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Credit Card Fraud Detection(CFD) using GNN and ensemble Techniques 3

Credit Card Fraud Detection(CFD) using GNN and Ensemble Tech...

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3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Vinay, B.V.S.N.S. Radha, D. Kirthika Devi, V.S. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidhyapeetham Bengaluru India Department of Electrical and Electronics Engineering Amrita School of Engineering Amrita Vishwa Vidhyapeetham Bengaluru India

ISBN: (纸本)9798331527549

Credit card fraud is an essential problem in the economic industry;thus, its detection is solved with the help of the developed methods in order to minimize the overall loses and to improve the confidence of clients. Towards this end, this paper presents a novel framework that applies GNNs in combination with ensemble learning to accurately identify credit card fraud. GNNs are used for cardinality, representing various relationships between transactions, cardholders, and merchants where complicated types of forgery are identified and are beyond the capability of conventional approaches. ensemble learning further improves the accuracy of the system in order to reduce high false positive rates by using multiple models to solve the problem of imbalanced classes that are characteristic of the COVID-19 data. The effectiveness of the proposed framework is thus compared with several state-of-the-art malicious account detection techniques and various highly relevant real credit card transaction datasets show the proposed framework attains better precision, recall, F1-score, scalability. Thus, this strategy is much more suitable for ongoing and unspecific problem addressing in an unobstructed and ambiguous environment, such as credit card fraud. © 2025 ieee.

关键词： Crime

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Forecasting Bitcoin Price Trends: Integrated Machine Learning with Market Trends 3

Forecasting Bitcoin Price Trends: Integrated Machine Learnin...

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3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Samir Ahamed, S. Radha, D. Kirthika Devi, V.S. Department of Computer Science And Engineering Amrita school of computing Amrita Vishwa Vidhyapeetham Bengaluru India Department of Electrical and Electronics Engineering Amrita school of Engineering Amrita Vishwa Vidhyapeetham Bengaluru India

ISBN: (纸本)9798331527549

Bitcoin price prediction remains a complicated task in financial markets since price fluctuations are characterized by high variability, non-linear and dependent on different trends. The common models of forecasting can be disruptive because they do not readily accommodate the breadth of the data and the dynamics of the marketplace. The paper presents a new approach to predicting Bitcoin price shifts based on state-of-the-art data structures and both machine learning and technical analysis. The formative historical price datasets and large scale features are organized and manipulated in an efficient manner with the aid of data structures as well as the temporal and non-linear trends in prices are captured by ARIMA,exponential smoothing and Random. Also, trends of moving averages are used to boost the model’s competency to analyze the sentiments of the market. The proposed framework was put through a test on real world Bitcoin price data and it was shown to provide better results as compared to the traditional methods with better accuracy and visualization. Besides that, our method enhances the accuracy of the forecast, while the deployment of the method allows developing a realtime Bitcoin price prediction model that can be useful for traders and investors. The integration of machine learning and technical analysis gives a powerful and reliable tool to forecast the Bitcoins price trends. © 2025 ieee.

关键词： Prediction models

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Securing Wireless Communication: A Comprehensive Arduino-based Approach 3

Securing Wireless Communication: A Comprehensive Arduino-bas...

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3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Navaneeth, M. Vamsi Krishna, K. Belwal, Meena Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

This research aims at developing Arduino solutions to improve the security of wireless communication systems for this work and to present a broad intervention plan for achieving this aim. Incorporating the features of Arduino microcontrollers the system has the potential of mitigating some of the weak wireless communications paradigms. The methodology consists in applying the use of such measures as the encryption algorithms and authentication and the use of secure data transmission protocols. The approach, proposed, not only enhances the security of wireless communication but also is cost effective and easy to install. In this respect, it is hoped that the outcomes of the project will offer effective and efficient solutions for implementing quality security elements for wireless transmission with practical and experimental *** purpose of this work is to generate and transmit the text message through a wireless communication system in a secured way. This facility prevails in the mobile network for which the user pays for it, whereas the system designed here can be used as personal communication system and information can be transmitted at free of *** result of the work is expected to be a secure information transmission with wireless technology implemented and encrypt the data that need to be transmitted without letting interception of a third party and reach the destination, convert and decrypt the message into readable *** work more particularly targets at reducing some of the risks associated with present wireless communication systems through use of effective encryption and authentication. The results are expected to include a major decrease in the interception risks, as well as the effective and safe text message transmission with real-world evidence as proof. © 2025 ieee.

关键词： Microcontrollers

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Accurate Identification and Location Technology of Fault Types based on Multi-Dimensional Feature Fusion Analysis Algorithm 3

Accurate Identification and Location Technology of Fault Typ...

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3rd international conference on Integrated Circuits and Communication Systems, ICICACS 2025

作者： Zhou, Kun Zheng, Youzhuo Yan, Jiangfeng Gu, Jian Zhou, Qi Power Grid Corporation Bijie Power Supply Bureau of Guizhou Guizhou Bijie China

ISBN: (纸本)9798331508456

With increasing complexity in industrial equipment operations, conventional single-feature diagnostic methods struggle to detect anomalies promptly under dynamic conditions. This study introduces an intelligent fault identification framework using Multi-Dimensional Feature Fusion Analysis. First, vibration, temperature, and pressure signals undergo wavelet threshold denoising with rigrsure-optimized thresholds to extract transient features. Next, a Gaussian Mixture Model (GMM) clusters these features through expectation-maximization iterations, resolving nonlinear correlations while mitigating overfitting risks. Finally, a Convolutional Neural Network (CNN) with spatial attention mechanisms fuses multi-source features hierarchically, enabling simultaneous fault classification and heatmap-based localization. experimental validation on NASA's CMAPSS dataset demonstrates significant improvements: the proposed method achieves 90.2% average accuracy across five fault types, outperforming Random Forest by 12.3%. CNN-based heatmaps localize fault origins with 92% spatial resolution accuracy, proving 15.6% superior to traditional spectral analysis in handling concurrent failure modes. These results confirm GMM-guided feature fusion effectively addresses generalization limitations in complex industrial scenarios. © 2025 ieee.

关键词： Diagnostic products

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Agricultural Water Conservation through AI-enhanced Solar IoT Networks 3

Agricultural Water Conservation through AI-Enhanced Solar Io...

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3rd international conference on electronics and Renewable Systems, ICeARS 2025

作者： Maniraj, S.P. Monisha, J. Amutha, R. Kavitha, R. Shriidhar, P.J. Srinivasan, C. Srm Institute of Science and Technology School of Computing Department of Data Science and Business Systems Kattankulathur Tamilnadu Chennai India Tamil Nadu Chennai India Ultra College of Engineering and Technology Department of Electrical and Electronics Engineering Tamil Nadu Madurai India Chennai Institute of Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Vinayaka Missions Kirupananda Variyar Engineering College Department of Computer Science and Engineering Tamil Nadu Salem India Saveetha Universityi Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331509675

With the increasing water shortage and climatic uncertainty, creative strategies for effective water management in agriculture are necessary. This research investigates the integration of Artificial Intelligence (AI), particularly Artificial Neural Networks (ANN), with solar-powered Internet of Things (IoT) networks to enhance water utilization in agricultural activities. The proposed system facilitates accurate irrigation scheduling using real-time data from soil moisture sensors, meteorological stations, and crop health monitoring devices. The ANN model analyses this data to predict ideal irrigation schedules and volumes, minimizing water waste while improving crop yields. The solar-powered IoT framework provides sustainability and reduces dependence on traditional energy sources. Field trials indicate that the AI-enhanced system may promote water saving by as much as 30% relative to traditional irrigation techniques. Moreover, using AI enables adaptive learning, enabling the system to enhance its irrigation tactics using historical and real-time data. This novel method conserves water resources and fosters sustainable agriculture practices, coinciding with global initiatives to address water shortages and assure food security. The findings underscore the potential of technology-based solutions to revolutionize agricultural water management for a sustainable future. © 2025 ieee.

关键词： Smart agriculture

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Hybrid Blockchain and IoT Driven Framework for Supply Chain Optimization by enhancing Transparency, efficiency and Cost Reduction 3

Hybrid Blockchain and IoT Driven Framework for Supply Chain ...

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3rd international conference on electronics and Renewable Systems, ICeARS 2025

作者： Pradeep Kumar, S. Basha, C.H. Hussaian Prasath, C. Arun Amirthayogam, G. Lathif, Syed Ismail Abdul Leelavathi, R. Rajalakshmi Engineering College Computer Science Design Department Thandalam Chennai602105 India Sr University Department of Electrical and Electronics Engineering Warangal506371 India Mahendra Engineering College Department of Ece Namakkal637503 India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology School of Computing Department of Computer Science and Engineering Chennai600062 India Srm Institute of Science and Technology Department of Data Science and Business Systems Chennai603203 India Velalar College of Engineering and Technology Department of Biomedical Engineering Erode638012 India

ISBN: (纸本)9798331509675

Blockchain technology represents a modern supply chain management revolution which fixes operational challenges while providing enhanced transparency at reduced costs. The research develops HB-SCOF (Hybrid Blockchain-enabled Supply Chain Optimization Framework) which combines blockchain self-verification databases with automatic smart contracts to maintain continuous supply chain observation and evaluate data credibility. The framework integrates tamper-proof transaction tracking mechanisms with unified supply chain network connectivity for securing data transmission as a trust delivery method through unbreakable shared databases. The retail-industry case study demonstrated a 25% decrease in expenses stemming from agency elimination alongside enhanced flow management and better stock distribution. The system demonstrates its effectiveness through assessments of key performance indicators including transaction speed and data accuracy together with business cost efficiency. This part looks at implementation methods through training stakeholders in addition to transforming organizational policies which produce successful outcomes. Blockchain technology labs verify its capability to enhance supply chain management efficiency while showing realistic deployment methods. © 2025 ieee.

关键词： Smart contract

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Speech Measuring Following Semiconductor Feature for Acoustic using Biodegradable Material 3

Speech Measuring Following Semiconductor Feature for Acousti...

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3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Upadhyay, Shrikant Kumar, Rakesh Kumar, Binod Kumari, Barkha Lakra, Ankita Mandal, Sampurna Department of Electronics and Communication Engineeing MLR Insitute of Technology Hyderabad India Wipro Engineering Edge Hyderabad India Facultyt of CSE & IT Jharkhand Rai University Ranchi India GH Raisoni College of Engineering and Management Pune India Faculty of Computing and IT Usha Martin Univerity Ranchi India Department of Computer Science and Engineering-Artifical Intelligence Brainware University Kolkata India

ISBN: (纸本)9798331527549

This research paper primarily focuses to identify the various feature removal presence used for addresser recognition and validation. The current template i.e. classical and typical are considered to examine its role in different acoustic surroundings and also try to measure feature removal in acoustic condition considering factors like jitters, noise, echo etc. which truly a factor that affect the speech performance and degrades the overall performance of any system. effort has been put to inspect the attainment of various feature removal approach with the help of classifier considering different structures. The behavior of different feature extraction removal simulated using Hindi samples and it will be analysed in terms of efficiency and error rate. The result may be useful for suitable for existing as well as any proposed model by changing its classifiers. Speech of different ages as well groups are used to analysed and implementation using 16-bit TMS 320 C5X semiconductor devices with the feature extraction and algorithm may improve the overall efficiency of the proposed system. Bio-degradable material can also help to reduce the acoustic level at different of speaker identifications. The feature of semiconductor helps to understand and also add the improvements in proper selection of feature extraction that consume less time in evaluating the algorithm and provide better efficiency in different acoustic conditions. Biodegradable material has not used so far in various studies and biodegradable paly a very important role in acoustic condition as we are dealing with acoustic condition and it is very important to take care of acoustic to come up with better efficiency. © 2025 ieee.

关键词： Semiconductor devices

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Advanced Financial Sentiment Analysis using FinBeRT to explore Sentiment Dynamics 3

Advanced Financial Sentiment Analysis using FinBERT to Explo...

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3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Baghavathi Priya, S. Kumar, Madhav Nitheesh Prakash, J.D. Krithika, N. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India

ISBN: (纸本)9798331527549

This research investigates the incorporation of sophisticated Natural Language Processing (NLP) methods in the intricate field of finance. In particular, it utilizes FinBeRT, a tailored language model created to understand the complex subtleties of financial text data, in conjunction with assessments of DistilBeRT and Bidirectional encoder Representations from Transformers (BeRT). The main goal is to create a strong preprocessing framework that improves the interpretative ability of models for sentiment classification designed for financial uses while providing an in-depth evaluation of the comparative performance of the models. Through extensive empirical validation, our approach demonstrates that FinBeRT outperforms the other models in accurately capturing subtle sentiment variations and financial terminology. The comparative study underlines the compromises between computational efficiency and precision, with DistilBeRT providing a streamlined option. This research emphasizes FinBeRT’s transformative capabilities in analyzing financial sentiment and simultaneously delivering essential insights into the comparative strengths and weaknesses of other approaches, presenting a comprehensive viewpoint to inform decision-making within the financial sector. Upon comprehensive analysis of the methods used in this paper, it is shown that FinBeRT is best at capturing hidden features within the data and able to work well with unseen data also with an average accuracy of 89.6% over all the 3 classes that are present in the dataset. The suggested framework has the potential to greatly improve predictive analytics and risk management approaches, allowing for more informed, precise, and prompt financial decisions in intricate market conditions. © 2025 ieee.

关键词： Predictive analytics

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Double Self-Lift (DSL) Cell Based High Gain Modified Quadratic Converter for Fuel Cell Application 3

Double Self-Lift (DSL) Cell Based High Gain Modified Quadrat...

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3rd ieee international conference on Industrial electronics: Developments and Applications, ICIDeA 2025

作者： Behera, Subrat Patel, Ranjeeta Nayak, Byamakesh Abhishek, Amruta Roy, Tapas Guerrero, Josep M. School of Electrical Engineering KIIT Deemed to be University Bhubaneswar India Indian Institute of Science Bengaluru India University of Valladolid Spain

ISBN: (纸本)9798331533205

Fuel Cell(FC) has high energy conversion capacity compared to combustion engines. Fuel cells posses low voltage but are very effective in terms of clean energy sources. For wider range of operation FC needs a suitable gain DC-DC converter applicable for fuel cell electric vehicles. Here a high gain double self-lift (DSL) based DC-DC quadratic boost converter (DSL-QBC) has been proposed. The proposed (DSL-QBC) possesses the benefit of low input current stress and low voltage stress across the switch and high output voltage gain. This property of the converter assists in the synchronization of converter with FC for better output. Double self lift network is an inductor capacitor network which helps in uplifting the voltage gain. Double self lift network is integrated with the simple quadratic boost converter to create a hybrid circuit and the detailed analysis of DSL-QBC has been presented. The modification has been highlighted in the figures shown in paper and the results have been verified using Matlab simulation platform. The proposed circuit topology DSL-QBC has been designed for 150 Watts under steady state condition. © 2025 ieee.

关键词： education computing

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Cultural Intelligence in AI ethics: A Systematic Framework for Implementation Across Global Contexts 3

Cultural Intelligence in AI Ethics: A Systematic Framework f...

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3rd international conference on Intelligent Systems, Advanced computing, and Communication, ISACC 2025

作者： Kumar, Devesh Kumar, Kamlesh Choudhary, Rahul Kumar Singh, Varnika NIT Hamirpur Dept. of Computer Science & Engineering India NIT Hamirpur Dept. of Electrical Engineering India Panjab University UIET Dept. of Electronics & Communication Engineering Chandigarh India

ISBN: (纸本)9798331523893

This research examines artificial intelligence ethics implementation across diverse cultural contexts through case studies in healthcare, finance, education, and corporate sectors. Using mixed-methods analysis across six cultural regions, the study reveals fundamental variations in approaches to AI ethics, particularly regarding data privacy and human-technology relationships. The integration of Western, eastern, and African perspectives yields three frameworks: a cultural intelligence model for AI development, an adaptive governance mechanism, and a cross-cultural collaboration approach. Results demonstrate that successful AI implementation requires balancing diverse cultural perspectives with technical innovation through flexible governance structures, providing practical pathways for culturally sensitive AI development. © 2025 ieee.

关键词： Artificial Intelligence ethics Cross-Cultural computing Cultural Intelligence Framework Global Technology Governance

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