• Title/Summary/Keyword: Beijing Image

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A Factor Analysis of Lifestyle and Fashion Attitude of Chinese New generation (중국 신세대 남녀의 생활 및 패션태도 요인분석)

  • Kim, Jung-Won;Quli, Quli
    • Fashion & Textile Research Journal
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    • v.8 no.1
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    • pp.71-79
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    • 2006
  • The study of young people's attitudes towards appearance management has special significance for understanding young people's living, thought and attitudes. It was handed out 600 questionnaires in the three cities and look 573 questionnaires back, out of which 552 were used as the basic material for the analysis. These 522 questionnaires included 178 in Beijing, 200 in Shanghai, 175 in Dalian. 154 questions in four aspects were raised in the questionnaires. The purpose of this study were to identify the Chinese generation' lifestyle and fashion attitudes. Questionnaires developed by researcher were distributed and collected from 552 chinese new generation of the three cities(178 in Beijing, 200 in Shanghai, 175 in Dalian). 1) Life attitudes of new generation men and women in China were classified into five factors, which were extravagant pleasure-seeking, sports-oriented, marriage-oriented, appearance-oriented and study-oriented attitudes. 2) Fashion attitudes of new generation men and women in China were classified into eight factors, which were fashion attitude of being conscious of others, others-dependent fashion attitude, rational fashion attitude, brand-pursuing fashion attitude, active appearance management fashion attitude, unique fashion attitude, fashion attitude of being conscious of sex role and individuality-oriented fashion attitude.

Advantage of the Intensive Light Scattering by Plasmonic Nanoparticles in Velocimetry

  • Rong, Tengda;Li, Quanshui
    • Current Optics and Photonics
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    • v.6 no.1
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    • pp.79-85
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    • 2022
  • Tracers are one of the critical factors for improving the performance of velocimetry. Silver and gold nanoparticles as tracers with localized surface-plasmon resonance are analyzed for their scattering properties. The scattering cross sections, angular distribution of the scattering, and equivalent scattering cross sections from 53° and 1.5° half-angle cones at 532 nm are calculated, with particle sizes in the nanoscale range. The 53° and 1.5° half-angle cones used as examples correspond respectively to the collection cones for microscope objectives in microscopic measurements and camera lenses in macroscopic measurements. We find that there is a transitional size near 35 nm when comparing the equivalent scattering cross sections between silver and gold nanoparticles in water at 532 nm. The equivalent scattering cross section of silver nanoparticles is greater or smaller than that of gold nanoparticles when the particle radius is greater or smaller than 35 nm respectively. When the radius of the plasmonic nanoparticles is smaller than about 44 nm, their equivalent scattering cross sections are at least ten times that of TiO2 nanoparticles. Plasmonic nanoparticles are promising for velocimetry applications.

Visual Saliency Detection Based on color Frequency Features under Bayesian framework

  • Ayoub, Naeem;Gao, Zhenguo;Chen, Danjie;Tobji, Rachida;Yao, Nianmin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.2
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    • pp.676-692
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    • 2018
  • Saliency detection in neurobiology is a vehement research during the last few years, several cognitive and interactive systems are designed to simulate saliency model (an attentional mechanism, which focuses on the worthiest part in the image). In this paper, a bottom up saliency detection model is proposed by taking into account the color and luminance frequency features of RGB, CIE $L^*a^*b^*$ color space of the image. We employ low-level features of image and apply band pass filter to estimate and highlight salient region. We compute the likelihood probability by applying Bayesian framework at pixels. Experiments on two publically available datasets (MSRA and SED2) show that our saliency model performs better as compared to the ten state of the art algorithms by achieving higher precision, better recall and F-Measure.

A study of influencing factors on Korean SPA brand assets for the Chinese market (중국진출 한국 SPA 브랜드 자산 영향요인 연구)

  • Jia, Yuan Bo;Lee, Bomi;Kim, Mi Sook
    • The Research Journal of the Costume Culture
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    • v.27 no.3
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    • pp.206-221
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    • 2019
  • This study examined the causal relations among brand personality, brand identification, and brand equity of Korean SPA brands that target Chinese consumers. Data were collected from 600 Chinese consumers residing in Beijing and Shanghai from August 15th to August 30th of 2015 by using convenience sampling; 561 of the questionnaires were used in the statistical analyses. Structural equation models were employed using AMOS 22.0. The results were as follows. First, the factors of Korean SPA brand personality, such as sophistication, competence, tenacity, and interest, exerted significant influences on the brand identification, while honesty had no significant influence on brand identification. Second, brand identification had significant influence on brand awareness, brand image, and brand loyalty. Third, brand awareness showed significant influence on brand image and brand loyalty. Fourth, brand image had significant influence on brand loyalty. These results indicated that brand equity can be strengthened by enhancing brand identification with the proper brand personality. This demonstrates that if Chinese consumers can associate Korean SPA brands with a sophisticated, attractive image, brand identification may be improved and brand equity may be strengthened in the long run, providing basic data for establishing efficient marketing strategies for Korean SPA brands in the Chinese market.

Fast and Accurate Single Image Super-Resolution via Enhanced U-Net

  • Chang, Le;Zhang, Fan;Li, Biao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.4
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    • pp.1246-1262
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    • 2021
  • Recent studies have demonstrated the strong ability of deep convolutional neural networks (CNNs) to significantly boost the performance in single image super-resolution (SISR). The key concern is how to efficiently recover and utilize diverse information frequencies across multiple network layers, which is crucial to satisfying super-resolution image reconstructions. Hence, previous work made great efforts to potently incorporate hierarchical frequencies through various sophisticated architectures. Nevertheless, economical SISR also requires a capable structure design to balance between restoration accuracy and computational complexity, which is still a challenge for existing techniques. In this paper, we tackle this problem by proposing a competent architecture called Enhanced U-Net Network (EUN), which can yield ready-to-use features in miscellaneous frequencies and combine them comprehensively. In particular, the proposed building block for EUN is enhanced from U-Net, which can extract abundant information via multiple skip concatenations. The network configuration allows the pipeline to propagate information from lower layers to higher ones. Meanwhile, the block itself is committed to growing quite deep in layers, which empowers different types of information to spring from a single block. Furthermore, due to its strong advantage in distilling effective information, promising results are guaranteed with comparatively fewer filters. Comprehensive experiments manifest our model can achieve favorable performance over that of state-of-the-art methods, especially in terms of computational efficiency.

Classification of Livestock Diseases Using GLCM and Artificial Neural Networks

  • Choi, Dong-Oun;Huan, Meng;Kang, Yun-Jeong
    • International Journal of Internet, Broadcasting and Communication
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    • v.14 no.4
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    • pp.173-180
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    • 2022
  • In the naked eye observation, the health of livestock can be controlled by the range of activity, temperature, pulse, cough, snot, eye excrement, ears and feces. In order to confirm the health of livestock, this paper uses calf face image data to classify the health status by image shape, color and texture. A series of images that have been processed in advance and can judge the health status of calves were used in the study, including 177 images of normal calves and 130 images of abnormal calves. We used GLCM calculation and Convolutional Neural Networks to extract 6 texture attributes of GLCM from the dataset containing the health status of calves by detecting the image of calves and learning the composite image of Convolutional Neural Networks. In the research, the classification ability of GLCM-CNN shows a classification rate of 91.3%, and the subsequent research will be further applied to the texture attributes of GLCM. It is hoped that this study can help us master the health status of livestock that cannot be observed by the naked eye.

The Relationship among Localized Marketing, Brand Image, and Customer's Intention to Revisit of Korean Restaurant Franchises: Focused on Beijing, China (한식당 프랜차이즈 기업의 현지화 마케팅과 브랜드 이미지, 고객 재방문의도와의 관계: 중국 베이징 지역을 중심으로)

  • JUNG, Sung Mok;LEE, Il Han
    • The Korean Journal of Franchise Management
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    • v.13 no.2
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    • pp.1-15
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    • 2022
  • Purpose: The globalization of the Korean restaurant franchise industry differs from the business performance of enhancing the brand image and customers' intention to revisit depending on the degree of localization marketing. Therefore, it is necessary to consider the extent to which the localization marketing activities of overseas Korean restaurant franchise companies affect the customer's perception. This study aims to investigate the effects of localization marketing (Localized Menu, Localized Price, Localized Service Experience, Localized Promotion, Localized Physical Environment) of Korean restaurant franchise companies on customer revisit intention. Research design, data, and methodology: For this study, 150 questionnaires using local Korean restaurants in Beijing, China, were analyzed using SPSS Ver.21 and AMOS Ver.22. Result: It was confirmed that the localized menu, localized service experience, and localized physical environment all affect the intention to revisit customers. Based on these verification results, if overseas franchises fully recognize localization marketing, which is an important factor for local business success, and establish localization strategies, they can gain an edge in competition with local Korean restaurants or restaurant franchises founded by locals. There may be a higher probability that However, it was found that localization price and localization promotion had no mediating effect of brand image between revisit intention and revisit intention. It was found that it had no effect on the degree of inquiry and had a negative effect. Conclusions: Due to the impact of the COVID-19 pandemic, there have been many changes in the domestic and overseas food service industry over the past two years. Therefore, in future research, it is necessary to study the localization of overseas Korean restaurant franchise companies that are more multidimensionally subdivided. Various measures of customized localization marketing for optimal regional characteristics should be developed and applied to enhance customer revisiting and brand image of Korean restaurant franchise companies entering overseas. In the future, this study will be meaningful data for the establishment of localization marketing (Localized Menu, Localized Price, Localized Service Experience, Localized Promotion, Localized Physical Environment) strategies for Korean restaurant franchise companies that consider overseas expansion or have already entered.

Watershed Segmentation of High-Resolution Remotely Sensed Imagery

  • WANG Ziyu;ZHAO Shuhe;CHEN Xiuwan
    • Proceedings of the KSRS Conference
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    • 2004.10a
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    • pp.107-109
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    • 2004
  • High-resolution remotely sensed data such as SPOT-5 imagery are employed to study the effectiveness of the watershed segmentation algorithm. Existing problems in this approach are identified and appropriate solutions are proposed. As a case study, the panchromatic SPOT-5 image of part of Beijing urban areas has been segmented by using the MATLAB software. In segmentation, the structuring element has been firstly created, then the gaps between objects have been exaggerated and the objects of interest are converted. After that, the intensity valleys have been detected and the watershed segmentation have been conducted. Through this process, the objects in an image are divided into separate objects. Finally, the effectiveness of the watershed segmentation approach for high-resolution imagery has been summarized. The approach to solve the problems such as over-segmentation has been proposed.

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The Impact of Country Image on the Chinese Consumers' Purchase Intention (국가이미지가 중국 소비자의 구매의향에 미치는 영향에 관한 연구)

  • Su, Shuai
    • Journal of Distribution Science
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    • v.8 no.1
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    • pp.43-52
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    • 2010
  • Country images of Korea and Japan based on economic development, education level, goods' quality, R&D, political democratization and quality of life, perceived by Chinese university students in Beijing, Shanghai and Shandong province of chinese emerging markets as the representative of a potential buying power group, are surveyed, which, then are used to study how the perceived country images effect on their purchasing intention for Korean and Japanese products, such as, foods, cars, fashions, music CDs, electronic products and living goods. The study shows that, in chinese emerging markets, country image affects on the purchase intention of each products differently. The country image of Korea was less influential than that of Japan on the Chines students' purchasing intention for the goods other than the electronic goods. Despite the small number of the sample, this study showed the importance of country image in the in chinese emerging markets and suggested the need for both the government and private sector to take a strategy to enhance the country image by finding the relation between the elements of country image and the intention to purchase certain product.

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A Motion Detection Approach based on UAV Image Sequence

  • Cui, Hong-Xia;Wang, Ya-Qi;Zhang, FangFei;Li, TingTing
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.3
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    • pp.1224-1242
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    • 2018
  • Aiming at motion analysis and compensation, it is essential to conduct motion detection with images. However, motion detection and tracking from low-altitude images obtained from an unmanned aerial system may pose many challenges due to degraded image quality caused by platform motion, image instability and illumination fluctuation. This research tackles these challenges by proposing a modified joint transform correlation algorithm which includes two preprocessing strategies. In spatial domain, a modified fuzzy edge detection method is proposed for preprocessing the input images. In frequency domain, to eliminate the disturbance of self-correlation items, the cross-correlation items are extracted from joint power spectrum output plane. The effectiveness and accuracy of the algorithm has been tested and evaluated by both simulation and real datasets in this research. The simulation experiments show that the proposed approach can derive satisfactory peaks of cross-correlation and achieve detection accuracy of displacement vectors with no more than 0.03pixel for image pairs with displacement smaller than 20pixels, when addition of image motion blurring in the range of 0~10pixel and 0.002variance of additive Gaussian noise. Moreover,this paper proposes quantitative analysis approach using tri-image pairs from real datasets and the experimental results show that detection accuracy can be achieved with sub-pixel level even if the sampling frequency can only attain 50 frames per second.