Understanding the environmental health implications of tourism on carbon emissions in China by Jinhua Shao, Sheng Fang, Meiling Zhao, Wanxin Qian, Cai Wang

“…Studying the impact of China’s tourism industry on carbon emissions is of great significance in scientifically formulating emission reduction policies and helping China to realize its carbon reduction goals. …”
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Rapid and Nondestructive Identification of Origin and Index Component Contents of Tiegun Yam Based on Hyperspectral Imaging and Chemometric Method by Yue Zhang, Yuan Li, Cong Zhou, Junhui Zhou, Tiegui Nan, Jian Yang, Luqi Huang

“…The optimal residual predictive deviation (RPD) values of starch, polysaccharide, and protein prediction models selected in this study were 5.21, 3.21, and 2.94, respectively. …”
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External validation of the PAR-Risk Score to assess potentially avoidable hospital readmission risk in internal medicine patients. by Lukas Higi, Angela Lisibach, Patrick E Beeler, Monika Lutters, Anne-Laure Blanc, Andrea M Burden, Dominik Stämpfli

“…Univariable logistic regression was used to predict potentially avoidable readmissions (PARs), as identified by the SQLape algorithm. …”
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Comparing machine learning approaches for estimating soil saturated hydraulic conductivity. by Ali Akbar Moosavi, Mohammad Amin Nematollahi, Mohammad Omidifard

“…Since the associated laboratory/field experiments are time-consuming and labor-intensive, pedotransfer functions (PTFs) that rely on statistical predictors are usually integrated with the existing measurements to predict Kfs in other areas of the field. In this study some of the most appropriate machine learning approaches, including variants of artificial neural networks (ANNs) were used for predicting Kfs by some easily measurable soil attributes. …”
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Identification and validation of hub m7G-related genes and infiltrating immune cells in osteoarthritis based on integrated computational and bioinformatics analysis by Zhenhui Huo, Chongyi Fan, Kehan Li, Chenyue Xu, Yingzhen Niu, Fei Wang

“…Functional enrichment, drug target prediction, and target gene-related miRNA prediction were performed for these genes. …”
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Charge Diagnostics and State Estimation of Battery Energy Storage Systems Through Transformer Models by Rolando Antonio Gilbert Zequera, Anton Rassolkin, Toomas Vaimann, Ants Kallaste

“…Time series and state estimation are the Supervised Learning techniques executed for charge diagnostics and State of Charge (SOC) predictions. The results show remarkable performance metrics of the Transformer models, achieving over 94% accuracy in Model evaluation compared to traditional Deep Learning algorithms.…”
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Rapid Identification of Nine Easily Confused Mineral Traditional Chinese Medicines Using Raman Spectroscopy Based on Support Vector Machine by Jing Ming, Long Chen, Yan Cao, Chi Yu, Bi-Sheng Huang, Ke-Li Chen

“…The identification model was subsequently built by the SVM algorithm. The 3-fold cross validation (3-CV) accuracy of the SVM model established based on extracting characteristic intensity data from spectra pretreated by first derivation was 98.61%, and the prediction accuracies of the training set and validation set were 100%. …”
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Eco-Driving Optimal Controller for Autonomy Tracking of Two-Wheel Electric Vehicles by Y. Bello, T. Azib, C. Larouci, M. Boukhnifer, N. Rizoug, D. Patino, F. Ruiz

“…The eco-driving profiles are algorithms able to use additional information in order to create recommendations or limitation over the driver capabilities. …”
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Joint Optimal Production Planning for Complex Supply Chains Constrained by Carbon Emission Abatement Policies by Longfei He, Zhaoguang Xu, Zhanwen Niu

“…We focus on the joint production planning of complex supply chains facing stochastic demands and being constrained by carbon emission reduction policies. We pick two typical carbon emission reduction policies to research how emission regulation influences the profit and carbon footprint of a typical supply chain. …”
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Clustering-Based Thermography for Detecting Multiple Substances Under Large-Scale Floating Covers by Yue Ma, Benjamin Steven Vien, Thomas Kuen, Wing Kong Chiu

“…The method integrates infrared thermal imaging with a clustering algorithm to predict the distribution of various substrates beneath Traditional outdoor large-scale opaque geomembranes, using solar radiation as an excitation source. …”
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Hydrogen Enhancement in Syngas Through Biomass Steam Gasification: Assessment with Machine Learning Models by Yunye Shi, Diego Mauricio Yepes Maya, Electo Silva Lora, Albert Ratner

“…These algorithms outperform traditional models by accurately handling complex, high-dimensional data more efficiently and cost-effectively. …”
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Gene expression-based modeling of overall survival in Black or African American patients with lung adenocarcinoma by Bin Zhu, Stephanie S. McHale, Michelle Van Scoyk, Gregory Riddick, Pei-Ying Wu, Chu-Fang Chou, Ching-Yi Chen, Robert A. Winn

“…Unsupervised machine learning algorithms stratified B/AA patients into groups with distinct survival outcomes, while supervised algorithms demonstrated a higher accuracy in predicting survival for B/AA LUAD patients compared to white patients.DiscussionIn total, this study explored OS-associated genes and pathways specific for B/AA LUAD patients. …”
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Integrating artificial intelligence into thermodynamics: A new paradigm for sustainable future by Marwan Al-Raeei

“…By integrating machine learning algorithms and statistical techniques into predictive modeling, we demonstrate that it is possible to develop highly accurate models that forecast performance based on historical data. …”
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AI-powered Somatic Cancer Cell Analysis for Early Detection of Metastasis: The 62 principal Cancer Types by Sandile Buthelezi, Solly Matshonisa Seeletse, Taurai Hungwe, Vimbai Mbirimi-Hungwe

“…Furthermore, the models demonstrated exceptional predictive accuracy, with XGBoost and Support Vector Machines achieving an accuracy of 0.95. …”
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Rapid in-air ultrasound holography measurement and camera-in-the-loop generation using thermography by Zak Morgan, Youngjun Cho, Sriram Subramanian

“…Finally, we integrate this with holography algorithms to propose a camera-in-the-loop algorithm that employs real-time measurement, enabling targeted data acquisition and on-line training of acoustic holography algorithms. …”
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Heisenberg-Limited Adaptive Gradient Estimation for Multiple Observables by Kaito Wada, Naoki Yamamoto, Nobuyuki Yoshioka

“…The proposed method is an adaptive version of the quantum gradient-estimation algorithm and has a resource-efficient implementation due to its adaptiveness. …”
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Quality assessment of chicken using machine learning and electronic nose by Hassan Anwar, Talha Anwar

“…This study investigates the use of an electronic nose system—a sensor array that detects odors and generates data, which is then analyzed by machine learning algorithms to predict chicken freshness. An electronic nose system was developed using six MQ gas sensors and one humidity temperature sensor. …”
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Application of Machine Learning for Target Selection and Acid Treatment Design by I. I. Mannanov, M. A. Varfolomeev, G. R. Ganieva, A. R. Gimaeva, R. R. Giniyatullin

“…These algorithms significantly simplify the tasks of acid treatment design.…”
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Computerized Adaptive Testing Framework Based on Excitation Block and Gumbel-Softmax by Chengsong Liu, Yan Wei

“…In addition, most algorithms primarily focus on accurately predicting students’ abilities, neglecting critical factors such as concept diversity and question exposure rate, which are essential for model effectiveness. …”
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Short-Term Electrical Load Forecasting in Power Systems Using Deep Learning Techniques by Nihat Pamuk

“…Using a real dataset for one-step forecasting, this article compares three deep learning algorithms for short-term power load forecasting: LSTM, GRUs, and CNN. …”
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