THE NEOTECTONIC STRUCTURE OF INTERMOUNTAIN BASINS OF MOUNTAINOUS ALTAI ACCORDING TO ELECTROMAGNETIC AND GEOLOGICAL DATA by N. N. Nevedrova, A. M. Sanchaa, E. V. Deev, S. M. Babushkin

“…The article presents new data on the geoelectrical structure of Chuya, Kuray and Uymon intermountain basins, which are the three largest ones in Mountainous Altai, Russia. …”
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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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MRS-BIDS, an extension to the Brain Imaging Data Structure for magnetic resonance spectroscopy by Amy E. Bouchard, Dickson Wong, Wolfgang Bogner, Rémi Gau, Yaroslav O. Halchenko, Damon G. Lamb, Christopher J. Markiewicz, Paul G. Mullins, Guiomar Niso, Georg Oeltzschner, BIDS Maintainers, William T. Clarke, Martin Wilson, Mark Mikkelsen

“…The Brain Imaging Data Structure (BIDS) is an increasingly adopted standard for organizing scientific data and metadata. …”
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Combining Several Substitution Cipher Algorithms using Circular Queue Data Structure by Noor Ibraheem, Mokhtar Hasan

“…Lots of algorithms and techniques are available for data security.  This paper presents a cryptosystem that combines several Substitution Cipher Algorithms along with the Circular queue data structure. …”
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Fast and accurate short-read alignment with hybrid hash-tree data structure by Junichiro Makino, Toshikazu Ebisuzaki, Ryutaro Himeno, Yoshihide Hayashizaki

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A CDE-based data structure for radiotherapeutic decision-making in breast cancer by Fabio Dennstädt, Maximilian Schmalfuss, Johannes Zink, Janna Hastings, Roberto Gaio, Max Schmerder, Nikola Cihoric, Paul Martin Putora

“…Abstract Background The growing complexity of oncology and radiation therapy demands structured and precise data management strategies. The National Institutes of Health (NIH) have introduced Common Data Elements (CDEs) as a uniform approach to facilitate consistent data collection. …”
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Determination of Spatial-Temporal Correlation Structure of Troposphere Ozone Data in Tehran City by S.S. Mousavi, M. Mohammadzadeh

“…For eliminating the trend of data, a dynamic linear model is used, then some features of correlation structure of de-trended data, such as stationarity, symmetry and separability are considered. …”
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Research on Smart Scaling Mechanism and Structure for Big Data Network Server Groups by Hongyao Ju

“…The principle and construction of the structure of smart telescopic on big data network server groups were elaborated.The key technologies involved in the smart scaling of big data network server groups were discussed.After investigating key technologies,including the monitoring of the workload of the server group,the smart control of the number of servers,and the scheduling of access loads,the principle and realization method for the smart scaling of big data network server groups were proposed and technical supports were provided for the smart scaling and effective energy conservation of big data network server groups.According to the proposed construction method and key technologies,a smart scaling model for big data network server groups was provided as well.…”
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New data on the geological structure and zonality of the Vorontsovka gold field in the Northern Urals by Vikentyev I. V., Vikentieva O. V., Blokov I. V., Vykhristenko R. I., Yushko N. A., Krinochkin L. A.

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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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SemantiPack: An Efficient Real-World Data Compressor Using Structural and Semantic Metadata by Yoshiteru Nagata, Daiki Kohama, Yoshiki Watanabe, Shin Katayama, Kenta Urano, Takuro Yonezawa, Nobuo Kawaguchi

“…The exponential growth of Real-World Data (RWD), primarily collected from IoT sensors and spanning domains such as mobility, environment, and energy consumption, presents critical challenges due to its scale, heterogeneity, and structural variability. …”
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Preliminary data on terrestrial isopods from some railways in Dobruja, eastern Romania by Daniel-Răzvan POP, Alexandra-Roxana-Maria MAIER, Achim-Mircea CADAR, Sára FERENȚI

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DEEP STRUCTURE OF THE ALTAI MOUNTAINS AND MODERN GRAVITY FIELD MODELS by V. Yu. Timofeev, D. G. Ardyukov, D. N. Goldobin, A. V. Timofeev, D. A. Nosov, I. S. Sizikov, E. N. Kalish, Yu. F. Stus

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Enhancing Anomaly Detection in Structured Data Using Siamese Neural Networks as a Feature Extractor by Elizabeth P. Chou, Bo-Cheng Hsieh

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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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RETRACTED: An Adaptive Hierarchical Network Model for Studying the Structure of Economic Network by Xiaoteng Yang, Zhenqiang Wu, Shumaila Javaid

“…In the presented dynamically evolving network model, new directed edges are generated depending on the existing nodes and the hierarchical structures among the network, and these edges decay over time. …”
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Scanning the Universe for Large-Scale Structures Using Gamma-Ray Bursts by Istvan Horvath, Zsolt Bagoly, Lajos G. Balazs, Jon Hakkila, Bendeguz Koncz, Istvan I. Racz, Peter Veres, Sandor Pinter

Subjects: “…cosmology: large-scale structure of the universe…”
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Beyond contrastive learning: adaptive graph representations with mutual information maximization for blockchain and structured data by Yifeng Zhang, Qianqian Ren, Yourong Chen, Meng Han

“…Abstract Graph representation learning has emerged as a powerful approach for modeling structured data across diverse domains, including social networks, biochemical interactions, and financial transaction systems. …”
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Identifying the diagnostic gap of tardive dyskinesia: an analysis of semi-structured electronic health record data by Kira Griffiths, Yida Won, Zachery Lee, Lu Wang, Christoph U. Correll, Rashmi Patel

“…Results Altogether, 1,301 (4.0%) patients had either description of abnormal movements associated with TD (n=691) or documented TD (n=610) within semi-structured EHR data. Of those patients, only 64 (4.9%) had an ICD-TD diagnosis in structured EHR data. …”
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Federated Learning in Healthcare: A Benchmark Comparison of Engineering and Statistical Approaches for Structured Data Analysis by Siqi Li, Di Miao, Qiming Wu, Chuan Hong, Danny D’Agostino, Xin Li, Yilin Ning, Yuqing Shang, Ziwen Wang, Molei Liu, Huazhu Fu, Marcus Eng Hock Ong, Hamed Haddadi, Nan Liu

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