Improving time upscaling of instantaneous evapotranspiration based on machine learning models by Danni Yang, Shanshan Yang, Jiaojiao Huang, Shuyu Zhang, Sha Zhang, Jiahua Zhang, Yun Bai

“…To resolve this issue, this study aimed to assess four machine learning (ML) algorithms—XGBoost, LightGBM, AdaBoost, and Random Forest—to integrate meteorological and remote sensing data for upscaling [Formula: see text] across 88 global flux sites. …”
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Advances in ECG and PCG-based cardiovascular disease classification: a review of deep learning and machine learning methods by Asmaa Ameen, Ibrahim Eldesouky Fattoh, Tarek Abd El-Hafeez, Kareem Ahmed

“…This work compares and reports the classification, machine learning, and deep learning algorithms that predict cardiovascular illnesses. For this study, articles from 2012 to 2023 were considered; after filtering, 82 articles were chosen for primary research. …”
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Advanced Multiplier Architecture Optimization for Accelerated Arithmetic Operations and its Integration in Wireless Sensor Network Applications by Nirmal Kumar R., Valarmathi R. S., Kalamani M.

“…OMA-WSN combines RTSBA, Booth Multiplier, and Binary Common Sub-Expression Elimination (BCS2E) algorithms for a new viewpoint. This system's architecture implements efficient computation methods that minimize logic levels and propagation delays. …”
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Bidimensional Increment Entropy for Texture Analysis: Theoretical Validation and Application to Colon Cancer Images by Muqaddas Abid, Muhammad Suzuri Hitam, Rozniza Ali, Hamed Azami, Anne Humeau-Heurtier

“…Entropy algorithms are widely applied in signal analysis to quantify the irregularity of data. …”
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A lightweight and optimized deep learning model for detecting banana bunches and stalks in autonomous harvesting vehicles by Duc Tai Nguyen, Phuoc Bao Long Do, Doan Dang Khoa Nguyen, Wei-Chih Lin

“…Developing algorithms to identify fruit cutting locations is important for the functionality of harvesting robots. …”
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Identification of novel gut microbiota-related biomarkers in cerebral hemorrhagic stroke by Fengli Ye, Huili Li, Hongying Li, Xiue Mu

“…Hub genes were screened using LASSO, RandomForest, and SVM-RFE algorithms. Validation was conducted in plasma samples from ICH patients (n=20) and controls (n < 20) by qRT-PCR, and in a collagenase-induced ICH mouse model. …”
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Recent technical advancements and clinical applications of MR-guided radiotherapy in lung cancer treatment by Chi Ma, Xiao Wang, Ke Nie, Zhenyu Xiong, Keying Xu, Ning Yue, Yin Zhang

“…Recent technological innovations, including AI-powered auto-contouring algorithms, deep-learning (DL) based prediction models, and adaptive treatment strategies, further optimize MRgRT by improving workflow efficiency and reducing treatment time. …”
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Empirical Evaluation and Analysis of YOLO Models in Smart Transportation by Lan Anh Nguyen, Manh Dat Tran, Yongseok Son

“…You Only Look Once (YOLO) and its variants have emerged as the most popular real-time object detection algorithms. They have been widely used in real-time smart transportation applications due to their low-latency detection and high accuracy. …”
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Analysis of mid-infrared spectrum characteristics of sandstone with different acidification degrees based on fusion model by Lu Chen, Longfei Chang, Huiqing Lian, En Wang, Bixing Zhang, Jia Kang

“…Subsequently, K-Nearest Neighbor (KNN), Support Vector Machine (SVM), and Random Forest (RF) algorithms were compared, and a fusion model of mid-infrared spectral prediction models for red sandstone samples with varying degrees of acidification was established. …”
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ENDOCRINE PANCREATIC FUNCTION IN ACUTE PANCREATITIS by P. V. Novokhatny

“…However, there is still no clear understanding of the pathogenetic mechanisms of hormonal dysfunction of the pancreas in acute pancreatitis, there is no uniform algorithms for its correction. Aim of the research was to study the endocrine function of pancreas in acute pancreatitis. …”
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Advancing nearshore and onshore tsunami hazard approximation with machine learning surrogates by N. Ragu Ramalingam, K. Johnson, M. Pagani, M. Pagani, M. L. V. Martina

“…To address these challenges, it is crucial to develop concepts and algorithms for reducing the number of events simulated and more efficiently approximate the needed simulation results. …”
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Automated attendance management with RFID and geospatial visualization by Jilbert C. Bati-On, Kyle P. Kuizon, Krischel Ann Y. Catulpos, Johnloyd B. Bonghanoy, Jose Jr. Costillas Agoylo

“…Conclusion: The integration of genetic algorithms and facial recognition in a web-based scheduling system demonstrated improvements in efficiency, accuracy, and data security. …”
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Apoptosis mapping in space and time of 3D tumor ecosystems reveals transmissibility of cytotoxic cancer death. by Irina Veith, Arianna Mencattini, Valentin Picant, Marco Serra, Marine Leclerc, Maria Colomba Comes, Fathia Mami-Chouaib, Jacques Camonis, Stéphanie Descroix, Hamasseh Shirvani, Fatima Mechta-Grigoriou, Gérard Zalcman, Maria Carla Parrini, Eugenio Martinelli

“…In this work, we develop and apply novel video analysis algorithms to automatically measure the cytotoxic effects on human cancer cells (lung and breast) induced either by doxorubicin chemotherapy drug or by autologous tumor-infiltrating cytotoxic T lymphocytes (CTL). …”
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Specific features of pregnancy in patients with type 1 diabetes in the prepubertal period. Results of a 15-year long clinical observation by Lyubov' Leonidovna Bolotskaya, Natalya Vladimirovna Efremova, Yury Ivanovich Suntsov

“…Long-term follow-up of patients wit DM1 in accordance with algorithms of specialized medical aid to DM1 patients in Russia at a multidisciplinaryendocrinological centre decreases the risk of pregnancy and delivery complications and that of microvascular diabetic complications…”
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ES-Net Empowers Forest Disturbance Monitoring: Edge–Semantic Collaborative Network for Canopy Gap Mapping by Yutong Wang, Zhang Zhang, Jisheng Xia, Fei Zhao, Pinliang Dong

“…However, traditional monitoring methods have notable limitations: ground-based measurements are inefficient; remote-sensing interpretation is susceptible to terrain and spectral interference; and traditional algorithms exhibit an insufficient feature representation capability. …”
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Tribological Performance Enhancement in FDM and SLA Additive Manufacturing: Materials, Mechanisms, Surface Engineering, and Hybrid Strategies—A Holistic Review by Raja Subramani, Ronit Rosario Leon, Rajeswari Nageswaren, Maher Ali Rusho, Karthik Venkitaraman Shankar

“…Further, the review highlights the growing use of finite element modeling, digital twins, and machine learning algorithms for predictive control of tribological performance at AM parts. …”
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Time Frequency Analysis Based Fault Detection in PV Array Using Scaling Basis Chirplet Transform by S Ramana Kumar Joga, Chidurala SaiPrakash, Srikanth Velpula, Alivarani Mohapatra, Theophilus A. T. Kambo Jr.

“…The SBCT with combination of various machine learning algorithms is proposed to detect faults in PV array. …”
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Integrated analysis unraveling the immunologic and clinical prognostic values of synaptotagmin like 4 in pan-cancer by Yuehan Ren, Xiangbin Wu, Jinlei Li, Zhenhua Zhou, Shichang Ni, Jianhui Cai

“…We use multiple immune infiltration algorithms in TIMER2.0 and TISCH database to cross-verify the associations between SYTL4 expression and tumor immune microenvironment. …”
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Synthetic Data-Enhanced Classification of Prevalent Osteoporotic Fractures Using Dual-Energy X-Ray Absorptiometry-Based Geometric and Material Parameters by Luca Quagliato, Jiin Seo, Jiheun Hong, Taeyong Lee, Yoon-Sok Chung

“…To model the association of the bone’s current health status with prevalent FXs, three prediction algorithms—extreme gradient boosting (XGB), support vector machine, and multilayer perceptron—were trained using two-dimensional dual-energy X-ray absorptiometry (2D-DXA) analysis results and subsequently benchmarked. …”
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AI-powered IoT and UAV systems for real-time detection and prevention of illegal logging by Montaser N.A. Ramadan, Mohammed A.H. Ali, Shin Yee Khoo, Mohammad Alkhedher

“…The drone streams live video to the cloud, where AI algorithms analyze the footage for human presence. If detected, the drone activates sound and light alarms to deter illegal logging. …”
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