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Екосистемний підхід до відродження авіабудівної галузі України з орієнтацією на майбутнє

2023· article· uk· W6928693534 on OpenAlexaboutno aff

Bibliographic record

VenueElectronic Institutional Repository of the National Aviation University of Ukraine (National Aviation University, Ukraine) · 2023
Typearticle
Languageuk
FieldEngineering
TopicMilitary Technology and Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsIntellectualizationAviationAutomationSustainable developmentAerospaceObstacle

Abstract

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1. Харазішвілі Ю. М., Бугайко Д. О., Ляшенко В. І. (2022). Сталий розвиток авіаційного транспорту Укра- їни: стратегічні сценарії та інституційний супровід:монографія / НАН України, Ін-т економіки пром-сті. Київ, 2022. 276 с. 2. Про схвалення Концепції Державної цільової науково-технічної програми розвитку авіаційної промисловості на 2021-2030 роки: Розпорядження Кабінету Міністрів України від 11 листопада 2020 р. № 1412-р. URL: https://zakon.rada.gov.ua/laws/show/ 1412-2020-%D1%80#Text. 3. Про схвалення Національної транспортної стратегії України на період до 2030 року. Розпорядження Кабінету Міністрів України від 24 лютого 2016 р. № 126. URL:https://zakon.rada.gov.ua/laws/show/126-2016-%D0%BF#Text. 5. Bugayko, D. O., Shevchenko, O. R., Perederii, N. M., Sokolova, N. P., Bugayko, D. D. Risk management of Ukrainian aviation transport post-war recovery and sustainable development. Intellectualization of logistics and Supply Chain Management. 2022. Vol. 16. Р. 6-22. URL: https://smart-scm.org/en/journal-16-2022/riskmanagement-of-ukrainian-aviation-transport-post-war-recovery-and-sustainable-development/. DOI: https://doi.org/10.46783/smart-scm/2022-16-1. 6. Tsuzuki, R. Development of automation and artificial intelligence technology for welding and inspection process in aircraft industry.Welding in the World, Le Soudage Dans Le Monde. 2021. Vol. 66 (8). Р. 105—116. DOI: https://doi.org/10.1007/s40194-021-01210-3. 7. Todd, D., & Simpson, J. (2019). The world aircraft industry. Routledge. 8. Lin W., Lu J., Zhu J., Xu L. Research on the Sustainable Development and Dynamic Capabilities of China’s Aircraft Leasing Industry Based on System Dynamics Theory. Sustainability. 2022. Vol. 14(3). Р. 1-19. DOI: https://doi.org/10.3390/su14031806. 9. Rawahi, S. H. A., Jamaluddin, Z. B., & Bhuiyan, A. B. The conceptual framework for the resources management attributes and aircraft maintenance efficiency in the aviation industries in Оman. International Journal of Accounting & Finance Review. 2020. Vol. 5(3). Р. 31-40. DOI: https://doi.org/10.46281/ijafr.v5i3.808. 10. Ho, T. S. G., Tang, Y. M., Tsang, K. Y., Tang,V., & Chau, K. Y. A blockchain-based system to enhance aircraft parts traceability and trackability for inventory management. Expert Systems with Applications. 2021. Vol. 179. Article 115101. DOI: https://doi.org/10.1016/j.eswa.2021.115101. 11. Pitchaimuthu, S., Thakkar, J. J., & Gopal, P. R. C. Modelling of risk factors for defence aircraft industry using interpretive structural modelling, interpretive ranking process and system dynamics. Measuring Business Excellence. 2019. Vol. 23. No. 3. P. 217-239. DOI: https://doi.org/10.1108/MBE-05-2018-0028. 12. Milambo, D., & Phiri, J. Aircraft spares supply chain management for the aviation industry in Zambia based on the supply chain operations reference (SCOR) model. Open Journal of Business and Management. 2019. Vol. 7(3). Р. 1183-1195. DOI: https://doi.org/10.4236/ ojbm.2019.73083. 13. Gallego-Garcнa, S., Gejo-Garcнa, J., & Garcнa-Garcнa, M. Development of a maintenance and spare parts distribution model for increasing aircraft efficiency. Applied Sciences. 2021. Vol. 11(3), 1333. DOI: https://doi.org/10.3390/app11031333. 14. Yadav, D. K., Kulkarni, A., & Yao, H. A Comparative Study of Managing a Project Using Traditional Management Techniques and a Critical Chain Project Management Methodology in Aircraft Maintenance Field. Journal of Transportation Technologies. 2022. Vol. 12(4). Р. 544-558. DOI: https://doi.org/ 10.4236/jtts.2022. 124032. 15. IСAO Global Aviation Safety Plan for 2023-2025. URL: https://www.icao.int/safety/GASP/Pages/Home.aspx. 16. Convention on International Civil Aviation (Doc 7300), signed in Chicago on December 7, 1944. SMS Manual. Doc 9859. Quarterly edition. ICAO, Montreal, 2019. 17. Annex 19 to the Convention on the International Civil Aviation Organization. Safety Management. URL:https://www.easa.europa.eu/sites/default/files/dfu/ICAOannex-19.pdf. 18. Global Air Navigation Plan (Doc 9750) ICAO,Montreal. 19. Aviation Benefits Report 2019, ICAO (Report based on material of ACI, CANSO, IATA, ICAO, ICCAIA, ATAG). URL: https://pdf4pro.com/amp/ view/aviation-benefits-report-2019-icao-67311c.html. 20. The European Aviation Safety Programme, EASA, the Member States, the European Commission, the Performance Review Body and Eurocontrol 2011. 21. European Plan for Aviation Safety. 12th ed. EPAS 2023-2025, EASA, 2022. 22. EUROCONTROL Long-Term Forecast Flight Movements 2008-2030. 23. Boeing Commercial Market Outlook 2019—2038. 24. Airbus Global Market Forecast/ Cities, Airorts&Aircraft, 2019—2038. 25. Про національну безпеку України: Закон Ук- раїни від 21.06.2018 р. № 2469-VIII. Відомості Верховної Ради (ВВР). 2018. URL: https://zakon.rada.gov.ua/ laws/show/2469-19. 26. Гелена Саврук (2019). Бізнес-екосистеми. Логіка ведення бізнесу, що дозволила Amazon перемогти Sony. URL: https://biz.nv.ua/ukr/experts/biznes-korporaciy-i-lokalnih-kompaniy-yak-organizuvati-50027774.html. 27. Bugayko D. O., Ierkovska Y. M., Aliyev F. F., Bahrii M. M. (2021) The concept of national integrated risk management of aviation transport of Ukraine. Intellectualization of logistics and Supply Chain Management. vol. 10, pp. 6-18, URL: https://smart-scm.org/en/journal- 10-2021/the-concept-of-national-integrated-risk-management-of-aviation-transport-of-ukraine. DOI: https://doi.org/10.46783/smart-scm/2021-10-1. 28. ICAO. ICAO’S CO2 STANDARD FOR NEW AIRCRAFT, ICAO, 2017. 29. ICAO. Assembly – 39th Session Executive Committee. Agenda Item 22: Environmental Protection — International Aviation and Climate Change — Policy, Standardization and Implementation Support/ ICAO’S CO2 STANDARD FOR NEW AIRCRAFT (Presented by the International Coalition for Sustainable Aviation (ICSA). URL: https://www.transportenvironment.org/sites/te/ files/publications/wp_207_en%20ICSA%20CO2%20Standard.pdf. 30. ICAO. 2019 Environmental Report - Aviation and Environment, ICAO, 2019. 31. Bugayko D. O., Borysiuk A. V., Perederii N. M., Sokolova N. P., Bugayko D. D. (2022). Role of ICAO CO2 emissions standard for new aircraft in civil aviation sustainable development process. Intellectualization of logistics and Supply Chain Management, vol. 13, pp. 6-14. URL:https://smart-scm.org/en/journal-13-2022/role-of-icaoco2-emissions-standard-for-new-aircraft-in-civil-aviationsustainable-development-process/. DOI: https://doi.org/10.46783/smart-scm/2022-13-1.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.142
Threshold uncertainty score0.476

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0060.004
Scholarly communication0.0140.009
Open science0.0010.005
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.1420.110

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.194
Teacher spread0.184 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2023
Admission routes1
Has abstractyes

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