• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.310-313
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• 2011

Broadcasting nature of wireless communications makes it possible to apply opportunistic network coding (OPNC) by overhearing transmitted packets from a source to sink nodes. However, it is difficult to apply network coding to the topology of multiple relay and sink nodes. We propose to use relay node selection, which finds a proper node for network coding since the OPNC alone in the topology of multiple relays and sink nodes cannot guarantee network coding gain. The proposed system is a novel combination of wireless network coding and relay selection, which is a key contribution of this paper. In this paper, with the consideration of channel state and potential network coding gain, we propose relay node selection techniques, and show performance gain over the conventional OPNC and a channel-based selection algorithm in terms of average system throughput.

• Journal of IKEEE
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• v.24 no.4
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• pp.1050-1057
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• 2020

Immersive 360-degree media has a problem of slowing down the video recognition speed when the video is processed by the conventional method using a variety of rendering methods, and the video size becomes larger with higher quality and extra-large volume than the existing video. In addition, in most cases, only one scene is captured by fixing the camera in a specific place due to the characteristics of the immersive 360-degree media, it is not necessary to extract feature information from all scenes. In this paper, we propose a reference frame selection method for immersive 360-degree media and describe its application process to copyright protection technology. In the proposed method, three pre-processing processes such as frame extraction of immersive 360 media, frame downsizing, and spherical form rendering are performed. In the rendering process, the video is divided into 16 frames and captured. In the central part where there is much object information, an object is extracted using an RGB vector per pixel and deep learning, and a reference frame is selected using object feature information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.11
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• pp.2143-2159
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• 2011

The hybrid architecture of content delivery networks (CDN) and peer-to-peer overlay networks (P2P) is a promising technology enables effective real-time streaming services. It complements the advantages of quality control and reliability in a CDN, and the scalability of a P2P system. With real-time streaming services, however, high connection setup and media delivery latency are becoming the critical issues in deploying the CDN-P2P system. These issues result from biased peer selection without location awareness or content awareness, and can lead to significant service disruption. To reduce service disruption latency, we propose a group-based CDN-P2P hybrid architecture (iCDN-P2P) with a location/content-aware selection of peers. Specifically, a SuperPeer network makes a location-aware peer selection by employing a content addressable network (CAN) to distribute channel information. It also manages peers with content awareness, forming a group of peers with the same channel as the sub-overlay. Through a performance evaluation, we show that the proposed architecture outperforms the original CDN-P2P hybrid architecture in terms of connection setup delay and media delivery time.

• Smart Media Journal
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• v.9 no.1
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• pp.23-29
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• 2020

This paper presents an approach for dynamic hand gesture recognition by using algorithm based on 3D Convolutional Neural Network (3D_CNN), which is later extended to 3D Residual Networks (3D_ResNet), and the neural network based key frame selection. Typically, 3D deep neural network is used to classify gestures from the input of image frames, randomly sampled from a video data. In this work, to improve the classification performance, we employ key frames which represent the overall video, as the input of the classification network. The key frames are extracted by SegNet instead of conventional clustering algorithms for video summarization (VSUMM) which require heavy computation. By using a deep neural network, key frame selection can be performed in a real-time system. Experiments are conducted using 3D convolutional kernels such as 3D_CNN, Inflated 3D_CNN (I3D) and 3D_ResNet for gesture classification. Our algorithm achieved up to 97.8% of classification accuracy on the Cambridge gesture dataset. The experimental results show that the proposed approach is efficient and outperforms existing methods.

• Korean Journal of Breeding Science
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• v.42 no.4
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• pp.351-356
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• 2010

Brachypodium distachyon is rapidly emerged in biological study and has been currently used as a model system for genetics and functional studies for crop improvement and biofuel production. Phosphinothricin (PPT) has been widely used as a selectable agent, which raises ammonium content and induces toxicity in non-transformed plant cells. However PPT selection is not much effective on Brachypodium callus consequently reducing transformation efficiency. In order to identify the efficient conditions of PPT selection, calli obtained from mature seeds of Brachypodium (PI 254867) were cultured on the callus inducing medium (CIM) or regeneration medium (ReM) containing serial dilutions of the PPT (0, 2, 5, 10, and 15 mg/l) in dark or light condition. Callus growth and ammonium content of each treatment were measured 2 weeks after the treatment. Although callus growth and ammonium content did not show much difference in CIM, slow callus growth and increased ammonium accumulation were found in ReM. No significant difference of ammonium accumulation in response to PPT was found between dark and light conditions. In order to identify major factors affecting increased ammonium accumulation, callus was cultured on the media in combined with phytohormones (2,4-D or kinetin) and carbon sources (sucrose or maltose) containing with PPT (5 mg/l). The highest ammonium content in callus was found in the kinetin and maltose media.

• Journal of Information Science Theory and Practice
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• v.10 no.2
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• pp.86-101
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• 2022

This research aimed at studying the factors that influence new media exposure of political news by youths in Isan society in Thailand. The target group comprised 1,200 individuals, obtained from multi-stage sampling from undergraduate students in Isan's autonomous universities, governmental universities, and private institutions. The data collection tool was a questionnaire, the content of which was validated by experts. The reliability of the tool was tested by the formula for Cronbach's alpha coefficient, which yielded a reliability of 0.83. Multiple regression analysis was applied to analyze the data. The results, regarding factors influencing the channels for political news exposure, showed that channels for political news exposure were mostly influenced by inner drives, followed by importance in political news exposure, influence from social networks, and specific characteristics of the Internet. This could explain the variation of channels for political news exposure at 46.5%. In terms of factors influencing political news selection, it was found that political news selection was influenced mostly from social networks, followed by inner drives, benefits from political news exposure, specific characteristics of the Internet, and the field of study. The variation of the political news selection could be explained at 44.6%. These results elaborate on the current situation in Thailand, especially in Isan region, where youths in higher education are playing an increasing role in demonstrating their political stance through various political activities.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.9
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• pp.1363-1368
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• 2015

Recently, computer form were smaller than before because of computing technique's development and many wearable device are formed. So, computer's cognition of human emotion has importantly considered, thus researches on analyzing the state of emotion are increasing. Human voice includes many information of human emotion. This paper proposes a discriminative feature vector selection for emotion classification based on speech. For this, we extract some feature vectors like Pitch, MFCC, LPC, LPCC from voice signals are divided into four emotion parts on happy, normal, sad, angry and compare a separability of the extracted feature vectors using Bhattacharyya distance. So more effective feature vectors are recommended for emotion classification.

• Journal of Korea Game Society
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• v.10 no.4
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• pp.73-80
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• 2010

This paper proposes an effective method to select MIP-Map level of texture images for ray-traced texture mapping. This MIP-Map level selection method requires only the total length of intersected ray. By supporting MIP-Map for texture mapping, we can reduce the texture aliasing effects, while our approach decreases rendering performance very slightly.

• Journal of the Korean Home Economics Association
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• v.30 no.4
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• pp.27-38
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• 1992

The purpose of this study was to evaluate the effect of self-actualization and demographic variables of adult women on the modesty and aethetics in the selection of clothes. The qestionnaire were completed by 647 women in taegu and jinju. The major findings of this research can be summairzed as follows : 1. Marital status has effect on the self-actualizing values. religion, occupation and income have effect on self-acceptance. Marital staus and religion have effect on nature of man. 2. Frequency of contact with mass media has effect on the modesty of clothing. Self-actualization and demographic variables have no direct effect on the modesty of clothing. 3. Self-actualizing values, self-acceptance, nature of man, income, frequency of contact with mass media have direct effect on the aethetics of clothing.

• Journal of the Korean Society of Clothing and Textiles
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• v.34 no.2
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• pp.200-211
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• 2010

This study examines the clothing purchasing behavior of elderly female consumers based on their perceived age. This study grouped elderly female consumers by their perceived age and examined what influence the clothing selection criteria or fashion information sources have on individual clothing purchase behavior. From January $10^{th}$ to February $25^{th}$ 2008, data research was conducted on 194 elderly women in their 60s and 70s from Seoul. The SPSS 14.0 software program was used to conduct data analyses such as descriptive statistics, frequency analysis, factor analysis, reliability analysis, ANOVA, and the Duncan test as a post-hoc analysis. The results of this study are as follows: First, the elderly female consumers were divided into three groups, younger, average, and older according to their perceived age. Second, the factors derived from the factor analysis of their clothing selection criteria included personal relevance, practicability, conformity, and economic efficiency. In addition, three factors of advertising/media-provided, consumer-provided and store-provided information were extracted from the factor analysis of fashion information sources. Third, there were significant differences in personal relevance and conformity that depended on the perceived age of elderly female consumers for clothing selection criteria. Fourth, in the use of fashion information sources, significant differences were found in all aspects of advertising/media-provided, consumer-provided, and store-provided information sources that depended on their perceived age.