Bolt Anchorage Quality Levels Classification Method Based on HO‐VMD‐CNN‐BiLSTM by Fan Kesong, Zhang Can, Liu Shaowei, Feng Mengyin, Yan Ao, Fu Mengxiong, He Deyin, Nie Zhibin

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Direct prismatic coefficient variation to hull form surface by Dayeon Jeong, Min-Jae Oh

“…Thus, we propose a method to directly apply CP variation onto the hull form surface, setting the variated section line as a constraint. …”
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Meta-learning approach for variational autoencoder hyperparameter tuning by Michele Berti, Matheus Camilo da Silva, Sebastiano Saccani, Sylvio Barbon Junior

“…Synthetic data generation is a promising alternative to traditional data anonymization, with Variational Autoencoders (VAEs) excelling at generating high-quality synthetic tabular datasets. …”
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Variational Autoencoder-Based Framework for Retail Sales Prediction by Fuyu Li, Lei Wang, Bo Jin

“…For example, intelligent inventory replenishment based on forecasted sales can help reduce inventory backlog and turnover periods, improving operational efficiency. This paper presents a variational autoencoder (VAE)-based framework for retail sales prediction, with three unique contributions. …”
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Financial crisis impact on the efficiency evaluation of university research achievements transformation: a study based on fixed and interactive network data envelopment analysis me... by Yuping Ma, Yuping Ma, Mingqian Xu

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Online variational Gaussian process for time series data by Weidong Wang, Mian Muhammad Yasir Khalil, Leta Yobsan Bayisa

“…Our method capitalizes on the sophisticated design of the online variational inference framework, ensuring a technically robust derivation and implementation. …”
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Seasonal Variation In Cataract Surgery: A Myth or Reality? by Shekhar Mankad, Bennet Chacko Mathew, Dhaivat Shah

“…This causes problems with efficiency, quality and resource allocation. This study aims to analyse if seasonal variation exists and to determine the factors which can help in better planning for optimal utilisation of resources. …”
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Cancer staging diagnosis based on transcriptomics and variational autoencoder by LI Jiarui, QIAN Li, SHEN Junjie

“…Subsequently, the performance efficiency of our IFRSVAE model was evaluated in conjunction with Random Forest (RF), Support Vector Machine(SVM), and eXtreme Gradient Boosting (XGboost), and it was also compared with other methods. …”
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UAV-Based Remote Sensing Monitoring of Maize Growth Using Comprehensive Indices by Tingrui Yang, Jinghua Zhao, Ming Hong, Mingjie Ma, Shijiao Ma, Yingying Yuan

“…Comprehensive growth monitoring indices, CGMICV and CGMICT, were developed using the coefficient of variation method (CV) and the technique for order preference by similarity to an ideal solution (TOPSIS) based on the coefficient of variation method of empowerment (Coefficient of variation-TOPSIS, CT) respectively. …”
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Orbital Decay of the Ultra-hot Jupiter TOI-2109b: Tidal Constraints and Transit-timing Analysis by Jaime A. Alvarado-Montes, Mario Sucerquia, Jorge I. Zuluaga, Christian Schwab

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Methods of optimal subbands signal processing by Eugene G. Zhilyakov, S. P. Belov

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Inductive Construction of Variational Quantum Circuit for Constrained Combinatorial Optimization by Hyakka Nakada, Kotaro Tanahashi, Shu Tanaka

“…In this study, we propose a new method for constrained combinatorial optimization using variational quantum circuits. …”
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Multi-label Classification Based on Label-Aware Variational Autoencoder by SUN Hongjian, XU Pengyu, LIU Bing, JING Liping, YU Jian

“…Therefore, in order to solve the above problems, this paper proposes a multi-label classification method based on label-aware variational self-encoder from embedding representation learning and label relevance learning. …”
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Variational Autoencoder Transfer Functions for Onshore Tsunami Hazard Curves by Willington Renteria, Patrick Lynett, Maile McCann, Behzad Ebrahimi, Hong Kie Thio, Ian Robertson, Chris Siverd, Betsy Hicks

“…Overall, the transfer function method efficiently estimates onshore tsunami hazard curves, together with model uncertainty quantification, without requiring computationally expensive numerical simulations.…”
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Favourable Variations': Towards a Refreshed Approach for the Interviewing Classroom by Jane Ching

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Novel Laplace-integrated least square methods for solving the fractional nonlinear damped Burgers' equation by M. Mossa Al-Sawalha, Khalil Hadi Hakami, Mohammad Alqudah, Qasem M. Tawhari, Hussain Gissy

“…In this paper, we investigate the fractional damped Burgers' equation using two efficient analytical approaches: the Laplace least squares residual power series method and the Laplace least squares variational iteration method. …”
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Synthesis of Nanofiltration Membrane with Silica Variation for Waste Water Reduction by Fadly Abdul Malik, Muhammad Fahmi Hakim, Teguh Pambudi

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A Stochastic-Variational Model for Soft Mumford-Shah Segmentation by Jianhong (Jackie) Shen

“…In contemporary image and vision analysis, stochastic approaches demonstrate great flexibility in representing and modeling complex phenomena, while variational-PDE methods gain enormous computational advantages over Monte Carlo or other stochastic algorithms. …”
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Spatial variation of functional structure of fish communities in the Bohai Sea by Jianyu Zou, Hanxu Wang, Xiujuan Shan, Harry Gorfine, Yiping Ren

“…Functional space and diversity are powerful methods for understanding ecological patterns and describing changes in fish communities. …”
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Research on Water Flow Control Strategy for PEM Electrolyzer Considering the Anode Bubble Effect by Liheng An, Yizhi Tian, Haikun Zhao

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