• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2009년도 춘계학술대회 논문집
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• pp.400-401
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• 2009

본 논문에서는 DARPA의 지원하에 미공군이 이중모드 램제트를 이용하여 개발하고 있는 X-51A와 미 해군이 이중연소 램제트를 이용하여 개발하고 있는 HyFly 의 개념 및 연구 개발 활동에 대하여 소개한다.

• 한국생산제조학회지
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• 제24권5호
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• pp.548-552
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• 2015

In this paper, we describe the quadruped walking-control algorithm of the complete full-size humanoid DARPA Robotics Challenge-HUBO (DRC-HUBO) robot. Although DRC-HUBO is a biped robot, we require a quadruped walking function using two legs and two arms to overcome uneven terrains in the DRC. We design a wave-type quadruped walking pattern as a feedforward control using several walking parameters, and we design zero moment point (ZMP) controllers to maintain stable walking using an inverted pendulum model and an observed-state feedback control scheme. In particular, we propose a switching algorithm for ZMP controllers using supporting value and weighting factors in order to maintain the ZMP control performance during foot switching. Finally, we verify the proposed algorithm by performing quadruped walking experiments using DRC-HUBO.

• 대한조선학회논문집
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• 제58권2호
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• pp.58-65
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• 2021

In order to study the self-propulsion test and analysis techniques for the submerged body in Large Cavitation Tunnel (LCT). DARPA Suboff, a submarine model publicly available was manufactured. The resistance results of DARPA Suboff was acquired from the LCT tests and compared with those of DTRC. After the wall blockage correction, the resistance results of LCT were in good agreement with those of DTRC. On the basis of the resistance results of LCT, the self-propulsion tests were conducted in LCT. The test objective was to get the full-scale propeller operating conditions for the propeller cavitation and noise tests. The test results of DARPA Suboff were analyzed in a way similar to the analysis techniques of those of the Towing Tank (TT). Another submerged body, for which self-propulsion tests were conducted in TT, was selected for results verification. The results of LCT were in good agreement with those of TT. On the basis of the present study, it is thought that the operating conditions for the full-scale submerged body can be drawn through LCT tests.

• 한국데이타베이스학회:학술대회논문집
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• 한국데이타베이스학회 1997년도 International Conference MULTIMEDIA DATABASES on INTERNET
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• pp.24-48
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• 1997

. Supported byㆍDARPA′s image Understanding (IU) program under "Video Retrieval Based on Language and image Analysis" project.DARPA′s Computer Assisted Education and Training Initiative program (CAETI)ㆍObjective: Develop practical systems for automatic understanding and indexing of video sequences using both audio and video tracks(omitted)

• 정보와 통신
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• 제30권1호
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• pp.67-76
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• 2012

본고에서는 jamming 이나 은폐 등으로 인하여 통신 채널이 동적으로 변화하는 전장환경에서 dynamic spectrum access(DSA) 기술을 토대로 보다 안정된 통신을 하는 기술을 알아본다. DSA 통신의 핵심기술을 설명하고, 미국의 DARPA에서 수행한 neXt Generation(XG) 프로젝트와 Wireless Network after Next(WNaN) 국방통신 프로젝트를 소개한 후에 결론에서 시사점을 다룬다.

• 한국전산유체공학회지
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• 제20권2호
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• pp.81-87
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• 2015

For Underwater vehicles, Unwanted roll excursions are inevitable as they are caused by induced propeller torque, disturbances, and banking motion during turns. To estimate the manoeuvring performance of underwater vehicle, it is necessary to obtain the roll coefficient of body. This paper was covered estimation of roll coefficient of underwater vehicle using STAR-CCM+, commercial CFD(Computational Fluid Dynamics) code. The RANS equations for incompressible fluid flows was solved numerically by using a finite volume method. An MRF(Moving Reference Frame) Method was Also adopted for rotations of body. For the validation, the flow around a DARPA SUBOFF bare hull model was simulated and good agreement with experiments was obtained. And Pure roll coefficients were calculated and campared with the experimental data which were presented by Seoul National University. Finally, an underwater vehicle model with propeller was simulated and analyzed for estimation of roll coefficient variation caused by induced propeller torque.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권8호
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• pp.3884-3910
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• 2016

Intrusion Detection System (IDS) in general considers a big amount of data that are highly redundant and irrelevant. This trait causes slow instruction, assessment procedures, high resource consumption and poor detection rate. Due to their expensive computational requirements during both training and detection, IDSs are mostly ineffective for real-time anomaly detection. This paper proposes a dimensionality reduction technique that is able to enhance the performance of IDSs up to constant time O(1) based on the Principle Component Analysis (PCA). Furthermore, the present study offers a feature selection approach for identifying major components in real time. The PCA algorithm transforms high-dimensional feature vectors into a low-dimensional feature space, which is used to determine the optimum volume of factors. The proposed approach was assessed using HTTP packet payload of ISCX 2012 IDS and DARPA 1999 dataset. The experimental outcome demonstrated that our proposed anomaly detection achieved promising results with 97% detection rate with 1.2% false positive rate for ISCX 2012 dataset and 100% detection rate with 0.06% false positive rate for DARPA 1999 dataset. Our proposed anomaly detection also achieved comparable performance in terms of computational complexity when compared to three state-of-the-art anomaly detection systems.

• Journal of Computing Science and Engineering
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• 제5권4호
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• pp.305-313
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• 2011

Due to the expansion of high-speed Internet access, the need for secure and reliable networks has become more critical. The sophistication of network attacks, as well as their severity, has also increased recently. As such, more and more organizations are becoming vulnerable to attack. The aim of this research is to classify network attacks using neural networks (NN), which leads to a higher detection rate and a lower false alarm rate in a shorter time. This paper focuses on two classification types: a single class (normal, or attack), and a multi class (normal, DoS, PRB, R2L, U2R), where the category of attack is also detected by the NN. Extensive analysis is conducted in order to assess the translation of symbolic data, partitioning of the training data and the complexity of the architecture. This paper investigates two engines; the first engine is the back-propagation neural network intrusion detection system (BPNNIDS) and the second engine is the radial basis function neural network intrusion detection system (BPNNIDS). The two engines proposed in this paper are tested against traditional and other machine learning algorithms using a common dataset: the DARPA 98 KDD99 benchmark dataset from International Knowledge Discovery and Data Mining Tools. BPNNIDS shows a superior response compared to the other techniques reported in literature especially in terms of response time, detection rate and false positive rate.

• 대한조선학회논문집
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• 제43권4호
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• pp.460-466
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• 2006

The three-dimensional RANS equations were applied to analyze the flow field of a submarine. To validate the code, the DARPA SUBOFF bare hull and an eliipsoid at angles of attack of $10^{\circ}\;and\;30^{\circ}$ were simulated and good agreement with experiments was obtained. After the code validation, the flows over the full configuration of DARPA SUBOFF model having a fairwater and four stern appendages were simulated at four angles of attack $(0^{\circ},\;10^{\circ},\;20^{\circ},\;30^{\circ})$ and three yaw angles $(10^{\circ},\;20^{\circ},\;30^{\circ})$ Specifically, the pressure contours and streamlines of fairwater and stern appendage were compared as the angle of attack and yaw angle changed. The variations of hydrodynamic forces were also calculated.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2008년도 제30회 춘계학술대회논문집
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• pp.303-306
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• 2008

미국은 X-43A 를 통한 스크램제트 무인기의 비행 시험을 성공적으로 마치고 미공군 주도하에 X-51A 스크램제트 기술 실증기를 개발하고 있다. X-51A는 PWR 사의 X-1 탄화수소 연료 스크램제트 엔진을 이용하여 2008년에 지상시험을 마치고 2009년에 비행시험이 계획되어 있으며, 이를 통하여 X-51A에서 확립된 기술은 향후 DARPA의 Falcon 프로그램에 의한 HTV-3X 극초음속 시험기 및 HCV 순항기 개발에 적용될 것이다. 본 논문에서는 액체 및 초임계 JP-7 연료를 이용한 엔진 구조물의 냉각 및 연소 등 X-51의 추진기관 핵심 기술에 대하여 살펴보고자 한다.