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A. P. Ruhil
Researcher at National Dairy Research Institute
Publications - 26
Citations - 399
A. P. Ruhil is an academic researcher from National Dairy Research Institute. The author has contributed to research in topics: Sahiwal cattle & Destination-Sequenced Distance Vector routing. The author has an hindex of 8, co-authored 24 publications receiving 346 citations. Previous affiliations of A. P. Ruhil include Indian Council of Agricultural Research & Jawaharlal Nehru University.
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Proceedings ArticleDOI
Voronoi diagram and convex hull based geocasting and routing in wireless networks
TL;DR: A general algorithm is proposed, in which message is forwarded to exactly those neighbors, which may be best choices for a possible position of destination (using the appropriate criterion), in which memoryless and past traffic memorization variants of each scheme are proposed.
Journal ArticleDOI
Prediction of sensory quality of UHT milk : A comparison of kinetic and neural network approaches
TL;DR: In this article, chemical kinetics and artificial neural network approach was used to predict sensory quality of the product in terms of flavour score and total sensory score as dependent variables and the prediction performance was judged on the basis of percent root mean square error.
Journal ArticleDOI
Comparative efficiency of artificial neural networks and multiple linear regression analysis for prediction of first lactation 305-day milk yield in Sahiwal cattle
TL;DR: In this article, a comparison was made between the relative efficiency of multiple linear regression analysis and artificial neural network (ANN) for prediction of first lactation 305-d milk yield (FL305DMY) in Sahiwal cows.
Journal ArticleDOI
Effective and accurate discrimination of individual dairy cattle through acoustic sensing
Singh Yajuvendra,S. S. Lathwal,Nitendra Rajput,T.V. Raja,Ashok Kumar Gupta,Tushar Kumar Mohanty,A. P. Ruhil,Atish Kumar Chakravarty,P.C. Sharma,Vivek Sharma,Gulab Chandra +10 more
TL;DR: In this article, the authors investigated the existence of significant differences for various acoustic features of vocal signals uttered from different individuals of a herd of crossbred cows, including mean call duration, mean pitch, 1st formant, periodicity and degree of voice breaks of adult lactating Karan Fries crossbred cattle.
Journal ArticleDOI
Comparison of connectionist and multiple regression approaches for prediction of body weight of goats
TL;DR: A comparative study of connectionist network [also known as artificial neural network (ANN)] and multiple regression is made to predict the body weight from body measurements in Attappady Black goats to show that connectionistnetwork model is a better tool to predict body weight in goats than MRA.