Emergent Technologies in Big Data Sensing: A Survey by Ting Zhu, Sheng Xiao, Qingquan Zhang, Yu Gu, Ping Yi, Yanhua Li

“…However, big data is a fuzzy data science concept and there is no existing research architecture for it nor a generic application structure in the field of sensing. …”
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Proactive Data Categorization for Privacy in DevPrivOps by Catarina Silva, João P. Barraca, Paulo Salvador

“…Our approach uses a hierarchical, multi-tiered tree structure, encompassing direct data categorization, dynamic tags, and structural attributes. …”
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From data to medical context: the power of categorization in healthcare by Batoul Msheik, Hamid Mcheick, Sara Hariri, Mehdi Adda, Mohamed Dbouk

“…In the rapidly evolving healthcare domain, the ability to structure and interpret contextual medical data is crucial for delivering personalized and efficient patient care. …”
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Listen to genes: dealing with microarray data in the frequency domain. by Jianfeng Feng, Dongyun Yi, Ritesh Krishna, Shuixia Guo, Vicky Buchanan-Wollaston

“…<h4>Background</h4>We present a novel and systematic approach to analyze temporal microarray data. The approach includes normalization, clustering and network analysis of genes.…”
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Characterising London parks and gardens using open data by Dace Kirsteina, Marie A.E. Mueller, Ross S. Purves

“…To do so, we used open data, including OpenStreetMap and Light Detection and Ranging (LiDAR) data, to measure six characteristics, identified from the literature as being important for well-being, in 1,638 parks in London: size, trail and pathway density, water cover, buildings and other anthropogenic features, horizontal vegetation coverage, and vertical vegetation structure. …”
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MTAHG and MTBHG: Modified Approaches for Interpreting Gravity Data by Hazel Deniz Toktay, Hanbing Ai, Ahmad Alvandi, Kejia Su, Jinlei Li

“…Locating these signatures using edge detection techniques is crucial for geological structural interpretation and imaging of horizontal boundaries. …”
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Data‐Driven Kinematic Modeling of Physical Origami Robots by Mustafa Mete, Alexander Schüßler, Yves Martin des Taillades, Bruno Trivelli, Jamie Paik

“…Origami‐inspired structures facilitate the design of compliant and compact robots. …”
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Evaluation of Plaid Models in Biclustering of Gene Expression Data by Hamid Alavi Majd, Soodeh Shahsavari, Ahmad Reza Baghestani, Seyyed Mohammad Tabatabaei, Naghme Khadem Bashi, Mostafa Rezaei Tavirani, Mohsen Hamidpour

“…Two simulated matrices with different degrees of overlap and noise are generated and then the intrinsic structure of these data is compared with biclusters result. …”
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An autoencoder for compressing angle-resolved photoemission spectroscopy data by Steinn Ýmir Ágústsson, Mohammad Ahsanul Haque, Thi Tam Truong, Marco Bianchi, Nikita Klyuchnikov, Davide Mottin, Panagiotis Karras, Philip Hofmann

“…Angle-resolved photoemission spectroscopy (ARPES) is a powerful experimental technique to determine the electronic structure of solids. Advances in light sources for ARPES experiments are currently leading to a vast increase of data acquisition rates and data quantity. …”
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Methods of teaching educational data mining for pedagogical students by E. A. Terbusheva

“…The main aspects underlying the methodology: a form of flipped learning, a concentric (iterative) content structure, research teaching methods, a set of practical tasks for developing research competencies and Weka software for data mining as the main technical training tool for practical tasks implementation. …”
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DATA COMPRESSION USING WAVELET TRANSFORM IN BIOTELEMETRY SYSTEMS by O.E. Bezborodova, A.Yu. Bodin, O.N. Bodin, M.N. Kramm, D.V. Martynov

“…For a biotelemetric system as a radio engineering and information-measuring system, the main indicators are measurement error and reliability of data transmission. Materials and methods. The article presents a structural diagram of a biotelemetric system, based on the structure of the developed distributed cardiodiagnostic system and its communication channel, and discusses data compression methods based on redundancy reduction and wavelet transformation. …”

Expert information technology in the collection and analysis of computer data by M. H. Shcherbakovskyi, S. O. Kolomiitsev

“…In the modern period of society’s informatisation, the growth of heterogeneous information resources, the development of information technology and the existence of traces of offences in the form of computer data serve as the basis for the formation of expert information technologies. …”
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Adaptive Data Warehouse as the Technological basis of the banking Ecosystem by E. V. Vasilieva, K. S. Solyanov, T. D. Konevtseva

“…It makes it possible to set the warehouse contours for specific business tasks, combine elements, and expand the structure of the banking data warehouse in the context of its integration with various external software objects. …”
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Statistical data analysis methods in Brillouin spectroscopy: Tutorial by Christopher G. Poulton, Hadi Mahmodi, Matthew D. Arnold, Luke McAlary, Lezanne Ooi, Irina Kabakova

“…In this tutorial, we discuss in detail the application of the two unsupervised machine learning methods, principal component analysis and vertex component analysis, which can be used to retrieve information from the Brillouin microscopy data of heterogeneous samples. The main advantage of both methods is their unsupervised nature, thus no preliminary knowledge of structure and composition is needed to isolate the components of interest. …”
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Online Asynchronous Learning over Streaming Nominal Data by Hongrui Li, Shengda Zhuo, Lin Li, Jiale Chen, Tianbo Wang, Jun Tang, Shaorui Liu, Shuqiang Huang

“…However, most existing online learning methods assume homogeneous data types and synchronous arrival of features and labels. …”
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Starrydata: from published plots to shared materials data by Yukari Katsura, Masaya Kumagai, Tomoya Mato, Yu Takada, Yuki Ando, Erina Fujita, Fumikazu Hosono, Eiji Koyama, Farhan Mudasar, Ton Nu Thanh Phuong, Naoto Saito, Yoshihiro Sakamoto, Atsumi Tanaka, Dewi Yana, Kaoru Kimura, Koji Tsuda, Masahiko Demura

“…In this paper, we introduce the web interface, data curation workflow, data structure, and system architecture of Starrydata2. …”
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Quantum-Inspired Data Embedding for Unlabeled Data in Sparse Environments: A Theoretical Framework for Improved Semi-Supervised Learning without Hardware Dependence by Shawn Ray

“…This approach aims to advance semi-supervised learning in contexts characterized by limited labeled data by enabling more intricate and expressive embeddings that capture the underlying structure of the data effectively. …”
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An integrative framework to combine migratory connectivity and demographic data by Killian A. Gregory, Charlotte Francesiaz, Frédéric Jiguet, Pierre‐André Crochet, Pierrick Bocher, Heinz Düttmann, Jaanus Elts, Thomas Fartmann, Stefan Garthe, Steffen Kämpfer, Helmut Kruckenberg, Riho Marja, Markus Piha, Philipp Schwemmer, Aurélien Besnard

“…This flexible framework can be generalised to include diverse data on migration movements, population structure, individual heterogeneity or environmental variables, allowing further investigation of the interaction between migration patterns and population dynamics.…”
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Innovative Solutions for Oil Well Monitoring: Data-Driven Multiphase Virtual Flow Metering Using Ensemble Machine Learning and Historical Field Data by Wael A. Farag, Hussein H. Ismail, Muhammad Nadeem

“…By combining data-driven ensemble machine-learning algorithms and historical oil field portable test reports, this paper proposes a Data-Drive Multiphase Virtual Flow Meter (DD-MVFM) that estimates oil, gas, and water flow rates and provides real-time monitoring, and predicts future production with appropriate accuracy. …”
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Building an Associative Classification Data Model Based on the Apriori Method by K. V. Mulyukova, V. M. Kureichik

“…The module includes an intelligent data processing class. The structural scheme of the module and system architecture were developed. …”
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