• 한국군사과학기술학회지
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• 제23권3호
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• pp.204-212
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• 2020

For general target tracking works by receiving a set of measurements from sensor. However, if the SNR(Signal to Noise Ratio) is low due to small RCS(Radar Cross Section), caused by remote small targets, the target's information can be lost during signal processing. TBD(Track Before Detect) is an algorithm that performs target tracking without threshold for detection. That is, all sensor data is sent to the tracking system, which prevents the loss of the target's information by thresholding the signal intensity. On the other hand, using all sensor data inevitably leads to computational problems that can severely limit the application. In this paper, we propose an iterative Joint Integrated Probabilistic Data Association as a practical target tracking technique suitable for a low SNR multi-target environment with real time operation capability, and verify its performance through simulation studies.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.541-547
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• 1992

The phased array antenna has the ability to perform adaptive sampling by directing the radar beam without inertia in any direction. The adaptive sampling capability of the phased array antenna allows each sampling time interval to be varied for each target, depending on the acceleration of each target at any time. In this paper we design a three-dimensional adaptive tracking algorithm for the phased array radar system with a given set of measurement parameters. The tracking algorithm avoids taking unnecessarily frequent samples, while keeping the angular prediction error within a fraction of antenna beamwidth so that the probability of detection will not be degraded during a track update illuminations. In our algorithm, the target model and the sampling rate are selected depending on the target range and the target maneuver status which is determined by a maneuver detector. A detailed simulation is conducted to test the validity of our tracking algorithm for encounter geometries under various conditions of maneuver.

• 한국멀티미디어학회논문지
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• 제21권9호
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• pp.1062-1067
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• 2018

Conventional active sonar technology has relied heavily on the hearing of sonar operator, but recently, many techniques for automatic detection and classification have been studied. In this paper, we extract the image data from the spectrogram of the active sonar signal and classify the extracted data using CNN(convolutional neural networks), which has recently presented excellent performance improvement in the field of pattern recognition. First, we divided entire data set into eight classes depending on the ratio containing the target. Then, experiments were conducted to classify the eight classes data using proposed CNN structure, and the results were analyzed.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 춘계 학술대회 학술발표 논문집
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• pp.243-246
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• 2003

Data mining is a process of discovering useful patterns for decision making from an amount of data. It has recently received much attention in a wide range of business and engineering fields Classifying a group into subgroups is one of the most important subjects in data mining Tree-based methods, known as decision trees, provide an efficient way to finding classification models. The primary concern in tree learning is to minimize a node impurity, which is evaluated using a target variable in the data set. However, there are situations where multiple target variables should be taken into account, for example, such as manufacturing process monitoring, marketing science, and clinical and health analysis. The purpose of this article is to present several methods for measuring the node impurity, which are applicable to data sets with multiple target variables. For illustrations, numerical examples are given with discussion.

• International Journal of Quality Innovation
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• 제6권2호
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• pp.31-45
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• 2005

The target costing technique, mathematically discussed by Sauers, only uses the $C_p$ index along with Taguchi loss function and ${\bar{X}}-R$ control charts to set up goal control limits. The new specification limits derived from Taguchi loss function is linked through the $C_p$ value to ${\bar{X}}-R$ control charts to obtain goal control limits. This study further considers the reflected normal loss function as well as the $C_{pk}$ index along with its lower confidence interval in forming goal control limits. With the use of lower confidence interval to replace the point estimator of the $C_{pk}$ index and reflected normal loss function proposed by Spiring to measure the loss to society, this modified and improved target costing technique would become more robust and applicable in practice. Finally, an example is provided to illustrate how this modified and improved target costing technique works.

• 한국군사과학기술학회지
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• 제16권4호
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• pp.441-448
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• 2013

This paper describes the development of Target Simulator developed for performance test and failure detection of Imaging Infra-Red(IIR) seeker which is one of the most important equipments in specific cruise missile systems. The simulator makes it possible to test detecting and tracking performance for target, uniformity of IIR, FOV status and spatial resolving power. Besides, it includes several self-test functions and optic axis alignment methods to improve its own reliability.

• 한국통신학회논문지
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• 제28권4A호
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• pp.208-215
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• 2003

H-ARQ를 적용한 시스템에서 최대 수율(throughput)을 얻기 위한 Target PER을 수치적 해석 방법을 이용하여 구하였고 시뮬레이션 과정을 통하여 검증하였다. 수치적 해석 방법을 위하여 chase combine의 효과는 해밍 거리가 증가하는 효과로 간주하였고 이를 바탕으로 수율 계산식과 터보 부호에서 평균 상호값(Average upper bound)을 이용한 PER간의 연계식을 유도하여 최적의 Targer PER값을 구했다. 그 결과 H-ARQ방법이 적용된 경우 현재 3GPP2 표준에 선정되어 있는 5%에 비해 더 높은 6% target PERㅇ에서 최대 수율이 나타나는 결과를 확인할 수 있었다.

• 한국항공우주학회지
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• 제49권7호
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• pp.601-608
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• 2021

공대지 유도폭탄의 투하 가능 영역(LAR)은 플랫폼이 목표하는 지점에 장착물이 성공적으로 명중하기 위해 진입해야 하는 영역을 의미한다. 목표물의 기동 종류에 따라 크게 고정표적, 이동표적으로 나누며, 본 논문에서는 고정표적 및 이동표적에도 적용 가능한 투하 가능 영역의 산출 알고리즘에 대해 연구하였다. 이는 플랫폼과 표적, 대기환경을 매개변수로 하여 입력변수를 변화시키며 다중 시뮬레이션을 수행 후 회귀 및 분류 알고리즘을 이용하여 적절한 투하 가능 영역을 시현하기 위한 함수를 개발하였다. 운용 적합성을 위한 시현 알고리즘을 적용하여 적절한 투하 가능 영역이 도출되며, 결과적으로 이동표적에도 적용할 수 있는 공대지 유도폭탄의 투하 가능 영역 알고리즘의 적용 가능성을 확인하였다.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2009년도 춘계학술대회 논문집
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• pp.252-255
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• 2009

The roll gap set-up in the finishing mill is one of the most important technologies in the hot plate rolling process. As the target thickness can be obtained by the correct set-up of the roll gap, improving the roll gap set-up technology is very critical for plate thickness accuracy. The main cause of thickness variation in hot plate mills is the non-uniform temperature distribution along the length of the slab. The objective of this study is to adjust the roll gap set-up for the thickness accuracy of plate in hot rolling process considering top-end temperature drop. Therefore this study has concentrated on determining the correct amounts of roll gap to compensate thickness variation due to top-end temperature drop. The off-line simulation of compensated roil gap significantly decreases top-end thickness variation.

• The Journal of Asian Finance, Economics and Business
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• 제7권2호
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• pp.221-228
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• 2020

This study suggests an alternative to the conventional collaborative filtering method for predicting consumer choice, using case-based reasoning. The algorithm of case-based reasoning determines the similarity between the alternative sets that each subject chooses. Case-based reasoning uses the inverse of the normalized Euclidian distance as a similarity measurement. This normalized distance is calculated by the ratio of difference between each attribute level relative to the maximum range between the lowest and highest level. The alternative case-based reasoning based on similarity predicts a target subject's choice by applying the utility values of the subjects most similar to the target subject to calculate the utility of the profiles that the target subject chooses. This approach assumes that subjects who deliberate in a similar alternative set may have similar preferences for each attribute level in decision making. The result shows the similarity between comparable alternatives the consumers consider buying is a significant factor to predict the consumer choice. Also the interaction effect has a positive influence on the predictive accuracy. This implies the consumers who looked into the same alternatives can probably pick up the same product at the end. The suggested alternative requires fewer predictors than conjoint analysis for predicting customer choices.