Oil palm fronds (OPF) are one of the main by-products of the oil palm industry in Malaysia. It contains about 38.5 % crude fibre with ME values of about 5.65 MJ/kg dry matter. OPF has great potential to be utilized as a roughage source or as a component in a complete feed for ruminant animals. This paper briefly reviews the availability of OPF in Malaysia and its importance in the local beef an...

Optimal power flow (OPF) is a major task in power system economics and operation. In OPF power real power outputs from the generators of a power system are so adjusted that the total production cost is minimum. Security constraint OPF (SC-OPF) is minimizing the cost keeping line flows within their respective limits for security reasons. Real power output from generators, generator bus voltage m...

Optimal power flow (OPF) is a major task in power system economics and operation. In OPF power real power outputs from the generators of a power system are so adjusted that the total production cost is minimum. Security constraint OPF (SC-OPF) is minimizing the cost keeping line flows within their respective limits for security reasons. Real power output from generators, generator bus voltage m...

In this work we propose a novel automatic cast iron segmentation approach based on the Optimum-Path Forest classifier (OPF). Microscopic images from nodular, gray and malleable cast irons are segmented using OPF, and Support Vector Machines (SVM) with Radial Basis Function and SVM without kernel mapping. Results show accurate and fast segmented images, in which OPF outperformed SVMs. Our work i...

This paper describes the Obje Perception Framework (OPF ), a distributed software architecture for context sensing and inference in ubiquitous computing environments. OPF provides flexibility, scalability, and robustness even as the sensor configuration changes. For flexibility, OPF supports many context inference tasks, ways of achieving those tasks, and heterogeneity in sensor types. With res...

We have recently shown that the optimal power flow (OPF) problem with a quadratic cost function can be solved in polynomial time for a large class of power networks, including IEEE benchmark systems, due to their physical properties. In this work, our previous zero-duality-gap result is extended to OPF with arbitrary convex cost functions, and then it is proved that adding phase shifters to the...

Optimal power flow (OPF) is a key problem in system operations. OPF problems that use the nonlinear AC equations to accurately model network physics have inherent challenges associated with non-convexity. To address these challenges, recent research has applied various convex relaxation approaches problems. The QC promising approach convexifies trigonometric and product terms by enclosing envel...

With distributed generation highly integrated into the grid, the transmission-distribution-coupled AC OPF (TDOPF) becomes increasingly important. This paper proposes a response-function-based coordination method to solve the TDOPF. Different from typical decomposition methods, this method employs approximate response functions of the power injections with respect to the bus voltage magnitude in...

In this work, Particle Swarm Optimizationand Genetic algorithm for the solution of the optimal power flow (OPF) is studied. Traditionally, classical optimization methods were used to effectively solve OPF. But more recently due to incorporation of Flexible A.C. Transmission System (FACTS) devices and deregulation of a power sector, the traditional concepts and practices of power systems are sup...

This paper presents the k-Optimum Path Forest (k-OPF) supervised classifier, which is a natural extension of the OPF classifier. k-OPF is compared to the k-Nearest Neighbors (k-NN), Support Vector Machine (SVM) and Decision Tree (DT) classifiers, and we see that k-OPF and k-NN have many similarities. This work shows that the k-OPF is equivalent to the k-NN classifier when all training samples a...