KCG College of Technology

About: KCG College of Technology is a based out in . It is known for research contribution in the topics: Adsorption & Diesel fuel. The organization has 427 authors who have published 381 publications receiving 2193 citations.

Design and development of maximum power point tracking in wind power optimization using fuzzy PLL controller

Abstract: This paper proposes an improved maximum power point tracking (MPPT) method for Wind system using a fuzzy with PLL algorithm. The main advantage of the method is the reduction of the steady state oscillation (to practically zero) once the maximum power point (MPP) is located. Furthermore, the proposed method has the ability to track the MPP for extreme environmental condition, e.g. large fluctuations of isolation and partial shading condition. The algorithm is simple and can be computed very rapidly. To evaluate the effectiveness of the proposed method, MATLAB simulations are carried out under very challenging conditions, namely step changes in irradiance, step changes in load and partial shading of wind array. The proposed method in simulation shows it is efficient than the conventional controllers in terms of achieving maximum wind power generation effectively with steady state output compared to other conventional controllers.

Colorogram: A Color Feature Descriptor for Human Blob Labeling

Abstract: Tracking is one of the most important research fields for computer vision. Human Identity tracking is significant in the field of surveillance where a foolproof system is required that not only finds an existence of some person behaving suspicious but also his identification. In this paper, a novel feature descriptor by the name Colorogram has been proposed for labeling human blobs in videos. Two constraints were introduced into the system by way of color information and spatial spread of pixels in a new coordinate system. This feature descriptor helped in identifying/labeling human blobs with a priori knowledge of the scene. Two color spaces (HSV, RGB) and two histogram distance measures (Intersection, Euclidean) were considered for computation. The proposed Colorograms were compared with the conventional Histograms and Spatiograms. Experiments were conducted and the results have been tabulated. It was inferred that the new feature descriptor had classified humans with an acceptable precision and recall rates.

Module for DYSPRAXIA

Abstract: In India 6 to 10 % of the population is affected by dyspraxia with 2% are severely affected by dyspraxia. It is defined as the Developmental Coordination Disorder (DCD) of the brain in childhood causing difficulty in activities requiring coordination and movements. Developmental coordination disorder may occur alone or with other developmental disorder such as DYSLEXIA, Attention /Hyperactivity Disorder (ADHT). It usually continues to adulthoods. The main objective of this module is to improve the child's disability. To support individual and families affected by DCD and to help perfection in health and educate to assist that dyspraxia/DCD. The further most important objective is to educate teachers and school-based therapists to increase the awareness and understanding of DYSPRAXIA. The major aim of the project is to improve the child’s gross motor movements. To increase the mental confidence of dyspraxia patients. To identify great scientist to the world with this disorder. Better living conditions and more hope in the life of people with DYSPRAXIA. And to create awareness about DYSPRAXIA in future and Mainly to save many people’s life.