• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.12
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• pp.1-8
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• 2005

In this paper, we study a call admission control algorithm for supporting multicast service under the BcN environment where broadcasting, communication and Internet are converging to be one. It is necessary to control service requests with a certain criteria in order to guarantee QoS because the system capacity is limited. As a possible solution, we divide one multicast service into 3 classes and set up a threshold per each class to control service request. Especially, for the purpose of system benefit, we define system pay-off rate 'GAIN' with the term 'Reward' and 'Penalty' according to admit and reject service request. And we confine the range of threshold which makes GAIN to be maximized. For the performance analysis, we model the system as M/M/m/m queueing system, investigate GAIN under various conditions and show the effectiveness of the proposed algorithm.

• International journal of advanced smart convergence
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• v.7 no.1
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• pp.42-47
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• 2018

Recently, as the demand for limited resources continues to rise and problems of resource depletion rise worldwide, the importance of renewable energy is gradually increasing. In order to solve these problems, various methods such as energy conservation and alternative energy development have been suggested, and biogas, which can utilize the gas produced from biomass as fuel, is also receiving attention as the next generation of innovative renewable energy. New and renewable energy using biogas is an energy production method that is expected to be possible in large scale because it can supply energy with high efficiency in compliance with energy supply method of recycling conventional resources. In order to more efficiently produce and manage these biogas, a biogas plant has emerged. In recent years, a large number of biogas plants have been installed and operated in various locations. Organic wastes corresponding to biogas production resources in a biogas plant exist in a wide variety of types, and each of the incoming raw materials is processed in different processes. Because such a process is required, the case where the biogas plant process is inefficiently operated is continuously occurring, and the economic cost consumed for the operation of the biogas production relative to the generated biogas production is further increased. In order to solve such problems, various attempts such as process analysis and feedback based on the feedstock have been continued but it is a passive method and very limited to operate a medium/large scale biogas plant. In this paper, we propose "CNN-based production yield prediction algorithm for increasing process efficiency of biogas plant" for efficient operation of biogas plant process. Based on CNN-based production yield forecasting, which is one of the deep-leaning technologies, it enables mechanical analysis of the process operation process and provides a solution for optimal process operation due to process-related accumulated data analyzed by the automated process.

• The KIPS Transactions:PartC
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• v.18C no.4
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• pp.227-236
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• 2011

IPTV(Internet Protocol Television) is one of the typical businesses which are the convergence of Broadcast and Communication. It provides broadcasting service using IP networks. Recently, IPTV service is developed to Mobile IPTV or Open IPTV. Especially, Open IPTV uses open platform so not only service providers but also general users can provide contents to other users. Open IPTV system has many content providers, so existing security solution of IPTV cannot be adopted. In this paper, we suggest user authentication and key distribution mechanism on Open IPTV. Our proposed mechanism is based on Kerberos, so it can support distribution environment such as Open IPTV. We demonstrate that proposed mechanism can guarantee secure transmission of contents and reduce the delay of user authentication on Open IPTV system compared to other authentication mechanisms. We also compare our proposal and other mechanisms in various aspects, and analyze efficiency and safety of proposed mechanism. As a result, we insist that this mechanism satisfies the security requirements for IPTV.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.497-502
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• 2022

Information delivery among young generation has a distinct tendency to prefer visual to text as means of information distribution and sharing recently, and it is natural to distribute information through Youtube or one-man broadcasting on Internet. That is, young generation usually get their information through this kind of distribution procedure. Many young generation are also drastic and more aggressive for decorating themselves very uniquely. It tends to create personal characteristics freely through drastic expression and attempt of face makeup, hair styling and fashion coordination without distinction of sex. Especially, face makeup becomes an object of major concern among males nowadays, and female of course, then it is the major means to express their personality. In this study, to meet the demands of the times, we design and implement the intellectual smart mirror application that efficiently retrieves and recommends the related videos among Youtube or one-man broadcastings produced by famous professional makeup artists to implement the face makeup congruous with our face shape, hair color & style, skin tone, fashion color & style in order to create the face makeup that represent our characteristics. We also introduce the AI technique to provide optimal solution based on the learning of user's search patterns and facial features, and finally provide the detailed makeup face images to give the chance to get the makeup skill stage by stage.

• Korean journal of communication and information
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• v.79
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• pp.40-69
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• 2016

This study examines how the Korean media has covered the leukemia case of Samsung workers. The news articles on the cases, published in the three terrestrial broadcasting stations, the five major newspapers, progressive Internet news media, conservative Internet news media, and business newspapers between 2007 and 2015, were retrieved and analyzed. Four characteristics of news reports were discovered as following: First, while conservative news media and business news media have exnominated the first phase of the case in which a civil organization Sharp claimed that Samsung workers had leukemia from their workplace; they have nominated the second phase of the case in which Samsung attempted to solve the problem by compensating the victims for their disease. Second, the media generally have displayed more interests in the results than in the causes of the case. Third, the conservative press and business newspapers have reported the case in favor of Samsung rather than laborer victims. Fourth, the conservative press have deployed market-friendly discourses, rather than problematizing the state and civil society. Through an abduktive analysis, this study argues that except the Hangyore and Kyunghyang Shinmun, most of the Korean media, assuming pro-business attitude, do not question or clarify where the responsibility of the industrial disaster lies by displaying their interests in the phase of solution, not in the phase of cause.

• Smart Media Journal
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• v.8 no.1
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• pp.74-81
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• 2019

Recently, machine learning technology has had a significant impact on society, particularly in the medical, manufacturing, marketing, finance, broadcasting, and agricultural aspects of human lives. In this paper, we study how to apply machine learning techniques to foods, which have the greatest influence on the human survival. In the field of Smart Farm, which integrates the Internet of Things (IoT) technology into agriculture, we focus on optimizing the crop growth environment by monitoring the growth environment in real time. KT Smart Farm Solution 2.0 has adopted machine learning to optimize temperature and humidity in the greenhouse. Most existing smart farm businesses mainly focus on controlling the growth environment and improving productivity. On the other hand, in this study, we are studying how to apply machine learning with respect to harvest time so that we will be able to harvest fruits of the highest quality and ship them at an excellent cost. In order to apply machine learning techniques to the field of smart farms, it is important to acquire abundant voluminous data. Therefore, to apply accurate machine learning technology, it is necessary to continuously collect large data. Therefore, the color, value, internal temperature, and moisture of greenhouse-grown fruits are collected and secured in real time using color, weight, and temperature/humidity sensors. The proposed FPSML provides an architecture that can be used repeatedly for a similar fruit crop. It allows for a more accurate harvest time as massive data is accumulated continuously.