Hot deformation physical mechanisms and a unified constitutive model of a solid solution Ti55511 alloy deformed in the two-phase region by Huijie Zhang, Y.C. Lin, Gang Su, Yongfu Xie, Wei Qiu, Ningfu Zeng, Song Zhang, Guicheng Wu

“…Material constants are determined using a genetic algorithm (GA), and the experimental data align well with the predicted data. …”
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Indoor positioning systems provide insight into emergency department systems enabling proposal of designs to improve workflow by Marius Huguet, Canan Pehlivan, François Ballereau, Antoine Dodane-Loyenet, Franck Fontanili, Thierry Garaix, Youri Yordanov, Vincent Augusto, Karim Tazarourte, Abdesslam Redjaline

“…Additionally, we developed a user recognition algorithm (i.e., random forest classifier) capable of detecting the job category of the participant wearing the sensor. …”
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Reaction Behavior and Kinetic Model of Hydroisomerization and Hydroaromatization of Fluid Catalytic Cracking Gasoline by Haijun Zhong, Xiwen Song, Shuai He, Xuerui Zhang, Qingxun Li, Haicheng Xiao, Xiaowei Hu, Yue Wang, Boyan Chen, Wangliang Li

“…Kinetic parameters were estimated using the Levenberg–Marquardt algorithm and validated against experimental data. …”
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Unveiling shadows: A data-driven insight on depression among Bangladeshi university students by Sanjib Kumar Sen, Md. Shifatul Ahsan Apurba, Anika Priodorshinee Mrittika, Md. Tawhid Anwar, A.B.M. Alim Al Islam, Jannatun Noor

“…Seven machine learning models, including Support Virtual Machine (SVM), K-Nearest Neighbor (K-NN), Gaussian Naive Bayes (GNB), Decision Tree (DT), Random Forest Classifier (RFC), Artificial Neural Network (ANN), and Gradient Boosting (GB), were trained and tested using the collected data (n = 750) to identify the most effective method for predicting depression. After rigorous analysis, Random Forest emerged as the best-performing algorithm, exhibiting remarkable accuracy (87%), precision (78%), recall (95%), and f1-score (86%). …”
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Research on the Inversion Method of Dust Content on Mining Area Plant Canopies Based on UAV-Borne VNIR Hyperspectral Data by Yibo Zhao, Shaogang Lei, Xiaotong Han, Yufan Xu, Jianzhu Li, Yating Duan, Shengya Sun

“…The spectral transformations significantly enhance the feature information for canopy dust. The CARS algorithm extracted characteristic bands representing 20 to 30% of the total spectral bands, evenly spread across the entire range, thereby reducing the estimation model’s computational complexity. …”
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Comparative analysis of antibodies and lymphocytes in pulmonary tuberculosis patients with negative and positive cultures by Fernando-Renato Cázares-Sosa, Alejandro Hernández-Solís, Atenea-Estela Andrés-Dionicio, Heliodora González-González, Miguel Ibáñez-Hernández, Raúl Cicero-Sabido, Herón Huerta, Raquel Tapia-Romero, Jorge-Luis de-la-Rosa-Arana

“…The results will contribute to improve the diagnostic algorithm and appropriate treatment of patients with clinical tuberculosis. …”
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Identification of Factors Causing Land Cover Change in the Cikapundung Watershed by A. B. Harto, A. B. Harto, R. Virtriana, R. Virtriana, R. J. Kusuma, I. K. C. Reynaldi, A. Q. Karima, A. A. Kuntoro

“…Land cover classification was conducted using random forest algorithm based on Landsat 5, Landsat 8, and Sentinel-2 satellite images. …”
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Smart Management of Energy Losses in Distribution Networks Using Deep Neural Networks by Ihor Blinov, Virginijus Radziukynas, Pavlo Shymaniuk, Artur Dyczko, Kinga Stecuła, Viktoriia Sychova, Volodymyr Miroshnyk, Roman Dychkovskyi

“…Given the presence of anomalies and missing values in the operational data, a two-stage preprocessing algorithm incorporating DBSCAN clustering was applied for data cleansing and imputation. …”
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Integrated Additive Manufacturing Trajectory Control and Repair Management for Spiral Bevel Gear Using Fractional-Order PID and Adaptive Fuzzy Neural Inference System by Hiyam Adil Habeeb, Abdul Hadi Azman, Mohd Rizal Alkahari, Dzuraidah Abd Wahab, Nurhasyimah Abd Aziz

“…The research objectives concentrate on constructing an adaptive control algorithm for gear repair using metal powder bed fusion technology and assessing these algorithms against state-of-the-art methods. …”
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Body mass index as the main predictor for length of stay in COVID-19 patients with mild and moderate symptoms: a cross-sectional study in COVID-19 emergency hospital in Indonesia by Siti Rahayu Nadhiroh, Anisa Lailatul Fitria, Armedy Ronny Hasugian, Erwin Astha Triyono, Nono Tri Nugroho, Alfadhila Khairil Sinatrya, Hazreen B Abdul Majid

“…The Chi-square automatic interaction detection (CHAID) algorithm was employed for model building. Results: Most participants were overweight (34.6%) and obese (17.2%). …”
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Optimization and image quality in CT studies: application of DRLs based on clinical indication by Carmine Picone, Annamaria Porto, Roberta Fusco, Claudio Granata, Maria Chiara Brunese, Vincenza Granata, Alessandro Ottaiano, Marialuisa Barretta, Ferdinando Caranci, Biagio Pecori, Eugenio Sorgente, Sergio Salerno, Raffaella Mormile, Fabio Pinto, Antonio Pinto, Andrea Magistrelli, Antonella Petrillo

“…Recent advancements, including iterative reconstruction algorithms and artificial intelligence, offer promising avenues for dose reduction without compromising diagnostic value. …”
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Automatic two-wheeler rider identification and triple-riding detection in surveillance systems using deep-learning models by Uttam U. Deshpande, Supriya Shanbhag, Rudragoud Patil, Ramchandra Alias Ameet Chate, Sufola Das Chagas Silva Araujo, Kevin Pinto, J. Arjun, Mayankraj Patil, Balagouda Nirwani

“…To address challenging environments like occlusions and precise vehicle detection from a long distance we use the ResNet18-based DetectNet_v2 model. To reliably predict triple riding from several riders sitting on a two-wheeler and extract license plate information, we employ a cutting-edge YOLOv8 object-detection algorithm that operates on the Darknet framework. …”
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Forecasting reference crop evapotranspiration using deep learning model and online training by DENG Xuanying, LYU Xinwei, ZHENG Wenyan, ZHENG Shizong, ZHANG Yadong, LUO Tongyuan, CUI Yuanlai, LUO Yufeng

“…A deep learning model based on the backpropagation (BP) neural network algorithm was developed and deployed for online training using Alibaba Cloud servers. …”
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Comparative Analysis of Computed Tomography and Laparoscopy Data in Preoperative Staging of Gastric Cancer by N. K. Silanteva, T. A. Аgababyan, A. A. Kholeva, V. Yu. Skoropad, Z. N. Shavladze, S. A. Ivanov, L. P. Zhavoronkov

“…The combined use of CT and DL is a current algorithm for examining patients with gastric cancer. …”
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Enhancing environmental models with a new downscaling method for global radiation in complex terrain by A. Druel, J. Ruffault, H. Davi, A. Chanzy, O. Marloie, M. De Cáceres, A. Olioso, F. Mouillot, C. François, K. Soudani, N. K. Martin-StPaul

“…Finally, by using two different PBMs (CASTANEA, a PBM simulating tree growth, and SurEau, a plant hydraulic model simulating hydraulic failure risk), we showed that accounting for fine-resolution radiation can have a great impact on predictions of forest functions.</p>…”
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An Enhanced Deep Neural Network Approach for WiFi Fingerprinting-Based Multi-Floor Indoor Localization by Shehu Lukman Ayinla, Azrina Abd Aziz, Micheal Drieberg, Misfa Susanto, Afidalina Tumian, Mazlaini Yahya

“…The CV process is repeated multiple times to assess the RFE&#x2019;s generalization ability for optimal feature selection, and the BN algorithm is integrated into each layer of the DNN to ensure consistent activation value distribution and stabilization of the training process. …”
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Management and edaphoclimatic factors that determine soybean top-performing farmers in Brazil by Victor Delino Barasuol Scarton, Ivan Ricardo Carvalho, Christiane de Fátima Colet, Leonardo Cesar Pradebon, Willyan Júnior Adorian Bandeira, Jaqueline Piesanti Sangiovo, Murilo Vieira Loro, José Antonio Gonzalez da Silva

“…Machine learning models proved superior to traditional methods for predicting productivity, offering a strategic tool for agribusiness. …”
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Diagnostic performance of actigraphy in Alzheimer’s disease using a machine learning classifier – a cross-sectional memory clinic study by Mathias Holsey Gramkow, Andreas Brink-Kjær, Frederikke Kragh Clemmensen, Nikolai Sulkjær Sjælland, Gunhild Waldemar, Poul Jennum, Steen Gregers Hasselbalch, Kristian Steen Frederiksen

“…We derived movement patterns (walking, running, resting, etc.) from raw accelerometry data using a proprietary algorithm. By evaluating the movement patterns during day and nighttime, we calculated 510 activity-related features, including robustness and fragmentation of the circadian rhythm. …”
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Artificial intelligence enhanced electrochemical immunoassay for staphylococcal enterotoxin B by Yuliang Zhao, Tingting Sun, Huawei Zhang, Chao Lian, Zhongpeng Zhao, Yongqiang Jiang, Huiqi Duan, Yuhao Ren, Xuyang Sun, Zhikun Zhan, Mingyue Qu, Shaolong Chen

“…Lastly, a multivariate linear regression algorithm is employed to effectively train and fit the extracted feature data. …”
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Using Machine Learning and Feature Importance to Identify Risk Factors for Mortality in Pediatric Heart Surgery by Lorenz A. Kapsner, Manuel Feißt, Ariawan Purbojo, Hans-Ulrich Prokosch, Thomas Ganslandt, Sven Dittrich, Jonathan M. Mang, Wolfgang Wällisch

“…A random survival forest (RSF) and the ‘eXtreme Gradient Boosting’ algorithm (XGB) were applied to model mortality (incidence: 5.6% [<i>n</i> = 73 events]). …”
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