This paper presents a two-agent framework to build a natural language query interface for IC information system, focusing more on scope queries in a single English sentence. The first agent, parsing agent, syntactically processes and semantically interprets natural language sentence to construct a fuzzy structured query language (SQL) statement. The second agent, defuzzifying agent, defuzzifies the imprecise part of the fuzzy SQL statement into its equivalent executable precise SQL statement based on fuzzy rules. The first agent can also actively ask the user some necessary questions when it manages to disambiguate the vague retrieval requirements. The adaptive defuzzification approach employed in the defuzzifying agent is discussed in detail. A prototype interface has been implemented to demonstrate the effectiveness.
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http://dx.doi.org/10.1631/jzus.2003.0152 | DOI Listing |
Clin Oral Investig
January 2025
Department of Bone Metabolism, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University & Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Research Center of Dental Materials and Oral Tissue Regeneration & Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, Shandong, China.
Objectives: This paper aims to review the immunopathogenesis of Diabetes-associated periodontitis (DPD) and to propose a description of the research progress of drugs with potential clinical value from an immunotherapeutic perspective.
Materials And Methods: A comprehensive literature search was conducted in PubMed, MEDLINE, Embase, Web of Science, Scopus and the Cochrane Library. Inclusion criteria were studies on the association between diabetes and periodontitis using the Boolean operator "AND" for association between diabetes and periodontitis, with no time or language restrictions.
Sci Rep
January 2025
North Carolina School of Science and Mathematics, Durham, NC, 27705, USA.
Mobile Ad Hoc Networks (MANETs) are increasingly replacing conventional communication systems due to their decentralized and dynamic nature. However, their wireless architecture makes them highly vulnerable to flooding attacks, which can disrupt communication, deplete energy resources, and degrade network performance. This study presents a novel hybrid deep learning approach integrating Convolutional Neural Networks (CNN) with Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) architectures to effectively detect and mitigate flooding attacks in MANETs.
View Article and Find Full Text PDFBMC Womens Health
January 2025
School of Nursing, Fudan University, 305 Fenglin Road, Shanghai, 200032, China.
Purpose: This scoping review aims to summarize online health information seeking (OHIS) behavior among breast cancer patients and survivors, identify research gaps, and offer insights for future studies.
Methods: Following Arksey and O'Malley's framework, we conducted a review across PubMed, Web of Science, CINAHL, MEDLINE, Cochrane, Embase, CNKI, Wanfang Data, and SinoMed, covering literature from 1 January 2014 to 13 August 2023. A total of 1,368 articles were identified, with 33 meeting the inclusion criteria.
BMC Psychiatry
January 2025
Research Center of Psychiatry and Behavioral Sciences, Tabriz University of Medical Sciences, Tabriz, Islamic Republic of Iran.
Introduction: Mental disorders, such as anxiety and depression, significantly impacted global populations in 2019 and 2020, with COVID-19 causing a surge in prevalence. They affect 13.4% of the people worldwide, and 21% of Iranians have experienced them.
View Article and Find Full Text PDFTrends Genet
January 2025
Computer Science Division, University of California, Berkeley, CA, USA; Department of Statistics, University of California, Berkeley, CA, USA; Center for Computational Biology, University of California, Berkeley, CA, USA. Electronic address:
Large language models (LLMs) are having transformative impacts across a wide range of scientific fields, particularly in the biomedical sciences. Just as the goal of natural language processing is to understand sequences of words, a major objective in biology is to understand biological sequences. Genomic language models (gLMs), which are LLMs trained on DNA sequences, have the potential to significantly advance our understanding of genomes and how DNA elements at various scales interact to give rise to complex functions.
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