Supply Chain Risk Prevention and Control Based on Fuzzy Influence Diagram and Discrete Hopfield Neural Network by Xin Su, Maohua Zhong

“…To explore different influence degrees of multirisk factors and multilinks on enterprises, we propose a supply chain risk prevention and control model based on a fuzzy influence diagram and Hopfield neural network. Using the model that both calculates the risk size and occurrence probability of the supply chain and allows identifying various risk prevention and control levels, the supply chain risk is evaluated both objectively and fairly. …”
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Research on Adaptive Trajectory Tracking Algorithm for a Quadrotor Based on Backstepping and the Sigma-Pi Neural Network by Zhiming Chen, Kang Niu, Lei Li

“…Then a new trajectory tracking algorithm is designed by using the sigma-pi neural network and backstepping. The paper designs the sigma-pi neural network compensation control law and gives the Lyapunov-type stability analysis. …”
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Stability in Switched Cohen-Grossberg Neural Networks with Mixed Time Delays and Non-Lipschitz Activation Functions by Huaiqin Wu, Guohua Xu, Chongyang Wu, Ning Li, Kewang Wang, Qiangqiang Guo

“…The stability for the switched Cohen-Grossberg neural networks with mixed time delays and α-inverse Hölder activation functions is investigated under the switching rule with the average dwell time property. …”
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Neural Network-Based Lower Limb Prostheses Control Using Super Twisting Sliding Mode Control by Adisu Tadese Demora, Chala Merga Abdissa

Subjects: “…Artificial neural network (ANN)…”
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Frugal method for extracting DNA from saliva suitable for low-budget labs and usable in PCR assays by Kamar Shayah, Joseph Shenekji, Lana Karnoub, Sana Wohbeh, Hagar Hamsho

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Assessment of a Neural-Network-Based Optimization Tool: A Low Specific-Speed Impeller Application by Matteo Checcucci, Federica Sazzini, Michele Marconcini, Andrea Arnone, Mario Coneri, Luigi De Franco, Matteo Toselli

“…The design procedure relies on a modern optimization technique such as an Artificial-Neural-Network-based approach (ANN). The impeller geometry is parameterized in order to allow geometrical variations over a large design space. …”
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A comprehensive dataset and neural network approach for named entity recognition in the Uzbek languageMendeley Data by Davlatyor Mengliev, Vladimir Barakhnin, Mukhriddin Eshkulov, Bahodir Ibragimov, Shohrux Madirimov

“…Moreover, in conclusion, the authors propose possible scenarios for the development of the work, in the form of further scaling of the dataset, as well as the use of other neural network architectures.…”
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Neurally Derived Tissues in Xenopus laevis Embryos Exhibit a Consistent Bioelectrical Left-Right Asymmetry by Vaibhav P. Pai, Laura N. Vandenberg, Douglas Blackiston, Michael Levin

“…We investigated two important developmental events: physiological controls of eye development and specification of neural crest derivatives, in Xenopus laevis embryos. …”
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Insulin Resistance Increases MRI-Estimated Pancreatic Fat in Nonalcoholic Fatty Liver Disease and Normal Controls by Niraj S. Patel, Michael R. Peterson, Grace Y. Lin, Ariel Feldstein, Bernd Schnabl, Ricki Bettencourt, Ekihiro Seki, Claude B. Sirlin, Rohit Loomba

“…Patients with NAFLD have greater pancreatic fat than normal controls. Insulin resistance is associated with liver and pancreatic fat accumulation.…”
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Hearing Loss: Reestablish the Neural Plasticity in Regenerated Spiral Ganglion Neurons and Sensory Hair Cells 2018 by Renjie Chai, Geng-Lin Li, Jian Wang, Hai Huang

“…Neural Plasticity…”
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Ignition delay prediction for fuels with diverse molecular structures using transfer learning-based neural networks by Mo Yang, Dezhi Zhou

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Fully Connected Neural Networks Ensemble with Signal Strength Clustering for Indoor Localization in Wireless Sensor Networks by Marcin Bernas, Bartłomiej Płaczek

“…For each region a prototype of the received signal strength is determined and a dedicated artificial neural network (ANN) is trained by using only those fingerprints that belong to this region (cluster). …”
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A Randomized Controlled Clinical Trial of Lifestyle Intervention and Pioglitazone for Normalization of Glucose Status in Chinese with Prediabetes by Yingying Luo, Hongyuan Wang, Xianghai Zhou, Cuiqing Chang, Wei Chen, Xiaohui Guo, Jinkui Yang, Linong Ji, Sanjoy K. Paul

“…However, no study has ever explored whether these interventions could revert prediabetes to normal glycemic status as the primary outcome. Interventions that may revert prediabetes back to normal glucose status would be of great clinical importance. …”
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A Novel Prediction Model for Car Body Vibration Acceleration Based on Correlation Analysis and Neural Networks by Shubin Zheng, Qianwen Zhong, Xiaodong Chai, Xingjie Chen, Lele Peng

“…Taking the selected parameters and previous car body vibration acceleration as the inputs, a prediction model for car body vibration acceleration was established based on several training algorithms and neural network structures. Then, the model was successfully applied to predict the car body vibration acceleration of test datasets on different segments of the same railway. …”
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Unambiguous identification of fungi: where do we stand and how accurate and precise is fungal DNA barcoding? by Robert Lücking, M. Catherine Aime, Barbara Robbertse, Andrew N. Miller, Hiran A. Ariyawansa, Takayuki Aoki, Gianluigi Cardinali, Pedro W. Crous, Irina S. Druzhinina, David M. Geiser, David L. Hawksworth, Kevin D. Hyde, Laszlo Irinyi, Rajesh Jeewon, Peter R. Johnston, Paul M. Kirk, Elaine Malosso, Tom W. May, Wieland Meyer, Maarja Öpik, Vincent Robert, Marc Stadler, Marco Thines, Duong Vu, Andrey M. Yurkov, Ning Zhang, Conrad L. Schoch

“…Despite the prevalence of DNA-based fungal taxonomy, phenotype-based approaches remain an important strategy to catalog the global diversity of fungi and establish initial species hypotheses.…”
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Algorithm development for recognizing human emotions using a convolutional neural network based on audio data by V. V. Semenuk, M. V. Skladchikov

Subjects: “…neural network…”
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Exponential Stability of Stochastic Delayed Neural Networks with Inverse Hölder Activation Functions and Markovian Jump Parameters by Yingwei Li, Huaiqin Wu

“…The exponential stability issue for a class of stochastic neural networks (SNNs) with Markovian jump parameters, mixed time delays, and α-inverse Hölder activation functions is investigated. …”
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Seed Protein Content Estimation with Bench-Top Hyperspectral Imaging and Attentive Convolutional Neural Network Models by Imran Said, Vasit Sagan, Kyle T. Peterson, Haireti Alifu, Abuduwanli Maiwulanjiang, Abby Stylianou, Omar Al Akkad, Supria Sarkar, Noor Al Shakarji

“…Sensitivity analyses were also conducted to identify the most sensitive bands for seed protein estimation. Convolutional neural networks (CNNs) with attention mechanisms were proposed along with traditional machine learning models based on feature engineering including Random Forest (RF) and Support Vector Machine (SVM) regression for comparative analysis. …”
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Fuzzy Neural Network for Fuzzy Quadratic Programming With Penalty Function and Mean-Variance Markowitz Portfolio Model by Izaz Ullah Khan, Muhammad Aamir, Mehran Ullah, Muhammad Shahbaz Shah

“…This research tries to integrate fuzzy neural networks with penalty function to address the quadratic programming based on the mean-variance Markowitz portfolio model. …”
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Haralick Texture Analysis for Differentiating Suspicious Prostate Lesions from Normal Tissue in Low-Field MRI by Dang Bich Thuy Le, Ram Narayanan, Meredith Sadinski, Aleksandar Nacev, Yuling Yan, Srirama S. Venkataraman

“…For each cancerous ROI, a matching ROI of identical size was drawn in a non-suspicious region presumed to be normal tissue. Four Haralick texture features (Energy, Correlation, Contrast, and Homogeneity) were extracted and compared between cancerous and non-suspicious ROIs. …”
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