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TL;DR: The proposed scheme allows periodic group based sharing of resource inventories and supports search and retrieval of queries within a restricted time period and outperforms one of the state-of the art content sharing schemes, discover-predict-deliver in terms of response delivery, average energy consumption and average delivery latency.
16 citations
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TL;DR: Three different regression models such as artificial neural network, vector-valued regularized kernel function approximation, and support vector regression are used to evaluate the performance of the proposed method for prediction of TF and TR using ET signals.
Abstract: Liquor characteristics of black cut, tear, and curl tea mostly depend on two biochemical components like theaflavin (TF) and thearubigin (TR). Evaluation of tea quality can be done efficiently by estimating the concentration of TF and TR without using biochemical tests as it takes much time, which requires laborious effort for sample preparation, storage, and measurement. Moreover, the required instruments for this test are very costly. In this paper, we have proposed an efficient method of TF and TR prediction in a given tea sample using electronic tongue (ET) signal. Combinations of transformed features, like discrete cosine transform, Stockwell transform (ST), and singular value decomposition, of ET signals are fused to develop regression models to predict the contents of TF, TR, and TR/TF. Three different regression models such as artificial neural network, vector-valued regularized kernel function approximation, and support vector regression are used to evaluate the performance of the proposed method. High prediction accuracy using fusion of features ensures the effectiveness of the proposed method for prediction of TF and TR using ET signals.
16 citations
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TL;DR: In this article, the authors investigated the cholesterol-lowering properties of rice bran oil and sesame oil containing soy yogurt and found that the addition of oil(s) improved physicochemical and microbiological characteristics of soy yogurt.
16 citations
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TL;DR: In this paper, the authors considered a model of the universe filled with modified Chaplygin gas and another fluid (with barotropic equation of state) and its role in accelerating the universe.
Abstract: In this letter, we consider a model of the universe filled with modified Chaplygin gas and another fluid (with barotropic equation of state) and its role in accelerating phase of the universe. We have assumed that the mixture of these two fluid models is valid from (i) the radiation era to ΛCDM for -1 ≤ γ ≤ 1 and (ii) the radiation era to quintessence model for γ < -1. For these two fluid models, the statefinder parameters describe different phase of the evolution of the universe.
16 citations
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TL;DR: The proposed method attempts to identify those mallicious Botnet traffic from regular traffic using novel deep learning approaches like Artificial Neural Networks (ANN), Gatted Recurrent Units (GRU), Long or Short Term Memory (LSTM) model, and demonstrates significant improvement of all previous works.
Abstract: Advancement of information and communication techniques have led to share big amount of information which is increasing day by day through online activities and creating new added value over the internet services. At the same time threats to the security of cyber world has been increased with increasing number of heterogeneous connection points having powerful computational capacity. Internet being used to interact and control such automatic network devices connected to it. But hackers/crackers can exploit this network environment by putting malicious dummy node(s) or machine(s) called Botnet(s) to co-ordinate the attacks on security such as Denial of Service (DoS) or Distributed Denial of Service (DDoS). The proposed method attempts to identify those mallicious Botnet traffic from regular traffic using novel deep learning approaches like Artificial Neural Networks (ANN), Gatted Recurrent Units (GRU), Long or Short Term Memory (LSTM) model. The proposed model demonstrates significant improvement of all previous works. The testing dataset, Bot-IoT dataset is the latest and one of the largest public domain dataset used to justify improvement. Testing shows 99.7% classification accuracy which is precise and better than all previous works done. Results analysis and comparison shows the accuracy and supremacy over the latest work done on this field.
16 citations
Authors
Showing all 581 results
Name | H-index | Papers | Citations |
---|---|---|---|
Debnath Bhattacharyya | 39 | 578 | 6867 |
Samiran Mitra | 38 | 198 | 5108 |
Dipankar Chakravorty | 35 | 369 | 5288 |
S. Saha Ray | 34 | 217 | 3888 |
Tai-hoon Kim | 33 | 526 | 4974 |
Anindya Sen | 29 | 109 | 3472 |
Ujjal Debnath | 29 | 335 | 3828 |
Anirban Mukhopadhyay | 29 | 169 | 3200 |
Avijit Ghosh | 28 | 121 | 2639 |
Mrinal K. Ghosh | 26 | 64 | 2243 |
Biswanath Bhunia | 23 | 75 | 1466 |
Jayati Datta | 23 | 55 | 1520 |
Nabarun Bhattacharyya | 23 | 136 | 1960 |
Pinaki Bhattacharya | 19 | 114 | 1193 |
Dwaipayan Sen | 18 | 71 | 1086 |