Market Phases and Price Discovery in NFTs: A Deep Learning Approach to Digital Asset Valuation by Ho-Jun Kang, Sang-Gun Lee

“…For long-term forecasting (720-h horizon), CARD maintains a 35.5% performance advantage over the next best model. Through SHAP-based regime analysis, we identify distinct feature importance patterns across market phases, revealing how liquidity metrics, top trader activity, and royalty dynamics drive valuations in bear, bull, and neutral markets respectively. …”
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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

“…The model accurately identifies internal defects in bolts through precise signal decomposition and feature extraction, achieving a high classification accuracy of 96.78% even in a complex noise environment. …”
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Advancements in image classification for environmental monitoring using AI by Jinjing Zhu, Ling Li

“…AETS employs dynamic data augmentation to simulate real-world variations, domain-specific regularization to enhance feature consistency, and feedback-driven optimization to iteratively refine the model‘s performance based on real-time evaluation metrics.ResultsExtensive experiments conducted on multiple benchmark datasets demonstrate that MABEC-Net, in conjunction with AETS, significantly outperforms state-of-the-art models in terms of classification accuracy, robustness to domain shifts, and computational efficiency. …”
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An Efficient ISAR Imaging Method for Space Maneuvering Target Based on Multisynchrosqueezing Transform by Ting Zhao, Chengxiang Zhang, Yu Zheng, Jishen Liang

“…By extracting instantaneous Doppler features through energy concentration optimization, the framework achieves enhanced ISAR image resolution. …”
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Vision-Based UAV Localization on Various Viewpoints by Yee-Ming Ooi, Che-Cheng Chang, Yu-Min Su, Chiao-Ming Chang

“…Our findings illustrate the importance and relationship of various training data among the different performances of the model. The model achieves only 17% accuracy without applying rotational augmentation in the most practical scenario. …”
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Machine learning-based prediction of volatile compounds profiles in Saccharomyces cerevisiae fermentation simulating canned meat by Lin Du, Shujie Wang, Yongyan Chen, Zhongxu Zhu, Hai-Xi Sun, Tsan-Yu Chiu

“…We proposed a framework encompassing data generation and preprocessing, feature selection, model construction, and evaluation. …”
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An Inspiration Recommendation System for Automotive Styling Design Based on User Behavior Data and Group Preferences by Wanxin Cai, Mingqing Yang, Li Lin

“…Using a multi-user joint evaluation approach, we compare the performance of IR with baseline models across multiple metrics. …”
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Using deep learning artificial intelligence for sex identification and taxonomy of sand fly species. by Mohammad Fraiwan, Rami Mukbel, Dania Kanaan

“…Using locally field-caught and prepared samples over a period of two years, and based on convolutional neural networks, transfer learning, and early fusion of genital and pharynx images, we achieved exceptional classification accuracy (greater than 95%) across multiple performance metrics and using a wide range of pre-trained convolutional neural network models. …”
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Towards Machine Learning-Driven Catalyst Design and Optimization of Operating Conditions for the Production of Jet Fuel Via Fischer-Tropsch Synthesis by Parisa Shafiee, Bogdan Dorneanu, Harvey Arellano-Garcia

“…The random forest ML algorithm was evaluated for predicting CO conversion and C8-C16 selectivity using this dataset. Feature engineering identified the most significant descriptors influencing performance. …”
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“AT THE BEGINNING AND AT THE END OF TIMES” BY PAVLO ARIE: INTERMEDIATIVE ASPECT OF COMPREHENSION by Larysa Gorbolis

“… The article, based on the play «At the Beginning and At the End of Times» by the contemporary Ukrainian playwright Pavlo Arie and the performance of Lviv Lesia Ukrainka Academic Drama Theatку, directed by Oleksiy Kravchuk, ascertains the expedience to use an intermedial approach to find out the features of architectonics, genre originality, the role of the title, dedication, remarks, chronotope in the literary and stage modelling of the heroes, reflection of the general concept of works, visualization of the ideological and thematic direction. …”
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Proximal Neural Networks based reconstruction for few-view CT applications by Hoang Trieu Vy Le, Caroline Bossuyt, Julie Escoda, Marius Costin, Jan De Beenhouwer, Jan Sijbers

“…In contrast, learning-based models offer faster performance and higher reconstruction quality, although they lack interpretability. …”
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An innovative efficiency of incubator to enhance organization supportive business using machine learning approach. by Xin Li, Qian Zhang, Hanjie Gu, Salwa Othmen, Somia Asklany, Chahira Lhioui, Ali Elrashidi, Paolo Mercorelli

“…USAV classifies and validates critical data associations based on business features to improve startup incubation and innovation decision-making. …”
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Impact of stellar variability on exoplanet detectability and characterisation by Meunier, Nadège

“…This has been done in different ways, based on observations and models. This is crucial because it is then possible to compare disk-integrated radial velocities with actual structures on the solar surface, such as spots and plages, and with photospheric flows at different spatial scales. …”
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Pressurized Water Reactor Transient Detection With Artificial Intelligence to Support Reactor Operators by Ceyhun Yavuz, Senem Şentürk Lüle

“…The success and failure rates of the models have also been analyzed and presented. When accuracy, precision, recall, and F1-score are compared together, the random forest method showed the best performance.…”
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Harnessing Transfer Learning for Rapid Malware Family Classification in Large-Scale Cyber Datasets by Mohan Rishabh, Gupta Himanshu

“…Leveraging pre-trained deep learning models, we demonstrate significant improvements in classification accuracy and speed while reducing the dependency on extensive labelled data. …”
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Deep learning with attention modules and residual transformations improves hepatocellular carcinoma (HCC) differentiation using multiphase CT by Yuenan Wang, Wanwei Jian, Zhidong Yuan, Fada Guan, David Carlson

“…Abstract Background We hypothesize generative adversarial networks (GAN) combined with self‐attention (SA) and aggregated residual transformations (ResNeXt) perform better than conventional deep learning models in differentiating hepatocellular carcinoma (HCC). …”
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Impact of Interleukin-10 Promoter Region Polymorphisms on Recurrent Miscarriage: A Case–Control Approach by Neha Sudhir, Mandeep Kaur, Sukhjashanpreet Singh, Archana Beri, Tajinder Kaur, Anupam Kaur

“…A statistically significant difference was also found for the distribution of genetic models (dominant and co-dominant model) between both groups for rs1800896. …”
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Automatic description of rock thin sections: A web application by Stalyn Paucar, Christian Mejia-Escobar, Victor Collaguazo

“…A dataset of images and corresponding textual descriptions is used to train a hybrid deep learning model. Features extracted from the images using EfficientNetB7 are processed by a Transformer network to generate textual descriptions, which are then converted into verbal responses using a speech synthesis service. …”
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Tire-road surface characteristics estimation for skid-steered wheeled vehicle by Ao Li, Xiaolin Guo, Yuzheng Zhu, Xueyuan Li, Xin Gao

“…To address these issues, we propose a hybrid off-line and on-line estimation approach. Initially, a dynamic model for multi-axle vehicles and a brush-based tire model were constructed. …”
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The influence of urban form and socio-demographics on active transport: A 40-neighborhoods study in Chengdu, China by ChengHe Guan, Ann Forsyth

“…Neighborhood type was significant in models but so too were many other individual-level variables and infrastructural and locational features such as bike lanes and location near the river. …”
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