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461
Application of artificial intelligence in insect pest identification - A review
Published 2026-03-01“…These methods have revolutionized insect identification by analyzing large databases of insect images and identifying distinct patterns and features linked to different species. …”
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462
Order picking dataset from a warehouse of a footwear manufacturing companyMendeley Data
Published 2025-08-01“…Anonymization and randomization techniques were applied while retaining realistic operational patterns to preserve confidentiality. This dataset is highly versatile and suitable for developing optimization algorithms for picker routing, order batching, wave generation, and intralogistics, as well as for advancing automation and robotics research through navigation-specific data for autonomous guided vehicles (AGVs) and robotic systems. …”
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463
Progress and trends on machine learning in proteomics during 1997-2024: a bibliometric analysis
Published 2025-08-01“…Thematic clustering revealed key research foci, including deep learning algorithms, protein–protein interaction prediction, and integrative multi-omics analysis. …”
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464
GAINSeq: glaucoma pre-symptomatic detection using machine learning models driven by next-generation sequencing data
Published 2025-07-01“…These algorithms demonstrated outstanding accuracy and resilience. …”
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465
A Review of Optimization Scheduling for Active Distribution Networks with High-Penetration Distributed Generation Access
Published 2025-08-01“…This paper provides a comprehensive review of research in this domain over the past decade. Initially, it analyzes the voltage impact patterns and control principles in distribution networks under varying levels of renewable energy penetration. …”
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466
Computer vision applications for the detection or analysis of tuberculosis using digitised human lung tissue images - a systematic review
Published 2024-11-01“…We categorised the computer vision platform into four technologies: image processing, object/pattern recognition, computer graphics, and deep learning. …”
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467
Multivariate determinants of self-management in Health Care: assessing Health Empowerment Model by comparison between structural equation and graphical models approaches
Published 2015-03-01“…</strong> This paper aims at investigating the consistency of Health Empowerment Model by means of both graphical models approach, which is a “data driven” method and a Structural Equation Modeling (SEM) approach, which is instead “theory driven”, showing the different information pattern that can be revealed in a health care research context.…”
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468
Review of Methods and Models for Forecasting Electricity Consumption
Published 2025-07-01“…The authors conducted a comparative analysis of various models, such as autoregressive models, neural networks, fuzzy logic systems, hybrid models, and evolutionary algorithms. Particular attention was paid to the effectiveness of these methods in the context of variable input data, such as weather conditions, seasonal fluctuations, and changes in energy consumption patterns. …”
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469
Integrating AI-generated content tools in higher education: a comparative analysis of interdisciplinary learning outcomes
Published 2025-07-01“…Using a mixed-methods approach, we analyzed implementation patterns and learning outcomes across humanities, STEM, and social sciences programs at multiple institutions. …”
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470
Human-based metaheuristics and non-parametric learning for groundwater-prone area mapping
Published 2025-12-01“…This study addresses these challenges by integrating human-inspired metaheuristics with non-parametric machine-learning techniques to enhance groundwater potential prediction. This research introduces a novel approach combining human-based metaheuristics—Teaching Learning Based Optimization (TLBO) and Cultural Algorithms (CA)—with non-parametric Decision Tree (DT) models. …”
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471
Calculation Model of Multi-roll Straightening Process Based on Bilinear Hardening and Power Hardening
Published 2025-05-01“…The bilinear model shows a linear increase in error, while the power model displays a nonlinear pattern. The magnitude of the hardening coefficient affects only the degree of curvature error, not the underlying behavior or material applicability. …”
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472
Melanoma Skin Lesion Classification Using Neural Networks: A systematic review
Published 2022-12-01“…Given neural networks' evolutionary patterns, updated, changed, and integrated networks are expected to increase the performance of such systems. …”
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473
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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474
Employing Data Mining Techniques and Machine Learning Models in Classification of Students’ Academic Performance.
Published 2024“…The study deals with the use of data mining techniques to build a classification model to predict students' academic performance. The research indicates that the use of machine learning models and data mining methods can reveal hidden patterns and relationships in big data, making them indispensable tools in the field of education analysis. …”
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475
A Comprehensive Vector Dataset of Bus Networks Across China for the Year 2024
Published 2025-03-01“…The dataset offers valuable insights for studying network patterns in China’s bus systems, supporting international comparative analyses of public transportation systems. …”
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476
BanglaNewsClassifier: A machine learning approach for news classification in Bangla Newspapers using hybrid stacking classifiers.
Published 2025-01-01“…Previous studies mostly focused on traditional models, overlooking the potential of hybrid techniques to handle the ever-growing complex dataset and its linguistic patterns in Bangla to achieve higher accuracy. Addressing the challenge, this study presents a comprehensive approach to classify Bangla news articles into eight distinct categories using various machine learning and deep learning techniques. …”
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477
Analysis on Acoustic Disturbance Signals Expected During Partial Discharge Measurements in Power Transformers
Published 2020-11-01“…As a result, an energy patterns analysis based on the wavelet decomposition is found as the most reliable tool for identification of PD signals. …”
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478
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479
Aspects of Developing A Methodology for Managing Digital Financial Assets
Published 2023-09-01“…In accordance with the scientific novelty of the research and methodology, a set of interrelated research stages is formed, consisting of an ordered cascade of methods, models and algorithms that perform preliminary analysis, processing and forecasting of financial time series of value indicators.Conclusion. …”
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480
A comparative analysis of classical machine learning models with quantum-inspired models for predicting world surface temperature
Published 2025-08-01“…The study compares the performance of classical machine learning algorithms to quantum algorithms, which use the concepts of superposition and entanglement to handle subtle temporal patterns in time-series data. …”
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