• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.13-19
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• 2008

A Wire-woven Bulk Kagome (WBK) is the new truss type cellular metal fabricated by assembling the helical wires in six directions. The WBK seems to be promising with respect to morphology, fabrication cost, and raw materials. In this paper, first, the geometric and material properties are defined as the main design parameters of the WBK considering the fact that the failure of WBK is caused by buckling of truss elements. Taguchi approach was used as statistical design of experiment(DOE) technique for optimizing the design parameters in terms of maximizing the compressive strength. Normalized specific strength is constant regardless of slenderness ratio even if material properties changed, while it increases gradually as the strainhardening coefficient decreases. Compressive strength of WBK dominantly depends on the slenderness ratio rather than one of the wire diameter, the strut length. Specifically the failure of WBK under compression by elastic buckling of struts mainly depended on the slenderness ratio and elastic modulus. However the failure of WBK by plastic failed marginally depended on the slenderness ratio, yield stress, hardening and filler metal area.

• 소성∙가공
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• 제29권4호
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• pp.218-228
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• 2020

The prediction of final mass and optimized process conditions of injection molded products using Artificial Neural Network (ANN) were demonstrated. The ANN was modeled with 10 input parameters and one output parameter (mass). The input parameters, i.e.; melt temperature, mold temperature, injection speed, packing pressure, packing time, cooling time, back pressure, plastification speed, V/P switchover, and suck back were selected. To generate training data for the ANN model, 77 experiments based on the combination of orthogonal sampling and random sampling were performed. The collected training data were normalized to eliminate scale differences between factors to improve the prediction performance of the ANN model. Grid search and random search method were used to find the optimized hyper-parameter of the ANN model. After the training of ANN model, optimized process conditions that satisfied the target mass of 41.14 g were predicted. The predicted process conditions were verified through actual injection molding experiments. Through the verification, it was found that the average deviation in the optimized conditions was 0.15±0.07 g. This value confirms that our proposed procedure can successfully predict the optimized process conditions for the target mass of injection molded products.

• 한국지반공학회지:지반
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• 제8권4호
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• pp.17-30
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• 1992

연약한 점토지반에서는, 정규압밀상태와 더불어 미약한 과압밀상태에서의 구성관계가 실제 지반구조물의 거동을 해석하는 데 중요한 역할을 한다. 미약한 과압밀상태의 거동에 실용적으로 적용될 수 있는 구성모델은 비교적 간편한 계수만을 사용하여 실제의 다양한 거동을 정확하게 예측할 수 있도록 개발되어야 한다. 이러한 연유로 본 연구에서는 등가응력 (자)으로규준화하였을 때 나타나는 지반의 비 배수거동을 재현하여 미약한 과압밀상태에 적용할 수 있는 구성모델을 제안하였다. 제안된 모델은 단지 정규압밀상태의 거동으로 도출할 수 있는 모델계수만을 사용하여 초기항복면내부에서 발생하는 항복현상을 표현할 수 있다. 뿐만아니라 제안된 모델은 과압밀상태, 2차압밀, 응력이완등의 영향에 따른 실제의 거동을 기존의 모델들에 비하여 더욱 간편하고 정확하게 예측할 수 있다.

• 대한원격탐사학회지
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• 제34권1호
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• pp.127-139
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• 2018

The GOCI atmospheric correction overland surfaces is essential for the time-series analysis of terrestrial environments with the very high temporal resolution. We develop an operational GOCI atmospheric correction method over land surfaces, which is rather different from the one developed for ocean surface. The GOCI atmospheric correction method basically reduces gases absorption and Rayleigh and aerosol scatterings and to derive surface reflectance from at-sensor radiance. We use the 6S radiative transfer model that requires several input parameters to calculate surface reflectance. In the sensitivity analysis, aerosol optical thickness was the most influential element among other input parameters including atmospheric model, terrain elevation, and aerosol type. To account for the highly variable nature of aerosol within the GOCI target area in northeast Asia, we generate the spatio-temporal aerosol maps using AERONET data for the aerosol correction. For a fast processing, the GOCI atmospheric correction method uses the pre-calculated look up table that directly converts at-sensor radiance to surface reflectance. The atmospheric correction method was validated by comparing with in-situ spectral measurements and MODIS reflectance products. The GOCI surface reflectance showed very similar magnitude and temporal patterns with the in-situ measurements and the MODIS reflectance. The GOCI surface reflectance was slightly higher than the in-situ measurement and MODIS reflectance by 0.01 to 0.06, which might be due to the different viewing angles. Anisotropic effect in the GOCI hourly reflectance needs to be further normalized during the following cloud-free compositing.

• 한국정보통신학회논문지
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• 제14권4호
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• pp.959-966
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• 2010

정량적 초음파 분석(Quantitative Ultrasound Analysis)은 반향된 초음파 신호의 짧은 시간 간격의 주파수 성분을 추출하여 개별 초음파 지수의 값을 예측한다. 따라서 반향 신호의 정확한 주파수 특성 추출은 분석의 정확도와 정밀도 향상에 기본이 된다. 본 논문에서는 초음파 지수의 정량적인 예측 및 분석에 이용할 수 있는, 짧은 시간 간격의 반향 신호의 주파수 특성 추출 방법을 제안한다. 제안된 알고리듬은 인접한 반향 초음파 신호간의 위상 차이를 보상하고, 동일 반향 깊이를 가지는 작은 영역의 신호를 가중치 평균함으로써 보다 정확한 주파수 특성을 추출한다. 컴퓨터 모의 실험을 통한 수치 분석 결과, 제안된 알고리듬은 일반적인 주파수 추출 알고리듬보다 정확한 예측 결과를 보였으며, 예측 결과의 정밀도도 10% 이상 향상되었다.

• 한국토양비료학회지
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• 제50권5호
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• pp.409-421
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• 2017

Recently Unmanned Aerial Vehicle (UAV) technology offers new opportunities for assessing crop growth condition using UAV imagery. The objective of this study was to select optimal vegetation indices and regression model for estimating of rice growth using UAV images. This study was conducted using a fixed-wing UAV (Model : Ebee) with Cannon S110 and Cannon IXUS camera during farming season in 2016 on the experiment field of National Institute of Crop Science. Before heading stage of rice, there were strong relationships between rice growth parameters (plant height, dry weight and LAI (Leaf Area Index)) and NDVI (Normalized Difference Vegetation Index) using natural exponential function ($R{\geq}0.97$). After heading stage, there were strong relationships between rice dry weight and NDVI, gNDVI (green NDVI), RVI (Ratio Vegetation Index), CI-G (Chlorophyll Index-Green) using quadratic function ($R{\leq}-0.98$). There were no apparent relationships between rice growth parameters and vegetation indices using only Red-Green-Blue band images.

• 센서학회지
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• 제25권6호
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• pp.431-434
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• 2016

Currently, the radial basis function network (RBFN) and various other neural networks are employed to classify gases using chemical sensors arrays, and their performance is steadily improving. In particular, the identification performance of the RBFN algorithm is being improved by optimizing parameters such as the center, width, and weight, and improved algorithms such as the radial basis function network-stochastic gradient (RBFN-SG) and radial basis function network-normalized stochastic gradient (RBFN-NSG) have been announced. In this study, we optimized the number of centers, which is one of the parameters of the RBFN-NSG algorithm, and observed the change in the identification performance. For the experiment, repeated measurement data of 8 samples were used, and the elbow method was applied to determine the optimal number of centers for each sample of input data. The experiment was carried out in two cases(the only one center per sample and the optimal number of centers obtained by elbow method), and the experimental results were compared using the mean square error (MSE). From the results of the experiments, we observed that the case having an optimal number of centers, obtained using the elbow method, showed a better identification performance than that without any optimization.

• 환경영향평가
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• 제21권1호
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• pp.161-169
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• 2012

Recently various attempts have been made to apply HSPF model to calculate runoff and diffuse pollution loads of stream and reservoir watersheds. Because the role of standard flow is very important in the water quality modelling of Total Water Pollution Load Management, HSPF was used as a means of estimating standard flow. In this study, BASINS 4.0 and WinHSPF was applied to the Gomakwoncheon watershed, genetic algorithm(GA) and influence coefficient algorithm were used to calibrate the runoff parameters of the WinHSPF. The objective function is the sum of the squares of the normalized residuals of the observed and calculated flow and it is optimized using GA. Estimates of the optimum runoff parameters are made at each iteration of the influence coefficient algorithm. The calibration results showed a relatively good correspondence between the observed and the calculated values. The standard flow(Q275) of the Gomakwoncheon watershed was estimated using the ten years of weather data.

• Journal of Information Processing Systems
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• 제10권4호
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• pp.503-522
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• 2014

In the cursive handwriting recognition process, script trajectory segmentation and modeling represent an important task for large or open lexicon context that becomes more complicated in multi-writer applications. In this paper, we will present a developed system of Arabic online handwriting modeling based on graphemes segmentation and the extraction of its geometric features. The main contribution consists of adapting the Fourier descriptors to model the open trajectory of the segmented graphemes. To segment the trajectory of the handwriting, the system proceeds by first detecting its baseline by checking combined geometric and logic conditions. Then, the detected baseline is used as a topologic reference for the extraction of particular points that delimit the graphemes' trajectories. Each segmented grapheme is then represented by a set of relevant geometric features that include the vector of the Fourier descriptors for trajectory shape modeling, normalized metric parameters that model the grapheme dimensions, its position in respect to the baseline, and codes for the description of its associated diacritics.

• The Korean Journal of Physiology and Pharmacology
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• 제23권6호
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• pp.467-474
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• 2019

Exposure to lead during pregnancy is a risk factor for the development of psychiatric disorders in the offspring. In this study, we investigated whether exposure to low levels of lead acetate (0.2%) in drinking water during pregnancy and lactation causes behavioral impairment and affects the expression of proteins associated with neurodevelopment. Lead exposure altered several parameters in rat offspring compared with those unexposed in open-field, social interaction, and pre-pulse inhibition tests. These parameters were restored to normal levels after clozapine treatment. Western blot and immunohistochemical analyses of the hippocampus revealed that several neurodevelopmental proteins were downregulated in lead-exposed rats. The expression was normalized after clozapine treatment (5 mg/kg/day, postnatal day 35-56). These findings demonstrate that downregulation of several proteins in lead-exposed rats affected subsequent behavioral changes. Our results suggest that lead exposure in early life may induce psychiatric disorders and treatment with antipsychotics such as clozapine may reduce their incidence.