• 융합정보논문지
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• 제11권1호
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• pp.12-19
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• 2021

원활한 작전 수행을 통한 국방력의 강화를 위해 전술네트워크의 기능은 필수적이다. 전시 상황에서 다양한 전술, 전략은 수많은 정보들을 근거로 한다. 이를 위해 정찰기를 비롯한 다양한 정보 수집 장치 및 자원들이 방대한 양의 정보 수집을 위해 사용되고, 이들 대다수는 전술네트워크를 통해 정보를 전달한다. 채널의 사용 여부를 판단하여 상황에 따라 경쟁 기반으로 채널에 접속을 하는 국방전술네트워크 환경에서, 매우 높은 이동성을 갖는 정찰기 등 고속 이동 노드는 불필요한 채널 점유로 인하여 잠재적인 성능 열화 문제가 발생할 수 있다. 본 논문에서는 채널 예약 시점을 정하는 경쟁 윈도우(Contention Window)의 크기를 경험적으로 학습시켜 네트워크 처리량을 증가시키는 Learning-Backoff 방식의 무전 채널 접속 방법을 제안한다. 제안하는 방법은 고속 이동 노드의 수가 많아짐에 따라 더욱 좋은 성능을 보이고 있으며, 정찰기 4대가 운영되는 특정 작전 시나리오에 적용하였을 경우 처리량이 최대 25% 증가한다.

• 융합정보논문지
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• 제11권12호
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• pp.106-114
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• 2021

무선 통신에 대한 요구는 민간 분야에서 뿐만 아니라 군 에서도 계속해서 증가하고 있다. 그러므로 무선 통신 기술의 개선이 사용자 요구에 부응할 필요가 있다. 무선 통신 기술의 활용에 있어서 주요 단점 중 하나는 할당된 주파수 대역의 많은 부분이 미 사용되는 스펙트럼의 비 효율적인 사용이라고 할 수 있다. 군 통신에 있어서 스펙트럼 부족문제는 다국적 연합 작전과 같은 상황에서 성공적인 작전을 수행하는데 제한사항이 될 수도 있다. 이러한 문제점을 해결할 수 있는 방안으로 인지무선 네트워크는 실시간 사용 가능한 스펙트럼을 찾아서 사용할 수 있도록 해주는 중요한 기술이다. 또한 인지무선 네트워크 기술은 간섭을 피하고 시스템 전체의 스펙트럼 효율성을 개선하며 다양한 환경에서 유연성을 제공하는 등 스펙트럼 관련 문제들을 해결할 수 있다. 본 논문은 인지무선 네트워크의 군 작전환경에서의 활용 방안을 구체적으로 분석하여 제시하였으며 실제 작전 상황별로 적용 가능한 최적의 방안을 제시하였다.

• Journal of Contemporary Eastern Asia
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• 제15권2호
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• pp.191-210
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• 2016

While general belief is that the military alliances are stable and rigid, the authors argue that the states are far more flexible in their behavior and often act against their alliances. This paper looks at states' behavior in the UN GA and looks how it is reflected in participation in military alliances during three periods of history since 1976 to this day. The authors illustrate the need to consider the network representation of co-sponsoring groups in General Assembly votes. They find significant support for their argument, indicating that social aspects can be extended beyond alliances. An application of social network analysis shows some unexpected affiliations in UN GA. If the UN GA is the "true" nature of these countries' alliance strategies, then it might suggest some significant defections and interesting association.

• Journal of Information Processing Systems
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• 제13권1호
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• pp.128-140
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• 2017

The wireless sensor networks (WSNs) became a very essential tool in borders and military zones surveillance, for this reason specific applications have been developed. Surveillance is usually accomplished through the deployment of nodes in a random way providing heterogeneous topologies. However, the process of the identification of all nodes located on the network's outer edge is very long and energy-consuming. Before any other activities on such sensitive networks, we have to identify the border nodes by means of specific algorithms. In this paper, a solution is proposed to solve the problem of energy and time consumption in detecting border nodes by means of node selection. This mechanism is designed with several starter nodes in order to reduce time, number of exchanged packets and then, energy consumption. This method consists of three phases: the first one is to detect triggers which serve to start the mechanism of boundary nodes (BNs) detection, the second is to detect the whole border, and the third is to exclude each BN from the routing tables of all its neighbors so that it cannot be used for the routing.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2005년도 추계종합학술대회
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• pp.799-802
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• 2005

In this paper, we analyses of Key Management Protocol for Wireless Sensor Networks in Wireless Sensor Networks. Wireless sensor networks have a wide spectrum of civil military application that call for security, target surveillance in hostile environments. Typical sensors possess limited computation, energy, and memory resources; therefore the use of vastly resource consuming security mechanism is not possible. In this paper, we propose a cryptography key management protocol, which is based on identity based symmetric keying.

• 한국군사과학기술학회지
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• 제16권3호
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• pp.304-313
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• 2013

Wireless Sensor Networks, especially supporting for surveillance service, are one of the core properties of network-centric warfare(NCW) that is a key factor of victory in future battlefields. Such a tactical surveillance sensor network must be designed not just for energy efficiency but for real-time requirements of emergency data transmission towards a control center. This paper proposes efficient clustering-based methods for supporting mobile sinks so that the network lifetime can be extended while emergency data can be served as well. We analyze the performance of the proposed scheme and compare it with other existing schemes through simulation via Qualnet 5.0.

• 경영과학
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• 제16권1호
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• pp.89-99
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• 1999

Combat fatigues are issued to military personnel with ready made clothes. Ready made combat fatigues should be fitted to various bodies of military personnel within given standard size. This paper develops a standard sizes selection method in order to increase the coverage rate and fitness for combat fatigues. The method utilizes a generalized learning vector quantization(GLVQ) algorithm that is one of cluster algorithm in neural networks techniques. The GLVQ moves the standard sizes from initial arbitrary sizes to next sizes in order to increase more coverage rate and fitness. Finally, when it cannot increase those, algorithm is terminated. The results of this method show more coverage rate and fitness than those of the other methods.

• 한국군사과학기술학회지
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• 제1권1호
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• pp.82-91
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• 1998

본 논문에서는 실제 물리적인 여유 센서를 가지지 않는 수중운동체의 센서 고장진단 및 극복에 관한 문제를 신경회로망을 사용하여 접근하였다. 이를 위하여 설계된 신경회로망은 센서 고장 진단을 위한 신경회로망과 고장 확인 및 대체정보 생성을 위한 신경회로망으로 구성하였으며, 온라인(on-line) 학습을 위하여 확장 역전(Extended Back-Propagation) 학습법을 사용하였다. 시뮬레이션은 수중운동체의 방위변화율 센서에 대하여 수행하였으며, 제안된 기법이 센서에 대한 고장진단기와 센서 추정기로 사용할 수 있음을 확인하였다.

• 정보와 통신
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• 제32권10호
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• pp.31-40
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• 2015

This paper investigates several existing techniques to reduce high-availability seamless redundancy (HSR) traffic. HSR is a redundancy protocol for Ethernet networks that provides duplicated frames for separate physical paths with zero recovery time. This feature makes it very useful for real-time and mission-critical applications, such as military applications and substation automation systems. However, the major drawback of HSR is that it generates too much unnecessary redundant traffic in HSR networks. This drawback degrades network performance and may cause congestion and delay. Several HSR traffic reduction techniques have been proposed to reduce the redundant traffic in HSR networks, resulting in the improvement of network performance. In this paper, we provide an overview of these HSR traffic reduction techniques in the literature. The operational principles, advantages, and disadvantages of these techniques are investigated and summarized. We also provide a traffic performance comparison of these HSR traffic reduction techniques.

• 한국군사과학기술학회지
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• 제26권5호
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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.