• Geophysics and Geophysical Exploration
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• v.6 no.3
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• pp.143-152
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• 2003

Among the various geophysical approaches to identify the leakage of leachate with conductivity variation, conventional electrical resistivity survey has been mainly used at waste landfill. We adopted small-loop electromagnetic (EM) survey using multi-frequencies in parallel with electrical resistivity survey to delineate the leakage of leachate through the shallow soil layer at a waste landfill in Jeju Island, and also with self-potential monitoring to detect the streaming potential produced by the movement of leachate. There were no evidences of leakage from waste landfill according to the results of the electrical resistivity survey and SP monitoring, and it was also true from the results of water quality analysis at stream around waste landfill periodically. On the other hand, the results of one-dimensional inversion of spatially-filtered small-loop EM survey data showed the anomalous zone of low resistivity with depth both around and inner waste landfill.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.6
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• pp.460-471
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• 2004

Since the RTP is suitable for real-time data transmission in multimedia services like VoD, AoD, and VoIP, it has been adopted as a real-time transport protocol by RTSP, H.323, and SIP. Even though the RTP protocol stack for embedded systems has been in great need for efficient support of multimedia services, such a stack has not been developed yet. In this paper, we explain embeddedRTP which supports the RTP protocol stack at the kernel level so that it is suitable for embedded systems. Since embeddedRTP is designed to reside in the UBP module, existing applications which rely ell TCP/IP services can proceed the same as before, while applications which rely on the RTP protocol stack can request HTP services through embeddedRTp API. EmbeddedRTP stores transmitted RTP packets into per session packet buffer, using the packet's port number and multimedia session information. Communications between applications and embeddedRTP is performed through system calls and signal mechanisms. Additionally, embeddedRTP API makes it possible to develop applications more conveniently. Our performance test shows that packet-processing speed of embeddedRTP is about 7.5 times faster than that oi VCL RTP for multimedia streaming services on PDA in spite that its object code size is reduced about by 58% with respect to UCL RTP's.

• Journal of the Korea Society of Computer and Information
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• v.27 no.1
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• pp.149-156
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• 2022

This research focuses on women in their 20s and 30s who have experience in consuming beauty products in the live broadcast of beauty products in China to find out the effects of consumers' consumption propensity on beauty product selection attributes. The data analysis is performed from April 29 to May 25, 2021 by using SPSSWIN 21.0 program for frequency analysis, factor analysis, reliability appraisal, technical statistical analysis, correlation analysis and multiple regression analysis. And the results of the study are as follows: According to the survey, the general characteristics are 20~25 years old, university, and the consumer price is between 500,000 and 1 million won. In terms of consumption propensity that the intrinsic pursuit of consumption, the impulsive consumption, the external pursuit of consumption were on a high average score which was 3.76, 3.63, 3.56 respectively, and in terms of the selection attributes of beauty products that the product intrinsic attributes, and the external attributes of products were on a high average score which was 3.91, 3.69 respectively. The external/internal attributes of beauty product selection attributes are all related to consumption propensity. According to the survey, the external pursuit of consumption, internal pursuit of consumption, and impulsive consumption of the propensity to consume all have a meaningful influence on the external/internal attributes of products. This result proves that the consumption tendency of beauty live broadcast consumers has a huge impact on the selection attributes of beauty products. In this regard, according to the consumption tendencies of Chinese women, the necessity of differentiated live-streaming marketing strategies for beauty products based on the characteristics of beauty product brands, categories, and designs has been proposed.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.1
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• pp.42-50
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• 2023

The development of technology has achieved digital innovation throughout the media industry, including production techniques and editing technologies, and has brought diversity in the form of consumer viewing through the OTT service and streaming era. The convergence of big data and deep learning networks automatically generated text in format such as news articles, novels, and scripts, but there were insufficient studies that reflected the author's intention and generated story with contextually smooth. In this paper, we describe the flow of pictures in the storyboard with image caption generation techniques, and the automatic generation of story-tailored scenarios through language models. Image caption using CNN and Attention Mechanism, we generate sentences describing pictures on the storyboard, and input the generated sentences into the artificial intelligence natural language processing model KoGPT-2 in order to automatically generate scenarios that meet the planning intention. Through this paper, the author's intention and story customized scenarios are created in large quantities to alleviate the pain of content creation, and artificial intelligence participates in the overall process of digital content production to activate media intelligence.

• Information Systems Review
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• v.22 no.2
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• pp.25-41
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• 2020

Along with the expectation about 5G network commercialization, interests in realistic and immersive media industries such as virtual reality (VR) are increasing. However, most of studies on VR still focus on video technologies instead of factors for popularity and consumption. Thus, the main objective of this research is to identify meaningful factors, which affect the view counts of VR videos and to provide business implications of the content strategies for VR video creators and service providers. Using a regression analysis with 700 VR videos, this study tries to find major factors that affect the view counts of VR videos. As a result, user assessment factors such as number of likes and sicknesses have a strong influence on the view counts. In addition, the result shows that both general information factors (video length and age) and content characteristic factors (series, one source multi use (OSMU), and category) are all influential factors. The findings suggest that it is necessary to support recommendation and curation based on user assessments for increasing popularity and diffusion of VR video streaming.

• Information Systems Review
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• v.22 no.3
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• pp.143-156
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• 2020

Price promotion is one of the most frequently marketing strategies with a long history. According to various studies, the effect of price promotion is controversial. Some studies have argued that price promotion has a positive effect, while others have found that it has no effect or rather has a negative effect. This study aims to examine the effect of price promotion in a subscription-based service. First, we check the effect of price promotion on the repurchase of the consumer. And we investigate how this effect varies depending on the characteristics of the consumer. Using the data from one of the music streaming service in South Korea, the effect of consumers' price promotion experience, demographic characteristics, and behavioral characteristics on their repurchase is analyzed through logistic regression analysis. As a result of the study, it is found that consumers' experience of price promotion has a positive effect on repurchase. In addition, the positive effect of price promotion is relatively greater in younger and female consumers. This study has implications in that it not only confirmed the positive effect of price promotion in a subscription-based environment but also empirically confirmed that the characteristics of consumers should be considered when performing price promotion.

• Information Systems Review
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• v.18 no.4
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• pp.89-106
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• 2016

The latest movement in live video streaming service is mobile personal broadcasting (MPB), which refers to consumers accessing the service through social media with mobile devices, such as smartphones and tablet PCs. This service is possible through the advancements in mobile video technology and platforms. Features such as enhanced user interaction, personalization, and real-time broadcasting, combined with a greater variety of content, have led to the development of MPB. The increase in MPB users calls for research, including that on the hedonic motivational angle. This study aims to assess MPB users' intrinsic motives through the hedonic-motivation system adoption model (HMSAM) using seven factors: joy, temporal dissociation, escapism, focused immersion, perceived ease of use, perceived usefulness and intention to watch. Survey data collected from 154 samples were analyzed with statistical techniques, such as structural equation modeling. Results showed that time dissociation, escapism, and perceived ease of use have a positive relationship with heightened enjoyment. Joy significantly affects focused immersion and intention to watch. Escapism also had a statistically significant influence on focused immersion. This study contributes to the advancement of the MPB study under the HMSAM theoretical framework and offers practical suggestions to managers to enhance MPB content viewership.

• 한국지구물리탐사학회:학술대회논문집
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• 2002.09a
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• pp.139-162
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• 2002

Since weak zones or geological lineaments are likely to be eroded, weak zones may develop beneath rivers, and a careful evaluation of ground condition is important to construct structures passing through a river. Dc resistivity surveys, however, have seldomly applied to the investigation of water-covered area, possibly because of difficulties in data aquisition and interpretation. The data aquisition having high quality may be the most important factor, and is more difficult than that in land survey, due to the water layer overlying the underground structure to be imaged. Through the numerical modeling and the analysis of case histories, we studied the method of resistivity survey at the water-covered area, starting from the characteristics of measured data, via data acquisition method, to the interpretation method. We unfolded our discussion according to the installed locations of electrodes, ie., floating them on the water surface, and installing at the water bottom, since the methods of data acquisition and interpretation vary depending on the electrode location. Through this study, we could confirm that the dc resistivity method can provide the fairly reasonable subsurface images. It was also shown that installing electrodes at the water bottom can give the subsurface image with much higher resolution than floating them on the water surface. Since the data acquired at the water-covered area have much lower sensitivity to the underground structure than those at the land, and can be contaminated by the higher noise, such as streaming potential, it would be very important to select the acquisition method and electrode array being able to provide the higher signal-to-noise ratio data as well as the high resolving power. The method installing electrodes at the water bottom is suitable to the detailed survey because of much higher resolving power, whereas the method floating them, especially streamer dc resistivity survey, is to the reconnaissance survey owing of very high speed of field work.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.145-165
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• 2023

Recommendation system plays a significant role on relieving difficulties of selecting information among rapidly increasing amount of information caused by the development of the Internet and on efficiently displaying information that fits individual personal interest. In particular, without the help of recommendation system, E-commerce and OTT companies cannot overcome the long-tail phenomenon, a phenomenon in which only popular products are consumed, as the number of products and contents are rapidly increasing. Therefore, the research on recommendation systems is being actively conducted to overcome the phenomenon and to provide information or contents that are aligned with users' individual interests, in order to induce customers to consume various products or contents. Usually, collaborative filtering which utilizes users' historical behavioral data shows better performance than contents-based filtering which utilizes users' preferred contents. However, collaborative filtering can suffer from cold-start problem which occurs when there is lack of users' historical behavioral data. In this paper, hybrid music recommendation system, which can solve cold-start problem, is proposed based on the playlist data of Melon music streaming service that is given by Kakao Arena for music playlist continuation competition. The goal of this research is to use music tracks, that are included in the playlists, and metadata of music tracks and playlists in order to predict other music tracks when the half or whole of the tracks are masked. Therefore, two different recommendation procedures were conducted depending on the two different situations. When music tracks are included in the playlist, LightFM is used in order to utilize the music track list of the playlists and metadata of each music tracks. Then, the result of Item2Vec model, which uses vector embeddings of music tracks, tags and titles for recommendation, is combined with the result of LightFM model to create final recommendation list. When there are no music tracks available in the playlists but only playlists' tags and titles are available, recommendation was made by finding similar playlists based on playlists vectors which was made by the aggregation of FastText pre-trained embedding vectors of tags and titles of each playlists. As a result, not only cold-start problem can be resolved, but also achieved better performance than ALS, BPR and Item2Vec by using the metadata of both music tracks and playlists. In addition, it was found that the LightFM model, which uses only artist information as an item feature, shows the best performance compared to other LightFM models which use other item features of music tracks.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.21-35
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• 2018

Since the introduction of MP3 players, CD recordings have gradually been vanishing, and the music consuming environment of music users is shifting to mobile devices. The introduction of smart devices has increased the utilization of music through music playback, mass storage, and search functions that are integrated into smartphones and tablets. At the time of initial MP3 player supply, the bitrate of the compressed music contents generally was 128 Kbps. However, as increasing of the demand for high quality music, sound quality of 384 Kbps appeared. Recently, music content of FLAC (Free License Audio Codec) format using lossless compression method is becoming popular. The download service of many music sites in Korea has classified by unlimited download with technical protection and limited download without technical protection. Digital Rights Management (DRM) technology is used as a technical protection measure for unlimited download, but it can only be used with authenticated devices that have DRM installed. Even if music purchased by the user, it cannot be used by other devices. On the contrary, in the case of music that is limited in quantity but not technically protected, there is no way to enforce anyone who distributes it, and in the case of high quality music such as FLAC, the loss is greater. In this paper, the author proposes an audio watermarking technology for copyright protection of high quality stereo music. Two kinds of information, "Copyright" and "Copy_free", are generated by using the turbo code. The two watermarks are composed of 9 bytes (72 bits). If turbo code is applied for error correction, the amount of information to be inserted as 222 bits increases. The 222-bit watermark was expanded to 1024 bits to be robust against additional errors and finally used as a watermark to insert into stereo music. Turbo code is a way to recover raw data if the damaged amount is less than 15% even if part of the code is damaged due to attack of watermarked content. It can be extended to 1024 bits or it can find 222 bits from some damaged contents by increasing the probability, the watermark itself has made it more resistant to attack. The proposed algorithm uses quantization in DCT so that watermark can be detected efficiently and SNR can be improved when stereo music is converted into mono. As a result, on average SNR exceeded 40dB, resulting in sound quality improvements of over 10dB over traditional quantization methods. This is a very significant result because it means relatively 10 times improvement in sound quality. In addition, the sample length required for extracting the watermark can be extracted sufficiently if the length is shorter than 1 second, and the watermark can be completely extracted from music samples of less than one second in all of the MP3 compression having a bit rate of 128 Kbps. The conventional quantization method can extract the watermark with a length of only 1/10 compared to the case where the sampling of the 10-second length largely fails to extract the watermark. In this study, since the length of the watermark embedded into music is 72 bits, it provides sufficient capacity to embed necessary information for music. It is enough bits to identify the music distributed all over the world. 272 can identify $4*10^{21}$, so it can be used as an identifier and it can be used for copyright protection of high quality music service. The proposed algorithm can be used not only for high quality audio but also for development of watermarking algorithm in multimedia such as UHD (Ultra High Definition) TV and high-resolution image. In addition, with the development of digital devices, users are demanding high quality music in the music industry, and artificial intelligence assistant is coming along with high quality music and streaming service. The results of this study can be used to protect the rights of copyright holders in these industries.