Timing of activation of different inspiratory muscles during incremental inspiratory loading in healthy adults: A cross-sectional study by Umi Matsumura, Antenor Rodrigues, Tamires Mori, Peter Rassam, Marine Van Hollebeke, Dmitry Rozenberg, Laurent Brochard, Ewan C Goligher, Darren Roblyer, W Darlene Reid

“…# Purpose To evaluate whether the onset and duration of electromyography (EMG) activity of different inspiratory muscles vary during an incremental inspiratory threshold loading (ITL) in healthy adults and whether it is associated with dyspnea and inspiratory mouth pressure (Pm) at task failure…”
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Filtration of histogram evaluation of probability density based on fuzzy data accessibility to a grouping interval by A. V. Ausiannikau, V. M. Kozel

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Detection of Water Surface Using Canny and Otsu Threshold Methods with Machine Learning Algorithms on Google Earth Engine: A Case Study of Lake Van by Pinar Karakus

“…In 2017, the highest producer accuracy, user accuracy, overall accuracy, kappa, and f score evaluation criteria were all 100% with the SVM algorithm and AWEI. …”
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Quantitative analysis of deep learning-based denoising model efficacy on optical coherence tomography images with different noise levels by Furkan Kirik, Farid Iskandarov, Kamile Melis Erturk, Hakan Ozdemir

“…Background: To quantitatively evaluate the effectiveness of the Noise2Noise (N2N) model, a deep learning (DL)-based noise reduction algorithm, on enhanced depth imaging-optical coherence tomography (EDI-OCT) images with different noise levels. …”
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Development and validation of a prediction model for coronary heart disease risk in depressed patients aged 20 years and older using machine learning algorithms by Yicheng Wang, Yicheng Wang, Yicheng Wang, Chuan-Yang Wu, Hui-Xian Fu, Jian-Cheng Zhang, Jian-Cheng Zhang, Jian-Cheng Zhang

“…Several evaluation metrics were employed to assess and compare the performance of eight different machine learning models, aiming to identify the most effective algorithm for predicting coronary heart disease risk in individuals with depression. …”
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CECT-Based Radiomic Nomogram of Different Machine Learning Models for Differentiating Malignant and Benign Solid-Containing Renal Masses by Qian L, Fu B, He H, Liu S, Lu R

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Data Collection in Studies on Internet of Things (IoT), Wireless Sensor Networks (WSNs), and Sensor Cloud (SC): Similarities and Differences by Ihsan Ali, Ismail Ahmedy, Abdullah Gani, Muhammad Umair Munir, Mohammad Hossein Anisi

“…Nine novel contributions are found with models, algorithms, and frameworks being the most utilized by the selected studies. …”
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Formulating and Solving Routing Problems on Quantum Computers by Stuart Harwood, Claudio Gambella, Dimitar Trenev, Andrea Simonetto, David Bernal Neira, Donny Greenberg

“…Finally, the solutions obtained on simulated quantum devices demonstrate the relative benefits of different algorithms and their robustness when put into practice.…”
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Numercial modeling for enhanced heat transfer efficiency of spiral coils with supercritical fluid flow under different operating conditions by Xinling Wang, Naeim Farouk, Xiaoqing Fu, Pradeep Kumar Singh, Guo Xu, Fahad M. Alhomayani, Baseem Khan, Fawaz S. Alharbi, Barno Sayfutdinovna Abdullaeva, Laith H. Alzubaidi, Yasser Elmasry, Hakim A.L. Garalleh

“…The thermophysical properties of carbon dioxide are evaluated within a defined range of operating conditions (298. 15 K < T < 455 K and 8 MPa < p < 10 MPa). …”
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A framework for counterfactual analysis, strategy evaluation, and control of epidemics using reproduction number estimates. by Baike She, Rebecca Lee Smith, Ian Pytlarz, Shreyas Sundaram, Philip E Paré

“…Building on this mechanism, the framework 2) proposes a method to reverse engineer the effective reproduction number under different strengths of the intervention strategy. In addition, based on the method that quantifies the impact of the testing-for-isolation strategy on the basic reproduction number, the framework 3) proposes a closed-loop control algorithm that uses the effective reproduction number both as feedback to indicate the severity of the spread and as the control goal to guide adjustments in the intensity of the intervention. …”
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Light adaptive image enhancement for improving visual analysis in intercropping cultivation by Wei Zhong, Wanting Yang, Yunfei Wang, Xiang Dong, Xiaowen Wang, Weidong Jia, Mingxiong Ou, Mingde Yan

“…Based on the height difference between crops, solar elevation angle, and light intensity at the top of the soybean canopy, an illumination compensation regression model was developed. …”
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The Evaluation and Promotion Strategy of TSC for Distribution System with New Energy under Power Market Environment by BAI Hao, WANG Yu-shan, ZHOU Chang-cheng, PAN Shu-hui, YE lin-hao, CAI Jian-yi

“…Secondly, in order to explore the impact of power market ti·ansactions, the improved repeated power flow method is used to calculate the maximum power supply capacity (TSC) and mru·ket revenue of the distribution network under different power transaction scenarios. Finally, for scenarios where the TSC does not meet the standard, the improved PSO optimization algorithm is used to re-dispatch and improve TSC. …”
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Toward a Clinical Decision Support System for Monitoring Therapeutic Antituberculosis Medical Drugs in Tanzania (Project TuberXpert): Protocol for an Algorithm' Development and Imp... by Yann Thoma, Annie E Cathignol, Yuan J Pétermann, Margaretha L Sariko, Bibie Said, Chantal Csajka, Monia Guidi, Stellah G Mpagama

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Classification evaluation and improvement of airborne PolSAR images for land use mapping using deep learning by Jiafeng Wang, Yongjiu Feng, Xiaohua Tong, Zhenkun Lei, Mengrong Xi, Yi Zhou, Panli Tang

“…The classification performance of different algorithms was evaluated by the overall accuracy. …”
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Prediction of carbon dioxide emissions from Atlantic Canadian potato fields using advanced hybridized machine learning algorithms – Nexus of field data and modelling by Muhammad Hassan, Khabat Khosravi, Aitazaz A. Farooque, Travis J. Esau, Alaba Boluwade, Rehan Sadiq

“…Greedy stepwise (GS) approach was implemented for feature selection. Finally, different qualitative (scatter plot, line graph, Taylor diagram, box plot, and Rug plot), and quantitative (uncertainty analysis, root mean square error (RMSE), percent of BIAS (PBIAS), Nash Sutcliff efficiency (NSE) and RMSE-observations standard deviation ratio (RSR)) techniques were used for model evaluation and comparison. …”
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Comprehensive benefits evaluation of low impact development using scenario analysis and fuzzy decision approach by Ting Ni, Xiaohong Zhang, Peng Leng, Mark Pelling, Jiuping Xu

“…The framework’s novelty lies in the integration of the hesitant fuzzy weighted average algorithm to handle subjective uncertainties in expert judgment and the incorporation of multi-return period scenarios to enhance the robustness of the evaluation. …”
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Multi-Criteria Analysis of Steel–Concrete–Steel Slab Performance: Dynamic Response Assessment Under Post-Fire Explosion by Shijie Zhang, Zhenfu Chen, Yizhi Liu, Qiuwang Tao, Dan Wu, Pinyu Zou

“…This article uses ABAQUS 2020 finite element software and combines the different advantages of the implicit heat transfer algorithm and explosion display algorithm to establish a numerical simulation method for dynamic analysis of SCS slab under explosion after fire. …”
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A robust method for evaluating the potentials of 15-minute cities: Implications for sustainable urban futures by Jianying Wang, Mei-Po Kwan, Gezhi Xiu, Fangxu Deng

“…However, the achievability of this concept for different cities varies considerably across diverse population distributions, urban contexts, and development priorities. …”
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Evaluation of Shelf Life Prediction for Broccoli Based on Multispectral Imaging and Multi-Feature Data Fusion by Xiaoshuo Cui, Xiaoxue Sun, Shuxin Xuan, Jinyu Liu, Dongfang Zhang, Jun Zhang, Xiaofei Fan, Xuesong Suo

“…Multi-feature data fusion of spectral image information and physical and chemical parameters were combined with different machine learning methods to predict and evaluate the shelf life of broccoli.…”
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TAL-SRX: an intelligent typing evaluation method for KASP primers based on multi-model fusion by Xiaojing Chen, Xiaojing Chen, Jingchao Fan, Jingchao Fan, Shen Yan, Longyu Huang, Longyu Huang, Longyu Huang, Guomin Zhou, Guomin Zhou, Jianhua Zhang, Jianhua Zhang

“…To address the above problems, we proposed a typing evaluation method for KASP primers by integrating deep learning and traditional machine learning algorithms, called TAL-SRX. …”
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