Influence of Support Vector Regression (SVR) on Cryogenic Face Milling by Rao M. C. Karthik, Rashmi L. Malghan, Fuat Kara, Arunkumar Shettigar, Shrikantha S. Rao, Mervin A. Herbert

“…The benchmark function of the proposed mode hybrid-bias (BNN-SVR) algorithm showcases the propensity to emerge out of the local minimum and coincide with the optimal target value. …”
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Immune checkpoint inhibitors-related thyroid dysfunction: influencing factor analysis, prediction model development, and management strategy proposal by Xinya Li, Zaiwei Song, Yixuan Chen, Jingjing Wu, Dan Jiang, Zhen Zhang, Zeyuan Wang, Rongsheng Zhao

“…The model based on the LightGBM algorithm demonstrated superior performance, leading to the development of a web calculator. …”
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Postoperative fever following surgery for oral cancer: Incidence, risk factors, and the formulation of a machine learning-based predictive model by Yanling Zhang, Kun Long, Zhaojian Gong, Ruping Dai, Shuiting Zhang

“…Machine learning algorithms can be effectively used to identify potential risk factors of POF, which may enhance individualized treatment plans in oral cancer patient during perioperative period. …”
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Estimating whole-body centre of mass sway during quiet standing with inertial measurement units. by Liam H Foulger, Emma R Reiter, Calvin Kuo, Mark G Carpenter, Jean-Sébastien Blouin

“…These results indicate that IMUs can be used to estimate CoM displacements during quiet standing and that four IMUs are necessary to do so. Using an algorithm based on a simple biomechanical model, researchers and clinicians can estimate whole-body CoM displacements accurately during unperturbed quiet standing. …”
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Modeling of resonance of currents on higher harmonics with non-stationary mode of power supply system operation by D. V. Kovalenko, L. A. Faifer, B. Yu. Kiselyov, A. O. Shepelev, P. S. Smirnov, V. I. Surovtsev

“…In addition to simulating the mode of parallel resonance arising at frequencies close to the frequencies of higher harmonics, the proposed algorithm determines all possible resonance frequencies at which the parallel resonance condition under different assumptions can be satisfied, as well as the relative error of calculation for different cases: when all the components of complex impedances are taken into account; without taking into account the active components of the resistance; taking into account the active component of the resistance of the transformer, but not taking into account the resistance of the loads; without taking into account the active component of the resistance of the transformer and without taking into account the resistance of the loads. …”
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Patch-Level and Neighborhood-Dependency Spatial Optimization Method (PNO): Application to Urban Land-Use Planning to Facilitate Both Socio-Economic and Environmental Development in... by Yuhan Cheng, Xiuyuan Zhang, Qi Zhou, Xiaoyan Dong, Shihong Du

“…The PNO represents land-use patterns in a graph structure, quantifies land-use patterns’ impacts on the population, economy, and land surface temperature, defines the spatiotemporal constraints of land-use optimization considering neighborhood-dependency and optimization sequences, and finally optimizes land uses and their spatial layouts based on a multi-objective genetic algorithm. Experiments were conducted in the urban area of Beijing, and the results suggested that, after optimization, the population and GDP can be improved by 667,323 people (4.72%) and USD 10.69 billion in products (2.75%) in the study area; meanwhile, the land surface temperature can be reduced by 0.12 °C (−0.32%). …”
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Method of Helicopter Turboshaft Engines’ Protection During Surge in Starting Mode by Denys Baranovskyi, Serhii Vladov, Maryna Bulakh, Victoria Vysotska, Viktor Vasylenko, Jan Czyżewski

“…The backpropagation algorithm with hyperparameter optimization via Bayesian optimization was used to train the network. …”
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An LDPC Encoder Architecture With Up to 47.5 Gbps Throughput for DVB-S2/S2X Standards by Decai Liu, Yanfei Luo, Yunfeng Li, Zhijie Wang, Zhengxuan Li, Qianwu Zhang, Junjie Zhang, Yingchun Li

“…In this paper, by extracting the periodicity of the parity-check matrix, we introduce a fast encoding algorithm that can efficiently process the multiplication of the information sequence and a large-dimensional sparse matrix, and propose an encoder architecture with low encoding delay and high throughput. …”
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Impact of climate change over distribution and potential range of chestnut in the Iberian Peninsula by Pedro Álvarez-Álvarez, Adrián Aviñoa-Arias, Adrián Aviñoa-Arias, Emilio Díaz-Varela, José Vicente López-Bao, José Carlos Pérez-Girón

“…The SDMs were constructed using the Random Forest algorithm.Results and DiscussionOur model achieved an accuracy of 86.82%, with high sensitivity (89.91%) and specificity (83.73%). …”
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Modeling Canopy Height of Forest–Savanna Mosaics in Togo Using ICESat-2 and GEDI Spaceborne LiDAR and Multisource Satellite Data by Arifou Kombate, Guy Armel Fotso Kamga, Kalifa Goïta

“…We tested four methods: Random Forest (RF), Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost) and Deep Neural Network (DNN). The RF algorithm obtained the best predictions using 98% relative height (RH98). …”
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Enhancing smart home environments: a novel pattern recognition approach to ambient acoustic event detection and localization by Ahsan Shabbir, Abdul Haleem Butt, Taha Khan, Lorenzo Chiari, Ahmad Almadhor, Vincent Karovic

“…Random forest and linear discriminant analysis classifiers were employed for event detection, while the estimation signal parameters through rational-in-variance techniques (ESPRIT) algorithm was used for sound source localization.ResultsThe study achieved high detection accuracy, with random forest and linear discriminant analysis classifiers attaining 95% and 87%, respectively, for event detection. …”
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Deep Learning Unravels Differences Between Kinematic and Kinetic Gait Cycle Time Series from Two Control Samples of Healthy Children Assessed in Two Different Gait Laboratories by Alfonso de Gorostegui, Damien Kiernan, Juan-Andrés Martín-Gonzalo, Javier López-López, Irene Pulido-Valdeolivas, Estrella Rausell, Massimiliano Zanin, David Gómez-Andrés

“…To address the inter-laboratory differences, we explored various pre-processing methods and time series properties that may have been detected by the algorithm. We found that the standardization of the time series values was a successful approach to decrease the ability of the model to distinguish between the two centers. …”
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Development and validation of a risk prediction model for acute kidney injury in coronary artery disease by Ming Ye, Chang Liu, Duo Yang, Hai Gao

“…To refine predictor selection, we applied a random forest algorithm. The top 10 variables, including admission to the surgical department, EGFR, hemoglobin, and others, were incorporated into a logistic regression-based prediction model. …”
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A novel adaptive droop-based SoC balancing control strategy for distributed energy storage system in DC microgrid by Liangliang Guo, Xinrui Liu, Xinyu Li, Rui Wang, Hanwen Ren, Zhiliang Wang, Qiuye Sun

“…In order to realize low-bandwidth communication in sparse communication networks, multi-agent consensus algorithm (MACA) is used to perform local estimation of global mean variables. …”
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Development of a respiratory virus risk model with environmental data based on interpretable machine learning methods by Shuting Shi, Haowen Lin, Leiming Jiang, Zhiqi Zeng, ChuiXu Lin, Pei Li, Yinghua Li, Zifeng Yang

“…We utilized the CRFC algorithm, a random forest-based method for multi-label classification, to predict the presence of various respiratory viruses. …”
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R-CNN Based Vehicle Object Detection via Segmentation Capabilities in Road Scenes by Bisma Riaz Chughtai, Haifa F. Alhasson, Mohammed Alnusayri, Mohammed Alatiyyah, Hanan Aljuaid, Ahmad Jalal, Jeongmin Park

“…We propose a novel approach that leverages state-of-the-art machine learning and deep learning algorithms to enhance accuracy and efficiency. The proposed model comprises five stages. …”
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Predicting the clinical subcutaneous absorption rate constant of monoclonal antibodies using only the primary sequence: a machine learning approach by Ronghua Bei, Justin Thomas, Shiven Kapur, Mahlet Woldeyes, Adam Rauk, Jason Robarge, Jiangyan Feng, Kaoutar Abbou Oucherif

“…Once trained, our model (enabled by the XGBoost algorithm in machine learning) can predict the ka of a mAb following a subcutaneous injection using in silico molecular properties alone (generated from the primary sequence). …”
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Device Modeling Based on Cost-Sensitive Densely Connected Deep Neural Networks by Xiaoying Tang, Zhiqiang Li, Lang Zeng, Hongwei Zhou, Xiaoxu Cheng, Zhenjie Yao

“…Therefore, this work proposes a machine learning-based device modeling algorithm to capture the complex nonlinear relationship between parameters and electrical characteristics of gate-all-around (GAA) nanowire field-effect transistors (NWFETs) from technology computer-aided design (TCAD) simulation results. …”
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Enhanced Seismic Structural Reliability on Reinforced Concrete Buildings by Using Buckling Restrained Braces by Victor Baca, Juan Bojórquez, Edén Bojórquez, Herian Leyva, Alfredo Reyes-Salazar, Sonia E. Ruiz, Antonio Formisano, Leonardo Palemón, Robespierre Chávez, Manuel Barraza

“…For this aim, three traditional RC framed structures with 3, 6, and 9 story levels are designed by using the well-known technique nondominated sorting genetic algorithm (NSGA-II) in order to reduce the cost and maximize the seismic performance. …”
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Pharmacotherapy for POAG. Individual approach by S.V. Balalin, V.P. Fokin

“…Tolerant IOP calculations will help to adjust treatment in time to achieve individual IOP normal ranges, to predict glaucoma stabilization or progression as well glaucoma progression rate. The algorithm of treatment strategy for POAG is described.…”
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