• Journal of Information Processing Systems
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• v.9 no.4
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• pp.538-547
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• 2013

In this paper, we propose a bias detection method that is based on personal and social opinions that express contrasting views on competing topics on Twitter. We used unsupervised polarity classification is conducted for learning social opinions on targets. The $tf{\cdot}idf$ algorithm is applied to extract targets to reflect sentiments and features of tweets. Our method addresses there being a lack of a sentiment lexicon when learning social opinions. To evaluate the effectiveness of our method, experiments were conducted on four issues using Twitter test collection. The proposed method achieved significant improvements over the baselines.

• Journal of the Korean earth science society
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• v.23 no.5
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• pp.397-405
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• 2002

This study investigated science gifted middle school students' philosophical views on scientific knowledge, and the effects of discussing and reading related to the knowledge. Ten eighth-graders in a science gifted class participated in this study. The results can be summarized as follows: 1, At the beginning, the students had one of six positions: (a) relativism (n = 2); (b) falsificationism (n = 2); (c) borderline between relativism and eclecticism (n = 1); (d) borderline between falsificationism and eclecticism (n = 3); (e) borderline among relativism, falsificationism, and eclecticism (n = 1); and (f) borderline inductivism and eclecticism (n = 1). This result indicated that most students had on almost modern philosophical view of scientific knowledge. 2, Some students, who had chosen the item of inductivism in some questions of the instrument at the beginning, maintained their selection despite discussions and readings related to scientific knowledge. The data were examples which indicated the difficulty of changing from a traditional view to a modern view of scientific knowledge.

• Journal of the Optical Society of Korea
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• v.20 no.2
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• pp.239-244
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• 2016

Mugshot face images, routinely collected by police, usually contain both frontal and profile views. Existing automated face recognition methods exploited mugshot databases by enlarging the gallery with synthetic multi-view face images generated from the mugshot face images. This paper, instead, proposes to match the query arbitrary view face image directly to the enrolled frontal and profile face images. During matching, the 3D face shape model reconstructed from the mugshot face images is used to establish corresponding semantic parts between query and gallery face images, based on which comparison is done. The final recognition result is obtained by fusing the matching results with frontal and profile face images. Compared with previous methods, the proposed method better utilizes mugshot databases without using synthetic face images that may have artifacts. Its effectiveness has been demonstrated on the Color FERET and CMU PIE databases.

• Journal of Engineering Education Research
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• v.25 no.2
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• pp.42-56
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• 2022

This study aimed to investigate the views of STEM college students on the social responsibility of scientists and engineers. A total of 660 students in STEM majors at several Korean universities participated in the study. We assessed social responsibility among college students in STEM majors using the VSRoSE scale, which taps into eight different domains of social responsibility: Concern for human welfare and safety (HUMAN), Concern for environmental sustainability (ENVIR), Consideration of societal risks and consequences (CONSEQ), Consideration of societal risks and consequences (CONSEQ), Consideration of societal needs and demands (NEEDS), Pursuit of the common good (COMGOOD), Civic engagement and services (CIVIC), Communication with the public (COMMU), and Participation in policy decision-making (POLICY). Group differences in social responsibility by gender, majors, and years in school were examined. Mean scores in HUMAN, ENVIR, and CONSEQ were relatively higher than those in NEEDS, COMGOOD, CIVIC, COMMU, and POLICY. Cluster analysis identified five different groups with similar patterns of social responsibility scores. In addition to two groups with overall high and low scores across all eight factors of VSRoSE, three additional groups with different combinations of high and low scores in different factors were identified. The results indicated that students with low social responsibility are not homogeneous and these heterogeneous sub-groups of students will need tailored interventions highlighting different factors of social responsibility that they lack. Pedagogical implications of social responsibility for education were discussed.

• Journal of Home Health Care Nursing
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• v.29 no.3
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• pp.278-287
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• 2022

Purpose: To analyze Korean nurse-related channels and video titles on YouTube, the world's largest online video sharing and social media platform, to clarify public opinion and image of nurses. We seek utilization strategies and measures through current status analysis. Methods: Data is collected by crawling video information related to Korean nurses, and correlation is analyzed with frequent word analysis and keyword network analysis. Results: Through the YouTube algorithm, 2,273 videos of 'Nurse' were analyzed in order of recent views, relevance, and rating, and 2,912 videos searched for with the keyword 'Nurse + Hospital, COVID-19, Awareness, University, National Examination' were analyzed. Numerous videos were uploaded, and nursing work that was uploaded in the form of a vlog recorded a high number of views. Conclusion: We could see if the YouTube video shows images of nurses. It has been confirmed that various information is being exchanged rather than information just for promotional purposes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5506-5521
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• 2017

Three-dimensional video (3DV), as the new generation of video format standard, can provide the viewers with a vivid screen sense and a realistic stereo impression. Meanwhile the view synthesis has become an important issue for 3DV application. Differently from the conventional methods based on depth, in this paper we propose a new view synthesis algorithm, which can employ the correlation among views and warp in the image domain only. There are mainly two contributions. One is the incorporation of sobel edge points into feature extraction and matching, which can obtain a better stable homography and then a visual comfortable synthesis view compared to SIFT points only. The other is a novel image blending method proposed to obtain a better synthesis image. Experimental results demonstrate that the proposed method can improve the synthesis quality both in subjectivity and objectivity.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2212-2214
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• 1998

As there comes out better and better solutions for delivering multimedia data on the internet, the number of WebCAM sites which transmits pictures of any spot to the user's system is getting increased. WebCAM service over the internet can be compared with the CATV in that it is beyond the spatial constraints. In this project, we construct a WebCAM site which performs not only the fundamental WebCAM functions of capturing images and of transmitting them periodically but also various kinds of modules carrying out tasks such as image processing, remote control of the camera, processing multiple user requests, making panorama views and so on using Java which is the most popular language for the internet or CGI. The past images are stored in a database implemented for the WebCAM system, so the system can be extended to get over the constraints in time also.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.853-873
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• 2021

In recent years, deep reinforcement learning (DRL) models are enjoying great interest as their success in a variety of challenging tasks. Deep Q-Network (DQN) is a widely used deep reinforcement learning model, which trains an intelligent agent that executes optimal actions while interacting with an environment. This model is well known for its ability to surpass skilled human players across many Atari 2600 games. Although DQN has achieved excellent performance in practice, there lacks a clear understanding of why the model works. In this paper, we present a visual analytics system for understanding deep Q-network in a non-blind matter. Based on the stored data generated from the training and testing process, four coordinated views are designed to expose the internal execution mechanism of DQN from different perspectives. We report the system performance and demonstrate its effectiveness through two case studies. By using our system, users can learn the relationship between states and Q-values, the function of convolutional layers, the strategies learned by DQN and the rationality of decisions made by the agent.

• Journal of Korean Elementary Science Education
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• v.18 no.2
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• pp.1-19
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• 1999

Based on the analysis of commonalities and differences in the views of science achievement in major reform documents in the United States and Korea, an aggregated view of science achievement is presented in this paper Science achievement is conceived of in terms of science content and science process. The components of science content include: (a) concepts and theories I n physical, life, and earth and space science;(b) science, mathematics, and technology;(c) science in personal and social perspectives;(d)history and nature of science;and (e) unifying themes. The components of science process include: (a) scientific understanding;(b) scientific investigation;(c) scientific communication; and (d) scientific habits of mind. The components of science process.cut across and intersect with the components of science content. The components of science achievement overlap and are related to one another. Despite such an overlap, understanding the rot e that each component plays provides insight into its unique contributions as well as its interactions with other components. A definition of science achievement and identification of its components based on major reform documents provides a guideline for science assessment as well a s science teaching and learning.

• Journal of the Korea Safety Management & Science
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• v.10 no.4
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• pp.315-325
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• 2008

This study examines the effect of brand personality on consumer's attitude. Previous research has suggested that the greater the congruity between consumer personalities and brand personalities, the greater the preference for the brand. However, empirical explorations of this hypothesis revealed that the congruity between consumer personalities and brand personalities is limitedly related, if ever, to the preference for the brand. It is partly because of the views of the previous researchers who considered human personality as a uni-dimensional concept, and partly because of the lack of consensus regarding what brand personality really is. This study examines the relative effect of brand personality on company image. In this study, brand personality is represented by the 'Big Five' factors - Sincerity, Excitement, Competence, Sophistication and Ruggedness - which were suggested by Jennifer Aaker.