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A Multi-Stage NLP Framework for Knowledge Discovery from Crop Disease Research Literature

Jantima Polpinij, Manasawee Kaenampornpan, Christopher S. G. Khoo, Wei-Ning Cheng et al. • Mathematics (2026)

Extracting and organizing knowledge from the agricultural crop disease research literature are challenging tasks because of the heterogeneous terminologies, complicated symptom descriptions, and unstructured nature of scientific documents. ...

DOAJ Open Access (DOAJ) DOI: 10.3390/math14020299

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

Imran Mirza, Akbar Anbar Jafari, Cagri Ozcinar, Gholamreza Anbarjafari • Information (2025)

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...

DOAJ Open Access (DOAJ) DOI: 10.3390/info16050358

On Application of Natural Language Processing in Machine Translation

Zhaorong Zong, Changchun Hong • International Conference on Mechanical, Control and Computer Engineering (ICMCCE) (2018)

Natural language processing is the core of machine translation. In the history, its development process is almost the same as machine translation, and the two complement each other. This article compares the natural language processing of s...

OPENALEX DOI: https://doi.org/10.1109/icmcce.2018.00112

Understanding the regulatory grammar of sepsis-causing Staphylococcus aureus bacteria using contexualised DNA language models

Tyrone Chen, Anton Y. Peleg, Sonika Tyagi • Scientific Reports (2025)

Abstract To efficiently and accurately understand, detect, and treat sepsis, we require a deep understanding of how its underlying biological systems work. Conventional methods struggle to provide a detailed view of both the functional and ...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-16701-2

Large Language Models and the Elliott Wave Principle: A Multi-Agent Deep Learning Approach to Big Data Analysis in Financial Markets

Michał Wawer, Jarosław A. Chudziak, Ewa Niewiadomska-Szynkiewicz • Applied Sciences (2024)

Traditional technical analysis methods face limitations in accurately predicting trends in today’s complex financial markets. Meanwhile, existing AI-driven approaches, while powerful in processing large datasets, often lack interpretability...

DOAJ Open Access (DOAJ) DOI: 10.3390/app142411897

L’IGF A L’EPREUVE DU CONTROLE SYSTEMIQUE ET DE LA DIGITALISATION : MUTATIONS DU CONTROLE FINANCIER PUBLIC EN RDC (2020-2027)

Drisceince MUTINDU CLAUDE, Raoul KIENGE-KIENGE INTUDI & Joël NZAMPUNGU IMBOLE • Ziglôbitha (2026)

Résumé : Cette étude analyse la transformation de l’Inspection Générale des Finances (IGF) de la RDC à travers les réformes de 2020-2023 et l’annonce de son plan stratégique 2025-2027 articulant contrôle systémique et digitalisation. A part...

DOAJ Open Access (DOAJ) DOI: 10.60632/ziglobitha.n018.23.vol.3.2026

Research on application of GPS-based wireless communication system in highway landslide

Zhiwen Xiong • EURASIP Journal on Wireless Communications and Networking (2021)

Abstract Machine learning is a branch of the field of artificial intelligence. Deep learning is a complex machine learning algorithm that has unique advantages in image recognition, speech recognition, natural language processing, and indus...

DOAJ Open Access (DOAJ) DOI: 10.1186/s13638-021-02038-7

Text Filtering through Multi-Pattern Matching: A Case Study of Wu–Manber–Uy on the Language of Uyghur

Turdi Tohti, Jimmy Huang, Askar Hamdulla, Xing Tan • Information (2019)

Given its generality in applications and its high time-efficiency on big data-sets, in recent years, the technique of text filtering through pattern matching has been attracting increasing attention from the field of information retrieval a...

DOAJ Open Access (DOAJ) DOI: 10.3390/info10080246

Different hybrid machine intelligence techniques for handling IoT‐based imbalanced data

Gaurav Mohindru, Koushik Mondal, Haider Banka • CAAI Transactions on Intelligence Technology (2021)

Abstract In the era of automatic task processing or designing complex algorithms, to analyse data, it is always pertinent to find real‐life solutions using cutting‐edge tools and techniques to generate insights into the data. The data‐drive...

DOAJ Open Access (DOAJ) DOI: 10.1049/cit2.12032

Construction and practice of an intelligent management system for preoperative anemia based on multidisciplinary collaboration

TAO Cuihua, HU Yingsen, LIAO Xin, TANG Hongling et al. • Zhongguo shuxue zazhi (2025)

[Objective] To improve the efficiency and standardization of preoperative anemia diagnosis and treatment by establishing a systematic intelligent management platform for preoperative anemia. [Methods] A multidisciplinary collaborative model...

DOAJ Open Access (DOAJ) DOI: 10.13303/j.cjbt.issn.1004-549x.2025.09.019

Transformer-Based Abstractive Summarization for Reddit and Twitter: Single Posts vs. Comment Pools in Three Languages

Ivan S. Blekanov, Nikita Tarasov, Svetlana S. Bodrunova • Future Internet (2022)

Abstractive summarization is a technique that allows for extracting condensed meanings from long texts, with a variety of potential practical applications. Nonetheless, today’s abstractive summarization research is limited to testing the mo...

DOAJ Open Access (DOAJ) DOI: 10.3390/fi14030069

Using 311 data to develop an algorithm to identify urban blight for public health improvement.

Jessica Athens, Setu Mehta, Sophie Wheelock, Nupur Chaudhury et al. • PLoS ONE (2020)

The growth of administrative data made available publicly, often in near-real time, offers new opportunities for monitoring conditions that impact community health. Urban blight-manifestations of adverse social processes in the urban enviro...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pone.0235227

USE OF ARTIFICIAL INTELLIGENCE TO IDENTIFY AND CORRECT MISCONCEPTIONS ABOUT RADIATION

Oleksandr Tymoshchuk • Інформаційні технології і засоби навчання (2025)

The expansion of nuclear technologies in various industries, combined with the constant threat of radiation-related incidents, highlights the urgent need for effective radiation education. This study is devoted to an empirical investigation...

DOAJ Open Access (DOAJ) DOI: 10.33407/itlt.v105i1.5905