as the turbulence model. In addition, the simulation results were compared with the previous wind tunnel experimental data. The results indicated no significant changes in the overall wake flow structure when Re was increased. According to power spectral density analysis, increasing the Reynolds number increased the turbulence intensity of the wake which gradually dissipated as the distance from the train increased. The findings of the study could be used to better understand the flow characteristics at the wake of NG-HSTs for future development