Institution
Indian Agricultural Statistics Research Institute
Facility•New Delhi, India•
About: Indian Agricultural Statistics Research Institute is a facility organization based out in New Delhi, India. It is known for research contribution in the topics: Population & Small area estimation. The organization has 454 authors who have published 870 publications receiving 7987 citations.
Papers published on a yearly basis
Papers
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TL;DR: In the study undertaken among sixty e-learner farmers of Malappuram district of Kerala state to analyze the various constraints coming in the way of e-learning of agricultural technologies, the most important constraint observed was: technological constraints out of the four groups of constraints.
Abstract: In a country like India where most of the farming communities have low access to the right information sources, extension has so much scope to enter into new vistas like e-learning which can be utilized for virtual education, training and dissemination of information. e- Learning and its promotion carry a number of barriers too along with the favourable factors. In the study undertaken among sixty e-learner farmers of Malappuram district of Kerala state to analyze the various constraints coming in the way of e-learning of agricultural technologies, the most important constraint observed was: technological constraints out of the four groups of constraints. Lack of prompt reply to online queries and information, high cost of establishment, lack of time and relevant information in the website was found to be affecting the e- learner farmers.
2 citations
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TL;DR: In this paper, the authors extended the concept of resistance to general variance balanced block designs as well as universally optimal block designs with unequal block sizes, and constructed locally resistant balanced incomplete block designs of degree one.
2 citations
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01 Jan 2021
TL;DR: Simple random sampling (SRS) as discussed by the authors is the simplest method of selecting a sample of n units out of N units by drawing units one by one with or without replacement, and every unit in the population has an equal probability of selection.
Abstract: Simple random sampling (SRS) is the simplest method of selecting a sample of n units out of N units by drawing units one by one with or without replacement. Every unit in the population has an equal probability of selection. This sampling method is useful whenever the underlined population is homogeneous.
2 citations
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01 Feb 2012
TL;DR: The predicted structure of the bubaline IFNt constructed through homology modeling from ovine IFnt, could be used for further profiling the species specific difference in IFNT activity.
Abstract: Interferon-Tau (IFNt) contributes towards maternal recognition of pregnancy in ruminants (like, cattle, buffalo, goat, giraffe). IFNt has been extensively studied in most of the ruminants except for buffalo Bubalus bubalis). The present study has been undertaken to predict the secondary structure of Interferon-tau in buffalo. The available amino acid sequence of bubaline IFNt (sequence database of SwissProt) was subjected to protein-BLAST to find similar sequences with high scores and low e-values. The ovine IFNt sequence (PDB code: 1B5L) was selected for further computational analysis of the bubaline IFNt sequence to predict the secondary and tertiary structure. The secondary structure of the modeled bubaline IFNt was predicted using STRIDE. The 3D structure was generated using academic version of MODELER9v6. The probability density functions (pdf) were used to restrain Cα-Cα distances, main chain N-O distances as well as main-chain and side-chain dihedral angles. The energy minimization and van der waal contacts were taken care of using ACCELRYS DS Modeling 2.0. The residue profiles of the obtained three-dimensional models were checked by VERIFY3D. The energetic architecture and the correctness of the generated model revealed that the predicted secondary model was correct and acceptable. The predicted structure of the bubaline IFNt constructed through homology modeling from ovine IFNt, could be used for further profiling the species specific difference in IFNt activity.
2 citations
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TL;DR: In this paper, the optimality of block design with interference effect from neighboring unit under a general non-additive model is investigated, which allows for the presence of interactions among the treatments applied in the adjacent plots.
Abstract: Here, the optimality of block design with interference effect from neighboring unit under a general non additive model is investigated, which allows for the presence of interactions among the treatments applied in the adjacent plots. A non additive model with interference × direct effects of treatments is considered as these effects contribute significantly to the response. A class of complete block designs balanced for interference effects from left neighboring unit is shown to be universally optimal for the estimation of direct and interference effects of treatments and two such series of designs have been constructed. Furthermore, considering direct treatment × block non additivity with interference effects, the optimality is studied and the optimal designs are obtained.
2 citations
Authors
Showing all 462 results
Name | H-index | Papers | Citations |
---|---|---|---|
Sunil Kumar | 30 | 230 | 3194 |
Atmakuri Ramakrishna Rao | 21 | 109 | 1803 |
Charanjit Kaur | 20 | 80 | 4320 |
Anil Rai | 20 | 208 | 1595 |
Ranjit Kumar Paul | 17 | 93 | 875 |
Hukum Chandra | 17 | 75 | 825 |
Sudhir Srivastava | 17 | 69 | 1123 |
Krishan Lal | 16 | 68 | 1022 |
Ashish Das | 15 | 146 | 1218 |
Eldho Varghese | 15 | 127 | 842 |
Deepti Nigam | 14 | 29 | 812 |
Mir Asif Iquebal | 14 | 88 | 604 |
Rajender Parsad | 13 | 98 | 799 |
Deepak Singla | 13 | 32 | 422 |
Prem Narain | 13 | 80 | 503 |