Multi-facts devices installation for loss minimization and techno-economic impact assessment using EPSO approach

This thesis presents a new meta-heuristic approach technique for optimal location and sizing of multi-unit Flexible Alternating Currents System (FACTS) device installation using single- and multi-objective problems. It also considers techno-economic impact in the system. In this research, the first objective is to develop heuristic technique Single�Objective Particle Swarm Optimization (SOPSO) for optimal location and sizing of single-unit FACTS device installation with loss minimization, voltage monitoring and taking into account the cost of installation in the system. The verification was conducted through comparative studies with Single-Objective Evolutionary Programming (SOEP) and Single-Objective Artificial Immune System (SOAIS) techniques. The effect of weight coefficient, c1 and c2 and the effect of population size of loss minimization are also investigated. The second objective is to determine the location and sizing of multi-unit and multi-type FACTS device installation using SOPSO and SOEP. Consequently, the third objective of this research is to develop a new meta-heuristic technique termed as Evolutionary Particle Swarm Optimization (EPSO) for optimal placement and sizing of multi-unit FACTS device with single-objective problem. Comparative studies with respect to traditional PSO and classical EP techniques indicated that EPSO has its merit in terms of loss minimization. In addition, the cluster formation of FACTS device installation is also derived from the obtained results. The cluster formation of FACTS device installation was derived by looking at how many times (frequency) the load buses are selected for FACTS device installation identified by EPSO, PSO and EP techniques. The fourth objective in this research is to develop a new optimization technique termed as sigma-Multi-Objective EPSO (σ-MOEPSO) technique for optimal location and sizing of FACTS devices installation for multi-objective problem to minimize the transmission loss and cost of installation in power system. Finally, the fifth objective is to assess the techno-economic impact of FACTS device installation in power system. This assessment is performed by using a hybrid Evolutionary Particle Swarm Optimization - Net Present Value (EPSO-NPV) for assessing the impact of FACTS devices installation in duration up to 20 years. Comparative study has been done with Evolutionary Programming - Net Present Value (EP-NPV) technique. It was found that the proposed technique has been able to produce better performance as compared to other techniques and could be beneficial to power system planner in order to perform FACTS devices installation scheme for the minimization of loss and cost in their systems

Real-time video streaming with multi-camera for a telepresence wheelchair

© 2016 IEEE. This paper presents a new approach for telepresence wheelchairs equipped with multiple cameras. The aim of this system is to provide effective assistance for the elderly and people with disabilities. The work explores the integration of the Internet of Things, such as multimedia, wireless Internet communication, and automation control techniques into a powered wheelchair system. In particular, multiple videos are streamed in real-time from an array of cameras mounted on the wheelchair, allowing wide visualization surrounding the wheelchair. By using video communication and interaction, remote users can assist to navigate a wheelchair via the Internet through wireless connections in a distant location. The experimental results show that video streaming can achieve high-quality video with the streaming rate up to 30 frames per second (fps) in real-time. The average round-trip time is under 27 milliseconds (ms). The results confirmed the effectiveness of the proposed system for tele-monitoring and remote control to achieve safer navigation tasks for wheelchair users

Regression between headmaster leadership, task load and job satisfaction of special education integration program teacher

Managing school is a daunting task for a headmaster. This responsibility is exacerbated when it involves the Special Education Integration Program (SEIP). This situation requires appropriate and effective leadership in addressing some of the issues that are currently taking place at SEIP such as task load and job satisfaction. This study aimed to identify the influence of headmaster leadership on task load and teacher job satisfaction at SEIP. This quantitative study was conducted by distributing 400 sets of randomized questionnaires to SEIP teachers across Malaysia through google form. The data obtained were then analyzed using Structural Equation Modeling (SEM) and AMOS software. The results show that there is a significant positive effect on the leadership of the headmaster and the task load of the teacher. Likewise, the construct of task load and teacher job satisfaction has a significant positive effect. However, for the construct of headmaster leadership and teacher job satisfaction, there was no significant positive relationship. This finding is very important as a reference to the school administration re-evaluating their leadership so as not to burden SEIP teachers and to give them job satisfaction. In addition, the findings of this study can also serve as a guide for SEIP teachers to increase awareness of the importance of managing their tasks. This study also focused on education leadership in general and more specifically on special education leadership

One-shot assistance estimation from expert demonstrations for a shared control wheelchair system

An emerging research problem in the field of assistive robotics is the design of methodologies that allow robots to provide human-like assistance to the users. Especially within the rehabilitation domain, a grand challenge is to program a robot to mimic the operation of an occupational therapist, intervening with the user when necessary so as to improve the therapeutic power of the assistive robotic system. We propose a method to estimate assistance policies from expert demonstrations to present human-like intervention during navigation in a powered wheelchair setup. For this purpose, we constructed a setting, where a human offers assistance to the user over a haptic shared control system. The robot learns from human assistance demonstrations while the user is actively driving the wheelchair in an unconstrained environment. We train a Gaussian process regression model to learn assistance commands given past and current actions of the user and the state of the environment. The results indicate that the model can estimate human assistance after only a single demonstration, i.e. in one-shot, so that the robot can help the user by selecting the appropriate assistance in a human-like fashion

Impulsive differential equations by using the Euler method

The theory of impulsive differential equations is emerging as an important area of investigation since such equations appear to represent a natural framework for mathematical modeling of several real phenomena. There have been intensive studies on the qualitative behavior of solutions of the impulsive differential equations. However, many impulsive differential equations cannot be solved analytically or their solving is complicated. In this paper, we represent the algorithm which follows the theory of impulsive differential equations to solve the impulsive differential equations by using the Euler methods. It is clearly shown the impulsive operators k I that acts at the moments k t influence the error. Finally, the better convergence result of the numerical solution is given by solving the numerical examples