• Title/Summary/Keyword: Defense Science Technology

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A Study on the Application of Analytic Hierarchy Process to Improve the Fairness of Evaluation Indicators for the National Defense Core Technology R&D Projects (국방 핵심기술 연구개발 사업의 평가지표 개선을 위한 계층분석적의사결정기법 적용 연구)

  • Kim, Chan-Soo;Cho, Kyu-Kab
    • Journal of the Korea Institute of Military Science and Technology
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    • v.10 no.3
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    • pp.79-89
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    • 2007
  • This study suggests the applicability of an AHP(Analytic Hierarchy Process) to improve the validity and fairness of evaluation index to assess the defense core-technology R&D projects. This study focused on the design of the proposal and performance evaluation index to structure them into a hierarchy using AHP which can be applicable to take the opinion of the defense R&D experts. Using the refined evaluation index, we propose a technique to enhance the reliability of the defense R&D projects evaluation system.

A Comparison for the Maturity Level of Defense AI Technology to Support Situation Awareness and Decision Making (상황인식 및 의사결정지원을 위한 국방AI기술의 성숙도 수준비교)

  • Kwon, Hyuk Jin;Joo, Ye Na;Kim, Sung Tae
    • Journal of the Korean Society of Systems Engineering
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    • v.18 no.1
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    • pp.90-98
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    • 2022
  • On February 12, 2019, the U.S. Department of Defense newly established and announced the "Defense AI Strategy" to accelerate the use of artificial intelligence (AI) technology for military purposes. As China and Russia invested heavily in AI for military purposes, the U.S. was concerned that it could eventually lose its advantage in AI technology to China and Russia. In response, China and Russia, which are hostile countries, and especially China, are speeding up the development of new military theories related to the overall construction and operation of the Chinese military based on AI. With the rapid development of AI technology, major advanced countries such as the U.S. and China are actively researching the application of AI technology, but most existing studies do not address the special topic of defense. Fortunately, the "Future Defense 2030 Technology Strategy" classified AI technology fields from a defense perspective and analyzed advanced overseas cases to present a roadmap in detail, but it has limitations in comparing private technology-oriented benchmarking and AI technology's maturity level. Therefore, this study tried to overcome the limitations of the "Future Defense 2030 Technology Strategy" by comparing and analyzing Chinese and U.S. military research cases and evaluating the maturity level of military use of AI technology, not AI technology itself.

Online Hop Timing Detection and Frequency Estimation of Multiple FH Signals

  • Sha, Zhi-Chao;Liu, Zhang-Meng;Huang, Zhi-Tao;Zhou, Yi-Yu
    • ETRI Journal
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    • v.35 no.5
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    • pp.748-756
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    • 2013
  • This paper addresses the problem of online hop timing detection and frequency estimation of multiple frequency-hopping (FH) signals with antenna arrays. The problem is deemed as a dynamic one, as no information about the hop timing, pattern, or rate is known in advance, and the hop rate may change during the observation time. The technique of particle filtering is introduced to solve this dynamic problem, and real-time frequency and direction of arrival estimates of the FH signals can be obtained directly, while the hop timing is detected online according to the temporal autoregressive moving average process. The problem of network sorting is also addressed in this paper. Numerical examples are carried out to show the performance of the proposed method.

Estimation of Physical Layer Scrambling Code Sequence of DVB-S2

  • Wu, Hao;Xie, Hui;Huang, Zhi-Tao;Zhou, Yi-Yu
    • ETRI Journal
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    • v.36 no.2
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    • pp.329-332
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    • 2014
  • In this letter, the problem of estimating the physical layer (PL) scrambling code sequence of DVB-S2 is studied. We present the first ever scheme to estimate the scrambling sequence. The scheme is based on hypothesis testing. By analyzing the PL scrambling process, we construct a new sequence equivalent to the scrambling sequence. We then use hypothesis testing to estimate the new sequence. The threshold for the hypothesis testing is also discussed. The experiment results show that the performance of our estimation scheme can work even under high BER.

Design of stepwise foam claddings subjected to air-blast based on Voronoi model

  • Liang, Minzu;Lu, Fangyun;Zhang, Guodong;Li, Xiangyu
    • Steel and Composite Structures
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    • v.23 no.1
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    • pp.107-114
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    • 2017
  • Design of stepwise foam claddings subjected to air-blast is performed based on random Voronoialgorithm. FE models are constructed using the random Voronoialgorithm, and numerical analysis is carried out to simulate deformation mode and energy absorption of the cladding by the ABAQUS/Explicit software. The FE model is validated by test result, and good agreement is achieved. The deformation patterns are presented to give an insight into the influences of distribution on deformation mechanisms. The energy absorbed by the stepwise foam cladding is examined, and the parameter effects, including layer number, gradient, and blast loading, are discussed. Results indicate that the energy absorption capacity increases with the number of layer, gradient degree, and blast pressure increasing.

Driver's Face Detection Using Space-time Restrained Adaboost Method

  • Liu, Tong;Xie, Jianbin;Yan, Wei;Li, Peiqin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.6 no.9
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    • pp.2341-2350
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    • 2012
  • Face detection is the first step of vision-based driver fatigue detection method. Traditional face detection methods have problems of high false-detection rates and long detection times. A space-time restrained Adaboost method is presented in this paper that resolves these problems. Firstly, the possible position of a driver's face in a video frame is measured relative to the previous frame. Secondly, a space-time restriction strategy is designed to restrain the detection window and scale of the Adaboost method to reduce time consumption and false-detection of face detection. Finally, a face knowledge restriction strategy is designed to confirm that the faces detected by this Adaboost method. Experiments compare the methods and confirm that a driver's face can be detected rapidly and precisely.

Structural Design of Composite Blade and Tower for Small Wind Turbine System

  • Jang, Mingi;Lee, Sanggyu;Park, Gwanmun;Park, Hyunbum
    • International Journal of Aerospace System Engineering
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    • v.2 no.1
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    • pp.38-42
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    • 2015
  • This work is to propose a structural design and analysis procedure for development of the low noise 1kW class small wind turbine system which will be applicable to relatively low speed region like Korea and for the domestic use. The proposed structural configuration has a sandwich composite structure with the E-glass/Epoxy face sheets and the Urethane foam core for lightness, structural stability, low manufacturing cost and easy manufacturing process. Structural analysis including load cases, stress, deformation, buckling, vibration and fatigue life was performed using the Finite Element Method, the load spectrum analysis and Miner rule. In order to evaluate the designed structure, the structural test was carried out and its test results were compared with the estimated results. Moreover Investigation on structural safety of tower was verified through structural analysis by FEM.

Intention-Oriented Itinerary Recommendation Through Bridging Physical Trajectories and Online Social Networks

  • Meng, Xiangxu;Lin, Xinye;Wang, Xiaodong;Zhou, Xingming
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.6 no.12
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    • pp.3197-3218
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    • 2012
  • Compared with traditional itinerary planning, intention-oriented itinerary recommendations can provide more flexible activity planning without requiring the user's predetermined destinations and is especially helpful for those in unfamiliar environments. The rank and classification of points of interest (POI) from location-based social networks (LBSN) are used to indicate different user intentions. The mining of vehicles' physical trajectories can provide exact civil traffic information for path planning. This paper proposes a POI category-based itinerary recommendation framework combining physical trajectories with LBSN. Specifically, a Voronoi graph-based GPS trajectory analysis method is utilized to build traffic information networks, and an ant colony algorithm for multi-object optimization is implemented to locate the most appropriate itineraries. We conduct experiments on datasets from the Foursquare and GeoLife projects. A test of users' satisfaction with the recommended items is also performed. Our results show that the satisfaction level reaches an average of 80%.

Design and Experimental Demonstration of Coaxially Folded All-reflective Imaging System

  • Xiong, Yupeng;Dai, Yifan;Chen, Shanyong;Tie, Guipeng
    • Current Optics and Photonics
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    • v.3 no.3
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    • pp.227-235
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    • 2019
  • With slimmer, lighter and all-reflective imaging systems in high demand for consumer and military applications, coaxially folded optical image systems are widely considered because they can extend focal length and reduce track length. Most of these systems consist of multiple surfaces, and these surfaces are machined on one element or grouping processing on two elements. In this paper, we report and first experimentally demonstrate an all-aluminum all-reflective optical system which consists of two optical elements, with two high order aspherical surfaces in each element. The coaxially folded system is designed with Seidel aberration theory and advanced optimization with Zemax. The system is made of all-aluminum material processing by single point diamond turning (SPDT). On this basis, we completed the system integration and performed an imaging experiment. The final system has the advantages of short track length and long focal length and broad application prospects in the micro-unmanned aerial vehicle field.

Synthetic Image Generation for Military Vehicle Detection (군용물체탐지 연구를 위한 가상 이미지 데이터 생성)

  • Se-Yoon Oh;Hunmin Yang
    • Journal of the Korea Institute of Military Science and Technology
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    • v.26 no.5
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    • pp.392-399
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    • 2023
  • This research paper investigates the effectiveness of using computer graphics(CG) based synthetic data for deep learning in military vehicle detection. In particular, we explore the use of synthetic image generation techniques to train deep neural networks for object detection tasks. Our approach involves the generation of a large dataset of synthetic images of military vehicles, which is then used to train a deep learning model. The resulting model is then evaluated on real-world images to measure its effectiveness. Our experimental results show that synthetic training data alone can achieve effective results in object detection. Our findings demonstrate the potential of CG-based synthetic data for deep learning and suggest its value as a tool for training models in a variety of applications, including military vehicle detection.