Drowsiness Detection of Construction Workers: Accident Prevention Leveraging Yolov8 Deep Learning and Computer Vision Techniques by Adetayo Olugbenga Onososen, Innocent Musonda, Damilola Onatayo, Abdullahi Babatunde Saka, Samuel Adeniyi Adekunle, Eniola Onatayo

“…The system improves productivity and reduces costs by preventing accidents and enhancing worker safety. …”
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Enhanced prediction of ventilator-associated pneumonia in patients with traumatic brain injury using advanced machine learning techniques by Negin Ashrafi, Armin Abdollahi, Kamiar Alaei, Maryam Pishgar

“…XGBoost emerged as the top performing algorithm, achieving an AUC of 0.94 and an accuracy of 0.875 on the test set, marking substantial improvements over previously reported best results. …”
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Intelligent Data Processing Methods for the Atypical Values Correction of Stock Quotes by T. V. Zolotova, D. A. Volkova

“…The multiple imputation method creates for each missing value not one, but many imputations, which avoids a systematic error, but at the expense of high computational costs. For the initial data used in the work, the best result was shown by the implementation of the multiple imputation algorithm based on the detected outliers by the support vector method.Conclusion. …”
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A Framework for Autonomous UAV Navigation Based on Monocular Depth Estimation by Jonas Gaigalas, Linas Perkauskas, Henrikas Gricius, Tomas Kanapickas, Andrius Kriščiūnas

“…The solution utilizes a depth image estimation model to create an occupancy grid map of the surrounding area and uses an A* path planning algorithm to find optimal paths to end goals while navigating around the obstacles. …”
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CPFD Simulation of Operation Characteristics of a 10t/d Sludge and Biomass Co-incineration Fluidized Bed Reactor by REN Shaohui, YU Qiao, LIN Li, XIANG Jiatao, MA Lun, ZHANG Shihong

“…Higher bed temperatures (750→850℃) enhanced fuel conversion (CO₂↑12.03→13.46%) and H₂S oxidation (↓0.20→0.16%), while increased bed height (400→600 mm) paradoxically raised CNO by 57% despite improved residence time, suggesting channeling issues. …”
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The Role of Immunohistochemistry as a Surrogate Marker in Molecular Subtyping and Classification of Bladder Cancer by Tatiana Cano Barbadilla, Martina Álvarez Pérez, Juan Daniel Prieto Cuadra, Mª Teresa Dawid de Vera, Fernando Alberca-del Arco, Isabel García Muñoz, Rocío Santos-Pérez de la Blanca, Bernardo Herrera-Imbroda, Elisa Matas-Rico, Mª Isabel Hierro Martín

“…Further research is required to determine the optimal combination of markers, establish a consensus diagnostic algorithm, and validate IHC through large-scale trials. …”
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Interval-Aware Scheduling of Surveillance Drones: Exact and Heuristic Approaches by Kaito Mori, Hiroki Nishikawa, Hiroyuki Tomiyama

“…In comparison to the Greedy method, the Multi-stage method achieved an average improvement of 37.8% in total flight time, while its algorithm runtime deteriorated by a maximum of 1.26 seconds. …”
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Securing fruit trees future: AI-driven early warning and predictive systems for abiotic stress in changing climate by Muhammad Ahtasham Mushtaq, Muhammad Ateeq, Muhammad Ikram, Shariq Mahmood Alam, Muhammad Mohsin Kaleem, Muhammad Atiq Ashraf, Muhammad Asim, Khalid F. Almutairi, Mahmoud F. Seleiman, Fareeha Shireen

“…Specifically, multi-omics, data accessibility, algorithmic biases, the cost of implementation and requirements for robust training programs need to integrate for sustainable agriculture. …”
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YOLOv9-GDV: A Power Pylon Detection Model for Remote Sensing Images by Ke Zhang, Ningxuan Zhang, Chaojun Shi, Qiaochu Lu, Xian Zheng, Yujie Cao, Xiaoyun Zhang, Jiyuan Yang

“…On the Satellite Remote Sensing Power Tower Dataset (SRSPTD), the YOLOv9-GDV algorithm achieves an mAP of 80.2%, representing a 4.7% improvement over the baseline algorithm. …”
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Soft computing approaches of direct torque control for DFIM Motor's by Zakariae Sakhri, El-Houssine Bekkour, Badre Bossoufi, Nicu Bizon, Mishari Metab Almalki, Thamer A.H. Alghamdi, Mohammed Alenezi

“…This article provides a critical analysis of the following cutting-edge methods: DTC with Space Vector Modulation (DTC-SVM), DTC based on Fuzzy Logic (DTC-FL), DTC using Artificial Neural Networks (DTC-ANN), DTC optimized by Genetic Algorithms (DTC-GA), DTC with Ant Colony Optimization (DTC-ACO), DTC with rooted tree optimization (DTC-RTO), Sliding Mode Control (DTC-SMC), and Predictive DTC (P-DTC). …”
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Rapid Quality Assessment of Polygoni Multiflori Radix Based on Near-Infrared Spectroscopy by Bin Jia, Ziying Mai, Chaoqun Xiang, Qiwen Chen, Min Cheng, Longkai Zhang, Xue Xiao

“…After optimizing the model using CARS, R2C increased by 0.15%, 0.41%, and 0.34%, RMSECV decreased by 0.53%, 0.32%, and 0.24%, R2P increased by 0.21%, 0.63%, and 0.35%, RMSEP decreased by 0.36%, 0.41%, and 0.31%, and RPD increased by 1.1, 0.9, and 0.6, significantly improving the predictive capacity of the model. …”
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Digital augmentation of aftercare for patients with anorexia nervosa: the TRIANGLE RCT and economic evaluation by Janet Treasure, Katie Rowlands, Valentina Cardi, Suman Ambwani, David McDaid, Jodie Lord, Danielle Clark Bryan, Pamela Macdonald, Eva Bonin, Ulrike Schmidt, Jon Arcelus, Amy Harrison, Sabine Landau

“…Statistical uncertainty was explored through bootstrapping 1000 randomly resampled pairs of costs and outcomes with cost-effectiveness planes and cost-effectiveness acceptability curves showing the likelihood of ECHOMANTRA being cost-effective at different willingness-to-pay levels generated. …”
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Smart CAR-T Nanosymbionts: archetypes and proto-models by Juan C. Baena, Juan C. Baena, Juan Sebastián Victoria, Juan Sebastián Victoria, Alejandro Toro-Pedroza, Alejandro Toro-Pedroza, Cristian C. Aragón, Cristian C. Aragón, Joshua Ortiz-Guzman, Joshua Ortiz-Guzman, Joshua Ortiz-Guzman, Juan Esteban Garcia-Robledo, Juan Esteban Garcia-Robledo, David Torres, Lady J. Rios-Serna, Lady J. Rios-Serna, Ludwig Albornoz, Joaquin D. Rosales, Joaquin D. Rosales, Carlos A. Cañas, Carlos A. Cañas, Carlos A. Cañas, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Felipe Ocampo Osorio, Felipe Ocampo Osorio, Felipe Ocampo Osorio, Tania Fleitas, Ivan Laponogov, Alexandre Loukanov, Alexandre Loukanov, Alexandre Loukanov, Kirill Veselkov, Kirill Veselkov

“…At the same time, artificial intelligence (AI), with its powerful algorithms for data analysis and predictive modeling, is transforming how we design, evaluate, and monitor advanced therapies, including the optimization of manufacturing processes. …”
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Modeling pine forest growing stock volume in subtropical regions of China using airborne Lidar data by Zige Lan, Xiandie Jiang, Guiying Li, Yagang Lu, Hongwen Yao, Dengsheng Lu

“…More research is needed to quantitatively examine different contribution of sample sizes, modeling algorithms, variables from different sources, and stratification factors on modeling results, so that we can design an optimal procedure for GSV modeling using airborne Lidar data.…”
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Damage prediction of rear plate in Whipple shields based on machine learning method by Chenyang Wu, Xiangbiao Liao, Lvtan Chen, Xiaowei Chen

“…The results demonstrate that the training and prediction accuracies using the Random Forest (RF) algorithm significantly surpass those using Artificial Neural Networks (ANNs) and Support Vector Machine (SVM). …”
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Real-time temperature prediction of large-scale lithium battery module driven by data based on few measurement points by Jiajie HAN, Qingyang YUAN, Yu LI, Bo ZHANG, Ke XUE, Tian LAN

“…Proper thermal management ensures uniform heat distribution, which is essential for optimizing efficiency, safety, and reliability. However, obtaining comprehensive real-time temperature data for large-scale battery systems is challenging due to the high costs, complexity, and impracticality of deploying extensive sensor networks. …”
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A Modified Differential Evolution for Source Localization Using RSS Measurements by Yunjie Tao, Lincan Li, Shengming Chang

“…While differential evolution (DE) has demonstrated notable efficacy in optimizing multimodal cost functions, conventional implementations often grapple with suboptimal convergence rates and susceptibility to local optima. …”
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A Secure Data Collection Method Based on Deep Reinforcement Learning and Lightweight Authentication by Yunlong Wang, Jie Zhang, Guangjie Han, Dugui Chen

“…To address such challenges, we propose a lightweight chain authentication protocol for scalable IoT environments (LCAP-SIoT), which uses Physical Unclonable Functions (PUFs) and distributed authentication to secure communications, and a secure data collection algorithm, named LS-QMIX, which fuses the LCAP-SIoT and Q-learning Mixer (QMIX) algorithm to optimize the path planning and cooperation efficiency of the multi-UAV system. …”
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Long Short-Term Memory-Based Computerized Numerical Control Machining Center Failure Prediction Model by Jintak Choi, Zuobin Xiong, Kyungtae Kang

“…The anomaly detection and predictive maintenance functions are essential for improving efficiency and reducing time and costs. This study aims to strengthen service competitiveness by reducing quality assurance costs and implementing AI-based predictive maintenance services, as well as establishing a predictive maintenance system for CNC manufacturing equipment. …”
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Application of collaborative innovation between the logical brain and the associative brain in oil and gas gathering and transportation systems by Jing GONG, Siheng SHEN, Daqian LIU, Qi KANG, Shangfei SONG, Haihao WU, Bohui SHI

“…There is an urgent need to overcome bottlenecks in areas such as algorithmic fusion, dynamic data sharing, and deep AI integration to enable a leap from localized optimization to system-wide intelligent decision-making. …”
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