Adapting technology: effect of high-involvement HRM and organisational trust

This study is designed to empirically test a model of high-involvement human resource management (HIHRM), organisational trust, and technology adaptation grounded on social exchange theory in the context of the private banking sector. The proposed model intends to add to the understanding of the effect of HIHRM on technology adaptation via the mediating influence of organisational trust. Frontline employees were surveyed using a self-administered questionnaire. Results from partial least square-structural equation modelling suggest that there is a significant influence of HIHRM on technology adaptation. Organisational trust further mediates the relationship. Thus, this paper finds an answer to the ‘black box’ of human resource management (HRM) practices, explaining how HIHRM influences employees’ attitudes towards technology adaptation. The study can help management have a better understanding of the importance of employee involvement-oriented HRM in introducing and implementing a new technology through the integration of trust processes in the organisation.     

Robust hierarchical multiple hypothesis tracker for multiple-object tracking

Multiple object tracking is a fundamental subsystem of many higher level applications such as traffic monitoring, people counting, robotic vision and many more. This paper explains in details the methodology of building a robust hierarchical multiple hypothesis tracker for tracking multiple objects in the videos. The main novelties of our approach are anchor-based track initialization, prediction assistance for unconfirmed track and two virtual measurements for confirmed track. The system is built mainly to deal with the problems of merge, split, fragments and occlusion. The system is divided into two levels where the first level obtains the measurement input from foreground segmentation and clustered optical flow. Only K-best hypothesis and one-to-one association are considered. Two more virtual measurements are constructed to help track retention rate for the second level, which are based on predicted state and division of occluded foreground segments. Track based K-best hypothesis with multiple associations are considered for more comprehensive observation assignment. Histogram intersection testing is performed to limit the tracker bounding box expansion. Simulation results show that all our algorithms perform well in the surroundings mentioned above. Two performance metrics are used; multiple-object tracking accuracy (MOTA) and multiple-object tracking precision (MOTP). Our tracker have performed the best compared to the benchmark trackers in both performance evaluation metrics. The main weakness of our algorithms is the heavy processing requirement.     

Oil palm bunch ripeness classification using fluorescence technique

Oil palm is Malaysia’s major agriculture product and it covers approximately 5 million hectares of Malaysia’s land. Limited land resources have been an important factor that motivated the need to increase oil extraction rate (OER). OER of oil palm fresh fruit bunches (FFB) depends highly on their maturity stage. The ripe oil palm FFB will produce high OER while the under ripe and over ripe oil palm FFB will produce less oil. Thus, this paper presents a method of classification between oil palm FFB into ripe, under-ripe and over-ripe categories. This research was done at an oil palm plantation in peninsular Malaysia. A total of two-hundred and ten oil palm FFB that consist of seventy bunches for each category of under-ripe, ripe and over-ripe had been used. Each bunch was scanned ten times randomly with a hand-held multi-parameter fluorescence sensor called Multiplex®3. The parameter measured was the Blue-to-Red Fluorescence Ratio (BRR_FRF) obtained from blue-green (447 nm) and far-red (685 nm) emission signal by using ultraviolet (UV) light emitting diode as excitation light source. The novel contribution of this research is to prove that the oil palm FFB maturity can be determined using the Blue-to-Red Fluorescence ratio index. This is based to our finding of a significant difference among the three categories of ripeness based on the parameter. Classification and Regression Tree (C&RT) method was proposed in this paper. Hundred-fifty samples were used to develop the model by trained it using C&RT method and the remaining sixty samples for the test component. By using the C&RT method, the results show the best accuracy of overall testing classification is 90%. This research will be useful for future development of non-destructive, automatic and real time oil palm FFB grading system.     

On the Refinement Mechanism of Silicon in Al-Si-Cu-Zn Alloy with Addition of Bismuth

Obtained results of micro and nano studies reveal that bismuth refines the silicon in which the flake silicon changed to lamellar structure with reduction in twin spacing from 160 to 75 nm. Bismuth segregates towards the inter-dendritic regions and decreases the Al-Si contact angle resulting in suppression of the silicon growth causing refinement of the eutectic structure. Increased recalescence temperature and time confirmed that the refinement effect is attributed to the growth stage.     

Synthesis of Vanadium Pentoxide Nanoparticles as Catalysts for the Ozonation of Palm Oil

Vanadium pentoxide nanoparticles were synthesized using a solvo-thermal method and were characterized via X-ray powder diffraction (XRD) and field emission scanning electron microscopy (FE-SEM). The ozonation of palm oil was performed by using vanadium pentoxide nanoparticles as catalysts to synthesize ethyl malonate. This procedure presented several advantages, such as simple operation for a precise ozonation, excellent yield, short reaction times and reusability because of the recyclability of palm oil. Ethyl malonate was synthesized via the one-step ozonolysis of palm oil and was spectroscopically characterized using gas chromatography-mass spectroscopy (GC-MS).     

Growth mechanisms of MgO nanocrystals via a sol-gel synthesis using different complexing agents

In the preparation of nanostructured materials, it is important to optimize synthesis parameters in order to obtain the desired material. This work investigates the role of complexing agents, oxalic acid and tartaric acid, in the production of MgO nanocrystals. Results from simultaneous thermogravimetric analysis (STA) show that the two different synthesis routes yield precursors with different thermal profiles. It is found that the thermal profiles of the precursors can reveal the effects of crystal growth during thermal annealing. X-ray diffraction confirms that the final products are pure, single phase and of cubic shape. It is also found that complexing agents can affect the rate of crystal growth. The structures of the oxalic acid and tartaric acid as well as the complexation sites play very important roles in the formation of the nanocrystals. The complexing agents influence the rate of growth which affects the final crystallite size of the materials. Surprisingly, it is also found that oxalic acid and tartaric acid act as surfactants inhibiting crystal growth even at a high temperature of 950°C and a long annealing time of 36 h. The crystallite formation routes are proposed to be via linear and branched polymer networks due to the different structures of the complexing agents.     

Molecular Characterization of α- and β-Thalassaemia among Malay Patients

Both α- and β-thalassaemia syndromes are public health problems in the multi-ethnic population of Malaysia. To molecularly characterise the α- and β-thalassaemia deletions and mutations among Malays from Penang, Gap-PCR and multiplexed amplification refractory mutation systems were used to study 13 α-thalassaemia determinants and 20 β-thalassaemia mutations in 28 and 40 unrelated Malays, respectively. Four α-thalassaemia deletions and mutations were demonstrated. −−^SEA deletion and α^CSα accounted for more than 70% of the α-thalassaemia alleles. Out of the 20 β-thalassaemia alleles studied, nine different β-thalassaemia mutations were identified of which β^E accounted for more than 40%. We concluded that the highest prevalence of (α- and β-thalassaemia alleles in the Malays from Penang are −−^SEA deletion and β^E mutation, respectively.     

Optimization of biohydrogen production by Clostridium butyricum EB6 from palm oil mill effluent using response surface methodology

Clostridium butyricum EB6 successfully produced hydrogen gas from palm oil mill effluent (POME). In this study, central composite design and response surface methodology were applied to determine the optimum conditions for hydrogen production (P_c) and maximum hydrogen production rate (R_max) from POME. Experimental results showed that the pH, temperature and chemical oxygen demand (COD) of POME affected both the hydrogen production and production rate, both individually and interactively. The optimum conditions for hydrogen production (P_c) were pH 5.69, 36 °C, and 92 g COD/l; with an estimated P_c value of 306 ml H₂/g carbohydrate. The optimum conditions for maximum hydrogen production rate (R_max) were pH 6.52, 41 °C and 60 g COD/l; with an estimated R_max value of 914 ml H₂/h. An overlay study was performed to obtain an overall model optimization. The optimized conditions for the overall model were pH 6.05, 36 °C and 94 g COD/l. The hydrogen content in the biogas produced ranged from 60% to 75%.