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1,178 results on '"GOPINATH, K."'

2. Soil Carbon Sequestration and Agronomic Productivity as Influenced by the Long-Term Organic and Inorganic Fertilisation Under the Upland Rice–Wheat System in Vertisols of Central India

Author

Srinivasarao, Ch., Kundu, Sumanta, Dubey, D. P., Dubey, Rajiv, Rakesh, S., Lal, Rattan, Abhilash, P. C., Prasad, J. V. N. S., Pratibha, G., Jayaraman, Somasundaram, Mrunalini, K., Gopinath, K. A., Singh, Anil K., Dinesh, G. K., Naidu, G. Mohan, Singh, Pankaj K., Baral, Kirttiranjan, and Singh, Rajbir

Published
2024
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8. Healthcare AI: A Bibliometric Review

Author

Sarkar, Pramir, Gopinath, K., Prakash, Ashish V., Rannenberg, Kai, Editor-in-Chief, Soares Barbosa, Luís, Editorial Board Member, Carette, Jacques, Editorial Board Member, Tatnall, Arthur, Editorial Board Member, Neuhold, Erich J., Editorial Board Member, Stiller, Burkhard, Editorial Board Member, Stettner, Lukasz, Editorial Board Member, Pries-Heje, Jan, Editorial Board Member, Kreps, David, Editorial Board Member, Rettberg, Achim, Editorial Board Member, Furnell, Steven, Editorial Board Member, Mercier-Laurent, Eunika, Editorial Board Member, Winckler, Marco, Editorial Board Member, Malaka, Rainer, Editorial Board Member, Sharma, Sujeet K., editor, Dwivedi, Yogesh K., editor, Metri, Bhimaraya, editor, Lal, Banita, editor, and Elbanna, Amany, editor

Published
2024
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9. Human Resource Analytics: Leveraging Machine Learning for Employee Attrition Prediction

Author

Gopinath, K., Appavu alias Balamurugan, S., Rannenberg, Kai, Editor-in-Chief, Soares Barbosa, Luís, Editorial Board Member, Carette, Jacques, Editorial Board Member, Tatnall, Arthur, Editorial Board Member, Neuhold, Erich J., Editorial Board Member, Stiller, Burkhard, Editorial Board Member, Stettner, Lukasz, Editorial Board Member, Pries-Heje, Jan, Editorial Board Member, Kreps, David, Editorial Board Member, Rettberg, Achim, Editorial Board Member, Furnell, Steven, Editorial Board Member, Mercier-Laurent, Eunika, Editorial Board Member, Winckler, Marco, Editorial Board Member, Malaka, Rainer, Editorial Board Member, Sharma, Sujeet K., editor, Dwivedi, Yogesh K., editor, Metri, Bhimaraya, editor, Lal, Banita, editor, and Elbanna, Amany, editor

Published
2024
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18. Notification of Vivek Maize Hybrid 25

Author

Mahajan, V., Babu, R., Mani, V. P., Gupta, H. S., Koranga, K. S., Bisht, G. S., Pant, M. C., Pant, S. K., and Gopinath, K. A.

Published
2008

20. Enhancing the Credit Card Fraud Detection Using Decision Tree and Adaptive Boosting Techniques

Author

Prasanna Kumar, K. R., Aravind, S., Gopinath, K., Navienkumar, P., Logeswaran, K., Gunasekar, M., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Abraham, Ajith, editor, Pllana, Sabri, editor, Casalino, Gabriella, editor, Ma, Kun, editor, and Bajaj, Anu, editor

Published
2023
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24. Notification of Vivek Maize Hybrid 21

Author

Babu, R., Mani, V. P., Singh, Rajesh, Mahajan, V., Gupta, H. S., Koranga, K. S., Bisht, G. S., Pant, S. K., and Gopinath, K. A.

Published
2008

34. High temperature deformation behaviour and microstructure evolution in Cu containing High Strength Low Alloy (HSLA) steel.

Author

Ramana, A. Venkata, Balasundar, I., Davidson, M.J., Singh, Vajinder, Gautam, J.P., Gopinath, K., Balamuralikrishnan, R., and Raghu, T.

Subjects
LOW alloy steel, STRAIN rate, COPPER, CRYSTAL grain boundaries, TEMPERATURE effect
Abstract

The hot deformation behaviour of a Cu containing high strength low alloy (HSLA) steel has been evaluated by carrying out hot compression tests over a temperature range of 900 °C to 1100 °C and constant true strain rates of 0.0003 to 1 s−1. Although single peak flow curve is observed predominantly, a tendency to exhibit multiple peaks at low strain rates (0.0003 and/or 0.001 s−1) at temperature greater than 950 °C. The important parameters pertaining to dynamic recrystallisation (DRX), such as critical, peak, steady state stress and strain were ascertained, and the DRX state diagram depicting the variation of critical parameters governing DRX with Zener-Hollomon parameter Z was established. The volume fraction of recrystallised grains, computed from flow stress, as expected, follows a sigmoidal trend indicating higher kinetics at low strain rates for a given temperature. Reconstruction of prior austenite grain boundaries (PAGB) based on electron back scattered diffraction (EBSD) technique for a few select specimens clearly elucidated the effect of temperature and strain rate on the DRX behaviour of the steel. The DRX state diagram established here clearly demarcates the deformation space i.e. temperature-strain rate-stain space into regimes where the material exhibits full DRX, hardening/softening + DRX and only hardening (no DRX) behaviour. This would be useful for designing suitable forging sequence to achieve the desired microstructure and mechanical properties. [ABSTRACT FROM AUTHOR]

Published
2024
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35. Performance Tuning of Hadoop MapReduce: A Noisy Gradient Approach

Author

Kumar, Sandeep, Padakandla, Sindhu, L, Chandrashekar, Parihar, Priyank, Gopinath, K, and Bhatnagar, Shalabh

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Machine Learning
Abstract

Hadoop MapReduce is a framework for distributed storage and processing of large datasets that is quite popular in big data analytics. It has various configuration parameters (knobs) which play an important role in deciding the performance i.e., the execution time of a given big data processing job. Default values of these parameters do not always result in good performance and hence it is important to tune them. However, there is inherent difficulty in tuning the parameters due to two important reasons - firstly, the parameter search space is large and secondly, there are cross-parameter interactions. Hence, there is a need for a dimensionality-free method which can automatically tune the configuration parameters by taking into account the cross-parameter dependencies. In this paper, we propose a novel Hadoop parameter tuning methodology, based on a noisy gradient algorithm known as the simultaneous perturbation stochastic approximation (SPSA). The SPSA algorithm tunes the parameters by directly observing the performance of the Hadoop MapReduce system. The approach followed is independent of parameter dimensions and requires only $2$ observations per iteration while tuning. We demonstrate the effectiveness of our methodology in achieving good performance on popular Hadoop benchmarks namely \emph{Grep}, \emph{Bigram}, \emph{Inverted Index}, \emph{Word Co-occurrence} and \emph{Terasort}. Our method, when tested on a 25 node Hadoop cluster shows 66\% decrease in execution time of Hadoop jobs on an average, when compared to the default configuration. Further, we also observe a reduction of 45\% in execution times, when compared to prior methods.

Published
2016
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36. Predicting the Farmland for Agriculture from the Soil Features Using Data Mining

Author

Harshath, Kada, Mareedu, Kamalnath, Gopinath, K., Sathya Bama Krishna, R., Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Bhoi, Akash Kumar, editor, Mallick, Pradeep Kumar, editor, Balas, Valentina Emilia, editor, and Mishra, Bhabani Shankar Prasad, editor

Published
2021
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37. Failure Behaviour of a Thin Domed Steel Disc with and without Scores Under a Pressure Impulse

Author

Gopinath, K., Narayanamurthy, V., Rao, Y. V. D., Cavas-Martínez, Francisco, Series Editor, Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Haddar, Mohamed, Series Editor, Ivanov, Vitalii, Series Editor, Kwon, Young W., Series Editor, Trojanowska, Justyna, Series Editor, di Mare, Francesca, Series Editor, Rao, Y. V. D., editor, Amarnath, C., editor, Regalla, Srinivasa Prakash, editor, Javed, Arshad, editor, and Singh, Kundan Kumar, editor

Published
2021
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43. Are Markov Models Effective for Storage Reliability Modelling?

Author

Karmakar, Prasenjit and Gopinath, K.

Subjects
Computer Science - Performance
Abstract

Continuous Time Markov Chains (CTMC) have been used extensively to model reliability of storage systems. While the exponentially distributed sojourn time of Markov models is widely known to be unrealistic (and it is necessary to consider Weibull-type models for components such as disks), recent work has also highlighted some additional infirmities with the CTMC model, such as the ability to handle repair times. Due to the memoryless property of these models, any failure or repair of one component resets the "clock" to zero with any partial repair or aging in some other subsystem forgotten. It has therefore been argued that simulation is the only accurate technique available for modelling the reliability of a storage system with multiple components. We show how both the above problematic aspects can be handled when we consider a careful set of approximations in a detailed model of the system. A detailed model has many states, and the transitions between them and the current state captures the "memory" of the various components. We model a non-exponential distribution using a sum of exponential distributions, along with the use of a CTMC solver in a probabilistic model checking tool that has support for reducing large state spaces. Furthermore, it is possible to get results close to what is obtained through simulation and at much lower cost.

Published
2015

44. Scalable Reliability Modelling of RAID Storage Subsystems

Author

Karmakar, Prasenjit and Gopinath, K.

Subjects
Computer Science - Performance
Abstract

Reliability modelling of RAID storage systems with its various components such as RAID controllers, enclosures, expanders, interconnects and disks is important from a storage system designer's point of view. A model that can express all the failure characteristics of the whole RAID storage system can be used to evaluate design choices, perform cost reliability trade-offs and conduct sensitivity analyses. However, including such details makes the computational models of reliability quickly infeasible. We present a CTMC reliability model for RAID storage systems that scales to much larger systems than heretofore reported and we try to model all the components as accurately as possible. We use several state-space reduction techniques at the user level, such as aggregating all in-series components and hierarchical decomposition, to reduce the size of our model. To automate computation of reliability, we use the PRISM model checker as a CTMC solver where appropriate. Our modelling techniques using PRISM are more practical (in both time and effort) compared to previously reported Monte-Carlo simulation techniques. Our model for RAID storage systems (that includes, for example, disks, expanders, enclosures) uses Weibull distributions for disks and, where appropriate, correlated failure modes for disks, while we use exponential distributions with independent failure modes for all other components. To use the CTMC solver, we approximate the Weibull distribution for a disk using sum of exponentials and we confirm that this model gives results that are in reasonably good agreement with those from the sequential Monte Carlo simulation methods for RAID disk subsystems reported in literature earlier. Using a combination of scalable techniques, we are able to model and compute reliability for fairly large configurations with upto 600 disks using this model.

Published
2015

46. Adaptations and Safety Modifications to Perform Safe Minimal Access Surgery (MIS: Laparoscopy and Robotic) During the COVID-19 Pandemic: Practice Modifications Expert Panel Consensus Guidelines from Academia of Minimal Access Surgical Oncology (AMASO)

Author

Somashekhar, S. P., Acharya, Rudra, Saklani, Avinash, Parikh, Devendra, Goud, Jagdishwar, Dixit, Jagannath, Gopinath, K., Kumar, M. Vijay, Bhojwani, Rajesh, Nayak, Sandeep, Rao, Subramaneswar, Kothari, Kiran, Chandramohan, K., Desai, Sharad, and Gupta, Arnab

Published
2021
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48. High-Performance Photocatalysts for Organic Reactions

Author

Goutham, R., Gopinath, K. P., Ramprasath, A., Srikanth, B., Badri Narayan, R., Lichtfouse, Eric, Series Editor, Schwarzbauer, Jan, Series Editor, Robert, Didier, Series Editor, Inamuddin, editor, Ahamed, Mohd Imran, editor, and Asiri, Abdullah M., editor

Published
2019
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