fragSMILES as a chemical string notation for advanced fragment and chirality representation by Fabrizio Mastrolorito, Fulvio Ciriaco, Maria Vittoria Togo, Nicola Gambacorta, Daniela Trisciuzzi, Cosimo Damiano Altomare, Nicola Amoroso, Francesca Grisoni, Orazio Nicolotti

“…Abstract Generative models have revolutionized de novo drug design, allowing to produce molecules on-demand with desired physicochemical and pharmacological properties. …”
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Analytic Hierarchy Process (AHP) for a Landfill Site Selection in Chachapoyas and Huancas (NW Peru): Modeling in a GIS-RS Environment by Jhonsy O. Silva López, Rolando Salas López, Nilton B. Rojas Briceño, Darwin Gómez Fernández, Renzo E. Terrones Murga, Daniel Iliquín Trigoso, Elgar Barboza Castillo, Manuel Oliva Cruz, Miguel Ángel Barrena Gurbillón

“…The weighted linear combination (WLC) approach of maps allowed us to generate models and submodels of land suitability. From the territory of the districts of Chachapoyas and Huancas, 0.9% (1.71 km2), 71.1% (141.89 km2), 21.0% (41.86 km2), 0.0%, and 7.7% (14.21 km2) have highly suitable, moderately suitable, marginally suitable, unsuitable, and restricted conditions, respectively, for a landfill site. …”
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Inverse design of nanophotonic devices enabled by optimization algorithms and deep learning: recent achievements and future prospects by Kim Junhyeong, Kim Jae-Yong, Kim Jungmin, Hyeong Yun, Neseli Berkay, You Jong-Bum, Shim Joonsup, Shin Jonghwa, Park Hyo-Hoon, Kurt Hamza

“…Furthermore, we explore state-of-the-art deep learning techniques, involving discriminative models, generative models, and reinforcement learning. We also introduce and categorize several notable inverse-designed nanophotonic devices and their respective design methodologies. …”
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WGAN-GP for Synthetic Retinal Image Generation: Enhancing Sensor-Based Medical Imaging for Classification Models by Héctor Anaya-Sánchez, Leopoldo Altamirano-Robles, Raquel Díaz-Hernández, Saúl Zapotecas-Martínez

“…The proposed method outperformed traditional generative models, such as conditional GANs and PathoGAN, achieving the best performance on key metrics: a Fréchet Inception Distance (FID) of 15.21, a Mean Squared Error (MSE) of 0.002025, and a Structural Similarity Index (SSIM) of 0.89 in the Kaggle dataset. …”
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Predicting the glass transition temperature of polymer based on generative adversarial networks and automated machine learning by Zhanjie Liu, Yixuan Huo, Qionghai Chen, Siqi Zhan, Qian Li, Qingsong Zhao, Lihong Cui, Jun Liu

“…The proposed GAN–TPOT framework demonstrates the potential of combining generative models with automated machine learning to improve materials science research. …”
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Blind super-resolution network based on local fuzzy discriminative loss for fabric data augmentation by Ning Dai, Xiaohan Hu, Kaixin Xu, Xudong Hu, Yanhong Yuan, Bo Cao, Luhong Shi

“…Traditional data augmentation methods offer limited improvements in model performance, while generative data augmentation methods are plagued by difficulties in training generative models, susceptibility to artifacts, and the need for re-labeling. …”
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Edge-centric optimization: a novel strategy for minimizing information loss in graph-to-text generation by Zheng Yao, Jingyuan Li, Jianhe Cen, Shiqi Sun, Dahu Yin, Yuanzhuo Wang

“…Based on this framework, we further propose a new graph generation model, named TriELMR, highlighting the comprehensive interactive learning relationship between the model and the graph structure, as well as the importance of edges in the graph structure. …”
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IMPLEMENTATION OF LEARNING MANAGEMENT SYSTEMS WITH GENERATIVE ARTIFICIAL INTELLIGENCE FUNCTIONS IN THE POST-PANDEMIC ENVIRONMENT by Denis-Cătălin Arghir

“…The system proposes the integration of a language generation model equipped with Application Programming Interface (API) access. …”
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Application of Multimedia Quality Evaluation Relying on Intelligent Robot Numerical Control Technology in New Energy Power Generation System by Ruijuan Sun, Xiaoyuan Dang

“…In this paper, an appropriate wind and solar power generation model was constructed based on the output characteristics of wind and solar. …”
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Semi-automated Generation of Geometric Digital Twin for Bridge Based on Terrestrial Laser Scanning Data by Kaixin Hu, Daguang Han, Guocheng Qin, Yin Zhou, Long Chen, Chunli Ying, Tong Guo, Yanhui Liu

“…The quality of the generated models is gauged using a point cloud deviation chromatogram. …”
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Steam Generator Maintenance Robot Design and Obstacle Avoidance Path Planning by Fengwei Yuan, Gengzhen Ren, Qian Deng, Xiangjiang Wang

“…The volume level approximate convex decomposition algorithm was used to fit the steam generator model with a convex packet, and an experimental simulation platform was constructed. …”
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Climate change shifts risk of soil salinity and land degradation in water-scarce regions by Isaac Kramer, Nadav Peleg, Yair Mau

“…We combine a soil–water-salinity–sodicity model (SOTE) and a weather generator model (AWE-GEN) to develop a framework for studying salinity and sodicity dynamics under changing climate definitions. …”
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C. perfringens enterotoxin-claudin pore complex: Models for structure, mechanism of pore assembly and cation permeability by Santhosh Kumar Nagarajan, Joy Weber, Daniel Roderer, Jörg Piontek

“…Here, we used AlphaFold2 complex prediction, structure alignment, and molecular dynamics simulations to generate models of prepore and pore states of the CPE/claudin-4 complex. …”
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PEMBELAJARAN REMEDIAL TERPADU DENGAN MENERAPKAN MODEL PEMBELAJARAN GENERATIF UNTUK MENGUBAH MISKONSEPSI SISWA TERHADAP KONSEP USAHA DAN ENERGI by Nur Rosuli, Irwan Koto, Nyoman Rohadi

“…The result showed that there was a significant effect on remedial learning related to applying generative models to change in students’ conceptions with t hitung > t tabel (16,33 ). …”
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Extending the Meshless Natural-Neighbour Radial-Point Interpolation Method to the Structural Optimization of an Automotive Part Using a Bi-Evolutionary Bone-Remodelling-Inspired Al... by Carlos Oliveira, Ana Pais, Jorge Belinha

“…The structural performance of the generated models is analyzed, and the main differences between the solutions obtained with both numerical techniques are identified.…”
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Explanatory LSTM-AE-Based Anomaly Detection for Time Series Data in Marine Transportation by Zhan Wang, Mwamba Kasongo Dahouda, Hyoseong Hwang, Inwhee Joe

“…The LSTM-AE model shows superior performance compared to other data generation models such as GAN and diffusion models, which have accuracy issues and require high computational cost. …”
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Wrong Answers Only: Distractor Generation for Russian Reading Comprehension Questions Using a Translated Dataset by Никита Вячеславович Логин

“…On USE data models fine-tuned on translated dataset have shown better quality than that trained on existing Russian distractor dataset, with T5-based model also beating the baseline established by output of an existing English distractor generation model translated into Russian. Conclusion: The obtained results show the possibility of a translated dataset to be used in distractor generation and the importance of the domain (language examination) and question type match in the input data. …”
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Predicting Future Surface Runoff Delivered to the Euphrates River Using LARSWG and SWAT Models: (Sahiliya Valley in the Iraqi Western    Desert as a Case Study) by Wisam Abdulabbas Abidalla, Basim Sh. Abed

“… The Weather Generation Model “LARSWG” and hydrological Model “SWAT” used in this study to estimate the quantity of future surface runoff in the Sahiliya Valley located within the Iraqi western desert. …”
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Test-Retest Reliability of Two Computationally-Characterised Affective Bias Tasks by Alexandra C. Pike, Katrina H. T. Tan, Hoda Tromblee, Michelle Wing, Oliver J. Robinson

“…However, embedding the covariance between sessions within the generative modelling framework resulted in higher estimates of stability. …”
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Numerical Simulation Study of Fines Migration Impacts on an Early Water Drainage Period in Undersaturated Coal Seam Gas Reservoirs by Xiaolong Peng, Suyang Zhu, Zhenjiang You, Zhimin Du, Peng Deng, Chaowen Wang, Mingwei Wang

“…The corresponding models for different stages are established, including (1) a fines generation model, (2) the maximum fines-carrying concentration model and deviation factor of the modified Darcy model, (3) a fines deposition model, and (4) a dynamic permeability and porosity model. …”
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