• Title/Summary/Keyword: Feature-based Design

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An Efficient IPTV Distribution Network by Packet Transport System (Packet Transport System에 의한 효율적인 IPTV 분배망 구축 방안)

  • Jang, Jin-Hee;Park, Seung-Kwon;Roh, Jin-Young;Noh, Francis Tai
    • Journal of Broadcast Engineering
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    • v.12 no.2
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    • pp.80-92
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    • 2007
  • IPTV Services that is representative union service of broadcasting and telecommunication need guarantee of QoS, efficiency of multicasting, and hish bandwidth on the network. Because typical TDM based metro transport network was designed by transporting fixed voice traffic with stable and recovering method, it has a defect of bottleneck and a waste of bandwidth for acceptance of data traffic with burst feature and then all of data are treated equally at the transport network because it cannot classify between advanced high end service and best effort low end service. for completely resolving this kind of problem about increasing burst traffic and QoS issues, firstly we need to new design for transport network. This paper presents transformation method from TDM based metro transport network to packet based transport network and advantage and effectiveness of packet based transport network and also indicates technical factor and characters about method of packet transport system. As a result of research, the Packet Transport System, which is a transmission network for packet delivery, take in not only a specific character of legacy TDM but QoS, Multicast and high bandwidth, then, it is able to keep an effective bandwidth and a stabilized performance of packet transmissions. Additionally, if a fault be occurred on an optical link, the system is able to guarantee a differential QoS by an each service class using an algorithm to make certain of a traffic existence and contain a protective mechanism.

The Effects of Live Commerce and Show Host Features on Consumers' Likelihood of Impulse Buying: A Scenario-Based Experiment (라이브 커머스 및 쇼호스트 특성이 소비자의 충동구매가능성에 미치는 영향: 시나리오 기반 실험연구)

  • Nakyeong Kim;Sung-Byung Yang;Sang-Hyeak Yoon
    • Information Systems Review
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    • v.24 no.4
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    • pp.77-96
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    • 2022
  • Live commerce has recently received substantial attention due to the spread of the non-face-to-face consumption culture driven by the COVID-19 pandemic. Live commerce has a higher purchase conversion rate than other forms of commerce. Accordingly, the likelihood of impulse buying in a live commerce environment is expected to be high. However, there is a shortage of research on consumer impulse buying in the live commerce environment. This study designs a scenario-based experiment using the integrated model of consumption impulse formation and enactment. Through this method, this study validates the influence of the characteristics of live commerce (i.e., vicarious experience and real-time interaction) on consumers' likelihood of impulse buying and further examines the moderating role of a live commerce host feature (i.e., professionalism) in these relationships. The results of this study confirm that both vicarious experience and real-time interaction have a positive effect on consumers' likelihood of impulse buying and that professionalism strengthens the impact of vicarious experience on the likelihood of impulse buying. This study's scenario-based experimental design is meaningful because it analyzes the likelihood of impulse buying in the context of live commerce shopping. Additionally, it provides live commerce service and platform providers with practical insights into how to maximize profits and operate services more efficiently.

The relation between Movement working as a Grouping clue in Moving Picture and Semantic structure forming (동영상에서 그룹핑(grouping) 단서로 작용하는 움직임(Movement)과 의미구조 형성의 관계)

  • Lee, Soo-Jin
    • Archives of design research
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    • v.19 no.5 s.67
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    • pp.119-128
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    • 2006
  • The scale of visual expression has expanded from freeze frame to motion picture as media have developed. Moving pictures such as animation, movies, TV CM and GUI become formative elements whose movement is necessary compared to freeze frame as apparent movement phenomenon and unit structure such as short and scene appear. Therefore, of formative elements such as a shape, color, space, size and movement, movement is importantly distinguished in the moving image. The expression and form of image as a relationship between the signified and signifier explained by Saussure are accepted as a sign by mutual complement even though they limit the content. This makes it possible to infer that the formal feature of movement participates in the message content. To verify this, the result of moving picture visual perception experiment based on the gestalt grouping principle result shows that 70-80 percent of subjects think that 'movement' is the important grouping clue in perception. Movement affects the maintenance of the context of message content in the communication process when the meaning structure of moving picture is analyzed based on the structural feature. The identity can be maintained with if there is a movement with similar directive point even if the color and shape of people, things and background are changed. Second, the clarity of the content is elevated by a distinguished object as a figure by movement. Third, it acts as a knowledge representation which can predict similar movement process of next information processing. Forth, movement gives the content consistency even though more than two scenes have fast switch and complicated editing structure like cross-cutting. Movement becomes a clue which can make grouping information input by visual perception reaction. Also, it gives the order to the visual expression which can be used improperly by formation of structural frame of image message and has the effectiveness which elevates the clarity of signification. Moving picture has discourse with several mixed unit structures because it fundamentally contains time and the common and distinguished expression is needed by media-mix circumstances. Therefore, by the application of gestalt grouping principle to moving picture field, movement becomes the more distinguished than other formative elements and affects the formation of meaning structure. This study propose a viewpoint that develops structural formative beauty and new image expression in the media image field.

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Development of Neural Network Based Cycle Length Design Model Minimizing Delay for Traffic Responsive Control (실시간 신호제어를 위한 신경망 적용 지체최소화 주기길이 설계모형 개발)

  • Lee, Jung-Youn;Kim, Jin-Tae;Chang, Myung-Soon
    • Journal of Korean Society of Transportation
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    • v.22 no.3 s.74
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    • pp.145-157
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    • 2004
  • The cycle length design model of the Korean traffic responsive signal control systems is devised to vary a cycle length as a response to changes in traffic demand in real time by utilizing parameters specified by a system operator and such field information as degrees of saturation of through phases. Since no explicit guideline is provided to a system operator, the system tends to include ambiguity in terms of the system optimization. In addition, the cycle lengths produced by the existing model have yet been verified if they are comparable to the ones minimizing delay. This paper presents the studies conducted (1) to find shortcomings embedded in the existing model by comparing the cycle lengths produced by the model against the ones minimizing delay and (2) to propose a new direction to design a cycle length minimizing delay and excluding such operator oriented parameters. It was found from the study that the cycle lengths from the existing model fail to minimize delay and promote intersection operational conditions to be unsatisfied when traffic volume is low, due to the feature of the changed target operational volume-to-capacity ratio embedded in the model. The 64 different neural network based cycle length design models were developed based on simulation data surrogating field data. The CORSIM optimal cycle lengths minimizing delay were found through the COST software developed for the study. COST searches for the CORSIM optimal cycle length minimizing delay with a heuristic searching method, a hybrid genetic algorithm. Among 64 models, the best one producing cycle lengths close enough to the optimal was selected through statistical tests. It was found from the verification test that the best model designs a cycle length as similar pattern to the ones minimizing delay. The cycle lengths from the proposed model are comparable to the ones from TRANSYT-7F.

PVC Classification based on QRS Pattern using QS Interval and R Wave Amplitude (QRS 패턴에 의한 QS 간격과 R파의 진폭을 이용한 조기심실수축 분류)

  • Cho, Ik-Sung;Kwon, Hyeog-Soong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.4
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    • pp.825-832
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    • 2014
  • Previous works for detecting arrhythmia have mostly used nonlinear method such as artificial neural network, fuzzy theory, support vector machine to increase classification accuracy. Most methods require accurate detection of P-QRS-T point, higher computational cost and larger processing time. Even if some methods have the advantage in low complexity, but they generally suffer form low sensitivity. Also, it is difficult to detect PVC accurately because of the various QRS pattern by person's individual difference. Therefore it is necessary to design an efficient algorithm that classifies PVC based on QRS pattern in realtime and decreases computational cost by extracting minimal feature. In this paper, we propose PVC classification based on QRS pattern using QS interval and R wave amplitude. For this purpose, we detected R wave, RR interval, QRS pattern from noise-free ECG signal through the preprocessing method. Also, we classified PVC in realtime through QS interval and R wave amplitude. The performance of R wave detection, PVC classification is evaluated by using 9 record of MIT-BIH arrhythmia database that included over 30 PVC. The achieved scores indicate the average of 99.02% in R wave detection and the rate of 93.72% in PVC classification.

Design of Tour Guide System using Bluetooth 4.0 and WiFi Sensor Technology (블루투스4.0과 WiFi 센서 기술을 이용한 관광안내 시스템 설계)

  • Kim, Hee-Sook
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.10
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    • pp.6888-6894
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    • 2015
  • Bluetooth 4.0 is the most appropriate technology for Internet of Things, which can be used to enhance and expand the existing areas and areas with a variety of applications. In this paper, an example of the services of the Internet of Things, we developed a tour guide system using the Bluetooth 4.0 and WiFi sensor technology. iBeacon-based push service have been limited to iOS smart phone series, non-iOS family and lower version of iOS 6 smart phones can not receive push-based services. This paper proposed in iBeacon and WiFi sensor is more than tourists, while maintaining the existing system (non-iOS smartphone users) can provide the service to you. Service tourist information as well as that can provide the advertising associated with the service. With 10 kinds of smart phones used in Korea was the experiment on the MAC information collected. This experiment is to track the behaviour of tourists in history can provide customized services can be based. Tourist destinations as well as amusement parks, resorts, etc. If you want to apply this system in a crowded place for user behavior information-gathering feature views over the a prevention of a missing child features such as notifications, risk, prevention is possible for a variety of applications.

A Study of Relationship Derivation Technique using object extraction Technique (개체추출기법을 이용한 관계성 도출기법)

  • Kim, Jong-hee;Lee, Eun-seok;Kim, Jeong-su;Park, Jong-kook;Kim, Jong-bae
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2014.05a
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    • pp.309-311
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    • 2014
  • Despite increasing demands for big data application based on the analysis of scattered unstructured data, few relevant studies have been reported. Accordingly, the present study suggests a technique enabling a sentence-based semantic analysis by extracting objects from collected web information and automatically analyzing the relationships between such objects with collective intelligence and language processing technology. To be specific, collected information is stored in DBMS in a structured form, and then morpheme and feature information is analyzed. Obtained morphemes are classified into objects of interest, marginal objects and objects of non-interest. Then, with an inter-object attribute recognition technique, the relationships between objects are analyzed in terms of the degree, scope and nature of such relationships. As a result, the analysis of relevance between the information was based on certain keywords and used an inter-object relationship extraction technique that can determine positivity and negativity. Also, the present study suggested a method to design a system fit for real-time large-capacity processing and applicable to high value-added services.

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Predicting the Fetotoxicity of Drugs Using Machine Learning (기계학습 기반 약물의 태아 독성 예측 연구)

  • Myeonghyeon Jeong;Sunyong Yoo
    • Journal of Life Science
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    • v.33 no.6
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    • pp.490-497
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    • 2023
  • Pregnant women may need to take medications to treat preexisting diseases or diseases that develop during pregnancy. However, some drugs may be fetotoxic and lead to, for example, teratogenicity and growth retardation. Predicting the fetotoxicity of drugs is thus important for the health of the mother and fetus. The fetotoxicity of many drugs has not been established because various challenges hinder the ability of researchers to determine their fetotoxicity. The need exists for in silico-based fetotoxicity assessment models, as they can modernize the testing paradigm, improve predictability, and reduce the use of animals and the costs of fetotoxicity testing. In this study, we collected data on the fetotoxicity of drugs and constructed fetotoxicity prediction models based on various machine learning algorithms. We optimized the models for more precise predictions by tuning the hyperparameters. We then performed quantitative performance evaluations. The results indicated that the constructed machine learning-based models had high performance (AUROC >0.85, AUPR >0.9) in fetotoxicity prediction. We also analyzed the feature importance of our model's predictions, which could be leveraged to identify the specific features of drugs that are strongly associated with fetotoxicity. The proposed model can be used to prescreen drugs and drug candidates at a lower cost and in less time. It provides a predictive score for fetotoxicity risk, which may be beneficial in the design of studies on fetotoxicity in human pregnancy.

A Study on the Cause and Improvement of Crack in the Installing Structure of the Bulkhead of Aircraft (항공기 Bulkhead 체결구조의 균열 원인 및 개선에 관한 연구)

  • Choi, Hyoung Jun;Park, Sung Jae
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.6
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    • pp.448-454
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    • 2020
  • This study aims to determine the cause of structural defects occurring during aircraft operations and to verify the structural integrity of the improved features. The fracture plane was analyzed to verify the characteristics of the cracks and the fatigue failure leading to the final fracture was determined by the progress of the cracks by the repeated load. During aircraft operations, the comparative analysis of the load measurement data at the cracks with the aircraft design load determined that the measured load was not at the level of 30% of the design to be capable of being damaged. A gap analysis resulted in a significant stress of approximately 32 ksi at the crack site. Pre-Load testing also confirmed that the M.S. was reduced by more than 50% from +0.71 to +0.43, resulting in a sharp increase in aircraft load and the possibility of cracking when combined. Thus, structural reinforcement and the removal of the gap for aircraft cracking sites improved the defect. Based on the structural strength analysis of the improvement features, the bulkhead has a margin of about +0.88 and the fitting feature is about +0.48 versus allowable stress. In addition, the life analysis results revealed an improvement of approximately 84000 hours.

Categorization of Humor types in Animations (애니메이션에서의 유머 유형구분에 관한 연구 -드림웍스의 <슈렉(Shrek)>을 중심으로-)

  • Park, Yeong-Won;Im, Yu-Sang
    • Journal of Science of Art and Design
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    • v.11
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    • pp.51-78
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    • 2007
  • Entertainment Industry is a high value-added business and its market includes the whole world. With high-tech industry, it is said that entertainment industry strengthen country's competitiveness, and the Korean government is trying to find a way to develop the animation industry. Some domestic feature animations were made, but they failed to get sufficient audiences. Meanwhile, Shrek 2, made by PDI, has earned about 92,000,000,000$ through just theatrical revenue. The reason is that domestic animations are not exciting. Contents should have amusement in it. The humor is the most important thing to make fun. So this thesis suggest to analyse Humor Types in animations. It is based on several theories about Humor. The types of humor defined by the previous studies are summarized into (1) humor, (2) wit, (3) satire and (4) irony. I categorize the productive methods of visual humor into (1) visual pun, (2) visual parody and (3) visual paradox adopting Henri Bergson's theory of the production methods of humor. And I comment on humorous scenes of Shrek in points of design basic elements, such as (1) visual elements, (2) relational elements and (3) practical elements. And I classify humor responses into the incongruity theory, the superiority theory, and relief theory. Therefore this study suggest a reasoned method to categorize the humor types effectively for producing or analyzing various types of humor effects in animation fields.

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