Upcycling cement kiln dust for manufacturing clay bricks fired at different temperatures: RSM and ANN-GA hybrid-optimization by Rahma Mebarkia, Mansour Bouzeroura, Messaouda Boumaaza, Nasser Chelouah, Ahmed Belaadi, Ibrahim M.H. Alshaikh, Yazid Chetbani, Djamel Ghernaout

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Differences in Sexual Function Between Trimesters During Pregnancy: An Observational Study by Sunullah Soysal, Abdullah Sarioz, Umran Kilincdemir Turgut, Gokce Anik Ilhan, Yusuf Arman, Begum Yildizhan, Tanju Pekin

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The temporal and spatial evolution law of seepage parameters in the filter based on the CFD-DEM coupled flow-solid approach by Song Jingyu, Dang Faning, Gao Jun, Zhu Wuwei, Yao Yi

“…Abstract Filters are critical components of hydraulic structures such as earth-rock dams and tailings dams, functioning to prevent soil particle loss and control phreatic levels. …”
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Performance of cognitive tasks and functional brain activity in anxiety disorders by A. V. Kirenskaya, E. V. Fedorova, K. Yu. Telesheva, A. M. Gonopolsky, A. M. Chernorizov

“…The study demonstrated that anxiety disorders are accompanied by reallocation of attentional resources and changes in functional organization of brain networks involved in attention and executive functions. …”
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Functional MRI study on anxiety-enhanced temporomandibular joint pain by SUN Yidan, YANG Xin

“…There is significant activation in the brain regions related to the hippocampus-centered hyperalgesia reaction and the thalamic-limbic system and the thalamic-limbic system, which are involved in pain and emotion regulation networks.…”
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Auto-Probabilistic Mining Method for Siamese Neural Network Training by Arseniy Mokin, Alexander Sheshkus, Vladimir L. Arlazarov

“…This paper address these issues by proposing a novel mining method and metric loss function. Firstly, this paper presents an auto-probabilistic mining method designed to automatically select the most informative training samples for Siamese neural networks. …”
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Loan classification using a feed-forward neural network by U. I. Behunkou

“…Based on a feed-forward neural network using historical data on loans issued, the following metrics are calculated: cost function, Accuracy, Precision, Recall, and measure, calculated on Precision and Recall values. …”
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Prediction of dust storm using artificial neural networks in Kermanshah by Toba Alizadeheh, Majid rezaie banafsh, Gholamreza Goodarzi, Hashem Rostamzadeh

“…Additionally, the results of the time series prediction using the ANFIS model showed that the linear bell membership function with grade 3, during both the training and testing stages, was the most effective input function among other membership functions. …”
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Cluster Synchronization in Networked Phase Oscillators under Periodic Coupling by S. S. Li

“…Here, by the kernel of sinusoidal coupling function, we revisit the effects of periodic coupling on the synchronization of networked phase oscillators. …”
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A Novel Dynamic Weight Neural Network Ensemble Model by Kewen Li, Wenying Liu, Kang Zhao, Mingwen Shao, Lu Liu

“…In order to solve the problem that K -value cannot be selected automatically in the K -means clustering algorithm when conducting the selection of individuals, the K -value optimization algorithm based on distance cost function is put forward to find the optimal K -values. …”
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Neural networks for parameter estimation in geostatistical models with geometric anisotropies by Alejandro Villazón, Alfredo Alegría, Xavier Emery

“…This article presents two neural network approaches for estimating the covariance function of a spatial Gaussian random field defined in a portion of the euclidean plane. …”
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An Aeromagnetic Compensation Algorithm Based on a Temporal Convolutional Network by Han Wang, Boxin Zuo

“…We conducted experiments based on both simulated and real datasets and compared typical neural network compensation methods proposed by previous researchers. …”
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Private Data Protection with Machine Unlearning in Contrastive Learning Networks by Kongyang Chen, Zixin Wang, Bing Mi

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NEURAL NETWORK MODEL OF DIAGNOSTICS OF STAGES OF DEVELOPING CORPORATE BANKRUPTCY by S. A. Gorbatkov, S. A. Farkhieva

“…New features of the method, increasing the predictive power of the model, are: 1) optimal selection of factors using Bayesian ensemble of auxiliary neural networks, performing compression of factor space; 2) step compression of factors based on the generalized Harrington desirability function; 3) regularization of the main (working) neural network model on Bayesian ensemble of neural networks. …”
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Enhancing Binary Convolutional Neural Networks for Hyperspectral Image Classification by Xuebin Tang, Ke Zhang, Xiaolei Zhou, Lingbin Zeng, Shan Huang

“…The leading model for classifying hyperspectral images, which relies on convolutional neural networks (CNNs), has proven to be highly effective when run on advanced computing platforms. …”
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Energy-Efficient Coverage of Rechargeable UAV Networks in Forest Scenarios by Chi Zheng, Ting Su, Jianming Liu, Kuo Chi, Yongqin Yang

“…When conducting scientific research or emergency rescue in the forest, it is essential to establish a seamless communication network to ensure the safety of users. …”
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Robotic Assistant for Object Recognition Using Convolutional Neural Network by Sunday Oluyele, Ibrahim Adeyanju, Adedayo Sobowale

“…This study addressed and provided solutions to the limitations offered by recent solutions by introducing a Convolutional Neural Network (CNN) object recognition system integrated into a mobile robot designed to function as a robotic assistant for visually impaired persons. …”
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PROBLEMS OF USING NEURAL NETWORKS TO PREDICT THE PRICE OF VIRTUAL ASSETS by Andrii Tsemko, Maxym Matskiv

“…The study confirms that neural networks have limitations in the task of predicting virtual asset prices. …”
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A Convolutional Neural Network for Early Supraventricular Arrhythmia Identification by Emilio J. Ochoa, Luis C. Revilla

“…These challenges are of paramount importance, as recurrent SVEs may elevate the risk of developing severe SVAs, potentially resulting in cardiac weakening and subsequent heart failure. In the study conducted, an innovative approach was introduced that combined a convolutional neural network (CNN) architecture to enable the early identification and characterization of SVEs within electrocardiogram (ECG) signals. …”
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Identifying Influential Nodes Based on Evidence Theory in Complex Network by Fu Tan, Xiaolong Chen, Rui Chen, Ruijie Wang, Chi Huang, Shimin Cai

“…To verify the effectiveness of the proposed method, extensive experiments are conducted on real-world complex networks. The results show that, compared to the other algorithms, attacking the influential nodes identified by the DS method is more likely to lead to the disintegration of the network, which indicates that the DS method is more effective for identifying the key nodes in the network. …”
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