• Journal of Advanced Marine Engineering and Technology
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• v.23 no.4
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• pp.559-564
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• 1999

A particle image velocimetry is the representative technique for measuring flow velocities at whole field simultaneously. The present study adopted the PTV method for velocity acquisition in a square enclosure with initially isothermal fluid by using a general lamp-based sheet light source. The enclosure was composed of hot and cold vertical wall and was confined by two horizon-tal adiabatic walls. The drift velocities were measured and the drift was visualized by PTV for a rayleigh number of 5.28{\times}10^8.$ Obtained instant simulataneous velocity vectors show flow pattern and the result of horizontal velocity profile agree well with the numerical result.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.4
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• pp.1897-1903
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• 2011

This paper discusses a 2D/3D conversion of images using technologies like object extraction and depth-map creation. The general procedure for converting 2D images into a 3D image is extracting objects from 2D image, recognizing the distance of each points, generating the 3D image and correcting the image to generate with less noise. This paper proposes modified new methods creating a depth-map from 2D image and recognizing the distance of objects in it. Depth-map information which determines the distance of objects is the key data creating a 3D image from 2D images. To get more accurate depth-map data, noise filtering is applied to the optical flow. With the proposed method, better depth-map information is calculated and better 3D image is constructed.

• Journal of Korea Multimedia Society
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• v.15 no.10
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• pp.1205-1211
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• 2012

Recently, the evaluating method of the bone mineral density (BMD) in X-ray absorptiometry image has been studied for the early diagnosis of osteoporosis which is known as a metabolic disease. The BMD, in general, is evaluated by calculating pixel intensity in the bone segmented regions. Accurate bone region extraction is extremely crucial for the BMD evaluation. So, a X-Ray image enhancement is needed to get precise bone segmentation. In this paper, we propose an image enhancement method of X-ray image having multiple noise based sparse representation. To evaluate the performance of proposed method, we employ the contrast to noise ratio (CNR) metric and cut-view graphs visualizing image enhancement performance. Experimental results show that the proposed method outperforms the BayesShrink noise reduction methods and the previous noise reduction method in sparse representation with general noise model.

• The Research Journal of the Costume Culture
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• v.17 no.1
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• pp.90-104
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• 2009

If people want to project a successful personal style, hair style might play a big role as well as clothing. The purpose of this study was to observe hair behavior according to demographic variables, and to analyze correlation between desired hair image and clothing image sought. Questionnaires were distributed to 600 females aged $20s{\sim}40s$, using a convenient sampling method. Only 556 reliable questionnaires were selected for statistical analysis. Correlation r, ANOVA and Chi-square were used to analyze the data, using the SPSS program. There was a significant association between hair style and occupation. Career woman preferred roll straight perm treated hair, students preferred general perm treated hair and full time house wives preferred general wave perm treated. The medium layer cut was the most preferred cut style. People want to give different accents in hair styling with occupation and age variable. Certain desired clothing image had a high correlation with desired hair style image. Those who people want to express sexy, and bohemian image through clothing, they also want to create those image in hair styling with a high correlation(r=0.683, r=0.704).

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.212-220
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• 2024

When a typhoon or natural disaster occurs, a significant number of orchard fruits fall. This has a great impact on the income of farmers. In this paper, we introduce an AI-based method to enhance low-quality raw images. Specifically, we focus on apple images, which are being used as AI training data. In this paper, we utilize both a basic program and an artificial intelligence model to conduct a general image process that determines the number of apples in an apple tree image. Our objective is to evaluate high and low performance based on the close proximity of the result to the actual number. The artificial intelligence models utilized in this study include the Convolutional Neural Network (CNN), VGG16, and RandomForest models, as well as a model utilizing traditional image processing techniques. The study found that 49 red apple fruits out of a total of 87 were identified in the apple tree image, resulting in a 62% hit rate after the general image process. The VGG16 model identified 61, corresponding to 88%, while the RandomForest model identified 32, corresponding to 83%. The CNN model identified 54, resulting in a 95% confirmation rate. Therefore, we aim to select an artificial intelligence model with outstanding performance and use a real-time object separation method employing artificial function and image processing techniques to identify orchard fruits. This application can notably enhance the income and convenience of orchard farmers.

• Journal of Korean Academy of Nursing Administration
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• v.7 no.3
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• pp.455-472
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• 2001

The purpose of this study was to serve as a basis for mapping out successful strategies to build the professional self-image of nurses through uniform, by examining their satisfaction with uniform and professional self-image by general characteristics, and identifying the correlational relationship between the two factors. The subjects in this study were 205 nurses who served in general departments of two university hospitals in Seoul. The departments where special uniform was required, including ICU, RR, OR and CSR, were excluded. The data were collected from September 15 through 22, 2000. For measurement of uniform satisfaction level, a uniform satisfaction scale was prepared by myself, and Arthur(1990)'s PSCNI translated and modified by Song Kyong Ae and Rho Chun Hee(1996) was employed. The Cronbach a of the uniform satisfaction scale and PSCNI was 0.90 and 0.86 respectively. The collected data were analyzed by SAS, and real number, percentage, average and standard deviation were calculated. Besides, t-test, one-way ANOVA, Pearson's r procedures were utilized, and Scheffe test was conducted as a posttest. The findings of this study were as below: 1. The uniform satisfaction of the nurses investigated was scored 2.52 on the basis of 4 points, which was on the medium level. By subarea, symbolicity satisfaction was 2.48, and aesthetic satisfaction was 2.60. The functionability satisfaction was 2.44. So the esthetic satisfaction was greatest. 2. Among general characteristics of the subjects, two factors made a significant difference to their uniform satisfaction : age(F=4.05, P=.0189), and total career(F=4.25, P=.0061). 3. Their professional self-image got 2.75 on the basis of 4 points, which was on upper middle level. The subarea score was 2.79 for professional work, 2.52 for satisfaction and 2.97 for communication. The communication area was rated highest, and the satisfaction area was scored lowest. 4. Among the general characteristics of the subjects, professional self-image was different according to five factors : age(F=17.83, P=.001), marital status(T=5.18, P=.0000), educational background(F=8.72, P=.0002), position(T=-5.29, P=.0000) and total career(F=15.23, p=.0001). Better professional self-image was possessed by the older group than the younger one, by the married group than the singles, by the better-educated group than the less-educated, by the nurses in position equal to or higher than charge nurse, or by the higher-career group. 5. The correlational relationship of uniform satisfaction to professional self-image was statistically significant, yet very weak(r=.1978, p=.0045). The satisfaction area of professional self-image was correlated to every uniform satisfaction area, including symbolicity(4=.4393, p=.0001), aesthetics(r=.2471, p=.0004), functionability(r=.3094, p=.0001) and total satisfaction(r=.4050, p=.0001). Therefore, the uniform satisfaction gave an impact on the satisfaction area of professional self-image of the nurses, and there was a significant correlational relationship between uniform symbolicity area and total professional self-image(r=.2416, p=.0005).

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1995.06a
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• pp.91-96
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• 1995

In this paper we propose algorithms for high resolution image sequence interpolation. Image sequences, in general, are assumed to have greater amount of information than a still image. By this reason, image sequences can be used to improve the resolution of interpolated image sequences. Therefore the proposed algorithms can be the theoretical basis for interpolating dynamic image sequences. In order to demonstrate the validity of the proposed algorithms, experimental results using both synthetic and real test images are presented.

• Journal of radiological science and technology
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• v.46 no.2
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• pp.99-106
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• 2023

The height of the table should be considered important during computed tomography (CT) examination, but according to previous studies, not all radiology technologists set the table at the patient's center at the examination, which affects the exposure dose and image quality received by the patient. Therefore, this study intends to study the image quality exposure dose according to the height of the table to realize the optimal image quality and dose during the brain CT scan. The head phantom images were acquired using Philips Brilliance iCT 256. When the image was acquired, the table height was adjusted to 815, 865, 915, 965, 1015, and 1030 mm, respectively, and each scan was performed 3 times for each height. For the exposure dose measurement, optically stimulated luminescence dosimeter (OSLD) was attached to the front, side, eye, and thyroid gland of the head phantom. In the signal to noise ratio (SNR) measurement result, The SNR values for each table height were all lower than 915 mm. As a result of exposure dose, the exposure dose on each area increased as the table height decreased. The height of the table has a close relationship with the patient's radiation exposure dose in the CT scan.

• The Journal of Korean Academic Society of Nursing Education
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• v.9 no.1
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• pp.64-72
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• 2003

Purpose: The purpose of this study was to identify changes in nurses' image of student nurses before and after their first clinical practice. Method: Study samples were composed of 78 student nurses who were from nursing dept. of one college in G city. All participants had their first clinical practice for 4 weeks at two general hospitals in Gwangju. The internal consistency of the total scale was Cronbach's $\alpha$= .883. Results: After the first clinical practice, the mean score of nurses' image in general was lower than that of nurses' image before the clinical practice. In five subcategories, before the first clinical practice, professionalism and expertness were the highest followed by role performance, vision of a career, and temperature as a nurse in order but after the first clinical practice, professionalism was the highest score followed by expertness, temperature as a nurse, role performance, vision of a career in the mean scores of nurses' image. Conclusion: Based upon these findings, clinical practice will play an important role in improving role performance and vision of a nursing career for student nurses, so nursing administrators should make efforts to improve image of nurses in a variety of practice.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.3
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• pp.205-213
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• 2018

Hyperspectral image is more increasing spectral resolution that Multi-spectral image. Because of that, each pixel of the hyperspectral image includes much more information and it is considered the most appropriate technic for land cover classification. but recent research of hyperspectral image is stayed land cover classification of general level. therefore we classified land cover of detail level using ED, SAM, SSS method and made Decision Tree from result of that. As a result, the overall accuracy of general level was improved by 1.68% and the overall accuracy of detail level was improved by 5.56%.