95 Results Found

Ontology engineering (OE) plays a critical role in modeling and managing structured knowledge across various domains. This study examines the performance of fine-tuned large language models (LLMs), specifically GPT-4 and Mistral 7B, in efficiently au...

Marseille (France) is a city on the Mediterranean coast characterized by two specific wind patterns: mistral (northwesterly wind blowing above 10 m/s) and sea/land breezes (southwesterly wind during daytime/northeasterly wind during the nighttime, bl...

Despite promising results obtained in the early diagnosis of several pathologies, breath analysis still remains an unused technique in clinical practice due to the lack of breath sampling standardized procedures able to guarantee a good repeatability...

This study investigates the strategic decision-making abilities of large language models (LLMs) via the game of Tic-Tac-Toe, renowned for its straightforward rules and definitive outcomes. We developed a mobile application coupled with web services,...

Effective communication in critical care units, such as the Cardiovascular Intensive Care Unit (CVICU), is vital for patient safety; however, clinical notes from multiple professionals are often lengthy and complex. This study evaluated the Mistral l...

The purpose of this paper is to explore the implementation of retrieval-augmented generation (RAG) technology with open-source large language models (LLMs). A dedicated web-based application, PaSSER, was developed, integrating RAG with Mistral:7b, Ll...

In this article, we present a tool for matching resumes to job posts and vice versa (job post to resumes). With minor modifications, it may also be adapted to other domains where text matching is necessary. This tool may help organizations save time...

Background: The rapid diffusion of large language models (LLMs) such as Claude, ChatGPT, Gemini, LLaMA, and Mistral is reshaping logistics and supply chain management by embedding generative intelligence into planning, coordination, and governance pr...

This paper investigates, applies, and evaluates state-of-the-art Large Language Models (LLMs) for the classification of posts from a dark web hackers’ forum into four cyber-security categories. The LLMs applied included Mistral-7B-Instruct-v0.2...

The Mediterranean region is a densely populated and economically relevant area with complex orography including mountain ranges, islands, and straits. In combination with pressure gradients, this creates many mesoscale wind systems that cause, e.g.,...

The rapid increase in scientific publications has made it challenging to keep up with the latest advancements. Conducting systematic reviews using traditional methods is both time-consuming and difficult. To address this, new review formats like rapi...

The contemporary digital landscape overwhelms visitors with fragmented and dynamic information, complicating travel planning and often leading to decision paralysis. This paper presents a real-world case study on the design and deployment of an intel...

Effective student feedback is fundamental to enhancing learning outcomes in higher education. While traditional assessment methods emphasise both achievements and development areas, the process remains time-intensive for educators. This research expl...

In-vitro viral studies are still fundamental for biomedical research since studying the virus kinetics on cells is crucial for the determination of the biological properties of viruses and for screening the inhibitors of infections. Moreover, testing...

The objective of this work is to evaluate the impact of regenerative agriculture alternatives in rainfed almond crops on a range of ecosystems services. A Multi-Criteria Analysis (MCA) was conducted to evaluate the different land management alternati...

The aim of this work is to present a preliminary study for the design of a digital auscultation system, i.e., a novel wearable device for patient chest auscultation and a digital stethoscope. The development and testing of the electronic stethoscope...

Candida spp. are an important opportunistic pathogen that can represent a possible cause of severe infections, especially in immunocompromised individuals. The clinical impact of Candida spp. depends, in part, on the ability to form biofilms, communi...

Orf virus (ORFV) belongs to the genus Parapoxvirus (Poxviridae family). It is the causative agent of contagious ecthyma (CE) that is an economically detrimental disease affecting small ruminants globally. Contagious ecthyma outbreaks are usually repo...

Staphylococcus argenteus, identified in 2006, represents a challenging case of bacterial taxonomic identification because of its high similarity to Staphylococcus aureus. In this context, neither mass spectrometry (MS) nor 16S gene analysis cannot pr...

This paper proposes an enhanced vibration-based damage detection index leveraging autoregressive moving average (ARMA) time-series modeling. The method relies on the fact that material deterioration alters the vibration features of the structure. Thu...

Orf virus (ORFV), a member of the Parapoxvirus genus, is commonly associated with a highly infectious skin disease primarily affecting sheep and goats, with a reported zoonotic potential. Initially identified in the 18th century, ORFV has been sporad...

Large language models (LLMs) are transformer-based neural networks that can provide human-like responses to questions and instructions. LLMs can generate educational material, summarize text, extract structured data from free text, create reports, wr...

Background: Large Language Models (LLMs) have demonstrated strong performances in clinical question-answering (QA) benchmarks, yet their effectiveness in addressing real-world consumer medical queries remains underexplored. This study evaluates the c...

Background/Objectives: This study compares the accuracy of responses from state-of-the-art large language models (LLMs) to patient questions before CT and MRI imaging. We aim to demonstrate the potential of LLMs in improving workflow efficiency, whil...

Stance detection for low-resource languages, such as the Kuwaiti dialect, poses a significant challenge in natural language processing (NLP) due to the scarcity of annotated datasets and specialized tools. This study addresses these limitations by ev...

(1) Background and objectives: Large language models (LLMs) such as GPT, Mistral, and LLaMA exhibit strong capabilities in text generation, yet assessing the quality of their reasoning—particularly in open-ended and argumentative contexts&mdash...

In today’s digital age, ensuring the appropriateness of content for children is crucial for their cognitive and emotional development. The rise of automated text generation technologies, such as Large Language Models like LLaMA, Mistral, and Ze...

Large language models (LLMs) are trained on huge datasets, which allow them to answer questions from various domains. However, their expertise is confined to the data that they were trained on. In order to specialize LLMs in niche domains like health...

Background/Objectives: Large Language Models (LLMs) like ChatGPT, LLAMA, and Mistral are widely used for automating tasks such as content creation and data analysis. However, due to their training on publicly available internet data, they may inherit...

Large Language Models are often fine-tuned on proprietary corpora, motivating reliable provenance signals. A corpus-level watermark method is proposed for fine-tuning datasets that survives training and common text transformations. The method subtly...

Emotion detection in Brazilian Portuguese is less studied than in English. We benchmarked a large language model (Mistral 24B), a language-specific transformer model (BERTimbau), and the lexicon-based EmoAtlas for classifying emotions in Brazilian Po...

In this work, the ERA5 reanalysis dataset, with its fine spatial and temporal resolution, is used to study the wind speed and direction characteristics in the Mediterranean basin from 1979 to 2020. Their variability, trend and mean values, as well as...

Timely forecast of atmospheric pollutants fallout due to accidental fires can provide decision-makers with useful information for effective emergency response, for planning environmental monitoring and for conveying essential alerts to the population...

This paper evaluates multi-agent coordination strategies against single-agent retrieval-augmented generation (RAG) for open-source language models. Four coordination strategies (collaborative, sequential, competitive, hierarchical) were tested across...

Large language models (LLMs) offer new opportunities for agricultural education and decision support, yet their adoption is limited by domain-specific terminology, ambiguous retrieval, and factual inconsistencies. This work presents AgroLLM, a domain...

Motorcyclists face a disproportionately high risk of severe injury or death compared to other road users, highlighting the need for intelligent rider assistance technologies. This paper presents an initial, modular, and interpretable AI pipeline that...

This paper explores the novel application of large language models (LLMs) as evaluators for structured scientific summaries—a task where traditional natural language evaluation metrics may not readily apply. Leveraging the Open Research Knowled...

The cognitive core of human beings is closely connected to the concept of animacy, which significantly influences their memory, vision, and complex language comprehension. While animacy is reflected in language through subtle constraints on verbs and...

This study presents a comprehensive evaluation of embedding techniques and large language models (LLMs) for Information Retrieval (IR) and question answering (QA) across languages, focusing on English and Italian. We address a significant research ga...

Dementia is a neurodegenerative disorder characterized by progressive cognitive impairment that significantly affects daily living. Early detection of Alzheimer’s disease—the most common form of dementia—remains essential for prompt...

The aim of this study is to investigate the potential of ChatGPT in analyzing the financial sentiment analysis of entrepreneurs. Sentiment analysis involves detecting if it is positive, negative, or neutral from a text. We examine several prompts on...

Background/Objectives: Multimodal large language models (MLLMs) offer potential for automated fracture detection, yet their diagnostic stability under repeated inference remains underexplored. This study evaluates the diagnostic accuracy, stability,...

In the rapidly evolving landscape of digital marketing and electronic commerce, short-form content—particularly on platforms like Twitter (now X)—has become pivotal for real-time branding, community engagement, and product promotion. The...

Large language models (LLMs) are increasingly used as rubric-guided graders for short-answer exams, but their decisions can be unstable across prompts and vulnerable to answer-side prompt injection. In this paper, we study SteadyEval, a guardrailed e...

The wide availability of sensor data stored in multiple formats makes it difficult to reuse in other applications. We consider the problem of extracting sensor data from unstructured and semi-structured texts using Large Language Models. With careful...

This document presents a proposal for designing an expert system in the Gabriela Mistral Division’s crushing plant belonging to Codelco (Chile) with the objective of maximizing stacked tonnage, allowing the improvement of operational variables...

Nutrition plays a pivotal role in preventive health, yet existing digital solutions often lack personalization and accessibility. This study presents an AI-driven framework that integrates machine learning (ML) and natural language processing (NLP) t...

Electronic health records (EHRs) are typically stored in relational databases, making them difficult to query for nontechnical users, especially under privacy constraints. We evaluate two practical clinical NLP workflows, natural language to SQL (NL2...

Large language models (LLMs) are a compressed repository of a vast corpus of valuable information on which they are trained. Therefore, this work hypothesizes that LLMs such as Llama, Orca, Falcon, and Mistral can be used for misinformation detection...

In the field of databases, Large Language Models (LLMs) have recently been studied for generating SQL queries from textual descriptions, while their use for conceptual or logical data modeling remains less explored. The conceptual design of relationa...