Academic Articles & Research Papers

On the practical aspects of machine learning based active power loss forecasting in transmission networks

Abstract The cost for covering active power losses makes a significant item in transmission system operators (TSO) annual budgets, and still it received limited attention in the existing literature. The focus of accurate power loss forecast...

Explainable and perturbation-resilient model for cyber-threat detection in industrial control systems Networks

Abstract Deep learning-based intrusion detection systems (DL-IDS) have proven effective in detecting cyber threats. However, their vulnerability to adversarial attacks and environmental noise, particularly in industrial settings, limits pra...

MCoGCN-motif high-order feature-guided embedding learning framework for social link prediction

Abstract Traditional social link prediction models primarily concentrate on the adjacency features of the network, overlooking the rich high-order structural information within. Therefore, the study of effective extraction and encoding of t...

Generative artificial intelligence

Abstract Recent developments in the field of artificial intelligence (AI) have enabled new paradigms of machine processing, shifting from data-driven, discriminative AI tasks toward sophisticated, creative tasks through generative AI. Lever...

Cobdock: an accurate and practical machine learning-based consensus blind docking method

Abstract Probing the surface of proteins to predict the binding site and binding affinity for a given small molecule is a critical but challenging task in drug discovery. Blind docking addresses this issue by performing docking on binding r...

AI-assisted neurocognitive assessment protocol for older adults with psychiatric disorders

IntroductionEvaluating neurocognitive functions and diagnosing psychiatric disorders in older adults is challenging due to the complexity of symptoms and individual differences. An innovative approach that combines the accuracy of artificia...

Raman Spectroscopy Pre-Trained Encoder: A Self-Supervised Learning Approach for Data-Efficient Domain-Independent Spectroscopy Analysis

Deep-learning methods have boosted the analytical power of Raman spectroscopy, yet they still require large, task-specific, labeled datasets and often fail to transfer across application domains. The study explores pre-trained encoders as a...

Identification of Aspergillus at section and species levels by artificial intelligence-based microscopic morphology image recognition

ABSTRACT Rapid and accurate identification of Aspergillus species in clinical microbiology laboratories is crucial for aspergillosis diagnosis and antifungal therapy. However, traditional methods still face challenges in distinguishing phyl...

Molecular biology and integrated strategies for activating cryptic biosynthetic gene clusters toward next-generation antibiotic discovery

Antimicrobial resistance (AMR) has been identified as one of the 21st century’s severest global public health crises. AMR led to an estimated 4.95 million deaths in 2019 and will claim 10 million lives a year by 2050 in the absence of targe...

Enhancing Online Security: A Novel Machine Learning Framework for Robust Detection of Known and Unknown Malicious URLs

The rapid expansion of the internet has led to a corresponding surge in malicious online activities, posing significant threats to users and organizations. Cybercriminals exploit malicious uniform resource locators (URLs) to disseminate har...

ID-Det: Insulator Burst Defect Detection from UAV Inspection Imagery of Power Transmission Facilities

The global rise in electricity demand necessitates extensive transmission infrastructure, where insulators play a critical role in ensuring the safe operation of power transmission systems. However, insulators are susceptible to burst defec...

Electromagnetic Field Distribution Mapping: A Taxonomy and Comprehensive Review of Computational and Machine Learning Methods

Electromagnetic field (EMF) exposure mapping is increasingly important for ensuring compliance with safety regulations, supporting the deployment of next-generation wireless networks, and addressing public health concerns. While numerous su...

Silhouette-driven contrastive learning with hierarchical neighborhood structure for unsupervised clothes change person re-identification

This paper addresses a highly challenging yet critical task: unsupervised person re-identification (Re-ID) under clothing changes. Unfortunately, existing unsupervised person Re-ID methods are mainly designed for short-term scenarios that r...

Artificial intelligence in retina

Major advances in diagnostic technologies are offering unprecedented insight into the condition of the retina and beyond ocular disease. Digital images providing millions of morphological datasets can fast and non-invasively be analyzed in ...

Machine Learning-Guided Discovery of Novel Inhibitors of Escherichia coli MurB.

A multi-branch network for cooperative spectrum sensing via attention-based and CNN feature fusion

Abstract In cognitive radio (CR) systems, the accurate detection of spectrum holes is a cornerstone for efficient spectrum utilization. However, the increasing complexity of CR environments, particularly those with multiple primary users (P...

Flattening the Curve of Flexible Space Robotics

Infrastructure monitoring, inspection, repair, and replacement in space is crucial for continued usage and safety, yet it is expensive, time-consuming, and technically very challenging. New robotics technologies and artificial intelligence ...

Integrating Merkle Trees with Transformer Networks for Secure Financial Computation

In this paper, the Merkle-Transformer model is introduced as an innovative approach designed for financial data processing, which combines the data integrity verification mechanism of Merkle trees with the data processing capabilities of th...

Save Our Roads from GNSS Jamming: A Crowdsource Framework for Threat Evaluation

Global Navigation Satellite Systems (GNSS) jamming is an acute problem in the world of modern navigation. As more and more applications rely on GNSS for both position and timing, jamming ramifications are becoming more severe. In this paper...

InsDD-YOLO: Detection of Transmission Line Insulator Damage Based on the Improved YOLOv13 Model

Amidst the rapid global expansion of smart grids, ensuring the safety and reliability of power transmission systems has become paramount. Insulators are critical components of high-voltage transmission lines, providing both electrical insul...