• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.12
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• pp.1274-1285
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• 1991

This paper presents a statistical convergence analysis of the normalized least mean square(NLMS)algorithm that employs a single-pole lowpass filter, In this algorithm the lowpass filter is used to adjust its output towards the estimated value of the input signal power recursively. The estimated input signal power so obtained at each time is then used to normalize the convergence parameter. Under the assumption that the primary and reference inputs to the adaptive filter are zero mean wide sense stationary, and Gaussian random processes, and further making use of the independence assumption. we derive expressions that characterize the mean and maen squared behavior of the filter coefficients as well as the mean squared estimation error. Conditions for the mean and mean squared convergence are explored. Comparisons are also made between the performance of the NLMS algorithm and that of the popular least mean square(LMS) algorithm Finally, experimental results that show very good agreement between the analytical and emprincal results are presented.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.307-313
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• 2021

In this paper, a lightweight network with fewer parameters compared to the existing object detection method is proposed. In the case of the currently used detection model, the network complexity has been greatly increased to improve accuracy. Therefore, the proposed network uses EfficientNet as a feature extraction network, and the subsequent layers are formed in a pyramid structure to utilize low-level detailed features and high-level semantic features. An attention process was applied between pyramid structures to suppress unnecessary noise for prediction. All computational processes of the network are replaced by depth-wise and point-wise convolutions to minimize the amount of computation. The proposed network was trained and evaluated using the PASCAL VOC dataset. The features fused through the experiment showed robust properties for various objects through a refinement process. Compared with the CNN-based detection model, detection accuracy is improved with a small amount of computation. It is considered necessary to adjust the anchor ratio according to the size of the object as a future study.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.359-359
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• 2021

기후변화로 인한 강수량의 지역별, 계절별 불균형은 홍수로 인한 하천 범람피해뿐만 아니라 하천의 건천화로 인한 수생태, 수질, 경관 저해 등의 피해를 야기하고 있다. 이와 같은 기후변화로 인한 수자원의 영향을 평가하기 위해 기상 현상을 재현하고 예측하기 위한 기후모형과 이와 연계하여 지표의 수문 순환과 에너지 순환과정을 모의할 수 있는 지표수문모형의 필요성이 대두되고 있다. 그러나, 하천유출에 대한 모니터링시스템 체계를 구축하기 위해 지표수문모형을 사용하여 하천의 장기유출을 모의하는 시도는 국내에서는 아직 일반화되지 않고 있다. 따라서, 본 연구에서는 횡방향 유출흐름 모의가 가능하도록 개선된 격자형 지표수문모형인 Common Land Model(CoLM)의 우리나라 하천유역에 대한 장기하천유출 모의 적용성을 확인하고자 한다. 이를 위하여 4대강(한강, 낙동강, 금강, 섬진강)의 자연유역을 대상으로 주요 댐 상류유역에 대하여 CoLM이 필요로 하는 지표경계조건자료와 기상입력자료를 구축하고 모형의 주요 매개변수에 대한 검보정을 수행하여 각 지점별 최적의 장기하천유출 모의결과를 도출하고자 한다. CoLM의 지표경계조건자료 구축을 위해서는 고해상도의 인공위성자료 및 지점측정자료를 수집하고, 기상입력자료 구축을 위해서는 기상청에서 제공하는 기상자료를 수집하여, 모형의 계산시간 및 지역예보모델에 많이 사용되고 있는 공간해상도를 고려한 모형의 입력자료는 30km 계산 격자망 자료로 구축될 예정이다. CoLM의 모의성능 평가 및 결과분석을 위해 총 30년(1990-2019) 기간에 대한 모의결과 중, 초기 10년은 초기조건 수립을 위한 안정화 기간으로 제외하고, 다음 10년(2000~2009)은 보정기간으로 설정하고 마지막 10년(2010~2019)은 검정기간으로 설정하여 지표수문모형의 장기하천유출모의 적용성이 평가될 예정이다. 본 논문의 결과는 향후 우리나라 주요 유역에 대해 이상기후로 인한 하천 수자원 및 수생태의 영향을 분석하고, 하천의 건천화 대책 수립 등에 대한 기초정보를 제공할 수 있을 것이라 기대한다.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.4
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• pp.721-732
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• 2024

Species identification of zooplankton is the most basic process in understanding the marine ecosystem and studying global warming. In this study, we propose an convolutional neural network model that can classify females and males of three zooplankton at the species level. First, training data including morphological features is constructed based on microscopic images acquired by researchers. In constructing training data, a data argumentation method that preserves morphological feature information of the target species is applied. Next, we propose a convolutional neural network model in which features can be learned from the constructed learning data. The proposed model minimized the information loss of training image in consideration of high resolution and minimized the number of learning parameters by using the global average polling layer instead of the fully connected layer. In addition, in order to present the generality of the proposed model, the performance was presented based on newly acquired data. Finally, through the visualization of the features extracted from the model, the key features of the classification model were presented.

• Journal of the Korean Geophysical Society
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• v.3 no.3
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• pp.161-174
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• 2000

Bayesian inversion is a stable approach to infer the subsurface structure with the limited data from geophysical explorations. In geophysical inverse process, due to the finite and discrete characteristics of field data and modeling process, some uncertainties are inherent and therefore probabilistic approach to the geophysical inversion is required. Bayesian framework provides theoretical base for the confidency and uncertainty analysis for the inference. However, most of the Bayesian inversion require the integration process of high dimension, so massive calculations like a Monte Carlo integration is demanded to solve it. This method, though, seemed suitable to apply to the geophysical problems which have the characteristics of highly non-linearity, we are faced to meet the promptness and convenience in field process. In this study, by the Gaussian approximation for the observed data and a priori information, fast Bayesian inversion scheme is developed and applied to the model problem with electric well logging and dipole-dipole resistivity data. Each covariance matrices are induced by geostatistical method and optimization technique resulted in maximum a posteriori information. Especially a priori information is evaluated by the cross-validation technique. And the uncertainty analysis was performed to interpret the resistivity structure by simulation of a posteriori covariance matrix.

• Journal of the Korea Convergence Society
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• v.10 no.12
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• pp.337-343
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• 2019

The need for preparation for old life has been further increased due to the increase of the elderly population and changes in economic conditions today. The purpose of this study is to analyze the relationship between income instability and the degree of preparation for old life and satisfaction of current life. The key variables were extracted through prior study review. And the data collected through the survey were statistically analyzed with a structural equation model. The analysis found that the indirect effect of the current income risk on the satisfaction of current life through the preparation for old life had a significant negative effect under the statistically significant level of 0.05. However, it was found that the direct effects of current income risk on the satisfaction of current life were not statistically significant. An additional analysis was conducted by dividing the age, the number of dependents by two groups respectively. To summarize the results, preparation for old life played a significant role as a prerequisite for improving the satisfaction of current life. And the variability(risk) of current income played an important role in preparing for old life. At this time, the degree of relevance between the factors(potential variables) differed somewhat between the two groups. The results of this analysis will be meaningful in providing basic source of data to prepare for a satisfactory life in each individual's current situation. This study, meanwhile, has limitations that have only been done with cross-sectional analysis and would like to analyze time-series changes in the future.

• Proceedings of the Korean Society of Organic Agriculture Conference
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• 2009.12a
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• pp.299-299
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• 2009

유기농업에서 유기자원을 이용하여 적정량의 양분을 공급하기 위해서는 먼저 유기자원의 무기화특성을 고려하여야 한다. 토성, 기온, 재배형태 등 다양한 요인을 고려하면서 무기화모델을 이용하여 유기농업에서 많이 사용되고 있는 유기질비료와 작물잔사 등을 대상으로 잠재 무기화가능 질소량(PMN, Potentially mineralizabe nitrogen)을 추정하였다. 실험은 실내에서 항온 배양하여 유기자원별 질소 무기화 양상을 분석함으로서 대상 유기자원의 PMN 및 무기화 속도를 도출하였다. 실험재료는 팜박, 피마자박, 팽화왕겨, 토마토, 수박, 감자, 마늘 등 7종을 대상으로 $20^{\circ}C,\;25^{\circ}C,\;30^{\circ}C$ 조건에서 하였으며, 최대수분보유량의 60% 수준으로 하여 사양토 및 식양토 조건에서 실험하였다. 유기자원은 토양 100g에 질소 30kg/10a 해당량을 시용하여 112일까지 항온하였다. 토성별 무기화량은 식양토 보다 사양토에서 다소 높은 경향을 보였다. 또한 항온온도가 높을수록 무기화량이 증가하였다. 유기자원별로는 피마자박에서 높았고, 팽화왕겨는 낮은 경향이었다. 유기자원이 처리된 것에서 토양 자체의 무기화량을 뺀 순무기화량은 피마자박, 토마토잔사, 감자잔사가 항온초기부터 무기화가 진행되었으며, 수박잔사, 마늘잔사는 항온 초기에 음의 값을 가지는 유기화 과정을 거친 후 항온 60일에서 80일 사이에서 무기화가 진행되었고 팽화왕겨의 경우 항온 11일까지 유기화가 계속되었다. PMN 및 무기화속도를 추정하기 위하여 반응속도식을 이용하였으며, 모델의 적합도를 높이기 위하여 이중지수모형을 이용하여 매개변수를 결정하고 무기화경향을 예측한 결과 PMN은 피마자박>마늘잔사=팜박>수박잔사=토마토잔사>감자잔사의 순이었다. 또한 유기자원의 무기화량과 C/N율과는 부의 상관관계($r^2$=0.8653)를 나타내었다. 요소의 PMN(135.6mg/kg)에 대한 유기자원별 PMN의 상대적 비율은 피마자박이 100%, 팜박과 마늘잔사가 81%, 토마토, 수박 및 감자잔사가 28~65% 수준이었다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.10
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• pp.1925-1934
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• 1994

In this paper, it was studied the method of performance improvement of trellis encoded 4-ray continuous phase FSK with nonconstant frequency space when permitted complexity. It was used the nonconstant mapper in order to produce nonconstant frequency, fixed maximum symbol values 3, -3 for comparision in similar bandwidth, changed symbol values 1, -1 from 0.5 to 3.0 as symmetry. Free Euclidean distance evaluation of all encoder/nonconstant mapper combinations, which is the parameter of performance of error probability, was performed with the trellis-based algorithm, we analyzed the characteristics of those.

• The Transactions of the Korea Information Processing Society
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• v.5 no.11
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• pp.2884-2896
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• 1998

For on-line signature verification, the local shape of a signature is an important information. The current approaches, in which signatures are represented into a function of time or a feature vector without regarding of local shape, have not used the various features of local shapes, for example, local variation of a signer, local complexity of signature or local difficulty of forger, and etc. In this paper, we propose a new technique for on-line signature verification based on a structural signature representation so as to analyze local shape and to make a selection of important local parts in matching process. That is. based on a structural representation of signature, a technique of important of local weighting and personalized decision threshold is newly introduced and its experimental results under different conditions are compared.

• Journal of Environmental Science International
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• v.2 no.3
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• pp.193-199
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• 1993

This study has two objectives. One is developing the runoff model for Hoe-Dong Reservoir basin located at the upstream of Su-Young River in Pusan. To develop the runoff model, basic hydrological parameters - curve number to find effective rainfall, and storage coefficient, etc. - should be estimated. In this study, the effective rainfall was calculated by the SCS method, and the storage coefficient used in the Clark watershed routing was cited from the report of P.E.B. The other is the derivation of transfer function for Hoe-Dong Reservoir basin. The linear, discrete, input-output model which contained six parameters was selected, and the parameters were estimated by the least square method and the correlation function method, respectively. Throughout this study, rainfall and flood discharge data were based on the field observation in 1981.8.22 - 8.23 (typhoon Gladys). It was observed that the Clark watershed routing regenerated the flood hydrograph of typhoon Gladys very well, and this fact showed that the estimated hydrological parameters were relatively correct. Also, the calculated hydrograph by the linear, discrete, input-output model showed good agreement with the regenerated hydrograph at Hoe-Dong Dam site, so this model can be applicable to other small urban areas. Key Words : runoff, effective rainfall, SCS method, clark watershed iou상ng, hydrological parameters, parameter estimation, least square method, correlation function method, input-output model, typhoon gladys.