Analysis of Influencing Factors of Thermal Management System for LiFePO₄ Lithium Battery under High Power Charging by Jiuyu Du, Yizhao Sun, Yingxuan Huang, Xiaogang Wu

“…The coupling calculation between the one-dimensional electro-chemical model and the 3D heat generation model is realized. The accuracy of the model is verified by charging the battery at different rates. …”
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Simulation and Optimization Study of Ultra-Precision Turning Process by Samar Elsanabary, Ahmed Elkaseer, Saber Abd-Rabbo, Shaban Abdou

“…However, the surface generation model was improved by incorporating the effect of cutting speed into the model considerations. …”
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Data Augmentation Based on Generative Adversarial Networks to Improve Stage Classification of Chronic Kidney Disease by Yun-Te Liao, Chien-Hung Lee, Kuo-Su Chen, Chie-Pein Chen, Tun-Wen Pai

“…The images generated by the ACWGAN-GP generation model and the original images are simultaneously input into the pre-training model MobileNetV2 for training. …”
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Learning Perfectly Secure Cryptography to Protect Communications with Adversarial Neural Cryptography by Murilo Coutinho, Robson de Oliveira Albuquerque, Fábio Borges, Luis Javier García Villalba, Tai-Hoon Kim

“…Bibliographic review shows the main approach to this problem have been addressed throughout complex Neural Networks, but without understanding or proving the security of the generated model. This paper presents an analysis of the security of cryptographic algorithms generated by a new technique called Adversarial Neural Cryptography (ANC). …”
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Investigation on Battery Thermal Management Based on Enhanced Heat Transfer Disturbance Structure within Mini-Channel Liquid Cooling Plate by Renzheng Li, Yi Yang, Fengwei Liang, Jichao Liu, Xinbo Chen

“…First, an accurate battery heat generation model is established and verified by experiments. …”
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Sustainable Agriculture through the Enhancement of Microbial Biocontrol Agents: Current Challenges and New Perspectives by Arun Gokul, Jabulani Mabaso, Nontuthuko Henema, Laetitia Otomo, Olalekan Olanrewaju Bakare, Ashwil Klein, Augustine Innalegwu Daniel, Aina Omolola, Lee-Ann Niekerk, Mbukeni Nkomo, Marshall Keyster

“…Additionally, the research advances through utilization of specialized techniques (CRISPR/Cas9 system, nanoparticles and multi-omics) are highlighted to assist in elucidating the mechanism revolving around plant-microbe interactions and to generate model systems demonstrating improved biocontrol capabilities of endophytes. …”
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Visual Writing Prompts: Character-Grounded Story Generation with Curated Image Sequences by Xudong Hong, Asad Sayeed, Khushboo Mehra, Vera Demberg, Bernt Schiele

“…We also propose a character-based story generation model driven by coherence as a strong baseline. …”
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Probabilistic Methodology for Calculating PV Hosting Capacity in LV Networks Using Actual Building Roof Data by Miha Grabner, Andrej Souvent, Nermin Suljanović, Andrej Košir, Boštjan Blažič

“…Monte Carlo simulations with incorporated stochastic consumption and PV generation models are utilized for load flow calculations of the actual LV network. …”
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Evaluating Origin–Destination Matrices Obtained from CDR Data by Marco Mamei, Nicola Bicocchi, Marco Lippi, Stefano Mariani, Franco Zambonelli

“…In the literature dealing with CDR data there are two main approaches to extract OD matrices from such data: (a) in time-based matrices, the analysis focuses on estimating mobility directly from a sequence of CDRs; (b) in routine-based matrices (OD by purpose) the analysis focuses on routine kind of movements, like home-work commute, derived from a trip generation model. In both cases, the OD matrix measured by CDR counts is scaled to match the actual number of people moving in the area, and projected to the road network to estimate actual flows on the streets. …”
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Bayesian inference of chemical kinetic models from proposed reactions by Galagali, Nikhil, Marzouk, Youssef M

“…We present a new framework for tractable Bayesian model inference and uncertainty quantification using a large number of systematically generated model hypotheses. The approach involves imposing point-mass mixture priors over rate constants and exploring the resulting posterior distribution using an adaptive Markov chain Monte Carlo method. …”
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tRF-Gln-CTG-026 ameliorates liver injury by alleviating global protein synthesis by Sunyang Ying, Pengcheng Li, Jiaqiang Wang, Kaiqiong Chen, Yu Zou, Moyu Dai, Kai Xu, Guihai Feng, Changjian Zhang, Haiping Jiang, Wei Li, Ying Zhang, Qi Zhou

“…Here, we demonstrate the roles of tsRNAs in alleviating liver injury by utilizing the loss of NSun2 (NOP2/Sun domain family, member 2) as a tsRNAs-generating model. Mechanistically, the loss of NSun2 reduces methyluridine-U5 (m5U) and cytosine-C5 (m5C) of tRNAs, followed by the production of various tsRNAs, especially Class I tsRNAs (tRF-1s). …”
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Damage Detection for Conveyor Belt Surface Based on Conditional Cycle Generative Adversarial Network by Xiaoqiang Guo, Xinhua Liu, Grzegorz Królczyk, Maciej Sulowicz, Adam Glowacz, Paolo Gardoni, Zhixiong Li

“…Generative adversarial networks (GAN) are one of the deep learning methods based on generative models and have been proved to be of great potential. …”
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Utilization of computational methods for the identification of new natural inhibitors of human neutrophil elastase in inflammation therapy by Alzain Abdulrahim A., Elbadwi Fatima A., Al-Karmalawy Ahmed A., Elhag Rashid, Osman Wadah, Mothana Ramzi A.

“…A library of 449,008 NPs from the SN3 database was screened against the generated model, resulting in 29,613 NPs that matched the pharmacophore hypothesis. …”
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Computational approaches to treatment response prediction in major depression using brain activity and behavioral data: A systematic review by Povilas Karvelis, Colleen E. Charlton, Shona G. Allohverdi, Peter Bedford, Daniel J. Hauke, Andreea O. Diaconescu

“…We argue that theory-driven generative modeling, which explicitly models information processing in the brain and thus can capture disease mechanisms, is a promising emerging approach that is only beginning to be utilized in treatment response prediction. …”
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Development of Knowledge-Based Engineering System for Structural Size Optimization of External Fixation Device by Elmedin Mešić, Nedim Pervan, Adis J. Muminović, Adil Muminović, Mirsad Čolić

“…The system is based on algorithms for generative modeling, finite element model (FEM) analysis, and size optimization. …”
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A simple ANN-MLP model for estimating 60-GHz PDP inside public and private vehicles by Rajeev Shukla, Abhishek Narayan Sarkar, Aniruddha Chandra, Jan M. Kelner, Cezary Ziolkowski, Tomas Mikulasek, Ales Prokes

“…Such artificially generated models can help extrapolate other relevant scenarios for which measurement data are unavailable. …”
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Ten years after ImageNet: a 360° perspective on artificial intelligence by Sanjay Chawla, Preslav Nakov, Ahmed Ali, Wendy Hall, Issa Khalil, Xiaosong Ma, Husrev Taha Sencar, Ingmar Weber, Michael Wooldridge, Ting Yu

“…The rise of attention networks, self-supervised learning, generative modelling and graph neural networks has widened the application space of AI. …”
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Automatic completion of geometric models from point clouds for analyzing historic timber roof structures by Taşkın Özkan, Norbert Pfeifer, Georg Hochreiner

“…The proposed method was applied to two different roof structures, and structural assessments show that it is feasible to import and process the generated models in a structural analysis software application. …”
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Artifact Reduction in 3D and 4D Cone-Beam Computed Tomography Images With Deep Learning: A Review by Mohammadreza Amirian, Daniel Barco, Ivo Herzig, Frank-Peter Schilling

“…One of the key findings of this work is an observed trend towards the use of generative models including GANs and score-based or diffusion models, accompanied with the need for more diverse and open training datasets and simulations.…”
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Toward Interactive Music Generation: A Position Paper by Shayan Dadman, Bernt Arild Bremdal, Borre Bang, Rune Dalmo

“…Researchers have developed various generative models capable of imitating musical conventions, comprehending the musical corpora, and generating new samples based on the learning outcome. …”
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