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

“…However, the security and privacy issues, such as data leakage, still challenge the wide deployment of fog computing infrastructure. …”
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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. …”
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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. …”
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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. …”
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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. …”
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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. …”
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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. …”
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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. …”
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Modelling of Correlated Ordinal Responses, by Using Multivariate Skew Probit with Different Types of Variance Covariance Structures by Mohammad Reza Zadkarami, Mohammad Reza ghalani

“…The Schizophrenia Collaborative Study data invokes the proposed MFSN model. The results confirm that the first-order autoregressive (AR(1)) structure substantially enhances the estimation of the parameters. …”
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Determination of the enthalpy of evaporation of pentaerythritol esters of various structures using gas chromatographic retention characteristics by Yu. F. Ivanova, V. V. Emelyanov, S. V. Levanova, Yu. N. Telnov

“…The enthalpies of evaporation calculated based on the enthalpies of sorption and logarithmic retention indices within the limits of error of the correlation dependencies coincide with the literature data and the values predicted by the quantitative structure–property relationship method. …”
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Soft-Sediment Deformation Structures Interpreted as Seismites in the Kolankaya Formation, Denizli Basin (SW Turkey) by Savaş Topal, Mehmet Özkul

“…The deformation mechanism and driving force for the soft-sediment deformation are related essentially to gravitational instability, dewatering, liquefaction-liquidization, and brittle deformation. Field data and the wide lateral extent of the structures as well as regional geological data show that most of the deformation is related to seismicity and the structures are interpreted as seismites. …”
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Path analysis of the effect of irrational beliefs on the structures of the planned behavior model in the field of physical activity by Bita Arabnarmi, Hesam Ramezanzade

“…A path analysis model was used to analyse the relationships between variables and calculate the direct and indirect structural effects. Also, multiple regression analysis was used to predict theoretical constructs of planned behavior using irrational beliefs dimensions. …”
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The impact of environmental conditions of Persian Gulf on the probability of chloride corrosion initiation in reinforced concrete structures by Hossein Rahami, shahram abedini, S. M. Mirhosseini Hezaveh, Mohammad GhanooniBagha, Ehsanollah Zeighami

“…According to the technical literature, the amount of chloride that is transported by air from the sea surface depends on the amount of salt in the seawater in that area, the speed and direction of the wind, and the distance from the sea. Accordingly, data on the highest annual wind speed and direction of the wind are collected in several reinforced concrete structures (RC structures) in southern cities near the Persian Gulf at different distances from the sea. …”
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Development of a hybrid model of the tensile behaviour of weft-knitted structures for medical compression stockings by Inés Pita Miguélez, Ahmad Rashed Labanieh, Coline Mesmin, David Dupuy, Damien Soulat

“…A unit cell was used to model the weft-knitted fabric at a mesoscopic level. 3D-shell elements and connectors were combined in the unit cell to model the mechanical behaviour of the loop structure and the inlay yarn, respectively. Mechanical and structural parameters were identified from experimental data. …”
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Machine Learning Models for Carbonation Depth Prediction in Reinforced Concrete Structures: A Comparative Study by Rafael Aredes Couto, Igor Augusto Guimarães Campos, Elvys Dias Reis, Daniel Hasan Dalip, Flávia Spitale Jacques Poggiali, Péter Ludvig

“…The methodologies developed here can be extended beyond carbonation modeling to other deterioration processes, supporting data-driven strategies for maintenance planning and resilience design in RC structures.…”
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Multifunctional TPMS-based interpenetrating phase composites: A comprehensive review of structure, properties, piezoelectricity and applications by Kishor B. Shingare, Suhas Alkunte, Baosong Li, Andreas Schiffer, Ian Kinloch, Kin Liao

“…It highlights their pivotal role in advancing technology and addressing contemporary challenges while illuminating the uncharted possibilities presented by TPMS cellular structures in the dynamic landscape of 3D printing.…”
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Damage Identification in Large-Scale Structures Using Time Series Analysis and Improved Sparse Regularization by Huihui Chen, Xiaojing Yuan

“…The academic community has paid much attention to the research topic of structural health monitoring (SHM) and damage identification for several decades, which flourishes the development of diverse damage identification approaches. …”
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Predicting Future Deterioration of Hydraulic Steel Structures with Markov Chain and Multivariate Samples of Statistical Distributions by Guillermo A. Riveros, Elias Arredondo

“…Combined effects of several complex phenomena cause the deterioration of elements of steel hydraulic structures on the nation’s lock systems: loss of protective systems, corrosion, cracking and fatigue, impacts, and overloads. …”
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