• Journal of Information Technology Services
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• v.13 no.4
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• pp.189-203
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• 2014

With the evolution of Internet technologies and the increasing variety of Internet devices, advertisements in various web services have also expanded. Interactive web services often go hand in hand with effective advertisements for a business model. We estimated statistical parameters of the interactive web server for service monitoring and advertisement-effect. In the web pages, we integrated the plugins of social networking services (SNSs) (e.g. Facebook, Twitter) and an advertisement scheme (e.g. Google AdSense) that regards social name-directory contents. Empirical data analysis and statistical results are presented with the implementation of estimations of parameters (e.g. utilization-level and serviceability) and advertisements in a social networking name-directory service (http://ktrip.net or http://한국.net). We found that estimated parameters were applicable to service monitoring of web-server as well as to synthesis of advertisement-effect in our social-web name-directory service.

• Journal of Information Processing Systems
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• v.4 no.2
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• pp.53-60
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• 2008

The Web Services infrastructure is a distributed computing environment for service-sharing. Mechanisms for Web services Discovery proposed so far have assumed a centralized and peer-to-peer (P2P) registry. A discovery service with centralized architecture, such as UDDI, restricts the scalability of this environment, induces performance bottleneck and may result in single points of failure. A discovery service with P2P architecture enables a scalable and an efficient ubiquities web service discovery service that needs to be run in self-organized fashions. In this paper, we propose an autonomic -interleaving Registry Overlay Network (RgON) that enables web-services' providers/consumers to publish/discover services' advertisements, WSDL documents. The RgON, doubtless empowers consumers to discover web services associated with these advertisements within constant D logical hops over constant K physical hops with reasonable storage and bandwidth utilization as shown through simulation.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.8
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• pp.3-12
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• 2016

Bluetooth Low Energy (BLE) protocol has attracted attention as a promising technology for low data throughput and low energy wireless sensor networks. Fast device discovery is very important in a BLE based wireless network. It is necessary to configure the network to work with minimized energy consumption because the BLE network nodes are expected to operate a long time typically on a coin cell battery. However, since it is difficult to obtain low energy and low latency at the same time, the BLE standard introduces wide range setting of parameters related to device discovery process and let the network operators to set up parameter values for the application. Therefore, it is necessary to analyze the performance of device discovery according to the related parameter values prior to BLE network operation. In this paper we analyze the expected value and the cumulative distribution function of the number of advertisements for device discovery in the BLE network. In addition, we propose a scheme for controlling the interval between advertising events that can improve the performance of device discovery without increasing energy consumption.

• The Journal of the Convergence on Culture Technology
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• v.6 no.3
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• pp.83-90
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• 2020

Recently, a growing number of copyright infringement websites have illegally copied and posted works such as broadcasting, movies and music, and posted advertisements to make profits. The research is aimed at finding solutions by analyzing the current status of advertisements on copyright infringement websites. The results of this study are as follows. First of all, there are many advertisements harmful to teenagers, such as casinos, betting, games, adult products, and adult meeting, which is necessary to deal with. Secondly, there were many unethical advertisements on copyright infringement websites, but there were also many advertisements from famous companies. Advertisements from large companies and famous brands are also being executed continuously, which can create trust in illegal sites. Therefore, the government, advertisers, citizens, and academia should participate in a campaign to root out the use of illegal websites because it is impossible to eradicate them by crackdown alone. In this paper, we pointed out the practical problems of advertising execution, the main source of revenue for copyright infringement websites, and presented a comprehensive solution.

• Herbal Formula Science
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• v.23 no.1
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• pp.15-24
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• 2015

Objectives l: This study is to investigate the emergence of herbal medicine during Japanese colonial period by reviewing newspaper advertisements and brochures about patient medicine of Chosun Maiyak Corporation. Methods : 69 kinds of patent medications and 584 newspaper advertisements are throughly reviewed to investigate dosage form, drug effect, sales unit and method, price, and advertisement pattern. Results : Lyungsinwhan represented more than half of the total advertisements, followed by Yungmihwan, Sahyangsohabwon, Yeollyeonggobondan, and Chiljehyangbuhwan. Lyungsinwhan was advertised mostly in spring and summer whereas Yungmihwan and Yeollyeonggobondan were advertised in spring and fall. Dosage form included pill(丸), mixture(膏), powder(散), and liquid(水, 液), while pill and mixture prevailed over other forms. Drug effect included dermatological, pediatric, digestive, and gynecological effects in the increasing order of drug numbers. Sales unit and price were found to vary significantly. Sales method included nationwide network distribution of medicine through postcards and stores. Conclusion : Herbal medicine during the colonial period was distributed in various kinds of forms with different effects and advertisement patterns through diverse sales unit and price.

• Cartoon and Animation Studies
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• s.10
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• pp.149-157
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• 2006

With the expansion of the Internet population, the online market is achieving a rapid growth and the size of the Internet advertisement market is increasing at a high rate. Different from passive types of information transmission, online media allows active two way communication thanks to communication and network technologies, so they can ascertain the effects of advertisement and users' response immediately. Rich media refer to such new advertisement techniques on the Internet, and are expected to lead the future Internet advertisement market. Thus, the present study purposed to analyze the visual expression elements of rich media advertisements in order to understand and enhance the effects of rich media advertisements with higher interactivity than existing Internet advertisements, and to propose guidelines for applying unique designs for the promotion of businesses and organizations and the provision of effective information to users.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.599-614
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• 2021

This paper proposes a digital signage system based on an intelligent recommendation model. The proposed system consists of a server and an edge. The server manages the data, learns the advertisement recommendation model, and uses the trained advertisement recommendation model to determine the advertisements to be promoted in real time. The advertisement recommendation model provides predictions for various products and probabilities. The purchase index between the product and weather data was extracted and reflected using correlation analysis to improve the accuracy of predicting the probability of purchasing a product. First, the user information and product information are input to a deep neural network as a vector through an embedding process. With this information, the product candidate group generation model reduces the product candidates that can be purchased by a certain user. The advertisement recommendation model uses a wide and deep recommendation model to derive the recommendation list by predicting the probability of purchase for the selected products. Finally, the most suitable advertisements are selected using the predicted probability of purchase for all the users within the advertisement range. The proposed system does not communicate with the server. Therefore, it determines the advertisements using a model trained at the edge. It can also be applied to digital signage that requires immediate response from several users.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.197-206
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• 2021

This study examined the networked structure and message types of newspapers advertisements in which universities have put in Daegu and Gyeongbuk provinces in Korea. Data were collected from July to September in 2020. As a result, universities preferred newspapers located in Daegu and Pohang areas. Next, universities have emphasized their cooperations with industries, basic competency capacities, and specialization programs in the advertising messages. When analyzing the findings in terms of university level, key words related to mid- to long-term development plans often appeared in the four-year schools. On the other hand, two or three-year universities frequently used an appeal that emphasized tangible performances. The findings showed the way in which the direction of university newspaper advertisements have been set in line with the rapidly changing environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.5
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• pp.326-328
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• 2014

In this paper we propose an efficient algorithm for LSA(Link State Advertisements) flooding. Link state routing protocols have been widely adopted in wired networks. When link state change occurs, a LSA is flooded into the whole network. The overhead of LSA flooding may be a big problem in wireless networks because their link states can be changed frequently. We propose an efficient flooding method that optimizes the flooding processes in wireless networks.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.21-30
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• 2023

The study proposes a model that utilizes Python-based deep learning text classification techniques to detect the legality of illegal financial advertising posts on the internet. These posts aim to promote unlawful financial activities, including the trading of bank accounts, credit card fraud, cashing out through mobile payments, and the sale of personal credit information. Despite the efforts of financial regulatory authorities, the prevalence of illegal financial activities persists. By applying this proposed model, the intention is to aid in identifying and detecting illicit content in internet-based illegal financial advertisining, thus contributing to the ongoing efforts to combat such activities. The study utilizes convolutional neural networks(CNN) and recurrent neural networks(RNN, LSTM, GRU), which are commonly used text classification techniques. The raw data for the model is based on manually confirmed regulatory judgments. By adjusting the hyperparameters of the Korean natural language processing and deep learning models, the study has achieved an optimized model with the best performance. This research holds significant meaning as it presents a deep learning model for discerning internet illegal financial advertising, which has not been previously explored. Additionally, with an accuracy range of 91.3% to 93.4% in a deep learning model, there is a hopeful anticipation for the practical application of this model in the task of detecting illicit financial advertisements, ultimately contributing to the eradication of such unlawful financial advertisements.