Using the YOLO v8 model and deep learning approaches, this study explores the field of e-waste management and provides effective item detection. Our research attempts to increase the accuracy and scalability of e-wast...
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Desertification greatly affects land deterioration, farming efficiency, economic growth, and health, especially in Gulf nations. Climate change has worsened desertification, making developmental issues in the area eve...
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Desertification greatly affects land deterioration, farming efficiency, economic growth, and health, especially in Gulf nations. Climate change has worsened desertification, making developmental issues in the area even more difficult. This research presents an enhanced framework utilizing the internet of Things (IoT) for ongoing monitoring, data gathering, and analysis to evaluate desertification patterns. The framework utilizes Bayesian Belief Networks (BBN) to categorize IoT data, while a low-latency processing method on edge computing platforms enables effective detection of desertification trends. The classified data is subsequently analyzed using an Artificial Neural Network (ANN) optimized with a Genetic Algorithm (GA) for forecasting decisions. Using cloud computing infrastructure, the ANN-GA model examines intricate data connections to forecast desertification risk elements. Moreover, the Autoregressive Integrated Moving Average (ARIMA) model is employed to predict desertification over varied time intervals. Experimental simulations illustrate the effectiveness of the suggested framework, attaining enhanced performance in essential metrics: Temporal Delay (103.68 s), Classification Efficacy—Sensitivity (96.44 %), Precision (95.56 %), Specificity (96.97 %), and F-Measure (96.69 %)—Predictive Efficiency—Accuracy (97.76 %) and Root Mean Square Error (RMSE) (1.95 %)—along with Reliability (93.73 %) and Stability (75 %). The results of classification effectiveness and prediction performance emphasize the framework's ability to detect high-risk zones and predict the severity of desertification. This innovative method improves the comprehension of desertification processes and encourages sustainable land management practices, reducing the socio-economic impacts of desertification and bolstering at-risk ecosystems. The results of the study hold considerable importance for enhancing regional efforts in combating desertification, ensuring food security, and formulatin
Customer churn prediction is an important task in customer relationship management because it helps businesses know who is at risk of leaving and retain such at-risk *** and time-efficient churn prediction is essentia...
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The rapid evolution of smartphone technology and the diverse range of available models have made selecting a cost-effective mobile phone a complex decision for consumers. Although brand, internal memory, camera qualit...
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Serverless computing has emerged as a compelling paradigm for the deployment of applications at the edge facilitating performant and lightweight services. Services deployed at the edge typically consume lesser compute...
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The proceedings contain 31 papers. The special focus in this conference is on Scientific computing and Bioinformatics,. The topics include: Austere Runway Simulated Identification;using Rhai to Create and Be...
ISBN:
(纸本)9783031859014
The proceedings contain 31 papers. The special focus in this conference is on Scientific computing and Bioinformatics,. The topics include: Austere Runway Simulated Identification;using Rhai to Create and Benchmark Bevy Entities;pyO3: Building Python Extension Modules in Native Rust with Performance and Safety in Mind;Leveraging Python Interpreters for Concurrency in SeQUeNCe;benchmark Performance of a Rust-Based Python Extension;quantum Error Correction in Repetition Codes;investigating Selective Reliability with the Laminar Networking Package;an Entanglement Swapping Throughput Analysis for Quantum Networks Using Linear Quantum Optics;notes on Symmetric Generalized Tent Map: Route to Chaos;scalable Service Model and Scheduler for Delay-Sensitive Services;regret-Minimization Heuristics for Identifying Monotone Boolean Functions;multi-class Classification of Satellite Orbits for Database Quality Control;real-Time Motion Planning for Autonomous Vehicles in Dynamic Environments;A Novel Deep Learning Method for Solving PDE’s Applied to a Shallow Water Problem;exploring the Impact of Social Media on Mental Health and Well-Being: A Multi-dimensional Analysis;the Strategic Optimization of a Tabletop Role-Playing Game;Problem-Solving Using Logic and Reasoning, Mathematics, Algorithms, Python, and Generative AI: Part Two;acquisition and Analysis of Mobile Data Using Digital Forensics Tools and Techniques;structural Health Monitoring for Risk Assessment and Reliability of a Structure After Extreme Loads;scientific Constructing Adequate Statistical Decision Rules Under Parametric Uncertainty of Applied Mathematical Models via the Smart Use of Pivotal Quantities and Ancillary Statistics;a Smart Air Quality Analysis and Pollutant Diffusion Detection and Prediction System Based on Tree Canopy Shape Research Using Machine Learning and Artificial Intelligence;a High Order Scheme for Modelling Viscous Incompressible Fluid Flow in a Channel with a Step;Feasibility Study of Neutron M
The proceedings contain 37 papers. The special focus in this conference is on Applied Cognitive computing. The topics include: Assessing Information Influence for Node Attribute Prediction;in-Vehicle Sensing Plat...
ISBN:
(纸本)9783031856273
The proceedings contain 37 papers. The special focus in this conference is on Applied Cognitive computing. The topics include: Assessing Information Influence for Node Attribute Prediction;in-Vehicle Sensing Platform for the Inference of Older Drivers’ Mild Cognitive Condition;infusing Human Feedback into Intermediate Prompting Steps of Large Language Models;experimental Analysis of Contemporary Trends, Performance, and Limitations in Graph Embeddings: A Concise Review;a Secure Self-Adaptive System in Applications of Cognitive computing;revisiting the Nexus Between Handwriting and Personality: Graphology;from Static Graph Attention Generation to Dynamic Graph Attention Coefficient;An Integrated Approach for AI-Assisted Survey Systems Using Deterministic and Nondeterministic Models;a Voxel-Representation-Based Data Generator of Adversarial Objects for Robotic Manipulators;an Analysis of Different Information Granularity Distribution Protocols to Improve Consistency in Intuitionistic Reciprocal Preference Relations;enhancing Differential Evolution for Neural Network Optimization Through Boundary Individual Consideration;predictive Modeling of Shading Effects on Photovoltaic Panels Using Regression Analysis;enhancing Cultural Algorithm Guided Policy Gradients with Parameter-Based Exploration Through Topographic Knowledge and Adaptive Weighting;Enhancing Clinical Documentation Through NLP-Driven Disease Categorization and Visualization: A Case Study Utilizing the Llama2 AI Model;automatic Modulation Recognition: A Hybrid Approach Using Deep Learning and K-Means Clustering;An ISR Asset Planning Application;causal Discovery with Interactive Human Inputs;implementation of a Lightweight Gradient Descent Trained Expert System Algorithm;Leveraging JSBSim and Gymnasium: A Reinforcement Learning Approach for Air Combat Simulation;orthogonal Activation Functions in Neural Networks: Utilizing Chebyshev, Legendre, and Hermite Polynomials;XAI-Based Assessment of Software Vulnerabil
Many problems have been solved using the internet of things (IoT). Waste management, resource management, traffic management, financial services (e.g. stock rate prediction), logistics services, agriculture, etc. are ...
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The research combines Deep Q-Learning(DQN) with a Mininet-based network simulation and Scapy intrusions detection system (IDS) for malicious traffic prioritizing. The RL agent continuously learns to act based on real-...
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