Enhancing data analysis and programming skills through structured prompt training: The impact of generative AI in engineering education by Ashish Garg, K. Nisumba Soodhani, Ramkumar Rajendran

“…Our research investigates the impact of structured prompt training on students' learning in data analysis and programming. …”
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THE STRUCTURE AND HISTORY OF ABYSSAL HILLS OF THE NORTH-WESTERN PACIFIC PLATE FROM CONTINUOUS SEISMIC PROFILING AND STRATIGRAPHIC DATA by V. L. Lomtev

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Local structure of solid and liquid gold probed by reverse Monte Carlo analysis of X-ray absorption data by Nodoka Hara, Fabio Iesari, Toshihiro Okajima, Andrea Di Cicco

“…The increase in computational capabilities of modern computers has allowed us to develop new accurate methods for EXAFS (extended X-ray absorption fine structure) data-analysis. In particular, the RMC-GNXAS package provides models of the three-dimensional structure applying the reverse Monte Carlo (RMC) method to EXAFS of condensed or molecular systems. …”
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Leveraging LLMs for optimised feature selection and embedding in structured data: A case study on graduate employment classification by Radiah Haque, Hui-Ngo Goh, Choo-Yee Ting, Albert Quek, M.D. Rakibul Hasan

“…The primary objective is to determine whether converting structured data into text format improves model accuracy. …”
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Automated Collection Planning for Civilian and Commercial Satellite Imagery, and Definition and Exploitation of the Collection Asset Specification Data Structure by Jeff Secker, Katerina Biron, Dany Dessureault, Pierre Lamontagne, Rodney Rear

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Biomass prediction of Typha latifolia on a paludiculture site by combining structural and spectral features from UAS data by Christina Hellmann, Bernd Bobertz, Fabian Hübner, Nora Köhn, Jürgen Kreyling, Sebastian van der Linden

“…As single UAS surveys offer both structural and spectral information, UAS data will contribute to precise biomass and vegetation monitoring at high spatial resolution in upcoming rewetting efforts.…”
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Data of vegetation structure metrics retrieved from airborne laser scanning surveys for European demonstration sitesZenodo by W. Daniel Kissling, Wessel Mulder, Jinhu Wang, Yifang Shi

“…A total of 35 LiDAR metrics were calculated, of which 28 represent vegetation structural attributes. These include vegetation height (seven metrics), vegetation cover (fourteen metrics), and vegetation vertical variability (seven metrics). …”
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Structural mapping for groundwater occurrence using remote sensing and geophysical data in Ilesha Schist Belt, Southwestern Nigeria by Stephen Olubusola Ilugbo, Isaac Aigbedion, Kesyton Oyamenda Ozegin

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Physics-Based AI-Driven Surrogate Modeling for Structural Displacement Prediction in Mechanical Systems With Limited Sensor Data by Ali Hashemi, Javad Beheshti, Mahdieh Mohammadi

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Gaussian Process Regression (GPR)-based missing data imputation and its uses for bridge structural health monitoring by Matteo Dalmasso, Marco Civera, Valerio De Biagi, Bernardino Chiaia

“…Abstract Structural health monitoring (SHM) apparatuses rely on continuous measurement and analysis to assess the safety condition of a target system. …”
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Structuring data analysis projects in the Open Science era with Kerblam! [version 1; peer review: 2 approved] by Federico Alessandro Ruffinatti, Luca Munaron, Luca Visentin

“…Background Structuring data analysis projects, that is, defining the layout of files and folders needed to analyze data using existing tools and novel code, largely follows personal preferences. …”
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Enhancing Standardized and Structured Recording by Elderly Care Physicians for Reusing Electronic Health Record Data: Interview Study by Charlotte A W Albers, Yvonne Wieland-Jorna, Martine C de Bruijne, Martin Smalbrugge, Karlijn J Joling, Marike E de Boer

“…The findings will be used to formulate recommendations aimed at enhancing standardized and structured data recording for the reuse of EHR data. …”
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Integrated structural analysis for geothermal exploration: A new protocol combining remote sensing and aeromagnetic geophysical data by Jawad Rafiq, Israa S. Abu-Mahfouz, Konstantinos Chavanidis, Pantelis Soupios

“…The approach integrates surface data from remote sensing and data from airborne magnetic geophysical surveys that provide information on the subsurface structures, to analyze structural lineament density analysis, orientation, and high permeable zones, and assess geothermal potential. …”
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Debiasing Structure Function Estimates from Sparse Time Series of the Solar Wind: A Data-driven Approach by Daniel Wrench, Tulasi N. Parashar

“…Structure functions (SFs), which quantify the moments of increments of a stochastic process, are essential complementary statistics to power spectra for analyzing the self-similar behavior of a time series. …”
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Grain Protein Function Prediction Based on CNN and Residual Attention Mechanism with AlphaFold2 Structure Data by Jing Liu, Xinping Zhang, Kai Huang, Yuqi Wei, Xiao Guan

“…The experimental results indicate that secondary structure and spatial structure information contribute to improving model performance. …”
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Shell Model Reconstruction of Thin-Walled Structures from Point Clouds for Finite Element Modelling of Existing Steel Bridges by Tomoya Nakamizo, Mayuko Nishio

“…There are some studies that show finite element (FE) models from point cloud data. While most of those approaches focus on modelling by solid elements, modelling of some civil structures, such as bridges, requires various uses of beam and shell elements. …”
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Multi-stage hashing network storage structure for intelligent routing by Feng ZHU, Qun HUANG

“…Network data collection and storage are fundamental for intelligent routing control,providing massive flow data for model training and decision-making.However,as the key device in network storage system,switches have very limited memory size and design flexibility,which can’t satisfy the needs of intelligent routing control for comprehensive high-precision data and lightweight storage system,thus reducing the effectiveness of intelligent routing control.A multi-stage hashing network storage structure (MHNSS) was proposed for intelligent routing control,which fully utilized the limited memory resource of switch and completed network data storage with low collision rate.The number of candidate buckets of the flow key was augmented by multi-stage hash table,thus reducing collision rate and improving memory load ratio.Hash collision was resolved via coarse-grained timestamp LRU algorithm,which always stored most recently used data and cleared least recently used data to avoid subsequent collisions as far as possible.Trace-driven experiments showed that compared with widely used single hash table,MHNSS had significant performance advantage in collision rate and load ratio.…”
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Generation of Structural Components for Indoor Spaces from Point Clouds by Junhyuk Lee, Yutaka Ohtake, Takashi Nakano, Daisuke Sato

“…Currently, particularly in data-driven modeling methods, data preprocessing for dividing structural components and nonstructural components is required before modeling. …”
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Structural insights into Beclin 1 interactions with it's regulators for autophagy modulation by Debapriyo Sarmadhikari, Shailendra Asthana

“…This challenge is further compounded by the absence of structural data, which makes deciphering the intricate web of PPIs even more difficult. …”
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Analysis of the structure of palliative pathology in children of the Voronezh region in 2021 by Yu. Yu. Razuvaeva, V. S. Ledneva, L. V. Ulyanova

“…In the Voronezh region, the largest number of patients with palliative pathology is located in the Novousmansky district, which can be attributed to the immediate proximity of the district to the city. According to the structure of the detected palliative pathologies, non-oncological diseases prevail in children of the Voronezh region, which is compared with statistical data for Russia. …”
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