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Exploring Consumer Behavior in E-Commerce with AI Personalization and Market Trends Analysis Models 3

Exploring Consumer Behavior in E-Commerce with AI Personaliz...

引用

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

作者： Kumar, Gaurav Devayani, G. Saraswathi, C. Melba Kani, R. Dongre, Sandeep Mallick, M. S. Mohamed School of Computer Application Lovely Professional University Phagwara India M.Kumarasamy College of Engineering Department of Computer Science and Business Systems Karur India School of Management Studies Bannari Amman Institute of Technology Erode India Mar Ephraem college of Engineering and Technology Kanyakumari India Nagpur India Department of Computer Science Engineering Chennai India

ISBN: (纸本)9798331508456

Online retailers must monitor and respond to changing consumer trends to stay competitive. AI-driven customization's revolutionary impact on market trends is the focus of this study on online buying and customer behavior. As AI advances, e-commerce platforms will be able to customize user experiences. Preprocessing, feature extraction, and model training comprise the AI-driven personalization process. Customer data from online marketplaces is collected first. It manages missing values, balance the data, encode categorical variables, scale the features, and minimize the dimensions as part of our thorough data preprocessing to ensure fair and applicable results. To trained the algorithms with CNN and Convolutional LSTM Based on key criteria, the AI model beat LSTM and CNN. It provides personalized insights and recommendations with an average accuracy of 92.03%. Personalized experiences and product suggestions enabled by AI-powered personalization have transformed e-commerce. It's important to use smart algorithms to engage customers and examine large databases. This proposed approach to shows that AI can transform online shopping and improve customer experiences. © 2025 IEEE.

关键词： Marketplaces

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Integrating Federated Learning and Blockchain for Enhanced Financial Portfolio Management 3

Integrating Federated Learning and Blockchain for Enhanced F...

引用

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

作者： Murugan, V.G. Nanda, Sudhansu Sekhar Sudindra, V.R. Jatty, Gajendra Naidu Kumar, N.Rajesh Chamundeeswari, Vijaya Department of Management Studies Andhra Pradesh Madanapalle India Sri Sri University Odisha Cuttack India Icfai Business School Department of Finance Bangalore India University of Botswana Gaborone Botswana St.Michael College of Engineering and Technology Sivagangai India Saveetha Engineering College Department of Computer Science and Engineering Tamilnadu Chennai India

ISBN: (纸本)9798331508456

Financial portfolio management receives secure and efficient processing through the combination of Federated Learning (FL) with blockchain technology. FL protects data privacy through its distributed training capabilities that prevent financial data exposure. Blockchain secures operations and maintains transparency through the creation of unalterable model change logs on its ledger systems. A proposed approach reaches 91.3% model accuracy level and a 1.27 Sharpe Ratio and delivers a 14.3% return on investment which surpasses conventional approaches. The training duration reaches 4.8 hours while security enhancements and increased efficiency become available in the system. The designed framework supports 200 transactions per second at 250 ms response time while maintaining complete security with 0.10 USD transaction fees. It demonstrates the ability of FL and blockchain technology to boost security measures and risk-adjusted performance metrics and computational capability. Future Work will concentrate on blockchain performance optimization while testing practical applications of algorithms and revising algorithms to optimize financial applications. © 2025 IEEE.

关键词： Investments

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Single particle imaging of biological specimens 6

Single particle imaging of biological specimens

引用

6th conference on Frontiers in Optical Imaging and Technology: Novel Imaging systems

作者： Cheng, Guanxiao Yu, Jinjie Key Laboratory of Optoelectronic Devices and Systems Ministry of Education and Guangdong Province College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen518060 China

ISBN: (数字)9781510679719

ISBN: (纸本)9781510679702

Single-particle imaging (SPI) at an X-ray free electron laser (XFEL) is demonstrating its potential to support the imaging and structure determination of biological specimens at atomic resolution without the need for crystallization. According to a principle of diffraction before damage, diffraction patterns of specimens with random orientations injected to the focus of ultra-short and extremely bright XFEL can be recorded before the specimens are damaged. For a successful image reconstruction, robust algorithms are needed. So far, fast and robust reconstruction algorithms from noisy and incomplete diffraction patterns have been challenges for XFEL SPI. Here we briefly outline the workflow of SPI and discuss key challenges and corresponding approaches to both phase retrieval and orientations determination. We also give an outlook of the promising algorithms for SPI by means of machine learning or deep learning and believe that the current computational challenges of XFEL SPI can be handled by utilizing techniques of modern data processing and artificial intelligence for imaging at atomic resolution and femtosecond temporal resolution in the future. © 2024 SPIE.

关键词： Diffraction patterns

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Fault Detection in Smart Grids by Hybrid Generative Adversarial Networks with Neuro Fuzzy Algorithm

Fault Detection in Smart Grids by Hybrid Generative Adversar...

引用

2024 international conference on Intelligent algorithms for Computational Intelligence systems, IACIS 2024

作者： Tejaswini, N.P. Riad Al-Fatlawy, Ramy Malathy, V. Kirthiga, N. Vidya Sagar Mudunuri, E.C. Nitte Meenakshi Institute of Technology Dept. of Ise Bengaluru India The Islamic University Engineering College of Technical Engineering Department of Computers Techniques Najaf Iraq Sr University Department of Ece Warangal India Kalasalingam Academy of Research and Education Department of Cse India Sagi Rama Krishnam Raju College Engineering College Bhimavaram India

ISBN: (纸本)9798350360660

Inrecent years, integration of advanced communication networks and estimation techniques smart grid enables real time analysis and has control to optimize distribution of energy, improve grid resilience. Detecting and classification of faults in electricity networks is important for uninterrupted provision and maintenance of costs at minimum. By implementing data-driven approaches these systems brought many improvements like consumption of energy and quick re-establishment. In this paper, hybrid Generative adversarial networks (GAN) - neuro fuzzy algorithm is implemented for detection of faults in smart grids and done by extraction of features which are extracted from smart meters, training is done by GAN then trained model is further sent for classification which is done by neuro fuzzy algorithm if there is a fault then model sent for identification or location of fault and evaluation of accuracy is done, if there is no fault then again sent to feature extraction process. Proposed hybrid GAN-neuro fuzzy algorithm achieved 95.33 % of precision and 97.23 % of recall. © 2024 IEEE.

关键词： Generative adversarial networks

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Architecture Design of Flexible Production Line Control System for reconfigurable Operations and Maintenance 3

Architecture Design of Flexible Production Line Control Syst...

引用

3rd international conference on Cloud Computing, Big Data Application and Software engineering, CBASE 2024

作者： Zhang, Yangyang Xu, Bo Wang, Dong Dang, Xing Tianjin Institute of Aerospace Mechanical and Electrical Equipment Tianjin300000 China

ISBN: (纸本)9798331506582

Thereis an urgent need for flexible production lines and other control systems, such as uncertain production scale, rapid iteration and optimization of business processes and structured data packages. It is urgent to design and package flexible systems and services with business as the core, to achieve 'on-demand use, on-demand adaptation'. This article starts with the requirements and architecture design of a flexible satellite batch production line control system, abstracts the physical system of intelligent equipment into a digital model, proposes a solution of 'business domain+middleware platform+intelligent equipment information model', designs an open software architecture for a microservice based control system, constructs a rule-based process configuration method, decouples business and hardware, and can efficiently match different business scenarios. The microservice partitioning of intelligent warehousing systems, intelligent distribution systems, and production management systems will be iteratively configured based on the business complexity of the system application scenarios and the microservice partitioning methods;The middleware platform is a bridge for information exchange between business domains and intelligent equipment. It digitizes the information model of intelligent equipment and interacts with business data for processing, obtaining standard and effective data for traceability and display purposes;The intelligent equipment information model forms a standardized solution for the interconnection and intercommunication of equipment and workshop information systems, ensuring the interconnection and intercommunication of on-site equipment and solving the problem of communication protocols not being open or standardized. © 2024 IEEE.

关键词： Digital storage

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Intrusion Detection using Machine learning 15

Intrusion Detection using Machine learning

引用

15th international conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Manasa, U. Kuzhalivaimozhi, S. Department of Information Science and Engineering The National Institute of Engineering Karnataka Mysore India

ISBN: (纸本)9798331300579

The fast development in the use of computer networks raises concerns about network availability, integrity, and confidentiality. This requires network managers to use various types of intrusion detection systems (IDS) to monitor network traffic for unauthorized and malicious activity. An intrusion is a malicious breach of security policy. As a result, an intrusion detection system monitors network traffic flowing through computer systems to look for malicious actions and recognized dangers, providing alarms when it detects them. Mining approaches can be highly useful in the development of an intrusion detection system. In order to detect intrusions, network traffic might be categorized as normal or anomalous. After examining over twenty-five studies, we chose the top three classification algorithms in our paper: Logistic Regression, Naive Bayes, and SVM. This study compares the top three classification algorithms based on their performance criteria to determine the best suited method available. © Grenze Scientific Society, 2024.

关键词： Network intrusion

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MediGuide AI using Machine Learning 2

MediGuide AI using Machine Learning

引用

2nd international conference on Machine Learning and Autonomous systems, ICMLAS 2025

作者： Pooja, R. Elugubanti, Nikitha Mary Shiba, C. Kalai priya, V. Sasirekha, K. Sabapathy, S Rathana R.M.K Engineering College Computer Science and Business Systems Tiruvallur District Kavaraipettai India R.M.K Engineering College Department Of Computer Science and Business Systems Kavaraipettai India R.M.K College of Engineering and Technology Department Of Computer Science and Engineering Tiruvallur District Puduvoyal India R.M.D Engineering College Department Of Computer Science and Business Systems Kavaraipettai India Dhaanish Ahmed College of Engineering Department Of Computer Science and Engineering Vanchuvanchery Chennai India

ISBN: (纸本)9798331505745

Providing diverse patient groups with their specific medication requirements, using a wide range of drugs, poses meaningful challenges for prescribing. Standardized approaches often lead to large waste, many side effects and suboptimal outcomes. Therefore, we need improved, more personalized healthcare. MediGuide AI's drug recommendation system is powered by machine learning and it offers a thorough solution. Optimized data pre-processing and analysis, leading to the desired outcome, is achieved using advanced machine learning algorithms like Naive Bayes, TF-IDF and the Natural Language Toolkit. Highly personalized prescriptions are generated using thorough patient data, including demographics and meaningful clinical factors to achieve substantially better accuracy. Important enhancements include dual recommendation outputs, which provide many drug recommendations alongside a large number of alternative Ayurvedic treatments presented side by side for effortless comparison. An advanced personalized dosage calculation module precisely determines drug dosages using advanced regression models based on age, weight and metabolism. This system helps patients track and record their medications and it also suggests several nearby Ayurvedic shops based on their location. MediGuide AI employs exceptionally powerful algorithms and its advanced tools deliver remarkably precise and exceptionally user-friendly healthcare solutions. Current systems make use of rule-based methods that cannot learn from new data, whereas MediGuide AI leverages a hybrid Naïve Bayes and PassiveAggressiveClassifier model for higher accuracy and real-time adaptability. It also includes Ayurvedic options to ensure personalized healthcare experience. © 2025 IEEE.

关键词： Drug dosage

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A novel in-motion initial alignment method for SINS assisted by DVL 4

A novel in-motion initial alignment method for SINS assisted...

引用

4th international conference on Testing Technology and Automation engineering, TTAE 2024

作者： Li, Juan Chen, Ziheng Ding, Wenjing College of Intelligent Systems Science and Engineering Harbin Engineering University Harbin150001 China

ISBN: (数字)9781510686656

ISBN: (纸本)9781510686649

The in-motion initial alignment of the strapdown inertial navigation system (SINS) assisted by the Doppler Velocity Log (DVL) plays a significant role in the efficient operation of the autonomous underwater vehicle (AUV). In the case of severe maneuvering or low accuracy of inertial sensors, the output error of the gyroscope gradually increases, which leads to a decrease in the initial alignment accuracy of the inertial navigation system. In this paper, an in-motion alignment method for DVL-assisted SINS is proposed, which eliminates the effect of attitude matrix variations on the observation noise by establishing an accurate filtering model for the constructed inertial vectors. Experimental results verify that the proposed algorithm can accurately estimate the attitude matrix, and the initial alignment accuracy is improved as compared with existing algorithms. © 2024 SPIE.

关键词： Inertial navigation systems

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An Intelligent Security systems in Cloud Computing using Cryptography Techniques 5

An Intelligent Security Systems in Cloud Computing using Cry...

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5th international conference on Electronics and Sustainable Communication systems, ICESC 2024

作者： Srilakshmi, V. Chetana, V. Lakshmi Dornala, Raghunadha Reddi Vallabaneni, S. Parvathi Ramanjaiah, Ganji School of Computer Science and Engineering Vit -AP University Andhra Pradesh Amaravati522237 India School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Amaravati Campus India Walgreens United States Pvp Siddhartha Institute of Technology Department of It Vijayawada India R v Institute of Technology Dept.of Cse Guntur India

ISBN: (纸本)9798350379945

Delivering computing resources over the internet has seen a paradigm shift towards cloud computing. However, there are serious security risks because cloud environments are distributed and shared. Intelligent Security systems (ISS) that use cryptographic techniques are now necessary to overcome these issues, such as data confidentiality, integrity, and authenticity;this study developed an ISS for cloud computing, concentrating on cryptographic techniques. The RSA-OAEP (Optimal Asymmetric Encryption Padding) and X.509 algorithms are combined to create the ISS and further cover a variety of cryptographic methods, emphasizing their functions in protecting cloud-based systems, including encryption, digital signatures, and key management. It also looks at improving security systems' threat detection and response capabilities by integrating artificial intelligence (AI) algorithms like Grubbs' Test. In addition, several issues and potential paths for intelligent security systems in cloud computing are examined, highlighting the necessity of ongoing study and development to remain ahead of developing cyber threats. © 2024 IEEE.

关键词： Cloud security

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Analysis of College Students' Mental Health Based on Machine Learning Algorithm 2

Analysis of College Students' Mental Health Based on Machine...

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2nd IEEE international conference on Integrated Circuits and Communication systems, ICICACS 2024

作者： Ren, Yaping Min, Qiuyue Jain, Amar Weifang Engineering Vocational College Shandong China Symbiosis International Symbiosis Institute of Technology Department of Civil Engineering Pune India

ISBN: (纸本)9798350317558

College students are the hope and future of national development, and all walks of life pay more attention to college students. However, the immaturity of the mind, changes in the external environment, employment pressure, and study pressure have caused different types of psychological cognitive disorders among contemporary college students, resulting in deficiencies in emotional regulation, interpersonal communication, and self-character, forming serious mental health problems. Based on machine learning algorithms, this paper analyzes the mental health of college students, obtains the law of college students' mental health data analysis, and establishes a classification model according to the law, so as to quickly screen college students with sub-mental health, adopt psychological counseling to communicate with students with abnormal mental health, and formulate targeted treatment plans for students who have shown obvious mental health problems, help college students solve mental health problems, and cultivate high-quality, mentality and all-round development of psychological data, contribute to the development of the motherland. © 2024 IEEE.

关键词： health conditions machine learning algorithms mental health Psychological

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