Multilayer network analysis in patients with end-stage kidney disease by Jiyae Yi, Chang Min Heo, Bong Soo Park, Yoo Jin Lee, Sihyung Park, Yang Wook Kim, Dong Ah Lee, Kang Min Park, Jinseung Kim, Junghae Ko

Subjects: “…Neural networks…”
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A Robust Multi-Modal Deep Learning-Based Fault Diagnosis Method for PV Systems by Shahabodin Afrasiabi, Sarah Allahmoradi, Mousa Afrasiabi, Xiaodong Liang, C. Y. Chung, Jamshid Aghaei

Subjects: “…Convolutional neural networks (CNNs)…”
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A Real-Time and Closed-Loop Control Algorithm for Cascaded Multilevel Inverter Based on Artificial Neural Network by Libing Wang, Chengxiong Mao, Dan Wang, Jiming Lu, Junfeng Zhang, Xun Chen

“…In order to control the cascaded H-bridges (CHB) converter with staircase modulation strategy in a real-time manner, a real-time and closed-loop control algorithm based on artificial neural network (ANN) for three-phase CHB converter is proposed in this paper. …”
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Unveiling endothelial cell border heterogeneity: VE-cadherin adherens junction stratification by deep convolutional neural networks by Rudmer J. Postma, Susan E. Fischer, Roel Bijkerk, Anton Jan van Zonneveld

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Retracted: Adoption of Convolutional Neural Network Algorithm Combined with Augmented Reality in Building Data Visualization and Intelligent Detection by null Complexity

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Addressing Distribution Discrepancies in Pulsar Candidate Identification via Bayesian-neural-network-based Multimodal Incremental Learning by Yi Liu, Jing Jin, Hongyang Zhao, Zhenyi Wang, Yi Shen

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GaitRec-Net: A Deep Neural Network for Gait Disorder Detection Using Ground Reaction Force by Chandrasen Pandey, Diptendu Sinha Roy, Ramesh Chandra Poonia, Ayman Altameem, Soumya Ranjan Nayak, Amit Verma, Abdul Khader Jilani Saudagar

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Enhancement of Performance for Steam Turbine in Thermal Power Plants Using Artificial Neural Network and Electric Circuit Design by Hosham Salim, Khalid Faisal, Raheel Jawad

“…Artificial neural networks technique is used to control a lot of industrial models practically. …”
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Multi-region infectious disease prediction modeling based on spatio-temporal graph neural network and the dynamic model. by Xiaoyi Wang, Zhen Jin

“…In this study, we incorporate the Graph Transformer Neural Network and graph learning mechanisms into a metapopulation SIR model to build a hybrid framework, Metapopulation Graph Transformer Neural Network (M-Graphormer), for high-dimensional parameter estimation and multi-regional epidemic prediction. …”
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Retracted: Development of Integrated Neural Network Model for Identification of Fake Reviews in E-Commerce Using Multidomain Datasets by Applied Bionics and Biomechanics

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Novel deep neural network architecture fusion to simultaneously predict short-term and long-term energy consumption. by Abrar Ahmed, Safdar Ali, Ali Raza, Ibrar Hussain, Ahmad Bilal, Norma Latif Fitriyani, Yeonghyeon Gu, Muhammad Syafrudin

“…Therefore, this research proposes a novel hybrid model employing Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and Bi-directional LSTM (Bi-LSTM) to simultaneously predict both short-term and long-term residential energy consumption with enhanced accuracy measures. …”
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An Area-Efficient Integrate-and-Fire Neuron Circuit with Enhanced Robustness against Synapse Variability in Hardware Neural Network by Arati Kumari Shah, Kannan Udaya Mohanan, Jisun Park, Hyungsoon Shin, Eou-Sik Cho, Seongjae Cho

“…In this study, a compact leaky integrate-and-fire neuron circuit has been designed, with resilience to synaptic device state variations, for hardware implementation of spiking neural networks (SNNs). The proposed neuron circuit is simulated on the 0.35-μm Si complementary metal-oxide-semiconductor technology node by a series of circuit simulations based on HSPICE. …”
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Research on Mental Health Monitoring Scheme of Migrant Children Based on Convolutional Neural Network Based on Deep Learning by Guangyan Yang

“…The main research focus is feature extraction, trying to use one-dimensional convolutional neural network (1D-CNN) to mine students’ online patterns from online behavior sequences, calculate abnormal scores based on students’ consumption data in the cafeteria, and describe the dietary differences among students. …”
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Storm‐Time Ring Current Plasma Pressure Prediction Based on the Multi‐Output Convolutional Neural Network Model by Yun Yan, Zi‐Kang Xie, Chao Yue, Jiu‐Tong Zhao, Fan Yang, Lun Xie, Qiu‐Gang Zong, Xu‐Zhi Zhou, Shan Wang

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Integrating deformable CNN and attention mechanism into multi-scale graph neural network for few-shot image classification by Yongmin Liu, Fengjiao Xiao, Xinying Zheng, Weihao Deng, Haizhi Ma, Xinyao Su, Lei Wu

“…The feature extraction module of graph neural networks has always been designed as a fixed convolutional neural network (CNN), but due to the intrinsic properties of convolution operations, its receiving domain is limited. …”
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Artificial neural network analysis of Jeffrey hybrid nanofluid with gyrotactic microorganisms for optimizing solar thermal collector efficiency by Anup Kumar, Bhupendra K. Sharma, Bandar Almohsen, Laura M. Pérez, Kamil Urbanowicz

“…The Cash and Carp method is implemented to solve the non-dimensional equations. The artificial neural network is also developed for the non-dimensional governing equations using the Levenberg Marquardt algorithm. …”
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Enhancing air quality predictions in Chile: Integrating ARIMA and Artificial Neural Network models for Quintero and Coyhaique cities. by Fidel Vallejo, Diana Yánez, Patricia Viñán-Guerrero, Luis A Díaz-Robles, Marcelo Oyaneder, Nicolás Reinoso, Luna Billartello, Andrea Espinoza-Pérez, Lorena Espinoza-Pérez, Ernesto Pino-Cortés

“…Additionally, the adaptability and precision of neural network models were highlighted, showcasing the potential of advanced technologies in refining air quality forecasts. …”
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Event-Type Identification in Power Grids Using a Spectral Correlation Function-Aided Convolutional Neural Network by Ozgur Alaca, Ali Riza Ekti, Jhi-Young Joo, Nils Stenvig

“…This study introduces a novel event-type identification method, utilizing a Spectral Correlation Function (SCF)-aided Convolutional Neural Network (CNN). The proposed method employs a six-stage cascaded structure consisting of: (1) data collection, (2) clipping, (3) augmentation, (4) feature extraction (FE), (5) training, and (6) testing. …”
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Basketball technical action recognition based on a combination of capsule neural network and augmented red panda optimizer by Nu Sha

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Federated Digital Twins: A Scheduling Approach Based on Temporal Graph Neural Network and Deep Reinforcement Learning by Young-Jin Kim, Hanjin Kim, Beomsu Ha, Won-Tae Kim

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