• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.11
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• pp.1-10
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• 2007

In this paper, we proposed channel estimation scheme for LR-UWB system which has low data rate for WPAN in IEEE 802.15.4a. At the transmitter, we proposed dynamic power level allocation depends on channel condition in specific period when we modulate signal. We use two orthogonal code to estimate channel at once. It can estimate channel more accurately by using two code which shows good correlation characteristic then it can estimate more accurately by spreading gain. Using estimated channel condition, we synchronize symbol timing of transmitted signal. Then determined power allocation scheme and channel information is transmitted to transmiter side. Finally, using these information, transmiter side change the power level of repeated pulse to adopt to channel condition. Simulation is performed under S-V channel for LR-WPAN in IEEE 802.15.4a and we compare the performance with a different type of receiver type. We use coherent and non-coherent method at the receiver. Simulation result shows us at the NLOS channal performance evaluation is greater than that of LOS channel and the result is independent of receiver type. In the NLOS channel, as the signal delay spreading is big, performance evaluation is also increased.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.4
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• pp.395-403
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• 2016

This paper introduces a multi-cell search method for heterogeneous networks (HetNet), in which user equipments need to search multiple cells in its vicinity simultaneously. Due to the difficulty of acquiring channel informations for multiple cells, a non-coherent approach is preferred. In this paper, a non-coherent single-cell search scheme using a weighted vector is proposed, and the successive interference cancellation based multi-cell search algorithm is devised. In order to improve cell search performance, the weighted vector is designed in a way to exploit the general characteristic of wireless channel. Based on the fact that the performance of the proposed single-cell search scheme deviates slowly from the one using the optimal weighted vector, a universal weighted vector is also proposed, which shows the performance close to the optimal ones for various channel environments and signal-to-noise ratio regimes. Simulation results confirm that the proposed multi-cell search algorithm is capable of identifying cells more accurately with the help of the proposed single-cell search scheme, and can detect the remaining cells more effectively by removing the signals of the identified cells from the received signal.

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.777-783
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• 2004

하천 세내지 주변은 급속한 시가지 조성과 인구밀집으로 유역의 불투수층이 증가하여 홍수도달시간이 짧아지고 홍수유출량이 증가하고 있다. 또한 엘리뇨${\cdot}$라니냐 등의 이상기후로 홍수사상의 발생 빈도와 규모가 증가하면서 홍수피해도 대형화되어 가고 있다. 그러나 치수사업은 다른 공공사업에 비해 경제성이 저평가 되어 투자우선순위가 밀려 사업시행이 지연되고 예방적 차원의 대책도 미흡하여 피해가 증가하는 악순환이 계속되고 있다. 따라서 본 인구에서는 우리나라의 치수경제성 분석에 있어 계량화하지 못하고 있는 자산이용고도화 효과를 치수안전도와 더불어 분석하고자 한다. 자산이용고도화는 치수사업 시행으로 해당지역의 치수안전도 향상에 따른 자산가치의 상승을 말하는데, 특정지역의 자산가치를 가장 객관적으로 표현할 수 있는 공시지가를 근거로 분석을 수행하였다. 치수사업 시행으로 인한 편익과 하천 특성에 따른 지가변동률의 차이가 통계적으로 유의성이 있는지를 분산분석을 통해 검증하였으면, 자산가치의 상승을 순수 연평균지가변동률로 나타내었다. 치수안전도는 홍수피해 잠재성과 홍수방어능력으로 구분하였는데 홍수피해 잠재성은 도시화율에 따라 구분하였고, 홍수방어능력은 홍수량의 빈도해석과 불확실성을 고려하여 조건부 비초과확률로 나타내었다. 본 연구에서는 소도시 지역(경안천, 복하천, 청미천)을 대상으로 200년 빈도의 홍수사상에 내해 10년, 50년 설계빈도로 건설된 제방의 조건부 비초과확률을 산정하여 지가변동률의 추이를 비교 분석하였다. 분석 결과, 소도시 지역에서는 조건부 비초과확률이 $10\%$ 상승했을 때 순수 연평균지가변동률이 5배정도 상승함을 알 수 있었다.다시 입력자료로 사용하는 업데이트 방식을 사용하기 때문에 예측결과의 오차가 완전하게 보정되지 않으면 다음 결과에 역시 오차를 주게 되어 오차보정이 상당히 중요하다는 것을 알 수 있었다. 오차를 보다 효과적으로 보정하기 위해서는 퍼지제어에 사용되는 퍼지규칙의 수를 늘리고, 유입량에 직접적인 영향을 주는 강우량과 연계한 2변수의 Fuzzy-Grey 모형을 이용한다면 보다 정확한 유입량 예측이 가능할 것으로 사료된다.이 작은 오차를 발생하였으며, 전체적으로 퍼프 모형이 입자모형보다는 훨씬 적은 수의 계산을 통해서도 작은 오차를 나타낼 수 있다는 것을 알 수 있었다. 그러나 Gaussian 분포를 갖는 퍼프모형은 전단흐름에서의 긴 유선형 농도분포를 모의할 수 없었고, 이에 관한 오차는 전단계수가 증가함에 따라 비선형적으로 증가하였다. 향후, 보다 다양한 흐름영역에서 장${\cdot}$단점 분석 및 오차해석을 수행한 후에 각각의 Lagrangian 모형의 장점만을 갖는 모형결합 방법을 제시할 수 있을 것으로 판단된다.mm/$m^{2}$로 감소한 소견을 보였다. 승모판 성형술은 전 승모판엽 탈출증이 있는 두 환아에서 동시에 시행하였다. 수술 후 1년 내 시행한 심초음파에서 모든 환아에서 단지 경등도 이하의 승모판 폐쇄 부전 소견을 보였다. 수술 후 조기 사망은 없었으며, 합병증으로는 유미흉이 한 명에서 있었다. 술 후 10개월째 허혈성 확장성 심근증이 호전되지 않아 Dor 술식을 시행한 후 사망한 예를 제외한 나머지 6명은 특이 증상 없이 정상 생활 중이다 결론: 좌관상동맥 페동맥이상 기시증은 드물기는 하나, 영유아기에 심근경색 및 허혈성 심근증 또는 선천성 승모

• Journal of Environmental Impact Assessment
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• v.27 no.3
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• pp.251-266
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• 2018

This study predicted the effect of operation pattern of flood control dam on water quality. Flood control dam temporarily impound floodwaters and then release them under control to the river below the dam preventing the river ecosystem from the extreme flood. The Hydrological Simulation Program Fortran (HSPF) and the Environmental Fluid Dynamics Code (EFDC) were adapted to predict the water quality before and after the dam construction in the proposed reservoir. The non-point pollutant delivery load from the river basin was estimated using the HSPF, and the EFDC was used to predict the water quality using the provided watershed boundary conditions from the HSPF. As a result of water quality simulation, it is predicted that the water quality will be improved due to the decrease of pollution source due to submergence after dam construction and temporary storage during rainfall. There would be no major water quality issues such as the eutrophication in the reservoir since the dam would impound the floodwater for a short time (2~3 days). In the environmental impact assessment stage of a planned dam, there may be some limitations to the exact simulation because the model can not be sufficiently calibrated. However, if the reliability of the model is improved through the acquisition of actual data in the future, it will be possible to examine the influence of the water environment according to various operating conditions in the environmental impact assessment of the new flood control dam.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.128-128
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• 2023

우리나라 농업용 저수지는 저수량만을 참조하여 운영한다. 이러한 현실을 개선하기 위해, 유입량을 고정시키고 저수지 물수지 분석에 의해 방류량을 생산하는 체계를 구축했다. 2018년부터 2021년까지 총저수량 142만m³의 옥서저수지, 106만m³의 홍동저수지에 적용하여 일별로 저수량을 모의하여 관측값과 비교하고, 저수지 물수지 분석에 의해 실시간 계측되는 수로유량의 신뢰도를 평가하였다. 장기간의 계측 자료를 보유하고 있는 인근 다목적댐인 보령댐의 운영자료(2018~2021)를 이용하여 유입량 모형의 매개변수(α=3.500)를 결정하고, 저수지 유입량을 모의한 결과 NSE 0.854, R² 0.858의 높은 신뢰도를 얻었다. 유입량을 고정시키고, 저수지 물수지 분석에 의해 방류량을 계산한 결과 옥서저수지는 일최대 방류량 5.7m³/s, 일평균 0.2m³/s, 홍동저수지는 각각 5.9m³/s, 0.2m³/s로 나타났다. 총방류량을 측정 수로유량과 여수로 방류량으로 분할하고, 저수지 물수지 분석에 의해 수로유량의 신뢰도를 평가한 결과 옥서저수지는 R²가 0.771, 일평균 저수위 오차 88.6cm, 일평균 저수량 오차 9.4%, 홍동저수지는 R²가 0.086, 일평균 저수위 오차 69.9cm, 일평균 저수량 오차 18.0%로 오차가 크게 나타났다. 저수지 수위가 만수위(FWL) 이하일 때는 여수로 방류량을 0으로 하여 총방류량을 여수로 방류량과 수로유량으로 분할한 후, 물수지 분석에 의해 신뢰도를 평가한 결과, 옥서저수지의 경우 R²는 0.941, 일평균 저수위 오차 2.6cm, 일평균 저수량 오차 0.35%를 나타내, 신뢰도가 크게 증가했다. 그러나 홍동저수지의 경우는 R²는 0.521, 일평균 저수위 오차 2.2cm, 일평균 저수량 오차1.02%를 나타냈지만, 낮은 신뢰도를 보였다. 측정 수로유량의 신뢰도는 두 저수지 모두 낮게 나타났다. 수로유량 조정을 통해 옥서저수지의 신뢰도는 향상 시킬 수 있었지만 홍동저수지의 경우는 향상 시킬 수 없었다. 이는 여수토 비상수문조작 실적과 저수지 사통 수문 조작 실적이 없어, 그 결과를 정확히 반영할 수 없었기 때문인 것으로 결론을 내렸다.

• Journal of the Korean Society of Radiology
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• v.18 no.3
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• pp.187-201
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• 2024

Osteoporosis is a major health issue globally, often remaining undetected until a fracture occurs. To facilitate early detection, deep learning (DL) models were developed to classify osteoporosis using abdominal computed tomography (CT) scans. This study was conducted using retrospectively collected data from 3,012 contrast-enhanced abdominal CT scans. The DL models developed in this study were constructed for using image data, demographic/clinical information, and multi-modality data, respectively. Patients were categorized into the normal, osteopenia, and osteoporosis groups based on their T-scores, obtained from dual-energy X-ray absorptiometry, into normal, osteopenia, and osteoporosis groups. The models showed high accuracy and effectiveness, with the combined data model performing the best, achieving an area under the receiver operating characteristic curve of 0.94 and an accuracy of 0.80. The image-based model also performed well, while the demographic data model had lower accuracy and effectiveness. In addition, the DL model was interpreted by gradient-weighted class activation mapping (Grad-CAM) to highlight clinically relevant features in the images, revealing the femoral neck as a common site for fractures. The study shows that DL can accurately identify osteoporosis stages from clinical data, indicating the potential of abdominal CT scans in early osteoporosis detection and reducing fracture risks with prompt treatment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.3
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• pp.639-648
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• 2017

Electronic warfare systems for extracting information of the threat signals can be employed under the circumstance where the power of the received signal is weak. To precisely and rapidly detect the threat signals, it is required to use methods exploiting whole energy of the received signals instead of conventional methods using a single received signal input. To utilize the whole energy, numerous sizes of windows need to be implemented in a detector for dealing with all possible unknown length of the received signal because it is assumed that there is no preliminary information of the uncooperative signals. However, this grid search method requires too large computational complexity to be practically implemented. In order to resolve this complexity problem, an approach that reduces the number of windows by selecting the smaller number of representative windows can be considered. However, each representative window in this approach needs to cover a certain amount of interval divided from the considering range. Consequently, the discordance between the length of the received signal and the window sizes results in degradation of the detection performance. Therefore, we propose the weighted energy detector which results in improved detection performance comparing with the conventional energy detector under circumstance where the window size is smaller than the length of the received signal. In addition, it is shown that the proposed method exhibits the same performance under other circumstances.

• Journal of KIISE:Software and Applications
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• v.33 no.5
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• pp.508-524
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• 2006

We present our experience of combining, in a realistic setting, a static analyzer with a statistical analysis. This combination is in order to reduce the inevitable false alarms from a domain-unaware static analyzer. Our analyzer named Airac(Array Index Range Analyzer for C) collects all the true buffer-overrun points in ANSI C programs. The soundness is maintained, and the analysis' cost-accuracy improvement is achieved by techniques that static analysis community has long accumulated. For still inevitable false alarms (e.g. Airac raised 970 buffer-overrun alarms in commercial C programs of 5.3 million lines and 737 among the 970 alarms were false), which are always apt for particular C programs, we use a statistical post analysis. The statistical analysis, given the analysis results (alarms), sifts out probable false alarms and prioritizes true alarms. It estimates the probability of each alarm being true. The probabilities are used in two ways: 1) only the alarms that have true-alarm probabilities higher than a threshold are reported to the user; 2) the alarms are sorted by the probability before reporting, so that the user can check highly probable errors first. In our experiments with Linux kernel sources, if we set the risk of missing true error is about 3 times greater than false alarming, 74.83% of false alarms could be filtered; only 15.17% of false alarms were mixed up until the user observes 50% of the true alarms.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.1_2
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• pp.15-34
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• 2006

This paper introduces an empirical modeling technique. This technique uses a set of sample results which are collected from a few small scale simulations. Empirical models are developed by applying a couple of statistical estimation techniques to these samples. We built two types of models for cache miss rates in Symmetric Multiprocessor systems. One is for the changes of input data set size while the specification of target system is fixed. The other is for the changes of the number of processors in target system while the input data set size is fixed. To develop accurate models, we built individual model for every kind of cache misses for each shared data structure in a program. The final model is then obtained by integrating them. Besides, combined use of Least Mean Squares and Robust Estimations enhances the quality of models by minimizing the distortion due to outliers. Empirical modeling technique produces extremely accurate models without analysis on sample data. In addition, since only snail scale simulations are necessary, once a set of samples can be collected, empirical method can be adopted in any research areas. In 17 cases among 24 trials, empirical models present extremely low prediction errors below $1\%$. In the remaining cases, the accuracy is excellent, as well. The models sustain high quality even when the behavioral characteristics of programs are irregular and the number of samples are barely enough.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.8
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• pp.628-635
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• 2017

It is important to prescribe and take medicines that are appropriate for symptoms, since medicines are closely related to human health and life. Moreover, it becomes more important to accurately classify genuine medicines with counterfeit, since the number of counterfeit increases worldwide. However, the number of high-quality experts who have enough experience to properly classify them is limited and there exists a need for the automatic technique to classify medicine tablets. In this paper, we propose a method to classify the tablets by using a handheld spectrometer which provides both Near Infra-Red (NIR) and visible light spectrums. We adopted Support Vector Machine(SVM) as a machine learning algorithm for tablet classification. As a result of the simulation, we could obtain the classification accuracy of 99.9 % on average by using both NIR and visible light spectrums. Also, we proposed a two-step SVM approach to discriminate the counterfeit tablets from the genuine ones. This method could improve both the accuracy and the processing time.