Morphometric and thermo-physiological diversity in two chicken genotypes kept by rural farmers under tropical conditions by Elijah Akumbugu Faith, Danlami Moses Ogah, Abdulmojeed Yakubu, Oladeji Bamidele

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An Assessment of the Bearing Capacity of High-Strength-Concrete-Filled Steel Tubular Columns Through Finite Element Analysis by Leonardo André Rossato, Alexandre Rossi, Carlos Humberto Martins, Gustavo de Miranda Saleme Gidrão, Laura Silvestro, Rúbia Mara Bosse

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Prediction of Variable-speed Compressor Power Based on Particle Swarm Optimization and Back Propagation Neural Network by Gong Qijian, Guo Yabin, Chen Huanxin, Cheng Yahao, Xu Shenming

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FATIGUE LIFE PREDICTION AND EXPERIMENTAL STUDY OF ALUMINUM ALLOY WHEEL HUB CONSIDERING DAMAGE ACCUMULATION (MT) by WANG ZhaoHua, WU FengHe, LIU JiaLiang, LIAN Hui

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Bus Arrival Time Prediction Using Wavelet Neural Network Trained by Improved Particle Swarm Optimization by Yuanwen Lai, Said Easa, Dazu Sun, Yian Wei

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Cross-Scene Multi-Object Tracking for Drones: Leveraging Meta-Learning and Onboard Parameters with the New MIDDTD by Chenghang Wang, Xiaochun Shen, Zhaoxiang Zhang, Chengyang Tao, Yuelei Xu

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Spatio-Temporal Transformer Networks for Inland Ship Trajectory Prediction with Practical Deficient Automatic Identification System Data by Youan Xiao, Xin Luo, Tengfei Wang, Zijian Zhang

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The global burden of lead exposure-related ischemic stroke: based on Bayesian age-period-cohort analysis by Xiaofang Chen, Lihua Zhao, Xiaxia Wu, Dan Chen, Mingya Yao

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Body size prediction in scorpions: a phylogenetic comparative examination of linear measurements of individual body parts by Stênio Í. A. Foerster

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Detection and Prediction of Wind and Solar Photovoltaic Power Ramp Events Based on Data-Driven Methods: A Critical Review by Jie Zhang, Xinchun Zhu, Yigong Xie, Guo Chen, Shuangquan Liu

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Radial Basis Function Neural Network with Particle Swarm Optimization Algorithms for Regional Logistics Demand Prediction by Zhineng Hu, Yixin Zhang, Liming Yao

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Combining Charlson comorbidity and VACS indices improves prognostic accuracy for all-cause mortality for patients with and without HIV in the Veterans Health Administration by Kathleen A. McGinnis, Amy C. Justice, Amy C. Justice, Vincent C. Marconi, Vincent C. Marconi, Maria C. Rodriguez-Barradas, Maria C. Rodriguez-Barradas, Ronald G. Hauser, Ronald G. Hauser, Krisann K. Oursler, Krisann K. Oursler, Sheldon T. Brown, Kendall J. Bryant, Janet P. Tate, Janet P. Tate, for the Veterans Aging Cohort Study

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TourismNER: A Tourism Named Entity Recognition method based on entity boundary joint prediction by Kai Gao, Jiahao Zhou, Yunxian Chi, Yimin Wen

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Machine Learning-Based Prediction of In-Hospital Mortality in Severe COVID-19 Patients Using Hematological Markers by Rongrong Dong, Han Yao, Taoran Chen, Wenjing Yang, Qi Zhou, Jiancheng Xu

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Deep Neural Networks Based on Sp7 Protein Sequence Prediction in Peri-Implant Bone Formation by Pradeep Kumar Yadalam, Carlos M. Ardila

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Improving kinetic modelling of magnesium hydrogenation by including interfacial polarisation and interstitial hydrogen clustering behaviour within the site availability model by Marcus J. Adams, Alastair Stuart, Gavin S. Walker, David M. Grant

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Socially Responsible Investment Portfolio Construction with a Double-Screening Mechanism considering Machine Learning Prediction by Jun Zhang, Xuedong Chen

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An Advanced Approach for Predicting Workpiece Surface Roughness Using Finite Element Method and Image Processing Techniques by Taoming Chen, Chun Li, Zhexiang Zou, Qi Han, Bing Li, Fengshou Gu, Andrew D. Ball

“…By employing range and regression analyses methods, this study quantitatively evaluates the interdependencies among cutting parameters, forces, temperatures, and roughness, subsequently formulating a multivariate regression model to predict surface roughness. Finally, a turning experiment under actual working conditions was conducted, confirming the model’s capacity to predict the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>R</mi></mrow><mrow><mi>a</mi></mrow></msub></mrow></semantics></math></inline-formula> trend with an accuracy of 85.07%. …”
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On the Use of an Improved Artificial Fish Swarm Algorithm-Backpropagation Neural Network for Predicting Dam Deformation Behavior by Bo Dai, Hao Gu, Yantao Zhu, Siyu Chen, E. Fernandez Rodriguez

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Machine Learning-enhanced loT and Wireless Sensor Networks for predictive analysis and maintenance in wind turbine systems by Lei Gong, Yanhui Chen

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