• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.2
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• pp.141-146
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• 2018

The Ground Moving Target Indication(GMTI) technique can detect the moving targets on land using its Doppler returns. Also, the GMTI system can work in night regardless of the weather condition because it is an active sensor that uses the electromagnetic waves as its source. In order to develop the GMTI system, Constant False Alarm Rate(CFAR) threshold optimization is important because the main performances like detection probability, false alarm rate and Minimum Detectable Velocity(MDV) are related deeply with CFAR threshold. These key variables are used to calculate CFAR threshold and then trade-off between the variables is performed. In this paper, CFAR threshold optimization procedures are introduced, and the optimization results are demonstrated.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.1
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• pp.32-40
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• 2013

In this paper, we propose a multi-channel speech enhancement algorithm using beamforming and direction-of-arrival (DOA)-based masking. The proposed algorithm enhances noisy speech basically by the linearly constrained minimum variance (LCMV) algorithm and then a mel-scale Wiener filter designed using DOA-based masking is applied to remove still remaining noises. To improve the performance, we optimize the learning rate of the adaptive filters in LCMV and the DOA threshold to detect target speech spectrum. As performance indices, the perceptual evaluation of speech quality (PESQ) score and output SNRs are measured. Experimantal results show that the proposed algorithm outperforms the conventional LCMV beamformer by 0.09 in PESQ score and 5.75 dB in output SNR, respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.11
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• pp.23-30
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• 2017

Most superconducting magnets which generate more than 20 T consist of nested magnets. A combination of LTS and HTS magnets is conventionally used, but high field magnets which use only HTS magnets have been developed recently. As HTS wires have very strong magnetic anisotropy, appropriate techniques should be used to consider this effect properly. The load line method has been conventionally used to design nested magnets for high field generation. Because this method considers only parallel and perpendicular magnetic fields, the effect of their orientation is not taken into account. In this paper, the actual orientation of the magnetic fields from 0 to 90 degrees is considered. The critical currents of the two kinds of high field nested magnets designed using the proposed method are calculated. The finite element method is used to calculate the distribution of the magnetic fields and the evolution strategy is used to find the critical current which maximizes the central magnetic field.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.283-285
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• 2023

이상 탐지는 데이터에서 일반적인 범주에서 크게 벗어나는 인스턴스 또는 패턴을 식별하는 중요한 작업이다. 본 연구에서는 시계열 데이터의 특징 추출을 위한 비지도 학습 기반 방법과 정규화 흐름의 결합을 통한 이상 탐지 프레임워크를 제안한다. 특징 추출기는 1차원 합성곱 신경망 기반의 오토인코더로 구성되며, 정상적인 시퀀스로만 구성된 훈련 데이터를 압축하고 복원하는 과정을 통해 최적화된다. 추출된 시계열 데이터의 특징 맵은 가능도를 최대화하도록 훈련된 정규화 흐름의 입력으로 사용된다. 이와 같은 방식으로 훈련된 이상 탐지 시스템은 테스트 샘플에 대한 이상치를 계산하며, 최종적으로 임계값과의 비교를 통해 이상 여부를 예측한다. 성능 평가를 위해 시계열 이상 탐지를 위한 공개 데이터셋을 이용하여 공정하게 이상 탐지 성능을 비교하였으며, 실험 결과는 제안하는 정규화 흐름 기법이 시계열 이상 탐지 시스템에 활용될수 있는 잠재성을 시사한다.

• KIISE Transactions on Computing Practices
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• v.20 no.11
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• pp.579-585
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• 2014

A phoneme is the minimal unit of speech, and it plays a very important role in speech recognition. This paper proposes a novel method that can be used to recognize 'ㅅ', 'ㅈ', and 'ㅊ' among Korean phonemes. The proposed method is based on a volatility indicator and a turning point indicator that are calculated for each constituting block of the input speech signal. The volatility indicator is the sum of the differences between the values of each two samples adjacent in a block, and the turning point indicator is the number of extremal points at which the direction of the increment or decrement of the values of the sample are inverted in a block. A phoneme recognition algorithm combines the two indicators to finally determine the positions at which the three target phonemes mentioned above are recognized by utilizing optimized thresholds related with those indicators. The experimental results show that the proposed method can markedly reduce the error rate of the existing methods both in terms of the false reject rate and the false accept rate.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.4
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• pp.50-57
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• 2009

This paper presents a new model-based macroblock layer rate control algorithm for low bit rate video coding which generates output bits corresponding to a target bit budget. The H.264 standard uses various coding modes and optimization methods to improve the compression performance, which makes it difficult to control the generated traffic accurately in low bit rate environments. In the proposed scheme, we first estimate MAD values of macroblocks in a frame and define a target remaining bits using the estimated MAD values before encoding each macroblock. If a difference between the target value and the actual value is greater than a threshold value, the quantization parameter is adjusted to decrease the difference. It is shown by experimental results that the new algorithm can obtain more than 66% decrease of the difference between the target bits and the resulting bits for a frame with the PSNR performance better than that of the existing rate control algorithm.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1087-1094
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• 2023

Due to the development of technologies, such as big data, cloud, IoT, and AI, The high data throughput is required, and the importance of network flexibility and scalability is increasing. However, existing network systems are dependent on vendors and equipment, and thus have limitations in meeting the foregoing needs. Accordingly, SDN technology that can configure a software-centered flexible network is attracting attention. In particular, a load balancing method based on SDN can efficiently process massive traffic and optimize network performance. In the existing load balancing studies in SDN environment have limitation in that unnecessary traffic occurs between servers and controllers or performing load balancing only after the server reaches an overload state. In order to solve this problem, this paper proposes a method that minimizes unnecessary traffic and appropriate load balancing can be performed before the server becomes overloaded through a method of assigning weights to servers in stages according to server load.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.127-137
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• 2019

Recidivism prediction has been a subject of constant research by experts since the early 1970s. But it has become more important as committed crimes by recidivist steadily increase. Especially, in the 1990s, after the US and Canada adopted the 'Recidivism Risk Assessment Report' as a decisive criterion during trial and parole screening, research on recidivism prediction became more active. And in the same period, empirical studies on 'Recidivism Factors' were started even at Korea. Even though most recidivism prediction studies have so far focused on factors of recidivism or the accuracy of recidivism prediction, it is important to minimize the prediction misclassification cost, because recidivism prediction has an asymmetric error cost structure. In general, the cost of misrecognizing people who do not cause recidivism to cause recidivism is lower than the cost of incorrectly classifying people who would cause recidivism. Because the former increases only the additional monitoring costs, while the latter increases the amount of social, and economic costs. Therefore, in this paper, we propose an XGBoost(eXtream Gradient Boosting; XGB) based recidivism prediction model considering asymmetric error cost. In the first step of the model, XGB, being recognized as high performance ensemble method in the field of data mining, was applied. And the results of XGB were compared with various prediction models such as LOGIT(logistic regression analysis), DT(decision trees), ANN(artificial neural networks), and SVM(support vector machines). In the next step, the threshold is optimized to minimize the total misclassification cost, which is the weighted average of FNE(False Negative Error) and FPE(False Positive Error). To verify the usefulness of the model, the model was applied to a real recidivism prediction dataset. As a result, it was confirmed that the XGB model not only showed better prediction accuracy than other prediction models but also reduced the cost of misclassification most effectively.

• Journal of KIISE:Information Networking
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• v.33 no.1
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• pp.38-48
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• 2006

For extending of hot-spot of WLAN, (2) proposes internetworking scheme between wireless LAN (WLAN) and mobile ad-hoc network (MANET), which employ the same layer-2 protocol with different mode. Compared to internetworking schemes between UMTS (Universal Mobile Telecommunications Systems) and WLAN (3-4), the scheme from (2) has relatively low overhead and latencies because WLAN and MANET are physically and logically similar to each other. However, the mode switching algorithm proposed in r2] for internetworking between WLAN and MANET only considers signal strength and determines handoff, and mobile nodes following a zigzag course in pollution area may perform handoff at short intervals. Furthermore, (2) employs mobile IPv6 (MIPv6) at base, which brings still high delay on handoff and overhead due to signal message exchange. In this paper, we present optimized internetworking scheme between WLAN and MANET, modified from (2). To settle ping-pong handoff from (2), we propose adaptive mode switching algorithm. HMIPv6 is employed for IP connectivity and mobility service in WLAN, which solves some shortcomings, such as high handoff overhead and vulnerable security. For routing in MANET, OLSR is employed, which is a proactive Protocol and has optimally reduced signal broadcasting overhead. OLSR operates with current P protocol compatibly with no change or modification. The proposed internetworking scheme based on adaptive mode switching algorithm shows better performance than scheme from (2).

• Korean Journal of Remote Sensing
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• v.35 no.5_1
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• pp.751-761
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• 2019

Mt. Baekdu, Mt. Aso, Mt. Sakurajima, Mt. Kikai and etc are distributed around the Korean Peninsula. Recently signs of eruption of Mt. Baekdu are increasing, raising concerns over possible damage to volcanic ash from seasonal winds during the winter eruption. Therefore, detailed procedures for investigation and countermeasures for volcanic ash spread and damage are required. But the standards for the warning and alarm signal of volcanic ash presented by Korea Ministry of Government Legislation are vague, with "when damage is expected" and "when serious damage is expected". In this study, to analyze the damage threshold and to apply the cases of overseas damage to the country, a survey was conducted on the establishment of domestic spatial information by public institutions with public confidence. As a result of the investigation of damage from volcanic ash overseas, the details of the damage cases were different depending on the type of life or income sources of each country. Therefore, instead of applying the volcanic ash damage cases abroad in Korea, spatial information analysis was performed to reflect domestic social and natural characteristics. In addition, we selected the areas to be considered in the event of volcanic ash damage in Korea. Finally, domestic volcanic ash damages should be classified as health, residential, road, railroad, aviation, power, water, agriculture, livestock, forest, and soil. When establishing the volcanic ash alarm optimized for Korea in the future, overseas volcanic ash damage cases and domestic spatial information construction in this study will be helpful in policy establishment.