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Artificial Intelligence Based Predictive Analytics for Website Performance Optimization 7

Artificial Intelligence Based Predictive Analytics for Websi...

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7th international conference on Contemporary computing and Informatics, IC3I 2024

作者： Mathur, Sandeep Hasan, Yazdani Bhargava, Deepshikha Bhattacharjee, Subhangee Rana, Ajay Amity University Uttar Pradesh Greater Noida India Noida International University Uttar Pradesh Greater Noida India Gisma University of Applied Sciences Potsdam Germany

ISBN: (纸本)9798350350067

In the contemporary digital landscape, the efficacy of websites as vital platforms for businesses cannot be overstated. they serve as primary interfaces for interaction with customers, facilitating transactions, brand representation, and engagement. However, optimizing website performance to ensure maximal user engagement and satisfaction presents a formidable challenge. Traditional methods of website optimization often rely on retrospective analysis of Past data, which might not fully convey the subtle dynamics of user behaviour and market trends. this paper poses an innovative approach to address this challenge by integrating AI (Artificial Intelligence) - based predictive analytics into website optimization strategies. With the utilization of machine learning algorithms, our approach aims to analyse extensive datasets encompassing user interactions, website metrics, and external market dynamics. By leveraging predictive analytics, we anticipate user behaviour, predict future trends, and create data-driven decisions for the optimization of website content, layout, and features in real-time. this proactive method allows organizations to stay ahead of the curve, anticipate user needs, and deliver personalized experiences tailored to individual preferences and behaviours. the effectiveness of our approach is demonstrated through a series of experiments, showcasing improvements in key website performance metrics such as user engagement, conversion rates, and overall effectiveness. By empowering organizations to anticipate user behaviour and adapt their strategies accordingly, our method holds promise for revolutionizing website management practices in the digital age. © 2024 IEEE.

关键词： Customer satisfaction

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ICRAI 2021 - 2021 7th international conference on Robotics and Artificial Intelligence

ICRAI 2021 - 2021 7th International Conference on Robotics a...

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7th international conference on Robotics and Artificial Intelligence, ICRAI 2021

ISBN: (纸本)9781450385855

the proceedings contain 22 papers. the topics discussed include: automatic 3D skeleton-based dynamic hand gesture recognition using multi-layer convolutional LSTM;automatic defect recognition method of aluminum profile surface defects;benchmarking lane-changing decision-making for deep reinforcement learning;infrared face recognition based on yolo network and its application;an improved detection algorithm of moving targets based on envelope alignment in sea environments;design and obstacle-surmounting analysis of a novel 6 × 6 wheel-tracked unmanned ground platform;efficient mixed-integer nonlinear programming for optimal motion planning of non-holonomic autonomous vehicles;and integral reinforcement learning-based optimal control for nonzero-sum games of multi-player input-constrained nonlinear systems.

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Using Artificial Intelligence to Control Drones 7

Using Artificial Intelligence to Control Drones

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7th IEEE international conference on Methods and systems of Navigation and Motion Control, MSNMC 2023

作者： Pavlenko, Volodymyr Ponomarenko, Ihor Morhulets, Oksana Osadchyi, Viacheslav Ponomarenko, Dmytro Hrygorevska, Olena Kyiv National University of Technologies and Design Faculty of Mechatronics and Computer Technologies Kyiv Ukraine State University of Trade and Economics Department of Marketing Kyiv Ukraine Kyiv National University of Technologies and Design Department of Tourism Hotel and Restaurant Business Kyiv Ukraine Borys Grinchenko Kyiv University Faculty of Economics and Management Kyiv Ukraine International University of Business and Law Kyiv Ukraine Kyiv National University of Technologies and Design Department of Finance and Business Consulting Kyiv Ukraine

ISBN: (纸本)9798350395150

the importance of using drones to optimize results by types of economic activity is presented. the expediency of conducting comprehensive scientific research with the aim of finding new ways of using the presented technology and identifying ways to optimize the control of unmanned vehicles has been proven. It has been established that thanks to the improvement of the drone control system, it is possible to achieve qualitatively new results regarding the collection of various information and solving logistical problems in an extreme environment or conditions of uncertainty. the main factors of the active development of algorithms in the Data science, which allow optimizing various processes in the field of human activity, are presented. the importance of using server storage for the accumulation and processing of large arrays of heterogeneous information is revealed. Features of the transformation of the mathematical models use directions for data processing and the activation of the machine learning algorithms development are given. the reasons for the intensification of artificial intelligence introduction as a technology for making effective management decisions are revealed. the main directions of using artificial intelligence to optimize the management and operation of unmanned aerial vehicles are presented. A conceptual scheme of collection, accumulation and processing of heterogeneous information, which is generated by various devices placed on drones, and directions for applying artificial intelligence to achieve effective results are presented. the expediency of improving pattern recognition technology on a permanent basis has been proven, which will allow more accurate assessment of individual elements of the external environment and increase the efficiency of the logistics systems implementation. the possibility of using artificial intelligence for decision-making in conditions of uncertainty without the influence of the human factor and training on a perm

关键词： Drones

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7th Annual international conference on Information Management and Big Data, SIMBig 2020

7th Annual International Conference on Information Managemen...

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7th Annual international conference on Information Management and Big Data, SIMBig 2020

ISBN: (纸本)9783030762278

the proceedings contain 39 papers. the special focus in this conference is on Information Management and Big Data. the topics include: Modeling and Predicting the Lima Stock Exchange General Index with Bayesian Networks and Information from Foreign Markets;Comparative Study of Spatial Prediction Models for Estimating PM2.5 Concentration Level in Urban Areas;prediction of Solar Radiation Using Neural Networks Forecasting;COVID-19 Infection Prediction and Classification;towards a Benchmark for Sedimentary Facies Classification: Applied to the Netherlands F3 Block;mobile Application for Movement Recognition in the Rehabilitation of the Anterior Cruciate Ligament of the Knee;semantic Segmentation Using Convolutional Neural Networks for Volume Estimation of Native Potatoes at High Speed;symbiotic Trackers’ Ensemble with Trackers’ Re-initialization for Face Tracking;symbiotic Trackers’ Ensemble with Trackers’ Re-initialization for Face Tracking;peruvian Citizens Reaction to Reactiva Perú Program: A Twitter Sentiment Analysis Approach;static Summarization Using Pearson’s Coefficient and Transfer Learning for Anomaly Detection for Surveillance Videos;humpback Whale’s Flukes Segmentation algorithms;improving Context-Aware Music Recommender systems with a Dual Recurrent Neural Network;classification of Cybercrime Indicators in Open Social Data;StrCoBSP: Relationship Strength-Aware Community-Based Social Profiling;identifying Differentiating Factors for Cyberbullying in Vine and Instagram;effect of Social algorithms on Media Source Publishers in Social Media Ecosystems;the Identification of Framing Language in Business Leaders’ Speech from the Mass Media;Clustering Analysis of Website Usage on Twitter During the COVID-19 Pandemic;calibrated Viewability Prediction for Premium Inventory Expansion;twitter Early Prediction of Preferences and Tendencies Based in Neighborhood Behavior;distributed Identity Management for Semantic Entities.

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IoT Revolutionization using Federated Learning and Decentralized AI on Edge Devices 7

IoT Revolutionization using Federated Learning and Decentral...

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7th international conference on Contemporary computing and Informatics, IC3I 2024

作者： Chaudhary, Diwakar Verma, S.K. Pundir, Sumit Ranganathan, S. Umadevi, V. Srinivasan, K. Mangalmay Institute of Management & Technology Department of Management Uttar Pradesh Greater Noida India Noida International University School of Business Management Uttar Pradesh Greater Noida India Graphic Era Deemed to be University Department of Computer Science and Engineering Uttarakhand Dehradun India Affiliated to Bharathidasan University Department of Computer Science Tamil Nadu Trichy India Saveetha College of Liberal Arts and Sciences Simats Department of Commerce General Tamil Nadu Chennai India

ISBN: (纸本)9798350350067

this research proposes a novel strategy for addressing the limitations of centralized architectures in IoT data processing. Traditional systems experience significant bandwidth use, privacy difficulties, and scalability issues. To address these difficulties, the proposed approach combines Federated Learning (FL) with Decentralized AI on Edge Devices (DAI-ED). By decentralizing processing duties and utilizing FL methods, data is kept local to edge devices, lowering latency and improving privacy. Deployment entails choosing AI-capable edge devices and configuring them for seamless integration. Secure communication techniques provide privacy throughout FL operations. Model optimization approaches help to improve efficiency even further. Compared to centralized systems, the results show higher model accuracy, decreased communication overhead, and increased resource utilization. the proposed system has an overall accuracy of 95%, with edge device accuracy at 94.5% and central server accuracy at 96%. Communication overhead during the training and inference phases is greatly minimized, with the proposed system requiring 150 MB per device against 400 MB in centralized systems. the proposed system has low memory consumption and computational complexity, but it is very scalable. © 2024 IEEE.

关键词： Federated learning

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7th international conference on Artificial Intelligence and Security, ICAIS 2021

7th International Conference on Artificial Intelligence and ...

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7th international conference on Artificial Intelligence and Security, ICAIS 2021

ISBN: (纸本)9783030786205

the proceedings contain 183 papers. the special focus in this conference is on Artificial Intelligence and Security. the topics include: Research on Automation Strategy of Coq;a Model Design of Blockchain-Based Data Storage for E-Government Application;offloading Method Based on Reinforcement Learning in Mobile Edge computing;a Dynamic Decision-Making Method for Endorser Node Selection;a Proxy Node Resource Load Balancing Strategy Based on the Swift System;research on the Picture Database of Minority Emotion;An Improved CNN Model for Fast Salient Object Detection;instant Messaging Application Traffic Recognition;control System Design of Transport Robot Based on Multi-color Recognition;SACache: Size-Aware Load Balancing for Large-Scale Storage systems;Heterogeneous-ISA Application Migration in Edge computing: Challenges, Techniques and Open Issues;preface;An Approach Based on Demand Prediction with LSTM for Solving Multi-batch 2D Cutting Stock Problems;the Interaction Between Probe and Cavity Field Assists Quantum Synchronization;w-Louvain: A Group Detection Algorithm Based on Synthetic Vectors;application of Non-negative Matrix Factorization in Fault Detection of Distribution Network;patent Citation Network Analysis Based on Improved Main Path Analysis: Mapping Key Technology Trajectory;on-Chain and Off-Chain Collaborative Management System Based on Consortium Blockchain;the Implementation of Aeronautical Information Exchange Model in SWIM;CCTL: Cascade Classifier Text Localization Algorithm in Natural Scene Image;research on the Application of Big Data Analysis in University Library;research on Support Vector Machine in Traffic Detection Algorithm;application Research on Crop Straw Biomass Waste in Logistics Packaging System;the Identification of Slope Crack Based on Convolutional Neural Network.

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16th international conference on Parallel Computational Technologies, PCT 2022

16th International Conference on Parallel Computational Tech...

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16th international conference on Parallel Computational Technologies, PCT 2022

ISBN: (纸本)9783031116223

the proceedings contain 22 papers. the special focus in this conference is on Parallel Computational Technologies. the topics include: High-Performance Calculations for Modeling the Propagation of Allergenic Plant Pollen in an Atmospheric Boundary Layer;simulation of Nonstationary thermal Fields in Permafrost Using Multicore Processors;HPC TaskMaster – Task Efficiency Monitoring System for the Supercomputer Center;modeling of Two-Phase Fluid Flow Processes in a Fractured-Porous Type Reservoir Using Parallel Computations;MPI-Based PFEM-2 Method Solver for Convection-Dominated CFD Problems;construction of a Parallel Algorithm for the Numerical Modeling of Coke Sediments Burning from the Spherical Catalyst Grain;parallel Simulations of Dynamic Interaction Between Train Pantographs and an Overhead Catenary Line;a New Approach to the Supercomputer Simulation of Carbon Burning Sub-grid Physics in Ia Type Supernovae Explosion;visualizing Multidimensional Linear Programming Problems;Tuning of a Matrix-Matrix Multiplication Algorithm for Several GPUs Connected by Fast Communication Links;Measuring the Effectiveness of SAT-Based Guess-and-Determine Attacks in Algebraic Cryptanalysis;Implementation of the Algebraic Multigrid Solver Designed for Graphics Processing Units Based on the AMGCL Framework;VGL Rating: A Novel Benchmarking Suite for Modern Supercomputing Architectures;kinetic Modeling of Isobutane Alkylation with Mixed C4 Olefins and Sulfuric Acid as a Catalyst Using the Asynchronous Global Optimization Algorithm;quantum-Chemical Calculations of the Enthalpy of Formation of Some Tetrazine Derivatives;preface;Analysis of Block Stokes-Algebraic Multigrid Preconditioners on GPU Implementations;Compact LRnLA algorithms for Flux-Based Numerical Schemes;parallel Methods for Solving Saddle Type systems;optimization of the Computational Process for Solving Grid Equations on a Heterogeneous computing System.

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7th international conference on Artificial Intelligence and Security, ICAIS 2021

7th International Conference on Artificial Intelligence and ...

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7th international conference on Artificial Intelligence and Security, ICAIS 2021

ISBN: (纸本)9783030786144

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7th international conference on Artificial Intelligence and Security, ICAIS 2021

7th International Conference on Artificial Intelligence and ...

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7th international conference on Artificial Intelligence and Security, ICAIS 2021

ISBN: (纸本)9783030786175

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Deep Learning-based Paddy Doctor for Sustainable Agriculture 7

Deep Learning-based Paddy Doctor for Sustainable Agriculture

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7th international conference on Image Information Processing, ICIIP 2023

作者： Garg, Vijay Agarwal, Stuti Sharma, Sahil International Institute of Information Technology Bangalore India Panjab University Chandigarh India Ulster University School of Computing Engineering And Intelligent Systems Londonderry United Kingdom

ISBN: (纸本)9798350371406

In promoting sustainable agriculture, the prompt and precise identification of plant diseases and pests becomes critical in mitigating economic setbacks via timely interventions. Utilizing EfficientNet, a deep learning-based convolutional neural network (CNN), we categorized images using open-source datasets on various rice strains. Our empirical findings confirm that our suggested model architecture attains a commendable accuracy of 91% with imbalanced classes. Discarding blurry images and employing data augmentation techniques enhanced the model's precision in rice disease categorization by an additional 8.4%. the corresponding code will be publicly accessible here. © 2023 IEEE.

关键词： Convolutional neural networks

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