Structural Safety Evaluation of Tunnel Based on the Dynamic Monitoring Data during Construction by Xiaokun Yan, Hu Li, Feng Liu, Yang Liu

“…It is still a challenge to accurately evaluate the structural safety of tunnel during the process of construction. …”
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The Impact of Structural Funds on Regional Growth: A Panel Data Spatial Analysis by Micaela Antunes, Miguel Viegas, Celeste Varum, Carlos Pinho

“…However, the new economic geography states that structural funds may also facilitate the geographic concentration of economic activities, thus perpetuating regional imbalances. …”
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THE CENOZOIC CRUSTAL STRESS STATE OF MONGOLIA ACCORDING TO GEOLOGICAL AND STRUCTURAL DATA (REVIEW) by V. A. Sankov, A. V. Parfeevets

“…The studies commenced in the southern Baikal rift zone in the 1970s and were extended further southwards to cover mobile regions neighbouring the Siberian platform. Geological, structural and morphostructural data were collected and analysed to define the crustal stress types and spatial characteristics. …”
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Information hiding algorithm based on mapping and structure data of 3D model by Shuai REN, Zhen WANG, Dongxu SU, Tao ZHANG, Dejun MU

“…The existing 3D information hiding schemes are not robust enough against the joint attacks,as a result the secret information will be vulnerable and cannot be extracted correctly.In order to solve the above problem,an information hiding algorithm based on mapping and structure data of 3D models was proposed.First,several texture maps of the original 3D models in .stl format were picked from the standard model library,so the backup secret data after twice two-dimension discrete Daubechies transform can be embedded using dbl function just as the watermark.Secondly,the original 3D model in .stl format was operated by frame sampling in wavelet domain to obtain the coefficient in transform domain,thus the secret data was embedded into the corresponding transform coefficient.Finally,the .obj documents with the secret information were generated by multiplying the 2D texture map data and the 3D .stl data matrix based on orthogonal projection.Texture maps and coordinate space of 3D model were both used to embed the secret information repeatedly in order to enhance the robustness.The experiment analysis indicated that the imperceptibility,robustness and resistance against analysis are improved and information transmission safety in complex environment can be achieved based on the redundancy space of multi-type carriers.…”
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Faster computation of left-bounded shortest unique substrings by Larissa L. M. Aguiar, Felipe A. Louza

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TS-WRSVM: twin structural weighted relaxed support vector machine by Fatemeh Sheykh Mohammadi, Ali Amiri

Subjects: “…imbalanced data classification…”
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Modal Parameters Estimation of Building Structures from Vibration Test Data Using Observability Measurement by Jae-Seung Hwang, Hongjin Kim, Bong-Ho Cho

“…The numerical simulation is performed to evaluate the proposed procedure, and the results show that the modal participation factor and mode shapes are estimated from the structural responses accurately. The procedure is also applied to the experimental data obtained from the shaking table test of a three-story shear building model.…”
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The Data-Driven Performance Prediction of Lattice Structures: The State-of-the-Art in Properties, Future Trends, and Challenges by Siyuan Yang, Ning Dai, Qianfeng Cao

Subjects: “…lattice structure…”
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Delineation of mineralization-related geologic structures and lithological units using airborne magnetic and radiometric data by Christian Ordóñez, Stephen Eguba Ekwok, Ahmad Alkhayaat, Pardeep Singh Bains, Rohit Sharma, Raman Kumar, Ankur Kulshreshta, Vikasdeep Singh Mann, Yasser Elmasry

Subjects: “…Geologic structures…”
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Characterizing Subsurface Structures From Hard and Soft Data With Multiple‐Condition Fusion Neural Network by Zhesi Cui, Qiyu Chen, Jian Luo, Xiaogang Ma, Gang Liu

“…In this study, we introduce a multiple‐condition fusion network (MCF‐Net) to characterize subsurface structures based on both hard and soft data. To harness the full potential of multiple‐source subsurface observations, two distinct neural networks extract implicit features from hard and soft data. …”
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The intraorganic architecture of musculoskeletal structures in maxillofacial area of children according to x-ray diagnostics data

“…The combined use of the methods of teleradiography, computer and magnetic resonance imaging to study the structure of bone structures of MFA on the same object provides information that significantly reinforce the concept of morpho-functional unity of all structural components of the facial part of the head.…”
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A Method for Compressing Event Log Data Based on Combinatorial Generation Using AND/OR Tree Structures by Yuriy Shablya

“…Based on this idea, a method for compressing event log data based on combinatorial generation using AND/OR tree structures is proposed. …”
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Gravity Data Fusion and Imaging of Geological Structures in the Red River Fault Zone and Adjacent Areas by Guiju Wu, Fei Yu, Hongbo Tan, Jiapei Wang, Weihua Liu

“…The geological structure in the Red River fault zone (RRF) and adjacent areas is complex. …”
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An Enhanced Cloud Network Integrity and Fair Compensation Scheme Through Data Structures and Blockchain Enforcement by Renato Racelis Maaliw

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Improving the performance of damage repair in thin-walled structures with analytical data and machine learning algorithms by Abdul Aabid, Md Abdul Raheman, Meftah Hrairi, Muneer Baig

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Damage Indicators for Structural Monitoring of Fiber-Reinforced Polymer-Strengthened Concrete Structures Based on Manifold Invariance Defined on Latent Space of Deep Autoencoders by Javier Montes, Juan Pérez, Ricardo Perera

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Large Language Model-Driven Structured Output: A Comprehensive Benchmark and Spatial Data Generation Framework by Diya Li, Yue Zhao, Zhifang Wang, Calvin Jung, Zhe Zhang

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Constructing Rasterized Covariates from LiDAR Point Cloud Data via Structured Query Language by Rory Pittman, Baoxin Hu

Subjects: “…structured query language (SQL)…”
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Enhancing structured data generation with GPT-4o evaluating prompt efficiency across prompt styles by Ashraf Elnashar, Jules White, Douglas C. Schmidt

Subjects: “…structured data generation…”
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UPN-GCN: Update Positive-Negative Graph Convolution Neural Network in Non-Euclidean Structured Data by Lijun Fan, Shichao Yi, Wenrui Guan, Pingxin Wang

“…Graph Convolutional neural Networks (GCNs) demonstrate exceptional effectiveness when working with data that have non-Euclidean structures. In recent years, numerous researchers have utilized GCNs for data with Euclidean structures. such as image data and language data, and achieved good results, expanding the application scope of GCN. …”
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