• 스마트미디어저널
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• 제10권1호
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• pp.79-87
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• 2021

In recent years research on automatic font generation with machine learning mainly focus on using transformation-based methods, in comparison, generative model-based methods of font generation have received less attention. Transformation-based methods learn a mapping of the transformations from an existing input to a target. This makes them ambiguous because in some cases a single input reference may correspond to multiple possible outputs. In this work, we focus on font generation using the generative model-based methods which learn the buildup of the characters from noise-to-image. We propose a novel way to train a conditional generative deep neural model so that we can achieve font style control on the generated font images. Our research demonstrates how to generate new font images conditioned on both character class labels and character style labels when using the generative model-based methods. We achieve this by introducing a modified generator network which is given inputs noise, character class, and style, which help us to calculate losses separately for the character class labels and character style labels. We show that adding the character style vector on top of the character class vector separately gives the model rich information about the font and enables us to explicitly specify not only the character class but also the character style that we want the model to generate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권2호
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• pp.412-434
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• 2023

This study discusses the high-order diffusion method in the wavelet domain. It aims to improve the edge protection capability of the high-order diffusion method using wavelet coefficients that can reflect image information. During the first step of the proposed diffusion method, the wavelet packet decomposition is a more refined decomposition method that can extract the texture and structure information of the image at different resolution levels. The high-frequency wavelet coefficients are then used to construct the edge detection function. Subsequently, because accurate wavelet coefficients can more accurately reflect the edges and details of the image information, by introducing the idea of state weight, a scheme for recovering wavelet coefficients is proposed. Finally, the edge detection function is constructed by the module of the wavelet coefficients to guide high-order diffusion, the denoised image is obtained. The experimental results showed that the method presented in this study improves the denoising ability of the high-order diffusion model, and the edge protection index (SSIM) outperforms the main methods, including the block matching and 3D collaborative filtering (BM3D) and the deep learning-based image processing methods. For images with rich textural details, the present method improves the clarity of the obtained images and the completeness of the edges, demonstrating its advantages in denoising and edge protection.

• 한국엔터테인먼트산업학회논문지
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• 제13권1호
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• pp.47-57
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• 2019

20세기 말, 뉴미디어 기술의 보급과 뉴미디어 예술이 대두됨에 따라, 무용은 시각예술과 신체언어예술로써 점점 더 풍부하고, 많은 변화의 특징을 갖게 되었다. 인터넷이 엄청난 속도로 발전하고 있는 오늘날의 뉴미디어 환경에서 수많은 서로 다른 분야(예로 들면, 영화 연극, 컴퓨터 기술, 디지털 예술 등)들이 그 공통성과 특징을 빌려 다양한 교호 창작을 함으로써 새로운 학문적 연구와 이론 모델이 생겨나고 있다. 각 분야의 크로스오버가 화제가 되면서 전통적인 댄스 퍼포먼스 형식도 새로운 돌파구를 찾고 있다. 이 글은 두 부분으로 나누어져 있는데, 첫 번째 부분은 영상 장치의 춤 공연예술에 대한 연구이며, 두번째 부분은 무용예술의 전파 가능성과 영향을 연구하는 것으로, 이 두 부분의 연구를 통해 뉴미디어 환경에서 무용예술의 크로스오버 실현과 전파에 본 연구의 내용이 활용되길 기대한다.

• 경영과정보연구
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• 제29권4호
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• pp.89-108
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• 2010

소셜네트워크서비스(Social Network Service)는 사람들 사이의 사회적 관계를 중심으로 온라인상에 구축된 친목기반형 서비스이다. 최근 이러한 서비스의 수요와 관심이 그 어느 때 보다 높아진 반면 기술과 서비스적인 측면에서 접근이 아직은 미흡한 실정이다. 본 연구는 다양한 소셜네트워크 서비스 가운데 전 세계적으로 가장 유명하고 이용자수가 최대인 페이스북(Facebook)을 대상으로 기술과 서비스적 접근을 바탕으로 페이스북이 성공한 요인이 무엇인지 살펴보았다. 이를 위해 소셜네트워서비스를 사용한 경험이 풍부한 사용자들의 행동을 관찰 하였다. 그 결과 기술적인 측면에 해당하는 비동기적인 방식이 사교성을 향상시키고 기술의 공개성은 서비스적인 측면에서 폐쇄성을 지향하는 방향으로 작동하는 것을 발견하였다. 이는 소셜 미디어가 갖는 독특한 특질이다. 이러한 요소를 고려해서 소셜 미디어를 개발할 때 성공적인 소셜네트워크서비스가 가능 할 것으로 기대한다.

• Asian-Australasian Journal of Animal Sciences
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• 제17권8호
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• pp.1168-1176
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• 2004

Intensive animal industries create large volumes of nutrient rich effluent, which, if untreated, has the potential for substantial environmental degradation. Aquatic plants in aerobic lagoon systems have the potential to achieve inexpensive and efficient remediation of effluent, and to recover valuable nutrients that would otherwise be lost. Members of the family Lemnaceae (duckweeds) are widely used in lagoon systems, but despite their widespread use in the cleansing of sewage, only limited research has been conducted into their growth in highly eutrophic media, and little has been done to systematically distinguish between different types of media. This study examined the growth characteristics of duckweed in abattoir effluent, and explored possible ways of ameliorating the inhibitory factors to growth on this medium. A series of pot trials was conducted to test the tolerance of duckweed to abattoir effluent partially remediated by a sojourn in anaerobic fermentation ponds, both in its unmodified form, and after the addition of acid to manipulate pH, and the addition of bentonite. Unmodified abattoir effluent was highly toxic to duckweed, although duckweed remained viable and grew sub optimally in media with total ammonia nitrogen (TAN) concentrations of up to 100 mg/l. Duckweed also grew vigorously in effluent diluted 1:4 v/v, containing 56 mg TAN/L and also modified by addition of acid to decrease pH to 7 and by adding bentonite (0.5%).

• Asian-Australasian Journal of Animal Sciences
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• 제17권1호
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• pp.137-145
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• 2004

Intensive animal industries create large volumes of nutrient rich effluent which, if untreated, has the potential for substantial environmental degradationand to recover valuable nutrients that would otherwise be lost. Members of the family Lemnaceae are widely used in lagoon systems, to achieve inexpensive and efficient remediation of effluent. Only limited research has been conducted into their growth in highly eutrophic media and there has been little done to systematically distinguish between different types of media. This study examined the growth characteristics of duckweed in abattoir effluent and explored possible ways of ameliorating the inhibitory factors to growth on this medium. A series of pot trials was conducted to test the tolerance of duckweed to abattoir effluent partially remediated by a sojourn in anaerobic fermentation ponds, both in its unmodified form and after the addition of acid to manipulate pH, and the addition of bentonite. Unmodified abattoir effluent was highly toxic to duckweed, even at dilutions of 3:1. Duckweed remained viable and grew sub-optimally in simplified media with total ammonia nitrogen (TAN) concentrations of up to 100 mg/L. Duckweed grew vigorously in effluent diluted 1:4 v/v, containing 56 mg TAN/L when modified by addition of acid (to decrease pH to 7) and bentonite at 0.5%. The results of this study suggest that bentonite plays an important role in modifying the toxicity of abattoir effluent to duckweed.

• Journal of Information Processing Systems
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• 제17권5호
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• pp.1020-1033
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• 2021

Nowadays, online or mobile social network services (SNS) are very popular and widely spread in our society and daily lives to instantly share, disseminate, and search information. In particular, SNS such as YouTube, Flickr, Facebook, and Amazon allow users to upload billions of images or videos and also provide a number of multimedia information to users. Information retrieval in multimedia-rich SNS is very useful but challenging task. Content-based media retrieval (CBMR) is the process of obtaining the relevant image or video objects for a given query from a collection of information sources. However, CBMR suffers from the dimensionality curse due to inherent high dimensionality features of media data. This paper investigates the effectiveness of the kernel trick in CBMR, specifically, the kernel principal component analysis (KPCA) for dimensionality reduction. KPCA is a nonlinear extension of linear principal component analysis (LPCA) to discovering nonlinear embeddings using the kernel trick. The fundamental idea of KPCA is mapping the input data into a highdimensional feature space through a nonlinear kernel function and then computing the principal components on that mapped space. This paper investigates the potential of KPCA in CBMR for feature extraction or dimensionality reduction. Using the Gaussian kernel in our experiments, we compute the principal components of an image dataset in the transformed space and then we use them as new feature dimensions for the image dataset. Moreover, KPCA can be applied to other many domains including CBMR, where LPCA has been used to extract features and where the nonlinear extension would be effective. Our results from extensive experiments demonstrate that the potential of KPCA is very encouraging compared with LPCA in CBMR.

• 한국콘텐츠학회논문지
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• 제21권2호
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• pp.507-519
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• 2021

본 연구는 숏폼(short-form) 동영상 소셜미디어 플랫폼인 틱톡의 이용 동기를 파악하고 틱톡 광고에 대한 소비자의 인식 및 태도를 고찰함으로써 틱톡 광고 효과에 주요한 광고 요인을 탐색하고자 한다. 20-30대 틱톡 이용자를 대상으로 심층 인터뷰를 진행한 결과, 주요 틱톡 이용 동기로는 정보성과 오락성이 도출되었으며 틱톡 특성으로 짧은 동영상, 다양한 콘텐츠 내용, 형식의 참신성이 언급되었다. 또한, 유용성, 오락성, 광고 회피를 위한 조작용이성, 친근감, 상호작용이 주요 틱톡 광고 특성으로 제시되었다. 마지막으로, 틱톡 광고 참여행위는 대체적으로 '좋아요' 클릭, 댓글쓰기, 공유, 구매 링크/광고주 홈페이지 클릭, 광고 제작 참여 등으로 나타났다. 이와 같은 연구 결과는 소셜미디어 광고의 이론적 확장에 기여하고 효율적인 틱톡 광고 전략 수립을 위한 지침을 제공할 것이다.

• 한국생물공학회:학술대회논문집
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• 한국생물공학회 2001년도 추계학술발표대회
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• pp.483-486
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• 2001

Growth and tropane alkaloids(hyoscyamine and scopolamine) contents were studied in root cultures from Scopolia paruiflora. All excised roots grew well, even without an addition of a growth regulators. Scopolia roots could be divided scopolamine-rich species. Among the culture media, SH medium was the best for tropane alkaloids production from the hairy roots, whereas the growth increased in SH medium. In precusor experiments, feeding of hyoscyamine was promotive for scopolamine formation. Abiotic elicitors made a slightly production promotion effect.

• Advances in Energy Research
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• 제1권1호
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• pp.53-78
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• 2013

Methane carbon dioxide reforming (MCDR) is a promising way of utilizing greenhouse gas for hydrogen-rich fuel production. Compared with other types of reactors, Compact Reformers (CRs) are efficient for fuel processing. In a CR, a thin solid plate is placed between two porous catalyst layers to enable efficient heat transfer between the two catalyst layers. In this study, the physical and chemical processes of MCDR in a CR are studied numerically with a 2D numerical model. The model considers the multi-component gas transport and heat transfer in the fuel channel and the porous catalyst layer, and the MCDR reaction kinetics in the catalyst layer. The finite volume method (FVM) is used for discretizing the governing equations. The SIMPLEC algorithm is used to couple the pressure and the velocity. Parametrical simulations are conducted to analyze in detail the effects of various operating/structural parameters on the fuel processing behavior.