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2. Revolutionizing Agriculture: A Mobile App for Rapid Plant Disease Prediction and Sustainable Food Security

Author

Kiran, Pasupuleti Sai, Reddy, B. Tirapathi, Dinesh, T., Harsha, V. Sri, Harini, S., Mohammad, S. K. Noor, 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, E. Balas, Valentina, editor, Prakash, Kolla Bhanu, editor, and Varma, G. P. Saradhi, editor

Published
2024
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3. Automatic Screw Jack Mobile Controller for Car Lifting Using the Car Battery

Author

Paul, P. Mano, Thomas, Aby K., Hashim, Syed Alay, Harsha, K. Sri, Mahesh, M., Goutham, Prince, 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, Tan, Kay Chen, Series Editor, Chakravarthy, V. V. S. S. S, editor, Bhateja, Vikrant, editor, Anguera, Jaume, editor, Urooj, Shabana, editor, and Ghosh, Anumoy, editor

Published
2024
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4. Evaluating the Suitability of Groundwater for Irrigational Purposes Using Electrical Resistivity Technique and the Implementation of Artificial Recharge at Kalugotla (V), Veldurthy (M), Kurnool District, Andhra Pradesh

Author

Harsha, G. Sri, Rao, G. Subba, Jeelani, Syed Hamim, Naresh, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Vinod Chandra Menon, N., editor, Kolathayar, Sreevalsa, editor, and Sreekeshava, K. S., editor

Published
2024
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5. Glaucoma Stage Classification Using Image Empirical Mode Decomposition (IEMD) and Deep Learning from Fundus Images

Author

Shankar, D., Harsha, I. Sri, Madhuri, P. Shyamala, Naidu, J. N. S. S. Janardhana, Madhuri, P. Krishna, Cherukuvada, Srikanth, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin, Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Pareek, Prakash, editor, Gupta, Nishu, editor, and Reis, M. J. C. S., editor

Published
2024
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8. Implementation of Automatic Detection of Text from Complex Images and Converting to Semantic Speech

Author

Santoshi, Gorli, Srinivas, Y., Harsha, Mullapudi Sri, 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, Mahapatra, Rajendra Prasad, editor, Peddoju, Sateesh Kumar, editor, Roy, Sudip, editor, Parwekar, Pritee, editor, and Goel, Lavika, editor

Published
2022
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15. Liquefaction Assessment of Gulf of Kutch Offshore Soils Using CPTU Data

Author

Harsha Gamidi, Sri, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Satyanarayana Reddy, C. N. V., editor, Saride, Sireesh, editor, and Haldar, Sumanta, editor

Published
2021
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17. Unravelling Complexity: Investigating the Effectiveness of SHAP Algorithm for Improving Explainability in Network Intrusion System Across Machine and Deep Learning Models.

Author

Vaswani, Lakshya, Harsha, Sai Sri, Jaiswal, Subham, and D., Aju

Subjects
ARTIFICIAL neural networks, MACHINE learning, DEEP learning, DISTRIBUTED computing, FEATURE selection, INTRUSION detection systems (Computer security)
Abstract

According to several studies, it is feasible to significantly raise the detection engine's effectiveness and accuracy by choosing the right features for a threat detection system. New advances like Distributed Computing and Enormous Information have expanded network traffic, and the danger identification framework must proactively gain and dissect the information delivered by the approaching traffic. Nonetheless, not all elements in an enormous dataset help to portray the traffic, therefore restricting and picking few reasonable highlights might accelerate and improve the danger discovery framework's exactness. Deep neural networks enhance the detection rates of intrusion detection models, making machine learning-based intrusion detection systems (IDS's) useful recently. Consumers, however, find it more and more challenging to comprehend the reasoning behind their selections as models become more complex accuracy. Using relevant features from the NSL-KDD dataset, we apply appropriate feature selection mechanisms to implement an intrusion detection system to implement a faster system with increased accuracy. We use Explainable Model (SHAP) to interpret the results of IDS. The interpretation of findings utilizing the Explainable Model (SHAP) for machine learning (ML) and deep learning (DL) models heavily depends on its efficiency. While DL models require more resources, ML models are computationally efficient. Both models, however, gain from SHAP interpretations, which offer perceptions into the significance of features and contributions to predictions. While DL models excel in accuracy, ML models offer efficiency. The decision is based on the particular needs and resources that are available, with SHAP offering greater knowledge of model behavior and feature impact. [ABSTRACT FROM AUTHOR]

Published
2024
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22. Improving the Performance of LiNi0.9Co0.05Mn0.05O2 via Atomic Layer Deposition of ZnxOy Coating.

Author

Blanga, Shalev, Harsha Akella, Sri, Tsubery, Merav, Zysler, Melina, Taragin, Sarah, and Noked, Malachi

Subjects
ATOMIC layer deposition, ENERGY storage, LITHIUM-ion battery manufacturing, MASS spectrometry, ENERGY density
Abstract

Nickel‐rich cathode materials such as LiNi0.9Co0.05Mn0.05O2 (NMC90) have gained attention due to their ability to deliver high energy densities while being cost‐effective for Lithium‐ion battery manufacturing. However, NMC90 cathodes suffer irreversible parasitic reactions such as electrolyte decomposition, severe capacity fading and impedance build‐up upon prolonged cycling. Herein, we synthesize a conformal ultrathin, surface protection layer on NMC90 powder using ZnxOyvia atomic layer deposition technique (ZnxOy@NMC90). Prolonged electrochemical investigation of full cells at high discharge rates of 2 C shows that ZnxOy@NMC90 cells yielded ~31 % improvement in discharge capacity compared to pristine NMC90. Furthermore, operando electrochemical mass spectroscopy studies show that the ZnxOy@NMC90 cells have significantly suppressed electrolyte decomposition as compared to pristine NMC90 cells. Post‐cycling electrochemical impedance spectroscopy studies show that the ZnxOy@NMC90 full cells have significantly reduced impedance compared with pristine NMC90 cells. Additionally, post cycling manganese dissolution studies show that ZnxOy@NMC90 cells have greatly enhanced chemo‐mechanical integrity thereby contributing to improved electrochemical performances. Our results underscore the potential of tailored ZnxOy surface coatings on nickel‐rich cathode materials to address critical challenges in advanced energy storage systems, offering promising prospects for the development of high‐energy‐density lithium‐ion batteries. [ABSTRACT FROM AUTHOR]

Published
2024
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30. Hybrid machine learning approach for trust evaluation to secure MANET from routing attacks.

Author

Meenakshi, K., Revathi, M., Harsha, Sanda Sri, Tamilarasi, K., Shanthi, T.S., Sugumar, D., Suriyakrishnaan, K., Uma Maheswari, B., and Rajaram, A.

Subjects
MACHINE learning, ENERGY consumption, AD hoc computer networks
Abstract

A new era in communication has been ushered in by MANET networks, in which users (nodes) interact with one another through a self-configuring network of handheld devices linked by wireless links. Nodes are capable of participating and enthusiastic about sending packets to other nodes. Consequently, the need for a routing protocol materializes. The most difficult aspect is dealing with the network's dynamic topology as a result of node mobility. This is because limited resources like storage space, battery life, and bandwidth require a protocol that can quickly adapt to topology changes while periodically updating messages. On the other hand, security is another important aspect of routing since the involvement of attackers will exhaust the network resources. This paper addresses the main issue of designing a routing protocol that handles all the adversaries and achieves better efficiency. For that, we proposed a Hybrid Machine Learning (HyML) model which evaluates the. Initially, the network is segregated by the Secure Stable Clustering (SSC) approach which first verifies the node's legacy and forms clusters based on stability. The HyML is designed by combining two important ML techniques such as ANN and fuzzy-C Means (FCM) algorithm. The ANN model learns multiple attributes of the trust value and computes the cumulative trust score. Next, FCM determines the node position upon trust score. After the computation of the trust value, optimal route selection is performed by the Spider Monkey Optimization (SMO) technique. The overall work is evaluated through comprehensive simulations based on network longevity, throughput, energy usage, PDR, attack detection efficiency, and delay. [ABSTRACT FROM AUTHOR]

Published
2024
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31. INTUBATING CONDITIONS AND CLINICAL ASSESSMENT OF CARDIOVASCULAR EFFECTS BY ANAESTHETIC DRUGS.

Author

Patel, Pushpraj, Jain, Anivesh, Harsha, Onteddu Sri, Mishra, Anjeney, Patel, Akhilesh, and Patel, Kaveri Shaw

Subjects
PHARMACODYNAMICS, VOCAL cords, MUSCLE relaxants, TRACHEA intubation, NEUROMUSCULAR blockade, ENDOTRACHEAL suctioning, PREMEDICATION
Abstract

Background: Endotracheal intubation requires the use of medications that are safer than suxamethonium and have the following benefits: early onset, extended duration, steady hemodynamic parameter, minimal adverse effects, and favourable intubating circumstances are necessary to achieve muscle relaxation. Aim: The purpose of this study was to compare the intubating circumstances and cardiovascular effects of rocuronium to those of vecuronium and suxamethonium. Methods: Based on the muscle relaxant used during intubation--Group I received 0.6 mg/kg rocuronium, Group II received 1.5 mg/kg suxamethonium, and Group III received 0.08 mg/kg vecuronium--a total of 120 participants were randomly assigned to 3 groups, each consisting of 40 subjects. 0.2 mg of glycopyrrolate was administered as a premedication, and 4-5 mg/kg of thiopentone sodium 2.5% was utilised as an anaesthetic agent. Vecuronium was also injected intermittently. Fasciculations, cardiovascular reaction, limb movement, coughing, vocal cord movement and position, jaw relaxation, and apnea start were among the parameters evaluated. Results: Group I saw a longer onset than Group II, but a lower one than Group III. Group II had fasciculation while Group I and III did not. Group III had better intubating circumstances. No subject from any group had any complications. Conclusion: The current investigation suggests that, in situations of tracheal intubation involving people who do not require a quick spontaneous breathing return, rocuronium is a safe and effective substitute for suxamethonium. As a result, it can serve as a bridge between suxamethonium and non-depolarizing neuromuscular blocking drugs, making it the perfect neuromuscular agent. [ABSTRACT FROM AUTHOR]

Published
2024

33. Mining knowledge for NP-complete scheduling problems.

Author

Harsha, A. Sri, Kumar, P. Vijaya, Nagaraju, Arumalla, Babu, K. Prakash, Medikondu, N. R., and Dharmendra, B. V.

Subjects
*NP-complete problems, *TARDINESS, *CLOUD computing, *RESEARCH personnel, *TASK performance, *HEURISTIC algorithms
Abstract

In this paper for executing and assigning different tasks heuristic algorithm is proposed. It minimizes the mean tardiness (lateness of due date) with utilizing maximum resources. Performance of algorithm evaluated with three examples with 40 number of tasks and processors Cloud computing is the most popular technology to improve system performance with efficient task scheduling algorithm. To perform multiple goals in task scheduling it is an important way to arrange customer needs with an order. Many papers attempted various areas like allocation of possessions, protection, seclusion and scheduling. Execution time, Execution cost, memory and resources are main areas focused by existing researchers. In this work for executing and assigning different tasks heuristic algorithm is proposed. It minimizes the mean tardiness (lateness of due date) with utilizing maximum resources. Performance of algorithm evaluated with three examples with 120 number of tasks and processors. [ABSTRACT FROM AUTHOR]

Published
2023
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34. Data mining application in task scheduling system.

Author

Harsha, A. Sri, Arshad, Mohammad, Sankara Rao, V., Babu, K. Prakash, Medikondu, N. R., and Dharmendra, B. V.

Subjects
*TRAVEL time (Traffic engineering), *DATA mining, *SCHEDULING, *TARDINESS, *CLOUD computing, *HEURISTIC algorithms
Abstract

To perform multiple goals in task scheduling it is an important way to arrange customer needs with an order. Many papers attempted various areas like allocation of possessions, protection, seclusion and scheduling. Execution time, Execution cost, memory and resources are main areas focused by existing researchers. In this paper for executing and assigning different tasks heuristic algorithm is proposed. It minimizes the mean tardiness (lateness of due date) with utilizing maximum resources. Performance of algorithm evaluated with three examples with 40 number of tasks and processors Cloud computing is the most popular technology to improve system performance with efficient task scheduling algorithm. In this work for executing and assigning different tasks heuristic algorithm is proposed. It minimizes the mean flow time with utilizing maximum resources with existing process time and travel time. [ABSTRACT FROM AUTHOR]

Published
2023
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35. Soft computing techniques for task scheduling.

Author

Farokhi, Md. K. M., Medikondu, N. R., Chalapathi, P. V., Harsha, A. Sri, Kumar, P. Vijaya, and Dharmendra, B. V.

Subjects
SOFT computing, TRAVEL time (Traffic engineering), HEURISTIC algorithms, SCHEDULING, RESEARCH personnel
Abstract

Cloud computing is the most popular technology to improve system performance with efficient task scheduling algorithm. To perform multiple goals in task scheduling it is an important way to arrange customer needs with an order. Many papers attempted various areas like allocation of possessions, protection, seclusion and scheduling. Execution time, Execution cost, memory and resources are main areas focused by existing researchers. In this work for executing and assigning different tasks heuristic algorithm is proposed. It minimizes the both completion time and execution time with utilizing maximum resources. Performance of algorithm evaluated with three examples with 40 number of tasks and processors with given process time and travel time. [ABSTRACT FROM AUTHOR]

Published
2023
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36. Data mining-based prediction for operational completion time and mean flow time.

Author

Medikondu, N. R., Prasad, Kona Ram, Meduri, Olive, Babu, K. Prakash, Harsha, A. Sri, and Dharmendra, B. V.

Subjects
TRAVEL time (Traffic engineering), HEURISTIC algorithms, NUMBER systems, CLOUD computing, MULTICASTING (Computer networks), RESEARCH personnel
Abstract

Performance of algorithm evaluated with examples with 40 number of tasks and processors cloud computing is the most popular technology to improve system performance with efficient task scheduling algorithm. Execution time, Execution cost, memory and resources are main areas focused by existing researchers. In this work for executing and assigning different tasks heuristic algorithm is proposed. It minimizes the number of operations in the system with utilizing maximum resources with given process time and travel time. To perform multiple goals in task scheduling it is an important way to arrange customer needs with an order. Many papers attempted various areas like allocation of possessions, protection, seclusion and scheduling. [ABSTRACT FROM AUTHOR]

Published
2023
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37. A data mining based heuristic algorithm implementation for intelligence system.

Author

Medikondu, N. R., Meduri, Olive, Babu, K. Prakash, Prasad, Kona Ram, Harsha, A. Sri, and Dharmendra, B. V.

Subjects
HEURISTIC algorithms, DATA mining, TRAVEL time (Traffic engineering), RESEARCH personnel, CLOUD computing, PARALLEL algorithms
Abstract

Performance of algorithm evaluated with three examples with 40 number of tasks and processors with considering half of the travel time and triple the process time. Many papers attempted various areas like allocation of possessions, protection, seclusion and scheduling. Execution time, Execution cost, memory and resources are main areas focused by existing researchers. Cloud computing is the most popular technology to improve system performance with efficient task scheduling algorithm. To perform multiple goals in task scheduling it is an important way to arrange customer needs with an order. Many papers attempted various areas like allocation of possessions, protection, seclusion and scheduling. Execution time, Execution cost, memory and resources are main areas focused by existing researchers. In this work for executing and assigning different tasks heuristic algorithm is proposed. It minimizes mean flow time and execution time with utilizing maximum resources. [ABSTRACT FROM AUTHOR]

Published
2023
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38. Improve the performance of complex system through artificial intelligence.

Author

Medikondu, N. R., Sankara Rao, V., Gandepudi, Jaya Raju, Babu, K. Prakash, Harsha, A. Sri, and Dharmendra, B. V.

Subjects
ARTIFICIAL intelligence, TARDINESS, CLOUD computing, RESEARCH personnel, TASK performance, HEURISTIC algorithms
Abstract

In this paper for executing and assigning different tasks heuristic algorithm is proposed. It minimizes the mean tardiness (lateness of due date) with utilizing maximum resources. Performance of algorithm evaluated with three examples with 40 number of tasks and processors Cloud computing is the most popular technology to improve system performance with efficient task scheduling algorithm. To perform multiple goals in task scheduling it is an important way to arrange customer needs with an order. Many papers attempted various areas like allocation of possessions, protection, seclusion and scheduling. Execution time, Execution cost, memory and resources are main areas focused by existing researchers. In this work for executing and assigning different tasks heuristic algorithm is proposed. It minimizes the mean tardiness (lateness of due date) with utilizing maximum resources. Performance of algorithm evaluated with three examples with 120 number of tasks and processors. [ABSTRACT FROM AUTHOR]

Published
2023
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39. Design and development of expert system through artificial intelligence.

Author

Jitendra, G., Kumar, O. N. V. P. Bhagavan, Prasad, G. Durga, Medikondu, N. R., Harsha, A. Sri, and Dharmendra, B. V.

Subjects
ARTIFICIAL intelligence, TRAVEL time (Traffic engineering), SYSTEMS development, EXPERT systems, HEURISTIC algorithms, TARDINESS
Abstract

Performance of algorithm evaluated with examples with 40 number of tasks and processors Cloud computing is the most popular technology to improve system performance with efficient task scheduling algorithm. To perform multiple goals in task scheduling it is an important way to arrange customer needs with an order. Many papers attempted various areas like allocation of possessions, protection, seclusion and scheduling. Execution time, Execution cost, memory and resources are main areas focused by existing researchers. In this work for executing and assigning different tasks heuristic algorithm is proposed. It minimizes the mean tardiness (lateness of due date) with utilizing maximum resources with double the process time and half of the travel time. [ABSTRACT FROM AUTHOR]

Published
2023
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40. Application of artificial intelligence in automation.

Author

Kumar, O. N. V. P. Bhagavan, Jitendra, G., Prasad, G. Durga, Medikondu, N. R., Harsha, A. Sri, and Dharmendra, B. V.

Subjects
ARTIFICIAL intelligence, HEURISTIC algorithms, AUTOMATION, TARDINESS, RESEARCH personnel
Abstract

In this work for executing and assigning different tasks heuristic algorithm is proposed. It minimizes mean tardiness (lateness of due date) with utilizing maximum resources. Cloud computing is the most popular technology to improve system performance with efficient task scheduling algorithm. To perform multiple goals in task scheduling it is an important way to arrange customer needs with an order. Many papers attempted various areas like allocation of possessions, protection, seclusion and scheduling. Execution time, Execution cost, memory and resources are main areas focused by existing researchers. In this work for executing and assigning different tasks heuristic algorithm is proposed. It minimizes the both completion time and execution time with utilizing maximum resources. Performance of algorithm evaluated with three examples with 40 number of tasks and processors. [ABSTRACT FROM AUTHOR]

Published
2023
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41. Implementation of beam search algorithm for expert system.

Author

Medikondu, N. R., Bindu, N. Madhu, Kumar, P. Vijaya, Shaik, Kareemulla, Harsha, A. Sri, and Dharmendra, B. V.

Subjects
SEARCH algorithms, TRAVEL time (Traffic engineering), HEURISTIC algorithms, RESEARCH personnel, CLOUD computing, EXPERT systems
Abstract

Many papers attempted various areas like allocation of possessions, protection, seclusion and scheduling. Execution time, Execution cost, memory and resources are main areas focused by existing researchers. Cloud computing is the most popular technology to improve system performance with efficient task scheduling algorithm. To perform multiple goals in task scheduling it is an important way to arrange customer needs with an order. Many papers attempted various areas like allocation of possessions, protection, seclusion and scheduling. Execution time, Execution cost, memory and resources are main areas focused by existing researchers. In this work for executing and assigning different tasks heuristic algorithm is proposed. It minimizes the both completion time and execution time with utilizing maximum resources. Performance of algorithm evaluated with three examples with 40 number of tasks and processors with considering half of the travel time and triple the process time [ABSTRACT FROM AUTHOR]

Published
2023
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42. Artificial intelligence technique for industry 4.0.

Author

Farokhi, Md. K. M., Chalapathi, P. V., Medikondu, N. R., Kumar, P. Vijaya, Harsha, A. Sri, and Dharmendra, B. V.

Subjects
ARTIFICIAL intelligence, INDUSTRY 4.0, TRAVEL time (Traffic engineering), HEURISTIC algorithms, RESEARCH personnel
Abstract

To perform multiple goals in task scheduling it is an important way to arrange customer needs with an order. Cloud computing is the most popular technology to improve system performance with efficient task scheduling algorithm. Many papers attempted various areas like allocation of possessions, protection, seclusion and scheduling. Execution time, Execution cost, memory and resources are main areas focused by existing researchers. In this work for executing and assigning different tasks heuristic algorithm is proposed. It minimizes the both completion time and execution time with utilizing maximum resources. Performance of algorithm evaluated with three examples with 40 number of tasks and processors with half of the travel time and double of the process time. [ABSTRACT FROM AUTHOR]

Published
2023
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45. In-Hospital cardiac arrest complicating ST-elevation myocardial Infarction: Temporal trends and outcomes based on management strategy

Author

Bhat, Anusha G, primary, Verghese, Dhiran, additional, Harsha Patlolla, Sri, additional, Truesdell, Alexander G, additional, Batchelor, Wayne B, additional, Henry, Timothy D, additional, Cubeddu, Robert J, additional, Budoff, Matthew, additional, Bui, Quang, additional, Matthew Belford, Peter, additional, X Zhao, David, additional, and Vallabhajosyula, Saraschandra, additional

Published
2023
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