RESEARCH

Research is "imaginative and precise work attempted to build the load of information, including learning of people, culture and society, and the utilization of this load of learning to devise new applications." It is utilized to set up or affirm actualities, reaffirm the consequences of past work, take care of new or existing issues, bolster hypotheses, or grow new speculations. An exploration task may likewise be a development on past work in the field. Research undertakings can be utilized to grow further learning on a point, or in the case of a school research venture, they can be utilized to advance an understudy's exploration ability to set them up for future occupations or reports. To test the legitimacy of instruments, methods, or analyses, research may recreate components of earlier ventures or the task all in all. The basic roles of fundamental research (instead of applied research) are documentation, disclosure, elucidation, or the innovative work (R&D) of techniques and frameworks for the headway of human information. Ways to deal with research rely upon epistemologies, which change significantly both inside and among humanities and sciences. There are a few types of research: logical, humanities, aesthetic, financial, social, business, promoting, professional research, life, mechanical, and so on. The logical investigation of research practices is known as meta-look into.

Image Enhancement

The emergence of computer-aided diagnostic technology has revolutionized the health sector and by use of medical imaging records, health experts are able to get detailed analysis which enable them in precise diagnosis of gliomas tumors. In this paper, we present an approach that uses domain-specific knowledge together with hybrid image enhancement techniques that provides resulting image(s) with more details and lesser noise levels. We did comparison of our KB proposed approach with existing techniques and the experimentation results showed improvement in quality and reduction of arbitrariness of images. The approach is proved to be feasible and effective, thus resulting in better medical diagnosis and evaluation of gliomas problems. Proposed research work recommends a new approach for medical imaging enhancements.

K-means Based Automatic Pests Detection and Classification for Pesticides Spraying

Agriculture is the backbone to the living being that plays a vital role to country’s economy. Agriculture production is inversely affected by pest infestation and plant diseases. Plants vitality is directly affected by the pests as poor or abnormal. Automatic pest detection and classification is an essential research phenomenon, as early detection and classification of pests as they appear on the plants may lead to minimizing the loss of production. This study puts forth a comprehensive model that would facilitate the detection and classification of the pests by using Artificial Neural Network (ANN). In this approach, the image has been segmented from the fields by using enhanced K-Mean segmentation technique that identifies the pests or any object from the image. Subsequently, features will be extracted by using Discrete Cosine Transform (DCT) and classified using ANN to classify pests. The proposed approach is verified for five pests that exhibited 94% effectiveness while classifying the pests.