Economic dispatch (ED) is one of the many important components in a power system operation. It is designed to calculate the exact amount of power generation needed to ensure a minimum cost of generation. A power system with multiple generators should be running under an economic condition. The operating cost has to be minimised for any feasible load demand. The increase of power demand is getting higher throughout the year. Economic dispatch is used to schedule and control all output of the fossil-fuel or coal-generators to satisfy the system load demand at a minimum cost. This paper presents the Multiverse Optimisation (MVO) for solving the economic dispatch in a power system. The proposed Multiverse optimisation engine developed in this study is implemented on the IEEE 30-Bus Reliability Test System (RTS). It has five generators, all of which are denoted as the control variables for the optimisation process. To reveal the superiority of MVO, a similar process was conducted using Evolutionary Programming (EP). Results from both techniques were compared, and it was revealed that MVO had outperformed EP in terms of reduced cost of generation for the system.

Rehabilitation training is a method of post-treatment for physically injured part of body especially the stroke patients. The training task such as massage and repetition exercises are needed to help them to have a normal life as before by a physiotherapist. The physiotherapist or physical therapy is a person who has experienced to treat disease or injury by physical methods. Therefore, a main objective of this paper is to develop a nursing-care robot system that can assist the stroke patient in doing daily activities. A one-degree of freedom nursing robot was designed based on the right-hand bicep using CATIA software. This robot was associated with the electromyography (EMG) sensors in order to collect the data from the muscle contractions. Meanwhile the EMG sensor is a muscle sensor that detect an electrical potential between the two-contraction flexion or extension muscle using the polymer Ag/AgCl coated electrodes. Then, the data from the muscle was sent to the Arduino microcontroller to control the servo motor. The different angle of servo motor can give the direction of movement of the nursing-care robot. The nursing robot was activated by electrical potential from the contraction of the muscle. The value of servo angle from 0 to 100 degrees angle made the robot will move up and down. The movement of robot in up and down direction is likely same as the therapist assistance doing to their patient. The size of robot is about 600 mm × 100 mm length and width and then was fabricated using 3D printer with one degree of freedom (DOF). The limitation of this project is focusing only the hand right hand bicep brachii muscle physiotherapy exercise.