Design of Low-Power Structural FIR Filter Using Data-Driven Clock Gating and Multibit Flip-Flops by Lamjed Touil, Abdelaziz Hamdi, Ismail Gassoumi, Abdellatif Mtibaa

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Promoting human-centered manufacturing through Lean Ergonomics – a structural equation model for ergonomics and management data by Stefan Brunner, Mathias Siebenbürger, Klaus Kühnel, Klaus Bengler

“…Data is analyzed using several Structural Equation Models (SEM). …”
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Litho-structural study and depth estimation of Shaki area of Southwestern, Nigeria using high resolution aeromagnetic data by Omonike Adedokun, Olagoke Oladejo, K. O Suleiman, Kehinde Alao, E. O. Adeniyi, H. Otobrise, Oluwaseun Adedokun, Lukman Sunmonu

“…Hence, there is a need to investigate the lithological structural trends in some parts of Southwestern Nigeria to determine the tectonic stability of the study area. …”
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A Data-Driven Analysis of Software Testing Automation Challenges Using Structural Equation Modeling (SEM) Approach by Muhammad Faisal Abrar, Muhammad Faran Majeed, Muhammad Saqib, Ali Alferaidi, Razauddin

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NEW INSIGHT INTO THE STRUCTURAL MODEL IN SOUTHERN SUMATRA INDONESIA USING GRAVITY AND MAGNETIC DATA: IMPLICATIONS FOR GEOTHERMAL RESOURCES by Irfan Prasetyo, Wawan Gunawan Abdul Kadir, Dadi Abdurrahman, Darharta Dahrin, Khalil Ibrahim, Andri Kurniawan

“…The integration of gravity and magnetic data reveals new relationships between tectonic structures in the GSF zone and previously unexplored geothermal potential.…”
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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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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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Civil structural health monitoring and machine learning: a comprehensive review by Asraar Anjum, Meftah Hrairi, Abdul Aabid, Norfazrina Yatim, Maisarah Ali

“…These methods could revolutionize the current situation by providing creative answers to complex problems that arise in civil structural applications.…”
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Research Progress on Structural Performance of Prefabricated Underground Station with Open-Cut Method by XIA Shengxiang, LI Peng, KANG Pengcheng, GUAN Dongzhi, FENG Shuaike

“…The bearing and seismic performance of prefabricated underground structures is mainly investigated by numerical methods, and lacks experimental data on the overall structure. …”
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Civil Structural Health Monitoring and Machine Learning: A Comprehensive Review by Asraar Anjum, Meftah Hrairi, Abdul Aabid, Norfazrina Yatim, Maisarah Ali

“…These methods could revolutionize the current situation by providing creative answers to complex problems that arise in civil structural applications. …”
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Innovation-Based Research Using Structural Flexibility and Acceptance Model (SFAM) by   Solimun, Adji Achmad Rinaldo Fernandes

“…The research objectives are as follows: (1) Develop a solid structural model assuming normality and homoscedasticity. (2) Obtain the property estimator of the flexible and robust SFAM structural model. (3) Obtaining hypothesis testing of each relationship built from the flexible and strong SFAM structural model. …”
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Small language models enable rapid and accurate extraction of structured data from unstructured text: An example with plants and their specialized metabolites by Lucas Busta, Alan R. Oyler

“…Small language models (SLMs), however, also have potential in this area as they have smaller compute footprints and allow users to keep data in-house. Here, we quantitatively evaluate the ability of SLMs to: (i) score references according to project-specific relevance and (ii) extract and structuring data from unstructured sources (scientific abstracts). …”
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Identifying long-term conditions in New Zealand general practice using structured and unstructured data: a cross-sectional study by Vanessa Selak, Katrina Poppe, Sue Wells, Yeunhyang Catherine Choi, Allan Ronald Moffitt, Claris Yee Seung Chung, Jane Ullmer

“…Objectives This study examined whether incorporating free-text entries into structured general practice records improves the detection of long-term conditions (LTCs) and multimorbidity (MM) in New Zealand (NZ) general practices.Methods Data from 374 071 deidentified individuals in general practices were analysed to identify 61 LTCs. …”
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Enhancing Frailty Assessments for Transcatheter Aortic Valve Replacement Patients Using Structured and Unstructured Data: Real-World Evidence Study by Mamoun T Mardini, Chen Bai, Anthony A Bavry, Ahmed Zaghloul, R David Anderson, Catherine E Crenshaw Price, Mohammad A Z Al-Ani

“…ObjectiveThis study aimed to enhance frailty assessments of TAVR candidates by integrating real-world structured and unstructured data. MethodsThis study analyzed data from 14,000 patients between January 2018 and December 2019 to assess frailty in TAVR patients at the University of Florida. …”
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A structural biology compatible file format for atomic force microscopy by Yining Jiang, Zhaokun Wang, Simon Scheuring

“…Abstract Cryogenic electron microscopy (cryo-EM), X-ray crystallography, and nuclear magnetic resonance (NMR) contribute structural data that are interchangeable, cross-verifiable, and visualizable on common platforms, making them powerful tools for our understanding of protein structures. …”
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Advancing Structural Health Monitoring with Deep Belief Network-Based Classification by Álvaro Presno Vélez, Zulima Fernández Muñiz, Juan Luis Fernández Martínez

“…In recent years, deep learning techniques have emerged as powerful tools for analyzing the complex data generated by SHM systems. This study investigates the use of deep belief networks (DBNs) for classifying structural conditions before and after retrofitting, using both ambient and train-induced acceleration data. …”
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Structural Health Monitoring of Laminated Composites Using Lightweight Transfer Learning by Muhammad Muzammil Azad, Izaz Raouf, Muhammad Sohail, Heung Soo Kim

“…Therefore, deep learning-based methods that use sensor data to conduct autonomous health monitoring have drawn much interest in structural health monitoring (SHM). …”
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Remote sensing‐based mapping of structural building damage in the Ahr valley by Guilherme Samprogna Mohor, Tobias Sieg, Oliver Koch, Aaron Buhrmann, Holger Maiwald, Jochen Schwarz, Annegret H. Thieken

“…Abstract Flood damage data are needed for various applications. Structural damage of buildings can reflect not only the economic damage but also the life‐threatening condition of a building, which provide crucial information for disaster response and recovery. …”
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