A hybrid extraction model for semantic knowledge discovery of water conservancy big data by Yanna Feng, Feng Zhang, Yongheng Zhang, Jiangang Dong, PengJu Wang

“…To address the growing demand for efficient public opinion analysis in water conservancy and related domains, as well as the inefficiencies and limited scalability of existing automated web data extraction algorithms for multi-source datasets, this research integrates advanced technologies including big data analytics, natural language processing, and deep learning. …”
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Racial Disparities in Conforming Mortgage Lending: A Comparative Study of Fintech and Traditional Lenders Under Regulatory Oversight by Zilong Liu, Hongyan Liang

“…Achieving equitable mortgage lending requires enhanced regulatory oversight, greater transparency in algorithmic decision-making, and stricter enforcement of fair lending practices.…”
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Carbon reduction analysis of power system based on carbon emission flow theory: a case study of Shenzhen power grid by Yinjie Li, Ningrui Zhou, Zeqi Zhang

“…To address these challenges, this study proposes an integrated framework combining carbon emission flow theory with a low carbon demand response mechanism, accompanied by corresponding computational algorithms. Utilizing operational data from the Shenzhen power grid, we conducted a comprehensive empirical study featuring three key innovations. …”
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Blockchain-driven framework for preventive maintenance management of aircraft hydraulic systems by Alaa Alqaryuti, Karim Moawad, Khaled Salah, Ahmad Mayyas, Raja Jayaraman

“…This paper details the system architecture, underlying algorithms, and rigorous testing and validation processes. …”
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Development and evaluation of accurate 3D human models using scan data: a comparison with SMPL and CLO models by Gyungin Jung, Minjoo Kang, Sungmin Kim

“…This study introduces a novel 3D human modeling framework that combines skeleton-driven deformation algorithms with high-resolution 3D body scan data to generate anatomically accurate virtual bodies. …”
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Aberrant mitochondrial homeostasis at the crossroad of musculoskeletal ageing and non-small cell lung cancer. by Konstantinos Prokopidis, Panagiotis Giannos, Oliver C Witard, Daniel Peckham, Theocharis Ispoglou

“…Overlapping module DEGs were ranked based on 11 topological algorithms and were correlated with prognosis, tissue expression, and tumour purity in NSCLC. …”
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A Literature Review on Security in the Internet of Things: Identifying and Analysing Critical Categories by Hannelore Sebestyen, Daniela Elena Popescu, Rodica Doina Zmaranda

“…From leveraging machine learning and blockchain for anomaly detection and real-time threat response to optimising lightweight algorithms for resource-limited devices, researchers propose innovative and adaptive solutions to address emerging threats. …”
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Analyzing the compressive performance of lightweight foamcrete and parameter interdependencies using machine intelligence strategies by Wang Guoyuan, Fan Wenbo, Shi Qingbin, Luo Yingqi

“…For this purpose, the compressive strength (C-S) of foamcrete was assessed using two machine learning algorithms: gene expression programming (GEP) and multi-expression programming (MEP). …”
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“He is my savior, my guiding light in the dark”: imagination and domestication in Chinese women’s romantic relationships with AI companions by Liyao Huang, Wenxue Zou, Yanghao Huang

“…A thematic analysis was conducted to examine a total of 2,485 posts written by female users.ResultsThe analysis uncovers three distinct themes: exploring romantic communication styles, rethinking romantic relationship roles, and challenging dominant gender hierarchies. While AI companions appear to afford women new forms of relational agency, this empowerment is marked by what we term “compromised resistance,” a dialectical engagement wherein users deploy technology to contest traditional gendered power structures even as they become enmeshed in new forms of algorithmic dependency.DiscussionThe findings position AI companions as ambivalent disruptors of gendered social orders: their subversive potential does not reside in the technology itself, but in the ways it incites users to reimagine and enact more inclusive intimacies. …”
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Linking Animal Feed Formulation to Milk Quantity, Quality, and Animal Health Through Data-Driven Decision-Making by Oreofeoluwa A. Akintan, Kifle G. Gebremedhin, Daniel Dooyum Uyeh

“…Leveraging advanced analytical techniques, such as machine learning and optimization algorithms, have created highly accurate feed formulations tailored to specific livestock needs. …”
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Role of Artificial Intelligence in Dentistry by V. Hysenaj-Cakolli, B. Kolgeci, V. Hysenaj-Hoxha, D. Kolgeci

“…Future research should focus on enhancing AI algorithms, expanding training datasets, and integrating AI seamlessly into dental practice. …”
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A Spatial–Temporal Time Series Decomposition for Improving Independent Channel Forecasting by Yue Yu, Pavel Loskot, Wenbin Zhang, Qi Zhang, Yu Gao

“…In this paper, we improve the performance of single-channel forecasting algorithms by designing an interpretable front-end that extracts the spatial–temporal components from the input multivariate time series. …”
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An enhanced machine learning approach with stacking ensemble learner for accurate liver cancer diagnosis using feature selection and gene expression data by Amena Mahmoud, Eiko Takaoka

“…This approach reduced the dimensionality of the data while preserving crucial biological information. …”
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New online in-air signature recognition dataset and embodied cognition inspired feature selection by Yuheng Guo, Yuhan Zhou, Yifan Ge, Junwei Yu, Gen Li, Hiroyuki Sato

“…Our methodology includes a thorough statistical analysis with domain descriptors and DTW algorithms, alongside a comparative evaluation of seven deep-learning models on both the MIAS-427 and smartwatch datasets. …”
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A Data-Driven Comparative Analysis of Machine-Learning Models for Familial Hypercholesterolemia Detection by Tomasz Kocejko

“…This study presents an assessment of familial hypercholesterolemia (FH) probability using different algorithms (CatBoost, XGBoost, Random Forest, SVM) and its ensembles, leveraging electronic health record data. …”
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Gravity experiments with radio pulsars by Paulo C. C. Freire, Norbert Wex

“…So far, GR has passed all pulsar tests with flying colours, while at the same time many alternative gravity theories have either been strongly constrained or even falsified. …”
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Transformer and Convolutional Neural Network: A Hybrid Model for Multimodal Data in Multiclass Classification of Alzheimer’s Disease by Abdulaziz Alorf

“…The proposed method was also compared to benchmark algorithms and outperformed them; it was substantially less computationally expensive while maintaining its accuracy.…”
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Integrating health equity in artificial intelligence for public health in Canada: a rapid narrative review by Samantha Ghanem, Marielle Moraleja, Danielle Gravesande, Jennifer Rooney

“…Several health equity considerations for applying AI in public health were identified, including gaps in AI epistemology, algorithmic bias, accessibility of AI technologies, ethical and privacy concerns, unrepresentative training datasets, lack of transparency and interpretability of AI models, and challenges in scaling technical skills.ConclusionWhile AI has the potential to advance public health in Canada, addressing equity is critical to preventing inequities. …”
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Multi-Objective Optimization of Machinability and Energy Consumption of Cast Iron Depending on Cooling Rate by Burak Öztürk, Fuat Kara

“…GA results indicated that a cutting speed of 200 m/min and a feed rate of 0.15 mm/rev minimized surface roughness to 1.359 Ra while reducing Specific Energy Consumption (SEC) from 3.25 to 2.83 Wh/mL. …”
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Automatic Scan-to-BIM—The Impact of Semantic Segmentation Accuracy by Jidnyasa Patil, Mohsen Kalantari

“…Given the rapid advancement of deep learning algorithms in recent years, it is crucial to analyze how their accuracy impacts reconstruction quality. …”
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