• Journal of KIISE:Computing Practices and Letters
• /
• v.14 no.2
• /
• pp.221-225
• /
• 2008

In this paper, to avoid the frequency analysis requiring a high sampling rate, time-warped similarity measure algorithms, which are able to classify objects even with a low-rate sampling rate as time- series methods, are presented and proposed the DTW-Cosine algorithm, as the best classifier among them in wireless sensor networks. Two problems, local time shifting and spatial signal variation, should be solved to apply the time-warped similarity measure algorithms to wireless sensor networks. We find that our proposed algorithm can overcome those problems very efficiently and outperforms the other algorithms by at least 10.3% accuracy.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.6
• /
• pp.566-572
• /
• 2021

A methodology for the identification and coordinates estimation of air cavities under urban ground or sandy soil using its natural poles and natural resonant frequencies is presented. The potential of this methodology was analyzed. Simulation models of PEC (Perfect Electric Conductor)s with various shapes and dimensions were developed using an EM (Electromagnetic) simulator. The Cauchy method was applied to the obtained EM scattering response of various objects from EM simulation models. The natural poles of objects corresponding to its instinct characterization were then extracted. Thus, a library of poles can be generated using their natural poles. The generated library of poles provided the possibility of identifying a target by comparing them with the computed natural poles from a target. The simulation models were made assuming that there is an air cavity under urban ground or sandy soil. The response of the desired target was extracted from the electromagnetic wave scattering data from its simulation model. The coordinates of the target were estimated using the time delay of the impulse response (peak of the impulse response) in the time domain. The MP (Matrix Pencil) method was applied to extract the natural poles of a target. Finally, a 0.2-m-diameter spherical air cavity underground could be estimated by comparing both the pole library of the objects and the calculated natural poles and the natural resonant frequency of the target. The computed location (depth) of a target showed an accuracy of approximately 84 to 93%.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.4
• /
• pp.182-188
• /
• 2013

In this paper, we propose a complex-valued support vector machine (SVM) classifier which process the complex valued signal measured by pulse doppler radar (PDR) to identify moving targets from the background. SVM is widely applied in the field of pattern recognition, but features which used to classify are almost real valued data. Proposed complex-valued SVM can classify the moving target using real valued data, imaginary valued data, and cross-information data. To design complex-valued SVM, we consider slack variables of real and complex axis, and use the KKT (Karush-Kuhn-Tucker) conditions for complex data. Also we apply radial basis function (RBF) as a kernel function which use a distance of complex values. To evaluate the performance of the complex-valued SVM, complex valued data from PDR were classified using real-valued SVM and complex-valued SVM. The proposed complex-valued SVM classification was improved compared to real-valued SVM for dog and human, respectively 8%, 10%, have been improved.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.21 no.1
• /
• pp.141-148
• /
• 2021

In some intersections or busy traffic roads, there are more pedestrians in a specific period of time, and there are many traffic accidents caused by road congestion. Especially at the intersection where there are schools nearby, it is particularly important to protect the traffic safety of students in busy hours. In the past, when designing traffic lights, the safety of pedestrians was seldom taken into account, and the identification of motor vehicles and traffic optimization were mostly studied. How to keep the road smooth as far as possible under the premise of ensuring the safety of pedestrians, especially students, will be the key research direction of this paper. This paper will focus on person, motorcycle, bicycle, car and bus recognition research. Through investigation and comparison, this paper proposes to use YOLO v4 network to identify the location and quantity of objects. YOLO v4 has the characteristics of strong ability of small target recognition, high precision and fast processing speed, and sets the data acquisition object to train and test the image set. Using the statistics of the accuracy rate, error rate and omission rate of the target in the video, the network trained in this paper can accurately and effectively identify persons, motorcycles, bicycles, cars and buses in the moving images.

• Proceedings of the Korean Information Science Society Conference
• /
• 2007.10a
• /
• pp.169-170
• /
• 2007

• Journal of Satellite, Information and Communications
• /
• v.4 no.2
• /
• pp.12-19
• /
• 2009

In the modern UAV systems, the role of radar payload has been increasing with its unique performance of day-and-night operation and see-through capability over hidden obstacles. Contrary to the satellite reconnaissance, UAV is expected to provide high resolution target detection and recognition capability while frequent flight missions would deliver enhanced SAR image and local information over the target area. STK(Satellite Tool Kit) is a professional space-analysis software widely used in all phases of a space system's life cycle. The simulation of STK is efficient and accurate relatively. In this paper, the author attempt to model the UAV operation and measure the expected SAR image quality. STK(Satellite Tool Kit) is employed to analyze UAV operation and produce SAR raw data. A SAR simulator is developed to produce high resolution SAR image for various ground targets.

• Journal of KIISE:Software and Applications
• /
• v.35 no.7
• /
• pp.424-430
• /
• 2008

Identifying crosscutting concerns during requirements engineering phase is one of the most essential parts in Aspect-Oriented Software Development. Considering crosscutting concerns in the earlier phase of the development improves consistency among requirements so that it can help maintain software systems efficiently and effectively. It also provides a systematic way to manage requirements changes by supporting traceability throughout the software lifecycle. Thus, identifying tangled and scattered concerns, and encapsulating them into separate entities must be addressed from the early phase of the development. To do so, first, functional and non-functional concerns must be clearly separated. Second, a pointcut where a main concern meets crosscutting concerns should be defined and specified precisely. Third, it is required to detect conflicts being occurred during composition of crosscutting concerns from the earlier phase. Therefore, this paper proposes a systematic approach to identifying and specifying crosscutting concerns using goal-scenario based requirements analysis. And we demonstrate the applicability of the approach by applying it into the intelligent service robot system.

• Proceedings of the KAIS Fall Conference
• /
• 2006.11a
• /
• pp.242-244
• /
• 2006

본 논문에서는 레이더와 전자정보에서 획득한 방향정보 자료를 이용해서 전자파 정보를 융합하는 기술을 제시한다. 레이더에서 획득한 표적신호와 전자정보에서 획득한 정보신호를 융합하면 표적을 정확하게 확인할 수 있기 때문에 레이더의 탐지 오차율이 줄어들고 표적에 대한 상세 정보를 확보할 수 있어서 표적식별이나 목표물 선정에 쉽게 사용할 수 있다.

• Convergence Security Journal
• /
• v.20 no.1
• /
• pp.77-84
• /
• 2020

Due to the lack of a system that can detect/identify and strike North Korea's small unmanned aerial vehicles, no immediate response was made. In order to solve the problem of response, we should prepare for threats by developing weapons systems that can be immediately hit when identifying small-sized unmanned aerial vehicle detection radar and creating specialized research organizations for research and development of equipment.

• The Korean Journal of Air & Space Law and Policy
• /
• v.35 no.1
• /
• pp.127-152
• /
• 2020

Despite growing international cooperation for maintenance of international peace and security, wars continue to occur due to conflicted state interests. Continuing conflicts has advanced development of various weapon systems such as global integrated intelligence, surveillance and reconnaissance. However, with a big increase in the number of civilian casualties caused by the weapon systems development, the international community has also advanced diplomatic efforts to minimize deaths of civilian and military personnel. Therefore, it is essential to observe the principle of discrimination between combatants and non-combatants when operating unmanned aerial vehicles (UAVs), better known as drones. Drones have become more capable of distinguishing combatants from non-combatants due to its high-tech prowess. In the operation of drones, any parties involved in combat or the war are responsible for mounting civilian casualties. In addition, it should comply with the principle of proportionality that calls for a balance between results of such action and expected military advantage anticipated from the attack. The rule of proportionality prohibits use of military force which may be expected to cause excessive civilian harm. Drones have been able to track and monitor targets for hours and select the accurate locations of the targets. The aim is to reduce civilian losses and damage to a minimum. Drones meet the standards of Article 51.4 of the Additional Protocol.