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192 results on '"Haritha K"'

1. Distributed Genetic Algorithm for Community Detection in Large Graphs with a Parallel Fuzzy Cognitive Map for Focal Node Identification

Author

Haritha K., Judy M. V., Konstantinos Papageorgiou, and Elpiniki Papageorgiou

Subjects
parallel fuzzy cognitive maps, distributed genetic algorithm, community detection, focal nodes, social networks, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
Abstract

This study addresses the importance of focal nodes in understanding the structural composition of networks. To identify these crucial nodes, a novel technique based on parallel Fuzzy Cognitive Maps (FCMs) is proposed. By utilising the focal nodes produced by the parallel FCMs, the algorithm efficiently creates initial clusters within the population. The community discovery process is accelerated through a distributed genetic algorithm that leverages the focal nodes obtained from the parallel FCM. This approach mitigates the randomness of the algorithm, addressing the limitations of the random population selection commonly found in genetic algorithms. The proposed algorithm improves the performance of the genetic algorithm by enabling informed decision making and forming a better initial population. This enhancement leads to improved convergence and overall algorithm performance. Furthermore, as graph sizes grow, traditional algorithms struggle to handle the increased complexity. To address this challenge, distributed algorithms are necessary for effectively managing larger data sizes and complexity. The proposed method is evaluated on diverse benchmark networks, encompassing both weighted and unweighted networks. The results demonstrate the superior scalability and performance of the proposed approach compared to the existing state-of-the-art methods.

Published
2023
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2. Assessing snowball effect of COVID-19 pandemic on Indian dairy sector

Author

GUNJAN BHANDARI, PRIYANKA LAL, UDITA CHAUDHARY, HARITHA K, R MALHOTRA, and B S CHANDEL

Subjects
Cost, COVID-19, Dairying, Demand, Impact, Animal culture, SF1-1100
Abstract

Dairy sector experienced supply setback as well as demand uncertainties owing to restrictive measures imposed for the control of COVID-19 pandemic. The present paper attempts to assess the multi-dimensional impact of pandemic on dairying by reviewing the emerging literature. The assessment shows that availability of feed and fodder declined by 11% during the initial months of lockdown making it the most affected supply chain. The dairy farmers incurred dual losses due to increase in cost of milk production (+6%) and simultaneous fall in milk prices (–5.6%). Major challenge for the dairy processors was posed by the fall in demand which declined steeply particularly for the ice-creams and milk based beverages. The estimated loss incurred by the dairy farmers is `4,000 per milch animal in the initial 40 days of lockdown which can further rise if losses due to missed artificial insemination and change in animal prices are also taken into account. Assessment of impact on the unorganized dairy sector is still unavailable without which the loss estimation from the perspective of milk buyers stands incomplete. Huge inventories of the Skimmed Milk Powder (SMP) are the immediate challenge which requires proper policy intervention for arresting further losses in the dairy sector.

Published
2022
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6. Random Matrices and Quantum Hamilton-Jacobi Method

Author

Haritha, K. and Chaitanya, K. V. S. Shiv

Subjects
Quantum Physics, Mathematical Physics
Abstract

In this paper, we start with the quantum Hamilton-Jacobi approach and show that the underlying complex pole evolution of the Schr\"odinger equation is described by the quantum action in terms of a random matrix. The wave function is given by the random matrix probability distribution function. In literature this is known as the famous Cole-Hopf Transformation., Comment: some of the content has overlap with arXiv:1801.00544 [quant-ph] and arXiv:1501.06665 [quant-ph]

Published
2021
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8. Performance Analysis of Distributed Algorithms for Big Data Classification

Author

Haritha, K., Judy, M. V., Angrisani, Leopoldo, Series Editor, Arteaga, Marco, 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, 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, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, 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, Venkataraman, Neelanarayanan, editor, Wang, Lipo, editor, Fernando, Xavier, editor, and Zobaa, Ahmed F., editor

Published
2023
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10. Statistical Mechanics of DNA Mutation using SUSY Quantum Mechanics

Author

Haritha, K. and Chaitanya, K. V. S. Shiv

Subjects
Condensed Matter - Statistical Mechanics, Quantum Physics
Abstract

In this paper, we investigate DNA denaturation through Statistical Mechanics and show that exceptional polynomials lead to DNA mutation. We consider a DNA model with two chains connected by Morse potential representing the H bonds, and then we calculate the partition function for this model. The partition function is converted into a Schr\"odinger like an equation. We exploit the techniques of SUSY quantum mechanics to model DNA mutation. We also compute the thermal denaturation of DNA for each mutated state.

Published
2020
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12. Relativistic Potentials with Rational Extensions

Author

Haritha, K. and Chaitanya, K. V. S. Shiv

Subjects
Quantum Physics
Abstract

In this paper, we construct isospectral Hamiltonians without shape invariant potentials for the relativistic quantum mechanical potentials such as the Dirac Oscillator and Hydrogen-like atom., Comment: 18 pages

Published
2019
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13. Structure-Texture Decomposition-Based Enhancement Framework for Weakly Illuminated Images

Author

Haritha, K. M., Sreeni, K. G., Zacharias, Joseph, Jeena, R. S., Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Raman, Balasubramanian, editor, Murala, Subrahmanyam, editor, Chowdhury, Ananda, editor, Dhall, Abhinav, editor, and Goyal, Puneet, editor

Published
2022
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17. Effectual Evaluation on Diabetic Retinopathy

Author

Nair, Arun T., Muthuvel, K., Haritha, K. S., 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 Thakur, Nileshsingh V., editor

Published
2022
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18. Artificial Intelligence in 3D Printing: A Revolution in Health Care

Author

Banerjee, Aishwarya, Haridas, Haritha K., SenGupta, Arunima, Jabalia, Neetu, Lovell, Nigel H., Advisory Editor, Oneto, Luca, Advisory Editor, Piotto, Stefano, Advisory Editor, Rossi, Federico, Advisory Editor, Samsonovich, Alexei V., Advisory Editor, Babiloni, Fabio, Advisory Editor, Liwo, Adam, Advisory Editor, Magjarevic, Ratko, Advisory Editor, Sandhu, Kamalpreet, editor, Singh, Sunpreet, editor, Prakash, Chander, editor, Sharma, Neeta Raj, editor, and Subburaj, Karupppasamy, editor

Published
2022
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21. Fuzzy Cognitive Map-Based Genetic Algorithm for Community Detection

Author

Haritha, K., Judy, M. V., 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, Panigrahi, Chhabi Rani, editor, Pati, Bibudhendu, editor, Mohapatra, Prasant, editor, Buyya, Rajkumar, editor, and Li, Kuan-Ching, editor

Published
2021
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26. Silanized aluminum trihydroxide as a green filler for improvement in tire performance

Author

Ameta, Rohit, Haritha, K., Ramakrishnan, S., Amarnath, S.K.P., Lorenzetti, Daniele, and Mohamed, P.K.

Subjects
Butadiene, Tire industry, Business, Chemicals, plastics and rubber industries
Abstract

A wide variety of rubber compositions is used in the tire industry. The base elastomers that are commonly used consist of blends of natural rubber (NR), butadiene rubber (BR) and [...]

Published
2022

44. A novel neural network model with distributed evolutionary approach for big data classification.

Author

Haritha, K, Shailesh, S, Judy, MV, Ravichandran, KS, Krishankumar, R, Gandomi, AH, Haritha, K, Shailesh, S, Judy, MV, Ravichandran, KS, Krishankumar, R, and Gandomi, AH

Abstract

The considerable improvement of technology produced for various applications has resulted in a growth in data sizes, such as healthcare data, which is renowned for having a large number of variables and data samples. Artificial neural networks (ANN) have demonstrated adaptability and effectiveness in classification, regression, and function approximation tasks. ANN is used extensively in function approximation, prediction, and classification. Irrespective of the task, ANN learns from the data by adjusting the edge weights to minimize the error between the actual and predicted values. Back Propagation is the most frequent learning technique that is used to learn the weights of ANN. However, this approach is prone to the problem of sluggish convergence, which is especially problematic in the case of Big Data. In this paper, we propose a Distributed Genetic Algorithm based ANN Learning Algorithm for addressing challenges associated with ANN learning for Big data. Genetic Algorithm is one of the well-utilized bio-inspired combinatorial optimization methods. Also, it is possible to parallelize it at multiple stages, and this may be done in an extremely effective manner for the distributed learning process. The proposed model is tested with various datasets to evaluate its realizability and efficiency. The results obtained from the experiments show that after a specific volume of data, the proposed learning method outperformed the traditional methods in terms of convergence time and accuracy. The proposed model outperformed the traditional model by almost 80% improvement in computational time.

Published
2023

45. Chemical stabilization of clay fly ash mixture.

Author

Swetha, G., Bhavitha, B., Namratha, D., Haritha, K., and Chandana, T.

Subjects
FLY ash, SHEAR strength, CLAY soils, SOIL particles, CLAY
Abstract

In nature, clayey soils are often costly. Because of its low shear strength, construction of any structure or pavement on such soils causes settling and functional failure. There are a variety of methods for stabilizing clayey soils, but mechanical and chemical stabilization play a key part in increasing their strength qualities. As a result, the clay soil is combined with Fly ash, and NaOH is added as a stabilizer to improve shear strength. Alkali activates fly ash to produce geopolymer, which increases the link between soil particles and the soil's durability. The goal of this project is to improve compressive strength and consequently shear strength by mixing ten percent fly ash with eight percent, ten percent, and twelve percent by weight of sodium hydroxide (NaOH) with normalities of two and four. For 0, 7, 14, and 28 days, the findings of unconfined compressive strength (UCS) are monitored and compared. We found from the laboratory study that increasing the proportion of NaOH causes an increase in MDD and UCS. This is attained at a concentration of 8-10% NaOH, but by increasing the concentration to 10-12% NaOH, the MDD and UCS were reduced. As a result of the findings, the soil has been stabilized, and 4N has gained increased strength at an 8% NaOH concentration. When the percentage of NaOH is greater than 8, the strength is reduced. [ABSTRACT FROM AUTHOR]

Published
2023
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