An ultrasonography of thyroid nodules dataset with pathological diagnosis annotation for deep learning by Xiaowen Hou, Menglei Hua, Wei Zhang, Jianxin Ji, Xuan Zhang, Huiru Jiang, Mengyun Li, Xiaoxiao Wu, Wenwen Zhao, Shuxin Sun, Lei Cao, Liuying Wang

“…Here, we present a large US dataset with pathological diagnosis annotation for each case, designed for developing deep learning algorithms to directly infer histological status from thyroid ultrasound images. …”
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Ai-powered digital twin in the industrial IoT by Željko Bolbotinović, Saša D. Milić, Žarko Janda, Dragan Vukmirović

“…According to DT needs and hierarchical data processing, as well as edge, fog, and cloud computing, the paper presents state-of-the-art ML models and algorithms. Real-time and low-latency requirements of smart edge devices and monitoring systems force the selection of DT models powered by ML models for time series processing and forecasting. …”
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Measuring the impact of technological innovation, green energy, and sustainable development on the health system performance and human well-being: Evidence from a machine learning-... by Alaeddine Mihoub, Montassar Kahia, Mohannad Alswailim

“…Mobile user penetration and CO₂ emissions have moderate to low importance, suggesting nuanced interactions with health expenditure. …”
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Cancer phylogenetic inference using copy number alterations detected from DNA sequencing data by Bingxin Lu

“…The challenges are discussed from the aspects of input data, models of evolution, and inference algorithms. The different methods are grouped according to the markers used for inference and the types of the reconstructed trees. …”
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DEEP LEARNING-BASED SUPER-RESOLUTION TECHNIQUES: A COMPARATIVE ANALYSIS WITH RECENT INSIGHTS by Renuka Sambhaji Sindge, Maitreyee Dutta, Jagriti Saini

“…Furthermore, this paper presents future directions for future researchers to follow SR trends with potential DL-based algorithms.…”
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Research progress and prospects of grating linear displacement measurement technology by ZHAO Zhicai, YU Hai, WAN Qiuhua, ZHAO Changhai, LI Yongjie

“…It reviews the research progress in these three areas and summarizes the strengths and limitations of existing studies: the grating linear displacement measurement technology based on Moire fringes is constrained by the diffraction limit, which hinders further improvements in resolution; the technology based on diffraction gratings struggles with absolute position measurement; and the technology based on image processing algorithms suffers from low integration and limited measurement range. …”
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STag marking visual guidance method for USV docking by Yongxin XIAO, Xianbo XIANG, Dian KONG, Lichun YANG, Shaolong YANG

“…By detecting STag markers in the video stream obtained by the camera on the USV, combined with the camera's internal parameters and the size of the markers, EPnP and direct linear transformation (DLT) algorithms are fused to calculate the relative pose of the recovery device and USV. …”
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Wearable Medical Devices: Application Status and Prospects by Xiaowen Wang, Yingnan Gao, Yueze Yuan, Yaping Wang, Anqin Liu, Sen Jia, Wenguang Yang

“…E-skin integrates multiple sensors and intelligent algorithms to automatically analyze data and provide health advice and early warning. …”
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A Comprehensive Review of Multiple Physical and Data-Driven Model Fusion Methods for Accurate Lithium-Ion Battery Inner State Factor Estimation by Junjie Tao, Shunli Wang, Wen Cao, Carlos Fernandez, Frede Blaabjerg

“…With the rapid global growth in demand for renewable energy, the traditional energy structure is accelerating its transition to low-carbon, clean energy. Lithium-ion batteries, due to their high energy density, long cycle life, and high efficiency, have become a core technology driving this transformation. …”
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Target identification of natural products in cancer with chemical proteomics and artificial intelligence approaches by Guohua Li, Qian Shi, Qibiao Wu, Xinbing Sui

“…AI-driven models, especially machine learning algorithms, have proven effective in processing complex proteomic data and predicting potential NP-protein interactions. …”
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A Normal Mode Model Based on the Spectral Element Method for Simulating Horizontally Layered Acoustic Waveguides by Yinuo Zhang, Houwang Tu, Yongxian Wang, Guojun Xu, Dongbao Gao

“…In classical normal mode models, these equations are typically discretized using low-order finite difference methods, which, while broadly applicable, suffer from a limited convergence rate. …”
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Advanced Technologies for Smart Fertilizer Management in Agriculture: A Review by Jian-Jun Liu, Hao Wu, Imran Riaz

“…However, key challenges hinder its widespread adoption, including regional disparities in data quality, scalability constraints in low-resource settings, regulatory inconsistencies, and the high costs of technology adoption for smallholder farmers. …”
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Deep Learning in Written Arabic Linguistic Studies: A Comprehensive Survey by Manar Almanea

“…This article presents a comprehensive survey on recent applications of deep learning (DL) algorithms to written Arabic. Despite the increasing amount of user-generated content in Arabic, linguistic studies focusing on Arabic suffer from low analytical resources. …”
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Bio-Inspired Traffic Pattern Generation for Multi-AMR Systems by Rok Vrabič, Andreja Malus, Jure Dvoršak, Gregor Klančar, Tena Žužek

“…Compared to the existing approaches, the proposed approach addresses the entire intralogistic problem, including plant layout, task distribution, release and dispatching algorithms, and fleet size. Its autonomous movement rule generation and low computational complexity make it well suited for dynamic intralogistic environments. …”
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Precision Medicine in Lung Cancer Screening: A Paradigm Shift in Early Detection—Precision Screening for Lung Cancer by Hsin-Hung Chen, Yun-Ju Wu, Fu-Zong Wu

“…Lung cancer remains the leading cause of cancer-related mortality globally, largely due to late-stage diagnoses. While low-dose computed tomography (LDCT) has improved early detection and reduced mortality in high-risk populations, traditional screening strategies often adopt a one-size-fits-all approach based primarily on age and smoking history. …”
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A Review of Optimization Scheduling for Active Distribution Networks with High-Penetration Distributed Generation Access by Kewei Wang, Yonghong Huang, Yanbo Liu, Tao Huang, Shijia Zang

“…Subsequently, it introduces optimization dispatch models for ADNs that focus on three key objectives: safety, economy, and low carbon emissions. Furthermore, addressing the challenge of solving non-convex and nonlinear models, the paper highlights model reformulation strategies such as semidefinite relaxation, second-order cone relaxation, and convex inner approximation methods, along with summarizing relevant intelligent solution algorithms. …”
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Multivariate determinants of self-management in Health Care: assessing Health Empowerment Model by comparison between structural equation and graphical models approaches by Filippo Trentini, Matteo Malgaroli, Anne Linda Camerini, Clelia Di Serio, Peter Schulz

“…Graphical modeling algorithms were implemented in a R software environment.…”
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Enhancing multivariate post‐processed visibility predictions utilizing Copernicus Atmosphere Monitoring Service forecasts by Mária Lakatos, Sándor Baran

“…We also demonstrate that post‐processing significantly improves the predictions of low visibility events, which opens the door for aeronautical applications.…”
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State of Charge Estimation in Li-Ion Batteries Using a Parallel LSTM-Based Approach: The Impact of Modeling Based on Operating States by Osman Ozer, Hayri Arabaci

“…To address this, deep learning algorithms such as long short-term memory (LSTM) have been focused on for SOC prediction. …”
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Attention-Based Color Difference Perception for Photographic Images by Hua Qiang, Xuande Zhang, Jinliang Hou

“…Existing deep learning-based CD measurement algorithms only focus on local features and cannot accurately simulate the human perception of CD. …”
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