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- 저자 : Mukherjee Priya (검색결과 2 건)
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Priya, K.,Pal, A.K.,Sahu, N.P.,Mukherjee, S.C. Asian Australasian Association of Animal Productio 2005 Animal Bioscience Vol.18 No.11
Ninety advanced Catla catla fingerlings (av. wt. 16 g) were randomly distributed in six treatment groups with three replicates each for an experimental period of 60 days to study the effect of dietary lipid source on growth, enzyme activities and immuno-hematological parameters. Six isoprotein (40.0-41.9%) and isocaloric (4,260 kcal $kg^{-1}$) semi-purified diets were prepared with varying levels of soybean oil (SBO) and cod liver oil (CLO) within a total of 8% lipid viz., $D_1$ (Control), $D_2$ (8% SBO), $D_3$ (6% SBO and 2% CLO), $D_4$ (4% SBO and 4% CLO), $D_5$ (2% SBO and 6% CLO) and $D_6$ (8% CLO). Highest SGR was noted in $D_5$ (0.73${\pm}$0.03) group, which was similar with $D_3$ (0.71${\pm}$0.02) and $D_4$ (0.69${\pm}$0.01) groups. Activity of intestinal lipase, hepatic glucose-6-phosphate dehydrogenase (G6PDH) and aspartate amino transferase (AST) of the lipid treatment groups were significantly higher (p<0.05) than the control group. The respiratory burst activity of the phagocytes (Nitroblue tetrazolium (NBT)) was highest in $D_2$ (1.95${\pm}$0.21) followed by $D_3$ (1.19${\pm}$0.15) group, which were significantly (p<0.05) higher than the other groups. Globulin level was significantly higher in $D_3$ (1.29${\pm}$0.08) than in the other groups expect $D_4$. Hemoglobin content and total erythrocyte count did not show any significant difference. From this study, it is concluded that a diet containing 6% soybean oil and 2% cod liver oil ($D_3$) yields higher growth and immune response in Catla catla fingerlings and would be cost effective.
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A Novel SDN-Based Security Framework for Wireless Sensor Networks Using TDCNN and PGF-ECCMohit
Kumar,Mukherjee Priya,Verma Sahil,Kavita,Jhanjhi N. Z.,Vimal S.,Almutain Bandar 한국컴퓨터산업협회 2023 Human-centric Computing and Information Sciences Vol.13 No.-
Wireless sensor networks (WSN) comprise a huge number of stationary or mobile sensor nodes that considerably support multi-hop communication. Intruder attacks such as wormholes, spoofing, etc., make it more susceptible in turn influence WSN’s confidentiality. Therefore, utilizing tanh activation function centered deep convolution neural network (TDCNN) and polynomial Galois field elliptical curve cryptography (PGF-ECC), a novel approach named malicious node detection and privacy preservation of software-defined WSN is conceptualized in this work. Many measures have been taken in the work for assuring security. Utilizing taxicab metric centered KMedoid (TM-KMedoid) algorithm, the sensor nodes of the network are initially sorted into clusters. After that, using the Horse optimization algorithm (HOA), the cluster head (CH) selection is performed where the best node in the cluster is selected as the CH. Next, the data packets are transferred by the CH to the base station (BS) via the software-defined networking (SDN) controller. The SDN controller is applied with a TDCNN classifier that predicts the node’s trustworthiness for detecting whether the node is malicious or not. The data is transferred to BS if the node is a trusted one else, the node gets rejected. The PGF-ECC algorithm is employed for ensuring the data’s secure transmission to the BS. The proposed method’s performance is contrasted with the existent systems in an experimental evaluation. It exhibits superior performance when analogized to top-notch techniques, and highly assures the network’s authenticity.
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