A Deep Graph-Embedded LSTM Neural Network Approach for Airport Delay Prediction by Weili Zeng, Juan Li, Zhibin Quan, Xiaobo Lu

“…Due to the strong propagation causality of delays between airports, this paper proposes a delay prediction model based on a deep graph neural network to study delay prediction from the perspective of an airport network. …”
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Retracted: Construction of Online Teaching Mode of College Sports Based on Neural Network Technology by International Transactions on Electrical Energy Systems

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Relationship between Angular Measurements and Facial Shape of Young Ivorians with Normal Dental Occlusion by Moussa Diomande, Jean-Bertin Beugre, Mariam Konaté Kady Koueita, Frédéric Vaysse

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Normalized Isometric Shoulder Strength as a Predictor of Ball Velocity in Youth Baseball Players by Amanda J Arnold, Charles A Thigpen, Paul F Beattie, Stacy L Fritz, Michael J Kissenberth, John M Tokish, Ellen Shanley

“…Changes in anthropometric measures, inherent in physically developing athletes, have been shown to impact strength measures, however normalization methodology is rarely reported. # PURPOSE The purposes of this study were to 1) compare the measurement properties of five potential methods for normalizing isometric shoulder strength in a cohort of 9-12 year old male baseball players and 2) examine the relationship between normalized isometric shoulder strength and ball velocity in a cohort of 9-12 year old male baseball players…”
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Modeling of Throughput in Production Lines Using Response Surface Methodology and Artificial Neural Networks by Federico Nuñez-Piña, Joselito Medina-Marin, Juan Carlos Seck-Tuoh-Mora, Norberto Hernandez-Romero, Eva Selene Hernandez-Gress

“…Response surface methodology and artificial neural network were used to develop predictive models to find optimal throughput values. 360 production rate values for different number of buffer slots and workstations were used to obtain a fourth-order mathematical model and four hidden layers’ artificial neural network. …”
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Application of convolutional neural networks trained on optical images for object detection in radar images by V.A. Pavlov, A.A. Belov, S.V. Volvenko, A.V. Rashich

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Global Robust Exponential Dissipativity for Interval Recurrent Neural Networks with Infinity Distributed Delays by Xiaohong Wang, Huan Qi

“…This paper is concerned with the robust dissipativity problem for interval recurrent neural networks (IRNNs) with general activation functions, and continuous time-varying delay, and infinity distributed time delay. …”
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Finite Element Analysis of Normal Pressure Hydrocephalus: Influence of CSF Content and Anisotropy in Permeability by K. Shahim, J.-M. Drezet, J.-F. Molinari, R. Sinkus, S. Momjian

“…Hydrocephalus is a cerebral disease where brain ventricles enlarge and compress the brain parenchyma towards the skull leading to symptoms like dementia, walking disorder and incontinence. The origin of normal pressure hydrocephalus is still obscure. In order to study this disease, a finite element model is built using the geometries of the ventricles and the skull measured by magnetic resonance imaging. …”
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p-Uniform Convexity and q-Uniform Smoothness of Absolute Normalized Norms on ℂ2 by Tomonari Suzuki

“…We next give a formulation on absolute normalized norms on ℂ2. Using these, we present some examples of Banach spaces. …”
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Mechanisms for dysregulation of excitatory-inhibitory balance underlying allodynia in dorsal horn neural subcircuits. by Alexander G Ginsberg, Scott F Lempka, Bo Duan, Victoria Booth, Jennifer Crodelle

“…These circuits are hypothesized to be part of the neural pathways that mediate two different types of allodynia: static and dynamic. …”
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Follow-Up and Risk Assessment in Patients with Myocardial Infarction Using Artificial Neural Networks by Tatjana Gligorijević, Zoran Ševarac, Branislav Milovanović, Vlado Đajić, Marija Zdravković, Saša Hinić, Marina Arsić, Milica Aleksić

“…Artificial neural networks (ANNs) are machine learning technique, inspired by the principles found in biological neurons. …”
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Retracted: Parameter-Tunable RBF Neural Network Control Facing Dual-Joint Manipulators by Journal of Robotics

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A generative deep neural network for pan-digestive tract cancer survival analysis by Lekai Xu, Tianjun Lan, Yiqian Huang, Liansheng Wang, Junqi Lin, Xinpeng Song, Hui Tang, Haotian Cao, Hua Chai

“…Results In this study, we propose GDEC, a multi-task generative deep neural network designed for precise digestive tract cancer subtyping. …”
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Robust Adaptive Neural Backstepping Control for a Class of Nonlinear Systems with Dynamic Uncertainties by Hongyan Yang, Huanqing Wang, Hamid Reza Karimi

“…This paper is concerned with adaptive neural control of nonlinear strict-feedback systems with nonlinear uncertainties, unmodeled dynamics, and dynamic disturbances. …”
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Solving Nonlinear Energy Supply and Demand System Using Physics-Informed Neural Networks by Van Truong Vo, Samad Noeiaghdam, Denis Sidorov, Aliona Dreglea, Liguo Wang

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Hexavalent Chromium Removal by a Paecilomyces sp. Fungal Strain Isolated from Environment by Juan F. Cárdenas-González, Ismael Acosta-Rodríguez

“…A resistant and capable fungal strain in removing hexavalent chromium was isolated from an environment near of Chemical Science Faculty, located in the city of San Luis Potosí, Mexico. …”
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Damage Identification for Large Span Structure Based on Multiscale Inputs to Artificial Neural Networks by Wei Lu, Jun Teng, Yan Cui

“…A methodology to combine the local and global measurements in noisy environments based on artificial neural network is proposed in this paper. For a real large span structure, the capacity of the methodology is validated, including the decision on damage placement, the discussions on the number of the sensors, and the optimal parameters for artificial neural networks. …”
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The pathways of technology and class models of English language learning: reflecting the new normal era by Miftachudin, Muhammad Zulfikar

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MagNet: Automated Magnetic Mineral Grain Morphometry Using Convolutional Neural Network by Zhaowen Pei, Liao Chang, Pengfei Xue, Richard J. Harrison

“…This framework, based on a convolutional neural network, performs well in the recognition and classification of magnetofossil nanoparticles in transmission electron microscopy images after training and testing. …”
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Adaptive Sliding Mode Tracking Control for Unmanned Autonomous Helicopters Based on Neural Networks by Min Wan, Mou Chen, Kun Yan

“…The uncertainty term of the system is handled by the inherent approximation ability of the neural network. The sliding model control scheme under the backstepping frame is developed for tackling disturbances. …”
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