• 제목/요약/키워드: media selection

검색결과 654건 처리시간 0.025초

Simple Relay Selection for Wireless Network Coding System

  • 김장섭;이정우
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 2011년도 하계학술대회
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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.

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실감형 360도 미디어의 RGB 벡터 및 객체 특징정보를 이용한 대표 프레임 선정 방법 (A Reference Frame Selection Method Using RGB Vector and Object Feature Information of Immersive 360° Media)

  • 박병찬;유인재;이재청;장세영;김석윤;김영모
    • 전기전자학회논문지
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    • 제24권4호
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    • pp.1050-1057
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    • 2020
  • 실감형 360도 미디어는 기존 영상보다 고품질, 초대용량으로 영상의 크기가 크며, 다양한 렌더링 방식을 사용하여 기존방식으로 이미지 처리할 경우 영상인식 속도가 느려지는 문제가 있다. 또한, 실감형 360도 미디어의 특성상 특정 장소에서 카메라를 고정시켜 한 장면만 촬영하는 경우가 대부분이기 때문에, 모든 영상에서 특징정보를 추출할 필요가 없다. 본 논문에서는 실감형 360 미디어의 프레임 추출과정, 프레임 다운사이징, 구형 형태의 렌더링 과정을 거치고, 렌더링 과정에서 영상을 16개 프레임으로 분할 캡처하여 캡처된 프레임에서 객체 정보가 많은 중앙 부분에서 픽셀당 RGB 벡터와 딥 러닝을 이용하여 객체를 추출한 뒤, 객체 특징정보를 이용하여 대표 프레임을 선정하는 방법을 제안한다.

A CDN-P2P Hybrid Architecture with Location/Content Awareness for Live Streaming Services

  • Nguyen, Kim-Thinh;Kim, Young-Han
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제5권11호
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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.

Effective Hand Gesture Recognition by Key Frame Selection and 3D Neural Network

  • Hoang, Nguyen Ngoc;Lee, Guee-Sang;Kim, Soo-Hyung;Yang, Hyung-Jeong
    • 스마트미디어저널
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    • 제9권1호
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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.

Efficient Phosphinothricin Mediated Selection of Callus Derived from Brachypodium Mature Seed

  • Jeon, Woong Bae;Lee, Man Bo;Kim, Dae Yeon;Hong, Min Jeong;Lee, Yong Jin;Seo, Yong Weon
    • 한국육종학회지
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    • 제42권4호
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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.

Factors Influencing New Media Exposure of Political News by Youths in Isan Society

  • Jitsaeng, Khanittha;Chaikhambung, Juthatip
    • Journal of Information Science Theory and Practice
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    • 제10권2호
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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.

60대~70대 여성 소비자의 인지된 연령에 따른 의복선택기준 및 패션 정보원 활용 (Clothing Selection Criteria and the Use of Fashion Information Sources Based on the Perceived Age of Elderly Female Consumers in their 60s~70s)

  • 홍경희;이윤정
    • 한국의류학회지
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    • 제34권2호
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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.

음성신호기반의 감정분석을 위한 특징벡터 선택 (Discriminative Feature Vector Selection for Emotion Classification Based on Speech)

  • 최하나;변성우;이석필
    • 전기학회논문지
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    • 제64권9호
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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.

광선 추적법 텍스쳐 매핑을 위한 MIP-Map 수준 선택 알고리즘 연구 (An Algorithm of MIP-Map Level Selection for Ray-Traced Texture Mapping)

  • 박우찬;김동석
    • 한국게임학회 논문지
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    • 제10권4호
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    • pp.73-80
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    • 2010
  • 본 논문은 광선 추적법 텍스쳐 매핑에서 MIP-Map 알고리즘 사용 시 텍스쳐 이미지들의 MIP-Map 수준을 선택하는 효과적인 방식을 제안한다. 이는 렌더링 시 물체와 교차하는 광선의 길이만을 사용하여 해당 물체의 텍스쳐 MIP-Map 수준을 선택하는 방법이다. 본 방식은 MIP-Map을 지원하지 않는 방식에 비하여 텍스쳐 알리아싱 면에서 우수하고 성능 저하는 미비하다.

의복의 정숙성.심미성에 영향을 미치는 관련변인 연구 (1) -자아실현을 중심으로- (A Study on the Effect of Self-Actualization Variables on the Modesty and Aethetics in the Selection of Clothing)

  • 강경자
    • 대한가정학회지
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    • 제30권4호
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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.

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