• Korean Journal of Oriental Medicine
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• v.5 no.1
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• pp.101-110
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• 1999

In Sasang constitutional medicine, the classification of Sasang constitutional types (Tae-Yang, Tae-Eum, So-Yang, and So-Eum) is important for the treatment. There are some problems with the methods used for classifying Sasang constitutional types; old methods such as pulse-palpation are not considered objective and recent methods such as immunohematology are considered expensive, painful and time-consuming. To overcome these problems, a body measurement and finger prints analysis were performed. The purpose of this study was to determine whether the palm prints and the palm creases could be helpful in classifying Sasang constitutional types. Thus, we looked for characteristics of the palm prints and the palm creases according to Sasang constitutional types. Before analyzing the palm prints and palm creases, 760 Korean (465 males, 295 females) were surveyed using two kinds of questionnaires for classifying Sasang constitutional types. As there were no Tae-Yang individuals, we were only able to identify the characteristics of the palm prints and the palm creases for Tae-Eum (288 persons), So-Yang (193 persons), and So-Eum (279 persons) individuals. In this study, the terminal points of D, closed crease, and open crease seemed to be helpful in classifying Tae-Eum and So-Eum individuals. Terminal point 11 and closed crease were frequent in Tae-Eum individuals; whereas, terminal point 7 and open crease were frequent in So-Eum individuals. Therefore, the palm prints and the palm creases seem to contribute to the classification of Sasang constitutional types.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.219-228
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• 2014

Various computational resources in distributed environment are to build a high-performance computing environments through virtualization technology. Recently, there is a growing need for a complicated process due to the improvement of the user-level application, which has led to demand for high-performance computing. The requested job from users is composed of data. And because of each data has own characteristics, the classifier may consider the features of data. In this paper, we propose Job Classifying method based on Data Traits for Increased Efficiency of Computational Resources in Distributed Environment (JCDT). JCDT classifies the job by data traits of the users' request, is expected to improve the job processing time and increase the processing speed of the calculation resources.

• Journal of Korea Multimedia Society
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• v.10 no.3
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• pp.391-400
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• 2007

According to the recent advances in multimedia computing, storage and searching technology have made large volume of music contents become prevalent. Also there has been increasing needs for the study on efficient categorization and searching technique for music contents management. In this paper, a new classifying method using the local information of music content and music tone feature is proposed. While the conventional classifying algorithms are based on entire information of music content, the algorithm proposed in this paper focuses on only the specific local information, which can drastically reduce the computing time without losing classifying accuracy. In order to improve the classifying accuracy, it uses a new classification feature based on music tone. The proposed method has been implemented as a part of MuSE (Music Search/Classification Engine) which was installed on various systems including commercial PDAs and PCs.

• The Journal of Korean Philosophical History
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• no.54
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• pp.115-151
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• 2017

With Seopa Ryu-Hee's Chunqiugwalyebulyu as the main research subject. this paper is to clarify characteristics in classification of the book's introductory remarks and its academic values. This book is a sort of synthetic collection of introductory remarks classification that defines standardized introductory remarks based on fundamental principles of Chunqiu introductory remarks. Seopa presented two fundamental principles for classifying Chunqiu introductory remarks. First, he clearly defined the nature and the system of the book Chunqiu, which was to present the background of classifying Chunqiu introductory remarks. Second, he declared that writing style and righteousness in Chunqiu serves as standard for classifying the introductory remarks. Seopa classified introductory remarks by type in accordance with these fundamental principles of introductory remarks in order to lay the groundwork for right interpretation of Chunqiu. Further, he was convinced that this classification of introductory remarks would block any chance of the book's wrong interpretation and at the same time, be able to remove the rationale behind distorted theories. This book can be appraised to have significant academic values in that it attempted standardization in classifying Chunqiu introductory remarks through systematic and synthetic analysis on various introductory remarks.

• Journal of The Korean Association For Science Education
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• v.23 no.3
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• pp.286-298
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• 2003

The purpose of this study was to analyze scientific thinking types and processes generated in inductive inquiry by college students. Subjects were three college student. Three inductive tasks were developed: Caminalcules set I which is a task consisted of 6 imaginary animals, a potato task which is a task about the interaction between juiced potato and $H_2O_2$, and Caminalcules set 2. Subjects' thinking types and processes were investigated through thinking-aloud method and interview. Subjects' performances were recorded on videotapes and analyzed. Subjects have shown 5 types of inductive thinking in the first task; observing, discovering commonness, discovering pattern, classifying, discovering hierarchy. The processes of inductive thinking shown by students are followed; observing $\rightarrow$discovering commonness $\rightarrow$classifying $\rightarrow$discovering pattern $\rightarrow$discovering hierachy. The subtypes of inductive thinking on observing were investigated by the analysis of subjects' performance on the second task. In analysis of protocol, student' thinking types on observing have been classified as simple observing and operational observing. Operational observing has been categorized conjectural observing and predictive observing. The subtypes of inductive thinking on classification and hierarchy were investigated by the analysis of subjects' performance on the third task. In analysis of protocol, students' thinking types on classification have been searching criteria for classifying and selecting criteria for classifying. Subtypes of discovering hierarchy have been classifying groups and hierarchical ordering by students. Processes of classifying groups proceeded from searching criteria for classifying to selecting criteria for classifying.

• Journal of KIISE:Software and Applications
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• v.37 no.3
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• pp.161-169
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• 2010

The requirement elicitation is the task of eliciting requirements from needs of stakeholders, and preparing for information for negotiation. However, there are methods for gathering needs, but there is no specific method for classifying them, generating information for negotiation. Therefore, To solve the problems, this paper proposes a method to classify requirement and to generate information for negotiation. The proposed methods use Kano model, statistical technique, and identifying relationship between requirements and problems within scope. Finally, we validate the proposed method on simulations, Rough Set Theory, and case study of model.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.794-798
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• 2009

We introduce an implementation of plug-ins on PLUTO. These plug-ins discriminate inflammatory nodules from other types of nodules in chest X-ray CT images. The PLUTO is a common platform for computer-aided diagnosis systems on Microsoft Windows series and it is easy to add new functions as plug-ins. We coded two plug-ins. One of the them calculates features based on medical knowledge. The other plug-in calculates parameters to classify the type of nodules, and it also classifies nodules into inflammatory nodules and others using SVM. These plug-ins are coded using MIST library which is produced at Nagoya University, Japan. In our previous study, the MIST library was parallelized, so that we can utilize a number of CPUs to calculate features and SVM learning/classifying depending on the amount of computation. Using these plug-ins, it became easy to extract features to discriminate inflammatory nodules from other types of nodules and to change parameters for feature extraction and SVM learning/classifying with GUI interface. The accuracy of the classifying result is 100% with 78 solid nodules which contains 43 inflammatory nodules and 35 other type of nodules.

• Korean Journal of Human Ecology
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• v.7 no.2
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• pp.63-73
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• 1998

To get well-fitted ready-made clothings with beautiful silhouettes, it's better to classify body forms into several forms and to assign sizing within each form than to grade just based on body size regardless of body styles. This study illucidated the importance of drop value in the results of surveying the current values of sizing and grading. Therefore, it's meaningful to get the classification of body form with appropriate distribution of drop values of the body, and the distribution of drop value and the frequency of each form is very helpful to name the combined sizing or coverage of ready-made clothes. This study aimed at classifying body forms with various drop values using multivariate analysis for sizing and grading. Factor analysis and cluster analysis were done using measured values from 346 unmarried women. The results are as follows: 1. The factor which explains body forms was obtained by factor analysis, and the representative major 18 items which have important roles in classifying body forms were selected among the measured values with high factor loading and communality. 2. The body forms were classified into 8 groups based on the charateristics, frequencies and distributions of them obtained from cluster analysis. 3. Each classified body form showed conspicuous difference in drop value and the difference of body form mainly resulted from the difference between waist and hip rather than the difference between bust circumference and waist in Korean unmarried women.

• Journal of the Korean Home Economics Association
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• v.38 no.10
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• pp.45-51
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• 2000

This study illucidated the importance of drop Value in the resets of surveying the current values of sizing and grading. Therefore, it is meaningful to get the classification of body form with the appropriate distribution of drop values of the body. The distribution of drop value and the frequency of each form is very helpful to name the combined sizing or coverage of ready-made clothes. This study aimed at classifying body forms with various drop values using multivariate analysis for sizing and grading. Factor analysis and cluster analysis were done using measured values from unmarried women. The resets are as follows; The factor which explains body forms was obtained by factor analysis, and the representative major 18 items which have important roles in classifying body forms were selected among the measured values with high factor loading and communality. 1) The body forms were classified into 3 groups based on the characteristics, frequencies and distributions of them obtained from cluster analysis. 2) Each classified body form showed conspicuous difference in drop value and the difference of body form mainly resulted from the difference between bust and hip(drop value) in Korean unmarried women. 3) Discriminant analysis showed that the most significant discriminant factor of the trunk classification were bust circumference, upper bust circumference, hip circumference and stature. 4) The cover ratio of size studied in this study for the Korean Sizing system for women's garment were founded high.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.4
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• pp.191-197
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• 2022

This study proposes an image-based Pose Intention Network (PIN) algorithm for rehabilitation via patients' intentions. The purpose of the PIN algorithm is for enabling an active rehabilitation exercise, which is implemented by estimating the patient's motion and classifying the intention. Existing rehabilitation involves the inconvenience of attaching a sensor directly to the patient's skin. In addition, the rehabilitation device moves the patient, which is a passive rehabilitation method. Our algorithm consists of two steps. First, we estimate the user's joint position through the OpenPose algorithm, which is efficient in estimating 2D human pose in an image. Second, an intention classifier is constructed for classifying the motions into three categories, and a sequence of images including joint information is used as input. The intention network also learns correlations between joints and changes in joints over a short period of time, which can be easily used to determine the intention of the motion. To implement the proposed algorithm and conduct real-world experiments, we collected our own dataset, which is composed of videos of three classes. The network is trained using short segment clips of the video. Experimental results demonstrate that the proposed algorithm is effective for classifying intentions based on a short video clip.