• Korean Journal of Human Ecology
• /
• v.6 no.2
• /
• pp.133-144
• /
• 1997

Clothing is considered as a means of self-projection in the childhood and children show clear preference on their own favorite clothing on which their latent identity is reflected. Changing sex-role identity, in particular, in the modern complex society specially affects the clothing behavior of children. The purpose of this study is to investigate the clothing behavior of children in conjunction with sen-role identity and home environment variables. This study will provide fundamental information on the clothing behavior in the childhood and be of help in selecting appropriate clothing in accordance with the variation of sex-role identity. Necessary information for this study was obtained through a questionaire. 'Bem sex-role identity inventory' was used to investigate the effect of sex-role identity and the clothing behavior was studied in conjunction with the factors of conformity, dependence, aesthetics and interest. The subjects of investigation are composed of three hundred male and female elementary school students in the 5th and 6th grades. For the statistical analysis of the collected data, percentage(%), mean value(M), standard deviation(SD) and Pearson's correlation coefficient were calculated and t-test, $x^2$-test, and Duncan's multiple range test were performed. The results form this study are as follows : 1. Sex-role identity shows a little difference according to gender, order of a birth and standard of living. This small difference is shown to be statistically insignificant. 2. In clothing behavior in connection with the sex-role identity, statistically significant trend was not found in typical sex-role identity group. However, clothing behavior in modernistic sex-role identity group exhibits statistically significant results in the factors of dependence, aesthetics and interest at the level of P<.001. 3. As concerns the clothing behavior in connection with gender, boy students show statistically more significant tendency in aesthetics and interest than girls do. However, boy students show statistically more significant tendency in aesthetics than girls do in connection with the standard of living. Although the clothing behavior associated with the level of parents education, mother's age and existence of mother's job shows a little difference in mean values, statistically significant trend was not detected. 4. Clothing behavior of the children shows a meaningful correlation between the factors. 5. Through 3-dimensional variables analysis, it is found that there is no mutual interaction between gender, sex-role identity and standard of living on the clothing behavior. The results from MCA supplementary analysis reveal that there is difference according to the gender, sex-role identity and standard of living.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.5
• /
• pp.177-187
• /
• 2014

This paper proposes a fast subspace tracking methods, which is called GVFF FAPI, based on FAPI (Fast Approximated Power Iteration) method and GVFF RLS (Gradient-based Variable Forgetting Factor Recursive Lease Squares). Since the conventional FAPI uses a constant forgetting factor for estimating covariance matrix of source signals, it has difficulty in applying to non-stationary environments such as continuously changing DOAs of source signals. To overcome the drawback of conventioanl FAPI method, the GVFF FAPI uses the gradient-based variable forgetting factor derived from an improved means square error (MSE) analysis of RLS. In order to achieve the decreased subspace error in non-stationary environments, the GVFF-FAPI algorithm used an improved forgetting factor updating equation that can produce a fast decreasing forgetting factor when the gradient is positive and a slowly increasing forgetting factor when the gradient is negative. Our numerical simulations show that GVFF-FAPI algorithm offers lower subspace error and RMSE (Root Mean Square Error) of tracked DOAs of source signals than conventional FAPI based MUSIC (MUltiple SIgnal Classification).

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.35S no.8
• /
• pp.1-11
• /
• 1998

One of the desired features for the realizations of high quality Information and Telecommunication services in future is "the Sensation of Reality". This will be achieved only with the visual communication based on the 3- dimensional (3-D) moving images. The main difficulties in realizing 3-D moving image communication are that there is no developed data transmission technology for the hugh amount of data involved in 3-D images and no established technologies for 3-D image recording and displaying in real time. The currently known stereoscopic imaging technologies can only present depth, no moving parallax, so they are not effective in creating the sensation of the reality without taking eye glasses. The more effective 3-D imaging technologies for achieving the sensation of reality are those based on the multiview 3-D images which provides the object image changes as the eyes move to different directions. In this paper, a multiview 3-D imaging system composed of 8 CCD cameras in a case, a RGB(Red, Green, Blue) beam projector, and a holographic screen is introduced. In this system, the 8 view images are recorded by the 8 CCD cameras and the images are transmitted to the beam projector in sequence by a signal converter. This signal converter converts each camera signal into 3 different color signals, i.e., RGB signals, combines each color signal from the 8 cameras into a serial signal train by multiplexing and drives the corresponding color channel of the beam projector to 480Hz frame rate. The beam projector projects images to the holographic screen through a LCD shutter. The LCD shutter consists of 8 LCD strips. The image of each LCD strip, created by the holographic screen, forms as sub-viewing zone. Since the ON period and sequence of the LCD strips are synchronized with those of the camera image sampling adn the beam projector image projection, the multiview 3-D moving images are viewed at the viewing zone.

• Journal of the Korean Data and Information Science Society
• /
• v.24 no.6
• /
• pp.1385-1400
• /
• 2013

This paper discusses income replacement ratios of national pension, retirement pension and individual annuities in Korea. These ratios are useful indicators for the assessment of retirement income security of workers. This paper projects income replacement ratios, using the pension entry rate, decrement rates, and life tables of the National Statistical Office. The result of the actuarial projection is that the income replacement ratio of national pension is approximately 21.0 to 22.7%, that the income replacement ratio of retirement pension is about 5.8 to 9.7%, and that the income replacement ratio of an individual annuity is about 13.5 to 21.0%, respectively. The income replacement ratio by income varies due to the effects of income redistribution in national pension and retirement pension, but the income replacement ratio of an individual annuity is constant, regardless of income.

• Journal of Korean Society of Forest Science
• /
• v.96 no.1
• /
• pp.29-33
• /
• 2007

The objective of this research was to provide basic information of Thuja orientalis stand for prediction system, which consists of the best model of diameter and basal area. Data was from cores of 45 sample trees of Thuja orientalis stand that was designated as a natural monument (No. 62) in Yeongcheon, Chungbuk. Of the projection functions tested, polymorphic equation using the overlapping data showed higher precision of the fitting than anamorphic equation using. In diameter growth, Schumacher polymorphic equation of $D_2={\exp}({\ln}(D_1)(T_1/T_2)^{0.4495}+3.8535(1-(T_1/T_2)^{0.4495}))$, and in basal area growth, Schumacher polymorphic equation of $BA_2={\exp}({\ln}(BA_1)(T_1/T_2)^{0.1235}+11.3793(1-(T_1/T_2)^{0.1235}))$ showed the highest precision of the fitting among them. The equation, therefore, could be available as basic information for estimation of growth and management of Thuja orientalis stand.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.15 no.1
• /
• pp.64-75
• /
• 2012

To predict the future distribution of forest vegetation, the present forest stand distributions of South Korea were represented by multinomial logit model with the following environmental variables: summer average precipitation, the coldest month average temperature, elevation, degree of base saturation, and soil organic matter. The future forest community was predicted by applying the MIROC3.2 hires A1B scenario. The future climate data were downscaled by statistically method. The coldest month average temperature increased $4.4^{\circ}C$, $6.0^{\circ}C$, and $9.4^{\circ}C$, and 3 months average precipitation changed -1.2%, 5.7%, and 5.3% for 2020s, 2050s, and 2080s respectively. For the projected summer precipitation and the coldest temperature, the future deciduous and mixed forests in the study area increased 56.9% and 8.3% and the coniferous forest decreased 11.2% in 2080s based on present.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.42 no.4 s.304
• /
• pp.11-18
• /
• 2005

For expressing intention the human often use body languages as well as vocal languages. Of course the gestures using arms and hands are the representative ones among the body languages. Therefore it is very important to understand the human arm motion in human-computer interaction. In this respect we present here how to estimate 3D pose of human arms by using computer vision systems. For this we first focus on the idea that the human arm motion consists of mostly revolute joint motions, and then we present an algorithm for understanding 3D motion of a revolute joint using vision systems. Next we apply it to estimating 3D pose of human arms using vision systems. The fundamental idea for this algorithm extension is that we may apply the algorithm for a revolute joint to each of the revolute joints of hmm arms one after another. In designing the algorithms we focus on seeking closed-form solutions with high accuracy because we aim at applying them to human computer interaction for ubiquitous computing and virtual reality.

• The Transactions of the Korea Information Processing Society
• /
• v.4 no.2
• /
• pp.465-482
• /
• 1997

In this paper, we have studied on cinstructing code-recognition shstem by neural network according to a image process taking the DOT classification code stamped on tire surface.It happened to a few problems that characters distorted in edge by diffused reflection and two adjacent characters take the same label,even very sen- sitive to illumination ofr recognition the stamped them on tire.Thus,this paper would propose the algorithm for tire code under being cinscious of these properties and prove the algorithm drrciency with a simulation.Also,we have suggerted the MCBP network composing of multi-linked recognizers of dffcient identify the DOT code being tire classification code.The MCBP network extracts the projection balue for classifying each character's rdgion after taking out the prjection of each chracter's region on X,Y axis,processes each chracters by taking 7$\times$8 normalization.We have improved error rate 3% through the MCBP network and post-process comparing the DOT code Database. This approach has a accomplished that learming time get's improvenent at 60% and recognition rate has become to 95% from 90% than BckPropagation with including post- processing it has attained greate rates of entire of tire recoggnition at 98%.

• Spatial Information Research
• /
• v.12 no.2
• /
• pp.181-191
• /
• 2004

Nowadays, GPS-photogrammetry can be applied to the basemap production, a land register and NGIS. And from now on, as the increase of GPS receiver rate, the study on the interpolation methods considering the exact movement of an aircraft at photoflight and the study on the supplement of GPS defect by INS are required continuously. GPS-Photogrammetry, which are based on the direct measurement of the projection centers and attitude at the moment of camera exposure time through loading the GPS receiver in aircraft. This photogrammetric methods can of for us to acquire the exterior orientation parameters with only minimum ground control points, even the ground control process could be completely skipped. Consequently, we can drastically reduce the time and cost far the mapping process. In this thesis, two test flights were conducted in area to evaluate the performance of accuracy and efficiency through the analysis of results between the two photogrammetric methods, that is, traditional photograrammetry, GPS-Photogrammetry. Test results shows that a large variety of advantages of GPS-Photogrammetry against traditional photogrammetry is to be verified. Especially, the number of ground control points for the exterior orientation could be saved more than 70～80%, and the cost far map production 30～50%, respectively. In addition, it was convinced that the large reduction of control points has not any effect on the block accuracy.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.40 no.1
• /
• pp.19-29
• /
• 2003

This paper presents a novel hybrid classifier for face recognition with artificially generated virtual training samples. We utilize both the nearest neighbor approach in feature angle space and a connectionist model to obtain a synergy effect by combining the results of two heterogeneous classifiers. First, a classifier called the nearest feature angle (NFA), based on angular information, finds the most similar feature to the query from a given training set. Second, a classifier has been developed based on the recall of stored frontal projection of the query feature. It uses a frontal recall network (FRN) that finds the most similar frontal one among the stored frontal feature set. For FRN, we used an ensemble neural network consisting of multiple multiplayer perceptrons (MLPs), each of which is trained independently to enhance generalization capability. Further, both classifiers used the virtual training set generated adaptively, according to the spatial distribution of each person's training samples. Finally, the results of the two classifiers are combined to comprise the best matching class, and a corresponding similarit measure is used to make the final decision. The proposed classifier achieved an average classification rate of 96.33% against a large group of different test sets of images, and its average error rate is 61.5% that of the nearest feature line (NFL) method, and achieves a more robust classification performance.