Zobrazeno 1 - 10
of 11 820
pro vyhledávání: '"A. MANIVANNAN"'
Autor:
Bhimireddy SUKRUTHA, Sivakami RAJESWARI, N. PREMALATHA, Narayana Manikanda BOOPATHI, K. THIRUKUMARAN, A. MANIVANNAN
Publikováno v:
Journal of Cotton Research, Vol 6, Iss 1, Pp 1-16 (2023)
Abstract Background For the purpose of utilising hybrid vigour to produce possible hybrids with a suitable level of stability, the knowledge of gene activity and combining ability is a crucial prerequisite before choosing desirable parents. The prese
Externí odkaz:
https://doaj.org/article/28fe0dddbe094117bf737d7a1f5e14cb
Publikováno v:
Complexity, Vol 2022 (2022)
This paper aims to explore the dynamic characteristics of the post treatment human immunodeficiency virus (HIV) type-1 model by proposing the theoretical frameworks. Distinct from the previous works, this study explores the effect of effector cells,
Externí odkaz:
https://doaj.org/article/93261fc5d64644aa84acdad610bbc52c
Publikováno v:
Electronic Journal of Plant Breeding, Vol 9, Iss 4, Pp 1348-1354 (2018)
Five new diversified Gossypium barbadense germplasm accessions NGB-555, NGB-556, NGB-557, NGB-558 and NGB-559 with a check variety Suvin were studied for correlation coefficients, genetic component and path analysis at CICR, Regional Station, Coimbat
Externí odkaz:
https://doaj.org/article/ed02e19b1c054365914cdff938c6f8a6
Autor:
Suri, Siddharth, Counts, Scott, Wang, Leijie, Chen, Chacha, Wan, Mengting, Safavi, Tara, Neville, Jennifer, Shah, Chirag, White, Ryen W., Andersen, Reid, Buscher, Georg, Manivannan, Sathish, Rangan, Nagu, Yang, Longqi
Until recently, search engines were the predominant method for people to access online information. The recent emergence of large language models (LLMs) has given machines new capabilities such as the ability to generate new digital artifacts like te
Externí odkaz:
http://arxiv.org/abs/2404.04268
Uncertainty Quantification aims to determine when the prediction from a Machine Learning model is likely to be wrong. Computer Vision research has explored methods for determining epistemic uncertainty (also known as model uncertainty), which should
Externí odkaz:
http://arxiv.org/abs/2403.09228
Autor:
Pichler, Georg, Romanelli, Marco, Manivannan, Divya Prakash, Krishnamurthy, Prashanth, Khorrami, Farshad, Garg, Siddharth
We introduce a formal statistical definition for the problem of backdoor detection in machine learning systems and use it to analyze the feasibility of such problems, providing evidence for the utility and applicability of our definition. The main co
Externí odkaz:
http://arxiv.org/abs/2402.16926
Publikováno v:
Electronic Journal of Plant Breeding, Vol 9, Iss 2, Pp 673-681 (2018)
A set of 816 accessions of desi cotton (G.arboreum) were evaluated in augmented design 1 during Kharif 2015-16. Traits namely stem color, leaf size, leaf lobbing, leaf shape, leaf color, petal color, bract size, boll shape, boll size, leaf nectaries,
Externí odkaz:
https://doaj.org/article/9dba7723fc384aab935795ae2f697a20
Publikováno v:
Electronic Journal of Plant Breeding, Vol 8, Iss 3, Pp 842-848 (2017)
Forty two Indian clusterbean genotypes were subjected to biochemical characterization. Biochemical profiling revealed the presence of ample amount of variation for crude protein, crude fibre, crude fat, ash, carbohydrate and guar gum content. Corre
Externí odkaz:
https://doaj.org/article/a2696589348b482ca08a5647ed4cf026
Autor:
A. Manivannan
Publikováno v:
Electronic Journal of Plant Breeding, Vol 8, Iss 1, Pp 371-378 (2017)
The variability of seed storage-proteins of 21 pearl millet genotypes were analyzed by sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE). Electrophorogram for 21 Pearl millet genotypes (seven hybrids, six female parent, five male
Externí odkaz:
https://doaj.org/article/7da41ddc099f4cf1b90f27144ad79d5c
Autor:
Shah, Chirag, White, Ryen W., Andersen, Reid, Buscher, Georg, Counts, Scott, Das, Sarkar Snigdha Sarathi, Montazer, Ali, Manivannan, Sathish, Neville, Jennifer, Ni, Xiaochuan, Rangan, Nagu, Safavi, Tara, Suri, Siddharth, Wan, Mengting, Wang, Leijie, Yang, Longqi
Log data can reveal valuable information about how users interact with Web search services, what they want, and how satisfied they are. However, analyzing user intents in log data is not easy, especially for emerging forms of Web search such as AI-dr
Externí odkaz:
http://arxiv.org/abs/2309.13063