• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.3
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• pp.29-33
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• 2007

All pixels of image sensor do not react uniformly even if the light of same radiance enters into the camera. This non-uniformity comes from the sensor pixel non-uniformity and non-uniformity induced by the changing transmission of the telescope over the field. The first contribution to the non-uniformity has high spatial frequency nature and has an influence on the result and quality of the data compression. The second source of non-uniformity has low frequency nature and has no influence of the compression result. As the contribution resulting from the sensor PRNU(Photo Response Non-Uniformity) is corrected inside the camera electronics, the effect of the remaining non-uniformity to the compression result will be negligible. The non-uniformity correction result shall have big difference according to the sensor modeling and the calculation method to get correction coefficient. Usually, the sensor can be modeled with one dimensional coefficients which are a gain and a offset for each pixel. Only two measurements are necessary theoretically to get coefficients. However, these are not the optimized value over the whole illumination level. This paper proposes the algorithm to calculate the optimized non-uniformity correction coefficients over whole illumination radiance. The proposed algorithm uses several measurements and the least square method to get the optimum coefficients. The proposed algorithm is verified using the own camera electronics including sensor, electrical test equipment and optical test equipment such as the integrating sphere.

• Journal of the Korean Society of Clothing and Textiles
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• v.19 no.4
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• pp.684-695
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• 1995

The purpose of this study was to investigate the influence of the mechanical properties on drapability in the peach skin-like finished fabrics. For this study, the samples used were 50 kinds of peach skin-like finished fabrics. The mechanical properties such as tensile, shearing, bending, compressional, surface characteristic values, thickness and weight were measured with a KES-F system and drupe coefficient by drape tester. The relationship between the characteristic values and drape coefficicients of the peach skin-like finished fabrics results were obtained. 1. Peach skin-like finished fabric had $\pm$2o range of shearing, bending, compression, surface. properties, thickness and weight as compared with Japanese women's thin fabrics. The characteristic mixing values were better with the values of WC/T, W/T, etc. as compared with that of japanese women's thin fabrics. Accordingly, the peach skin-like finished fabrics had a little volume, excellent hanging and drapability as compared with japanese women's thin fabrics. 2. The drape coefficient of peach skin-like finished fabric had a high level of correlation between 2HB, G, WC, MIU, WT, MMD, 2HG, RT, W, B etc. of the mechanical properties. The blocked properties that contributed to the drape coefficient of peach skin-like finished fabrics were in the order of the bending> tensile> thickness> weight properties. This drape coefficients(DC) were found by measuring the mechanical properties according to the obtained regress on equate on. DC=99.0179+17.9023 log G -17.0543 log 2HG5+17.2104 log 2HG+35.7685 log 2HB+ 4.6082 log B-30.5906 log T+4.2308 log W 3. The contribution to the drape coefficient of the characteristic mixing values of peach skin-like finished fabric was in the order of > 2HB/W> 2HB/B> B/W The drape coefficients were found by measuring the characteristic mixing values according to the obtained regression equation. 4. The drape coefficients of peach skin-like finished fabrics were influenced by the differences between the bending of warp direction, bending of weft direction, shearing etc which in turn determine the level of hanging. The regression equation was as follows; 5. The drape coefficients of peach skin.like finished fabrics had a highly positive correlation with the node index. It has an negative correlation with number of nodes.

• Wind and Structures
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• v.24 no.5
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• pp.405-430
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• 2017

The aerodynamic characteristics of vehicles are critical to assess vehicle safety and passenger comfort for vehicles running on long span bridges in a windy environment. However, in previous wind-vehicle-bridge (WVB) system analysis, the aerodynamic interference between the vehicle and the bridge was seldom considered, which will result in changing aerodynamic coefficients. In this study, the aerodynamic coefficients of a high-sided truck on the ground (ground case) and a typical bridge deck (bridge deck case) are determined in a wind tunnel. The effects of existent structures including the bridge deck and bridge accessories on the high-sided vehicle's aerodynamic characteristics are investigated. A three-dimensional analytical framework of a fully coupled WVB system is then established based on the finite element method. By inputting the aerodynamic coefficients of both cases into the WVB system separately, the vehicle safety and passenger comfort are assessed, and the critical accidental wind speed for the truck on the bridge in a windy environment is derived. The differences in the bridge response between the windward case and the leeward case are also compared. The results show that the bridge deck and the accessories play a positive role in ensuring vehicle safety and improving passenger comfort, and the influence of aerodynamic interference on the response of the bridge is weak.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.05a
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• pp.451-454
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• 2000

The impact ionization(I.I.) is necessary to analyze carrier transport properties under the influence of high electric field. The full band I-k relation and Fermi's golden rule are used for the calculation of impact ionization rate. We have investigated the temperature- and field-dependent impact ionization coefficient for silicon using full band Monte Carlo simulation. The impact ionization coefficients calculated by our impact ionization model are agreed with experimental data at look. We know that impact ionization coefficients and electron energies are decreasing along increasing temperature due to increase of phonon scattering, especially by emission. The logarithm of impact ionization coefficients are fitted to linear function for temperature and field. The residuals of linear function are within the error bound of 5%. We know logarithmic impact ionization coefficients are linearly dependent on temperature and field.

• Journal of the Korean Geotechnical Society
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• v.21 no.8
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• pp.85-93
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• 2005

Earth pressures acting on unmovable rigid walls vary according to loading-unloading conditions due to compaction experienced by backfill soil. Appropriate coefficients of earth pressure at rest with considering this influence need to be determined to estimate earth pressures more reasonably.0 this study, a single cycle hysteretic model simulating soil's loading-unloading-reloading behavior under $K_o-condition$ was reproduced by conducting a series of $K_o-triaxial$ test for compacted residual soils. Based on the results, coefficients of earth pressure at rest at each stage of stress paths such as, virgin loading, unloading and reloading were determined. Also, applicabilities of empirical equations to the estimation of the coefficients were evaluated by comparing the experimental results with those estimated by the equations. As a result, it was concluded that the empirical equations could be applied reasonably to the estimation of the coefficients for compacted residual soils in cases where some amount of error might be acceptable for the reloading stage of the hysteretic model.

• Fashion & Textile Research Journal
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• v.7 no.5
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• pp.509-518
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• 2005

In recent years retail competition has intensified, generally as a consequence of technologies, more sophisticated management practices and industry consolidation. An understanding of current customers' loyalty intentions and their determinants is an important basis for the identification of optimal retailer actions. The focus of this study is to examine the links between patronage intention and the effects of various antecedents of current customers' store loyalty intentions in fashion store. 340 female universities students living in Seoul were analyzed by utilizing multiple regressions to investigate the predictability of each of the 4 different sets of variables(consumer value, source of information, clothing benefits, importance of store attributes) on four patronage intentions of apparel shopping(discount store, speciality store, conventional market, Fashion shopping mall). Four factors were significant in predicting conventional market patronage intention. Brand had a negative coefficient, while price, social affiliation, store fashion service/promotion had positive coefficients. Fashion shopping mall were predicted by five factors:brand had a negative coefficient, while media, social affiliation, price, uniqueness had positive coefficients. For specialty store, four factors were significant: brand had a negative coefficient, while store fashion service/promotion, personal sources, uniqueness had positive coefficients. Four factors were significant in predicting discount store patronage intention :price, store fashion service/promotion, social affiliation, variety of price & product had positive coefficients. Despite the relatively low $r^2s$, all four variables appeared to have, to some degree, predictability of choosing among four different types of store for apparel shopping. Based on the results, patronage intention profiles for four retail stores were developed. Marketing implications are discussed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.12
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• pp.1772-1781
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• 2017

In this study, the design methodology for alleviating the overfitting problem of Polynomial Neural Networks(PNN) is realized with the aid of two kinds techniques such as L2 regularization and Sum of Squared Coefficients (SSC). The PNN is widely used as a kind of mathematical modeling methods such as the identification of linear system by input/output data and the regression analysis modeling method for prediction problem. PNN is an algorithm that obtains preferred network structure by generating consecutive layers as well as nodes by using a multivariate polynomial subexpression. It has much fewer nodes and more flexible adaptability than existing neural network algorithms. However, such algorithms lead to overfitting problems due to noise sensitivity as well as excessive trainning while generation of successive network layers. To alleviate such overfitting problem and also effectively design its ensuing deep network structure, two techniques are introduced. That is we use the two techniques of both SSC(Sum of Squared Coefficients) and $L_2$ regularization for consecutive generation of each layer's nodes as well as each layer in order to construct the deep PNN structure. The technique of $L_2$ regularization is used for the minimum coefficient estimation by adding penalty term to cost function. $L_2$ regularization is a kind of representative methods of reducing the influence of noise by flattening the solution space and also lessening coefficient size. The technique for the SSC is implemented for the minimization of Sum of Squared Coefficients of polynomial instead of using the square of errors. In the sequel, the overfitting problem of the deep PNN structure is stabilized by the proposed method. This study leads to the possibility of deep network structure design as well as big data processing and also the superiority of the network performance through experiments is shown.

• The Journal of Engineering Research
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• v.6 no.2
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• pp.141-151
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• 2004

The physical properties of gold investment materials are depending on it's thermal expansion coefficients, compressive strength, and particles size distributions. Normally the gold investment materials are consisted of cristobalite, quartz and plaster. Since the thermal expansion coefficient of cristobalite and quartz are $2.6\times10^{-6}/^\circC$, $2.32\times10^{-6}/^\circC$, respectively, the composition ratio of each components influence the thermal and clinical properties of gold investment materials. Recently are imported from overseas and the commercial market is expected to expand. Thus it is necessary to develop the optimum strength and compressive strength of gold investment materials which the an homogeneous size distribution and thermal expansion coefficients. Therefore two different experiments has been done. Firstly the homogeneous cristobalite and quartz are made by pulverizing milling. Secondly the compressive strength and thermal expansion coefficients are analysed by the composition ratio of cristobalite and quartz. As a results of experiments, homogeneous distribution of cristobalite and quartz are observed by pulverizing and milling. The optimum compressive strength was obtained at the ratio of 45:25 cristobalite, quartz respectively.

• Journal of the Korean Graphic Arts Communication Society
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• v.16 no.2
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• pp.23-36
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• 1998

Moisture content of printing paper and circumstance of printing room has great influence on the printing works. We have studied on the printability of domestic art paper according to the insufficient Korea weather. As the result, we found the printability of domestic art paper are much more affect by moisture content than any other printability coefficients, especially print density and hygroexpansivity decrease with moisture content increase.

• East Asian mathematical journal
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• v.27 no.1
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• pp.51-65
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• 2011

In the paper, we study questions on classical solvability of nonlocal problems for a third-order linear hyperbolic equation in a rectangular domain. The Riemann method is applied to the Goursat problem and solution is obtained in the integral form. Investigated problems are reduced to the uniquely solvable Volterra-type equation of second kind. Influence effects of coefficients at lowest derivatives on correctness of studied problems are detected.