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. …”
Get full text

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. …”
Get full text

Automated identification of bulk structures, two-dimensional materials, and interfaces using symmetry-based clustering by Thea Denell, Lauri Himanen, Markus Scheidgen, Claudia Draxl

“…Abstract With the rapidly increasing amount of materials data being generated in a variety of projects, efficient and accurate classification of atomistic structures is essential. …”
Get full text

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. …”
Get full text

A digital twin framework with MobileNetV2 for damage detection in slab structures by Duong Huong Nguyen, Huan Nguyen, Xiaohong Gao

“…To verify the proposed framework, we present a case study of slab structure using deflection measurement as input data. …”
Get full text

New Method of Impact Localization on Plate-like Structures Using Deep Learning and Wavelet Transform by Asaad Migot, Ahmed Saaudi, Victor Giurgiutiu

“…This paper presents a new methodology for localizing impact events on plate-like structures using a proposed two-dimensional convolutional neural network (CNN) and received impact signals. …”
Get full text

OAC-HAS: outsourced access control with hidden access structures in fog-enhanced IoT systems by Jiale Zhang, Zhen Cheng, Xiang Cheng, Bing Chen

“…In this paper, we propose an outsourced access control scheme with hidden access structures, named OAC-HAS, in fog-enhanced IoT systems. …”
Get full text

A Conditional Simulation Method for Predicting Wind Pressure Fields of Large-Span Spatial Structures by Fangjin Sun, Tiantian Liu, Daming Zhang, Zhonghao Xu

“…Considering the complexity of wind pressure fields of large-span spatial structures, a simplified nonparametric method based on conditional simulation is proposed to predict the unknown pressures using the existing data. …”
Get full text

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. …”
Get full text

Modeling of settlement of shallow-founded rocking structures using explainable physics-guided machine learning by Sivapalan Gajan, Christopher Kantor

“…Rocking foundation is an unorthodox seismic design philosophy of structures that enhances the performance of structures by absorbing and dissipating seismic energy into soil. …”
Get full text

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. …”
Get full text

MaxComp: Predicting single-cell chromatin compartments from 3D chromosome structures. by Yuxiang Zhan, Francesco Musella, Frank Alber

“…To address this, we present MaxComp, an unsupervised method, for inferring single-cell A/B compartments based on 3D geometric considerations in single-cell chromosome structures-derived either from multiplexed FISH-omics imaging or 3D structure models derived from Hi-C data. …”
Get full text

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). …”
Get full text

Spatiotemporal Deformation Prediction Model for Retaining Structures Integrating ConvGRU and Cross-Attention Mechanism by Yanyong Gao, Zhaoyun Xiao, Zhiqun Gong, Shanjing Huang, Haojie Zhu

“…With the exponential growth of engineering monitoring data, data-driven neural networks have gained widespread application in predicting retaining structure deformation in foundation pit engineering. …”
Get full text

Novel Automatic Classification Method for Geological Structures in Carbonate Formations Based on Electrical Imaging Logging by FU Yafeng, HUANG Ke, ZHU Hanbin, WANG Hui, ZHANG Xu, ZHAO Jie, XIAO Ni

“…Finally, these features are used to train an extreme gradient boosting (XGBoost) model, enabling the automatic classification of different geological structures. Validation using actual carbonate logging data shows that the classification accuracy of this method exceeds an 80% agreement rate with core observations. …”
Get full text

A Numerical Approach to Calculate the Radiation Efficiency of Baffled Planar Structures Using the Far Field by Mario A. GONZÁLEZ-MONTENEGRO, Roberto JORDAN, Arcanjo LENZI, Jorge P. ARENAS

“…In this work a different approach is used, based in the so-called Propagating Matrix, which is useful for calculating the sound pressure of an arbitrary number of points into free space, and it can be employed to estimate the sound power by integrating over a finite number of pressure points over a hemispherical surface surrounding the vibrating structure. Through numerical analysis, the advantages/disadvantages of the current method are investigated, when compared with numerical methods based on near field data. …”
Get full text

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. …”
Get full text

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. …”
Get full text

MODELING AND MATHEMATICAL PROCESSING OF GEODETIC LEVELING NETWORK WHILE MONITORING SETTLEMENT OF UNIQUE ENGINEERING STRUCTURES by D. V. Usov

“…The paper shows that reliability and trust of geodetic structure monitoring are related with new principles of leveling network construction, their testing and mathematical processing. …”
Get full text

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. …”
Get full text