A Semi-Supervised Deep Network Embedding Approach Based on the Neighborhood Structure by Wenmao Wu, Zhizhou Yu, Jieyue He

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Manufacturing cycle prediction using structural equation model toward industrial early warning system simulation: The Indonesian case by Tirta Wisnu Permana, Gatot Yudoko, Eko Agus Prasetio

“…Specifically, it investigates the relationships among CLIs to forecast Indonesia's Manufacturing Cycle (ManC) using Partial Least Squares-Structural Equation Modeling (PLS-SEM).Building on an extensive literature review, the study employs quarterly data spanning from Q1 2010 to Q2 2022, incorporating five constructs representing key economic sectors influencing the manufacturing cycle. …”
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Editorial: Approaches to improve the performance of virtual screening: scoring functions, structural filtration, prediction of physicochemical properties/pharmacological activity by Hélcio Silva Dos Santos, Hélcio Silva Dos Santos, Hélcio Silva Dos Santos, Alexander Veselovsky, Dmitry Nilov

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Decomposing the Sri Lanka Yield Curve Using Principal Component Analysis to Examine the Term Structure of the Interest Rate by K P N Sanjeewa Dayarathne, Uthayasanker Thayasivam

“…Our analysis encompasses data spanning from January 2010 to August 2022. The study applied several PCA variants such as multivariate PCA, Randomized PCA, Incremental PCA, Sparse PCA, Functional PCA, and Kernel PCA on smoothed data. …”
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Development of a Large Database of Italian Bridge Bearings: Preliminary Analysis of Collected Data and Typical Defects by Angelo Masi, Giuseppe Santarsiero, Marco Savoia, Enrico Cardillo, Beatrice Belletti, Ruggero Macaluso, Maurizio Orlando, Giovanni Menichini, Giacomo Morano, Giuseppe Carlo Marano, Fabrizio Palmisano, Anna Saetta, Luisa Berto, Maria Rosaria Pecce, Antonio Bilotta, Pier Paolo Rossi, Andrea Floridia, Mauro Sassu, Marco Zucca, Eugenio Chioccarelli, Alberto Meda, Daniele Losanno, Marco Di Prisco, Giorgio Serino, Paolo Riva, Nicola Nisticò, Sergio Lagomarsino, Stefania Degli Abbati, Giuseppe Maddaloni, Gennaro Magliulo, Mattia Calò, Fabio Biondini, Francesca da Porto, Daniele Zonta, Maria Pina Limongelli

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D3GNN: Double dual dynamic graph neural network for multisource remote sensing data classification by Teng Yang, Song Xiao, Jiahui Qu

“…Nevertheless, GNN faces challenges as the manually defined static graph structure might not accurately capture the complexity of the data. …”
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Structural and functional insights into the pilotin-secretin complex of the type II secretion system. by Shuang Gu, Saima Rehman, Xiaohui Wang, Vladimir E Shevchik, Richard W Pickersgill

“…Gram-negative bacteria secrete virulence factors and assemble fibre structures on their cell surface using specialized secretion systems. …”
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Utility of UAS-LIDAR for estimating forest structural attributes of the Miombo woodlands in Zambia. by Hastings Shamaoma, Paxie W Chirwa, Jules C Zekeng, Abel Ramoelo, Andrew T Hudak, F Handavu, Stephen Syampungani

“…The estimation of forest structural data in area-based forest inventories relies on the relationship between field-based estimates of forest structural attributes (FSA) and lidar-derived metrics at plot level, which can be modeled using either parametric or non-parametric regression techniques. …”
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Structural Feature-Preserving Point Cloud Denoising Method for Aero-Engine Profile by Jieqiong Yan, Laishui Zhou, Jun Wang, Xiaoping Wang, Xia Liu

“…In order to ensure that noise is removed without blurring or distorting structural features, a structural feature-preserving point cloud denoising method is proposed. …”
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Structural Component Identification and Damage Localization of Civil Infrastructure Using Semantic Segmentation by Piotr Tauzowski, Mariusz Ostrowski, Dominik Bogucki, Piotr Jarosik, Bartłomiej Błachowski

“…The data includes semantic segmentation masks for both categorizing structural elements (slabs, beams, and columns) and assessing structural damage (concrete spalling or exposed rebars). …”
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Deep learning of structural morphology imaged by scanning X-ray diffraction microscopy by Aileen Luo, Tao Zhou, Martin V. Holt, Andrej Singer, Mathew J. Cherukara

“…Abstract Scanning X-ray nanodiffraction microscopy is a powerful technique for spatially resolving nanoscale structural morphologies by diffraction contrast. One of the critical challenges in experimental nanodiffraction data analysis is posed by the convergence angle of nanoscale focusing optics which creates simultaneous dependency of the far-field scattering data on three independent components of the local strain tensor—corresponding to dilation and two potential rigid body rotations of the unit cell. …”
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Interpretive Structural Modeling of Factors Affecting Organizational Ambidexterity in the Ministry of Sports and Youth by Ainolah Ahmadnejad Joghie, Mozafar Yektayar, Mozhgan Khodamoradpoor

“…The statistical population of this study consisted of experts who were selected purposefully based on theoretical saturation of 15 of them. Semi-structured interviews were used to collect data in the qualitative study and a questionnaire was used to collect data in the quantitative study. …”
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Intelligent Identification of Structural Damage Based on the Curvature Mode and Wavelet Analysis Theory by Longsheng Bao, Yue Cao, Xiaowei Zhang

“…Data fitting is then performed to estimate the degree of structural damage. …”
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Predictive modeling of visible-light azo-photoswitches’ properties using structural features by Said Byadi, P. K. Hashim, Pavel Sidorov

“…Abstract In this manuscript we present the strategy for modeling photoswitch properties (maximum absorption wavelength and thermal half-life of photoisomers) of visible-light azo-photoswitches using structural data. We compile a comprehensive data set from literature sources and perform a rigorous benchmark to select the best feature type and modeling approach. …”
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Structural Constraints in Current Stomatal Conductance Models Preclude Accurate Prediction of Evapotranspiration by Pushpendra Raghav, Mukesh Kumar, Yanlan Liu

“…In contrast, a ML approach, wherein the model structure is learned from the data, outperforms traditional models, thus highlighting that there still is significant room for improvement in the structure of traditional models for predicting ET. …”
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Enhancing structural health monitoring with machine learning for accurate prediction of retrofitting effects by A. Presno Vélez, M. Z. Fernández Muñiz, J. L. Fernández Martínez

“…This research aimed to develop a methodology for training an artificial intelligence (AI) system to predict the effects of retrofitting on civil structures, using data from the KW51 bridge (Leuven). …”
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THE METHOD OF ADAPTIVE STATISTICAL CODING TAKING INTO ACCOUNT THE STRUCTURAL FEATURES OF VIDEO IMAGES by Volodymyr Barannik, Dmytro Havrylov, Serhii Pantas, Yurii Tsimura, Tatayna Belikova, Rimma Viedienieva, Vasyl Kryshtal

“…To reduce the output volume, the RLE algorithm and integral arithmetic coding are adapted to the new structure of the input data. Thus, the method of linearization of two-dimensional transformants based on zig-zag scanning was further developed. …”
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Synthesis and structural study of the Linde Type-A zeolite prepared from kaolinite by Szilvia Ormándi, István Dódony

“…The measured hkl and intensity data sets are the inputs for structure determination. …”
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Spearman Rank Correlation PCA for Mixed Scale Indicator in Structural Equation Modeling by Lisa Asaliontin, Eni Sumarminingsih, Solimun Solimun, Mohammad Ohid Ullah

“…Structural Equation Modeling (SEM) is a statistical modeling technique that integrates measurement models and structural models simultaneously. …”
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Durability Test and Service Life Prediction Methods for Silicone Structural Glazing Sealant by Bo Yang, Junjin Liu, Jianhui Li, Chao Wang, Zhiyuan Wang

“…Silicone structural glazing (SSG) sealants are crucial sealing materials in modern building curtain walls, whose performance degradation may lead to functional and safety issues, posing significant challenges to building safety maintenance. …”
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