• Title/Summary/Keyword: Profile Classification

Search Result 259, Processing Time 0.025 seconds

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
    • /
    • v.43 no.2
    • /
    • pp.101-111
    • /
    • 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.

A Wavelet-based Profile Classification using Support Vector Machine (SVM을 이용한 웨이블릿기반 프로파일분류에 관한 연구)

  • Kim, Seong-Jun
    • Proceedings of the Korean Institute of Intelligent Systems Conference
    • /
    • 2008.04a
    • /
    • pp.3-6
    • /
    • 2008
  • 베어링은 각종 설비에서 활용하는 중요한 기계요소 중 하나이다. 설비고장의 상당수는 베어링의 결함이나 파손에 기인하고 있다. 따라서 베어링에 대한 온라인모니터링기술은 설비의 정지를 예방하고 손실을 줄이는 데 필수적이다. 본 논문은 진동신호를 이용하여 베어링의 상태를 예측하기 위한 온라인모니터링에 대해 연구한다. 프로파일로 주어지는 진동신호는 이산웨이블릿변환을 통해 분석되고, 분해수준별 웨이블릿계수로부터 얻은 통계적 특징 중 유의한 것을 선별하고자 분산분석 (ANOVA)을 이용한다. 선별된 특징벡터는 Support Vector Machine (SVM)의 입력이 되는 데, 본 논문에서는 다중클래스 분류문제를 다루기 위한 계층적 SVM 네트워크를 제안한다.

  • PDF

Wide-Angle Radar Target Classification with Subclass Concept (Subclass 개념을 이용한 넓은 관측각에서의 레이더 표적인식 성능향상에 관한 연구)

  • 서동규;김경태;김효태
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
    • /
    • v.13 no.8
    • /
    • pp.777-782
    • /
    • 2002
  • The range profile is easily obtainable and promising feature vector in the aspect of real-time radar target recognition system. However, the range profile is highly dependent on a aspect angle of a target and this dependence make it difficult the recognition over wide-angular region. In this paper, we propose the classifier with subclass concept in order to solve this dependence problem. Recognition results using six aircraft models measured at compact range facility are presented to show the effectiveness of this proposed classifier over wide-angular region.

Case Study of the Precipitation System Occurred Around Cheongju Using Convective/Stratiform Radar Echo Classification Algorithm (레이더 반사도 유형분류 알고리즘을 이용한 청주 부근에서 관측된 강우시스템의 사례 분석)

  • Nam, Kyung-Yeub;Lee, Jeong-Seog;Nam, Jae-Cheol
    • Atmosphere
    • /
    • v.15 no.3
    • /
    • pp.155-165
    • /
    • 2005
  • The characteristics of six precipitation systems occurred around Cheongju in 2002 are analyzed after the convective/stratiform radar echo classification using radar reflectivity from the Meteorological Research Institute"s X-band Doppler weather radar. The Biggerstaff and Listemaa (2000) algorithm is applied for the classification and reveals a physical characteristics of the convective and stratiform rain diagnosed from the three-dimensional structure of the radar reflectivity. The area satisfying the vertical profile of radar reflectivity is well classified, while the area near the radar site and the topography-shielded area show a mis-classification. The seasonal characteristics of the precipitation system are also analyzed using the contoured frequency by altitude diagrams (CFADs). The heights of maximum reflectivity are 4 km and 5.5 km in spring and summer, respectively, and the vertical gradient of radar reflectivity from 1.5 km to the melting layer in spring is larger than in summer.

A Study on Gender Classification Based on Diagonal Local Binary Patterns (대각선형 지역적 이진패턴을 이용한 성별 분류 방법에 대한 연구)

  • Choi, Young-Kyu;Lee, Young-Moo
    • Journal of the Semiconductor & Display Technology
    • /
    • v.8 no.3
    • /
    • pp.39-44
    • /
    • 2009
  • Local Binary Pattern (LBP) is becoming a popular tool for various machine vision applications such as face recognition, classification and background subtraction. In this paper, we propose a new extension of LBP, called the Diagonal LBP (DLBP), to handle the image-based gender classification problem arise in interactive display systems. Instead of comparing neighbor pixels with the center pixel, DLBP generates codes by comparing a neighbor pixel with the diagonal pixel (the neighbor pixel in the opposite side). It can reduce by half the code length of LBP and consequently, can improve the computation complexity. The Support Vector Machine is utilized as the gender classifier, and the texture profile based on DLBP is adopted as the feature vector. Experimental results revealed that our approach based on the diagonal LPB is very efficient and can be utilized in various real-time pattern classification applications.

  • PDF

Discrepancies in Soft Tissue Profile of Patients for Orthognathic Surgery between Preoperative Lateral Facial Photograph, Lateral Cephalogram and Supine Position on Operation Table

  • Jung, Young-Eun;Yang, Hoon-Joo;Hwang, Soon-Jung
    • Maxillofacial Plastic and Reconstructive Surgery
    • /
    • v.34 no.3
    • /
    • pp.180-185
    • /
    • 2012
  • Purpose: An accurate preoperative analysis of the patient is essential in orthognathic surgery in order to acquire superior results. In profile, the location of the chin's position may change according to the neck's inclination. This may ultimately affect the amount of surgical movement. During acquisition of cephalometric radiographs, or in supine position, there is a discrepancy in the neck's inclination. This means that there are also various discrepancies between the actual profile and the various preoperative profile images. In the clinical situation, the decision in performing genioplasty usually lies in the analysis of the patient's profile on the operating table at the final stages of orthognathic surgery. This study aims to analyze the different preoperative profile images and to compare their discrepancies. Methods: Fifty eight patients undergoing orthognathic surgery were chosen. These patients were divided into three groups according to angle's classification of malocclusion, as class I, II or III. The right profile of these patients in centric occlusion was taken in natural head position (NHP). This was set as the 'actual profile image.' Another right profile image was taken on the operating table after insertion of the nasotracheal intubation and with muscle relaxants in effect. This was also taken in centric occlusion. The angle (denoted 'A') between the soft tissue glabella-pognion and the true vertical plane was found in the above-mentioned profile images and in the cephalometric radiographs. The differences of these values were analyzed. Results: There were differences in Angle 'A' in all of the preoperative images. These values were however, not statistically significant. Conclusion: In order to gain an esthetic profile during orthognathic surgery, the NHP is shown to be the most reliable position. Images reproducing such head positions should be used in the treatment planning process.

A Study on the Characteristics of Facial Shape in Adult Women by Sasang Constitution Using Hyungsang Classification (형상분류를 이용한 성인여성의 체질별 안면형태 특징에 관한 연구)

  • Jeon, Soo-Hyung;Kim, Jong-Won
    • Journal of Sasang Constitutional Medicine
    • /
    • v.29 no.2
    • /
    • pp.95-103
    • /
    • 2017
  • Objectives This study was aimed to analyze characteristics of facial shapes in adult women by sasang constitution using hyungsang classification. Methods Using a digital camera, we took a picture of 1,011 women who participated in clinical study on menstrual pain and acquired their 3D facial images with a face-only scanner. They filled out SSCQ-P(sasang constitution questionnaire for patient) for the diagnosis of sasang constitution. Based on the above photographs and 3D images, one of the hyungsang medicine specialist diagnosed according to five diagnostic criteria. The sasang constitution was diagnosed by referring to questionnaires and photographs. Frequency analysis was performed using the statistical analysis system version 9.4 and chi-square test was performed for validity evaluation. Results In taeeumin, the wide face shape(n=261, 74.36%) was much more than the narrow shape(n=90, 25.64%) and the convex face profile(n=164, 85.86%) was much more than the concave profile(n=27, 14.14%). Regardless of sasang constitution, angular face shape(n=501, 50%) was the most, followed by oval shape(n=317, 31.64%). Subjects with big ears(n=291, 29.19%) were the most, while big eyes(n=104, 10.43%) were the least. Subjects with eyes and nose tip upward(n=615, 78.05%) were the most, while eyes and nose tip downward(n=22, 2.79%) were the least. Conclusions Most Korean adult women have angular face, such as square or diamond, with slanted eyes and upturned nose. Taeeumin women have wide facial shape and convex profile.

Hierarchical Automatic Classification of News Articles based on Association Rules (연관규칙을 이용한 뉴스기사의 계층적 자동분류기법)

  • Joo, Kil-Hong;Shin, Eun-Young;Lee, Joo-Il;Lee, Won-Suk
    • Journal of Korea Multimedia Society
    • /
    • v.14 no.6
    • /
    • pp.730-741
    • /
    • 2011
  • With the development of the internet and computer technology, the amount of information through the internet is increasing rapidly and it is managed in document form. For this reason, the research into the method to manage for a large amount of document in an effective way is necessary. The conventional document categorization method used only the keywords of related documents for document classification. However, this paper proposed keyword extraction method of based on association rule. This method extracts a set of related keywords which are involved in document's category and classifies representative keyword by using the classification rule proposed in this paper. In addition, this paper proposed the preprocessing method for efficient keywords creation and predicted the new document's category. We can design the classifier and measure the performance throughout the experiment to increase the profile's classification performance. When predicting the category, substituting all the classification rules one by one is the major reason to decrease the process performance in a profile. Finally, this paper suggested automatically categorizing plan which can be applied to hierarchical category architecture, extended from simple category architecture.

A proper folder recommendation technique using frequent itemsets for efficient e-mail classification (효과적인 이메일 분류를 위한 빈발 항목집합 기반 최적 이메일 폴더 추천 기법)

  • Moon, Jong-Pil;Lee, Won-Suk;Chang, Joong-Hyuk
    • Journal of the Korea Society of Computer and Information
    • /
    • v.16 no.2
    • /
    • pp.33-46
    • /
    • 2011
  • Since an e-mail has been an important mean of communication and information sharing, there have been much effort to classify e-mails efficiently by their contents. An e-mail has various forms in length and style, and words used in an e-mail are usually irregular. In addition, the criteria of an e-mail classification are subjective. As a result, it is quite difficult for the conventional text classification technique to be adapted to an e-mail classification efficiently. An e-mail classification technique in a commercial e-mail program uses a simple text filtering technique in an e-mail client. In the previous studies on automatic classification of an e-mail, the Naive Bayesian technique based on the probability has been used to improve the classification accuracy, and most of them are on an e-mail in English. This paper proposes the personalized recommendation technique of an email in Korean using a data mining technique of frequent patterns. The proposed technique consists of two phases such as the pre-processing of e-mails in an e-mail folder and the generating a profile for the e-mail folder. The generated profile is used for an e-mail to be classified into the most appropriate e-mail folder by the subjective criteria. The e-mail classification system is also implemented, which adapts the proposed technique.