• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.795-796
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• 2006

Recently, blocking harmful contents such as adult images has been widely researched. However, most of adult image blocking methods use flush color model without shape information. In this paper, we present a new adult image blocking methods based on shape and color information. In the first step, the shape is considered. In the second step, adult images are detected using skin color model. Considering both shape and color, the detection rate can be increased. We evaluate adult image detection performance using sample images.

• Journal of the Korean Society of Physical Medicine
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• v.3 no.4
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• pp.277-284
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• 2008

Purpose : The purpose of this study was to identify the influence of Bobath and conventional method has an effect on gait of adult hemiplegic patients. Methods : The data were collected by each 15 adult stroke patients. The treatment was based on Bobath and conventional approach. Temporal and spatial parameters of gait were analysed for using the computerized GAITRite system. Results : The gait step (p<.05), gait velocity (p<.05), cadence (p<.05) and step length (p<.05) was significantly different with the Bobath method. The Gait step (p<.05) and gait velocity (p<.05) was significantly different with the conventional method. But the cadence and step length was not significantly increased in the conventional method. Conclusion : The Bobath method is more useful to improve the gait in hemiplegic patients than conventional method.

• Journal of the Korea Society of Computer and Information
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• v.14 no.5
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• pp.45-54
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• 2009

In this paper, we propose an adult images detection algorithm using a mean intensity filter and an improved 2D Hough Transform. This paper is composed of three major steps including a training step, a recognition step, and a verification step. The training step generates a mean nipple variance filter that will be used for detecting nipple candidate regions in the recognition step. To make the mean variance filter, we converts an input color image into a gray scale image and normalize it, and make an average intensity filter for nipple areas. The recognition step first extracts edge images and finds connected components, and decides nipple candidate regions by considering the ratio of width and height of a connected component. It then decides final nipple candidates by calculating the similarity between the learned nipple average intensity filter and the nipple candidate areas. Also, it detects breast lines of an input image through the improved 2D Hough transform. The verification step detects breast areas and identifies adult images by considering the relations between nipple candidate regions and locations of breast lines.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.23-29
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• 2015

The baby-step giant-step algorithm seeks b in a discrete logarithm problem when a,c,p of $a^b{\equiv}c$(mod p) are already given. It does so by dividing p by m block of $m={\lceil}{\sqrt{p}}{\rceil}$ length and letting one giant walk straight toward $a^0$ with constant m strides in search for b. In this paper, I basically reduce $m={\lceil}{\sqrt{p}}{\rceil}$ to p/l, $a^l$ > p and replace a giant with an adult who is designed to walk straight with constant l strides. I also extend the algorithm to allow $2^k$ adults to walk simultaneously. As a consequence, the proposed algorithm quarters the execution time of the basic adult-walk method when applied to $2^k$, (k=2) in the range of $1{\leq}b{\leq}p-1$. In conclusion, the proposed algorithm greatly shorten the step number of baby-step giant-step.

• The Journal of the Korea Contents Association
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• v.9 no.4
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• pp.1-11
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• 2009

To classifying and filtering of adult images, in recent the computer vision techniques are actively investigated because rapidly increase for the amount of adult images accessible on the Internet. In this paper, we investigate and develop the tool filtering of adult images using skin color model. The tool is consisting of two steps. In the first step, we use a skin color classifier to extract skin color regions from an image. In the nest step, we use a region feature classifier to determine whether an image is an adult image or not an adult image depending on extracted skin color regions. Using histogram color model, a skin color classifier is trained for RGB color values of adult images and not adult images. Using SVM, a region feature classifier is trained for skin color ratio on 29 regions of adult images. Experimental results show that suggested classifier achieve a detection rate of 92.80% with 6.73% false positives.

• Journal of Families and Better Life
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• v.15 no.2
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• pp.127-140
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• 1997

Researches found that the attitude of adult married children played an important role for the satisfaction and stability of the elderly remarriage. Therefore this study focused on the children's perception of the elderly remarriage. The results were as follows: Sex was found to be influential to elderly remarriage. Males were more positive than females. The degree of sex-stereotyping and supporting experience of the elderly parents were found to influence on children's perception. adult children positively perceived elderly remarriage as giving emotional satisfaction mutual-dependence and liveliness or freedom of later life. Meanwile they negatively considered elderly remarriage mainly because of traditional public attitudes toward remarriage difficulties of adaptation with step-familes and financial or legal conflicts. Adult children regarded health character financial independence and children's agreement level as the most considerate factors whereas the elderly the adaptati n among step-family members marital adaptaion and public attitudes toward their remarriage.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.6
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• pp.25-31
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• 2014

When the public key e and the composite number n=pq are disclosed but not the private key d in an asymmetric-key RSA, message decryption is carried out by obtaining ${\phi}(n)=(p-1)(q-1)=n+1-(p+q)$ and subsequently computing $d=e^{-1}(mod{\phi}(n))$. The most commonly used decryption algorithm is integer factorization of n/p=q or $a^2{\equiv}b^2$(mod n), a=(p+q)/2, b=(q-p)/2. But many of the RSA numbers remain unfactorable. This paper therefore applies baby-step giant-step discrete logarithm and $2^k$-ary modular exponentiation to directly obtain ${\phi}(n)$. The proposed algorithm performs a reverse baby-step and $2^k$-ary adult-step. As a results, it reduces the execution time of basic adult-step to $1/2^k$ times and the memory $m={\lceil}\sqrt{n}{\rceil}$ to l, $a^l$ > n, hence obtaining ${\phi}(n)$ by executing within l times.

• Korean Journal of Adult Nursing
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• v.22 no.4
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• pp.353-364
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• 2010

Purpose: The purpose of this study was to develop an algorithm for preventing and managing of pressure ulcer and to verify the its appropriateness. Methods: The first step was development of a pre-algorithm through a literature review and expert opinion. The second step was to establish content validity by submitting the algorithm questionnaires about the content to 12 experts. The third step was the revision of the algorithm. The fourth and last step was to establish the clinical validity of the algorithm with 25 experienced nurses. Results: For the ease of the practitioner the algorithm for prevention and the management of pressure ulcers was confined to one page depicting the main algorithm pathway and seven stepwise guidelines. The guidelines included skin care of pressure ulcer prevention, mechanical loading care, support surface care, reposition care of pressure ulcer, and Stages II, III and IV explanations along with debridement/wound irrigation and infection control. Most of all algorithm courses chosen more than 80% of agreement by expert index of content validity. The usefulness, appropriateness, and convenience of the algorithm were demonstrated through clinical validity with intensive care unit and ward nurses. Conclusion: The algorithm will improve the quality of pressure ulcer nursing care as it provides a model for decision making for clinical nurses as well as providing consistent and integrated nursing care for patients with pressure ulcer throughout an institution.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.1
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• pp.127-132
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• 2011

In this paper, we propose a novel method of adult image classification by combining skin color regions and edges in an input image. The proposed method consists of four steps. In the first step, initial skin color regions are detected by logical AND operation of all skin color regions detected by the existing methods of skin color detection. In the second step, a skin color probability map is created by modeling the distribution of skin color in the initial regions. Then, a binary image is generated by using threshold value from the skin color probability map. In the third step, after using the binary image and edge information, we detect final skin color regions using a region growing method. In the final step, adult image classification is performed by support vector machine(SVM). To this end, a feature vector is extracted by combining the final skin color regions and neighboring edges of them. As experimental results, the proposed method improves performance of the adult image classification by 9.6%, compared to the existing method.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.4
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• pp.334-340
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• 2013

Using a relationship between step length and accelerometer output, step length can be estimated. In this paper, we propose a new step length estimation algorithm, which can be used both for the plane and the slope by compensating the slope angle. The slope angle is estimated using a barometer and the slope angle is compensated by observing how the slope affects the step length estimation. The proposed algorithm is verified using five adult man walking data, where the average length error is about 3% regardless of the slope.