Transformative impact of explainable artificial intelligence: bridging complexity and trust
This research addresses the growing ‘black-box’ nature of AI by evaluating Explainable Artificial Intelligence (XAI) as a crucial bridge between model complexity and human trust. The paper provides a comprehensive analysis of model-specific, model-agnostic, and hybrid XAI methodologies across critical sectors like healthcare, finance, and industrial management. It highlights how transparency in decision-making can maximize […]
Hybrid Convolutional Neural Network for Robust Attack Detection in Wireless Sensor Networks
This paper proposes an intelligent hybrid intrusion detection model designed to secure Wireless Sensor Networks (WSNs) against evolving cyber threats in the IoT landscape. By integrating an Enhanced Black Widow Optimization (EBWO) algorithm with a Bidirectional Gated Recurrent Unit (BiGRU) and Attention Mechanism (ATTN), the framework achieves high-precision detection of malicious activities. The model effectively […]
Blockchain‐Assisted Trust Framework for Increased Survivability in Internet of Vehicles
This paper introduces a decentralized trust framework that synergistically combines Blockchain technology with advanced trust models to enhance the security and survivability of the Internet of Vehicles (IoV). By utilizing an immutable distributed ledger, the framework ensures data integrity and protects vehicular networks against malicious entities broadcasting false event messages. The proposed model features a […]
A Systematic Review on Text Summarization: Techniques, Challenges, Opportunities
This comprehensive review provides a critical analysis of the evolution of Text Summarization (TS) techniques, ranging from early statistical methods to modern Transformer-based Large Language Models (LLMs). The paper meticulously evaluates the architectural differences between extractive and abstractive summarization, emphasizing the importance of linguistic coherence and factual accuracy. It identifies current research gaps, such as […]
Map Matching Algorithm: Curve Simplification for Frechet Distance Computing & Precise Navigation Using RTKLIB
This study presents a map matching approach that combines curve simplification with Frechet distance computation to achieve highly accurate navigation results using RTKLIB. By comparing the vehicle’s trajectory with road network geometry, the algorithm identifies the most suitable path even in challenging urban conditions. RTKLIB integration offers enhanced GNSS precision, reducing positional errors and improving […]
Machine Learning–Based Biomedical Image Processing for Echocardiographic Images
This research applies machine learning methods to enhance the quality and clinical usefulness of echocardiographic images. By leveraging algorithms for noise reduction, segmentation, and structural feature enhancement, the system produces clearer and more accurate heart images for diagnostic evaluation. The study demonstrates how machine learning can help clinicians identify cardiac abnormalities more efficiently, improving diagnostic […]
Correction to LTE-NBP with UWB-WBAN for Biomedical Applications
This study presents corrections to the LTE-NBP model integrated with UWB-based Wireless Body Area Networks for advanced biomedical monitoring. The revised approach improves communication reliability, signal stability, and data accuracy between body-worn sensors and medical monitoring systems. By optimizing the interaction between UWB and LTE-NBP technologies, the corrected model reduces transmission errors and enhances patient […]
Statistical Impact Analysis of Congestion Control Algorithm in MANET
This study examines the statistical impact of congestion control algorithms within Mobile Ad-Hoc Networks (MANETs). By analyzing key performance metrics such as throughput, latency, packet loss, and network stability, the research evaluates how different algorithms respond under varying traffic loads. The findings highlight how congestion control strategies influence overall network efficiency and communication reliability. This […]
Stub Signature-Based Efficient Public Data Auditing System Using Dynamic Procedures in Cloud Computing
This research presents a stub signature–based system designed to improve the security and efficiency of public data auditing in cloud environments. By using lightweight, dynamically generated signatures, the framework enables third-party auditors to verify data integrity without accessing or exposing the original data. The approach reduces computation overhead, enhances privacy preservation, and ensures transparent and […]
Multiple Pattern Synthesis of Circular Antenna Arrays for Achieving Lower Side Lobe Level and Higher Directivity Using Hybrid Optimization Algorithm
This study focuses on synthesizing multiple radiation patterns in circular antenna arrays using a hybrid optimization algorithm. The approach improves antenna performance by reducing side lobe levels and enhancing main lobe directivity. By combining advanced optimization methods, the system achieves precise control over radiation characteristics, making it suitable for high-efficiency communication and radar applications. The […]