Business Performance and Social Media Adoption- An Influence Check by using PLS-SEM DOI

Kriti Bedi

Published: Dec. 8, 2023

This study examines how Indian service-oriented enterprises utilize social media differently and it impacts their profitability. Quantitative research uses online forms to collect data. It was done this way. Individual-level structural equation modeling (PLS-SEM) used test the hypothesis on acquired The suggests that firms applications may affect performance compared other ways. study's findings can help media-using businesses function more smoothly. Business operations be improved using knowledge.

Language: Английский

Integration of Solar Photovoltaic with Modular Multiport Converter Using a Pi Controller Optimized Through Hybrid Osprey Optimization Algorithm and Relational Bi-Level Aggregation Graph Network DOI
Srinivasa Rao Balasani, T. Santhana Krishnan, P.V.N. Prasad

et al.

International Journal of Computational Intelligence and Applications, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 12, 2025

The integration of solar photovoltaic (SPV) systems with modular multiport converters (MMPC) enables efficient energy conversion and distribution, enhancing the overall performance reliability renewable (RES). However, complexity control algorithms potential issues related to dynamic response can pose challenges in achieving optimal stability varying operating conditions. This paper proposes a hybrid method for integrating SPV MMPC achieve power management modern grids. proposed is combined execution Osprey Optimization Algorithm (OOA) Relational Bi-level Aggregation Graph Convolutional Network (RBAGCN). Hence it named as OOA-RBAGCN technique. aim ensure transfer, minimize total harmonic distortion (THD), maintain voltage under conditions, ultimately improve efficiency, reliability, SPV-based RES within smart grid applications. OOA used optimize parameter proportional-integral (PI) controller. RBAGCN predict these optimized parameters. By then, approach on MATLAB platform compared other approaches such Starling Murmuration (SMO), Dung Beetle Optimizer (DBO), Improved Harris Hawks (IHHO), Grey Wolf (GWO), Particle Swarm (PSO). achieves high efficiency 98.1%, reduced THD 2.9% significantly surpassing all existing methods.

Language: Английский

Citations

0
Innovative Integration of Machine Learning Predictive Models Within Blockchain Frameworks for Supply Chain Fault Tolerance DOI

Jatinder Kaur,

Maher Ali Rusho,

Kottala Sri Yogi

et al.

Communications in computer and information science, Journal Year: 2025, Volume and Issue: unknown, P. 158 - 171

Published: Jan. 1, 2025

Language: Английский

Citations

0
Machine Learning-Driven Anomaly Detection in Blockchain Transactions for High-Security Digital Banking DOI
A. Sen, Pramod Kumar,

Mansi Jitendra Dave

et al.

Communications in computer and information science, Journal Year: 2025, Volume and Issue: unknown, P. 143 - 157

Published: Jan. 1, 2025

Language: Английский

Citations

0
Blockchain and Machine Learning for Predictive Policing and Crime Pattern Analysis DOI

Shashi Prakash Dwivedi,

Modi Himabindu,

V. Revathi

et al.

2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT), Journal Year: 2024, Volume and Issue: 2, P. 231 - 235

Published: April 6, 2024

Crime pattern analysis and other forms of predictive policing are becoming indispensable tools for today's police forces. Hybrid Blockchain-Machine Learning Predictive Policing (HBL-PP) is a new method introduced by this study that aims to transform the sector bringing together best features blockchain technology machine learning algorithms. SecureCrimeChain guarantees safe handling crime-related data, while Convolutional Neural Networks (CNNs) Recurrent (RNNs) used advanced crime in HBL-PP. When compared conventional approaches, HBL-PP performs much better experimental evaluations. degree accuracy, precision, recall, F1 score, outperforming techniques. DeepCrimeNet has comparable performance comes close second. FairPredict Pro, although fairness-aware, maintains balance between equity prediction accuracy.

Language: Английский

Citations

1
A Comparative Analysis of Cuk, SEPIC, and Zeta Converters as Maximum Power Point Trackers DOI
Slimane Hadji,

Abdelhakim Belkaïd,

Korhan Kayışlı

et al.

Published: May 27, 2024

Language: Английский

Citations

1
Integrated PV energy generation system with high-gain converter and CHHO-FLC-based MPPT for grid integration DOI

N. Rishikesh,

J. Senthil Kumar

Electrical Engineering, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 21, 2024

Language: Английский

Citations

1
Natural Language Processing to Improve Optimal Customized Treatment in Clinical Decision Support Systems DOI

Sachin Malviya,

Shivendra Dubey,

Dinesh Kumar Verma

et al.

Published: Dec. 8, 2023

Through computational methods and natural language processing, sentiment analysis recognizes classifies the sentiments conveyed by personal statements. The current effort aims to apply entity semantic construct a test case for healthcare system individualized medication. To assess if patient's response cure, service, therapy, etc., is positive, negative, or neutral pharmaceutical data used. After more thorough investigation of patient surveys an excellent diagnostic decision system, gathered orientations were compared. classify contrast, polarity based on machine learning are also applied. Support vector machines (SVM), random forest classification, linear SVC, multinomial NB most used analytic Sklearn techniques. It has been discovered that SVM method achieves better accuracy than other algorithms.

Language: Английский

Citations

1
Machine Learning-Driven Blockchain for Enhanced Transparency in Government Public Records DOI
Sorabh Lakhanpal,

CH Vijendar Reddy,

Uma Reddy

et al.

2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT), Journal Year: 2024, Volume and Issue: 10, P. 698 - 703

Published: April 6, 2024

With more things done online, citizens have never wanted government data to be available and dependable. This paper proposes a solution using blockchain powerful algorithms. The recommended approach uses blockchain's immutability safety, machine learning discover outliers, NLP organize data. coordinated strategy automates opens records increase quality, accessibility, speed. Several tests performance assessments compared the traditional record-keeping method. Finding anomalies is faster anomaly detection natural language processing record sorting. ensures accuracy clarity in real time. Spreading keeps documents secure unchangeable. makes changing difficult for those who shouldn't. study found that proposed might improve public management. It improves transparency, crucial trait responsible leadership, powerful, safe, automated way technology cutting-edge

Language: Английский

Citations

0
Blockchain and Machine Learning for Intelligent Traffic Management Systems in Urban Planning DOI
Vijilius Helena Raj,

Y Manohar Reddy,

Pushpendra Singh Danghi

et al.

2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT), Journal Year: 2024, Volume and Issue: 97, P. 225 - 230

Published: April 6, 2024

Managing traffic and urban development in today's densely populated cities is becoming more difficult. Fortunately, there hope the form of a novel approach to problem solving: combination blockchain machine learning. This article delves at potential combining technology with learning for use Smart City Intelligent Traffic Management Systems (ITMS). With technology, data can be managed safely openly, allowing authenticated, near-real-time monitoring data. Thus, accuracy management improved, possibility manipulation reduced. Algorithms enable analysis predictive analytics. Large-scale optimize patterns improve mobility. examines how may complement each other. study benefits two technologies their strengthens IT systems. The research also possible issues holistic approach. innovative quality life by improving security, forecast accuracy, planning efficiency.

Language: Английский

Citations

0
The Role of Machine Learning in Optimizing Radar Signal Analysis DOI
Sorabh Lakhanpal,

S Aswini,

Rakesh Chandrashekar

et al.

2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT), Journal Year: 2024, Volume and Issue: 4, P. 748 - 753

Published: April 6, 2024

A paradigm change in the way humans analyze and understand complicated data has been made possible by incorporation of machine learning (ML) methods into field radar signal analysis. This research delves wide range uses for ML improving processing, from military to weather service. The purpose is assess efficiency adaptability approaches, including classic algorithms a suggested Adaptive SignalNet Optimization methodology. technique was compared against industry standards like Convolutional Neural Networks (CNN) Support Vector Machines (SVM) controlled testing environment. effectiveness various approaches evaluated using datasets signals that were meant be representative real-world conditions. results show relevance temporal grouping adaptive anomaly identification boosting accuracy responsiveness processing. not only outperformed state-of-the-art, but also demonstrated kind resilience essential real-time applications, where making right decision at moment utmost importance.

Language: Английский

Citations

0