Early diagnosis of skin cancer is essential health requirement for the patient and a critical task for the dermatologist. The factual thinking is that the chance of patient's survival is high if diagnosed early. Analysis of the skin images and dermoscopy is a mandatory for medical professionals to take appropriate decision on treatment. A number of methods have been researched to use automated and computerized system for skin diseases image processing. Various dermoscopy image processing techniques have been reviewed to explore the possible solution to skin diseases and to select an appropriate method for early detection7 of skin diseases. This review work will be a pathway to scientist, research scholars and medical practitioners.

Due to increase, the electricity demands and the cost of energy generation to cover the living requirement of modern societies, micro-grid (MG) has been established and played an important role to solve the problems of intermittent. This study focused on implementing the analytical algorithm for calculating the difference between generated units and consumed units under the control of the State of Charge (SOC) value and applied the Particle Swarm Optimization (ANALYTIC-PSO) algorithm to optimize the value resulting from the difference between generated units and consumed units. The simulation was performed using the python environment and the PSO algorithm converges to final state approximately after the 10th iterations. The results showed that the proposed approach is efficient compared to Grey Wolf Optimization (GWO) algorithm.