Modeling Spatial Data with Heteroscedasticity Using PLVCSAR Model: A Bayesian Quantile Regression Approach by Rongshang Chen, Zhiyong Chen

“…We apply a Bayesian quantile regression (BQR) of the partially linear varying coefficient spatial autoregressive (PLVCSAR) model for spatial data to improve the prediction of performance. It can be used to capture the response of covariates to linear and nonlinear effects at different quantile points. …”
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Research on intelligent routing with VAE-GAN in the internet of body. by Song Qian, Tianping Zhang, Siping Hu

“…The traditional artificial intelligence routing algorithm cannot deal with the low model prediction accuracy and poor generalization ability caused by large noise and small data volume. …”
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Exploring Protein Conformational Changes Using a Large‐Scale Biophysical Sampling Augmented Deep Learning Strategy by Yao Hu, Hao Yang, Mingwei Li, Zhicheng Zhong, Yongqi Zhou, Fang Bai, Qian Wang

“…Abstract Inspired by the success of deep learning in predicting static protein structures, researchers are now actively exploring other deep learning algorithms aimed at predicting the conformational changes of proteins. …”
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Energy Efficiency Maximization through Cooperative Transmit and Receive Antenna Selection for Multicell MU-MIMO System by Yanjie Dong, Yinghai Zhang, Weidong Wang, Gaofeng Cui, Yang Yu

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Influence of Particle Size Distribution on the Physical Characteristics of Pore-Filling Hydrate-Bearing Sediment by Peng Wu, Shenghua Yang, Le Wang, Xiangge Song, Yanghui Li

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Optimizing Deep Learning Models for Fire Detection, Classification, and Segmentation Using Satellite Images by Abdallah Waleed Ali, Sefer Kurnaz

“…The findings underscore the significant potential of optimized machine learning approaches in predicting extreme events, such as wildfires, and improving fire management strategies. …”
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Critical Review and Benchmark Proposal on FE Modeling for Patch Loading Resistance of Slender Steel Plate Girders in Launched Bridges by Marck Anthony Mora Quispe

“…It provides a comprehensive description of an FE model that accurately predicts both the load–displacement behavior and the patch loading resistance. …”
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LoD2 Building Reconstruction from Stereo Satellite Imagery using Deep Learning and Model-Driven Approach by Rojgar Qarani Ismael, Haval Sadeq

“…The suggested methodology is tested on the GeoEye-1 satellite imagery dataset for Erbil City, which is validated with ground truth data. The proposed algorithm presented promising results, it is shown that the model can predict building heights for ridge and eave to a mean absolute error of 0.70 m, and in the occluded area was approximately 1.0 m. …”
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Nasopharyngeal Carcinoma Subtype Discovery via Immune Cell Scores from Tumor Microenvironment by Yanbo Sun, Yun Liu, Hanqi Chu

“…Machine learning models, including random forest (RF) and support vector machine (SVM) algorithms, were constructed to predict the immune subtype. …”
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Modeling Estuarine Algal Bloom Dynamics with Satellite Data and Spectral Index-Based Classification by Mayya Podsosonnaya, Maria J. Schreider, Sergei Schreider

“…Although it is generally believed that algal blooms may be caused by a combination of excessive nutrients and temperature, their occurrences are hard to predict, and quantitative monitoring is a logistical challenge which requires the development of reliable and inexpensive techniques. …”
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Analytical Methods and Determinants of Frequency and Severity of Road Accidents: A 20-Year Systematic Literature Review by Carlos M. Ferreira-Vanegas, Jorge I. Vélez, Guisselle A. García-Llinás

“…This information is crucial for projecting further research on RTA analysis and developing computational and data visualization tools oriented to the automation of RTA predictions based on intelligent systems.…”
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The Use of Wearable Sensors and Machine Learning Methods to Estimate Biomechanical Characteristics During Standing Posture or Locomotion: A Systematic Review by Isabelle J. Museck, Daniel L. Brinton, Jesse C. Dean

“…This article provides a general overview of recent developments in using wearable sensors and ML to estimate or predict biomechanical characteristics such as center of pressure (CoP) and center of mass (CoM) motion. …”
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A human pose estimation network based on YOLOv8 framework with efficient multi-scale receptive field and expanded feature pyramid network by Shaobin Cai, Han Xu, Wanchen Cai, Yuchang Mo, Liansuo Wei

“…Abstract Deep neural networks are used to accurately detect, estimate, and predict human body poses in images or videos through deep learning-based human pose estimation. …”
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Non-Destructive Detection of Fillet Fish Quality Using MQ135 Gas Sensor and Neutrosophic Logic-Enhanced System by M. Y. Shams, M. R. Darwesh, Roheet Bhatnagar, N. S. A. Al-Sattary, A. A. Salama, M. S. Ghoname

“…Artificial intelligence algorithms were employed to predict quality and calculate regression coefficients. …”
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Machine Learning-Based Carbon Compliance Forecasting and Energy Performance Assessment in Commercial Buildings by Aditya Ramnarayan, Felipe de Castro, Andres Sarmiento, Michael Ohadi

“…The forecasts from the machine learning algorithms predicted that the portfolio of buildings would incur an annual average penalty of $31.7 million ($1.09/sq. ft.) and ~$348.7 million ($12.03/sq. ft.) over 11 years. …”
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Towards Reliable ECG Analysis: Addressing Validation Gaps in the Electrocardiographic R-Peak Detection by Syed Talha Abid Ali, Sebin Kim, Young-Joon Kim

“…To validate R-peak detectors, comparing the predicted results with reference annotations is crucial. …”
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Employing Streaming Machine Learning for Modeling Workload Patterns in Multi-Tiered Data Storage Systems by Edson Ramiro Lucas Filho, George Savva, Lun Yang, Kebo Fu, Jianqiang Shen, Herodotos Herodotou

“…Recently, different Machine-Learning (ML) algorithms have been used to model access patterns from complex workloads. …”
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Allocation of Oral Cholera Vaccines in Africa by Elisa M. Maffioli, Yutong Lu

“…Using machine learning algorithms, we assess the relative importance of socio-demographic, governance, and weather variables in predicting cholera outbreaks. …”
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Identification of mitophagy and ferroptosis-related hub genes associated with intracerebral haemorrhage through bioinformatics analysis by Yan Wang, Rufeng Wang, Jianzhong Zhu, Ling Chen

“…Hub genes were selected via STRING, MCODE, and MCC algorithms in Cytoscape. miRNAs targeting hubs were predicted using miRWalk 3.0, forming a miRNA-hub gene network. …”
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Thermoluminescence Properties of Plagioclase Mineral and Modelling of TL Glow Curves with Artificial Neural Networks by Mehmet Yüksel, Emre Ünsal

“…In addition, an artificial neural network (ANN) model was developed to predict TL glow curves using three optimization algorithms, including Levenberg–Marquardt (LM), Bayesian Regularization (BR), and Scaled Conjugate Gradient (SCG). …”
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