• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.4
• /
• pp.825-840
• /
• 2015

Adaptive bitrate (ABR) streaming technology has become an important and prevalent feature in many multimedia delivery systems, with content providers such as Netflix and Amazon using ABR streaming to increase bandwidth efficiency and provide the maximum user experience when channel conditions are not ideal. Where such systems could see improvement is in the delivery of live video with a closed loop cognitive control of video encoding. In this paper, we present streaming camera system which provides spatially and temporally adaptive video streams, learning the user's preferences in order to make intelligent scaling decisions. The system employs a hardware based H.264/AVC encoder for video compression. The encoding parameters can be configured by the user or by the cognitive system on behalf of the user when the bandwidth changes. A cognitive video client developed in this study learns the user's preferences(i.e. video size over frame rate) over time and intelligently adapts encoding parameters when the channel conditions change. It has been demonstrated that the cognitive decision system developed has the ability to control video bandwidth by altering the spatial and temporal resolution, as well as the ability to make scaling decisions.

• Journal of the Korea Convergence Society
• /
• v.9 no.1
• /
• pp.419-431
• /
• 2018

In this paper, we propose a novel method for monitoring mood trend of Twitter users by analyzing their daily tweets for a long period. Then, to more accurately understand their tweets, we analyze all types of content in tweets, i.e., texts and emoticons, and images, thus develop a multimodal sentiment analysis method. In the proposed method, two single-modal analyses first are performed to extract the users' moods hidden in texts and images: a lexicon-based and learning-based text classifier and a learning-based image classifier. Thereafter, the extracted moods from the respective analyses are combined into a tweet mood and aggregated a daily mood. As a result, the proposed method generates a user daily mood flow graph, which allows us for monitoring the mood trend of users more intuitively. For evaluation, we perform two sets of experiment. First, we collect the data sets of 40,447 data. We evaluate our method via comparing the state-of-the-art techniques. In our experiments, we demonstrate that the proposed multimodal analysis method outperforms other baselines and our own methods using text-based tweets or images only. Furthermore, to evaluate the potential of the proposed method in monitoring users' mood trend, we tested the proposed method with 40 depressive users and 40 normal users. It proves that the proposed method can be effectively used in finding depressed users.

• Journal of the Society of Cosmetic Scientists of Korea
• /
• v.40 no.1
• /
• pp.55-88
• /
• 2014

In this study, we examined the use of cosmetics among adolescents in our country and their purchasing behavior, as the use of cosmetics has increasingly been prevailing in the younger generation. The aims of this study were to investigate the state of the youth cosmetics market, to grasp the needs of youth and ultimately to suggest the right directions for the youth cosmetics market. The subjects in this study were 1,092 boys and girls from 10 selected secondary schools in Seoul. After a survey was conducted, the answer sheets from 1,074 respondents were gathered, and the collected data were analyzed by the statistical package (SPSS WIN 18.0). The vast majority of the teens participated in the survey were answered to use basic cosmetics daily, and there was a gradual increase in the frequency that they used color cosmetics. They started to use cosmetics earlier in ages than the older generations. Most of them were in trouble due to acne, and the most dominant way to get rid of their skin troubles was by using cosmetics. The most common place at which they purchased cosmetics were brand shops, and they gave priority to the function of the products when they bought cosmetics. The adolescents were still told by their schools to abstain from using cosmetics, and that was the case for social climate as well. Yet they definitely wanted to be allowed to use cosmetics.

• Journal of The Korean Association For Science Education
• /
• v.32 no.2
• /
• pp.320-330
• /
• 2012

Understanding the relation between basic science and applied science is important for students in understanding the importance of learning science, the relationship between scientific knowledge and human life, and for enhancing their science motivation. In this study, we evaluated the statistical validity of this hypothetical model and explored the effect of gender and students' preferred courses (e.g., humanities, science, and art) on four dependent variables. We also evaluated the differences of students' understanding across scientific domains and students' understanding concerning basic and applied scientific knowledge. Three hundred and twenty five 10th grade students participated in this survey research. Statistically, we employed bivariate correlation, partial correlation, path analysis, two-way ANOVA, and repeated measures ANOVA. Our findings illustrated that our hypothetical model was statistically valid. In addition, the significant interaction effects of gender and students' preferred courses on each dependent variable were shown. Students have different levels of understanding of the convergence of basic and applied science, the relation between scientific knowledge and human life, and the importance of learning science across scientific domains (e.g., physics, chemistry, earth science and biology).

• The Journal of Society for e-Business Studies
• /
• v.22 no.4
• /
• pp.159-173
• /
• 2017

In order to provide technical financial support to small and medium-sized venture companies based on technology, the government implemented the TCB evaluation, which is a kind of technology rating evaluation, from the Kibo and a qualified private TCB. In this paper, we briefly review the current state of TCB evaluation and available indicators related to technology evaluation accumulated in the Korea Credit Information Services (TDB), and then use indicators that have a significant effect on the technology rating score. Multiple regression techniques will be explored. And the relative importance and classification accuracy of the indicators were calculated by applying the key indicators as independent features applied to the generalized boosting model, which is a representative machine learning classifier, as the class influence and the fitness of each model. As a result of the analysis, it was analyzed that the relative importance between the two models was not significantly different. However, GBM model had more weight on the InnoBiz certification, R&D department, patent registration and venture confirmation indicators than regression model.

• KIPS Transactions on Software and Data Engineering
• /
• v.6 no.4
• /
• pp.203-210
• /
• 2017

In this paper, we propose an effective neural network model for image caption generation and model transfer. This model is a kind of multi-modal recurrent neural network models. It consists of five distinct layers: a convolution neural network layer for extracting visual information from images, an embedding layer for converting each word into a low dimensional feature, a recurrent neural network layer for learning caption sentence structure, and a multi-modal layer for combining visual and language information. In this model, the recurrent neural network layer is constructed by LSTM units, which are well known to be effective for learning and transferring sequence patterns. Moreover, this model has a unique structure in which the output of the convolution neural network layer is linked not only to the input of the initial state of the recurrent neural network layer but also to the input of the multimodal layer, in order to make use of visual information extracted from the image at each recurrent step for generating the corresponding textual caption. Through various comparative experiments using open data sets such as Flickr8k, Flickr30k, and MSCOCO, we demonstrated the proposed multimodal recurrent neural network model has high performance in terms of caption accuracy and model transfer effect.

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.25 no.2
• /
• pp.59-76
• /
• 2014

The purpose of this study is to recommend on the public library service for older adults through the analysis of the perceptions of older adults and librarians. To achieve the study purpose, interview method was employed. The interview questions are composed based on the ALA guidelines. According to the study results, the following ten factors were recommended by older adults: 1) various customized life long learning programs for older adults, 2) highly qualified staff for the public library life long learning programs and regular evaluation for the staff, 3) provision of various and new information resources, 4) promotion of public library services and programs, 5) public library staff's kindness and professionalism, 6) regular reeducation of the public library staff, 7) library user education, 8) customized resources, facilities, and equipments for older adults, 9) provision of the library space, and 10) customized library services for older adults. In addition, the following four factors were mentioned by librarians: 1) customized services and programs for older adults, 2) customized collection, facilities, and equipments, 3) adequate budget for public library service for older adults, 4) professionals for the public library service for older adults. The followings were recommended by both the older adults and librarians: 1) Customized library services, programs, collection, equipments, facilities for older adults, 2) Professionals for the public library service for older adults and Regular reeducation for them.

• Korean Journal of Social Welfare
• /
• v.56 no.1
• /
• pp.23-43
• /
• 2004

The purpose of this paper is to evaluate the performance of New Deal under the New Labour government in Britain and examines the nature of New Deal with respect to workfare. The time difference of five years after the New Deal was put into effect shows that New Deal has contributed not only to include the socially excluded groups such as the young unemployed, the long-term unemployed, single parents, and the disabled into the labour market, but also to decrease the amount of income-based benefits providing for working generation. It can be said that the nature of New Deal under the New Labour is near to human capital development model rather than labour force attachment model. New Deal provides the opportunity of policy learning for the countries which pursue the reform of social security system to moving welfare beneficiaries being able to work into jobs. Policy learning can be summed up as follows. First, imposing mutual responsibility and obligations on unemployed person should be accompanied by implementing active labour market programmes of education and job training. Second, the delivery system which administrates workfare programmes should be decentralized in a local society. The cooperation between local government and enterprisers will be critical in implementing various employment programmes and moving unemployed person into jobs. Third, the case management for individual participating in workfare programme is necessary. The personal adviser should continue to provide employment services for the unemployed until he or she get a job and enter the state of self-reliance. Finally, the workfare programme should be firmly backed by the political leadership in order to overcome the oppositions of beneficiary groups under the existing social security system.

• Culinary science and hospitality research
• /
• v.19 no.5
• /
• pp.280-295
• /
• 2013

This study analyzes the differences to examine which education is more effective for practical cooking skills. A survey was conducted on the 4 year university students majoring in culinary arts to examine the recognition levels of culinary practice education for the purpose of searching for an improvement plan for culinary education. The results are as follows. Seniors recognize the importance of learning theory, while the classes offered now are focusing on getting cooking certificates. The students approach cooking not only for eating food but also for the arts, showing increased interests in 'creative food' and 'fusion food.' In class, they feel the necessity of establishing a standard for a fair assessment and English skills for the globalization of food service. Hereupon this study recognizes the current state of culinary education service, draws factors which decide the quality of culinary arts education, and examines student satisfaction with theoretical education, practical education, assessment, and external education by using a factor analysis of twenty quality attributes. Through the development and application of various programs, operation of open practice classes and culinary organization reflecting social changes in learning courses, the culinary arts education is considered to be more vitalized. In this respect, this study introduces four measures which were designed to facilitate the education of highly-skilled human resources in the culinary field.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.16 no.2
• /
• pp.164-171
• /
• 2006

Recently Digital multimedia broadcasting (DMB) has been available as a commercial service. The users sometimes have difficulty in finding their preferred multimedia contents and need to spend a lot of searching time finding them. They are even very likely to miss their preferred contents while searching for them. In order to solve the problem, we need a method for recommendation users preferred only minimum information. We propose an algorithm and a system for recommending users' preferred contents using preference transition probability from user's usage history. The system includes four agents: a client manager agent, a monitoring agent, a learning agent, and a recommendation agent. The client manager agent interacts and coordinates with the other modules, the monitoring agent gathers usage data for analyzing the user's preference of the contents, the learning agent cleans the gathered usage data and modeling with state transition matrix over time, and the recommendation agent recommends the user's preferred contents by analyzing the cleaned usage data. In the recommendation agent, we developed the recommendation algorithm using a user's preference transition probability for the contents. The prototype of the proposed system is designed and implemented on the WIPI(Wireless Internet Platform for Interoperability). The experimental results show that the recommendation algorithm using a user's preference transition probability can provide better performances than a conventional method.