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(2025): Invulnerability Bias in Perceptions of Artificial Intelligence’s Future Impact on Employment. Scientific Reports, 15(1), 28698. Online: https://doi.org/10.1038/s41598-025-14698-2 BASCH, Corey et al. (2025): Artificial Intelligence in Higher Education: Student Knowledge, Attitudes, and Ethical Perceptions in the United States. SDGs Studies Review, 6, e034. Online: https://doi.org/10.37497/sdgs.v6istudies.34 BAVADHARANI, K. – ROSHAN, K. – KALAIVANI, N. (2025): Artificial Intelligence Awareness and its Influence on Career Decision-Making Among University Students. ASET Journal Management Science, 4(2), 325–333. Online: https://doi.org/10.47059/ajms/v4i2/33 BEWERSDORFF, Arne et al. (2025): AI Advocates and Cautious Critics: How AI Attitudes, AI Interest, Use of AI, and AI Literacy Build University Students’ AI Self-Efficacy. Computers and Education: Artifical Intelligence, 8, 100340. Online: https://doi.org/10.1016/j.caeai.2024.100340 BORWEIN, Sophie et al. (2026): Explaining Women’s Skepticism Toward Artificial Intelligence: The Role of Risk Orientation and Risk Exposure. PNAS Nexus, 5(1), pgaf399. Online: https://doi.org/10.1093/pnasnexus/pgaf399 BRAUNER, Philipp et al. (2023): What Does the Public Think About Artificial Intelligence? –A Criticality Map to Understand Bias in the Public Perception of AI. Frontiers in Computer Science, 5. Online: https://doi.org/10.3389/fcomp.2023.1113903 CACHERO, Cristina – TOMÁS, David – PUJOL, Francisco A. (2025): Gender Bias in Self-Perception of AI Knowledge, Impact, and Support among Higher Education Students: An Observational Study. ACM Transactions on Computing Education, 25(2), 1–26. Online: https://doi.org/10.1145/3721295 CHOUDHARY, Satyanarayan – NIROULA, Arjun Kumar – PANT, Ganesh Datt (2025): Beyond Discipline: Quantifying the Impact of Prior AI Experience and Digital Literacy on Student Acceptance of Educational AI. Nepal Journal Multidisciplinary Research, 8(2), 186–195. Online: https://doi.org/10.3126/njmr.v8i2.78027 DE LOYOLA, Rhyan et al. (2024): Sentiment Analysis of AI’s Impact on Labor Market: Opportunities and Threats. Philippine Journal of Science Engineering Technology, 1(1), 48–54. DOLENC, Kosta – BRUMEN, Mihaela (2024): Exploring Social and Computer Science Students’ Perceptions of AI Integration in (Foreign) Language Instruction. Computers and Education: Artifical Intelligence, 7, 100285. Online: https://doi.org/10.1016/j.caeai.2024.100285 DOROTIC, Matilda – STAGNO, Emanuela – WARLOP, Luk (2023): AI on The Street: Context-Dependent Responses to Artificial Intelligence. International Journal of Research in Marketing, 41(1), 113–137. Online: https://doi.org/10.1016/j.ijresmar.2023.08.010 GHERHEȘ, Vasile – OBRAD, Ciprian (2018): Technical and Humanities Students’ Perspectives on the Development and Sustainability of Artificial Intelligence (AI). Sustainability, 10(9), 3066. Online: https://doi.org/10.3390/su10093066 GHOTBI, N. – HO, Manh-Tung (2021): Moral Awareness of College Students Regarding Artificial Intelligence. Asian Bioethics Review, 13, 421–433. Online: https://doi.org/10.1007/s41649-021-00182-2 HRUŠKA, Adam – ROUBÍK, Hynek (2025): Fear of the Future in the Context of the Emergence of Generative Artificial Intelligence Among Young Adults: The Case of Czechia. Advances in Distributed Computing and Artifical Intelligence Journal, 14, e32644. Online: https://doi.org/10.14201/adcaij.32644 IVANOVA, A. E. – TARASOVA, K. V. – TALOV, D. P. (2025): Between Interest and Skill: How Students Perceive and Use AI (Между интересом и умением: как студенты воспринимают и применяют ИИ). Vysshee Obrazovanie V Rossii Higher Education in Russia, 34(8–9), 9–32, Online: https://doi.org/10.31992/0869-3617-2025-34-8-9-9-32 LI, Yifu – CASTULO, Nilo Jayoma – XU, Xiaoyuan (2025): Embracing or Rejecting AI? A Mixed-Method Study on Undergraduate Students’ Perceptions of Artificial Intelligence at a Private University in China. Frontiers in Education, 10. Online: https://doi.org/10.3389/feduc.2025.1505856 LIANG, Yanlong – ZHAI, Yun (2025): The Impact of Artificial Intelligence Impact Awareness on College Students’ Employment Risk Perception: A Moderated Mediation Model. Acta Psychologica, 261, 105808. Online: https://doi.org/10.1016/j.actpsy.2025.105808 LIU, Xuan – CHEN, Yuci (2025): The Impact of Artificial Intelligence Usage on Employee Career Commitment: The Moderating Role of Artificial Intelligence Awareness. American Journal of Applied Psychology, 14(3), 101–112. Online: https://doi.org/10.11648/j.ajap.20251403.14 LÜNICH, Marco – KELLER, Birte – MARCINKOWSKI, Frank (2024): Diverging Perceptions of Artificial Intelligence in Higher Education: A Comparison of Student and Public Assessments on Risks and Damages of Academic Performance Prediction in Germany. Computers and Education: Artifical Intelligence, 7, 100305. Online: https://doi.org/10.1016/j.caeai.2024.100305 MØGELVANG, Anja – GRASSINI, Simone (2025): Validating the AI Attitude Scale (AIAS-4) and Exploring Attitudinal Differences in a Large Sample of Norwegian University Students. Discover Education, 4, 212. Online: https://doi.org/10.1007/s44217-025-00657-6 MOON, Su-Ji (2024): Effects of Perception of Potential Risk in Generative AI on Attitudes and Intention to Use. International Journal on Advanced Science Engineering Information Technology, 14(5), 1748–1755. Online: https://doi.org/10.18517/ijaseit.14.5.20445 MUSYAFFI, Ayatulloh Michael et al. (2024): Improving Students’ Openness to Artificial Intelligence Through Risk Awareness and Digital Literacy: Evidence Form a Developing Country. Social Sciences Humanities Open, 10, 101168. Online: https://doi.org/10.1016/j.ssaho.2024.101168 NKEDISHU, Victor Chukwubueze – OKONTA, Vinella (2024): Unpacking Optimism versus Concern: Tertiary Students’ Multidimensional Views on the Rise of Artificial Intelligence (AI). Int. Res. J. Multidiscip. Scope, 5(4), 362–377. Online: https://doi.org/10.47857/irjms.2024.05i04.01261 OTERMANS, Pauldy C. J. – ROBERTS, Charlotte – BAINES, Stephanie (2025): Unveiling AI Perceptions: How Student Attitudes Towards AI Shape AI Awareness, Usage, and Conceptions. International Journal of Technology in Education, 8(1), 88–103. Online: https://doi.org/10.46328/ijte.995 PARK, Yong Jin et al. (2022): Digital Assistants: Inequalities and Social Context of Access, Use, and Perceptual Understanding. Poetics, 93, 101689. Online: https://doi.org/10.1016/j.poetic.2022.101689 PONCE ROJO, Antonio et al. (2025): From Digital Natives to AI Natives: Emerging Competencies and Media and Information Literacy in Higher Education. Education Sciences, 15(9), 1134. Online: https://doi.org/10.3390/educsci15091134 SAID, Nadia et al. (2023): An Artificial Intelligence Perspective: How Knowledge and Confidence Shape Risk and Benefit Perception. Computers in Human Behavior, 149, 107855. Online: https://doi.org/10.1016/j.chb.2023.107855 SANTOS-JAÉN, José Manuel et al. (2025): University Students’ Perceptions of the Impact of Artificial Intelligence in the Business Sector on Their Educational and Professional Development. Education and Information Technologies, 30(17), 24395–24428. Online: https://doi.org/10.1007/s10639-025-13712-4 STÖHR, Christian – OU, Amy Wanyu – MALMSTRÖM, Hans (2024): Perceptions and Usage of AI Chatbots Among Students in Higher Education Across Genders, Academic Levels and Fields of Study. Computers and Education: Artifical Intelligence, 7, 100259. Online: https://doi.org/10.1016/j.caeai.2024.100259 SUMARYANTO, Sumaryanto – RICADONNA, Nadia Adriane – SUSANTI, Nani Irma (2026): How Perceived Risk Shapes User Satisfaction and Continuance Intention Toward AI-Based Applications in Higher Education ? International Journal of Business, Law, and Education, 7(1), 55–66. Online: https://doi.org/10.56442/ijble.v7i1.1333 TEIXEIRA, Sónia et al. (2022): An Exploratory Diagnosis of Artificial Intelligence Risks for a Responsible Governance. Proceedings of the 15th International Conference on Theory and Practice of Electronic Governance, ACM, 25–31. Online: http://dx.doi.org/10.1145/3560107.3560298 VÁZQUEZ-PARRA, José Carlos et al. (2024): Importance of University Students’ Perception of Adoption and Training in Artificial Intelligence Tools. Societies, 14(8), 141. Online: https://doi.org/10.3390/soc14080141 VOLYNETS, Viktoriia – TRACH, Yuliia (2025): Ethical Awareness of Youth about Artificial Intelligence: Education, Risks, Regulation (Етична обізнаність молоді щодо штучного інтелекту: освіта, ризики, регулювання). Digital Platform Information Technologies in Sociocultural Sphere, 8(2), 289–298. Online: https://doi.org/10.31866/2617-796x.8.2.2025.347871 WANG, Chengliang et al. (2024): Factors Influencing University Students’ Behavioral Intention to Use Generative Artificial Intelligence: Integrating the Theory of Planned Behavior and AI Literacy. International Journal of Human–Computer Interaction, 41(11), 6649–6671. Online: https://doi.org/10.1080/10447318.2024.2383033 YAROVENKO, Hanna et al. (2024): The Future of Artificial Intelligence: Fear, Hope or Indifference? Human Technology, 20(3), 611–639. Online: https://doi.org/10.14254/1795-6889.2024.20-3.10 ZHANG, Xiaoxuan et al. (2025): Integrating AI Literacy with the TPB-TAM Framework to Explore Chinese University Students’ Adoption of Generative AI. Behavioral Science, 15(10), 1398. Online: https://doi.org/10.3390/bs15101398" ["copyrightYear"]=> int(2026) ["issueId"]=> int(696) ["licenseUrl"]=> string(49) "https://creativecommons.org/licenses/by-nc-nd/4.0" ["pages"]=> string(4) "5-25" ["pub-id::doi"]=> string(20) "10.32567/hm.2026.2.1" ["abstract"]=> array(2) { ["en_US"]=> string(1882) "

This study constitutes the second part of a two-part research series. The first part provided a theoretical framework and a comprehensive literature review, while the present paper analyzes the results of a questionnaire survey conducted among 1,027 students enrolled in humanities, social sciences, and teacher education programs. The aim of the study was to explore how students evaluate the future role of artificial intelligence in everyday life and in the labor market, which risks they identify, and how important they consider AI-related competencies for their future careers. The majority of respondents anticipate substantial societal impact; however, perceptions of career-related effects are differentiated. While 42.5% do not expect AI to significantly influence their career paths, 30.4% foresee positive and 27.2% negative consequences. Overall, 70.3% regard knowledge of AI technologies as important or indispensable for their future careers. Risk perception is particularly high in relation to visual manipulation, misinformation, data security, and privacy protection. Female students and part-time students report higher levels of perceived risk across several dimensions. Regular AI users are more likely to expect positive career effects (39.5%) compared to non-users (26.2%), whereas neutral evaluations are more prevalent among non-users (47.1%). Among those who completely reject AI use, 64.8% do not consider AI-related knowledge important for their careers. The findings suggest that career perceptions related to AI are shaped by the combined influence of usage experience, risk perception, and demographic characteristics. The high proportion of non-users (68.1%) indicates that AI integration in higher education remains limited, highlighting the need for targeted competence development, particularly in humanities and teacher education programs.

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A tanulmány egy kétrészes cikksorozat második része. Az első rész elméleti keretet és átfogó szakirodalmi áttekintést adott, míg a jelen írás 1027 bölcsészettudományi, társadalomtudományi és pedagógiai képzésben részt vevő hallgató kérdőíves vizsgálatának eredményeit elemzi. A kutatás célja annak feltárása volt, hogy a hallgatók miként értékelik a mesterséges intelligencia jövőbeli szerepét a mindennapi életben és a munkaerőpiacon, milyen kockázatokat azonosítanak, valamint milyen jelentőséget tulajdonítanak az MI-kompetenciáknak saját karrierjük szempontjából. A válaszadók többsége számottevő társadalmi hatással számol, ugyanakkor a karrierre gyakorolt hatás megítélése differenciált. A hallgatók 42,5%-a nem vár érdemi befolyást pályájára, 30,4% pozitív, 27,2% negatív következményekkel számol. Az MI-technológiák ismeretét 70,3% fontosnak vagy elengedhetetlennek tartja. A kockázatészlelés különösen erős a vizuális manipuláció, az álhírek terjesztése, az adatvédelem és a magánélet védelme esetében, a nők és a levelező tagozatos hallgatók több dimenzióban magasabb kockázati értékeket adtak. A rendszeres MI-használók nagyobb arányban várnak pozitív karrierhatást (39,5%), mint a nem használók (26,2%), miközben a nem használók körében gyakoribb a semleges álláspont (47,1%). Az MI-használattól teljesen elzárkózók 64,8%-a nem tartja fontosnak az MI-eszközök ismeretét. Az eredmények alapján a karrierpercepció a használati tapasztalat, a kockázatészlelés és a demográfiai jellemzők együttes hatásaként értelmezhető. A 68,1%-os nem használói arány arra utal, hogy az MI felsőoktatási integrációja korlátozott, ami célzott kompetenciafejlesztést indokol, különösen a humán és pedagógiai képzési területeken.

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Hadmérnök, 19(3), 183–200. Online: https://doi.org/10.32567/hm.2024.3.11 KOVÁCS László (2018): A kibertér védelme. Budapest: Dialóg Campus. Online: https://www.uni-nke.hu/document/uni-nke-hu/Kov%C3%A1cs%20L%C3%A1szl%C3%B3.pdf KRASZNAY Csaba (2022): Kiberbiztonság a XXI. században. Budapest: Katonai Nemzetbiztonsági Szolgálat. MIRON, Marina – THORNTON, Rod (2024): The Use of Cyber Tools by the Russian Military: Lessons from the War against Ukraine and a Warning for NATO? Applied Cybersecurity & Internet Governance, 3(1), 147–169. Online: https://doi.org/10.60097/ACIG/190142 MOYNIHAN, Harriet – WEBB, Philippa – CLOONEY, AMAL (2025): Legal Accountability for Malicious Cyber Operations. Oxford Institute of Technology and Justice. Online: https://doi.org/10.35489/BSG-OITJ-PB-1_2025-01 MUHA Lajos (2007): A Magyar Köztársaság kritikus információs infrastruktúráinak védelme. PhD-disszertáció. Budapest: Zrínyi Miklós Nemzetvédelmi Egyetem. Online: https://real-phd.mtak.hu/74/1/1228916.pdf ORBÓK Ákos (2013): A kibertér, mint hadszíntér. Biztonságpolitika, 2013, 101–108. Online: https://old.biztonsagpolitika.hu/documents/1375084295_Orbok_Akos_A_kiberter_mint_hadszinter_-_biztonsagpolitika.hu.pdf Protocol Additional to the Geneva Conventions of 12 August 1949, and Relating to the Protection of Victims of International Armed Conflicts (Protocol I), 8 June 1977 (1977). Online: https://ihl-databases.icrc.org/en/ihl-treaties/api-1977 Reuters (2022): Satellite Outage Knocks out Thousands Of Enercon’s Wind Turbines. Reuters, 2022. február 28. Online: https://www.reuters.com/business/energy/satellite-outage-knocks-out-control-enercon-wind-turbines-2022-02-28/ RID, Thomas (2013): Cyber War Will Not Take Place. Oxford: Oxford University Press. ROULETTE, Joey – BRYAN-LOW, Cassell – BALMFORTH, Tom (2025): Musk Ordered Shutdown of Starlink Satellite Service as Ukraine Retook Territory from Russia. Reuters, 2025. július 25. Online: https://www.reuters.com/investigations/musk-ordered-shutdown-starlink-satellite-service-ukraine-retook-territory-russia-2025-07-25/ SCHMITT, Michael N. – NATO Cooperative Cyber Defence Centre of Excellence szerk. (2017): Tallinn Manual 2.0 on the International Law Applicable to Cyber Operations. Cambridge–New York: Cambridge University Press. SMITH, Brad (2022): Digital Technology and the War in Ukraine. Microsoft on the Issues. Online: https://blogs.microsoft.com/on-the-issues/2022/02/28/ukraine-russia-digital-war-cyberattacks/ SOESANTO, S. (2022): The IT Army of Ukraine: Structure, Tasking, and Eco-System. Zürich: Center for Security Studies (CSS). Online: https://doi.org/10.3929/ethz-b-000552293 VERBRUGGEN, Yola (2023): Cybercrimes under Consideration by the ICC. International Bar Association, 2023. október 13. Online: https://www.ibanet.org/cybercrimes-under-consideration-by-the-ICC Про хмарні послуги [é. n.]. 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In 21st-century armed conflicts, cyberspace has become a dominant theater of war, where kinetic strikes and cyber operations support one another in close symbiosis and in real time. Building on the lessons learned from the Russia – Ukraine war, this study analyzes the technological and functional interdependence of military and civilian critical infrastructure. The author points out that during attacks on dual-use systems – particularly energy supply and telecommunications – the line between military and civilian targets becomes blurred, leading to serious social consequences and international ripple effects. Through specific case studies (Viasat, Kyivstar, and attacks on energy grids), the article examines the practice of hybrid warfare, demonstrating that the disruption of civilian systems has become an integral part of modern military operations. The analysis devotes particular attention to the paradigm shift in defense: it illustrates how global private technology companies and civil society have become key players in Ukraine’s digital defense. The study concludes that future national resilience can no longer be guaranteed solely through a state monopoly; rather, effective defense requires integrated, trust-based cooperation among the civil sector, the private sector, and defense agencies.

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A 21. századi fegyveres konfliktusokban a kibertér domináns hadszíntérré vált, ahol a kinetikus csapások és a kiberműveletek szoros szimbiózisban, valós időben támogatják egymást. Jelen tanulmány az orosz–ukrán háború tapasztalataira építve elemzi a katonai és a polgári kritikus infrastruktúrák technológiai és funkcionális összefonódását. A szerző rámutat, hogy a kettős felhasználású rendszerek – különösen az energiaellátás és a távközlés – elleni támadások során elmosódik a határ a katonai és civil célpontok között, ami súlyos társadalmi következményekkel és nemzetközi tovagyűrűző hatásokkal jár. A cikk konkrét esettanulmányokon keresztül (Viasat, Kyivstar, energetikai hálózatok elleni támadások) vizsgálja a hibrid hadviselés gyakorlatát, bizonyítva, hogy a civil rendszerek megbénítása a modern hadműveletek szerves részévé vált. Az elemzés kiemelt figyelmet szentel a védekezés paradigmaváltásának: bemutatja, hogyan váltak a globális technológiai magánvállalatok és a civil társadalom Ukrajna digitális védelmének kulcsszereplőivé. A tanulmány konklúziója szerint a jövőbeni nemzeti ellenálló képesség már nem garantálható kizárólag állami monopóliumként, a hatékony védelem alapfeltétele a civil szféra, a magánszektor és a védelmi szervek integrált, bizalmi alapú együttműködése.

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Multispectral and hyperspectral imaging offer complementary capabilities for remote reconnaissance by sampling reflected energy in several optical wavelength bands. This study evaluates their suitability for operational area monitoring, with an emphasis on lightweight, drone‑borne sensors. A theoretical overview explains how spectral signatures arise from electronic transitions and molecular vibrations, leading to characteristic vegetation and soil reflectance patterns. Common vegetation and moisture indices are introduced, noting their sensitivity to chlorophyll content, water absorption and the limitations of MSI sensors lacking short‑wave infrared bands. Remote‑sensing platforms including handheld spectrometres, satellites and unmanned aerial vehicles are compared. UAVs equipped with multispectral cameras offer a favourable balance of spatial resolution, cost and ease of deployment. The DJI Mavic 3 Multispectral is selected for field experimentation due to its integrated four‑band sensor (green, red, red‑edge, near‑infrared), sunlight sensor and RTK positioning. Other MSI cameras (MicaSense RedEdge‑MX, Parrot Sequoia+) and representative hyperspectral cameras are briefly reviewed, highlighting tradeoffs in weight, spectral resolution and cost. A case study over a military training ground uses the M3M to acquire two flights – before and after a rain event – and processes the images using WebODM, QGIS and MATLAB. Vegetation indices map plant vigour and relative soil moisture, and change detection highlights vehicle tracks and wet areas. Results demonstrate that NDRE remains linear at high biomass and that simple red-edge metrics sensitively capture moisture changes despite the absence of SWIR. While the Mavic 3M lacks a blue and SWIR band limits the calculation of some water related indices, its portability and affordability make it a valuable tool for rapid reconnaissance. The paper concludes by discussing future directions, including the integration of machine learning and additional sensors to enhance material identification and real‑time processing. The index-based analysis is explicitly interpreted as relative operational change detection rather than absolute biomass, reflectance or soil-moisture retrieval, because independent ground-reference measurements were not available during the field campaign.

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Vojenské Reflexie, 18(3), 59–73. Online: https://doi.org/10.52651/vr.a.2023.3.59-73 WINDLEY, Phillip (2005): Digital Identity. O’Reilly. Online: https://dl.acm.org/doi/abs/10.5555/1098715 YAMIN, Muhammad – KATT, Basel (2019): Mobile Device Management (MDM): Technologies, Issues, and Challenges. ICCSP ’19: Proceedings of the 3rd International Conference on Cryptography, Security and Privacy. New York: Association for Computing Machinery, 143–147. Online: https://doi.org/10.1145/3309074.3309103 " ["copyrightYear"]=> int(2026) ["issueId"]=> int(696) ["licenseUrl"]=> string(49) "https://creativecommons.org/licenses/by-nc-nd/4.0" ["pages"]=> string(5) "61-74" ["pub-id::doi"]=> string(20) "10.32567/hm.2026.2.4" ["abstract"]=> array(1) { ["en_US"]=> string(1509) "

Mobile Device Management (MDM) platforms have evolved into critical components of enterprise security architectures, influencing device governance, access control and policy enforcement across corporate networks. As these systems increasingly operate as centralised control planes, they have become attractive targets for adversaries seeking scalable organisational compromise. The study develops a comprehensive analytical framework that integrates public Ivanti security incident data with vulnerability assessment documents and current MDM system design materials. Through qualitative incident analysis and architectural interpretation, the research identifies three primary factors that amplify the systemic impact of MDM compromise: excessive privilege concentration, identity adjacency and update trust dependencies. The findings demonstrate that the security significance of MDM systems extends beyond conventional endpoint management, as these platforms increasingly influence authentication processes, trust relationships and enterprise-wide security decisions. The study argues that MDM platforms should be governed as high-value control-plane assets requiring architectural risk management rather than solely operational security maintenance. The results contribute to the broader understanding of centralised management infrastructures and highlight the need for stronger segmentation, authentication controls, and trust-boundary protection mechanisms within modern enterprise environments.

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Environmental Science and Pollution Research, 23(2), 974–984. Online: https://doi.org/10.1007/s11356-015-4233-0 YASHCHENKO, Liudmyla – Androshchuk, Oleksandr – VASYLENKO, Liudmyla – CHORNOIVAN, Yuliya (2025): Environmental Risks of Heavy Metal Pollution in War-Affected Soils in Ukraine. European Journal of Environmental Sciences, 15(1), 18–27. Online: https://doi.org/10.14712/23361964.2025.3" ["copyrightYear"]=> int(2026) ["issueId"]=> int(696) ["licenseUrl"]=> string(49) "https://creativecommons.org/licenses/by-nc-nd/4.0" ["pages"]=> string(5) "75-85" ["pub-id::doi"]=> string(20) "10.32567/hm.2026.2.5" ["abstract"]=> array(1) { ["en_US"]=> string(933) "

It is well known that during armed conflicts, as well as military trainings, large amounts of pollutants can be released into nature. Of the eleven environmentally toxic elements, Pb, Zn and Cu are often present in high concentrations in the soils of military sites, along with Cd and As. According to newer data from the Russo–Ukrainian War, the inorganic contaminants (mostly toxic elements) show a concentrical distribution in the affected areas, caused by artillery activity; however, the spatial distribution of Pb in the training sites is more dispersed.

Risk assessment, then physicochemical and bioremediation methods can be used for cleaning up the polluted areas from the contaminants after the closure of the armed conflicts or training; however, the complexity, caused by the contaminant mixtures and the great variability of soil components, of the pollution affects the success of the procedure heavily.

" } ["subtitle"]=> array(1) { ["en_US"]=> string(19) "A Scientific Review" } ["title"]=> array(1) { ["en_US"]=> string(46) "Military-related Heavy Metal Pollution in Soil" } ["copyrightHolder"]=> array(1) { ["hu_HU"]=> string(14) "Stadler Tamás" } ["locale"]=> string(5) "en_US" ["authors"]=> array(1) { [0]=> object(Author)#739 (6) { ["_data"]=> array(15) { ["id"]=> int(11754) ["email"]=> string(20) "tstadler93@gmail.com" ["includeInBrowse"]=> bool(true) ["publicationId"]=> int(9052) ["seq"]=> int(1) ["userGroupId"]=> int(184) ["country"]=> string(2) "HU" ["orcid"]=> string(37) "https://orcid.org/0009-0003-8564-594X" ["url"]=> string(0) "" ["affiliation"]=> array(2) { ["en_US"]=> string(0) "" ["hu_HU"]=> string(57) "a:1:{s:5:"hu_HU";s:31:"Nemzeti Közszolgálati Egyetem";}" } ["biography"]=> array(2) { ["en_US"]=> string(0) "" ["hu_HU"]=> string(0) "" } ["familyName"]=> array(2) { ["en_US"]=> string(7) "Stadler" ["hu_HU"]=> string(7) "Stadler" } ["givenName"]=> array(2) { ["en_US"]=> string(6) "Tamás" ["hu_HU"]=> string(6) "Tamás" } ["preferredPublicName"]=> array(2) { ["en_US"]=> string(0) "" ["hu_HU"]=> string(0) "" } ["submissionLocale"]=> string(5) "en_US" } ["_hasLoadableAdapters"]=> bool(false) ["_metadataExtractionAdapters"]=> array(0) { } ["_extractionAdaptersLoaded"]=> bool(false) ["_metadataInjectionAdapters"]=> array(0) { } ["_injectionAdaptersLoaded"]=> bool(false) } } ["keywords"]=> array(1) { ["en_US"]=> array(5) { [0]=> string(18) "soil contamination" [1]=> string(8) "military" [2]=> string(12) "geochemistry" [3]=> string(8) "ordnance" [4]=> string(11) "remediation" } } ["subjects"]=> array(0) { } ["disciplines"]=> array(0) { } ["languages"]=> array(0) { } ["supportingAgencies"]=> array(0) { } ["galleys"]=> array(1) { [0]=> object(ArticleGalley)#752 (7) { ["_data"]=> array(9) { ["submissionFileId"]=> int(48683) ["id"]=> int(6979) ["isApproved"]=> bool(false) ["locale"]=> string(5) "en_US" ["label"]=> string(3) "PDF" ["publicationId"]=> int(9052) ["seq"]=> int(0) ["urlPath"]=> string(0) "" ["urlRemote"]=> string(0) "" } ["_hasLoadableAdapters"]=> bool(true) ["_metadataExtractionAdapters"]=> array(0) { } ["_extractionAdaptersLoaded"]=> bool(false) ["_metadataInjectionAdapters"]=> array(0) { } ["_injectionAdaptersLoaded"]=> bool(false) ["_submissionFile"]=> NULL } } } ["_hasLoadableAdapters"]=> bool(false) ["_metadataExtractionAdapters"]=> array(0) { } ["_extractionAdaptersLoaded"]=> bool(false) ["_metadataInjectionAdapters"]=> array(0) { } ["_injectionAdaptersLoaded"]=> bool(false) }

object(Publication)#121 (6) { ["_data"]=> array(29) { ["id"]=> int(9074) ["accessStatus"]=> int(0) ["datePublished"]=> string(10) "2026-09-28" ["lastModified"]=> string(19) "2026-09-28 13:44:56" ["primaryContactId"]=> int(11788) ["sectionId"]=> int(54) ["seq"]=> int(1) ["submissionId"]=> int(8949) ["status"]=> int(3) ["version"]=> int(1) ["categoryIds"]=> array(0) { } ["citationsRaw"]=> string(1905) "- 2024. évi LXXXIV. törvény a kritikus infrastruktúrák ellenálló képességéről. BALOGH Zsuzsanna (2010): Üveg az építészetben, a terrorista robbantások tükrében. Műszaki Katonai Közlöny, 20(1–4), 257–271. EN 13541. Security Glazing – Testing and Classification of Resistance Against Explosion Pressure (2012). FÖLDES Tibor (2025): A biztonság szerepe és fontossága a szövetségesi kritikus infrastruktúra szabályozásának kialakításában. Katonai Nemzetbiztonsági Szolgálat Szakmai Szemle, 1, 146–163. Online: https://ojs.knbsz.gov.hu/index.php/szakmai/article/view/234/130 Joint Forward Operating Base Force Protection Handbook (2005). KOVÁCS Zoltán (2012): Repülőterek védelme improvizált robbanóeszközök (IED) ellen. Repüléstudományi Közlemények, 24(2), 70–79. Online: https://www.repulestudomany.hu/kulonszamok/2012_cikkek/05_Kovacs_Zoltan.pdf KOVÁCS Zoltán (2013): Repülőterek robbantások elleni védelmének technikai lehetőségei. Repüléstudományi Közlemények, 25(2), 78–88. Online: https://www.repulestudomany.hu/kulonszamok/2013_cikkek/2013-2-06-Kovacs_Zoltan.pdf KOVÁCS Zoltán (2014): Repülőtéri létesítmények fizikai védelme IED ellen. Repüléstudományi Közlemények, 26(2), 106–113. Online: https://folyoirat.ludovika.hu/index.php/reptudkoz/article/view/4602/3759 NATO Standardization Office (2024): AJP-3.14. Allied Joint Doctrine for Force Protection. Reference Manual to Mitigate Potential Terrorist Attacks Against Buildings (FEMA 426) (2011). U.S. Army (2009): FM 3-37 Protection. U.S. Army (2018): ADP 3-37 Protection. UFC 4-010-01. DoD Minimum Antiterrorism Standards for Buildings (2024). Whole Building Design Guide. Online: https://www.wbdg.org/dod/ufc/ufc-4-010-01 UFC 4-010-02. DoD Minimum Antiterrorism Standoff Distances for Buildings (2020). Online: https://www.wbdg.org/dod/ufc/ufc-4-010-02" ["copyrightYear"]=> int(2026) ["issueId"]=> int(696) ["licenseUrl"]=> string(49) "https://creativecommons.org/licenses/by-nc-nd/4.0" ["pages"]=> string(6) "87-101" ["pub-id::doi"]=> string(20) "10.32567/hm.2026.2.6" ["abstract"]=> array(2) { ["en_US"]=> string(1424) "

The physical protection of critical infrastructures is a complex, multivariable system‑design challenge in which the physical, informational, and human subsystems do not operate in isolation, but continuously influence one another’s functioning and jointly determine the overall performance of the system. This complexity is particularly evident in military facilities, where operational experience consistently indicates high threat intensity and considerable diversity, factors that directly shape planning and operational decision‑making.

The study analyses the physical protection of military critical infrastructures through system‑level interdependencies, with particular emphasis on multilayered defence architectures, the applicability of modern engineering solutions, and the practical effects of the regulatory environment. The analysis builds on international doctrines, engineering guidelines, and national–European standards that have proven in practice to provide a stable and comparable framework for the design and evaluation of physical protection systems. The findings highlight that the effectiveness of physical protection is fundamentally determined by the quality of information flow between subsystems, the system’s ability to delay hostile actions, and the integration of the response chain—factors that collectively shape the operational performance of the entire system.

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A kritikus infrastruktúrák fizikai védelme olyan összetett, többváltozós rendszertervezési kérdés, ahol a fizikai, információs és humán alrendszerek nem izoláltan, hanem egymás működését folyamatosan befolyásolva határozzák meg a rendszer egészének teljesítményét. Ez a komplexitás különösen a katonai létesítményeknél érzékelhető, ahol a tapasztalatok tartósan magas fenyegetési terhelést és jelentős sokféleséget mutatnak, és ezek a tényezők a tervezési és üzemeltetési döntéseket közvetlenül befolyásolják.

A tanulmány a katonai kritikus infrastruktúrák fizikai védelmét rendszerszintű összefüggések mentén elemzi, külön figyelmet fordítva a többrétegű védelmi architektúrákra, a korszerű műszaki megoldások alkalmazhatóságára és a szabályozási környezet tényleges hatásaira. A vizsgálat olyan nemzetközi doktrínákra, mérnöki irányelvekre és hazai-európai szabványokra épül, amelyek a gyakorlatban bizonyítottan stabil és összehasonlítható keretet adnak a fizikai védelmi rendszerek tervezéséhez és értékeléséhez. A vizsgálat rámutat, hogy a fizikai védelem hatékonyságát döntően az alrendszerek közötti információáramlás minősége, a késleltetési képesség és a reagálási lánc integráltsága határozza meg, amelyek együttesen befolyásolják a rendszer műveleti teljesítményét.

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object(Publication)#116 (6) { ["_data"]=> array(28) { ["id"]=> int(8971) ["accessStatus"]=> int(0) ["datePublished"]=> string(10) "2026-09-28" ["lastModified"]=> string(19) "2026-09-28 13:44:57" ["primaryContactId"]=> int(11622) ["sectionId"]=> int(53) ["seq"]=> int(1) ["submissionId"]=> int(8846) ["status"]=> int(3) ["version"]=> int(1) ["categoryIds"]=> array(0) { } ["citationsRaw"]=> string(2604) "- 36/2017. (IX. 18.) NFM rendelet a meghatározott össztömeget, tengelyterhelést, tengelycsoport-terhelést és méretet meghaladó járművek közlekedéséről. Online: https://net.jogtar.hu/jogszabaly?docid=a1700036.nfm - 1/1975. (II. 5.) KPM–BM együttes rendelet a közúti közlekedés szabályairól. Online: https://njt.hu/jogszabaly/1975-1-20-24?utm_source=chatgpt.com ACO Directive 084-004. Criteria and Standards for the Zones of the Reinforcement and Sustainment Network, Supreme Headquarters Allied Powers Europe (2024). Mons. Általános tájékoztató a meghatározott össztömeget, tengelyterhelést, tengelycsoport-terhelést és méretet meghaladó járművek közúti közlekedésének engedélyezéséről [é. n.]. Magyar Közút Nonprofit Zrt. Online: https://internet.kozut.hu/ugyfelszolgalat/utvonalengedely-uvr-e-office/altalanos-tajekoztato/ Bizottság (EU) 2021/1328 végrehajtási rendelete az (EU) 2021/1153 európai parlamenti és tanácsi rendelet értelmében a kettős felhasználású infrastruktúrával kapcsolatos intézkedések egyes kategóriáira alkalmazandó infrastrukturális követelmények meghatározásáról. Online: https://eur-lex.europa.eu/eli/reg_impl/2021/1328/oj HORVÁTH Attila (2018): A katonai logisztika alapképzési szak RSOM felkészítés tapasztalatai. Hadmérnök, 13(4), 81–96. Online: https://doi.org/10.32567/hm.2019.4.5 Közutak tervezése. e-ÚT 03.01.11:2008 [é. n.]. Magyar Közút Nonprofit Zrt. Online: https://ume.kozut.hu/dokumentum/1490 NATO Standardization Agency (2004): AMovP-1(A) Road Movements and Movement Control. Brussels. PÓCSMEGYERI Gábor (2003): A katonaföldrajzi tényezők hatása a Magyar Köztársaság közlekedési rendszerének védelmi célú előkészítésére. PhD-disszertáció. Budapest: Zrínyi Miklós Nemzetvédelmi Egyetem Hadtudományi Doktori Iskola. SPIEGEL, Murray R. – STEPHENSEN, Larry J. (2018): Statistics, [ePub]. New York: McGraw-Hill Education. Online: http://103.203.175.90:81/fdScript/RootOfEBooks/E%20Book%20collection%20-%202023/MATHAS/Statistics%206th%20Edition%202017%20.pdf SZAJKÓ Gyula (2019): Az út és úthálózatok értékelése a hadszíntéri logisztikai felderítés végrehajtásakor. Hadmérnök, 14(4), 61–77. Online: https://doi.org/10.32567/hm.2019.4.5 SZAJKÓ Gyula (2025): A logisztikai felderítés rendszerének továbbfejlesztési lehetőségei a Magyar Honvédség műveleteinek előkészítésében. PhD-disszertáció. Budapest: Nemzeti Közszolgálati Egyetem Katonai Műszaki Doktori Iskola. Online: https://doi.org/10.17625/NKE.2025.033" ["copyrightYear"]=> int(2026) ["issueId"]=> int(696) ["licenseUrl"]=> string(49) "https://creativecommons.org/licenses/by-nc-nd/4.0" ["pages"]=> string(7) "103-118" ["pub-id::doi"]=> string(20) "10.32567/hm.2026.2.7" ["abstract"]=> array(2) { ["en_US"]=> string(1574) "

The road sector plays an important role in the integrated transportation system, and its operation and maintenance are also significant importance for the Hungarian Defence Forces (HDF), as it provides a connecting link between the bases of military organizations, airports, seaports and river ports, and railway stations. The movement of forces including military equipment, and personnel — between unloading ports (sea, air, and rail unloading ports) and the receiving operational areas — is carried out through road transport. Moreover, the largest volume of theater movement are carried out by road transportation. Its importance is further increased by the fact that, during wartime, any capacity shortage in the railway sector must be compensated by the road network, enabling rapid access to border areas from the centre of the country. Accordingly, logistical organizations must pay special attention to the gathering and up-to-date maintenance of road infrastructure capacity during the preparation and the entire duration of operations as well. For the targeted recce of information, it is advisable to use checklists and to define requirements for each feature of the criterion. This procedure allows for a faster and more efficient assessment of road infrastructure capacities, which can provide significant support in planning and organizing the movement and transportation of forces. Therefore, the aim of this article is to define requirements for checklists that can enhance the efficiency and speed of military assessments of road infrastructure.

" ["hu_HU"]=> string(1817) "

A közúti alágazat meghatározó szerepet tölt be az integrált közlekedési rendszerben, működtetése és fenntartása szintén lényeges a Magyar Honvédség (MH) számára, hiszen összekötő kapcsolatot biztosít a katonai szervezetek bázisai, a repülőterek, a tengeri és folyami kikötők, valamint a vasútállomások között. A csapatok haditechnikai eszközeinek és személyi állományának mozgatása – a kirakó pontok (tengeri, légi, vasúti kirakó pontok), valamint a fogadó, alkalmazási körlet között – közúton valósul meg, ráadásul a hadszíntéri közlekedés legnagyobb volumenét is a közúti szállítási feladatok teszik ki. Jelentőségét tovább növeli, hogy minősített időszakban a vasúti alágazatnál jelentkező kapacitáshiányt a közúthálózatnak kell pótolnia, úgy, hogy lehetővé tegye az ország mélységéből kiindulva a határszakaszok gyors elérését. Ennek megfelelően a közúti infrastruktúrák kapacitásadatinak gyűjtésére, valamint naprakész nyilvántartására kiemelt figyelmet kell fordítani a logisztikai szervezeteknek a műveletek előkészítésekor és annak teljes időszakában is. Az információk célirányos felderítéséhez érdemes szemrevételezési szempontlistákat alkalmazni és a szempontokhoz követelményeket meghatározni. Ezzel az eljárással gyorsabban és hatékonyabban lehet kiértékelni a közúti infrastruktúrák kapacitásadatait, ami jelentős segítséget nyújthat az erők mozgatás-szállítási feladatinak tervezésekor és szervezésekor. A cikkben a szerző célja, hogy a szemrevételezési szempontlistákhoz olyan követelményeket határozzon meg, amelyeket alkalmazva gyorsítható és hatékonyabbá tehető a közúti alágazat katonai szempontú értékelése.

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practical instructor

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gyakorlati oktató

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object(Publication)#750 (6) { ["_data"]=> array(28) { ["id"]=> int(9018) ["accessStatus"]=> int(0) ["datePublished"]=> string(10) "2026-09-28" ["lastModified"]=> string(19) "2026-09-28 13:44:56" ["primaryContactId"]=> int(11708) ["sectionId"]=> int(52) ["seq"]=> int(1) ["submissionId"]=> int(8893) ["status"]=> int(3) ["version"]=> int(1) ["categoryIds"]=> array(0) { } ["citationsRaw"]=> string(2976) "CHAPPELL, Andrew – WHITEHEAD, Leigh H (2022): Application of Transfer Learning to Neutrino Interaction Classification. The European Physical Journal C, 82(12). Online: https://doi.org/10.1140/epjc/s10052-022-11066-6 FARKAS, Gábor – FAZEKAS, Gábor – NÉMETH, András (2025): FPV-drónok detektálásának alternatív megoldása konvolúciós neurális hálózattal. Haditechnika, 59(2), 2–7. Online: https://doi.org/10.23713/HT.59.2.01 HackRF documentation (s. a.). Online: https://hackrf.readthedocs.io/en/latest/index.html HAIG, Zsolt – KOVÁCS, László – VÁNYA, László – VASS, Sándor (2014): Elektronikai hadviselés. Budapest: Nemzeti Közszolgálati Egyetem. Online: https://opac.uni-nke.hu/webview?infile=&sobj=9276&source=webvd&cgimime=application%2Fpdf%0D%0A HELL, Péter (2017): Drónelhárító rendszerek az objektumvédelemben. Hadmérnök, 12(3), 37–47. Online: http://www.hadmernok.hu/173_04_hell.pdf HORVÁTH, Tamás – ÖRDÖGH, Attila – BORKÓ, Máté (2024): Dróndetektáló fejlesztés. Haditechnika, 58(1), 55–59. Online: http://doi.org/10.23713/HT.58.1.10 JACK, Keith (2011): Video Demystified. A Handbook for the Digital Engineer. Amsterdam: Elsevier. LEE, Dongkyu – LA, Woong Gyu – KIM, Hwangnam (2018): Drone Detection and Identification System Using Artificial Intelligence. 2018 International Conference on Information and Communication Technology Convergence (ICTC), 1131–1133. Online: https://doi.org/10.1109/ICTC.2018.8539442 LIU, Haixia – BRAILSFORD, Tim – BULL, Larry (2024): Resnet18 Performance: Impact of Network Depth and Image Resolution on Image Classification. Proceedings of the 2024 8th International Conference on Advances in Artificial Intelligence, 351–356. Online: https://doi.org/10.1145/3704137.3704173 MOLLOY, Oleksandra (2024): Drones in Modern Warfare: Lessons Learnt from the War in Ukraine. Australian Army Research Centre. Online: https://doi.org/10.61451/267513 NÉMETH, András – VIRÁGH, Krisztián (2023): Mesterséges intelligencia és haderő – Katonai alkalmazási lehetőségek VII. rész. Haditechnika, 57(1), 2–6. Online: https://doi.org/10.23713/HT.57.1.01 POPPINGA, Gerald – ANDERSON, David – AMENDOLA, Danilo (2025): Technical Developments in Counter-drone Technology: C-UAS Detection, Tracking and Identification Technology. Luxembourg: Publications Office of the European Union. Online: https://doi.org/10.2760/1517220 SEO, Kang-Il – CHO, Sang-Keun – PARK, Sang-Hyuk (2023): A Case Study on FPV Drone Combats of the Ukrainian Forces. The Journal of the Convergence on Culture Technology, 9(3), 263–270. SHIN, Hoo-Chang – ROTH, Holger R. – GAO, Mingchen – LU, Le – XU, Ziyue – NOGUES, Isabella (2016): Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning. IEEE Transactions on Medical Imaging, 35(5), 1285–1298. Online: https://doi.org/10.1109/TMI.2016.2528162" ["copyrightYear"]=> int(2026) ["issueId"]=> int(696) ["licenseUrl"]=> string(49) "https://creativecommons.org/licenses/by-nc-nd/4.0" ["pages"]=> string(7) "119-135" ["pub-id::doi"]=> string(20) "10.32567/hm.2026.2.8" ["abstract"]=> array(1) { ["en_US"]=> string(799) "

The increasing use of FPV drones in modern conflicts necessitates compact and energy-efficient detection systems capable of operating in dynamic electromagnetic environments. AI-based RF signal detection is a promising solution. However, its application can be limited by the lack of labelled datasets and the constraints of embedded platforms. This article presents a method for generating and augmenting training data directly from signals captured from analogue FPV video transmitters. Finally, a convolutional neural network was trained using the generated dataset and evaluated in a real-time environment. Experimental results demonstrate reliable detection performance, indicating that the proposed method is an effective and efficient solution for embedded FPV drone detection systems.

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object(Publication)#773 (6) { ["_data"]=> array(28) { ["id"]=> int(8988) ["accessStatus"]=> int(0) ["datePublished"]=> string(10) "2026-09-28" ["lastModified"]=> string(19) "2026-09-28 13:44:56" ["primaryContactId"]=> int(11652) ["sectionId"]=> int(52) ["seq"]=> int(2) ["submissionId"]=> int(8863) ["status"]=> int(3) ["version"]=> int(1) ["categoryIds"]=> array(0) { } ["citationsRaw"]=> string(3683) "BRANDELLO FARIAS SOARES, Amanda (2025): Heart Rate Variability in Military Pilots During Flight: A Scoping Review. Military Medicine, 190(3–4), e515–e522. Online: https://doi.org/10.1093/milmed/usae390 CAO, Xiaodong et al. (2019): Heart Rate Variability and Performance of Commercial Airline Pilots during Flight Simulations. International Journal Environmental Research Public Health, 16(2), 237. Online: https://doi.org/10.3390/ijerph16020237 DONG, Jin‑Guo (2016): The Role of Heart Rate Variability in Sports Physiology. Experimental and Therapeutic Medicine, 11(5), 1531–1536. Online: https://doi.org/10.3892/etm.2016.3104 DUDER, Kate (2025): Your Guide to Heart Rate Variability Tracking - Prevent Burnout and Support Recovery from Illness. Inside Matters, 2025. április 23. Online: https://www.insidematters.co.nz/post/a-guide-to-heart-rate-variability-tracking-prevent-burnout-and-support-recovery-from-illness KIM, Hye-Geum et al. (2018): Stress and Heart Rate Variability: A Meta-Analysis and Review of the Literature. Psychiatry Investigation, 15(3), 235–245. Online: https://doi.org/10.30773/pi.2017.08.17 LINDSAY, Karen – VAN DEN TOP, Erik (2025): The Utility of Heart Rate Variability in Aviation and Space Medicine. Journal of the Australasian Society of Aerospace Medicine, 14(1), 19–26. Online: https://doi.org/10.2478/asam-2025-0002 MAKIVIĆ, Bojan – DJORDJEVIĆ NIKIĆ, Marina – WILLIS, Monte S. (2013): Heart Rate Variability (HRV) as a Tool for Diagnostic and Monitoring Performance in Sport and Physical Activities. Journal of Exercise Physiologyonline, 16(3), 103–131. Online: https://bit.ly/4vA3OK9 MANSIKKA, Heikki et al. (2015): Fighter Pilots’ Heart Rate, Heart Rate Variation and Performance During Instrument Approaches. Ergonomics, 59(10), 1344–1352. Online: https://doi.org/10.1080/00140139.2015.1136699 MASI, Giulia (2024): Stress and Workload Assessment in Aviation. A Narrative Review. Sensors, 24(2), 690. Online: https://doi.org/10.3390/s23073556 PORGES, Stephen W. (2022): Heart Rate Variability: A Personal Journey. Applied Psychophysiology and Biofeedback, 47(4), 259–271. Online: https://doi.org/10.1007/s10484-022-09559-x SCHERER, Matthias – MARTINEK, Johannes – MAYR, Winfried (2019): HRV (Heart Rate Variability) as a Non-Invasive Measurement Method for Performance Diagnostics and Training Control. Current Directions in Biomedical Engineering, 5(1), 97–100. Online: https://doi.org/10.1515/CDBME-2019-0025 SHAFFER, Fred – GINSBERG, J. P. (2017): An Overview of Heart Rate Variability Metrics and Norms. Frontiers in Public Health, 5. Online: https://doi.org/10.3389/fpubh.2017.00258 SHAW, David M. – HARRELL, John W. (2023): Integrating Physiological Monitoring Systems in Military Aviation: A Brief Narrative Review of Its Importance, Opportunities, and Risks. Ergonomics, 66(12), 2242–2254. Online: https://doi.org/10.1080/00140139.2023.2194592 THAYER, Julian F. et al. (2012): A Meta-Analysis of Heart Rate Variability and Neuroimaging Studies: Implications for Heart Rate Variability as a Marker of Stress and Health. Neuroscience & Biobehavioral Reviews, 36(2), 747–756. Online: https://doi.org/10.1016/j.neubiorev.2011.11.009 WANG, Peizheng – HOUGHTON, Robert – MAJUMDAR, Arnab (2024): Detecting and Predicting Pilot Mental Workload Using Heart Rate Variability: A Systematic Review. Sensors, 24(12). Online: https://doi.org/10.3390/s24123723 WU, Alexander C. et al. (2016): Airplane Pilot Mental Health and Suicidal Thoughts: A Cross-Sectional Descriptive Study via Anonymous Web-Based Survey. Environmental Health,15, 121. Online: https://doi.org/10.1186/s12940-016-0200-6 " ["copyrightYear"]=> int(2026) ["issueId"]=> int(696) ["licenseUrl"]=> string(49) "https://creativecommons.org/licenses/by-nc-nd/4.0" ["pages"]=> string(7) "137-147" ["pub-id::doi"]=> string(20) "10.32567/hm.2026.2.9" ["abstract"]=> array(2) { ["en_US"]=> string(1466) "

Aircraft operation is a complex task that requires the full capacity of human attention and involves extensive information processing, consequently, it imposes significant psychological, cognitive, and physical workload on operators. Stressors encountered during flight can lead to performance degradation and may reduce flight safety. Therefore, monitoring pilots’ mental workload can provide valuable data for improving operational safety. Mental workload is a multidimensional construct influenced by numerous external and internal (human-related) factors. However, in today’s highly automated cockpit environments, conventional workload measurement protocols may face considerable limitations. Heart rate variability (HRV) has emerged as a promising tool for detecting professionals’ mental workload under real flight conditions. The application of HRV measurement to assess operator workload in complex environments opens up numerous future opportunities. Data generated through this method can be used to characterize the stress response and recovery capacity of the autonomic nervous system. Fatigue, for instance, is a subjective sensation that manifests at different rates and intensities across individuals, which makes its objective assessment difficult challenging. Heart rate variability represents a high-quality biomarker for evaluating fatigue status and may contribute to a more comprehensive understanding of fatigue-related processes.

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A légi járművek irányítása komplex, az emberi figyelem egészét kívánó tevékenység, amely mélyreható információfeldolgozást igényel, ezáltal aktív pszichológiai, kognitív és fizikai terhelést jelent az operátorok számára. A fellépő stresszorok teljesítménycsökkenéshez vezethetnek és redukálhatják a repülésbiztonságot, ennek érdekében a repülőgép-vezetők mentális terhelésének monitorozása kulcsfontosságú adatokkal szolgálhat a biztonság növelésének szempontjából. A mentális terhelés ugyanakkor többtényezős dimenzió, amelyet számos külső és belső (emberi) tényező befolyásolhat, ugyanakkor a mai magasan automatizált fülkékben a konvencionális mérési protokollok kihívásokba ütközhetnek. A szívfrekvencia-variabilitás (heart rate variability, HRV) ígéretes eszközként jelent meg a szakemberek mentális terhelésének valós repülési körülmények közötti detektálására. A szívfrekvencia-variabilitás mérésének lehetősége az operátorok terhelésének vizsgálatára összetett környezetben a jövőben számos új lehetőséget nyit meg. A módszer segítségével generált adatok révén alkalmas az autonóm idegrendszer stresszválaszának és regenerációs képességének feltérképezésére. Szemléltetésül: a fáradtság szubjektív, egyénenként változó ütemben és mélységben megjelenő érzet, amelynek objektív értékelése esetenként nehézségekbe ütközik. A szívfrekvencia-variabilitás olyan minőségű biomarker a fáradtsági állapot felmérésére, amely hozzásegíthet a fáradtság részletesebb megértéséhez.

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MH vitéz Szentgyörgyi Dezső 101. Repülődandár

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(2022): Intelligent Guidance and Control Methods for Missile Swarm. Computational Intelligence and Neuroscience, Wiley Online Library. Online: https://doi.org/10.1155/2022/8235148 ZHANG, Qirui – WEI, Ruixuan (2019): Ground Attack Strategy of Cooperative UAVs for Multitargets. Complexity, 9428087. Online: https://doi.org/10.1155/2019/9428087 DANIAL, Syed Nasir et al. (2019): Situation Awareness Modeling for Emergency Management on Offshore Platforms. Human-centric Computing and Inswarm Sciences, 9(37), 1–26. Online: https://doi.org/10.1186/s13673-019-0199-0 NOBAHARI, Hadi – NASROLLAHI, Saeed (2020): A Nonlinear Robust Model Predictive Differential Game Guidance Algorithm Based on the Particle Swarm Optimization. Journal of the Franklin Institute, 357(15), 11042–11071. Online: https://doi.org/10.1016/j.jfranklin.2020.08.032 ZHOU, Kai et al. (2020): An Air Combat Decision Learning System Based on a Brain-Like Cognitive Mechanism. Cognitive Computation, 12(4), 128–139. Online: https://doi.org/10.1007/s12559-019-09683-7 KUCHAR, James K. – YANG, Lee C. (2000): A Review of Conflict Detection and Resolution Modeling Methods. IEEE Transactions on Intelligent Transportation Systems, 1(4), 179–189. Online: https://doi.org/10.1109/6979.898217 YU, Wenwu et al. (2013): Distributed Control Gains Design for Consensus in Multi-Agent Systems with Second-Order Nonlinear Dynamics. Automatica, 49(7), 2107–2115. Online: https://doi.org/10.1016/j.automatica.2013.03.005 ZHU, Weiren – DUAN, Haibin (2013): Chaotic Predator-Prey Biogeography-Based Optimization Approach for UAV Path Planning. Aerospace Science and Technology, 32(1), 153–161. Online: https://doi.org/10.1016/J.AST.2013.11.003 LEVY, Maital – SHIMA, Tal – GUTMAN, Shaul (2013): Linear Quadratic Integrated versus Separated Autopilot-Guidance Design. Journal of Guidance, Control, and Dynamics, 36(6), 1722–1730. Online: https://doi.org/10.2514/1.61363 YUEH, William R. – LIN, Ching F. (1984): Optimal Controller for Homing Missile. Proceedings of the American Control Conference, San Diego, CA, USA, 737–742. Online: https://doi.org/10.23919/ACC.1984.4788473 YANG, Biao et al. (2013): Self-Adaptive PID Controller of Microwave Drying Rotary Device Tuning On-Line by Genetic Algorithms. Journal of Central South University, 20, 2685–2692. Online: https://doi.org/10.1007/s11771-013-1784-4 ZHANG, Yu – CHEN, Jing – SHEN, Lincheng (2013): Real-Time Trajectory Planning for UAV Air-To-Surface Attack Using Inverse Dynamics Optimization Method and Receding Horizon Control. Chinese Journal of Aeronautics, 26(4), 1038–1056. Online: https://doi.org/10.1016/j.cja.2013.04.040 GU, Wenjin – ZHAO, Hongchao – ZHANG, Ruchuan (2008): A Three-Dimensional Proportional Guidance Law Based on RBF Neural Network. Proceedings of the 7th World Congress on Intelligent Control And Automation, Chongqing, China, 6978–6982. 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Online: https://doi.org/10.23919/chicc.2017.8028323 HONG, Toan Dinh et al. (2017): Active Disturbance Rejection Control Design for Integrated Guidance and Control Missile Based SMC and Extended State Observer. Proceedings of the 2017 International Conference on System Science and Engineering, Ho Chi Minh City, Vietnam, 476–481. Online: https://doi.org/10.1109/ICSSE.2017.8030920 JIAN, Chen et al. (2016): Integrated Guidance and Control Design Based on a Reference Model. International Journal of Control, Automation and Systems, 14(5), 1299–1308. Online: https://doi.org/10.1007/s12555-015-0048-5 ZHU, Guodong – SHEN, Zuojun (2015): Three Dimensional Trajectory Linearization Control for Flight of Air-Breathing Hypersonic Vehicle. Procedia Engineering, 99, 1108–1119. Online: https://doi.org/10.1016/j.proeng.2014.12.646 ZHOU, Huan et al. (2015): Robust Integrated Guidance and Control Design Method for UAV Based on Trajectory Linearization Control. Proceedings of the 15th International Conference on Control, Automation and Systems, Busan, Korea (South). Online: https://doi.org/10.1109/ICCAS.2015.7364797 ZHANG, Xue et al. (2020): Nonlinear Distributed Model Predictive Control for Multiple Missiles Against Maneuvering Target with a Trajectory Predictor. Journal of Shanghai Jiaotong University, 25, 779–789. Online: https://doi.org/10.1007/s12204-020-2233-9" ["copyrightYear"]=> int(2026) ["issueId"]=> int(696) ["licenseUrl"]=> string(49) "https://creativecommons.org/licenses/by-nc-nd/4.0" ["pages"]=> string(7) "149-171" ["pub-id::doi"]=> string(21) "10.32567/hm.2026.2.10" ["abstract"]=> array(2) { ["en_US"]=> string(1308) "

The unmanned aerial vehicles (UAVs) are being used more and more widely in both the military and civilian sectors. The Russian-Ukrainian war has demonstrated the value of these systems, particularly in missile-carrying attacks, and they will play an indispensable key role in future wars as a specialized combat method. The authors summarize the C2 (command and control) procedures for missile-based attack operations, present traditional design solutions for command and control systems, and then analyze the command and control methods for typical swarm attacks while considering relevant characteristics, and discuss the limitations of traditional design methods. The article focuses on the advantages of intelligent integrated guidance and control design over traditional design concepts. It summarizes commonly used integrated guidance and control design methods and their applications, and explores a cooperative attack strategy for missile carriers suitable for an integrated guidance and control system. It examines the challenges of missile guidance and control and identifies issues worthy of further research in the future. The summary of missile guidance and control methods contributes to innovative research in this field, which promotes the development of drone swarm attack technology.

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A pilóta nélküli légi járműveket (UAV) egyre szélesebb körben alkalmazzák mind a katonai, mind pedig a polgári szférában. Az orosz–ukrán háború bebizonyította ezen eszközök létjogosultságát, különösen a rakétahordozó jellegű támadásokban, és kulcsszerepet fognak betölteni a jövőbeni háborúkban mint különleges harci mód. A szerzők összegzik a rakétahordozó támadási művelet irányítási és vezérlési eljárásait, bemutatják az irányító- és vezérlőrendszer hagyományos tervezési megoldásait, ezt követően pedig elemzik a jellegzetes rajtámadás irányítási és vezérlési módszereit a megfelelő jellemzők figyelembevételével, és kitérnek a hagyományos tervezési módszerek korlátjaira. A cikk az intelligens integrált irányítási és vezérlési tervezés előnyeire koncentrál a hagyományos tervezési ötletekkel szemben. Összegzi az általánosan alkalmazott integrált irányítási és vezérléstervezési módszereket és azok felhasználásait, valamint feltárja az integrált irányító- és vezérlőrendszerhez megfelelő rakétahordozó kooperatív támadási stratégiáját. Megvizsgálja a rakétahordozók irányításának és vezérlésének kihívásait, és feltárja azokat a problémákat, amelyek a jövőben további kutatásra érdemesek. A rakéták irányítási és vezérlési módszereinek összefoglalása hozzájárul az innovatív kutatáshoz ezen a területen, ami elősegíti a pilóta nélküli rajtámadási technológia fejlődését.

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