SemantiPack: An Efficient Real-World Data Compressor Using Structural and Semantic Metadata by Yoshiteru Nagata, Daiki Kohama, Yoshiki Watanabe, Shin Katayama, Kenta Urano, Takuro Yonezawa, Nobuo Kawaguchi

“…The exponential growth of Real-World Data (RWD), primarily collected from IoT sensors and spanning domains such as mobility, environment, and energy consumption, presents critical challenges due to its scale, heterogeneity, and structural variability. …”
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Ancestor regression in structural vector autoregressive models by Schultheiss Christoph, Ulmer Markus, Bühlmann Peter

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Adaptation of k-means to automated forecasting of poorly structured time series of economic dynamics by Dunskaia Lada, Popova Elena

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Semantic web ontology for structured knowledge representation and clinical decision support in eye diseases by Fatima Anjum, Fahad Maqbool, Muhammad Saad Razzaq, Hafiz Muhammad Faisal Shehzad, Shujaat Ali, Dilawar Shah, Muhammad Tahir, Muhammad Ilyas

“…Ontologies are used as excellent tools for organizing and managing complicated information due to their structured representations of domain knowledge and to make data more findable, accessible, interoperable, and reusable. …”
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Large Language Model-Driven Structured Output: A Comprehensive Benchmark and Spatial Data Generation Framework by Diya Li, Yue Zhao, Zhifang Wang, Calvin Jung, Zhe Zhang

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Integrating structured and unstructured data for livestock price forecasting: a sustainability study from South Korea by Yifan Zhu, Yifan Zhu, Yifan Zhu, Tserenpurev Chuluunsaikhan, Jong-Hyeok Choi, Aziz Nasridinov

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Constructing Rasterized Covariates from LiDAR Point Cloud Data via Structured Query Language by Rory Pittman, Baoxin Hu

Subjects: “…structured query language (SQL)…”
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Enhancing structured data generation with GPT-4o evaluating prompt efficiency across prompt styles by Ashraf Elnashar, Jules White, Douglas C. Schmidt

Subjects: “…structured data generation…”
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UPN-GCN: Update Positive-Negative Graph Convolution Neural Network in Non-Euclidean Structured Data by Lijun Fan, Shichao Yi, Wenrui Guan, Pingxin Wang

“…Graph Convolutional neural Networks (GCNs) demonstrate exceptional effectiveness when working with data that have non-Euclidean structures. In recent years, numerous researchers have utilized GCNs for data with Euclidean structures. such as image data and language data, and achieved good results, expanding the application scope of GCN. …”
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Advancing plant metabolic research by using large language models to expand databases and extract labeled data by Rachel Knapp, Braidon Johnson, Lucas Busta

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The Influence of Ownership Structure on the Financial Performance of Banks by Sigit Pamungkas, Muchtar Hidayat, Muhammad Syarif, Farah Margaretha Leon, Henny S. Lestari

Subjects: “…Ownership Structure, Financial Performance, Banking, Panel Data Regression, Indonesia Stock Exchange…”
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THE EFFECT OF GIVING ILL-STRUCTURED MATH PROBLEM AND WELL-STRUCTURED MATH PROBLEM ON THE SELF-EFFICACY OF JUNIOR HIGH SCHOOL STUDENTS by Indri Aninda Rahmasari, Susanah Susanah

“… This study aimed to determine the effect of giving ill-structured problems and well-structured problems to students' self-efficacy. …”
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Graph Neural Network Learning on the Pediatric Structural Connectome by Anand Srinivasan, Rajikha Raja, John O. Glass, Melissa M. Hudson, Noah D. Sabin, Kevin R. Krull, Wilburn E. Reddick

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A Robust Estimate Method for Damage Detection of Concrete Structures Using Contaminated Data by X. Peng, F. J. Qin, Q. W. Yang, H. Chen

“…It was found that the proposed method can successfully identify the location and extent of structural damage even if the used data have gross errors.…”
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Subdivisions and crossroads: Identifying hidden community structures in a data archive’s citation network by Sara Lafia, Lizhou Fan, Andrea Thomer, Libby Hemphill

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Data-intelligence driven methods for durability, damage diagnosis and performance prediction of concrete structures by Fan Li, Daming Luo, Ditao Niu

“…Abstract A large number of in-service reinforced concrete structures are now entering the mid-to-late stages of their service life. …”
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Hierarchical data structures in rendering scenes containing a massive number of light sources by Andrzej Lamecki, Krzysztof Kaczmarski, Joanna Porter-Sobieraj

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Data-driven assessment of corrosion in reinforced concrete structures embedded in clay dominated soils by Shahbaz Ahmad, Siraj Ahmad, Sabih Akhtar, Faraz Ahmad, Mujib Ahmad Ansari

“…Abstract The integration of Artificial Intelligence techniques, particularly Artificial Neural Networks (ANNs), has transformed predictive modeling in structural and durability engineering. This study investigates the use of ANN-based approaches to predict the corrosion rates of mild steel reinforcement embedded in cementitious composites subjected to clay-dominated soil environments. …”
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Improving the Accuracy of Flood Damage Assessments to Residential Structures via the Use of Experimental Data by Anna Katya Opel, Elizabeth Chisolm Matthews

“…This research presents a more robust, data driven, small‐scale, flood damage estimation approach for residential buildings. …”
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Delineation of Subsurface Structures Using Gravity Data of the Shallow Offshore, Lamu Basin, Kenya by Dennis Ombati, John Githiri, Maurice K'Orowe, Erick Nyakundi

“…Gravity interpretation techniques such as spectral analysis and first horizontal derivative were applied to the reduced gravity data to delineate and model structures to minimize the high investment risks. …”
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