Digital Core Modeling Based on Pretrained Generative Adversarial Neural Networks by Qing Zhang, Benqiang Wang, Xusheng Liang, Yizhen Li, Feng He, Yuexiang Hao

“…We can use the presented method to quickly complete the training and use the trained generator model to obtain multiple digital cores. By analyzing the quality of the generated cores from multiple aspects, it is revealed that the properties of the generated cores are in good agreement with the ones of the real core samples. …”
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A Rationale for Pollutograph Evaluation in Ungauged Areas, Using Daily Rainfall Patterns: Case Studies of the Apulian Region in Southern Italy by Angela Gorgoglione, Andrea Gioia, Vito Iacobellis, Alberto Ferruccio Piccinni, Ezio Ranieri

“…In particular, starting from the evaluation of the observed regional rainfall patterns by using a rainfall generator model, the storm water management model (SWMM) was applied on five case studies located in different climatic subareas. …”
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Dance Evaluation Based on Movement and Neural Network by Yan Lei, Xin Li, Yi Jiao Chen

“…The results show that the proposed dance generation model has a good effect in transforming into realistic dance videos.…”
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New Insight into the Kinetics of Deep Liquid Hydrocarbon Cracking and Its Significance by Wenzhi Zhao, Shuichang Zhang, Bin Zhang, Kun He, Xiaomei Wang

“…In addition, a quantitative gas generation model was also established to address the contribution of the cracking of residual oil and expulsed oil for natural gas accumulations in deep formations. …”
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Modeling carbon dioxide emissions in power plants: a perspective on smart cities and low-carbon economy by Isa S. Qamber

“…Researchers aim to identify strategies for meeting emission reduction goals by analyzing power generation models. This involves implementing policies and technologies aimed at reducing GHG emissions and mitigating climate change. …”
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An Effective Pipeline for Training Variational Autoencoders for Synthesizable and Optimized Molecular Design by Fardeen H. Mozumder, Byung-Jun Yoon

“…To demonstrate its efficacy, we apply the framework to a hierarchical molecular generation model built on a VAE and show that the enhanced model can effectively produce diverse molecules with significantly improved synthesizability.…”
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Weigh-in-Motion Method Based on Modular Sensor System and Axle Recognition with Neural Networks by Xiaoyong Liu, Zhiyong Yang, Bowen Shi

“…In addition, we propose a sequential generation model based on a Transformer and Gated Recurrent Unit to calculate the weighing signal generated by the weighing sensors, and then obtain the number of axles and the gross vehicle weight. …”
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An Efficient Frequency Domain Based Attribution and Detection Network by Junbin Zhang, Yixiao Wang, Hamid Reza Tohidypour, Panos Nasiopoulos

“…Detecting such images and attributing them to their generative models (GMs) is crucial. Existing deep learning methods attempt to identify and classify GM-specific artifacts but often struggle with content-independence and generalizability. …”
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A novel prediction method for low wind output processes under very few samples based on improved W‐DCGAN by Shihua Liu, Han Wang, Weiye Song, Shuang Han, Jie Yan, Yongqian Liu

“…Then, an LWOP sample generation model based on improved W‐DCGAN is established. …”
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Assessing the Uncertainty Associated with Flood Features due to Variability of Rainfall and Hydrological Parameters by Ahmad Sharafati, Mohammad Reza Khazaei, Mohamed Salem Nashwan, Nadhir Al-Ansari, Zaher Mundher Yaseen, Shamsuddin Shahid

“…The flood events are obtained by simulating runoff for rainfall events using the generated model parameters. The uncertainties due to rainfall and model parameters on generated flood hydrographs are evaluated using the relative coefficient of variation (RCV). …”
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Visual Simulation and Case Inversion of Gas Explosion in Underground Mine by Qiu Jinwei, Jiang Bingyou, Tang Mingyun, Zhou Liang, Ren Bo, Yang Yingdi

“…Through analyzing the characteristics of various field parameters, space geometric field models, physical attribute field models, and meteorological parameter field models were established to describe mine engineering, ventilation network, and explosion disaster process, respectively. Based on the generated model class and simulation timing flow of gas explosion disaster field, OpenGL technology was adopted to visualize the model of gas explosion disaster field, which simulated the overpressure propagation process of gas explosion shockwave and dynamic spread process of disaster gas, thereby to reveal the developing changes of gas explosion parameters in time and space. …”
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Distinguishing Reality from AI: Approaches for Detecting Synthetic Content by David Ghiurău, Daniela Elena Popescu

“…The advancement of artificial intelligence (AI) technologies, including generative pre-trained transformers (GPTs) and generative models for text, image, audio, and video creation, has revolutionized content generation, creating unprecedented opportunities and critical challenges. …”
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A tabular data generation framework guided by downstream tasks optimization by Fengwei Jia, Hongli Zhu, Fengyuan Jia, Xinyue Ren, Siqi Chen, Hongming Tan, Wai Kin Victor Chan

“…Abstract Recently, generative models have been gradually emerging into the extended dataset field, showcasing their advantages. …”
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Electric Signals on and under the Ground Surface Induced by Seismic Waves by Akihiro Takeuchi, Kan Okubo, Nobunao Takeuchi

“…We propose a signal generation model: seismic acceleration vertically shook pore water in the topsoil, generating the vertical streaming potential between the upper unsaturated water zone and the lower saturated water zone. …”
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From ChatGPT to Sora: Analyzing Public Opinions and Attitudes on Generative Artificial Intelligence in Social Media by Wenyan Feng, Yuhang Li, Chunhao Ma, Lisai Yu

“…This study examines public opinions, emotional tendencies, and psychological linguistic characteristics associated with the launch of OpenAI’s ChatGPT and the advanced video generation model, Sora, by analyzing discussions on the Chinese social media platform Weibo. …”
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Transient Study on the HTR-PM with TINTE-vPower Coupling Code Package by Jun Sun, Ximing Sun, Yanhua Zheng

“…Two TINTE models were built and coupled to one vPower model through the data exchange in the steam generator models. Using this code package, two typical transients were simulated by decreasing the primary flow rate or introducing the negative reactivity of one module. …”
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A Hybrid Strategy Two‐Dimensional Concrete Aggregate Filling Algorithm by Xu Tian, Jun Ao, ChunBo Ma, JunJie Shi, HanJun Guo

“…The random aggregates‐based method is a classic approach to meso‐structural modeling of concrete and is particularly suitable for generating models with low‐density aggregates. However, when facing the simulation requirements of concrete models with large volumes, small particle sizes, and high aggregate content, traditional random aggregates‐based methods encounter challenges in satisfying aggregate packing density and modeling efficiency. …”
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Development of a Machine‐Learning Model for Diagnosis of Pancreatic Cancer from Serum Samples Analyzed by Thermal Liquid Biopsy by Sonia Hermoso‐Durán, Nicolas Fraunhoffer, Judith Millastre‐Bocos, Oscar Sanchez‐Gracia, Pablo F. Garrido, Sonia Vega, Ángel Lanas, Juan Iovanna, Adrián Velázquez‐Campoy, Olga Abian

“…DSC thermograms are analyzed using ML models. The generated models are built applying algorithms based on penalized regression, resampling, categorization, cross validation, and variable selection. …”
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LPV Control for the Full Region Operation of a Wind Turbine Integrated with Synchronous Generator by Guoyan Cao, Karolos M. Grigoriadis, Yaw D. Nyanteh

“…The solution of a set of linear matrix inequalities (LMIs) leads to the LPV controller. A synchronous generator model is connected with the closed LPV control loop for examining the electrical subsystem performance obtained by an inner speed control loop. …”
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Optimization of Stirling generator for the production of electric energy using non-aggregate methods by Victor Zogbochi, Patrice Koffi Chetangny, Mawuena Medewou, Sossou Houndedako, Gerald Barbier, Didier Chamagne

“…This power constitutes the input variable of the generator model to determine the electrical power and the overall efficiency of the generator set. …”
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