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

“…This research therefore investigates the litho-structural trends and the overburden thickness around Shaki area, Southwestern, Nigeria. …”
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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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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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LUOJIA Explorer PMS: Panoramic Odometry and Mapping with Structural Information by Y. Xu, Y. Xu, Y. Xu, C. Chen, C. Chen, C. Chen, B. Yang, B. Yang, B. Yang, L. Li, Z. Wang, Z. Wang, Z. Wang, S. Sun, S. Sun, S. Sun, Z. Yan, Z. Yan, Z. Yan, S. Wu, S. Wu, S. Wu

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Structural Health Monitoring under Nonlinear Environmental or Operational Influences by Jyrki Kullaa

“…Vibration-based structural health monitoring is based on detecting changes in the dynamic characteristics of the structure. …”
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3D complex: a structural classification of protein complexes. by Emmanuel D Levy, Jose B Pereira-Leal, Cyrus Chothia, Sarah A Teichmann

“…Finally, through comparison of Biological Units in the Protein Data Bank with the Protein Quaternary Structure database, we identified many possible errors in quaternary structure assignments. …”
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Hemomicrocirculation and immune structural components changesin Chernobyl accident liquidators by F. F. Tetenev, Ya. V. Porovsky, T. N. Bodrova, A. I. Ryzhov, T. P. Vetlugina

“…The aim of the study was to investigate correlation of immunity structural components (morphologic-functional changes in derma and systemic immune reactionof the organisms of Chernobyl accident liquidators. …”
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Investigation and role of seismic table in dynamic analysis of structural parts by mahdi koushamanesh

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Structural and social determinants of health: The multi-ethnic study of atherosclerosis. by Lilah M Besser, Sarah N Forrester, Milla Arabadjian, Michael P Bancks, Margaret Culkin, Kathleen M Hayden, Elaine T Le, Isabelle Pierre-Louis, Jana A Hirsch

“…<h4>Background</h4>Researchers have increasingly recognized the importance of structural and social determinants of health (SSDOH) as key drivers of a multitude of diseases and health outcomes. …”
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Encoding Mie, plasmonic, and diffractive structural colors in the same pixel by Kim Youngji, Hyun Jerome K.

“…We present a 1D reflective multi-level structural color design that incorporates Mie, plasmonic, and diffractive mechanisms in the same pixel. …”
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Dynamic and structural characteristics of responsible investment strategies: regional focus by Yu.V. Yelnikovа

“…These data were structured by regions of the largest distribution of responsible investment in the world and taking into account the most well-known investment strategies: screening (exclusion), ESG integration, corporate involvement and stakeholder engagement, norm-based screening, positive screening (best-in-class), sustainable thematic investment, impact investment (impact / community investment). …”
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Sparse Deep Neural Network for Encoding and Decoding the Structural Connectome by Satya P. Singh, Sukrit Gupta, Jagath C. Rajapakse

“…Brain state classification by applying deep learning techniques on neuroimaging data has become a recent topic of research. However, unlike domains where the data is low dimensional or there are large number of available training samples, neuroimaging data is high dimensional and has few training samples. …”
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