• Journal of Smart Tourism
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• 제3권3호
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• pp.29-40
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• 2023

This research aims to understand the role of online reviews in the local search context by examining the effects of reviews on the representation of tourism businesses on local search platforms (LSPs). By simulating tourists' local searches for restaurants on three LSPs, namely Google, Bing, and Yelp, this study examines how different ranking results are generated across the platforms and how online reviews contribute to the differences. The findings suggest that online reviews are incorporated into LSPs as ranking factors and, thus, affect tourists' decision-making by influencing the information search results in the local search context. As one of the earliest studies on local search, this study discusses how the existing knowledge about the role of online reviews in tourists' decision-making needs to be reevaluated in mobile and more dynamic environments, and offers practical implications for tourism businesses' search engine marketing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권5호
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• pp.2346-2362
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• 2016

As one of the most important issues in computer vision and image processing, online object tracking plays a key role in numerous areas of research and in many real applications. In this study, we present a novel tracking method based on the proposed structured sparse representation model, in which the tracked object is assumed to be sparsely represented by a set of object and background templates. The contributions of this work are threefold. First, the structure information of all the candidate samples is utilized by a joint sparse representation model, where the representation coefficients of these candidates are promoted to share the same sparse patterns. This representation model can be effectively solved by the simultaneous orthogonal matching pursuit method. In addition, we develop a tracking algorithm based on the proposed representation model, a discriminative candidate selection scheme, and a simple model updating method. Finally, we conduct numerous experiments on several challenging video clips to evaluate the proposed tracker in comparison with various state-of-the-art tracking algorithms. Both qualitative and quantitative evaluations on a number of challenging video clips show that our tracker achieves better performance than the other state-of-the-art methods.

• Asian Journal for Public Opinion Research
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• 제8권4호
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• pp.432-452
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• 2020

This study explored the representation of risks from the controversial Lynas rare earth refining as a risk event by five Malaysian online mainstream and alternative newspapers using qualitative content analysis. The aim is to uncover the role of the news media in the social amplification and attenuation of risks within the literature evidence as those roles are still uncertain. Content analysis is used to explore the online newspapers' roles guided by the Social Amplification of Risk Framework (SARF). The representations typified environmental, financial, health, occupational, property, radioactive, and technological risks and established connections between four risk types (environmental, financial, radioactive, and health risks). Radioactive risk was repeatedly associated with other risks, suggesting that the volume and information flow focused on radioactive risk as a key ingredient for amplification. This connection shows that the nature of the relationship between risks is multidimensional, contradicting the unidirectional type found in previous studies. Alternative online newspapers amplified and attenuated more risks, thus, providing more diverse coverage than mainstream sources. Consequently, this study provides evidence that risk representation from rare earth refining in a digital news environment is multidimensional and intensified or weakened in a multi-layered pattern. The stakeholders are engaged in a contestation by positioning their narratives to oppose or support their interests, which are amplified or attenuated by the online newspapers as social amplification stations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권9호
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• pp.3655-3671
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• 2015

In this paper, we develop a novel object tracking method based on sparse representation. First, we propose a relaxed sparse representation model, based on which the tracking problem is casted as an inverse sparse representation process. In this process, the target template is able to be sparsely approximated by all candidate samples. Second, we present an objective function that combines the sparse representation process of different fragments, the relaxed representation scheme and a weight reference prior. Based on some propositions, the proposed objective function can be solved by using an iteration algorithm. In addition, we design a tracking framework based on the proposed representation model and a simple online update manner. Finally, numerous experiments are conducted on some challenging sequences to compare our tracking method with some state-of-the-art ones. Both qualitative and quantitative results demonstrate that the proposed tracking method performs better than other competing algorithms.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2021년도 추계학술대회
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• pp.212-214
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• 2021

In a society with Covid-19 as part of our daily lives, we had to adapt ourselves to a new reality to maintain our lifestyles as normal as possible. An example of this is teleworking and online classes. However, several issues appeared on the go as we started the new way of living. One of them is the doubt of knowing if real people are in front of the camera or if someone is paying attention during a lecture. Therefore, we encountered this issue by creating a 3D reconstruction tool to identify human faces and expressions actively. We use a web camera, a lightweight 3D face model, and use the 2D facial landmark to fit expression coefficients to drive the 3D model. With this Model, it is possible to represent our faces with an Avatar and fully control its bones with rotation and translation parameters. Therefore, in order to reconstruct facial expressions during online meetings, we proposed the above methods as our solution to solve the main issue.

• 한국게임학회 논문지
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• 제17권5호
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• pp.103-112
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• 2017

많은 사용자가 함께 즐기는 온라인 게임(MMOGs)에서 IoT의 확장은 서버에 엄청난 부하를 지속적으로 증가시켜, 모든 데이터들이 Big-Data화 되어가는 환경에 있다. 이에 본 논문에서는 딥러닝 기법 중에서 가장 많이 사용되는 Sparse Autoencoder와 이미 잘 알려진 부하분산 알고리즘(ProGReGA-KF)을 결합한다. 기존 알고리즘 ProGReGA-KF과 본 논문에서 제안한 알고리즘을 이동 안정성으로 비교하였고, 제안한 알고리즘이 빅-데이터 환경에서 좀 더 안정적이고 확장성이 있음 시뮬레이션을 통해 보였다.

• 한국게임학회 논문지
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• 제5권4호
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• pp.3-12
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• 2005

미디어 영상, 예술 분야에서의 표현 특징들 중 초현실주의의 표현 기법을 이용한 많은 작품이 출시되고 있으며 이에 대한 연구가 시작 진행되고 있다. 그러나 아직 게임 캐릭터의 표현 특징 중 초현실주의의 표현 특징에 관한 연구는 거의 전무한 상태이다. 따라서 본 논문에서는 초현실주의에서의 표현 기법을 중심으로 판타지 게임 캐릭터의 표현 특징을 분석하였다. 그 결과, 초현실주의에서는 신체의 일부와 동물 또는 다른 사물을 꼴라쥬 하는 형태와 변형, 그리고 왜곡을 이용하여 현실에 존재하지 않는 이미지들을 표현하였는데 이러한 방법들은 판타지를 기반으로 한 온라인 게임 캐릭터에서도 유사하게 사용되었다. 본 논문은 미학적 맥락 속에서 판타지 게임 캐릭터들의 특징을 분석하여 현 시대 문화적 배경 속에 게이머들의 심리를 이해하여 보다 호감 있고 창조적인 게임 캐릭터 제작에 도움을 주며, 예술 기법 활용의 가능성을 증가시켜 창의적인 게임 그래픽 제작의 가능성을 여는데 의미가 있다.

• International Journal of Precision Engineering and Manufacturing
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• 제8권4호
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• pp.16-21
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• 2007

Robotic applications, such as automatic fish cutting, require online trajectory planning because the material properties of the object, such as the bone or flesh conditions, are not known in advance. Different trajectories are required when the material properties vary. An effective online trajectory-planning algorithm is proposed using quaternions to determine the position and orientation of a robot manipulator with a spherical wrist. Quaternions are free of representation singularities and permit computationally efficient orientation interpolations. To prevent singular configurations, the exact locations of the kinematic singularities of the PUMA 560 manipulator are derived and geometrically illustrated when a forearm offset exists and the third link length is not zero.

• International Journal of Advanced Culture Technology
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• 제9권1호
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• pp.218-223
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• 2021

Pervasive enhancement and required enforcement of the Internet of Things (IoTs) in a distributed massively multiplayer online architecture have effected in massive growth of Big-Data in terms of server over-load. There have been some previous works to overcome the overloading of server works. However, there are lack of considered methods, which is commonly applicable. Therefore, we propose a combing Sparse Auto-Encoder and Load-Balancing, which is ProGReGA for Big-Data of server loads. In the process of Sparse Auto-Encoder, when it comes to selection of the feature-pattern, the less relevant feature-pattern could be eliminated from Big-Data. In relation to Load-Balancing, the alleviated degradation of ProGReGA can take advantage of the less redundant feature-pattern. That means the most relevant of Big-Data representation can work. In the performance evaluation, we can find that the proposed method have become more approachable and stable.

• 인터넷정보학회논문지
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• 제11권5호
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• pp.95-104
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• 2010

학습을 이해하는 새로운 패러다임으로 구성주의가 등장하면서 협력학습의 필요성이 강조되고 있다. 특히 교수와 학습에 대한 새로운 접근을 지원하는 테크놀로지로 온라인이 부각되면서 온라인 협력학습에 대한 관심이 증대하고 있다. 본 연구는 온라인 협력학습에서 하나의 주요한 요인인 학습과제 유형에 따른 협력학습 모형을 탐색하여 온라인 협력학습 실제에 도움을 주고자 하였다. 이를 위해 학습과제를 문제해결과제와 지식학습과제로 분류한 후, 학습과제 유형별로 적합한 온라인 협력학습 설계와 환경, 그리고 학습과정을 살펴보았다.