• Title/Summary/Keyword: Feature(s)

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Preschool Children's Understanding of the Graphic Features of Writing

  • Mortensen, Jennifer;Burnham, Melissa
    • Child Studies in Asia-Pacific Contexts
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    • v.2 no.1
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    • pp.45-60
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    • 2012
  • This project examined 2, 3, and 4-year-old children (N = 34) in a university campus child care setting to assess their understanding of the graphic features they use in their emergent writing (to distinguish it from a drawing of the same referent). The graphic features present in samples of the children's work were examined and compared to the graphic features children could identify through verbal and nonverbal communication. We examined the frequencies of graphic feature identification, as well as significant differences between graphic feature usage and graphic feature identification. The most frequently used graphic features were linearity, unidirectionality, and small size of units. The most frequently identified graphic feature was conventional letter. Overall, children used significantly more graphic features than they were able to identify. Significant relationships comparing the 2-year-old group and 4-year-old group's usage and identification were also found. The findings are discussed in terms of their application to early childhood classrooms. Teachers can apply these findings when engaging children in conversations about their emergent writing; these discussions are explored as a beneficial teaching tool.

The Esthetic Features of Femme Fatale Fashions in Movie (영화 <사랑보다 아름다운 유혹>에 나타난 팜므 파탈 의상의 미적 특성)

  • Kim, Bok-Hee;Nam, Yoon-Sook
    • Journal of the Korean Society of Costume
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    • v.56 no.9 s.109
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    • pp.14-23
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    • 2006
  • The purpose of this study is to identify the esthetic features of femme fatale character fashions, which are shown in Movie . The feature of evil femineity is the attribute of evil which brings men to ruin by the dangerous, cunning, and cruel trick, and is expressed in black color, red color, and slash fashion. This fashion shows the dark reverse side of women's sexual desire in relation to anxiety, evil, and death. The feature of sensuality evokes physical pleasures or desires, and maximizes the exposure of sexual regions by tightening or loosening women's body. In the fashion expressing this feature, the forms are fit or loose silhouette. and the colors are black and red. and the materials are soft. This fashion seems to deconstruct the past concept of sex consciousness and emphasize the independent and autonomous femineity. The feature of positiveness combines feminine elements with masculine elements in relation to power elements. This feature is expressed in tailored suit and trousers, with few patterns and details, and in black color and gray color. This fashion reflects the aggressive, challenging, and independent femineity, and expresses the potential defense for the weakness and danger of female body. The feature of purity expresses the earnest and truthful mind, and is expressed in the soft and light one-piece dress, the elegant suit, and the pink color and black color fashion. This fashion shows angel-like and reliable womanly beauty, but at the same time shows women's attribute which changes their behavior and thinking every moment, so that this fashion shows women's double-sided attribute which combines women's weakness and violence, or tenacity and conflict.

Extraction of kidney's feature points by SIFT algorithm in ultrasound image (SIFT 알고리즘으로 kidney 특징점 검출)

  • Kim, Sung-Jung;Yoo, JaeChern
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2019.07a
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    • pp.313-314
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    • 2019
  • 본 논문에서는 특징점 검출 알고리즘을 적용하여 ultrasound image에서 특징점을 검출하는 것과 object dectection을 위한 keypoints가 object에 올바르게 위치하는지를 검증하는 실험을 진행한다. 특징점 검출을 위한 알고리즘으로는 Scale Invariant Feature Transform(SIFT)과 Harris corner detection 을 적용하여 검증한다.

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Experimental Optimal Choice Of Initial Candidate Inliers Of The Feature Pairs With Well-Ordering Property For The Sample Consensus Method In The Stitching Of Drone-based Aerial Images

  • Shin, Byeong-Chun;Seo, Jeong-Kweon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.4
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    • pp.1648-1672
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    • 2020
  • There are several types of image registration in the sense of stitching separated images that overlap each other. One of these is feature-based registration by a common feature descriptor. In this study, we generate a mosaic of images using feature-based registration for drone aerial images. As a feature descriptor, we apply the scale-invariant feature transform descriptor. In order to investigate the authenticity of the feature points and to have the mapping function, we employ the sample consensus method; we consider the sensed image's inherent characteristic such as the geometric congruence between the feature points of the images to propose a novel hypothesis estimation of the mapping function of the stitching via some optimally chosen initial candidate inliers in the sample consensus method. Based on the experimental results, we show the efficiency of the proposed method compared with benchmark methodologies of random sampling consensus method (RANSAC); the well-ordering property defined in the context and the extensive stitching examples have supported the utility. Moreover, the sample consensus scheme proposed in this study is uncomplicated and robust, and some fatal miss stitching by RANSAC is remarkably reduced in the measure of the pixel difference.

Blur-Invariant Feature Descriptor Using Multidirectional Integral Projection

  • Lee, Man Hee;Park, In Kyu
    • ETRI Journal
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    • v.38 no.3
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    • pp.502-509
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    • 2016
  • Feature detection and description are key ingredients of common image processing and computer vision applications. Most existing algorithms focus on robust feature matching under challenging conditions, such as inplane rotations and scale changes. Consequently, they usually fail when the scene is blurred by camera shake or an object's motion. To solve this problem, we propose a new feature description algorithm that is robust to image blur and significantly improves the feature matching performance. The proposed algorithm builds a feature descriptor by considering the integral projection along four angular directions ($0^{\circ}$, $45^{\circ}$, $90^{\circ}$, and $135^{\circ}$) and by combining four projection vectors into a single highdimensional vector. Intensive experiment shows that the proposed descriptor outperforms existing descriptors for different types of blur caused by linear motion, nonlinear motion, and defocus. Furthermore, the proposed descriptor is robust to intensity changes and image rotation.

An Active Contour Approach to Extract Feature Regions from Triangular Meshes

  • Min, Kyung-Ha;Jung, Moon-Ryul
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.5 no.3
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    • pp.575-591
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    • 2011
  • We present a novel active contour-based two-pass approach to extract smooth feature regions from a triangular mesh. In the first pass, an active contour formulated in level-set surfaces is devised to extract feature regions with rough boundaries. In the second pass, the rough boundary curve is smoothed by minimizing internal energy, which is derived from its curvature. The separation of the extraction and smoothing process enables us to extract feature regions with smooth boundaries from a triangular mesh without user's initial model. Furthermore, smooth feature curves can also be obtained by skeletonizing the smooth feature regions. We tested our algorithm on facial models and proved its excellence.

A Survey on Feature Store (Feature 저장소 기술 동향)

  • Hur, S.J.;Kim, J.Y.
    • Electronics and Telecommunications Trends
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    • v.36 no.2
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    • pp.65-74
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    • 2021
  • In this paper, we discussed the necessity and importance of introducing feature stores to establish a collaborative environment between data engineering work and data science work. We examined the technology trends of feature stores by analyzing the status of some major feature stores. Moreover, by introducing a feature store, we can reduce the cost of performing artificial intelligence (AI) projects and improve the performance and reliability of AI models and the convenience of model operation. The future task is to establish technical requirements for establishing a collaborative environment between data engineering work and data science work and develop a solution for providing a collaborative environment based on this.

Automatic Fortified Password Generator System Using Special Characters

  • Jeong, Junho;Kim, Jung-Sook
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.15 no.4
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    • pp.295-299
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    • 2015
  • The developed security scheme for user authentication, which uses both a password and the various devices, is always open by malicious user. In order to solve that problem, a keystroke dynamics is introduced. A person's keystroke has a unique pattern. That allows the use of keystroke dynamics to authenticate users. However, it has a problem to authenticate users because it has an accuracy problem. And many people use passwords, for which most of them use a simple word such as "password" or numbers such as "1234." Despite people already perceive that a simple password is not secure enough, they still use simple password because it is easy to use and to remember. And they have to use a secure password that includes special characters such as "#!($^*$)^". In this paper, we propose the automatic fortified password generator system which uses special characters and keystroke feature. At first, the keystroke feature is measured while user key in the password. After that, the feature of user's keystroke is classified. We measure the longest or the shortest interval time as user's keystroke feature. As that result, it is possible to change a simple password to a secure one simply by adding a special character to it according to the classified feature. This system is effective even when the cyber attacker knows the password.

Adaptive Self Organizing Feature Map (적응적 자기 조직화 형상지도)

  • Lee , Hyung-Jun;Kim, Soon-Hyob
    • The Journal of the Acoustical Society of Korea
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    • v.13 no.6
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    • pp.83-90
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    • 1994
  • In this paper, we propose a new learning algorithm, ASOFM(Adaptive Self Organizing Feature Map), to solve the defects of Kohonen's Self Organiaing Feature Map. Kohonen's algorithm is sometimes stranded on local minima for the initial weights. The proposed algorithm uses an object function which can evaluate the state of network in learning and adjusts the learning rate adaptively according to the evaluation of the object function. As a result, it is always guaranteed that the state of network is converged to the global minimum value and it has a capacity of generalized learning by adaptively. It is reduce that the learning time of our algorithm is about $30\%$ of Kohonen's.

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