• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.10 no.1
• /
• pp.49-53
• /
• 2010

e-learning and m-learning have some problems that data transmission frequently discontinuously, communication cost increases, the computation speed of mass data drops, battery limitation in the mobile learning environments. In this paper, we propose the PULIMS for u-learning systems. The proposed system intellectualize the education environment using intelligent mobile agent, supports the customized education service, and helps that learners feasible access to the education information through mobile phone. We can see the fact that the efficience of proposed method is outperformed that of the conventional methods. The PULIMS is new technology that can be used to learn whenever and wherever learners want in Ubiquitous education environment.

• The Journal of the Convergence on Culture Technology
• /
• v.8 no.2
• /
• pp.1-6
• /
• 2022

Lifelog is a digital record of an individual collected from various digital sensors, and includes activity amount, sleep information, weight change, body mass, muscle mass, fat mass, etc. Recently, as wearable devices have become common, a lot of high-quality lifelog data is being produced. Lifelog data shows the state of an individual's body, and can be used not only for individual health care, but also for causes and treatment of diseases. However, at present, AI/ML-based correlation analysis and personalization are not reflected. It is only at the level of presenting simple records or fragmentary statistics. Therefore, in this paper, the correlation/relationship between lifelog data and disease, and AI/ML technology inside lifelog data are examined, and furthermore, a lifelog data analysis process based on AI/ML is proposed. The analysis process is demonstrated with the data collected in the actual Galaxy Watch. Finally, we propose a future convergence service roadmap including lifelog data, diet, health information, and disease information.

• Journal of Internet Computing and Services
• /
• v.16 no.6
• /
• pp.133-141
• /
• 2015

Mass multimedia contents are shared through various social media servies including social network service. As social network reveals user's current situation and interest, highly satisfactory personalized recommendation can be made when such features are applied to the recommendation system. In addition, classifying the music by emotion and using analyzed information about user's recent emotion or current situation by analyzing user's social network, it will be useful upon recommending music to the user. In this paper, we propose a music recommendation method that makes an emotion model to classify the music, classifies the music according to the emotion model, and extracts user's current emotional state represented on the social network to recommend music, and evaluates the validity of our method through experiments.

• Journal of Powder Materials
• /
• v.23 no.2
• /
• pp.149-169
• /
• 2016

Additive manufacturing (AM) is defined as the manufacture of three-dimensional tangible products by additively consolidating two-dimensional patterns layer by layer. In this review, we introduce four fundamental conceptual pillars that support AM technology: the bottom-up manufacturing factor, computer-aided manufacturing factor, distributed manufacturing factor, and eliminated manufacturing factor. All the conceptual factors work together; however, business strategy and technology optimization will vary according to the main factor that we emphasize. In parallel to the manufacturing paradigm shift toward mass personalization, manufacturing industrial ecology evolves to achieve competitiveness in economics of scope. AM technology is indeed a potent candidate manufacturing technology for satisfying volatile and customized markets. From the viewpoint of the innovation technology adoption cycle, various pros and cons of AM technology themselves prove that it is an innovative technology, in particular a disruptive innovation in manufacturing technology, as powder technology was when ingot metallurgy was dominant. Chasms related to the AM technology adoption cycle and efforts to cross the chasms are considered.

• Journal of information and communication convergence engineering
• /
• v.20 no.4
• /
• pp.288-294
• /
• 2022

The media content market has been growing, as various types of content are being mass-produced owing to the recent proliferation of the Internet and digital media. In addition, platforms that provide personalized services for content consumption are emerging and competing with each other to recommend personalized content. Existing platforms use a method in which a user directly inputs video metadata. Consequently, significant amounts of time and cost are consumed in processing large amounts of data. In this study, keyframes and audio spectra based on the YCbCr color model of a movie trailer were extracted for the automatic generation of metadata. The extracted audio spectra and image keyframes were used as learning data for genre recognition in deep learning. Deep learning was implemented to determine genres among the video metadata, and suggestions for utilization were proposed. A system that can automatically generate metadata established through the results of this study will be helpful for studying recommendation systems for media super-personalization.

• The Journal of the Korea Contents Association
• /
• v.5 no.4
• /
• pp.1-10
• /
• 2005

After Yahoo Korea opened up the Internet portal market in Korea in 1997, the Korean portal market has experienced fierce competition in the beginning of 2000s. After that period, however, Korean portal market looks relatively stable with top five rankers forming oligopoly and shows that Arthur's claim of network externalities can be applied to the portal industry. In this paper, based on case study of the Korean portals we empirically examined how portals have developed and evolved. In this course, we also investigated the sources of portal's competitiveness. The findings of the research suggest that portals develop and evolve through the reflexive four stages in which they compete over different goals: 1) service quality, 2) critical mass of customers, 3) interpersonal interactivity, and 4) innovative service. According to this framework of portal's evolution, we show that top ranking portals in the present have succeeded in accomplishing the goals of each stage.

• Archives of design research
• /
• v.18 no.1 s.59
• /
• pp.195-204
• /
• 2005

Due to the of evolution of digital technology, trends are moving toward personalization and customization in design (art), media, science. Existing mass media has been broadcasting to the general public due to technical and economic limitation and art works also communicate one-sidedly with spectators in the gallery or stage. But nowaday, it is possible for spectators to participate directly. We can make different products depending on the tastes of individuals who demand media or art. The essence of technology which makes it possible is 'interactive technology'. A goal of this research is to find out the true nature of the interactive design in multimedia contents and find the course of interactive communication design research. In this paper, we pass through two stages to solve this kind of problem. At first, we studied the concept of multimedia contents from the aspect of information revolution. Next, we decided our research topic to be 'visual reacting with audio' and made audio-visual art work as graphic designers. Through this research we can find the possibility to promote 'communication' in a broad sense, with appropriate interactive design.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.10a
• /
• pp.277-280
• /
• 2021

Recently as various contents are mass produced based on high accessibility, the media contents market is more active. Users want to find content that suits their taste, and each platform is competing for personalized recommendations for content. For an efficient recommendation system, high-quality metadata is required. Existing platforms take a method in which the user directly inputs the metadata of an image. This will waste time and money processing large amounts of data. In this paper, for media hyperpersonalization recommendation, keyframes are extracted based on the YCrCb color model of the video based on movie trailers, movie genres are distinguished through supervised learning of artificial intelligence and In the future, we would like to propose a utilization plan for generating metadata.

• Journal of Internet Computing and Services
• /
• v.22 no.1
• /
• pp.109-135
• /
• 2021

his study classified the development process of artificial intelligence (AI) speakers through analysis of the news text of artificial intelligence (AI) speakers shown in traditional news reports, and identified the characteristics of each product by period. The theoretical background used in the analysis are news frames and topic frames. As analysis methods, topic modeling and semantic network analysis using the LDA method were used. The research method was a content analysis method. From 2014 to 2019, 2710 news related to AI speakers were first collected, and secondly, topic frames were analyzed using Nodexl algorithm. The result of this study is that, first, the trend of topic frames by AI speaker provider type was different according to the characteristics of the four operators (communication service provider, online platform, OS provider, and IT device manufacturer). Specifically, online platform operators (Google, Naver, Amazon, Kakao) appeared as a frame that uses AI speakers as'search or input devices'. On the other hand, telecommunications operators (SKT, KT) showed prominent frames for IPTV, which is the parent company's flagship business, and 'auxiliary device' of the telecommunication business. Furthermore, the frame of "personalization of products and voice service" was remarkable for OS operators (MS, Apple), and the frame for IT device manufacturers (Samsung) was "Internet of Things (IoT) Integrated Intelligence System". The econd, result id that the trend of the topic frame by AI speaker development period (by year) showed a tendency to develop around AI technology in the first phase (2014-2016), and in the second phase (2017-2018), the social relationship between AI technology and users It was related to interaction, and in the third phase (2019), there was a trend of shifting from AI technology-centered to user-centered. As a result of QAP analysis, it was found that news frames by business operator and development period in AI speaker development are socially constituted by determinants of media discourse. The implication of this study was that the evolution of AI speakers was found by the characteristics of the parent company and the process of co-evolution due to interactions between users by business operator and development period. The implications of this study are that the results of this study are important indicators for predicting the future prospects of AI speakers and presenting directions accordingly.