• Trans-
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• v.8
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• pp.79-93
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• 2020

The main purpose of this article is to discuss the impact of "Dance Smash" TV show on Chinese dance, which uses the combination of dance and new media technology as the core content of the program. "Dance Smash", as a dance communication TV program for the public, first considers the entertainment attributes of variety shows. Spread the dance art on the basis of meeting the public's aesthetic needs, thereby expanding the popular living space of dance art. The use of 'moment of the storm' has let the general audience of non-dance majors feel the technical charm of dances, thus playing a healthy promotion role. However, whether "Bullet Time", a type of dance program that has had a successful case in the West, can also have a positive impact on the mass communication of dance in the localization of China, this is what questions and seeks of this article.

• Knowledge Management Research
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• v.20 no.3
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• pp.155-171
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• 2019

In the entertainment industry which has great uncertainty, it is essential to predict public preference first. Thanks to various mass media channels such as cable TV and internet-based streaming services, the reality audition program has been getting big attention every day and it is being used as a new window to new entertainers' debut. This phenomenon means that it is changing from a closed selection process to an open selection process, which delegates selection rights to the public. This is characterized by the popularity of the public being reflected in the selection process. Therefore, this study aims to implement a machine learning model which predicts the winner of , which has recently been popular in South Korea. By doing so, this study is to extend the research method in the cultural industry and to suggest practical implications. We collected the data of winners from the 1st, 2nd, and 3rd seasons of the Produce 101 and implemented the predictive model through the machine learning method with the accumulated data. We tried to develop the best predictive model that can predict winners of by using four machine learning methods such as Random Forest, Decision Tree, Support Vector Machine (SVM), and Neural Network. This study found that the audience voting and the amount of internet news articles on each participant were the main variables for predicting the winner and extended the discussion by analyzing the precision of prediction.

• Journal of the Korean Society of Food Culture
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• v.25 no.2
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• pp.160-169
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• 2010

This study was conducted to examine the relationship between dietary habits and time spent watching TV and using internet, in elementary school children. The data were collected by a questionnaire survey of 712 elementary school children, within Gwangju and Jeonnam area. The SPSS 12.0/win program was used to analyze the 523 samples. Amount of TV-watching time was found to be related to the dietary habit score in the subjects. The children who watch TV "less than 1 hour/day" on weekdays had a better dietary habit score than those who watch TV "more than 1 hour" (p<0.0001). The children who watch TV "less than 2 hours/day" on weekends had a better dietary habit than the children who watch TV "more than 2 hours/day" (p<0.0001). The internet usage was also related to the dietary habit score in these children: those who use internet "less than 1 hour/day" on weekdays had a better dietary habit score than the children who use internet "more than 2 hours/day" (p<0.0001). The children who use internet "less than 2 hours/day" on weekends had a better dietary habit score than the children who use internet "more than 2 hours/day" (p<0.0001). These results indicate that the children tend to have a better diet when their TV and internet time is limited and thus healthy dietary behavior is negatively associated with a sedentary pattern of activity in elementary school children.

• The Journal of the Korea Contents Association
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• v.8 no.2
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• pp.100-115
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• 2008

This case study states the suitability of using the program, Flash, when producing television series animations. It states the conveniences for the users of Flash when used as an animating tool, the advantages Flash has due to compatibility with other programs, the reduction of production costs, and more. The purpose of this case study is to introduce new overseas Flash animation production techniques for easier production, technically and financially. The outcome of the analysis states the importance of training animators that are able to make high quality television series animations using the new overseas flash animation techniques.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1997.06a
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• pp.75-81
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• 1997

A new DTPP (Desk-Top Program Production) system has been developed that enables multiple program producers (directors) working at different locations to collaborate over a computer network and prepare a single program for broadcasting. In this system, information is shared among users by exchanging data edited on non-linear editing terminals in program post-production work over a network in real time. In short, the new DTPP system provides a collaborative work space for producing TV programs. The system does not make use of a special server for collaborative work but rather multiple interconnected editing terminals having the same functions. In this configuration, data at a terminal which has just been edited by some operation is forwarded to all other connected terminals for updating. This form of information sharing, however, requires that some sort of data synchronizing method be established since multiple terminals are operating on the same data simultaneously. We therefore adopt a method whereby the system synchronizes the clocks on each terminal at the time of connection and sends an operation time stamp together with edited data. This enables most recently modified data to be identified and all information on all terminals to be updated appropriately. This paper provides an overview of this new collaborative DTPP system and describes the techniques for exchanging edited data and synchronizing data.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.414-421
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• 2005

시청률은 각 방송사의 주요 수입원인 광고비 책정의 중요한 변수이다. 따라서 프로그램 편성자(Program Planner)는 경쟁 방송사의 편성을 고려한 시청률 최대화 전략을 수립하려 하며, 시청률 예측 모델을 사용하여 그 목적을 달성할 수 있다. 나아가 시청률 예측모델이 정확할수록 현재의 임의적인 광고비 책정 방식보다 정확한 광고비의 가격 책정이 가능해져 보다 합리적인 광고 및 미디어 시장 환경을 성립할 수 있다. 본 연구에서는 최근의 국내 TV 시청률 자료를 이용하여 국내 공중파 방송에 대한 시청률 예측 모델을 성립하고, 이를 이용한 시청률 최대화 전략을 제시한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.06a
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• pp.34-35
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• 2013

본 논문에서는 오디오 피크 검출을 적용한 TV 방송 프로그램내 배경음악 식별 알고리즘을 제안한다. 제안한 알고리즘은 음악 핑거프린트 추출 및 전송부, 음악구간 검출부, 음악 핑거프린트는 고속 매칭 및 정보전송부 세 부분으로 구성되어 있다. 음악 핑거프린트 추출 및 전송부에서는 음악 원음 오디오 데이터를 퓨리에 변환하여 스펙트럼 계수를 추출한다. 추출된 스펙트럼의 성분 중에서 일정한 문턱값 이상의 에너지를 가지는 값을 피크로 검출하고 검출된 피크를 이용하이 핑거프린트를 생성하고 데이터 베이스화한다. 음악구간 검출부에서는 입력된 방송 프로그램 오디오 데이터에 GMM(Gaussian Mixture Model)을 적용하여 음악과 음악 외 오디오 데이터를 분류한다. 음악 핑거프린트 고속 매칭 및 정보전송부에서는 음악구간이라고 인식된 쿼리 오디오 데이터를 음악 핑거프린트 추출 및 전송부와 동일한 과정을 통해 핑거프린트를 생성하고 데이터 베이스화된 음악 원음의 핑거프린트들과 비교하여 가장 유사한 음원의 정보를 TV의 화면에 자막으로 보여준다.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.11a
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• pp.801-804
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• 2004

2001년 하반기 이후 디지털 TV 시대가 열리면서 채널의 수와 그에 따른 프로그램의 수가 폭발적으로 증가했다. 그리하여 기존의 방법으로는 시청자가 원하는 프로그램을 선택하는 것이 어려운 일이 되었다. 이 문제를 해결하는 방안으로서 pEPG(personalized Electronic Program Guide)가 많이 연구되어 왔으며 본 논문에서는 pEPG를 위한 추천 방법에 대해 연구하고자 한다. 기존의 추천 방법은 내용기반추천과 협업추천이 대표적인데, 이들은 어느 한족이 우월하다기 보다 각각의 단점을 상호보완해주는 관계에 있다. 각 추천 방법이 TV환경의 pEPG에 적용될 때는 어떤 장단점이 있는지 살펴보고, 이에 인구통계학적추천을 혼합한 기법을 제안한다.

• Korean journal of communication and information
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• v.77
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• pp.36-72
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• 2016

Comprehensive Cable TV Channels(CCCs) has been established as a political product around 5 years ago, and it's influence and position on the broadcasting field are keep increasing. CCC's stabilization is based on flooding the market with journalism. The repeating news and current affairs programs are appearing constantly in the afternoon which is CCC's primetime. The current affairs talk shows are a product of CCC's representative program type and it leads unique CCC style journalism. The guests of the current affairs talk show leading the program with critiques(comments) and discussions about political issues. The purpose of this study is to explore how these guests of the current affairs talk shows conceptually positioned as political mediating elites and same time to explore the television political landscape through the representative current affairs talk shows from TV chosun, Channel A, MBN, JTBC which are present by these political elites. This study wants to find out about that television political effects from CCCs which exemplified into certain directions by these political mediating elites saying their political biases and expresses their feelings drastically that causes high ratings and brings people's attention. The guests who called political mediating elites in this study are mostly considered to be extreme rightist, conservatives, conservative-centrist and they have close relationship with certain political party or political group. The political mediating elites gain the popularities and have great influence on the public from performing the television politics through CCCs' current affairs talk shows and use that to make political exchange connections with political groups. Therefore this study wants to point out that CCCs' current affairs talk shows are situated in political rally, exchange connection, so current affairs talk shows are existing only for political battle field.

• Journal of Broadcast Engineering
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• v.9 no.4 s.25
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• pp.305-321
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• 2004

With the advent of the digital broadcasting, the audiences can access a large number of TV programs and their information through the multiple channels on various media devices. The access to a large number of TV programs can support a user for many chances with which he/she can sort and select the best one of them. However, the information overload on the user inevitably requires much effort with a lot of patience for finding his/her favorite programs. Therefore, it is useful to provide the persona1ized broadcasting service which assists the user to automatically find his/her favorite programs. As the growing requirements of the TV personalization, we introduce our automatic user preference learning algorithm which 1) analyzes a user's usage history on TV program contents: 2) extracts the user's watching pattern depending on a specific time and day and shows our automatic TV program recommendation system using MPEG-7 MDS (Multimedia Description Scheme: ISO/IEC 15938-5) and 3) automatically calculates the user's preference. For our experimental results, we have used TV audiences' watching history with the ages, genders and viewing times obtained from AC Nielson Korea. From our experimental results, we observed that our proposed algorithm of the automatic user preference learning algorithm based on the Bayesian network can effectively learn the user's preferences accordingly during the course of TV watching periods.