• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.11 no.11
• /
• pp.4121-4128
• /
• 2010

A probe card is used in testing semiconductor wafers. It must maintain a precise location tolerance for a fine pitch due to highly densified chips. However, high heat transferred from its lower chuck causes thermal deformations of the probe card. Vertical deformation due to the heat will bring contact problems to the pins in the probe card, while horizontal deformation will cause positional inaccuracies. Therefore, probe cards must be designed with proper materials and structures so that the thermal deformations are within allowable tolerances. In this paper, heat transfer analyses under realistic loading conditions are simulated using ANSYS$^{TM}$ finite element analysis program. Thermal deformations are calculated based on steady-state temperature gradients, and an optimal structure of the probe card is proposed by adjusting a set of relevant design parameters so that the deformations are minimized.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.10 no.9
• /
• pp.2369-2378
• /
• 2009

In this paper, we implement measurement functionality for performance measurement of the GSM (Global System for Mobile Communication) terminal by using software. Generally speaking, the receiving algorithms in normal modems cannot be used directly to the measurement system due to the lack of the algorithm accuracy. In this paper, we propose the new receiver algorithm for precise GSM signal measurements. In the receiving algorithm, 2-stage (coarse stage, fine stage) parameters estimation (symbol-timing, frequency offset, carrier phase) scheme is used. To improve the estimation accuracy, we increase the number of the received signal samples by interpolation. The proposed GSM signal measurement algorithm can be used for verifying the hardware measurement system. In addition, the proposed algorithm can be used for the commercial system through code execution speed optimization.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.27 no.1
• /
• pp.22-28
• /
• 2017

The Convolutional Neural Network(CNN) can be divided into two stages: feature extraction and classification. The hyperparameters such as kernel size, number of channels, and stride in the feature extraction step affect the overall performance of CNN as well as determining the structure of CNN. In this paper, we propose a method to optimize the hyperparameter in CNN feature extraction stage using Parameter-Setting-Free Harmony Search (PSF-HS) algorithm. After setting the overall structure of CNN, hyperparameter was set as a variable and the hyperparameter was optimized by applying PSF-HS algorithm. The simulation was conducted using MATLAB, and CNN learned and tested using mnist data. We update the parameters for a total of 500 times, and it is confirmed that the structure with the highest accuracy among the CNN structures obtained by the proposed method classifies the mnist data with an accuracy of 99.28%.

• Korean Journal of Chemical Engineering
• /
• v.35 no.12
• /
• pp.2336-2347
• /
• 2018

The azeotrope of methyl acetate methanol and water was isolated using extractive distillation with water as entrainer. The pressure-swing extractive distillation (PSED) process and vapor side-stream distillation column (VSDC) with the rectifier process were designed to separate the methyl acetate, methanol and water mixture. It was revealed that the VSDC with the rectifier process had a reduction in energy consumption than the PSED process. Four control schemes of the two process were investigated: Double temperature control scheme (CS1), $Q_R/F$ feedforward control of reboiler duty scheme for PESD (CS2), $Q_R/F$ feedback control scheme for VSDC (CS3), the feedback control scheme of sensitive plate temperature of side-drawing distillation column to dominate the compressor shaft speed (CS4). Feed flow and composition disturbance were used to evaluate the dynamic performance. As a result, CS4 is a preferable choice for separation of methyl acetate-methanol-water mixture. A control scheme combining the operating parameters of dynamic equipment with the control indicators of static equipment was proposed in this paper. It means using the sensitive plate temperature of side-drawing column to control the compressor shaft speed. This is a new control scheme for extractive distillation.

• Korean Journal of Remote Sensing
• /
• v.15 no.3
• /
• pp.195-208
• /
• 1999

In the classification of satellite images, the representative of training of classes is very important factor that affects the classification accuracy. Hence, in order to improve the classification accuracy, it is required to optimize pre-classification stage which determines classification parameters rather than to develop classifiers alone. In this study, the normality of training are calculated at the preclassification stage using SPOT XS and LANDSAT TM. A correlation coefficient of multivariate Q-Q plot with 5% significance level and a variance of initial training are considered as an object function of genetic algorithm in the training normalization process. As a result of normalization of training using the genetic algorithm, it was proved that, for the study area, the mean and variance of each class shifted to the population, and the result showed the possibility of prediction of the distribution of each class.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2018.05a
• /
• pp.208-208
• /
• 2018

본 연구에서는 비슬산 강우레이더 관측반경 내 표준유역별 정규화오차 정확도를 이용하여 강우량, 유역특성 등 강우레이더 관측의 수문학적 평가요소와의 상관 특성을 분석하였다. 이를 분석하면 강우레이더 관측 오차 또는 정확도가 수문학적 특성에 따라 얼마나, 어떻게 발생하는지를 추정할 수 있고, 이를 이용하여 홍수예보에 활용되는 입력 자료의 오차를 유역단위로 명확히 정량화 할 수 있어 보다 정확하고 신뢰도 높은 홍수예보에 도움이 될 것으로 기대된다. 강수량 크기와 강수추정 정확도 간의 상관 특성을 분석하기 위해 표준유역 평균 최대 강수량과 강수추정 정확도 간의 분포특성을 분석하였다. 단기간의 자료를 분석하여 오차특성을 정규화 하기는 매우 어렵기 때문에 본 연구에서는 비슬산 강우레이더로 관측된 2012년에서 2016년(5년)사이의 236개 강우사상에 대하여, 동기간의 기상청 AWS 지점 강우량을 기준으로 비슬산 강우레이더의 정규화오차 정확도(1-NE)를 산정한 후 이를 이용하여 850개 표준유역 별 유역평균 정규화오차 정확도를 재산정 하였다. 분석결과 표준유역 평균 최대강수량과 정규화오차 정확도 간에는 유의한 상관성이 있는 것으로 나타났다. 표준유역 평균 최대강수량의 크기에 따라 정규화오차 정확도가 상대적으로 일정한 경향이 나타났고 후처리 단계에서의 편파변수 최적화 이후에는 레이더 강수추정의 정규화오차 정확도가 표준유역 평균 최대강수량 크기에 상관없이 일정해 지는 것으로 나타났다. 따라서 이러한 일정한 레이더 강수추정의 정규화오차 정확도는, 편파변수 최적화에 의해 관측 가능한 최대 기대 정확도 수준 도달에 도달했다고 볼 수 있으며, 표준유역에서 강우레이더의 강수추정 기대 정확도 수준은 84%(정규화오차 16%에 해당) 정도로 추정되었다.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2017.05a
• /
• pp.191-191
• /
• 2017

Floods have become more widespread and frequent among natural disasters and consisted significant losses of lives and properties worldwide. Flood's impacts are threatening socio-economic and people's lives in the Mekong River Basin every year. The objective of this study is to identify the flood hazard areas and inundation depth in the Mekong River Basin. A rainfall-runoff and flood inundation model is necessary to enhance understanding of characteristic of flooding. Rainfall-Runoff-Inundation (RRI) model, a two-dimensional model capable of simulating rainfall-runoff and flood inundation simultaneously, was applied in this study. HydoSHEDS Topographical data, APPRODITE precipitation, MODIS land use, and river cross section were used as input data for the simulation. The Shuffled Complex Evolution (SCE-UA) global optimization method was integrated with RRI model to calibrate the sensitive parameters. In the present study, we selected flood event in 2000 which was considered as 50-year return period flood in term of discharge volume of 500 km3. The simulated results were compared with observed discharge at the stations along the mainstream and inundation map produced by Dartmouth Flood Observatory and Landsat 7. The results indicated good agreement between observed and simulated discharge with NSE = 0.86 at Stung Treng Station. The model predicted inundation extent with success rate SR = 67.50% and modified success rate MSR = 74.53%. In conclusion, the RRI model was successfully used to simulate rainfall runoff and inundation processes in the large scale Mekong River Basin with a good performance. It is recommended to improve the quality of the input data in order to increase the accuracy of the simulation result.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.16 no.4
• /
• pp.763-770
• /
• 2021

In this paper, in order to exclude the influence of BAN(Body Area Network) signals operating in the ISM band, the design and optimization process of an on-body microstrip patch antenna operating at 4.567 GHz is presented. The antenna for the monitoring of the lower legs with cancellous osteoporosis is designed to be lightweight and compact with improved return loss and bandwidth. The structure around the applied lower leg consisted of a five-layer dielectric plane. Taking into account losses, the complex dielectric constant of each layer is calculated using multi Cole-Cole model parameters, whereas a unipolar model is used for normal or osteoporotic cancellous bones. The return loss of the coaxial feed antenna on the phantom is -67.26 dB at 4.567 GHz, and in the case of osteoporosis, at the same frequency the return loss difference is 35.88 dB, and the resonance frequency difference is about 7 MHz.

• Environmental Engineering Research
• /
• v.23 no.4
• /
• pp.474-484
• /
• 2018

The cleaning efficiency of reverse osmosis (RO) membranes inevitably fouled by organic foulants depends upon both chemical (type of cleaning agent, concentration of cleaning solution) and physical (cleaning time, flowrate, temperature) parameters. In attempting to determine the optimal procedures for chemical cleaning organic-fouled RO membranes, the design of experiments concept was employed to evaluate key factors and to predict the flux recovery rate (FRR) after chemical cleaning. From experimental results and based on the predicted FRR of cleaning obtained using the Central Composite Design of Minitab 17, a modified regression model equation was established to explain the chemical cleaning efficiency; the resultant regression coefficient ($R^2$) and adjusted $R^2$ were 83.95% and 76.82%, respectively. Then, using the optimized conditions of chemical cleaning derived from the response optimizer tool (cleaning with 0.68 wt% disodium ethylenediaminetetraacetic acid for 20 min at $20^{\circ}C$ with a flowrate of 409 mL/min), a flux recovery of 86.6% was expected. Overall, the results obtained by these experiments confirmed that the equation was adequate for predicting the chemical cleaning efficiency with regards to organic membrane fouling.

• Advances in Computational Design
• /
• v.4 no.1
• /
• pp.15-32
• /
• 2019

One of the efficient and useful tools to achieve the optimal design of structures is employing the sensitivity analysis in the finite element model. In the numerical optimization process, often the semi-analytical method is used for estimation of derivatives of the objective function with respect to design variables. Numerical methods for calculation of sensitivities are susceptible to the step size in design parameters perturbation and this is one of the great disadvantages of these methods. This article uses complex variables method to calculate the sensitivity analysis and combine it with discrete sensitivity analysis. Finally, it provides a new method to obtain the sensitivity analysis for linear structures. The use of complex variables method for sensitivity analysis has several advantages compared to other numerical methods. Implementing the finite element to calculate first derivatives of sensitivity using this method has no complexity and only requires the change in finite element meshing in the imaginary axis. This means that the real value of coordinates does not change. Second, this method has the lower dependency on the step size. In this research, the process of sensitivity analysis calculation using a finite element model based on complex variables is explained for linear problems, and some examples that have known analytical solution are solved. Results obtained by using the presented method in comparison with exact solution and also finite difference method indicate the excellent efficiency of the proposed method, and it can predict the sustainable and accurate results with the several different step sizes, despite low dependence on step size.