An efficient method for predicting the morphology of proppant packs based on a surrogate model by Tao ZHANG, Hangyu ZHOU, Yifan ZHANG, Jianchun GUO, Haoran GOU, Tang TANG

“…Intelligent proxy models for the prediction of proppant placement patterns were established on the basis of the cascade neural network, including a time-concentration model for predicting particle volume fraction and a displacement-height model for predicting particle placement height. …”
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Land Use Transition and Regional Development Patterns Under Shared Socioeconomic Pathways: Evidence from Prefecture-Level Cities in China by Xiaodong Zhang, Mingjie Yang, Rui Guo, Yaolong Li, Fanglei Zhong

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A comparative study of convolutional neural networks and traditional feature extraction techniques for adulteration detection in ground beef by Leila Bahmani, Saied Minaei, Alireza Mahdavian, Ahmad Banakar, Mahmoud Soltani Firouz

“…Convolutional Neural Network (CNN) was also used to extract features and classify images. …”
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Energy-Efficient Islanding Detection Using CEEMDAN and Neural Network Integration in Photovoltaic Distribution System by Sulayman Kujabi, Emmanuel Asuming Frimpong, Francis Boafo Effah

“…This paper proposes an enhanced islanding detection method based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and a pattern recognition neural network (PANN). Negative sequence voltage data from both islanding and non-islanding scenarios were acquired through MATLAB Simulink simulations, with samples collected at a frequency of 3.84 kHz over a 2.5-second period. …”
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Introducing a Novel Figure of Merit for Evaluating Stability of Perovskite Solar Cells: Utilizing Long Short-Term Memory Neural Networks by Zahraa Ismail, Ahmet Sait Alali, Ahmad Muhammad, Mahmoud Ashraf, Sameh O. Abdellatif

“…This study introduces a novel figure of merit for evaluating the stability of perovskite solar cells (PSCs) by employing advanced Long Short-Term Memory (LSTM) neural networks to investigate degradation mechanisms. …”
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Algorithm for analyzing randomness in point patterns by Tony Sampaio, Jorge Rocha, Cláudia M. Viana, Silvana Camboin, Fábio Marcelo Breunig, Edenilson Nascimento, Elaine de Cacia de Lima Frick

“…However, what is deemed ``random'’ in point spatial patterns may be influenced by socio-environmental factors such as wetlands or transportation networks. …”
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Urban agglomeration transportation resilience: evaluation and evolution analysis using a data-driven model by Zihao Guo, Xuanling Zhou, Cong Lu, Shixin Li, Yunlong Zhu, Yinhang Liu, Zhijian Li

“…This study proposes an innovative, data-driven approach to quantify urban transportation resilience, integrating genetic algorithms (GA), backpropagation (BP) neural networks, and the entropy weighting method. This approach aims to eliminate the introduction of subjective biases by experts in traditional methods, providing a more accurate and objective evaluation results. …”
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Evaluating the Vulnerability of Hiding Techniques in Cyber-Physical Systems Against Deep Learning-Based Side-Channel Attacks by Seungun Park, Aria Seo, Muyoung Cheong, Hyunsu Kim, JaeCheol Kim, Yunsik Son

“…DL models, including a Recurrent Neural Network (RNN), a Bidirectional RNN (Bi-RNN), and a Multi-Layer Perceptron (MLP), were used to evaluate classification performance. (3) Results: The models trained with dummy traces achieved high classification accuracy, with the MLP model reaching 97.81% accuracy and an F1-score of 97.77%. …”
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Fault diagnosis of micro gas turbine using a hybrid scheme of thermodynamic analysis and artificial neural network by S.S. Talebi, A. Madadi, A.M. Tousi

“…An artificial neural network is used to recognize the pattern of noisy transformed variables and find the faulty component. …”
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Spatial Heterogeneity in Soil Microbial Communities Impacts Their Suitability as Bioindicators for Evaluating Productivity in Agricultural Practices by Guoqiang Li, Xuanjing Li, Ting Jin, Muyilan Jiang, Peng Shi, Gehong Wei

“…Results revealed marked disparities in soil properties, bacterial community compositions, and co-occurrence network patterns between intra-row and inter-row soils. …”
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Deep Learning-Driven Beam-Steering for Dual-Polarized 28 GHz Antenna Arrays in 5G Wireless Networks by Siti Zainab M. Zainab Hamzah, Norun Farihah Abdul Malek, Sarah Yasmin Mohamad, Farah Nadia Mohd Isa, Teddy Surya Gunawan, Kuo-Sheng Chin

“…We propose a method for synthesizing the array antenna’s radiation pattern using an active element pattern-deep neural network (AEP-DNN). …”
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Performance Evaluation of Beluga Whale Optimization–Long Short-Term Memory–Random Forest Networks for Trajectory Control and Energy Optimization in Excavator Systems by Van Hien Nguyen, Kyoung Kwan Ahn

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Design of a Methodology to Evaluate the Energy Flexibility of Residential Consumers to Enhance Household Demand Side Management: The Case of a Spanish Municipal Network by Caterina Lamanna, Andrés Ondó Oná-Ayécaba, Lina Montuori, Manuel Alcázar-Ortega, Javier Rodríguez-García

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Symmetrical Modular Optical Phased Array With Combined Spatial and Amplitude Modulation for Scalable Indoor Wireless Networks by Kosala Herath, Malin Premaratne, Sharadhi Gunathilake, Ampalavanapillai Nirmalathas

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Multi-Scenario Simulation Evaluation and Strategic Zoning of Habitat Services Based on Habitat Quality and Ecological Network: A Case Study of Lanzhou City by Jin Shi, Xianglong Tang

“…Across various analysis radii of space syntax, except for MED at a 6000 m radius, the ecological priority scenario exhibits excellent network accessibility. The coupling coordination degree of the four scenarios generally lies within a mild imbalance level, with a spatial distribution pattern characterized by “high in the west and low in the east”. …”
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Analysis of traffic patterns between Karkh and Rusafa by Mahdi Lateef Ishraq, Hussein Abed Alaa, Moutaz Asmael Noor

“…Rapid and radical changes in urban activities lead to changes in spatial travel patterns. Recently, users of the road network in Baghdad have faced difficulty in mobility between Karkh and Rusafa due to the congestion of bridges connecting the east of the city to the west across the Tigris River during peak hours. …”
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Data generation for asphalt pavement evaluation: Deep learning-based insights from generative models by Mohammad Sedighian-Fard, Amir Golroo, Mahdi Javanmardi, Alexandre Alahi, Mehdi Rasti

“…Its generalization capabilities were validated across multiple real-world datasets, demonstrating reliable performance under diverse crack patterns and imaging conditions. By addressing the challenges of data scarcity and improving segmentation accuracy, this research offers a scalable and efficient framework for automated pavement evaluation. …”
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Construction of an Artificial Intelligence Model and Application for an Automatic Recognition of Traditional Chinese Medicine Herbals Based on Convolutional Neural Networks by WANG Ganhong, ZHANG Zihao, XI Meijuan, XIA Kaijian, ZHOU Yanting, CHEN Jian

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A Deep Learning Method for Improving Community Multiscale Air Quality Forecast: Bias Correction, Event Detection, and Temporal Pattern Alignment by Ioannis Stergiou, Nektaria Traka, Dimitrios Melas, Efthimios Tagaris, Rafaella-Eleni P. Sotiropoulou

“…The model is trained here, using data from ten stations in Texas, enabling it to capture both spatial and temporal patterns in atmospheric behavior. Performance evaluation shows notable improvements, with a Root Mean Square Error (RMSE) reduction ranging from 34.11% to 71.63%. …”
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Detection and Classification of <i>Agave angustifolia</i> Haw Using Deep Learning Models by Idarh Matadamas, Erik Zamora, Teodulfo Aquino-Bolaños

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