• Title/Summary/Keyword: component classification

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Multiscale Clustering and Profile Visualization of Malocclusion in Korean Orthodontic Patients : Cluster Analysis of Malocclusion

  • Jeong, Seo-Rin;Kim, Sehyun;Kim, Soo Yong;Lim, Sung-Hoon
    • International Journal of Oral Biology
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    • v.43 no.2
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    • pp.101-111
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    • 2018
  • Understanding the classification of malocclusion is a crucial issue in Orthodontics. It can also help us to diagnose, treat, and understand malocclusion to establish a standard for definite class of patients. Principal component analysis (PCA) and k-means algorithms have been emerging as data analytic methods for cephalometric measurements, due to their intuitive concepts and application potentials. This study analyzed the macro- and meso-scale classification structure and feature basis vectors of 1020 (415 male, 605 female; mean age, 25 years) orthodontic patients using statistical preprocessing, PCA, random matrix theory (RMT) and k-means algorithms. RMT results show that 7 principal components (PCs) are significant standard in the extraction of features. Using k-means algorithms, 3 and 6 clusters were identified and the axes of PC1~3 were determined to be significant for patient classification. Macro-scale classification denotes skeletal Class I, II, III and PC1 means anteroposterior discrepancy of the maxilla and mandible and mandibular position. PC2 and PC3 means vertical pattern and maxillary position respectively; they played significant roles in the meso-scale classification. In conclusion, the typical patient profile (TPP) of each class showed that the data-based classification corresponds with the clinical classification of orthodontic patients. This data-based study can provide insight into the development of new diagnostic classifications.

Light-weight Classification Model for Android Malware through the Dimensional Reduction of API Call Sequence using PCA

  • Jeon, Dong-Ha;Lee, Soo-Jin
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.11
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    • pp.123-130
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    • 2022
  • Recently, studies on the detection and classification of Android malware based on API Call sequence have been actively carried out. However, API Call sequence based malware classification has serious limitations such as excessive time and resource consumption in terms of malware analysis and learning model construction due to the vast amount of data and high-dimensional characteristic of features. In this study, we analyzed various classification models such as LightGBM, Random Forest, and k-Nearest Neighbors after significantly reducing the dimension of features using PCA(Principal Component Analysis) for CICAndMal2020 dataset containing vast API Call information. The experimental result shows that PCA significantly reduces the dimension of features while maintaining the characteristics of the original data and achieves efficient malware classification performance. Both binary classification and multi-class classification achieve higher levels of accuracy than previous studies, even if the data characteristics were reduced to less than 1% of the total size.

Classification of Microarray Gene Expression Data by MultiBlock Dimension Reduction

  • Oh, Mi-Ra;Kim, Seo-Young;Kim, Kyung-Sook;Baek, Jang-Sun;Son, Young-Sook
    • Communications for Statistical Applications and Methods
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    • v.13 no.3
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    • pp.567-576
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    • 2006
  • In this paper, we applied the multiblock dimension reduction methods to the classification of tumor based on microarray gene expressions data. This procedure involves clustering selected genes, multiblock dimension reduction and classification using linear discrimination analysis and quadratic discrimination analysis.

Confidence Intervals on Variance Components in Two-Way Classification with Interaction Model

  • Kim, Jung I.;Park, Sung H.
    • Journal of Korean Society for Quality Management
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    • v.10 no.1
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    • pp.7-12
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    • 1982
  • Arvesen (1969) has shown a procedure which produces an approximate confidence interval for a variance component in unbalanced one-way classification model. In this paper, his work is extended to the case when the model of interest is unbalanced two-way classification. Following the procedure described in this paper, approximate confidence intervals are computed by a Monte Carlo simulation.

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XML based Software Architecture Specification Language for Reuse (재사용을 위한 XML 기반 소프트웨어 아키텍쳐 명세 언어)

  • Lee, Yun-Su;Yun, Gyeong-Seop;Wang, Chang-Jong
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.3
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    • pp.808-817
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    • 2000
  • Component specification languages in consideration of reuse are essential factor in classification, verification and retrieval of components. A number of legacy specification languages have already been used, however, they are complex and include many necessary elements in the specification for implementation. In this paper, we present XML-based component specification and software architecture specification language to solve these problems of legacy specification languages. The presented specification languages consist of component specification, which is composed of signature specification, interface specification and message specification, and software architecture specification providing graphical notations and textural notations. Component specification supports component retrieval with behavioral match and black-box reuse of component. In addition to this, it improves the efficiency of retrieval and document management with XML-based component specification. Software architecture specification supports the structural reuse of architecture, which is white-box reuse, through mesage-based architecture specification.

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Image classification method using Independent Component Analysis and Gram-Schmidt method (독립성분해석 기법과 그람-슈미트 방법을 이용한 영상분리방법)

  • 홍준식;유정웅
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.04a
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    • pp.505-507
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    • 2001
  • 본 논문에서는 그람-슈미트 방법 및 독립 성분 해석(Independent Component Analysis, ICA)기법을 이용한 영상분리방법을 제안한다. 이 제안된 방법은 전처리 없이 ICA나 주성분 해석(Principal Component Analysis, PCA)을 이용한 것에 비해 개선된 영상을 보여준다. 이는 원래의 ICA 모델에 대하여 동일한 조건으로 일반화하여 그람-슈미트의 독립된 성분들이 ICA 모델에 충분히 동일하다는 것을 보여준다.

한강하류지형면의 분류와 지형발달에 대한 연구 (양수리에서 능곡까지)

  • Park, No-Sik
    • Journal of the Speleological Society of Korea
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    • no.68
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    • pp.23-73
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    • 2005
  • Purpose of study; The purpose of this study is specifically classified as two parts. The one is to attempt the chronological annals of Quaternary topographic surface through the study over the formation process of alluvial surfaces in our country, setting forth the alluvial surfaces lower-parts of Han River area, as the basic deposit, and comparing it to the marginal landform surfaces. The other is to attempt the classification of micro morphology based on the and condition premising the land use as a link for the regional development in the lower-parts of Han river area. Reasons why selected the Lower-parts of Han river area as study objects: 1. The change of river course in this area is very serve both in vertical and horizontal sides. With a situation it is very easy to know about the old geography related to the formation process of topography. 2. The component materials of gravel, sand, silt and clay are deposited in this area. Making it the available data, it is possible to consider about not oかy the formation process of topography but alsoon the development history to some extent. 3. The earthen vessel, a fossil shell fish, bone, cnarcoal and sea-weed are included in the alluvial deposition in this area. These can be also valuable data related to the chronological annals. 4. The bottom set conglometate beds is also included in the alluvial deposits. This can be also valuable data related to the research of geomorphological development. 5. Around of this area the medium landform surface, lower landform surface, pediment and basin, are existed, and these enable the comparison between the erosion surfaces and the alluvial surfaces. Approach : 1. Referring to the change of river beds, I have calculated the vertical and horizontal differences comparing the topographic map published in 1916 with that published in 1966 and through the field work 2. In classifying the landform, I have applied the method of micro morphological classification in accordance with the synthetic index based upon the land conditions, and furthermore used the classification method comparing the topographic map published in 1916 and in that of 1966. 3. I have accorded this classification with the classification by mapping through appliying the method of classification in the development history for the field work making the component materials as the available data. 4. I have used the component materials, which were picked up form the outcrop of 10 places and bored at 5 places, as the available data. 5. I have referred to Hydrological survey data of the ministry of Construction (since 1916) on the overflow of Han-river, and used geologic map of Seoul metropolitan area. Survey Data, and general map published in 1916 by the Japanese Army Survbey Dept., and map published in 1966 by the Construction Research Laboratory and ROK Army Survey Dept., respectively. Conclusion: 1. Classification of Morphology: I have added the historical consideration for development, making the component materials and fossil as the data, to the typical consideration in accordance with the map of summit level, reliefe and slope distribution. In connection with the erosion surface, I have divided into three classification such as high, medium and low-,level landform surfaces which were classified as high and low level landform surfaces in past. furthermore I have divided the low level landform surface two parts, namely upper-parts(200-300m) and bellow-parts(${\pm}100m$). Accordingly, we can recognize the three-parts of erosion surface including the medium level landform surface (500-600m) in this area. (see table 22). In condition with the alluvial surfaces I have classified as two landform surfaces (old and new) which was regarded as one face in past. Meamwhile, under the premise of land use, the synthetic, micro morphological classification based upon the land condition is as per the draw No. 19-1. This is the quite new method of classification which was at first attempted in this country. 2. I have learned that the change of river was most severe at seeing the river meandering rate from Dangjung-ni to Nanjido. As you seee the table and the vertical and horizontal change of river beds is justly proportionable to the river meandering rate. 3. It can be learned at seeing the analysis of component materials of alluvial deposits that the component from each other by areas, however, in the deposits relationship upper stream, and between upper parts and below parts I couldn't always find out the regular ones. 4. Having earthern vessel, shell bone, fossil charcoal and and seaweeds includen in the component materials such as gravel, clay, sand and silt in Dukso and Songpa deposits area. I have become to attempt the compilation of chronicle as yon see in the table 22. 5. In according to hearing of basemen excavation, the bottom set conglomerate beds of Dukso beds of Dukso-beds is 7m and Songpa-beds is 10m. In according to information of dredger it is approx. 20m in the down stream. 6. Making these two beds as the standard beds, I have compared it to other beds. 7 The coarse sand beds which is covering the clay-beds of Dukso-beds and Nanjidobeds is shown the existence of so-called erosion period which formed the gap among the alluvial deposits of stratum. The former has been proved by the sorting, bedding and roundness which was supplied by the main stream and later by the branch stream, respectively. 8. If the clay-beds of Dukeo-bed and Songpa-bed is called as being transgressive overlap, by the Eustatic movement after glacial age, the bottom set conglomerate beds shall be called as being regressive overlap at the holocene. This has the closest relationship with the basin formation movement of Seoul besides the Eustatic movement. 9. The silt-beds which is the main component of deposits of flood plain, is regarded as being deposited at the Holocene in the comb ceramic and plain pottery ages. This has the closest relationship with the change of river course and river beds.

Music Genre Classification Based on Timbral Texture and Rhythmic Content Features

  • Baniya, Babu Kaji;Ghimire, Deepak;Lee, Joonwhon
    • Proceedings of the Korea Information Processing Society Conference
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    • 2013.05a
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    • pp.204-207
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    • 2013
  • Music genre classification is an essential component for music information retrieval system. There are two important components to be considered for better genre classification, which are audio feature extraction and classifier. This paper incorporates two different kinds of features for genre classification, timbral texture and rhythmic content features. Timbral texture contains several spectral and Mel-frequency Cepstral Coefficient (MFCC) features. Before choosing a timbral feature we explore which feature contributes less significant role on genre discrimination. This facilitates the reduction of feature dimension. For the timbral features up to the 4-th order central moments and the covariance components of mutual features are considered to improve the overall classification result. For the rhythmic content the features extracted from beat histogram are selected. In the paper Extreme Learning Machine (ELM) with bagging is used as classifier for classifying the genres. Based on the proposed feature sets and classifier, experiment is performed with well-known datasets: GTZAN databases with ten different music genres, respectively. The proposed method acquires the better classification accuracy than the existing approaches.

A Study on Road Characteristic Classification using Exploratory Factor Analysis (탐색적 요인분석을 이용한 도로특성분류에 관한 연구)

  • Cho, Jun-Han;Kim, Seong-Ho;Rho, Jeong-Hyun
    • Journal of Korean Society of Transportation
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    • v.26 no.3
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    • pp.53-66
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    • 2008
  • This research is to the establishment of a conceptual framework that supports road characteristic classification from a new point of view in order to complement of the existing road functional classification and examine of traffic pattern. The road characteristic classification(RCC) is expected to use important performance criteria that produced a policy guidelines for transportation planning and operational management. For this study, the traffic data used the permanent traffic counters(PTCs) located within the national highway between 2002 and 2006. The research has described for a systematic review and assessment of how exploratory factor analysis should be applied from 12 explanatory variables. The optimal number of components and clusters are determined by interpretation of the factor analysis results. As a result, the scenario including all 12 explanatory variables is better than other scenarios. The four components is produced the optimal number of factors. This research made contributions to the understanding of the exploratory factor analysis for the road characteristic classification, further applying the objective input data for various analysis method, such as cluster analysis, regression analysis and discriminant analysis.