• Title/Summary/Keyword: Profile Classification

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Study on the Applicability of CPT Based Soil Classification Chart (콘관입시험결과를 이용한 흙분류차트의 적용성에 관한 연구)

  • Kim, Chan-Hong;Im, Jong-Chul;Kim, Young-Sang
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.5C
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    • pp.293-301
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    • 2008
  • Soil profiling is one of the most important work among geotehnical engineering practice. Generally, soil profile is estimated from the observation of soil samples during subsurface exploration but such estimation also includes some experiencing aspects such as flushed water from the borehole, slime colour, boring speed and so on. In addition, since the capacity of hydraulic drill rig is significantly increased, thin layers might be easily missed. So, continuous soil profile is almost impossible over all depth to be bored from conventional subsurface exploration. While CPT or CPTu can serve continuous soil profile information over all depth generally in 5cm interval. Many charts or methods for soil profile from CPT result have been proposed during last several decades over the world. However they have not been verified in local ground condition in Korea. In this research, CPT results and soil classification results based on USCS were compiled from 17 sites over the Korea. Soil classification results by using 7 CPT soil classification charts were compared with those of USCS for the compiled database. Most proper CPT soil classification chart for Korean soil characteristics was evaluated and effective parameters for the soil classification from CPT were discussed. Finally interrelationship between CPT soil classification chart and USCS soil classification was evaluated.

A STUDY ON THE FACIAL ESTHETIC PREFERENCES AMONG KOREAN YOUTHS: ASSESSMENT OF PROFILE PREFERENCES (한국 젊은이의 안면미 선호경향에 관한 연구 : 얼굴의 측모평가를 중심으로)

  • Song, Sejin;Choi, Ik-chan
    • The korean journal of orthodontics
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    • v.22 no.4 s.39
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    • pp.881-920
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    • 1992
  • This study was designed to assess profile preferences among Korean youths in the year 1992. Facial esthetics was evaluated by means of silhouette profiles, eliminating the influence of a number of aspects that may affect judgment when normal lateral photographs are used. The main points of preference to be clarified here are as follows. First, on facial convexity, Second, on nasion depth, Third, on mentolabial sulcus depth, Fourth, on the position of upper and lower lips, Fifth, on facial type according to Angle's classification of malocclusion, Sixth, on Song's tangents. The 54 subjects printed in questionnaire as black and white silhouettes were selected from 300 tracings from cephalometric radiographs of people whose age ranging from 11 to 20 years. Photographs of six female subjects were retouched by computer graphic software and printed in color and black/white photographs which were used for adaptation of eyes of participants in selecting profiles in silhouette. They constitute 2 questions. The 54 subjects were grouped as 22 questions, each of them composed of 6 subjects, according to the aspects to be clarified. Twenty four questions in total were asked to assess profile preferences. For the assessment, the profile line, the facial esthetic triangle, Song's tangents, and Angle's classification of malocclusion were introduced. The profile line is composed of 11 component points which are Trichion, Glabella, Nasion, Pronasale, Subnasale, Labrale superius, Stomion, Labrale inferius, Supramentale, Pogonion, and Gnathion. The facial esthetic triangle is composed of 3 tangents: A-tangent which is the tangent of dorsum of nose, B-tangent which is the line passing through Sn and Ls, and C-tangent which is drawn on the turning point of the curve which lies between mentolabial sulcus (Sm) and pogonion (Pg). Angle's classification has 3 types of malocclusion which are Class I, Class II, and Class III. Class II malocclusion is subdivided into Division 1 and Division 2. The participants of the survey were composed of 861 college students (448 male students, 413 female students) whose majors grouped as Fine Arts. Liberal Arts, and Natural Sciences, and whose mean age 21.8 years. The statistics program SPSS/PC + of SPSS Inc. was used to analyze answers of participants. Crosstabulation, Chi-square test, and Kendall test were done. The conclusions are as follows: First, Korean youths have a tendency to prefer the slightly convex face to the flat or concave face. Second, they prefer a moderately deep nasion. Third, they prefer a moderately deep mentolabial sulcus. Fourth, they prefer the position of lips which are near to Ricketts' E-line. The position of the upper lip which is slightly posterior to E-line is preferred. The upper lip which lies too far anterior or posterior to the lower lip is not perferred. Fifth, they prefer most, according to Angle's Classification of Malocclusion, Class I facial profile which has a slight inclination to Class II division 2. The order of preference is Class I, Class II division 2, Class III, and Class II division 1. Sixth, they prefer the type 2 and 3 of Song's tangents. The facial profile within which A-and B-tangent meet is preferred. The facial profile which has Cotangent that .meets with A-tangent slightly posterior to the crossing point of A-and B-tangent or that parallels with B-tangent is preferred.

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Video Data Classification based on a Video Feature Profile (특성정보 프로파일에 기반한 동영상 데이터 분류)

  • Son Jeong-Sik;Chang Joong-Hyuk;Lee Won-Suk
    • The KIPS Transactions:PartD
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    • v.12D no.1 s.97
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    • pp.31-42
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    • 2005
  • Generally, conventional video searching or classification methods are based on its meta-data. However, it is almost Impossible to represent the precise information of a video data by its meta-data. Therefore, a processing method of video data that is based on its meta-data has a limitation to be efficiently applied in application fields. In this paper, for efficient classification of video data, a classification method of video data that is based on its low-level data is proposed. The proposed method extracts the characteristics of video data from the given video data by clustering process, and makes the profile of the video data. Subsequently. the similarity between the profile and video data to be classified is computed by a comparing process of the profile and the video data. Based on the similarity. the video data is classified properly. Furthermore, in order to improve the performance of the comparing process, generating and comparing techniques of integrated profile are presented. A comparing technique based on a differentiated weight to improve a result of a comparing Process Is also Presented. Finally, the performance of the proposed method is verified through a series of experiments using various video data.

Development of Diagnostic System for Winding Profile Abnormality of Hot Coils (열연코일 권취형상 불량 자동진단 시스템 개발)

  • Lee, Sung-Jin
    • Proceedings of the KSME Conference
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    • 2000.11a
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    • pp.590-595
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    • 2000
  • On the contrary to the increasing needs of shape qualities, most of quality inspections are carried out by manual or operator's insight. To find the causes of shape inferiority, it is required to gather and analyze the shape measurement data. As a result the winding profile measurement system ($TELE-SCANNER^{(R)}$) is developed to analyze the coiling process and automate the manual measuring process for winding profile of hot-rolled coils. The winding profile measurement system measures and analyzes winding profile shapes of hot-rolled coils, and classifies them into several dominant patterns that are related to normal or abnormal mechanical conditions of down-coiler. The system also contains analysis software to quantify the winding profile shapes and patterns, and to produce statistics to help search the causes of profile shape inferiority.

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Ensemble Model using Multiple Profiles for Analytical Classification of Threat Intelligence (보안 인텔리전트 유형 분류를 위한 다중 프로파일링 앙상블 모델)

  • Kim, Young Soo
    • The Journal of the Korea Contents Association
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    • v.17 no.3
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    • pp.231-237
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    • 2017
  • Threat intelligences collected from cyber incident sharing system and security events collected from Security Information & Event Management system are analyzed and coped with expanding malicious code rapidly with the advent of big data. Analytical classification of the threat intelligence in cyber incidents requires various features of cyber observable. Therefore it is necessary to improve classification accuracy of the similarity by using multi-profile which is classified as the same features of cyber observables. We propose a multi-profile ensemble model performed similarity analysis on cyber incident of threat intelligence based on both attack types and cyber observables that can enhance the accuracy of the classification. We see a potential improvement of the cyber incident analysis system, which enhance the accuracy of the classification. Implementation of our suggested technique in a computer network offers the ability to classify and detect similar cyber incident of those not detected by other mechanisms.

A Recommendation System using Dynamic Profiles and Relative Quantification

  • Lee, Se-Il;Lee, Sang-Yong
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.7 no.3
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    • pp.165-170
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    • 2007
  • Recommendation systems provide users with proper services using context information being input from many sensors occasionally under ubiquitous computing environment. But in case there isn't sufficient context information for service recommendation in spite of much context information, there can be problems of resulting in inexact result. In addition, in the quantification step to use context information, there are problems of classifying context information inexactly because of using an absolute classification course. In this paper, we solved the problem of lack of necessary context information for service recommendation by using dynamic profile information. We also improved the problem of absolute classification by using a relative classification of context information in quantification step. As the result of experiments, expectation preference degree was improved by 7.5% as compared with collaborative filtering methods using an absolute quantification method where context information of P2P mobile agent is used.

A CEPHALOMETRIC STUDY ON THE SOFT TISSUE PROFILE CHANGES BY ORTHODONTIC TREATMENT IN FEMALE PATIENTS (여자 부정교합자의 치료전후 연조직 측모 변화에 관한 두부 방사선학적 연구)

  • Park, Sook-Kyu;Suhr, Cheong-Hoon
    • The korean journal of orthodontics
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    • v.21 no.1 s.33
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    • pp.113-130
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    • 1991
  • This study was undertaken to investigate soft tissue profile changes by orthodontic treatment in female patients. Traditional cephalometric appraisal yields data of dubious scientific value, the soft tissue profile forms were evaluated by finite element method. The subject was divided into three groups according to Angle's classification and each group was composed of 25 female patients averaged aged 12-14 years at the start of treatment. The changes in soft tissue form were evaluated by computing the degree of distortion in each triangle after treatment compared with the triangle before treatment. The conclusions were as follows; 1. The soft tissue profile forms were evaluated by finite element method and independent evaluation of each element by local changes was possible. 2. Maximum and minimum principal strains showed marked variability depending on the particular finite element and each group and Class II, III sample was greater than Class I sample. 3. Soft tissue size changes as a result of orthodontic treatment was not related to those of shape. 4. Soft tissue changes by orthodontic treatment were variable in individual patient, and were not related to Angle's classification.

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Investigating Students' Profiles of Mathematical Modeling: A Latent Profile Analysis in PISA 2012

  • SeoJin Jeong;Jihyun Hwang;Jeong Su Ahn
    • Research in Mathematical Education
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    • v.26 no.3
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    • pp.235-252
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    • 2023
  • We investigated the classification of learner groups for students' mathematical modeling competency and analyzed the characteristics in each profile group for each country and variable using PISA 2012 data from six countries. With a perspective on measuring sub-competency, we applied the latent profile analysis method to student achievement for mathematical modeling variables - Formulate, Employ, Interpret. The findings showed the presence of 4-6 profile groups, with the variables exhibiting high and low achievement within each profile group varying by country, and a hierarchical structure was observed in the profile group distribution in all countries, interestingly, the Formulate variable showed the largest difference between high-achieving and low-achieving profile groups. These results have significant implications. Comparison by country, variable, and profile group can provide valuable insights into understanding the various characteristics of students' mathematical modeling competency. The Formulate variable could serve as the most suitable predictor of a student's profile group and the score range of other variables. We suggest further studies to gain more detailed insights into mathematical modeling competency with different cultural contexts.

Classifying Cancer Using Partially Correlated Genes Selected by Forward Selection Method (전진선택법에 의해 선택된 부분 상관관계의 유전자들을 이용한 암 분류)

  • 유시호;조성배
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.3
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    • pp.83-92
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    • 2004
  • Gene expression profile is numerical data of gene expression level from organism measured on the microarray. Generally, each specific tissue indicates different expression levels in related genes, so that we can classify cancer with gene expression profile. Because not all the genes are related to classification, it is needed to select related genes that is called feature selection. This paper proposes a new gene selection method using forward selection method in regression analysis. This method reduces redundant information in the selected genes to have more efficient classification. We used k-nearest neighbor as a classifier and tested with colon cancer dataset. The results are compared with Pearson's coefficient and Spearman's coefficient methods and the proposed method showed better performance. It showed 90.3% accuracy in classification. The method also successfully applied to lymphoma cancer dataset.