Academic Articles & Research Papers

The rank of contextuality

Quantum contextuality is one of the most recognized resources in quantum communication and computing scenarios. We provide a new quantifier of this resource, the rank of contextuality (RC). We define RC as the minimum number of non-contextu...

QG-WRN: A Quantum-Enhanced Graph Convolutional Wide Residual Network for ASD Diagnosis via Neuroimaging Sensing Technology

The pathological mechanism of autism spectrum disorder (ASD) exhibits dual heterogeneity: abnormal local energy metabolism and brain-wide high-order topological failure. To synergistically characterize these complex signals captured by adva...

Enhancing Communication Security in Drones Using QRNG in Frequency Hopping Spread Spectrum

This paper presents a novel approach to enhancing the security and reliability of drone communications through the integration of Quantum Random Number Generators (QRNG) in Frequency Hopping Spread Spectrum (FHSS) systems. We propose a mult...

A Secure, Intelligent, and Smart-Sensing Approach for Industrial System Automation and Transmission over Unsecured Wireless Networks

In Industrial systems, Supervisory control and data acquisition (SCADA) system, the pseudo-transport layer of the distributed network protocol (DNP3) performs the functions of the transport layer and network layer of the open systems interc...

A Fully Adapted Headstage With Custom Electrode Arrays Designed for Electrophysiological Experiments

Electrophysiological recordings lead amongst the techniques that aim to investigate the dynamics of neural activity sampled from large neural ensembles. However, the financial costs associated with the state-of-the-art technology used to ma...

SIMULATION OF INFORMATION SECURITY RISKS OF AVAILABILITY OF PROJECT DOCUMENTS BASED ON FUZZY LOGIC

The widespread use of computer technology, its rapid development and use in almost all areas of human activity requires constant updating of information security issues. The activities of many enterprises in the field of IT, construction, a...

Blockchain Metamorphosis: Transforming Traditional Finance through Decentralization and Transparency

This study investigates how decentralization and transparency offered by blockchain technology could revolutionize traditional finance. Even with the rise of well-known cryptocurrencies such as Bitcoin and Ethereum, a general understanding ...

A study on process information-driven cyber threat detection for I&C systems in NPP

The increasing digitalization of Instrumentation and Control (I&C) systems in Nuclear Power Plants (NPPs) has improved operational efficiency while introducing cybersecurity vulnerabilities. Conventional network-based intrusion detection sy...

Artificial intelligence in clinical medicine: a state-of-the-art overview of systematic reviews with methodological recommendations for improved reporting

Medicine has become increasingly receptive to the use of artificial intelligence (AI). This overview of systematic reviews (SRs) aims to categorise current evidence about it and identify the current methodological state of the art in the fi...

TransKGQA: Enhanced Knowledge Graph Question Answering With Sentence Transformers

Knowledge Graph Question Answering (KGQA) plays a crucial role in extracting valuable insights from interconnected information. Existing methods, while commendable, face challenges such as contextual ambiguity and limited adaptability to di...

A Graph Database Representation of Portuguese Criminal-Related Documents

Organizations have been challenged by the need to process an increasing amount of data, both structured and unstructured, retrieved from heterogeneous sources. Criminal investigation police are among these organizations, as they have to man...

Higher Social Media Use Associated with Higher Hemoglobin A1C and Greater Diabetes Distress in Young Adults with Type 1 Diabetes.

D‐BERT: Incorporating dependency‐based attention into BERT for relation extraction

Abstract Relation extraction between entity pairs is an increasingly critical area in natural language processing. Recently, the pre‐trained bidirectional encoder representation from transformer (BERT) performs excellently on the text class...

Sequence Decision Transformer for Adaptive Traffic Signal Control

Urban traffic congestion poses significant economic and environmental challenges worldwide. To mitigate these issues, Adaptive Traffic Signal Control (ATSC) has emerged as a promising solution. Recent advancements in deep reinforcement lear...

A call for an interdisciplinary ethical foundation for GenAI governance in higher education

Abstract Generative artificial intelligence (GenAI) systems are increasingly embedded in higher education, shaping writing, instructional design, and institutional approaches to academic integrity. In response, universities have developed p...

Quantifying Gender Bias in Large Language Models Using Information-Theoretic and Statistical Analysis

Large language models (LLMs) have revolutionized natural language processing across diverse domains, yet they also raise critical fairness and ethical concerns, particularly regarding gender bias. In this study, we conduct a systematic, mat...

Advancements in natural language processing: Implications, challenges, and future directions

This research delves into the latest advancements in Natural Language Processing (NLP) and their broader implications, challenges, and future directions. With the ever-increasing volume of text data generated daily from diverse sources, ext...

Natural Language Processing in Psychiatry

The potential benefit of artificial intelligence (AI) technology as a tool of psychiatry has not been well defined. In this essay, the technology of natural language processing and its position with regard to the two main schools of AI is c...

Applications of natural language processing and large language models in materials discovery

The transformative impact of artificial intelligence (AI) technologies on materials science has revolutionized the study of materials problems. By leveraging well-characterized datasets derived from the scientific literature, AI-powered too...

BioBBC: a multi-feature model that enhances the detection of biomedical entities

Abstract The rapid increase in biomedical publications necessitates efficient systems to automatically handle Biomedical Named Entity Recognition (BioNER) tasks in unstructured text. However, accurately detecting biomedical entities is quit...