• Title/Summary/Keyword: surprise

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Characteristics of sustainable fashion design in Marine Serre collection (마린 세르 패션 컬렉션에 나타난 지속가능 디자인 특성)

  • Soohyun Lee;Younhee Lee
    • The Research Journal of the Costume Culture
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    • v.32 no.1
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    • pp.108-123
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    • 2024
  • This study aimed to explore sustainable fashion design plans and directions by analyzing Marine Serre's collection. Previous research was reviewed to derive classifications of the aesthetic characteristics of sustainable fashion design. This classification was then used to analyze the characteristics of the Marine Serre collection. Design analysis was conducted on Marine Serre's 2018 FW to 2023 SS collections. Marine Serre's sustainability characteristics are functionality, surprise, handicraft, and inclusion. The results are as follows. First, functionality is the highest among the four characteristics and includes the functionality of movement, the functionality of form, and futurism. This characteristic was observed in the use of all-in-one body suits, pockets, and workwear, showing the will and values of designers who value daily activity. Second, surprise includes the scarcity of materials and the unexpectedness of composition. The value of the clothing is enhanced by the use of scarce materials not typically used in clothing. In addition, Marine Serre is highly regarded for expanding clothing into life by incorporating material upcycling into the theme of the collection. Third, handcrafted features include exaggerated decorations, logo, retro designs, and natural properties, and intentional utilization is differentiated. Marine Serre's signature pattern suggests a suitable expression for the fabric to use the crescent moon for the season. Fourth, the collection expresses themes of inclusivity and cultural diversity. The results indicate that Marine Serre wants to contribute to a better future characterized by global coexistence.

Emotion Recognition Method based on Feature and Decision Fusion using Speech Signal and Facial Image (음성 신호와 얼굴 영상을 이용한 특징 및 결정 융합 기반 감정 인식 방법)

  • Joo, Jong-Tae;Yang, Hyun-Chang;Sim, Kwee-Bo
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2007.11a
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    • pp.11-14
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    • 2007
  • 인간과 컴퓨터간의 상호교류 하는데 있어서 감정 인식은 필수라 하겠다. 그래서 본 논문에서는 음성 신호 및 얼굴 영상을 BL(Bayesian Learning)과 PCA(Principal Component Analysis)에 적용하여 5가지 감정 (Normal, Happy, Sad, Anger, Surprise) 으로 패턴 분류하였다. 그리고 각각 신호의 단점을 보완하고 인식률을 높이기 위해 결정 융합 방법과 특징 융합 방법을 이용하여 감정융합을 실행하였다. 결정 융합 방법은 각각 인식 시스템을 통해 얻어진 인식 결과 값을 퍼지 소속 함수에 적용하여 감정 융합하였으며, 특정 융합 방법은 SFS(Sequential Forward Selection)특정 선택 방법을 통해 우수한 특정들을 선택한 후 MLP(Multi Layer Perceptron) 기반 신경망(Neural Networks)에 적용하여 감정 융합을 실행하였다.

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The Effects of Color Hue-Tone on Recognizing Emotions of Characters in the Film, Les Misérables

  • Kim, Yu-Jin
    • Science of Emotion and Sensibility
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    • v.18 no.1
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    • pp.67-78
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    • 2015
  • This study investigated whether people experience a correspondence between color hue-tone and the main characters' emotions in the 2012 British musical drama film, Les $Mis\grave{e}rables$ through three practical experiments. Six screen images, which represent the characters' different emotions (Parrot's six primary types including love, joy, surprise, anger, sadness, and fear) were selected. For each screen image, participants were asked to judge the degree of the character's dominant emotions evoked from 17 varied screen images, which consisted of original chromatic and achromatized images as well as 15 color-filtered images (5 hues X 3 tones of the IRI color system). These tasks revealed that a chromatic color scheme is more effective to deliver the characters' positive emotions (i.e. love and joy) than an achromatic one. In addition, they proved that the hue and tone dimensions partially influence the relationships between the character emotions and colors.

Deep Foundations for High-Rise Buildings in Hong Kong

  • Sze, James W.C.
    • International Journal of High-Rise Buildings
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    • v.4 no.4
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    • pp.261-270
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    • 2015
  • Hong Kong is a renowned small city with densely placed skyscrapers. It is no surprise that heavy duty or even mega foundations are built over the years to support these structures. To cope with the fast construction pace, several heavy deep foundation types have been widely adopted with some prescribed design rules. This Paper has selected two commonly adopted but distinctive foundation types, namely large diameter bored piles and percussive steel H-piles to illustrate the special design and construction considerations related to these pile types in related to local context. The supervision requirement in related to foundation works for which again may be unique in Hong Kong will also be highlighted. A case history is also discussed in the later part of the Paper to illustrate the application of one of these foundations and to highlight the importance of considering foundation design and basement excavation method in a holistic manner.

Emotion Recognition by Vision System (비젼에 의한 감성인식)

  • 이상윤;오재흥;주영훈;심귀보
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2001.12a
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    • pp.203-207
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    • 2001
  • In this Paper, we propose the neural network based emotion recognition method for intelligently recognizing the human's emotion using CCD color image. To do this, we first acquire the color image from the CCD camera, and then propose the method for recognizing the expression to be represented the structural correlation of man's feature Points(eyebrows, eye, nose, mouse) It is central technology that the Process of extract, separate and recognize correct data in the image. for representation is expressed by structural corelation of human's feature Points In the Proposed method, human's emotion is divided into four emotion (surprise, anger, happiness, sadness). Had separated complexion area using color-difference of color space by method that have separated background and human's face toughly to change such as external illumination in this paper. For this, we propose an algorithm to extract four feature Points from the face image acquired by the color CCD camera and find normalization face picture and some feature vectors from those. And then we apply back-prapagation algorithm to the secondary feature vector. Finally, we show the Practical application possibility of the proposed method.

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Case Studies for Potential Distribution due to Power Source by Environmental Condition (전원설비에 의한 공간조건별 전위분포 사례 연구)

  • Jung, Jin-Soo;Jung, Jong-Wook;Kim, Sun-Gu
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.25 no.1
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    • pp.50-58
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    • 2011
  • In this paper, potential distribution analysis through the six kinds of case studies examined in the environmental conditions change within a limited space, by the power supply system installed. To interpret the potential distribution using electromagnetic field analysis program and the parameters were state of the ground, the outer wall of the configuration state and the presence of human potential distribution was simulated. Potential distribution analysis, the size of nominal voltage, depending on the impedance of human body to be determined on the impact of surprise decision, but if equipped with appropriate protective equipment can be protected from lightning have been confirmed.

Face Image Analysis using Adaboost Learning and Non-Square Differential LBP (아다부스트 학습과 비정방형 Differential LBP를 이용한 얼굴영상 특징분석)

  • Lim, Kil-Taek;Won, Chulho
    • Journal of Korea Multimedia Society
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    • v.19 no.6
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    • pp.1014-1023
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    • 2016
  • In this study, we presented a method for non-square Differential LBP operation that can well describe the micro pattern in the horizontal and vertical component. We proposed a way to represent a LBP operation with various direction components as well as the diagonal component. In order to verify the validity of the proposed operation, Differential LBP was investigated with respect to accuracy, sensitivity, and specificity for the classification of facial expression. In accuracy comparison proposed LBP operation obtains better results than Square LBP and LBP-CS operations. Also, Proposed Differential LBP gets better results than previous two methods in the sensitivity and specificity indicators 'Neutral', 'Happiness', 'Surprise', and 'Anger' and excellence Differential LBP was confirmed.

Discrimination of Emotional States In Voice and Facial Expression

  • Kim, Sung-Ill;Yasunari Yoshitomi;Chung, Hyun-Yeol
    • The Journal of the Acoustical Society of Korea
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    • v.21 no.2E
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    • pp.98-104
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    • 2002
  • The present study describes a combination method to recognize the human affective states such as anger, happiness, sadness, or surprise. For this, we extracted emotional features from voice signals and facial expressions, and then trained them to recognize emotional states using hidden Markov model (HMM) and neural network (NN). For voices, we used prosodic parameters such as pitch signals, energy, and their derivatives, which were then trained by HMM for recognition. For facial expressions, on the other hands, we used feature parameters extracted from thermal and visible images, and these feature parameters were then trained by NN for recognition. The recognition rates for the combined parameters obtained from voice and facial expressions showed better performance than any of two isolated sets of parameters. The simulation results were also compared with human questionnaire results.

Detection of Face Expression Based on Deep Learning (딥러닝 기반의 얼굴영상에서 표정 검출에 관한 연구)

  • Won, Chulho;Lee, Bub-ki
    • Journal of Korea Multimedia Society
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    • v.21 no.8
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    • pp.917-924
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    • 2018
  • Recently, researches using LBP and SVM have been performed as one of the image - based methods for facial emotion recognition. LBP, introduced by Ojala et al., is widely used in the field of image recognition due to its high discrimination of objects, robustness to illumination change, and simple operation. In addition, CS(Center-Symmetric)-LBP was used as a modified form of LBP, which is widely used for face recognition. In this paper, we propose a method to detect four facial expressions such as expressionless, happiness, surprise, and anger using deep neural network. The validity of the proposed method is verified using accuracy. Based on the existing LBP feature parameters, it was confirmed that the method using the deep neural network is superior to the method using the Adaboost and SVM classifier.

False Positive SOD Activity of Bifidobacterium spp. Grown in MRS Medium

  • Chang, Woo-Suk;So, Jae-Seong
    • Journal of Microbiology and Biotechnology
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    • v.8 no.4
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    • pp.305-309
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    • 1998
  • The superoxide dismutase (SOD) activity of seven Bifidobacterium spp. strains was examined by an indirect SOD assay method. Some Bifidobacterium spp. showed significant levels of SOD activity. However, we could not observe any significant differences between anaerobic and aerobic cultures. Furthermore, although several Bifidobacterium spp. exhibited some degree of tolerance to paraquat which produces superoxide radicals, the apparent SOD activity of these strains was not correlated with their resistance to paraquat. In addition, when we added increasing amounts of manganese or iron to MRS medium which had been prepared without either of the metal ions, the apparent SOD activity of cell free extracts (CFEs) was increased with increasing concentration of both metal ions. To our surprise, the heat-denatured CFEs also showed nearly identical correlative patterns. Based on these results, the apparent SOD activity was likely due to a nonenzymatic dismutation. These results strongly suggest that high concentration of divalent metal ions ($Mn^{2+}$, $Fe^{2+}$) in MRS medium result in nonenzymatic dismutation which can lead to false positive SOD activities in Bifidobacerium spp.

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