Developing a Vital Signal Detection Electrode for Fabric Substrate Using a High-Performance Conductive Carbon-Based Ink by K. Chansaengsri, B. Tunhoo, K. Onlaor, T. Thiwawong

“…The ECG data from the prepared electrode were applied to the machine learning models. The Random Forest (RF) model exhibited the optimized prediction value, with an F1 score of 99.9%. …”
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Automated Semantic Segmentation of Arctic Surface Water Features with Very-High Resolution Satellite X-Band Radar Imagery and U-Net Deep Learning: Segmentation sémantique automatis... by Michael Allan Merchant, Masoud Mahdianpari, Laura Bourgeau-Chavez, Ben DeVries, Aaron Berg

“…Our study proposes a modified U-Net encoder-decoder model for this task, optimized using the Nadam algorithm. …”
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Advanced beamforming and reflection control in intelligent reflecting surfaces with integrated channel estimation by Sakhshra Monga, Anmol Rattan Singh, Nitin Saluja, Chander Prabha, Shivani Malhotra, Asif Karim, Md. Mehedi Hassan

“…This study presents a machine learning framework that directly maximises the beamformers at the BS and the reflective coefficients at the IRS, bypassing conventional methods that estimate channels before optimising system parameters. …”
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OpenTrack: a Sensor for Monitoring the Usage of Territory by D. Strigaro, A. Rollandi, M. Cannata

“…Processes video frames on edge using a lightweight machine learning model optimized for embedded devices and periodically transmits summary data (object type, direction, timestamp) via NB-IoT to a centralized data platform. …”
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Small-Disturbance Stability Analysis of Doubly Fed Variable-Speed Pumped Storage Units by Xiangyang Yu, Yujie Cui, Hao Qi, Chunyang Gao, Ziming He, Haipeng Nan

“…This study establishes a detailed mathematical model for the connection of doubly fed induction generator-based variable-speed pumped storage (DFIG-VSPS) to a single-machine infinite bus system under power generation conditions in the synchronous rotation direct-quadrature-zero coordinate system. …”
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Robustness of topological persistence in knowledge distillation for wearable sensor data by Eun Som Jeon, Hongjun Choi, Ankita Shukla, Yuan Wang, Matthew P. Buman, Hyunglae Lee, Pavan Turaga

“…To address this problem, knowledge distillation (KD) is utilized to generate a small model and accommodate topological features with persistence image (PI) representations from the raw time series data. …”
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A High-resolution Soil Organic Carbon Map for Great Britain by Salar Mahmood, Beccy Wilebore, Rhosanna Jenkins, Katherine J. Willis, Marc Macias-Fauria, Shibu M. Ebrahim

“…Our model explains 74% of SOC variability in the evaluation dataset, with a RMSE of 9.8 (tC ha− 1). …”
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Automatic Precision Planting Mechanism of Garlic Seeder by Guilin Chen, Yifan Yao, Lili Yi, Xiang Yin, Juan Du, Jun Chong

“…The single-seed extraction mechanism and the adjustment mechanism for the garlic clove direction were designed based on the appearance dimensions of garlic cloves, enabling precise single-seed selection and orientation. A kinematic model of the insertion planting process was established, with key parameters meticulously described and analyzed, providing theoretical support for determining optimal insertion parameters. …”
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An Information-Extreme Algorithm for Universal Nuclear Feature-Driven Automated Classification of Breast Cancer Cells by Taras Savchenko, Ruslana Lakhtaryna, Anastasiia Denysenko, Anatoliy Dovbysh, Sarah E. Coupland, Roman Moskalenko

“…These metrics demonstrate a balanced and effective model for automated breast cancer cell classification. …”
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Clinical application and immune infiltration landscape of stemness‐related genes in heart failure by Wenting Yan, Yanling Li, Gang Wang, Yuan Huang, Ping Xie

“…Feature selection was performed using two machine learning algorithms. Nomogram models were then constructed to predict HF risk based on the selected key genes. …”
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Enhanced wheat yield prediction through integrated climate and satellite data using advanced AI techniques by Muhamad Ashfaq, Imran Khan, Rana Fezan Afzal, Dilawar Shah, Shujaat Ali, Muhammad Tahir

“…Using the Google Earth Engine platform, the analysis integrates satellite imagery, seasonal weather variables, and soil information. A range of machine learning and deep learning models were tested to assess their predictive performance. …”
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Hybrid preprocessing and ensemble classification for enhanced detection of Parkinson's disease using multiple speech signal databases by Ling-Chun Sun, Chun-Wei Tseng, Ke-Feng Lin, Ping-Nan Chen

“…Methods We utilized three publicly available PD speech datasets—MIU (Sakar), UEX (Carrón), and UCI (Little)—to build ML models incorporating a hybrid preprocessing framework. …”
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Hybrid Method for Point Cloud Classification by Abdurrahman Hazer, Remzi Yildirim

“…By processing local and global features in parallel, the Hybrid ResPOL method combines these features and feeds them into the classification head, optimizing performance. Experimental results indicate that the Hybrid ResPOL method achieves an overall accuracy (OA) of 94.3% and a mean accuracy (mAcc) of 91.3% on the ModelNet40 dataset. …”
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Computed tomography-based radiomic features combined with clinical parameters for predicting post-infectious bronchiolitis obliterans in children with adenovirus pneumonia: a retro... by Li Zhang, Ling He, Guangli Zhang, Xiaoyin Tian, Haoru Wang, Fang Wang, Xin Chen, Yinglan Zheng, Man Li, Yang Li, Zhengxiu Luo

“…The length of hospitalization, number of pneumonia lobes, and optimal radiomic features were incorporated into the combined models. …”
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Key technologies for exploration and geological evaluation of deep carbon storage spaces by Wenping LI, Danping CAO, Wei QIAO, Zhengwu ZHOU, Qingliang CHANG, Songhang ZHANG, Shuangxing LIU, Yi SHEN, Wanjun LI, Xin FU, Bo LIU, Yan WANG, Qiqing WANG, Xiaoqin LI, Zhi YANG, Cong LIU, Zheng ZHANG, Hongjie XU, Zhennan ZHU, Xianggang CHENG

“…Methods such as the analytic hierarchy process (AHP), GIS, and machine learning are combined to optimize site selection decisions. …”
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THE COMPLEX USE OF LOCAL TYPES OF FUEL IN THE POROUS CONSTRUCTION MATERIALS PRODUCTION by N. P. Voronova, B. V. Lesun

“…A study of the temperature distribution within the charge depending on the different speeds of the belt sintering machine, and hence on the cooling time.The characteristics of the raw material deposits "Fanipol" and the optimal composition of the charge which includes loam, coal, milled peat. …”
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Task Scheduling with Mobile Robots—A Systematic Literature Review by Catarina Rema, Pedro Costa, Manuel Silva, Eduardo J. Solteiro Pires

“…However, due to the complexity of these problems, existing models often struggle to provide efficient optimal solutions. …”
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Autonomous Earthwork Machinery for Urban Construction: A Review of Integrated Control, Fleet Coordination, and Safety Assurance by Zeru Liu, Jung In Kim

“…Advances include centimeter-scale path tracking, real-time vision-light detection and ranging (LiDAR) fusion and geofenced safety envelopes, but formal validation protocols and robust inter-machine communication remain open challenges. The review distils five research priorities, including adaptive perception and artificial intelligence (AI), digital-twin integration with building information modeling (BIM), cooperative multi-robot planning, rigorous safety assurance, and human–automation partnership that must be addressed to transform isolated prototypes into connected, self-optimizing fleets capable of delivering safer, faster, and more sustainable urban construction.…”
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Precise application of water and fertilizer to crops: challenges and opportunities by Yingying Xing, Xiukang Wang

“…It examines the integration of advanced sensors, remote sensing, and machine learning algorithms in precision agriculture, assessing their roles in optimizing irrigation and nutrient management. …”
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Automatic extraction of upper-limb kinematic activity using deep learning-based markerless tracking during deep brain stimulation implantation for Parkinson's disease: A proof of c... by Sunderland Baker, Anand Tekriwal, Gidon Felsen, Elijah Christensen, Lisa Hirt, Steven G Ojemann, Daniel R Kramer, Drew S Kern, John A Thompson

“…A semi-supervised classification model, support vector machine (SVM), trained on the parameters defined by the parabolic fit reliably predicted movement type. …”
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