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Shafie N.A.H.,Universiti Sains Malaysia | Lau N.-S.,Universiti Sains Malaysia | Ramachandran H.,Quest International University Perak | Amirul A.-A.A.,Universiti Sains Malaysia
Genome Announcements | Year: 2017

Cupriavidus sp. USMAA1020, USMAA2-4, and USMAHM13 are capable of producing polyhydroxyalkanoate (PHA). This biopolymer is an alternative solution to synthetic plastics, whereby polyhydroxyalkanoate synthase is the key enzyme involved in PHA biosynthesis. Here, we report the complete genomes of three Cupriavidus sp. strains: USMAA1020, USMAA2-4, and USMAHM13. © 2017 Shafie et al.

Ponnusamy V.,Quest International University Perak | Low T.J.,Petronas University of Technology | Amin A.H.M.,Multimedia University
International Journal of Mobile Communications | Year: 2014

Sensor nodes deployed in a large topology require autonomous capabilities and scalability since frequent replacement of the nodes is almost impossible. These sensors should be self-healing and energy efficient. Biologically inspired algorithms offer a new paradigm in providing solutions to problems found within the wireless sensor networks (WSNs). In this paper, bee nectar harvesting (analogous to data harvesting from sensor nodes) and flower pollination (analogous to energy harvesting in sensor nodes) are proposed with detailed mapping. Simulation was conducted to evaluate the proposed mechanism and a prototype was developed to show the feasibility of mobile agent de-ployment and energy provisioning. The research outcome is a biologically inspired mobile agent-based system (BIMAS) that provides a novel self-healing (bee pollination analogy for energy efficiency) protocol, leading to a longer WSNs lifetime. BIMAS is aimed for delay tolerant applications and where sensor node replacement is almost impossible. Copyright © 2014 Inderscience Enterprises Ltd.

Applasamy V.,Quest International University Perak
ISBEIA 2011 - 2011 IEEE Symposium on Business, Engineering and Industrial Applications | Year: 2011

This article reviews the cost to generate per kilowatt hour of electricity applying life cycle costing (LCC) analysis for a typical household of four using stand-alone photovoltaic technology. RETScreen was used to determine the cost of developing the stand-alone photovoltaic system and finally deriving to the cost per kilowatt hour for the various photovoltaic technologies taking into consideration all major components involved in the construction. Life cycle costing is employed over a period of 25 years subject to annual interest rates and inflation to accurately ascertain the cost per kilowatt hour for each photovoltaic module. A price comparison was undertaken between the national utility company and the stand-alone system. Ultimately, results show that albeit having several advantages from the environmental perspective compared to current power generating sources, the major drawback is the high cost of between RM 1.17 - RM 1.21 per kilowatt hour which is more than five times the current cost of electricity for residential household. © 2011 IEEE.

Applasamy V.,Quest International University Perak
ISBEIA 2011 - 2011 IEEE Symposium on Business, Engineering and Industrial Applications | Year: 2011

This article reviews several methods of calculating solar radiation from satellite derived earth atmospheric reflectivity from the visible channel. Most models calculate global and direct beam solar radiation on daily and hourly basis. Statistical models do not require precise information on atmospheric parameters whereas physical models apply these atmospheric parameters. These later evolved where authors developed hybrid models combining both. Despite a considerable number of publications which use satellite data to derive solar radiation, many models were modified and improved from existing models which were considered popular models. These popular models are briefly reviewed in this article. Most models were developed for the North American or European climate except for the physical model of Janjai et al 2005, which considered the tropical climate and the Brazillian Solar Radiation model. The models estimate hourly global solar irradiation with a RMSE between 6.8% and 25.6% while the daily global solar irradiation RMSE is between 12.9% and 18.13%. © 2011 IEEE.

Akram N.A.,University of Nottingham Malaysia Campus | Isa D.,University of Nottingham Malaysia Campus | Rajkumar R.,University of Nottingham Malaysia Campus | Lee L.H.,Quest International University Perak
Ultrasonics | Year: 2014

This work proposes a long range ultrasonic transducers technique in conjunction with an active incremental Support Vector Machine (SVM) classification approach that is used for real-time pipeline defects prediction and condition monitoring. Oil and gas pipeline defects are detected using various techniques. One of the most prevalent techniques is the use of "smart pigs" to travel along the pipeline and detect defects using various types of sensors such as magnetic sensors and eddy-current sensors. A critical short coming of "smart pigs" is the inability to monitor continuously and predict the onset of defects. The emergence of permanently installed long range ultrasonics transducers systems enable continuous monitoring to be achieved. The needs for and the challenges of the proposed technique are presented. The experimental results show that the proposed technique achieves comparable classification accuracy as when batch training is used, while the computational time is decreased, using 56 feature data points acquired from a lab-scale pipeline defect generating experimental rig. © 2014 Elsevier B.V. All rights reserved.

Yagasena,Quest International University Perak
ARPN Journal of Engineering and Applied Sciences | Year: 2016

Two years of rain rate and attenuation measurement in Malaysia is presented. The analysis shows that the attenuation follows the power law and linear law for rain rates below and above a certain cut-off rain rate respectively. A simple Two-Part model is proposed for consideration in the tropical regions. © 2006-2016 Asian Research Publishing Network (ARPN).

Chia Y.Y.,University of Nottingham Malaysia Campus | Lee L.H.,Quest International University Perak | Shafiabady N.,University of Nottingham Malaysia Campus | Isa D.,University of Nottingham Malaysia Campus
Applied Energy | Year: 2015

This paper presents the use of a Support Vector Machine load predictive energy management system to control the energy flow between a solar energy source, a supercapacitor-battery hybrid energy storage combination and the load. The supercapacitor-battery hybrid energy storage system is deployed in a solar energy system to improve the reliability of delivered power. The combination of batteries and supercapacitors makes use of complementary characteristic that allow the overlapping of a battery's high energy density with a supercapacitors' high power density. This hybrid system produces a straightforward benefit over either individual system, by taking advantage of each characteristic. When the supercapacitor caters for the instantaneous peak power which prolongs the battery lifespan, it also minimizes the system cost and ensures a greener system by reducing the number of batteries. The resulting performance is highly dependent on the energy controls implemented in the system to exploit the strengths of the energy storage devices and minimize its weaknesses. It is crucial to use energy from the supercapacitor and therefore minimize jeopardizing the power system reliability especially when there is a sudden peak power demand. This study has been divided into two stages. The first stage is to obtain the optimum SVM load prediction model, and the second stage carries out the performance comparison of the proposed SVM-load predictive energy management system with conventional sequential programming control (if-else condition). An optimized load prediction classification model is investigated and implemented. This C-Support Vector Classification yields classification accuracy of 100% using 17 support vectors in 0.004866. s of training time. The Polynomial kernel is the optimum kernel in our experiments where the C and g values are 2 and 0.25 respectively. However, for the load profile regression model which was implemented in the K-step ahead of load prediction, the radial basis function (RBF) kernel was chosen due to the highest squared correlation coefficient and the lowest mean squared error. Results obtained shows that the proposed SVM load predictive energy management system accurately identifies and predicts the load demand. This has been justified by the supercapacitor charging and leading the peak current demand by 200. ms for different load profiles with different optimized regression models. This methodology optimizes the cost of the system by reducing the amount of power electronics within the hybrid energy storage system, and also prolongs the batteries' lifespan as previously mentioned. © 2014 Elsevier Ltd.

Cherian S.,Quest International University Perak | Figueroa C.R.,University of Concepción | Nair H.,Quest International University Perak
Journal of Experimental Botany | Year: 2014

Fruit ripening is a complex and highly coordinated developmental process involving the expression of many ripeningrelated genes under the control of a network of signalling pathways. The hormonal control of climacteric fruit ripening, especially ethylene perception and signalling transduction in tomato has been well characterized. Additionally, great strides have been made in understanding some of the major regulatory switches (transcription factors such as RIPENING-INHIBITOR and other transcriptional regulators such as COLOURLESS NON-RIPENING, TOMATO AGAMOUS-LIKE1 and ETHYLENE RESPONSE FACTORs), that are involved in tomato fruit ripening. In contrast, the regulatory network related to non-climacteric fruit ripening remains poorly understood. However, some of the most recent breakthrough research data have provided several lines of evidences for abscisic acid- and sucrose-mediated ripening of strawberry, a non-climacteric fruit model. In this review, we discuss the most recent research findings concerning the hormonal regulation of fleshy fruit ripening and their cross-talk and the future challenges taking tomato as a climacteric fruit model and strawberry as a non-climacteric fruit model. We also highlight the possible contribution of epigenetic changes including the role of plant microRNAs, which is opening new avenues and great possibilities in the fields of fruit-ripening research and postharvest biology. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Ooi B.L.,Quest International University Perak | Gilbert J.M.,University of Hull
Sensors and Actuators, A: Physical | Year: 2014

This paper describes the design of a wideband electromagnetic energy harvester that utilizes a novel dual-resonator method to improve the operational frequency range of the vibration-based generator. The device consists of two separate resonator systems (coil and magnet), which each comply with their respective resonance frequencies. This is because both resonators are designed in such a way that both magnet and coil components will oscillate at an additive phase angle, and hence create greater relative motion between the two dominating resonance frequencies, which realizes the wideband generator. Each resonator system consists of a distinctive cantilever beam, one attached with four magnets and steel keepers, the other attached with a copper coil and stainless steel holder as the free end mass. Both cantilevers are clamped and fitted to a common base that is subjected to a vibration source. Basic analytical models are derived and a numerical model is implemented in MATLAB-Simulink. Electromagnetic, structural modal and static mechanical analysis for the design of the prototype are completed using ANSYS finite element tools. For a 0.8 m s-2 acceleration, the open-loop voltage obtained from the experiment shows a good correlation with those from the simulation. Peak induced voltage is measured to be 259.5Vrms as compared to 240.9Vrms from the simulator at 21.3 Hz, which implies an error range of 7.7%. The results also indicate that there is a maximum of 58.22% improvement in the induced voltage within the intermediate region which occurs at the intersection point between the output response plots of two single resonator generators. © 2014 Elsevier B.V.

Chin T.A.,University of Technology Malaysia | Tat H.H.,Quest International University Perak | Sulaiman Z.,University of Technology Malaysia
Procedia CIRP | Year: 2015

The increased attention given to the topic of green supply chain management (GSCM) warrants the writing of this paper. The concept of GSCM is to integrate environmental thinking into supply chain management (SCM). As such, GSCM is important in influencing the total environment impact of any organizations involved in supply chain activities. More importantly, GSCM can contribute to sustainability performance enhancement. In this paper, we focus on the environmental collaboration, which has been seen as a key relational capability to facilitate the GSCM strategic formulation and execution. The purpose of this paper is two-fold: (i) review the extant literature on the relationship between GSCM, environmental collaboration and sustainability performance and (ii) propose a plausible conceptual model to elucidate the relationship between these three variables in the context of Malaysian manufacturing companies. Accordingly, such thought depends upon more detailed empirical research by using advanced structural equation modeling approaches. The research findings will be particularly important for manufacturing companies in developing environmental collaboration with their suppliers in order to achieve sustainability performance. © 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license.

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