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      저자 : Satish Kulkarni (검색결과 3 건)
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      • KCI등재

        Evaluation and Identification of Promising Bivoltine Double Hybrids of the Silkworm Bombyx mori L. for Tropics Through Large Scale In-House Testing

        Dayananda,Satish Kulkarni,Pala Rama Mohana Rao,Obalaiah Gopinath,dara Murthy Nirmal Kumar 한국잠사학회 2011 International Journal of Industrial Entomology Vol.23 No.2

        An attempt was made to assess the potentiality of bivoltine double hybrids under simulated conditions of farmers to identify the suitable bivoltine double hybrid combination. Four bivoltine double hybrids developed at Central Sericultural Research and Training Institute (CSRTI), Mysore along with popular single hybrid, CSR2 x CSR4 as control was assessed for economic traits. The rearing results showed significant improvement of 20-24% in fecundity of the double hybrids studied over single hybrid. Among the double hybrids, [D7 ×S5]×[D13×S1] recorded significantly higher survival (89.58 %), cocoon yield (76.328 kg/50,000 eggs), cocoon price (Rs. 180.87/kg) and lower cocoon leaf ratio of 1: 21.80. The performance of the reeling traits were also found significantly superior in [D7×S5]×[D13×S1] with higher filament length (1100 m), reelability (88%), raw silk (18.55%) and neatness (92 points) compared to CSR2 × CSR4 and other double hybrids evaluated. Besides, the cocoons of [D7×S5]×[D13×S1] exhibit uniformity in size with a standard deviation of < 8. Overall data indicated the superiority of [D7×S5] × [D13×S1] compared to the other hybrids evaluated and it has profound influence in expressing the full potentiality in the field.

      • KCI등재후보

        Evaluation and Identification of Promising Bivoltine Double Hybrids of the Silkworm Bombyx mori L. for Tropics Through Large Scale In-House Testing

        Dayananda, Dayananda,Kulkarni, Satish,Rao, Pala Rama Mohana,Gopinath, Obalaiah,Kumar, Sundara Murthy Nirmal Korean Society of Sericultural Science 2011 International Journal of Industrial Entomology Vol.23 No.2

        An attempt was made to assess the potentiality of bivoltine double hybrids under simulated conditions of farmers to identify the suitable bivoltine double hybrid combination. Four bivoltine double hybrids developed at Central Sericultural Research and Training Institute (CSRTI), Mysore along with popular single hybrid, $CSR2{\times}CSR4$ as control was assessed for economic traits. The rearing results showed significant improvement of 20-24% in fecundity of the double hybrids studied over single hybrid. Among the double hybrids, $[D7{\times}S5]{\times}[D13{\times}S1]$ recorded significantly higher survival (89.58 %), cocoon yield (76.328 kg/ 50,000 eggs), cocoon price (Rs. 180.87/kg) and lower cocoon leaf ratio of 1: 21.80. The performance of the reeling traits were also found significantly superior in $[D7{\times}S5]{\times}[D13{\times}S1]$ with higher filament length (1100 m), reelability (88%), raw silk (18.55%) and neatness (92 points) compared to $CSR2{\times}CSR4$ and other double hybrids evaluated. Besides, the cocoons of $[D7{\times}S5]{\times}[D13{\times}S1]$ exhibit uniformity in size with a standard deviation of < 8. Overall data indicated the superiority of $[D7{\times}S5]{\times}[D13{\times}S1]$ compared to the other hybrids evaluated and it has profound influence in expressing the full potentiality in the field.

      • KCI등재

        Cross domain analyzer to acquire review proficiency in big data

        Deepali Virmani,Preeti Arora,Pradnya Satish Kulkarni 한국통신학회 2017 ICT Express Vol.3 No.3

        Sentiment analysis is the pre-eminent technology for extracting relevant information in the data domain. In this paper, a cross-domain sentimental classification approach, the cross-domain analyzer (CDA), is proposed, which will extract positive words and replace their synonyms to escalate polarity. Additionally, the approach blends two different domains and detects all self-sufficient words. This is executed on Amazon datasets, in which two different domains are trained to analyze the sentiments of the reviews in the other domain. The proposed approach contributes promising results in the cross-domain analysis, and an accuracy of 92% is achieved. In BOMEST, the CDA improves precision and recall by 16% and 7%, respectively.

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