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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mzGroupAnalyzer--predicting pathways and novel chemical structures from untargeted high-throughput metabolomics data. by Hannes Doerfler, Xiaoliang Sun, Lei Wang, Doris Engelmeier, David Lyon, Wolfram Weckwerth

“…Pathways are extracted directly from the data and putative novel structures can be identified. …”
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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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Automated Processing of Imaging Data through Multi-tiered Classification of Biological Structures Illustrated Using Caenorhabditis elegans. by Mei Zhan, Matthew M Crane, Eugeni V Entchev, Antonio Caballero, Diana Andrea Fernandes de Abreu, QueeLim Ch'ng, Hang Lu

“…Increasingly, the capacity for high-throughput experimentation provided by new imaging modalities, contrast techniques, microscopy tools, microfluidics and computer controlled systems shifts the experimental bottleneck from the level of physical manipulation and raw data collection to automated recognition and data processing. …”
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An Improved Gaussian Mixture Model-Based Data Normalization Method for Removing Environmental Effects on Damage Detection of Structures by Xue-Yang Pei, Hai-Bin Huang, Peng Cao

Subjects: “…structural health monitoring…”
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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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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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Data structures for compound promiscuity analysis: promiscuity cliffs, pathways and promiscuity hubs formed by inhibitors of the human kinome by Filip Miljković, Jürgen Bajorath

“…Limitations & next steps: PC and PCP data structures capture structure–promiscuity relationships. …”
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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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ABOUT DATA MODELING SUBJECT DOMAINS PRACTICE-ORIENTED DIRECTION FOR UNIVERSAL SYSTEM OF STORAGE AND PROCESSING DATA by L. V. Rudikova, E. V. Zhavnerko

Subjects: “…data warehouse…”
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Weightage Identified Network of Keywords Technique: A Structured Approach in Identifying Keywords for Systematic Reviews by Sasidharan Sivakumar, Gowardhan Sivakumar

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High resolution weld semantic defect detection algorithm based on integrated double U structure by Xiaoyan Li, Yi Wei, Zhigang Lv, Peng Wang, Liangliang Li, Mengyu Sun, Chu Wang

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Evaluation of Bayesian network scoring functions in polychotomous data analysis by Xuejia Ke, Katherine Keenan, V. Anne Smith

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Digital Twin-Based Technical Research on Comprehensive Gear Fault Diagnosis and Structural Performance Evaluation by Qiang Zhang, Zhe Wu, Boshuo An, Ruitian Sun, Yanping Cui

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Field data on diversity and vegetation structure of natural regeneration in a chronosequence of abandoned gold-mining lands in a tropical Amazon forestMendeley Data by Jorge Garate-Quispe, Ramiro Canahuire-Robles, Marx Herrera-Machaca, Sufer Baez-Quispe, Gabriel Alarcón-Aguirre

“…This dataset can be useful for long-term study and monitoring of structure and tree diversity in relatively understudied yet important secondary forests after gold-mining abandonment. …”
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