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Recent Advances in Resistive Gas Sensors: Fundamentals, Material and Device Design, and Intelligent Applications
Published 2025-06-01“…Moreover, the incorporation of artificial intelligence (AI) and Internet of Things (IoT) technologies has significantly advanced signal processing, pattern recognition, and long-term operational stability. …”
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Sensor‐Guided Smart Irrigation for Tomato Production: Comparing Low and Optimum Soil Moisture in Greenhouse Environments
Published 2025-03-01“…Fruit yield increased by 47% in T2, with an average of 56 fruits per plant compared to 45 in T1, and the average fruit weight was 85 g in T2 compared to 56 g in T1. Future research should explore the integration of advanced sensors, machine learning algorithms, and predictive models to further optimize irrigation strategies, with an emphasis on scalability and environmental impact. …”
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How does the level of functional impairment vary in individuals with non-communicable disease and comorbidity? Cross-sectional analysis of linked census and administrative data in...
Published 2024-12-01“…Objectives This study examines national patterns of functional impairment, and how they vary by the presence of non-communicable disease (NCD), type of health condition, comorbidity, age, sex, ethnicity, deprivation and living situation.Design A cross-sectional examination using a national research database of linked administrative and survey data sets including census, tax and health data.Setting Aotearoa New ZealandParticipants All individuals living in NZ on 30 June 2018, identified by the Statistics NZ Integrated Data Infrastructure estimated residential population (4.79 million individuals). …”
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Machine Learning-Based Intrusion Detection Systems for the Internet of Drones: A Systematic Literature Review
Published 2025-01-01“…Existing Intrusion Detection Systems (IDS) for IoD face several limitations, including high false positive rates, resource constraints of drones, limited adaptability to evolving attack patterns, and a lack of standardized datasets for benchmarking, despite ongoing research efforts. …”
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Exploration of Epigenetic Mechanisms and Biomarkers Among Patients with Very-Late-Onset Schizophrenia-Like Psychosis
Published 2025-04-01“…Yansha Gan,1,* Weihua Yue,2,* JiaoJiao Sun,1 DanTing Yang,1 ChunXia Fang,1 Zhenhe Zhou,1 JiaJun Yin,1 Hongliang Zhou3 1The Affiliated Mental Health Center of Jiangnan University, Wuxi, Jiangsu, 214151, People’s Republic of China; 2National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, People’s Republic of China; 3Department of Psychology, The Affiliated Hospital of Jiangnan University, Wuxi City, Jiangsu, 214100, People’s Republic of China*These authors contributed equally to this workCorrespondence: JiaJun Yin, The Affiliated Mental Health Center of Jiangnan University, Wuxi, Jiangsu, 214151, People’s Republic of China, Email yinjiajun@jiangnan.edu.cn Hongliang Zhou, Department of Psychology, The Affiliated Hospital of Jiangnan University, No. 200, Huihe Road, Binhu District, Wuxi City, Jiangsu Province, People’s Republic of China, Email Hongliangzh2022@hotmail.comObjective: This study aimed to identify DNA methylation patterns associated with Very Late-Onset Schizophrenia-like Psychosis (VLOSLP) and to develop methylation-based biomarkers that differentiate VLOSLP from Schizophrenia (SCZ) and Alzheimer’s Disease (AD).Methods: We analyzed methylation microarray datasets (n = 1218) from SCZ and AD patients obtained from the GEO database. …”
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AI-driven pharmacovigilance: Enhancing adverse drug reaction detection with deep learning and NLP
Published 2025-12-01“…These findings suggest that specific demographic and clinical factors significantly influence the likelihood of adverse reactions, offering valuable insights for targeted monitoring and risk mitigation strategies[11]. This research underscores the potential of predictive modeling to enhance pharmacovigilance efforts and ensure safer clinical trial outcomes. • The research methodology includes a comparison of supervised learning algorithms, such as Logistic Regression, Random Forest, Gradient Boost, CNN, and genetic algorithms, to identify patterns and anomalies in clinical trial data. …”
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Graph neural networks and transfer entropy enhance forecasting of mesozooplankton community dynamics
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“Diwan”: Constructing the Largest Annotated Corpus for Arabic Poetry
Published 2025-01-01“…By leveraging intelligent annotation algorithms, Diwan serves as a foundational resource and benchmark dataset for advancing research in fields such as automatic poetry generation, metrical analysis, thematic classification, and plagiarism detection. …”
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A Preliminary Assessment of the VIIRS Cloud Top and Base Height Environmental Data Record Reprocessing
Published 2025-03-01“…It outperforms the operational product in capturing very high CTHs exceeding 15 km and exhibits CBH probability patterns more closely aligned with CloudSat-CALIPSO measurements. …”
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Applications of machine learning-assisted extracellular vesicles analysis technology in tumor diagnosis
Published 2025-01-01“…In recent years, machine learning (ML) technology in the medical field has gained momentum, which utilize various algorithms to analyze input data, identify potential patterns and trends, develop predictive models, and generate high-precision predictions of unknown data, demonstrating its clinical potential in disease diagnosis. …”
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IMPLEMENTATION OF THE DBSCAN METHOD FOR CLUSTER MAPPING OF EARTHQUAKE SPREAD LOCATION
Published 2023-06-01“…While the sample used in this study is data on the location of the distribution of earthquakes in West Java Province in 2021 taken from the BMKG online data website at dataonline.bmkg.go.id. This research began with nearest-neighbor analysis to see patterns of data distribution. …”
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Enhancing decision-making on detractor-causing failures: an approach combining data mining and machine learning
Published 2025-12-01“…The proposed approach employs Decision Tree (DT) algorithms to uncover patterns linked to service failures. …”
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Optimizing solar energy utilization in facilities using machine learning-based scheduling techniques: A case study
Published 2025-06-01“…Our approach overcomes these limitations by employing ML algorithms to accurately predict solar generation patterns, enabling more efficient scheduling of electrical appliances. …”
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Strategies and Challenges in Detecting XSS Vulnerabilities Using an Innovative Cookie Collector
Published 2025-06-01“…Additionally, clustering algorithms enabled user segmentation based on cookie data, identification of behavioral patterns, enhanced personalized web recommendations, and browsing experience optimization. …”
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Mapping Gridded GDP Distribution of China Based on Remote Sensing Data and Machine Learning Methods
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A Novel Self-Attention-Enabled Weighted Ensemble-Based Convolutional Neural Network Framework for Distributed Denial of Service Attack Classification
Published 2024-01-01“…This research addresses this gap by introducing a novel approach for DDoS attack detection. …”
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