A method of drawing double arrow symbols with automation support for 2D digital map applications
92 viewsDOI:
https://doi.org/10.54939/1859-1043.j.mst.94.2024.139-148Keywords:
Military maps; Military map symbols; Operations planning; Approximation; Artificial intelligence.Abstract
This paper addresses the challenges of translating pivotal military symbols like double arrows onto 2D digital maps, particularly when automation is essential. It proposes a comprehensive method integrating data structure, user workflow, and algorithms to generate tactically aligned, balanced, and visually appealing double arrows for military 2D digital maps. Experimental validation affirms its efficacy in meeting tactical requisites and aesthetic standards. Additionally, it outlines avenues for future research to further enhance and broaden the applicability of this method. In essence, this study presents a robust solution for the automated generation of double arrows on 2D digital military maps, marking a significant step in advancing automated symbolization for military planning.
References
[1]. Department of Cartography/General Staff, “Map consulting work”, (2019).
[2]. Nguyen Duc Dinh, Hoang Van Toan, “System Design Documentation of T3BD System”, (2020).
[3]. D Swann, “Geographical Information Systems”, Second Edition, Abridged, (2005).
[4]. G. Wallne, "Enhancing Battle Maps through Flow Graphs," IEEE Conference on Games (CoG), London, UK, pp. 1-4, (2019), doi: 10.1109/CIG.2019.8848052. DOI: https://doi.org/10.1109/CIG.2019.8848052
[5]. Ferenc FAZEKAS, “Application of Artificial Intelligence in Military Operations Planning”, AARMS (21) 2, (2022). DOI: https://doi.org/10.32565/aarms.2022.2.3
[6]. Kent, A. J., Davies, J., & Davis, M. “Soviet mapping: Then and now”. The Cartographic Journal, 59(4), 259-263, (2022). https://doi.org/10.1080/00087041.2022.2267282. DOI: https://doi.org/10.1080/00087041.2022.2267282
[7]. Meerveld, H.W., Lindelauf, R.H.A., Postma, E.O. et al. “The irresponsibility of not using AI in the military”. Ethics Inf Technol 25, 14, (2023). https://doi.org/10.1007/s10676-023-09683-0. DOI: https://doi.org/10.1007/s10676-023-09683-0
[8]. Dang Duc Thinh, Nguyen Chi Thanh, et al. “A voice search engine for military symbols to enhance the drafting of operational plan documents on digital map”. Journal of Military Science and Technology 87:40-49, (2023). DOI:10.54939/1859-1043.j.mst.87.2023.40-49. DOI: https://doi.org/10.54939/1859-1043.j.mst.87.2023.40-49
[9]. Minshuo Chen, Haoming Jiang, Wenjing Liao, Tuo Zhao, “Nonparametric regression on low-dimensional manifolds using deep ReLU networks: function approximation and statistical recovery”, Information and Inference: A Journal of the IMA, Volume 11, Issue 4, pp. 1203–1253, (2022), https://doi.org/10.1093/imaiai/iaac001. DOI: https://doi.org/10.1093/imaiai/iaac001
[10]. L. Kong, J. Wang and P. Zhao, "YOLO-G: A Lightweight Network Model for Improving the Performance of Military Targets Detection," in IEEE Access, vol. 10, pp. 55546-55564, (2022), doi: 10.1109/ACCESS.2022.3177628. DOI: https://doi.org/10.1109/ACCESS.2022.3177628
