Search

Your search keyword '"Kumar, G. S."' showing total 490 results
Start Over Author "Kumar, G. S." Publication Year Range Last 10 years
490 results on '"Kumar, G. S."'

7. Conversation Graph Construction Approach of Cyberbully Detection Using Bully Scores

Author

Valliyammai, C., Manikandan, D., Nithish Kumar, G. S., Keerthika, M., Kavin, B., 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, Joshi, Amit, editor, Mahmud, Mufti, editor, Ragel, Roshan G., editor, and Karthik, S., editor

Published
2024
Full Text
View/download PDF

8. A Systematic Comprehension of DL Models for Categorizing Plant Diseases

Author

Kapu, Prathyusha, Chouhan, Arun Singh, Talasila, Srinivas, Kumar, G. S. Naveen, Kumar, Chinthakindi Kiran, 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, Reddy, Vustikayala Sivakumar, editor, Wang, Jiacun, editor, and Reddy, K.T.V., editor

Published
2024
Full Text
View/download PDF

12. Explainable artificial intelligence approaches for COVID-19 prognosis prediction using clinical markers

Author

Krishnaraj Chadaga, Srikanth Prabhu, Niranjana Sampathila, Rajagopala Chadaga, Shashikiran Umakanth, Devadas Bhat, and Shashi Kumar G S

Subjects
Medicine, Science
Abstract

Abstract The COVID-19 influenza emerged and proved to be fatal, causing millions of deaths worldwide. Vaccines were eventually discovered, effectively preventing the severe symptoms caused by the disease. However, some of the population (elderly and patients with comorbidities) are still vulnerable to severe symptoms such as breathlessness and chest pain. Identifying these patients in advance is imperative to prevent a bad prognosis. Hence, machine learning and deep learning algorithms have been used for early COVID-19 severity prediction using clinical and laboratory markers. The COVID-19 data was collected from two Manipal hospitals after obtaining ethical clearance. Multiple nature-inspired feature selection algorithms are used to choose the most crucial markers. A maximum testing accuracy of 95% was achieved by the classifiers. The predictions obtained by the classifiers have been demystified using five explainable artificial intelligence techniques (XAI). According to XAI, the most important markers are c-reactive protein, basophils, lymphocytes, albumin, D-Dimer and neutrophils. The models could be deployed in various healthcare facilities to predict COVID-19 severity in advance so that appropriate treatments could be provided to mitigate a severe prognosis. The computer aided diagnostic method can also aid the healthcare professionals and ease the burden on already suffering healthcare infrastructure.

Published
2024
Full Text
View/download PDF

14. KNN-Based Decision Model for Device Argumentation in Ambient Assisted Living

Author

Madhan Kumar, G. S., Shiva Prakash, S. P., Krinkin, Kirill, 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, Li, Yong, 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, Oneto, Luca, 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, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Kulkarni, Anand J., editor, Mirjalili, Seyedali, editor, and Udgata, Siba Kumar, editor

Published
2023
Full Text
View/download PDF

21. Strain Measurement of Aluminium in Tensometer Using Digital Image Correlation (DIC)

Author

Vijaya, A., Kannan, N., Palaniappan, M., Kumar, G. S. Lohith, Cavas-Martínez, Francisco, Series Editor, Chaari, Fakher, Series Editor, di Mare, Francesca, Series Editor, Gherardini, Francesco, Series Editor, Haddar, Mohamed, Series Editor, Ivanov, Vitalii, Series Editor, Kwon, Young W., Series Editor, Trojanowska, Justyna, Series Editor, Singh, Manvandra Kumar, editor, and Gautam, Rakesh Kumar, editor

Published
2022
Full Text
View/download PDF

22. IoT-Based Energy Saving Recommendations by Classification of Energy Consumption Using Machine Learning Techniques

Author

Dhipti, G. Siva Naga, Swathi, Baggam, Reddy, E. Venkateswara, Kumar, G. S. Naveen, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Reddy, V. Sivakumar, editor, Prasad, V. Kamakshi, editor, Wang, Jiacun, editor, and Reddy, K.T.V., editor

Published
2022
Full Text
View/download PDF

23. Deep Learning Approach for Image-Based Plant Species Classification

Author

Venkateswara Reddy, E., Naveen Kumar, G. S., Swathi, Baggam, Siva Naga Dhipti, G., Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Reddy, V. Sivakumar, editor, Prasad, V. Kamakshi, editor, Wang, Jiacun, editor, and Reddy, K.T.V., editor

Published
2022
Full Text
View/download PDF

28. Wavelet based machine learning models for classification of human emotions using EEG signal

Author

Shashi Kumar G S, Niranjana Sampathila, and Tanishq Tanmay

Subjects
Electroencephalogram, Discrete wavelet transform, Machine learning, Convolutional neural network, Support vector machine, Electric apparatus and materials. Electric circuits. Electric networks, TK452-454.4
Abstract

Humans have the ability to portray different expressions contrary to the emotional state of mind. Therefore, it is difficult to judge the human's real emotional state simply by judging the physical appearance. Although researchers are working on facial expressions analysis, voice recognition, gesture recognition accuracy levels of such analysis are much less and the results are not reliable. Classifying the human emotions with machine learning models and extracting discrete wavelet features of Electroencephalogram (EEG) is proposed. The EEG data from Database for Emotion Analysis using Physiological signal (DEAP) online datasets is used for analysis and consists of peripheral biological signals as well as EEG recordings. EEG signal is collected from 32 subjects while watching 40 1-min-long music videos. Each video clip is rated by the participants in terms of the level of Valence, Arousal, Dominance. In the proposed work we have considered a significant band of EEG with a reduced frontal electrode (Fp1, F3, F4, Fp2) to get a comparable good result. The accuracy obtained from K- nearest neighbour (KNN), Fine KNN and Support Vector Machine (SVM) are 92.5%, 90% and 90% respectively for Valence, Arousal and Dominance.

Published
2022
Full Text
View/download PDF

30. Interactions between Diphenylamine with 2-Hydroxypropyl β-Cyclodextrin based on Spectral, Biological and Theoretical Investigations.

Author

Antony Muthu Prabhu, A., Suresh Kumar, G. S., Rajendiran, N., Sathiyaseelan, K., and Balamathi, M.

Subjects
*CYCLODEXTRINS, *ATOMS in molecules theory, *DIPHENYLAMINE, *FRONTIER orbitals, *MOLECULAR structure
Abstract

The inclusion complex of diphenylamine (DPA) in 2-hydroxypropyl β-cyclodextrin (HP-β-CD) was synthesized by a co-precipitation method. The structure and molecular properties of the newly synthesized inclusion complex (DPA: HP-β-CD) were investigated along with a β-cyclodextrin (β-CD) inclusion complex (DPA: β-CD) using various analytical and theoretical methods. Phase solubility, absorption, fluorescence, Fourier transform-Infrared spectroscopy (FTIR), powder X-ray diffraction (PXRD) and scanning electron microscope (SEM) techniques were used to investigate the structural properties of the DPA before and after being encapsulated by the CDs (β-CD and HP-β-CD). Furthermore, the antioxidant and antibacterial activities were evaluated for DPA and the inclusion complexes (DPA: β-CD and DPA: HP-β-CD). The structure of the inclusion complexes was proposed based on the experimental results and their structural optimization was done using Becke's three parameter density functional theory using Lee-Yang-Parr's 3-21 G method in the gas phase. Then the various theoretical molecular properties, such as frontier molecular orbitals (FMO), molecular electrostatic potential map (MEP), Mulliken atomic charges, natural bond orbitals (NBO), electron localization function (ELF), localized orbital locator (LOL), quantum theory of atoms in a molecule (QTAIM) and noncovalent interactions—reduced density gradient (NCI-RDG) were studied for DPA and its inclusion complexes using the Gaussian 09 W software and Multiwfn 3.8 tool. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

36. Extraction of Key Frames Using Rough Set Theory for Video Retrieval

Author

Naveen Kumar, G. S., Reddy, V. S. K., Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Reddy, V. Sivakumar, editor, Prasad, V. Kamakshi, editor, Wang, Jiacun, editor, and Reddy, K. T. V., editor

Published
2020
Full Text
View/download PDF

40. Influence of nano hexagonal boron nitride on the wear properties of aluminium alloy

Author

Thomas, Shijo, Menachery, Nice, Thomas, Lijo P, N, Santhosh, Kumar G S, Pradeep, and Hebbar, Gurumoorthy S

Abstract

ABSTRACTSpark plasma sintered, AA7050 reinforced with nano hexagonal boron nitride (n-h-BN) particles followed by characterisation research was carried out to determine the impact of h-BN in the aluminium matrix. With the aid of field-emission scanning electron microscopy , the uniform dispersion of hexagonal boron nitride was examined, and the impact of altering h-BN concentration on the mechanical and tribological properties was studied. In order to achieve individual dispersion of h-BN particles at low milling time without causing any structural damage, pre-mixing of powders prior to high-energy ball milling proved beneficial. Using the X-ray diffraction method, structural and phase analysis was performed on the powders as well as sintered samples. Pin-on disc apparatus is used for testing the weight loss of the composites. SEM was used to examine the worn surfaces of the substrate. According to the wear analysis, adding reinforcement with 0.5 wt% h-BN resulted in a 65% reduction in wear rate and a 33% increase in hardness. It has been found that h-BN tends to aggregate in composite powder above 0.5 wt%, reducing its physical and mechanical qualities.

Published
2024
Full Text
View/download PDF

42. Sheep pastoralism in southern Karnataka

Author

NAVEEN KUMAR G S, VANI A, and BASAVARAJ INAMDAR

Subjects
Karnataka, Kuruba, Migratory paths, Pastoralism, Sira sheep, Animal culture, SF1-1100
Abstract

Present study was conducted to understand and document the migratory system followed, socio-economic status, management and healthcare practices adopted by pastoralists of southern Karnataka. In-person interview method with a structured questionnaire was used for collecting data from 25 shepherd groups on migration. Migration starts during December and continues for 6–8 months covering around 200 km. The breed is locally called Tumkur or Sira sheep which is not yet recognized as a separate breed. Migratory flock usually contains 1,000 to 1,200 sheep, 50 goats, 10 donkeys and 2–4 dogs. The average adult male to female ratio is 1 : 22. Sale of lambs and penning rental are the main sources of income. Sheep pastoralism is an established and effective way of utilizing the excess green cover in transient regions by the sheep from pasture deficient dry zones. Maintaining the social and community pasture and forest lands at their home place will be a benefit during the lean and non-migratory periods. Assessing the migratory paths, fodder and water resource and penning demand by the farmers on migratory tract will help policy makers to provide suitable interventions to curtail the problems of pastoralists. The traditional knowledge of shepherds should be documentedand validated for larger use. The pastoralists need to be educated and trained about the use of digital finance management, herd diversification, health management and government schemes to increase their profitability and standard of living.

Published
2022
Full Text
View/download PDF

43. Neural Network Approach for Classification of Human Emotions from EEG Signal

Author

Shashi Kumar, G. S., Sampathila, Niranjana, Shetty, Harikishan, 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, Ruediger, 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, 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, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Ray, Kanad, editor, Sharan, S. N., editor, Rawat, Sanyog, editor, Jain, S. K., editor, Srivastava, Sumit, editor, and Bandyopadhyay, Anirban, editor

Published
2019
Full Text
View/download PDF

45. An Analysis of IPv6 Protocol Implementation for Secure Data Transfer in Cloud Computing

Author

Patibandla, Anitha, Naveen Kumar, G. S., Meneni, Anusha, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Wang, Jiacun, editor, Reddy, G. Ram Mohana, editor, Prasad, V. Kamakshi, editor, and Reddy, V. Sivakumar, editor

Published
2019
Full Text
View/download PDF

46. Key Frame Extraction Using Rough Set Theory for Video Retrieval

Author

Naveen Kumar, G. S., Reddy, V. S. K., Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Wang, Jiacun, editor, Reddy, G. Ram Mohana, editor, Prasad, V. Kamakshi, editor, and Reddy, V. Sivakumar, editor

Published
2019
Full Text
View/download PDF

47. Association between MHC gene and immune response to FMD vaccine in Malnad Gidda cattle

Author

HEMANTH GOWDA K, M NARAYANA SWMAY, C S NAGARAJA, K GANESH, and NAVEEN KUMAR G S

Subjects
Foot and mouth disease, Immune response, Malnad gidda, MHC gene, Animal culture, SF1-1100
Abstract

Malnad Gidda cattle with specific qualities like disease resistance, heat tolerance, ability to survive and productionunder stress and low input conditions needs to be conserved for future. They are found to be less susceptible forfoot and mouth disease (FMD) and are normally not vaccinated for FMD. The present study was conducted todetermine the genetic polymorphism at MHC DRB3.2 loci and cellular immune responsiveness to FMD vaccinationin Malnad Gidda compared to Hallikar × HF crossbred cattle. A total of 12 cattle, of which six Malnad Gidda andsix Hallikar × Holstein Friesian crossbred animals aged between one to three years were selected. The genomicDNA was isolated and utilized to determine the genetic polymorphism at MHC DRB3.2 loci. The blood sampleswere collected from the same animals for estimation of CD4 and CD8 lymphocytes by flow cytometry to determinethe cellular immune responsiveness to FMD vaccination. The data obtained were subjected to statistical analysisGraphPad Prism Version 5.01. The two allelic variants MHC DRB3.2*117 and *219 present between MalnadGidda and Holstein Friesian crossbred cattle could be responsible for better cellular immune responsiveness withsignificantly higher CD4 lymphocytes population to FMD vaccination in Malnad Gidda cattle compared to Hallikar× HF crossbred cattle.

Published
2022
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results