• Title/Summary/Keyword: Method of Expression

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The Effects of Child Abuse Experience and Anger Expression on the Method of Resolving Interpersonal Conflicts (아동학대경험과 분노표출이 대인간 갈등해결방식에 미치는 영향)

  • Lee, Seo-Won;Han, Ji-Sook
    • Journal of the Korean Home Economics Association
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    • v.49 no.5
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    • pp.71-80
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    • 2011
  • The purpose of this study was to investigate the mediating effects of anger expression on the relationship between child abuse experience and the method of resolving interpersonal conflicts. For the study, 3,050 4th to 6th grade children from Kyunggi-do were sampled. The collected data were analyzed using simple regression, multi regression and a path analysis. This study showed that child abuse experience influenced the method of resolving the interpersonal conflicts via the expression of anger. In other words, anger expression could function as a pathway between child abuse experience and the method of resolving interpersonal conflicts.

The Sliding Window Gene-Shaving Algorithm for Microarray Data Analysis

  • 이혜선;최대우;전치혁
    • Proceedings of the Korean Society for Bioinformatics Conference
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    • 2002.06a
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    • pp.139-152
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    • 2002
  • Gene-shaving(Hastie et al, 2000) is a very useful method to identify a meaningful group of genes when the variation of expression is large. By shaving off the low-correlated genes with the leading principal component, the primary genes with the coherent expression pattern can be identified. Gene-shaving method works well If expression levels are varied enough, but it may not catch the meaningful cluster in low expression level or different expression time even with coherent patterns. The sliding window gene-shaving method which is to apply gene-shaving in each sliding window after hierarchical clustering is to compensate losing a meaningful set of genes whose variation is not large but distinct. The performance to identify expression patterns is compared for the simulated profile data by the different variance and expression level.

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Informative Gene Selection Method in Tumor Classification

  • Lee, Hyosoo;Park, Jong Hoon
    • Genomics & Informatics
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    • v.2 no.1
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    • pp.19-29
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    • 2004
  • Gene expression profiles may offer more information than morphology and provide an alternative to morphology- based tumor classification systems. Informative gene selection is finding gene subsets that are able to discriminate between tumor types, and may have clear biological interpretation. Gene selection is a fundamental issue in gene expression based tumor classification. In this report, techniques for selecting informative genes are illustrated and supervised shaving introduced as a gene selection method in the place of a clustering algorithm. The supervised shaving method showed good performance in gene selection and classification, even though it is a clustering algorithm. Almost selected genes are related to leukemia disease. The expression profiles of 3051 genes were analyzed in 27 acute lymphoblastic leukemia and 11 myeloid leukemia samples. Through these examples, the supervised shaving method has been shown to produce biologically significant genes of more than $94\%$ accuracy of classification. In this report, SVM has also been shown to be a practicable method for gene expression-based classification.

Risk Situation Recognition Using Facial Expression Recognition of Fear and Surprise Expression (공포와 놀람 표정인식을 이용한 위험상황 인지)

  • Kwak, Nae-Jong;Song, Teuk Seob
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.3
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    • pp.523-528
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    • 2015
  • This paper proposes an algorithm for risk situation recognition using facial expression. The proposed method recognitions the surprise and fear expression among human's various emotional expression for recognizing risk situation. The proposed method firstly extracts the facial region from input, detects eye region and lip region from the extracted face. And then, the method applies Uniform LBP to each region, discriminates facial expression, and recognizes risk situation. The proposed method is evaluated for Cohn-Kanade database image to recognize facial expression. The DB has 6 kinds of facial expressions of human being that are basic facial expressions such as smile, sadness, surprise, anger, disgust, and fear expression. The proposed method produces good results of facial expression and discriminates risk situation well.

A Study on the Transformal Usage of Visual Information in Architectural Diagrams - Focusing on the Projects by Rem Koolhaas and MVRDV - (건축다이어그램에 나타난 시각정보의 변음방식에 관한 연구 - 렘 쿨하스와 MVRDV의 프로젝트를 중심으로 -)

  • Park, Young-Ho
    • Korean Institute of Interior Design Journal
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    • v.17 no.6
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    • pp.71-81
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    • 2008
  • The purposes of this research are to correctly understand the relationship between a visual communication structure and a semantic communication structure when integrating and changing various architectural visual information. This study will classify various diagrams, which have been actively applied to the works of Rem Koolhaas and MVRDV when designing architecture, and based on the classification, it will analyze how the expression viewpoints inherent in the diagrams are changed and applied to processing and changing architectural visual information. The transformal usage of the visual information of architectural diagrams is classified into an analysis-centered processing method and a concept-centered processing method, and the characteristics of their usage are analyzed. The former shows an observer-centered expression viewpoint which effectively delivers an architect's analyzed architectural information or intent to a customer or an observer. It also allows an easy perception of the analyzed data, and uses qualitative expression viewpoints. The method combines systematic expression viewpoints, which value a relationship with visual information, and various architectural visual information; uses the combined expression viewpoints as one diagram for delivering various information simultaneously and for changing visual information. The latter shows author-centered subjective expression viewpoints, which are different from reproduction-centered fixed expression viewpoints. This method uses arbitrary expression viewpoints that overly extort, change or manipulate visual information. It shows simultaneous expression viewpoints that integrate various architectural visual information via omniscient expression viewpoints, such as reversing or projecting the points of viewing subjects, which human beings cannot perceive.

A Study on the Expansion Methodology of Creative Fashion Design (크리에이티브 패션 디자인의 전개 방법에 관한 연구)

  • Kong Mi-Sun;Chae Keum-Seok
    • Journal of the Korean Society of Costume
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    • v.55 no.2 s.92
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    • pp.45-57
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    • 2005
  • The creative fashion design is the technique which ran be obtained through the structural analysis of the relationship between principle, element-combination and idea-expression. In the research, as the results of theoretical survey of design structure and idea-expression, the structural and subjective designs are classified and defined: a. the structural design is analyzed with the existing examples based on the combinational Idea-expression of the O.C.L method, and b. the subjective design is also analyzed connecting the real examples to Cordon method, Synetic method, Association method, and expansive idea-expression-method obtained by the Experiences of Geometrical Combinations. The research can be summarized as follows: 1. The creative fashion design which emphasizes the geometrical structure utilizes the modification method whirh combines the shapes and constructs extraordinary structural beauty coming from the complex structural principle, that is, emphasis and balance. 2. The creative fashion design which emphasizes specific subjects utilizes the modification method which mimics representative and plastic resemblances and constructs symbolic structural beauty coming from the simple structural principle, that is, material elements.

Facial Expression Recognition Method Based on Residual Masking Reconstruction Network

  • Jianing Shen;Hongmei Li
    • Journal of Information Processing Systems
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    • v.19 no.3
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    • pp.323-333
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    • 2023
  • Facial expression recognition can aid in the development of fatigue driving detection, teaching quality evaluation, and other fields. In this study, a facial expression recognition method was proposed with a residual masking reconstruction network as its backbone to achieve more efficient expression recognition and classification. The residual layer was used to acquire and capture the information features of the input image, and the masking layer was used for the weight coefficients corresponding to different information features to achieve accurate and effective image analysis for images of different sizes. To further improve the performance of expression analysis, the loss function of the model is optimized from two aspects, feature dimension and data dimension, to enhance the accurate mapping relationship between facial features and emotional labels. The simulation results show that the ROC of the proposed method was maintained above 0.9995, which can accurately distinguish different expressions. The precision was 75.98%, indicating excellent performance of the facial expression recognition model.

A Method for Computing the Network Reliability of a Computer Communication Network

  • Ha, Kyung-Jae;Seo, Ssang-Hee
    • Proceedings of the Korea Multimedia Society Conference
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    • 1998.10a
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    • pp.202-207
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    • 1998
  • The network reliability is to be computed in terms of the terminal reliability. The computation of a terminal reliability is started with a Boolean sum of products expression corresponding to simple paths of the pair of nodes. This expression is then transformed into another equivalent expression to be a Disjoint Sum of Products form. But this computation of the terminal reliability obviously does not consider the communication between any other nodes but for the source and the sink. In this paper, we derive the overall network reliability which all other remaining nodes. For this, we propose a method to make the SOP disjoint for deriving the network reliability expression from the system success expression using the modified Sheinman's method. Our method includes the concept of spanning trees to find the system success function by the Cartesian products of vertex cutsets.

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A modified partial least squares regression for the analysis of gene expression data with survival information

  • Lee, So-Yoon;Huh, Myung-Hoe;Park, Mira
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.5
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    • pp.1151-1160
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    • 2014
  • In DNA microarray studies, the number of genes far exceeds the number of samples and the gene expression measures are highly correlated. Partial least squares regression (PLSR) is one of the popular methods for dimensional reduction and known to be useful for the classifications of microarray data by several studies. In this study, we suggest a modified version of the partial least squares regression to analyze gene expression data with survival information. The method is designed as a new gene selection method using PLSR with an iterative procedure of imputing censored survival time. Mean square error of prediction criterion is used to determine the dimension of the model. To visualize the data, plot for variables superimposed with samples are used. The method is applied to two microarray data sets, both containing survival time. The results show that the proposed method works well for interpreting gene expression microarray data.

A Facial Expression Recognition Method Using Two-Stream Convolutional Networks in Natural Scenes

  • Zhao, Lixin
    • Journal of Information Processing Systems
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    • v.17 no.2
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    • pp.399-410
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    • 2021
  • Aiming at the problem that complex external variables in natural scenes have a greater impact on facial expression recognition results, a facial expression recognition method based on two-stream convolutional neural network is proposed. The model introduces exponentially enhanced shared input weights before each level of convolution input, and uses soft attention mechanism modules on the space-time features of the combination of static and dynamic streams. This enables the network to autonomously find areas that are more relevant to the expression category and pay more attention to these areas. Through these means, the information of irrelevant interference areas is suppressed. In order to solve the problem of poor local robustness caused by lighting and expression changes, this paper also performs lighting preprocessing with the lighting preprocessing chain algorithm to eliminate most of the lighting effects. Experimental results on AFEW6.0 and Multi-PIE datasets show that the recognition rates of this method are 95.05% and 61.40%, respectively, which are better than other comparison methods.