Artificial Intelligence, Computation, Communication and Network Security
Description
This book constitutes the refereed proceedings of the Second International Conference, AICCoNS 2026, held in Dubai, United Arab Emirates, during April 28-30, 2026.
The 137 full papers included in this book were carefully reviewed and selected from 887 submissions.The accepted papers have been organized into three volumes of the AICCoNS 2026 proceedings, reflecting the breadth of topics and research advancements presented at the conference. We trust that the contributions in these volumes will serve as a valuable reference for researchers and practitioners and will inspire continued innovation.
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Content
.- Agentic AI Framework for Nifty and Bank Nifty Options Trading.
.- Enhanced Fake Speech Detection System Using Conformer Architecture and Spectrogram Feature Analysis.
.- Explainable AI for Early Inflammatory Cascade De-tection in Skin Conditions.
.- An Explainable and Resource-Efficient Transformer Pipeline for CPU-Based Document Summarisation and Question Answering.
.- Reducing Overestimation Bias in Healthcare Decision Environments Using Double Q-Learning.
.- Automated Tree Species Identification for Carbon Credit Estimation.
.- Hybrid Models for Syntax Parsing: Bridging Automata Theory and Transformer Architectures.
.- DARE: A SLM-Based Digital Replica and Adaptive Honeypots for Mitigating Prompt Injection Attacks.
.- End-to-End Evaluation of Cloud-Enabled Artificial Intelligence for Financial Anomaly Detection.
.- Resource-Optimized AI Models for Secure Financial Decision-Making in Multi-Tenant Cloud Environments.
.- A Deep Learning Model for Automated Prediction of Obstructive Lung Disease Using Chest CT Images.
.- Cloud Misconfiguration Risk Analyzer with Data Analytics for Real-Time Detection and Security Posture Visualization.
.- AI powered Real-Time Traffic Anomaly Detection and Incident Prediction for Intelligent Urban Road Networks.
.- Optimization Based Plant Disease Detection and Soil Health Monitoring in Smart Agriculture using Deep Learning Techniques.
.- Design of a novel Intrusion Detection System and Evaluation using NSL-KDD Dataset.
.- Toward a Zero-Knowledge-Ready Architecture for Verifiable AI-Assisted Contract Signing.
.- PA-SAGE: Pareto-Aligned Self-Evolving Agentic Governance Engine for Multi-Objective Wireless Network Optimization.
.- SEET: A Self-Evolving Educational Tutor with Agent-Orchestrated LLMs for Lifelong Personalized Learning.
.- GOVERN-FL: Governance-Aware Federated Learning for Smart Cities via Blockchain and Multi-Objective Incentives.
.- Integrated Rule-Based Crop Recommendation Enhanced by Modified GAN-Generated Synthetic Data.
.- Automated Tomato Ripeness Detection and Yield Estimation Using YOLOv11 and Roboflow.
.- opology-Aware Hierarchical Federated Learning for Large-Scale IoT Networks.
.- Smart Visualization Systems for Societal Data: A User-Driven Computational Framework.
.- Patch-wise M-Net with Monarch Butterfly Optimization for Efficient Brain Tissue Segmentation in Magnetic Resonance Images.
.- Patch-wise M-Net with Monarch Butterfly Optimization for Efficient Brain Tissue Segmentation in Magnetic Resonance Images.
.- LDTH-Net: A Hybrid Content-Based Image Retrieval Framework Integrating Directional Text on Histograms and Deep CNN Features.
.- Multi-Layered Load Balancer for Enhanced Security and Performance in Cloud Computing.
.- An Efficient YOLOv8-Based Lightweight Model for Real-Time Paddy Leaf Disease Detection on Edge Devices.
.- A Framework for Multilanguage Code Generation with Cross-Language Semantic Consistency.
.- Decentralized Optimization in Distributed Systems Using Federated Multi-Agent Learning.
.- Quantum Classical Hybrid Surveillance System for Real Time Criminal Identification Using QCNN and LSTM Entanglement Based Alertin.
.- Predicting Hospital Readmission in Diabetic Patients: A Comparative Analysis of Machine Learning and
Attention-Based Deep Learning Models.
.- Federated Adversarial Learning Framework for Zero-Day Attack Detection in AI-Enabled IoT Networks.
.- Automated Pneumonia Detection Using Deep Learning.