Programmable friction control in 3D printed patterned multi-materials: a flexible design strategy by Xinle Yao, Yuxiong Guo, Mingyang Wang, Yaozhong Lu, Zhibin Lu, Xin Jia, Yu Gao, Xiaolong Wang

“…Accurate prediction and control of friction are vital for conserving energy, driving demand for intelligent tribological systems with adaptive control. …”
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Exploring the typhoon intensity forecasting through integrating AI weather forecasting with regional numerical weather model by Hongxiong Xu, Yang Zhao, Zhao Dajun, Yihong Duan, Xiangde Xu

“…Abstract Recent advancements in artificial intelligence (AI) have notably enhanced global weather forecasting, yet accurately predicting typhoon intensity remains challenging. This is largely due to constraints inherent in regression algorithm properties including deep neural networks and inability of coarse resolution to capture the finer-scale weather processes. …”
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A Dynamic and Timely Point-of-Interest Recommendation Based on Spatio-Temporal Influences, Timeliness Feature and Social Relationships by Jun Zhu, Haifeng Lin, Zhinan Gou, Yiqing Xu, Hongying Liu, Ming Tang, Li Wang, Shu Li, Bing Hu

“…The experimental results reveal that our algorithm outperforms seven state-of-the-art recommenders in terms of prediction accuracy and system timeliness.…”
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Precision Imaging for Early Detection of Esophageal Cancer by Po-Chun Yang, Chien-Wei Huang, Riya Karmakar, Arvind Mukundan, Tsung-Hsien Chen, Chu-Kuang Chou, Kai-Yao Yang, Hsiang-Chen Wang

“…We employed the Yolov5 model, a state-of-the-art object detection algorithm, to predict early ECA based on the provided images. …”
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Drug repositioning framework using embedding drug-protein-disease similarities with graph convolution network and ensemble learning by Hanaa Torkey, Heba El-Behery, Abdel-Fattah Atti, Nawal El-Fishawy

“…The results achieved by our model using 10-fold cross-validation testing showed an improvement of 2.52 % in prediction accuracy, 4.2 % in recall, 3.94 % in AUC, and 3.6 % in F-score compared to state-of-the-art methods.…”
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Simultaneous Determination of Caffeine and Taurine in Energy Drinks by FT-MIR Spectroscopy Coupled with Multivariate Analysis by Marcela González-Vázquez, Ofelia Gabriela Meza-Márquez, Tzayhri Gallardo-Velázquez, Guillermo Osorio-Revilla, José Luis Velázquez Hernández, Maylet Hernández-Martínez

“…The taurine and caffeine content in the 50 samples ranged between 0 and 69.51 mg/100 mL and 14.92 and 1126.17 mg/100 mL, respectively. The best prediction model was obtained with the partial least squares (PLS1) algorithm; for taurine, the following values were obtained: determination coefficient of calibration (Rc2) = 0.9999, standard error of calibration (SEC) = 0.15, determination coefficient of validation (Rv2) = 0.9997, and standard error of prediction (SEP) = 0.16; for caffeine, Rc2 = 0.9999, SEC = 0.26, Rv2 = 0.9999, and SEP = 0.32. …”
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Using Satellites to Monitor Soil Texture in Typical Black Soil Areas and Assess Its Impact on Crop Growth by Liren Gao, Yuhong Zhang, Deqiang Zang, Qian Yang, Huanjun Liu, Chong Luo

“…The results show that (1) the order of prediction accuracy differs for different soil texture types; April is determined to have the highest prediction accuracy for silt and sand, while May exhibits the greatest accuracy for clay. (2) Adding environmental variables can significantly improve the accuracy of soil texture predictions; the root mean square error (RMSE) has decreased to varying degrees (silt: 0.84; clay: 0.04; sand: 0.85). (3) Soybean growth has the strongest response to soil texture; clay grain is the key factor affecting crop growth in drought scenarios, and sand grain is the dominant factor influencing flooding. …”
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Experimental Study on Evaluation of Organization Collaboration in Prefabricated Building Construction by Dingjing Bao, Yuan Chen, Shuai Wan, Jinlai Lian, Ying Lei, Kaizhe Chen

“…The knowledge-driven part of this evaluation system used an evaluation model based on the analytic hierarchy process (AHP), while the data-driven part used a prediction model based on the BO-XGBoost algorithm to verify the validity of the AHP-based model. …”
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Identifying and Validating an Acidosis-Related Signature Associated with Prognosis and Tumor Immune Infiltration Characteristics in Pancreatic Carcinoma by Pingfei Tang, Weiming Qu, Dajun Wu, Shihua Chen, Minji Liu, Weishun Chen, Qiongjia Ai, Haijuan Tang, Hongbing Zhou

“…The tumor immune infiltrating pattern was characterized by the single-sample gene set enrichment analysis (ssGSEA) method, and the prediction of immunotherapy responsiveness was conducted using the tumor immune dysfunction and exclusion (TIDE) algorithm. …”
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Study on Outdoor Spectral Inversion of Winter Jujube Based on BPDF Models by Yabei Di, Jinlong Yu, Huaping Luo, Huaiyu Liu, Lei Kang, Yuesen Tong

“…The spectra were inverted using four semi-empirical BPDF models, Nadal–Breon, Litvinov, Maignan and Xie–Cheng, and the corrected spectra were obtained by mean fusion. The quality prediction models are subsequently combined with the competitive adaptive reweighting algorithm (CARS) and partial least squares (PLS). …”
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PIC2O-Sim: A physics-inspired causality-aware dynamic convolutional neural operator for ultra-fast photonic device time-domain simulation by Pingchuan Ma, Haoyu Yang, Zhengqi Gao, Duane S. Boning, Jiaqi Gu

“…Directly applying off-the-shelf models to predict the optical field dynamics shows unsatisfying fidelity and efficiency since the model primitives are agnostic to the unique physical properties of Maxwell equations and lack algorithmic customization. …”
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Electric Power Consumption Forecasting Models and Spatio-Temporal Dynamic Analysis of China’s Mega-City Agglomerations Based on Low-Light Remote Sensing Imagery Incorporating Socia... by Cuiting Li, Dongmei Yan, Shuo Chen, Jun Yan, Wanrong Wu, Xiaowei Wang

“…Utilizing 2017–2021 NPP/VIIRS low-light remote sensing imagery to extract total nighttime light data, this study proposed an EPC prediction method based on the K-Means clustering algorithm combined with multiple indicators integrated with socio-economic factors. …”
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Intelligent Vehicle Scheduling and Routing for a Chain of Retail Stores: A Case Study of Dhaka, Bangladesh by M. Azizur Rahman, Al-Amin Hossain, Binoy Debnath, Zinnat Mahmud Zefat, Mohammad Sarwar Morshed, Ziaul Haq Adnan

“…An android application, Intelligent Route Optimizer, is developed using the shortest path first algorithm based on the Dijkstra algorithm. The vehicle navigation scheme is programmed to change the direction according to the shortest possible path in the google map generated by the intelligent routing optimizer. …”
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Feature Importance Analysis for Compressive Bearing Capacity of HSCM Piles Based on GA-BPNN by Fangzhou Chu, Jiakuan Ma, Yang Luan, Shilin Chen

“…To address the complex pile–soil interaction mechanisms in predicting the compressive bearing capacity of HSCM piles (Helix Stiffened Cement Mixing piles) in marine soft soil regions, this study proposes an intelligent prediction method based on a GA-BPNN (Genetic Algorithm-Optimized Back Propagation Neural Network). …”
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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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Modeling of CO2 solubility and partial pressure in blended diisopropanolamine and 2-amino-2-methylpropanol solutions via response surface methodology and artificial neural network by Zohreh Khoshraftar

“…The accuracy of the predictions was notably high, with coefficients of determination of 0.99581 for CO2 solubility and 0.99839 for CO2 partial pressure, achieved using the Levenberg-Marquardt algorithm. …”
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Optimization of the heat recovery performance of enhanced geothermal system based on PSO-GA-BP neural networks and analytic hierarchy process by Ling Zhou, Jingchao Sun, Yanjun Zhang, Yunjuan Chen, Honglei Lei

“…Based on the numerical simulation data, optimized Back-Propagation Neural Network (BPNN) prediction models combining the Particle Swarm Optimization (PSO) and the Genetic Algorithm (GA) were developed to investigate the impact of various factors on the heat recovery performance of a three-horizontal-well EGS in the Zhacang geothermal field. …”
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Human Pose Estimation and Event Recognition via Feature Extraction and Neuro-Fuzzy Classifier by Muhammad Hanzla, Naif S. Alshammari, Shuaa S. Alharbi, Wasim Wahid, Nouf Abdullah Almujally, Ahmad Jalal, Hui Liu

“…Key point features are characterized through the degree of freedom, human landmark detection via the HSV algorithm, and angular point analysis using the media pipe algorithm. …”
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Identification of testicular cancer with T2-weighted MRI-based radiomics and automatic machine learning by Liang Wang, PeiPei Zhang, Yanhui Feng, Wenzhi Lv, Xiangde Min, Zhiyong Liu, Jin Li, Zhaoyan Feng

“…We developed an AutoML method based on the tree-based pipeline optimization tool (TPOT) algorithm to construct a discriminant model. The best pipeline was determined through 100 repeated operations using a 5-fold cross-validation algorithm in TPOT. …”
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Electric vehicle path optimization research based on charging and switching methods under V2G by Haoran Liu, Aobei Zhang

“…Moreover, we introduce a robust algorithmic approach for estimating battery degradation costs, meticulously accounting for ambient temperature fluctuations and discharge depth. …”
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