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Chaturvedi, O.H.,Bhatta, Raghavendra,Verma, D.L.,Singh, N.P. Asian Australasian Association of Animal Productio 2006 Animal Bioscience Vol.19 No.4
The present study was undertaken to evaluate the effect of flushing of ewes with concentrate pellets just before the mating season on their nutrient utilization and reproductive performance on farms. Forty-eight Malpura ewes, 1-5 years old were randomly divided into 2 groups of 24 each (G1and G2). Ewes in both the groups were grazed on natural rangeland from 07.00 to 18.00 hr followed by night shelter in animal shed. G1 ewes were maintained on sole grazing while G2 ewes, in addition to grazing, received concentrate pellets at the rate of 1.5% of their body weight. The mean biomass yield of the community rangeland was 0.46 ton DM/hectare. The intakes of DM (g/kg $W^{0.75}$), DCP (g/kg $W^{0.75}$) and ME (MJ/kg $W^{0.75}$) were higher (p<0.01) in G2 as compared to that of G1 being 86.5, 10.2 and 1.15 and 57.5, 4.7 and 0.75, respectively. The digestibility of DM, OM, CP, NDF and hemicellulose were also higher (p<0.01) in G2 as compared to that of G1 being 57.2, 76.7, 78.9, 51.9 and 81.6 and 50.8, 68.7, 68.4, 45.4 and 74.4, respectively. The conception rate was higher (79.2%) in flushed ewes as compared to that of non-flushed (66.7%). Five of the pregnant ewes died and another 5 aborted in G1 while in G2, 5 ewes aborted with no mortality. The lambing was higher (73.7%) in G2 than that in G1 (37.5%). The birth weight of lambs was higher (p<0.05) in G2 (3.47 kg) than that in G1 (2.95 kg). Further, the birth weight of male lambs was higher (3.28) than that of female lambs (3.14). It is concluded that the biomass yield of the community rangeland in semi-arid region of India is low and insufficient to meet the nutrient requirement of ewes prior to mating season. However, concentrate supplementation at the rate of 1.5% of body weight to ewes during this critical stage enhanced their plane of nutrition, reproductive performance, body condition and birth weights of lambs.
Oxidative Stress and Antioxidant Status during Transition Period in Dairy Cows
Sharma, N.,Singh, N.K.,Singh, O.P.,Pandey, V.,Verma, P.K. Asian Australasian Association of Animal Productio 2011 Animal Bioscience Vol.24 No.4
The study was conducted on 20 Holstein X Sahiwal cross bred dairy cows, with an average milk production of $2,752{\pm}113.79$ liters in $284{\pm}5.75$ days during a single lactation, that were divided in to two groups of 10 animals. We investigated the oxidative stress and antioxidant status during the transition period in dairy cows. In this study, plasma level of MDA was considered as an indicator of lipid peroxidation and SOD, catalase, GSH and GSHPx as antioxidants. The lipid peroxidation was significantly (p<0.001) higher in cows during early lactation as compared to the cows in advanced pregnancy. A significant positive correlation (r = +0.831, p<0.01) was determined between MDA and catalase in early lactating cows. In early lactating cows, blood glutathione was significantly lower than in advanced pregnant cows. However, early lactating cows showed non-significant negative correlation for all antioxidant enzymes with lipid peroxidation. In conclusion, dairy cows seemed to have more oxidative stress and low antioxidant defense during early lactation or just after parturition than advanced pregnant cows, and this appears to be the reason for their increased susceptibility to production diseases (e.g. mastitis, metritis, retention of fetal membranes etc.) and other health problems.
Simple Fuzzy Rule Based Edge Detection
( O. P. Verma ),( Veni Jain ),( Rajni Gumber ) 한국정보처리학회 2013 Journal of information processing systems Vol.9 No.4
Most of the edge detection methods available in literature are gradient based, which further apply thresholding, to find the final edge map in an image. In this paper, we propose a novel method that is based on fuzzy logic for edge detection in gray images without using the gradient and thresholding. Fuzzy logic is a mathematical logic that attempts to solve problems by assigning values to an imprecise spectrum of data in order to arrive at the most accurate conclusion possible. Here, the fuzzy logic is used to conclude whether a pixel is an edge pixel or not. The proposed technique begins by fuzzifying the gray values of a pixel into two fuzzy variables, namely the black and the white. Fuzzy rules are defined to find the edge pixels in the fuzzified image. The resultant edge map may contain some extraneous edges, which are further removed from the edge map by separately examining the intermediate intensity range pixels. Finally, the edge map is improved by finding some left out edge pixels by defining a new membership function for the pixels that have their entire 8-neighbourhood pixels classified as white. We have compared our proposed method with some of the existing standard edge detector operators that are available in the literature on image processing. The quantitative analysis of the proposed method is given in terms of entropy value.
Simple Fuzzy Rule Based Edge Detection
Verma, O.P.,Jain, Veni,Gumber, Rajni Korea Information Processing Society 2013 Journal of information processing systems Vol.9 No.4
Most of the edge detection methods available in literature are gradient based, which further apply thresholding, to find the final edge map in an image. In this paper, we propose a novel method that is based on fuzzy logic for edge detection in gray images without using the gradient and thresholding. Fuzzy logic is a mathematical logic that attempts to solve problems by assigning values to an imprecise spectrum of data in order to arrive at the most accurate conclusion possible. Here, the fuzzy logic is used to conclude whether a pixel is an edge pixel or not. The proposed technique begins by fuzzifying the gray values of a pixel into two fuzzy variables, namely the black and the white. Fuzzy rules are defined to find the edge pixels in the fuzzified image. The resultant edge map may contain some extraneous edges, which are further removed from the edge map by separately examining the intermediate intensity range pixels. Finally, the edge map is improved by finding some left out edge pixels by defining a new membership function for the pixels that have their entire 8-neighbourhood pixels classified as white. We have compared our proposed method with some of the existing standard edge detector operators that are available in the literature on image processing. The quantitative analysis of the proposed method is given in terms of entropy value.
Software Fault Prediction at Design Phase
Singh, Pradeep,Verma, Shrish,Vyas, O.P. The Korean Institute of Electrical Engineers 2014 Journal of Electrical Engineering & Technology Vol.9 No.5
Prediction of fault-prone modules continues to attract researcher's interest due to its significant impact on software development cost. The most important goal of such techniques is to correctly identify the modules where faults are most likely to present in early phases of software development lifecycle. Various software metrics related to modules level fault data have been successfully used for prediction of fault-prone modules. Goal of this research is to predict the faulty modules at design phase using design metrics of modules and faults related to modules. We have analyzed the effect of pre-processing and different machine learning schemes on eleven projects from NASA Metrics Data Program which offers design metrics and its related faults. Using seven machine learning and four preprocessing techniques we confirmed that models built from design metrics are surprisingly good at fault proneness prediction. The result shows that we should choose Naïve Bayes or Voting feature intervals with discretization for different data sets as they outperformed out of 28 schemes. Naive Bayes and Voting feature intervals has performed AUC > 0.7 on average of eleven projects. Our proposed framework is effective and can predict an acceptable level of fault at design phases.
Software Fault Prediction at Design Phase
Pradeep Singh,Shrish Verma,O. P Vyas 대한전기학회 2014 Journal of Electrical Engineering & Technology Vol.9 No.5
Prediction of fault-prone modules continues to attract researcher’s interest due to its significant impact on software development cost. The most important goal of such techniques is to correctly identify the modules where faults are most likely to present in early phases of software development lifecycle. Various software metrics related to modules level fault data have been successfully used for prediction of fault-prone modules. Goal of this research is to predict the faulty modules at design phase using design metrics of modules and faults related to modules. We have analyzed the effect of pre-processing and different machine learning schemes on eleven projects from NASA Metrics Data Program which offers design metrics and its related faults. Using seven machine learning and four preprocessing techniques we confirmed that models built from design metrics are surprisingly good at fault proneness prediction. The result shows that we should choose Naive Bayes or Voting feature intervals with discretization for different data sets as they outperformed out of 28 schemes. Naive Bayes and Voting feature intervals has performed AUC > 0.7 on average of eleven projects. Our proposed framework is effective and can predict an acceptable level of fault at design phases.
사과과일썩음증상을 일으키는 Alternaria alternata의 포자발아요인
S.K. TAK,O.P. VERMA,V.N. PATHAK 한국응용곤충학회 1985 한국응용곤충학회지 Vol.24 No.3
Effect of some physical and chemical factors on germination of conidia of Alternaria alternata (Fries) Keissler causing fruit rot of apple was investigated. The germination was maximum at , 100 per cent RH and at 5.5 pH Syllit, amongst the 11 fungicides and Planofix, amongst the 5 growth regulators caused maximum inhibition of conidial germination.
R.B.L. 굽타,V.N. 파닥,O.P. 베르마,Gupta, R.B.L.,Pathak, V.N.,Verma, O.P. Korean Society of Applied Entomology 1985 한국식물보호학회지 Vol.24 No.3
Influence of temperature, relative humidity, spore washing and spore drying on conidial germination of Alternaria porri(Ell.) Cif. was studied. Maximum conidial germination occurred at 100% relative humidity prevailing for 6 hours or more at $25^{\circ}C$. Conidial germination decreased with increase in number of spore washings. Drying of conidia for more than half an hour caused significant decrease in germination. In all the experiments, conidial germinatio increased with increase in incubation period.
R.B.L. GUPTA,V.N. PATHAK,O.P. VERMA 한국응용곤충학회 1985 한국응용곤충학회지 Vol.24 No.3
Influence of temperature, relative humidity, spore washing and spore drying on conidial germination of Alternaria porri(Ell.) Cif. was studied. Maximum conidial germination occurred at 100% relative humidity prevailing for 6 hours or more at . Conidial germination decreased with increase in number of spore washings. Drying of conidia for more than half an hour caused significant decrease in germination. In all the experiments, conidial germinatio increased with increase in incubation period.