• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.43-46
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• 2023

호흡기 관련 전염병의 주된 증상인 기침은 공기 중에 감염된 병원균을 퍼트리며 비감염자가 해당 병원균에 노출된 경우 높은 확률로 해당 전염병에 감염될 위험이 있다. 또한 사람들이 많이 모이는 공공장소 및 실내 공간에서의 기침 탐지 및 조치는 전염병의 대규모 유행을 예방할 수 있는 효율적인 방법이다. 따라서 본 논문에서는 탐지해야 하는 기침 소리 및 일상생활 속 발생할 수 있는 기침과 유사한 배경 소리 들을 Mel-Spectrogram으로 변환한 후 시각화된 특징을 CNN 모델에 학습시켜 기침 탐지를 진행하며, 일반적으로 사용되는 사전 학습된 CNN 모델에 제안된 Attention 모듈의 적용이 기침 탐지 성능 향상에 도움이 됨을 입증하였다.

• The Journal of the Acoustical Society of Korea
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• v.39 no.6
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• pp.549-558
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• 2020

In this paper, the method is discussed such that the robustness of automatic initiated narrowband target tracking is improved in passive sonar. In the case of automatic tracking initiation as target in passive sonar, due to a number of clutter, the clutter is initiated as target and tracked which prohibits the operation capability. The associated probability and information entropy of measurements, extracted from detection data, is calculated to keep going on automatic target initiation and tracking of true target, but reduce the automatic initiation and tracking of clutter. If the association probability and information entropy of the extracted measurements is satisfied for the predefined conditions, the procedure of automatic initiation begins. Using sea-trial data, simulations are executed and the results from the proposed method indicate that it keeps the automatic target initiation and tracking of true target and suppresses the automatic target initiation and tracking of clutters in contrary to the conventional method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.12
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• pp.1115-1123
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• 2011

This paper proposes an image processing algorithms for detection and tracking of aerial vehicles in short-range. Proposed algorithm detects moving objects by using image homography calculated from consecutive video frames and determines whether the detected objects are approaching aerial vehicles by the Probabilistic Multi-Hypothesis Tracking method(PMHT). This algorithm can perform better than simple color-based detection methods since it can detect moving objects under complex background such as the ground seen during low altitude flight and consider the characteristics of vehicle dynamics. Furthermore, it is effective for the flight test due to the reduction of thresholding sensitivity against external factors. The performance of proposed algorithm is verified by applying to the onboard video obtained by flight test.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.153-162
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• 2009

This paper suggests the novel light-weight signal processing algorithm for wireless sensor network applications which needs low computing complexity and power consumption. Exponential average method (EA) is utilized by real time, to process the magnetometer signal which is analyzed to understand the own physical characteristic in time domain. EA provides the robustness about noise, magnetic drift by temperature and interference, furthermore, causes low memory consumption and computing complexity for embedded processor. Hence, optimal parameter of proposal algorithm is extracted by statistical analysis. Using general and precision magnetometer, detection probability over 90% is obtained which restricted by 5% false alarm rate in simulation and using own developed magnetometer H/W, detection probability over 60~70% is obtained under 1~5% false alarm rate in simulation and experiment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1670-1675
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• 2020

In this study, to provide the basis for establishing effective network based countermeasures against DRDoS(Distributed Reflection Denial of Service) attacks, we propose a new 'DRDoS attack multi-level detection method' that identifies the network based characteristics of DRDoS and applies probability and statistical techniques. The proposed method removes the limit to which normal traffic can be indiscriminately blocked by unlimited competition in network bandwidth by amplification of reflectors, which is characteristic of DRDoS. This means that by comparing 'Server to Server' and 'Outbound Session Incremental' for it, accurate DRDoS identification and detection is possible and only statistical and probabilistic thresholds are applied to traffic. Thus, network-based information security systems can take advantage of this to completely eliminate DRDoS attack frames. Therefore, it is expected that this study will contribute greatly to identifying and responding to DRDoS attacks.

• The KIPS Transactions:PartC
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• v.12C no.7 s.103
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• pp.1007-1014
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• 2005

A generation of rules or patterns for detecting attacks from network is very difficult. Detection rules and patterns are usually generated by Expert's experiences that consume many man-power, management expense, time and so on. This paper proposes statistical methods that effectively detect intrusion and attacks without expert's experiences. The methods are to select useful measures in measures of network connection(session) and to detect attacks. We extracted the network session data of normal and each attack, and selected useful measures for detecting attacks using relative entropy. And we made probability patterns, and detected attacks using likelihood ratio testing. The detecting method controled detection rate and false positive rate using threshold. We evaluated the performance of the proposed method using KDD CUP 99 Data set. This paper shows the results that are to compare the proposed method and detection rules of decision tree algorithm. So we can know that the proposed methods are useful for detecting Intrusion and attacks.

• Journal of the Korea Society for Simulation
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• v.31 no.4
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• pp.11-22
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• 2022

Unlike a short-range, a long-range underwater acoustic communication(UWAC) uses low frequency signal and deep sound channel to minimize propagation loss. In this case, even though communication signals are modulated using a covert transmission technique such as spread spectrum, it is hard to conceal the existence of the signals. The unconcealed communication signal can be utilized as active sonar signal by enemy and presence of underwater vehicles may be exposed to the interceptor. Since it is very important to maintain stealthiness for underwater vehicles, the detection probability of friendly underwater vehicles should be considered when interceptor utilizes our long-range UWAC signal. In this paper, we modeled a long-range UWAC environment for analyzing the detection performance of underwater vehicles and proposed the region of interest(ROI) setup method and the measurement of detection performance. By computer simulations, we yielded parameters, analyzed the detection probability and the detection performance in ROI. The analysis results showed that the proposed detection performance analysis method for underwater vehicles could play an important role in the operation of long-range UWAC equipment.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.3
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• pp.37-46
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• 2012

In RADAR and SONAR detection systems, noise environment can be classified into homogeneous and heterogeneous environment. Especially heterogeneous environments are modelled as target masking and clutter edge. Since the variability-index (VI) CFAR, a composed CFAR algorithm, dynamically selects one of the mean-level algorithms based on the VI and the MR (mean ratio) test, it is robust to various environments. However, the VI CFAR still suffers from lowered detection probabilities in heterogeneous environments. To overcome these problems, we propose an improved VI CFAR processor where TM (trimmed mean) CFAR and a sub-windowing technique are introduced to minimize the degradation of the detection probabilities appeared in heterogeneous environments. Computer simulation results show that the proposed method has the better performance in terms of detection probability and false alarm probability compared to the VI CFAR and single CFAR algorithms.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.4
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• pp.35-41
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• 2008

When memory devices are exposed to a space environment. they suffer various effects such as SEU(Single Event Upset). For these reasons, memory systems for space applications are generally equipped with error detection and correction(EDAC) logics against SEUs. In this paper, the error detection and correction strategy in the Mass Memory Unit(MMU) of the STSAT-3 is discussed. The probability equation of un-recoverable SEUs in the mass memory system is derived when the whole memory is encoded and decoded by the RS(10,8) Reed-Solomon code. Also the probability value is analyzed for various occurrence rates of SEUs which the STSAT-3 possibly suffers. The analyzed results can be used to determine the period of scrubbing the whole memory, which is one of the important parameters in the design of the MMU.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.7 no.2
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• pp.100-105
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• 2014

This paper comparatively analyze to integration case to have a influence detection range estimation about radar cross section in radar system. This paper estimate detection range used to probability of detection in radar equation that used to swerling case 1 in case of radar cross section is small and used to swerling case 3 in case of radar cross section is large. Through simulation, coherent integration and non-coherent integration about swerling case difference were comparatively analyzed. Through simulation, non-coherent integration case is outstanding detection range and we known that coherent integration don't suitable for detection range estimation.