Efficient Data-Driven Crop Pest Identification Based on Edge Distance-Entropy for Sustainable Agriculture

Integrated Pest Management Farmer Field School for Sustainable Agriculture

The study was conducted among the two farmer groups in Bhaktapur and Kavre districts of Nepal. The main objective of the study is to evaluate the effectiveness of IPM FFS on creating awareness and disseminating the knowledge on sustainable pest management to the farmers and to assess the relationships between enhanced IPM knowledge and adoption of IPM strategies by the farmers. The study has be...

Weather-based Pest Forecasting for Efficient Crop Protection

Entropy-based Consensus for Distributed Data Clustering

The increasingly larger scale of available data and the more restrictive concerns on their privacy are some of the challenging aspects of data mining today. In this paper, Entropy-based Consensus on Cluster Centers (EC3) is introduced for clustering in distributed systems with a consideration for confidentiality of data; i.e. it is the negotiations among local cluster centers that are used in t...

integrated pest management farmer field school for sustainable agriculture

the study was conducted among the two farmer groups in bhaktapur and kavre districts of nepal. the main objective of the study is to evaluate the effectiveness of ipm ffs on creating awareness and disseminating the knowledge on sustainable pest management to the farmers and to assess the relationships between enhanced ipm knowledge and adoption of ipm strategies by the farmers. the study has be...

Testing Exponentiality Based on Renyi Entropy of Transformed Data

In this paper, we introduce new tests for exponentiality based on estimators of Renyi entropy of a continuous random variable. We first consider two transformations of the observations which turn the test of exponentiality into one of uniformity and use a corresponding test based on Renyi entropy. Critical values of the test statistics are computed by Monte Carlo simulations. Then, we compare p...