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.     

Trend Curve Optimal Control Model for Optimizing Pavement Maintenance Strategies Consisting of Various Treatments

Abstract: Most literature on pavement maintenance optimization for the case of continuous time assumes only one type of maintenance treatment, such as overlay, to be applicable and demonstrates solution procedures with simple cases of limited scopes. However, as overlays may not always be appropriate, depending on traffic loading/pavement situations, the objective of this article is to propose an optimization approach based on the trend curve optimal control model, to obtain optimal strategies possibly consisting of overlay, resealing, and reconstruction. The applicability of the solution procedure is demonstrated with several cases representing a variety of traffic loading/pavement situations. The solutions indicate that an optimal maintenance strategy can consist of multiple types of treatments depending on the situation, illustrating the versatility of the proposed procedure.     

Machine learning based optimized live virtual machine migration over WAN links

Live virtual machine migration is one of the most promising features of data center virtualization technology. Numerous strategies have been proposed for live migration of virtual machines on local area networks. These strategies work perfectly in their respective domains with negligible downtime. However, these techniques are not suitable to handle live migration over wide area networks and results in significant downtime. In this paper we have proposed a Machine Learning based Downtime Optimization (MLDO) approach which is an adaptive live migration approach based on predictive mechanisms that reduces downtime during live migration over wide area networks for standard workloads. The main contribution of our work is to employ machine learning methods to reduce downtime. Machine learning methods are also used to introduce automated learning into the predictive model and adaptive threshold levels. We compare our proposed approach with existing strategies in terms of downtime observed during the migration process and have observed improvements in downtime of up to 15 %.     

Model-based design verification for embedded systems through SVOCL: an OCL extension for SystemVerilog

Model Based System Engineering (MBSE) is a renowned approach in the context of embedded systems development. It is frequently used to deal with the structural and behavioral aspects of system design. However, the verification of system design is generally performed in isolation. It is particularly true in the context of assertion based verification. Consequently, there is a huge gap between system design and its verification that seriously effects the productivity and time-to market objectives. Therefore, in this research, we target to reduce this gap by exploiting the features of MBSE and SystemVerilog assertions (SVA’s). This article introduces a novel MBSE approach to model the design verification aspects of embedded systems, along with the system design (structural and behavioral aspects). We propose SystemVerilog in Object Constraint Language (SVOCL), an OCL temporal extension for SystemVerilog, to represent the design verification requirements by means of SVA’s. As a part of research, SVOCL transformation engine has been developed to generate SVA’s code in order to automate the design verification of embedded systems. The application of SVOCL has been validated through four case studies.     

Developing a hybrid PSO–ANN model for estimating the ultimate bearing capacity of rock-socketed piles

Neural Computing and Applications - Rock-socketed piles are commonly used in foundations built in soft ground, and thus, their bearing capacity is a key issue of universal concern in research,...     

Maleated Natural Rubber as a Coupling Agent for Recycled High Density Polyethylene/Natural Rubber/Kenaf Powder Biocomposites

Kenaf powder (KP) was incorporated into recycled high density polyethylene (rHDPE)/natural rubber (NR) blend using an internal mixer at 165°C and rotor speed of 50 rpm. The tensile strength and elongation at break of the composites decreased, while the tensile modulus increased with increasing filler loading. The water absorption was found to increase as the filler content increased. The maleic anhydride grafted natural rubber was prepared and used to enhance the composites performance. The addition of MANR as a coupling agent improved the tensile properties of rHDPE/NR/KP biocomposites. The water absorption was also reduced with the addition of MANR.     

Exploring the internationalization of Malaysian contractors: the international entrepreneurship dimension

The internationalization of construction companies is a subject of enduring interest among construction management scholars. The internationalization pattern of Malaysian contractors was explored, this time mainly using the international entrepreneurship body of literature as the theoretical basis. In doing so, the focus of the internationalization process was on the entrepreneurs or top management. Data were collected with a postal questionnaire survey and follow‐up semi‐structured interviews. The findings underscore the importance of the entrepreneurs’ decision in the surveyed firms’ internationalization trajectory. Top management’s perception of how their companies might benefit from internationalization was the highest ranked foreign market entry consideration. Top managements’ initial and subsequent motivation also fashioned their companies’ degree of internationalization and tactics for securing contracts. The characteristics of the entrepreneurs which drove their companies to internationalize were also captured. The international entrepreneurship domain continues to expand into previously uncharted areas. As such there is potential to uncover even more interesting findings from future research endeavours on international contractors using the international entrepreneurship approach.     

Effect of Sodium Carbonate on the Cloud Point in Alkyl Ether/Brine Systems: Apparent Relation with Dynamic Interfacial Tension Minimum

The effect of Na₂CO₃ on the cloud point in Na₂CO₃/surfactant/brine was investigated using two series of nonionic surfactants, C₁₃EO _x and C₁₇EO _x . The cloud point, T _cp, was found to decrease linearly with increasing Na₂CO₃ concentration. This was attributed to Na⁺ and particularly to CO₃ ^2?salting-out effect. The slope a = dTcp/d[Na₂CO₃] became more and more negative as the degree of ethoxylation is increased, suggesting that the higher the number of ethylene oxide (EO) groups the stronger is the cloud point depression for a given increment in Na⁺and CO₃ ^2?ions in solution. This was also illustrated by the linear variation of ΔT _cp = T _cp,0 ? T _cp,[Na2CO3] with the surfactant degree of ethoxylation.