Construction of digital case resources for the cultivation of big data professionals by PENG Yan, WANG Jie

“…This paper outlines a structured approach to establish a systematic and serialized data resource case library, adopting a dynamic hierarchical design that comprehensively illustrates the entire big data processing workflow while enabling dynamic expansion. …”
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Data Processing Method in Medium Range Coastal Radar Complex by Dang Quang Hieu, Nguyen Xuan Truong

“…It provides solutions for such missions as command and control of maritime forces, border monitoring and control, prevention of illegal activities such as piracy, smuggling, illegal immigration, illegal fishing, supporting search and rescue (SAR) operations, and creates a common situation awareness picture of the Naval Theatre. The system structure diagram is designed to solve computational overload problem when processing large volume of data received from radar stations. …”
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Domain Terminology Collection for Semantic Interpretation of Sensor Network Data by Myunggwon Hwang, Jinhyung Kim, Jangwon Gim, Sa-kwang Song, Hanmin Jung, Do-Heon Jeong

“…In this paper, we suggest a method of domain terminology collection based on Wikipedia category information in order to prepare seed data for such knowledge bases. However, Wikipedia has two weaknesses, namely, loops and unreasonable generalizations in the category structure. …”
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Data Management System and Software for Comprehensive Assessment of the State of the Biosphere by P. K. Shalkevich, D. S. Lavnikovich, Yu. S. Gorodnaya, A. V. Chementsova

“…As part of solving the problem of a comprehensive assessment of the state of the biosphere, the urgent question is to develop a geographic information system that will not only store large amounts of data of various types, but also provide the ability to use methods for processing and analyzing this data, numerical modeling me thods and intelligent decision-making methods. …”
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Hierarchical Event Descriptor library schema for EEG data annotation by Dora Hermes, Tal Pal Attia, Sándor Beniczky, Jorge Bosch-Bayard, Arnaud Delorme, Brian Nils Lundstrom, Christine Rogers, Stefan Rampp, Seyed Yahya Shirazi, Dung Truong, Pedro Valdes-Sosa, Greg Worrell, Scott Makeig, Kay Robbins

“…We demonstrate that the HED-SCORE library schema can be used to annotate events in EEG data stored in the Brain Imaging Data Structure (BIDS). …”
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A cultural heritage data curation framework for knowledge discovery by Ruijie He, Xiaoguang Wang

“… Introduction. Cultural heritage data resources (CHDR) serve as an important foundation for the revitalization of cultural heritage. …”
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Deciphering Design of Aggregation‐Induced Emission Materials by Data Interpretation by Junyi Gong, Ziwei Deng, Huilin Xie, Zijie Qiu, Zheng Zhao, Ben Zhong Tang

“…Abstract This work presents a novel methodology for elucidating the characteristics of aggregation‐induced emission (AIE) systems through the application of data science techniques. A new set of chemical fingerprints specifically tailored to the photophysics of AIE systems is developed. …”
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Seismic data denoising based on attention dual dilated CNN by Haixia Hu, Youhua Wei, Hui Chen, Xingan Fu, Ji Zhang, Quan Wang, Shiwei Cai

“…Traditional noise suppression methods often result in the loss of critical signals, affecting subsurface structure characterization. This study introduces an innovative Attention Dual-Dilated Convolutional Neural Network (ADDC-Net) to address random noise in seismic data. …”
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The data myth: interrogating the evidence base for evidence-based peacebuilding by Roger Mac Ginty, Pamina Firchow

“…Our discussion is concerned with issues of power, inclusion, and exclusion, and particularly how knowledge hierarchies attend to the collection and use of data in relation to conflict-affected contexts. We therefore question the axiomatic nature of these data myth claims and argue that the structure and dynamics of peacebuilding actors perpetuate the myth. …”
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To share or not to share? Image data sharing in the social sciences and humanities by Elina Late, Mette Skov, Sanna Kumpulainen

“…The study analyses qualitative semi-structured interviews with 14 scholars who incorporate digital images as a core component of their research data. …”
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Decision Analysis Data Model for Digital Engineering Decision Management by Gregory S. Parnell, C. Robert Kenley, Devon Clark, Jared Smith, Frank Salvatore, Chiemeke Nwobodo, Sheena Davis

“…This paper describes a Decision Analysis Data Model (DADM) developed in model-based systems engineering software to provide the process, methods, models, and data to support decision management. …”
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Fingerprint-Based Deduplication for Renewable Energy Data On-Site Analyzing by Zeng Zeng, Liyuan Gao, Hongyue Ma, Wenjing Li

“…By studying fine-grained data fingerprinting and neural network-based renewable energy data edge-analysis technologies, we have enabled edge processing of data, reducing latency and privacy issues, and enhancing the system’s real-time processing capabilities and responsiveness.…”
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Enhancing Real Estate Data Analytics Education with Digital Badges by Jeffrey G. Robert, Marc R. Zaldivar, Helen Ajao, Zhenhuan Yang

“…Real Estate statistical courses provide foundational content for students in business programs to be proficient in data analytics and management science skills. Not only are these skills essential for future real estate finance and investment analysis courses, but also they are highly demanded by real estate employers. …”
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Environmental data provide marginal benefit for predicting climate adaptation. by Forrest Li, Daniel J Gates, Edward S Buckler, Matthew B Hufford, Garrett M Janzen, Rubén Rellán-Álvarez, Fausto Rodríguez-Zapata, J Alberto Romero Navarro, Ruairidh J H Sawers, Samantha J Snodgrass, Kai Sonder, Martha C Willcox, Sarah J Hearne, Jeffrey Ross-Ibarra, Daniel E Runcie

“…We find that maize yield traits are best predicted by genome-wide relatedness and population structure, and that incorporating envGWAS-identified variants or environment-of-origin data provide little additional predictive information. …”
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Analysis of plant metabolomics data using identification‐free approaches by Xinyu Yuan, Nathaniel S. S. Smith, Gaurav D. Moghe

“…Abstract Plant metabolomes are structurally diverse. One of the most popular techniques for sampling this diversity is liquid chromatography–mass spectrometry (LC‐MS), which typically detects thousands of peaks from single organ extracts, many representing true metabolites. …”
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SENTINEL SYSTEM – electronic system for collecting real-world data by E. O. Eremenko, M. I. Baranova

“…The need to use more and more data to generate evidence in response to new challenges in clinical medicine requires a specific response from the healthcare system. …”
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Isolation Forests for Symbolic Data as a Tool for Outlier Mining by Marcin Pełka, Andrzej Dudek

“…The paper aims to propose how to adapt isolation forests for symbolic data case. Methodology: Isolation forest for symbolic data is used to detect outliers in four different artificial datasets with known cluster structure and a known number of outliers. …”
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Foundations and Innovations in Data Fusion and Ensemble Learning for Effective Consensus by Ke-Lin Du, Rengong Zhang, Bingchun Jiang, Jie Zeng, Jiabin Lu

“…Ensemble learning and data fusion techniques play a crucial role in modern machine learning, enhancing predictive performance, robustness, and generalization. …”
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Demystifying the Use of Open-Access Data in Smart Heritage Implementations by Shiran Geng, Hing-Wah Chau, Elmira Jamei, Zora Vrcelj

“…This study employed a structured methodology that transitions from global best practices to local applications, linking these data resources to Smart Heritage applications and identifying opportunities for improving urban management, heritage curation, and the tourism experience within the case study precinct. …”
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Improving data processing in medical education through machine learning by N. Shyndaliyev, A. Orynbayeva, K. Shadinova, A. Barakova, N. Nurmukhanbetova

“…Statistical tests supported the hypothesis that structured ML education enhances medical students’ competencies, suggesting that future healthcare professionals trained in ML can better leverage data-driven decision-­making for improved patient care. …”
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