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  1. 301

    Accident Data-Driven Consequence Analysis in Maritime Industries by Jiahui Shi, Zhengjiang Liu

    Published 2025-01-01
    “…Thirdly, a TAN (Tree Augmented Network)-based BN (Bayesian network) model is developed. Fourthly, a model validation process, including a comparative analysis, Kappa test, and scenario analysis are performed. …”
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  2. 302

    Analysis of the Data Presented by Tide Gauge Stations in Albania by Bledar Sina, Gezim Hasko

    Published 2024-06-01
    “…The research involves the deployment and maintenance of tide gauges at strategic locations along the Albanian coastline, coupled with an in-depth analysis of the collected data. The monitoring process includes continuous data acquisition from tide gauges, incorporating advanced sensors and telemetry systems to ensure realtime and accurate measurements. …”
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  3. 303

    System of complex data analysis of thematic sites ISCAD IS by I. I. Piletski, M. P. Batura, N. A. Volоrоva, P. A. Zorko, A. O. Kulevich

    Published 2024-03-01
    “…A system for comprehensive analysis of data from thematic sites ISKAD IS has been developed, a methodology for quickly constructing a thematic graph database and a comprehensive technology for in-depth analysis of data from Internet sources and analysis of data from the most important well-known world sites have been tested.Conclusion. …”
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  4. 304
  5. 305

    The swarm intelligence algorithms and their application for the educational data analysis by Y. Yu. Dyulicheva

    Published 2019-11-01
    “…According to the results of the study, we can conclude about the effectiveness of swarm intelligence algorithms usage to solve a wide range of tasks connected with learning content and students’ data analysis in the e-learning systems and perspectives to hybrid approaches development based on swarm intelligence algorithms for realizing the adaptive learning systems on the paradigm of “demand learning".The results can be used to automate the organization of learning content during project seminars for the first-year students, when it is important to understand the basic level of knowledge and students’ interest in learning new technologies.…”
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  6. 306
  7. 307

    Modeling of Distorted Degradation Data Based on Oil Analysis by Yue Chen, Jian Shi

    Published 2025-06-01
    “…Notably, though our methodology was initially developed for wear degradation analysis, this data-driven framework demonstrates adaptability to broader degradation scenarios. …”
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  8. 308

    Biomedical Data Analysis Systems for the Diagnosis of Skin Neoplasms by O. O. Myakinin

    Published 2020-07-01
    “…Recent advances in the study of non-invasive diagnostic tools makes this area very promising for research in a clinical condition. Aim. Developing of software modules based on the mathematical framework of texture analysis for biomedical data systems designed for the diagnosis of skin malignant neoplasms. …”
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  9. 309

    APPLICATION OF DATA ANALYSIS METHODS FOR AUTOMATION OF ONTOLOGY FORMATION by O. N. Yurkova

    Published 2018-06-01
    “…The aim of this work is to develop methods for automated text analysis and the retrieval of relevant data from full-text documents, as well as applying semantic text analysis methods for using linguistic ontologies as formalised models of subject area representation. …”
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  10. 310

    Leveraging large language models for data analysis automation. by Jacqueline A Jansen, Artür Manukyan, Nour Al Khoury, Altuna Akalin

    Published 2025-01-01
    “…Data analysis is constrained by a shortage of skilled experts, particularly in biology, where detailed data analysis and subsequent interpretation is vital for understanding complex biological processes and developing new treatments and diagnostics. …”
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    Article
  11. 311

    Intellectual Data Analysis as a Component of Education Management by I. I. Ovsyanitskaya

    Published 2015-03-01
    “…The author recommends the ways for developing the patterns underlying the Data mining methods. …”
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  12. 312

    Correcting for Signal Saturation Errors in the Analysis of Microarray Data by L.-L. Hsiao, R.V. Jensen, T. Yoshida, K.E. Clark, J.E. Blumenstock, S.R. Gullans

    Published 2002-02-01
    “…A variety of technical errors have arisen in data analysis when using cDNA or oligonucleotide microarrays. …”
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  13. 313

    Modern Bioinformatics Solutions Used for Genetic Data Analysis by Ya. A. Kibirev, A. V. Kuznetsovskiy, S. G. Isupov, I. V. Darmov

    Published 2024-04-01
    “…For each stage bioinformation utilities have been developed, differing  in implemented analysis algorithms. …”
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  14. 314
  15. 315

    Analysis of Software Read Cross-Contamination in DNBSEQ Data by Dmitry N. Konanov, Vera Y. Tereshchuk, Ignat V. Sonets, Elena V. Korneenko, Aleksandra V. Lukina-Gronskaya, Anna S. Speranskaya, Elena N. Ilina

    Published 2025-06-01
    “…Given their unprecedentedly high data yield per flow cell, the new PE300 kits could be a great choice for various sequencing tasks, but we found that combining different types of DNA libraries in a single run could lead to undesired artifacts in the data. …”
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  17. 317

    Developing PM₂.₅ mitigation solutions based on the analysis of the relationships between PM₂.₅ concentrations and precursor factors: a case study of Hanoi, Vietnam by Long Ta Bui, Binh Quoc Pham, Tho Thi Be Cao

    Published 2025-06-01
    “…To achieve this goal, a new approach has been developed based on the combination of modeling and big data technology, clarifying the relationship between the spatial–temporal distribution of PM2.5 pollution and the emission sources of its precursors. …”
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    Bioinformatic challenges for pharmacogenomic study: tools for genomic data analysis by Mariamena Arbitrio, Marianna Milano, Maria Lucibello, Emanuela Altomare, Nicoletta Staropoli, Nicoletta Staropoli, Pierfrancesco Tassone, Pierfrancesco Tassone, Pierosandro Tagliaferri, Pierosandro Tagliaferri, Mario Cannataro, Giuseppe Agapito

    Published 2025-04-01
    “…In this review, starting from our experience in PGx studies performed by DMET microarray platform, we propose a guideline combining machine learning, statistical, and network-based approaches to simplify and better understand complex DMET PGx data analysis which can be adapted for broader PGx applications, fostering accessibility to high-performance bioinformatics, also for non-specialists. …”
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