• Title/Summary/Keyword: Dynamic Network Analysis

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Analysis of Feedback Control CPU Scheduling in Virtualized Environment to Resolve Network I/O Performance Interference (가상화 환경에서 네트워크 I/O 성능 간섭 해결을 위한 피드백 제어 CPU 스케줄링 기법 분석)

  • Ko, Hyunseok;Lee, Kyungwoon;Park, Hyunchan;Yoo, Chuck
    • KIISE Transactions on Computing Practices
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    • v.23 no.9
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    • pp.572-577
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    • 2017
  • Virtualization allows multiple virtual machines to share the resources of a physical machine in order to utilize idle resources. The purpose of virtualization is the efficient allocation of resources among virtual machines. However, the efficient allocation of resources is difficult because the workload characteristics of each virtual machine cannot be understood in the current virtualization environment. This causes performance interference among virtual machines, which leads to performance degradation of the virtual machine. Previous works have been carried out to develop a method of solving such performance interference. This paper introduces a representative method, a CPU scheduling method that guarantees I/O performance by using feedback control to solve performance interference. In addition, we compare and analyze a model-based feedback control method and a dynamic feedback control method.

A Novel Perceptual No-Reference Video-Quality Measurement With the Histogram Analysis of Luminance and Chrominance (휘도, 색차의 분포도 분석을 이용한 인지적 무기준법 영상 화질 평가방법)

  • Kim, Yo-Han;Sung, Duk-Gu;Han, Jung-Hyun;Shin, Ji-Tae
    • Journal of Broadcast Engineering
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    • v.14 no.2
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    • pp.127-133
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    • 2009
  • With advances in video technology, many researchers are interested in video quality assessment to prove better performance of proposed algorithms. Since human visual system is too complex to be formulated exactly, many researches about video quality assessment are in progressing. No-reference video-quality assessment is suitable for various video streaming services, because of no requested additional data and network capacity to perform quality assessment. In this paper, we propose a novel no-reference video-quality assessment method with the estimation of dynamic range distortion. To measure the performance, we obtain mean opinion score (MOS) data by subject video quality test with the ITU-T P.910 Absolute Category Rating (ACR) method. And, we compare it with proposed algorithm using 363 video sequences. Experimental results show that the proposed algorithm has a higher correlation with obtained MOS.

Development of Real Time Smart Structure Monitoring System for Bridge Safety Maintenance using Sensor Network (센서 네트워크 기반 실시간 교량 안전관리를 위한 지능형 구조 건전성 모니터링시스템 개발)

  • Jo, Byung-Wan;Kim, Heon;Lee, Yun-Sung;Kim, Do-Keun
    • The Journal of the Korea Contents Association
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    • v.16 no.2
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    • pp.221-230
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    • 2016
  • As structures' long term performances and users' safety have been highlighted, a new maintenance technique using IT has drawn attention around the globe. Therefore, throughout the paper, by analyzing bridge's static and dynamic data using wireless measuring sensor, a "real time smart bridge monitoring system" has developed. Smart bridge monitoring system is consists of three main parts a sensor that can measure major members' movement, a wireless system that informs the data from the sensor, and the database system that analysis the data. In order to test the performance of the system, five different were placed on the Olympic Bridge, Seoul. The power system of the sensors was replaced by self-sustain solar energy system. In order to validate data from the real time smart bridge monitoring system, the data was collected for a week from both wireless system and the wired system and the two data were compared to see the relevance.

ASEAN Sculpture Garden and Typology of Space: An Evaluative Study of The Park's Failure

  • Ibrahim, Yuhanis;Yoon, Jiyoung
    • Architectural research
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    • v.16 no.2
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    • pp.37-44
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    • 2014
  • Utilizing spaces for awareness could be superficially noble. However, the typology of spaces played an important role in addressing the awareness of translating the messages through tangible forms, which in this context are sculptures. Assuring the efficacy of the typology of the spaces that is compatible with the content is important to ensure its timelessness to the dynamic demographical change of viewers. Therefore, the study proposes an investigation of the efficacy of typology of public urban space; garden that accommodates memorial sculptures. The study intends to analyze the features and flaws of ASEAN Sculpture Garden, as a mediatory role of ASEAN in instilling awareness of unity between ASEAN members to the public. The objective of the study is to analyze the efficacy of the garden to accommodate the rich memorial sculptures. The body of the research is formed by theoretical and case study research. It is projected by three methods; archival research, semi structured interviews and site documentation; direct observations and site visit. The qualitative data then will be analysed using Actor Network theory, keyword coding and site findings. Findings showed that as the main objective of the garden is to exhibit the sculptures, it could be summed up that it has failed to meet the apparent intention based on the site analysis conducted by the researcher. The typology of the space should be able to communicate the project's aims continuously rather than serving the function temporarily. The variables, which are space and time factors are debatable, as the neighboring tourist spot, National Monument residing the wide square managed to attract public attention due to its great efficacy of typological space regardless the time factor. As a conclusion, the typology of space is a huge factor to ensure the park's success.

Social Relation of Cyber Sports Supporter's Community and Social Capital (사이버 스포츠서포터스 공동체의 사회적 관계와 사회적 자본)

  • Kim, Kyong-Sik
    • The Journal of the Korea Contents Association
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    • v.13 no.8
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    • pp.386-395
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    • 2013
  • This study examined social relation of cyber sports supporter's community and social capital as time passes. This study selected spectator sports supporters of cyber sports community based on number of number and history of cyber sports supporter. This community is a representative supporter's club of spectator sports. This study utilized 1,848 members accumulated during three month. To analyze data, Netminer 4.0 and social network analysis were used. The conclusion is following: First, social relation of cyber sports supporter's community showed up dynamic change. Second, social capital of cyber sports supporter's community shows Sports events and training schedules, player transfer, manager, record, game watching and TV watching, cheering, cheering uniform and tools, players, teams and clubs, game photos and video, etc. This is the poor-get-poorer and the rich-get-richer phenomenon.

Deep Learning-based Action Recognition using Skeleton Joints Mapping (스켈레톤 조인트 매핑을 이용한 딥 러닝 기반 행동 인식)

  • Tasnim, Nusrat;Baek, Joong-Hwan
    • Journal of Advanced Navigation Technology
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    • v.24 no.2
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    • pp.155-162
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    • 2020
  • Recently, with the development of computer vision and deep learning technology, research on human action recognition has been actively conducted for video analysis, video surveillance, interactive multimedia, and human machine interaction applications. Diverse techniques have been introduced for human action understanding and classification by many researchers using RGB image, depth image, skeleton and inertial data. However, skeleton-based action discrimination is still a challenging research topic for human machine-interaction. In this paper, we propose an end-to-end skeleton joints mapping of action for generating spatio-temporal image so-called dynamic image. Then, an efficient deep convolution neural network is devised to perform the classification among the action classes. We use publicly accessible UTD-MHAD skeleton dataset for evaluating the performance of the proposed method. As a result of the experiment, the proposed system shows better performance than the existing methods with high accuracy of 97.45%.

Estimation of the Traffic Flow in the Korea Coastal Waterway by Computer Simulation (우리나라 연안의 해상교통관제시스템 설치를 위한 기초연구 시뮬레이션에 의한 우리나라 연안의 해상교통량 추정)

  • 구자윤;박양기;이철영
    • Journal of the Korean Institute of Navigation
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    • v.12 no.1
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    • pp.85-112
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    • 1988
  • From the point of view of safety of life and property at sea and the protection of the marine environment, the Vessel Traffic Management System along the Korea coastal waterway is inevitably introduced. But the establishing priority per area must be evaluated under the restricted budget. In this case, the estimated traffic flow has a major effect on priority evaluation. In the former paper , an algorithm was proposed for estimating the trip distribution between each pair of zones such as harbours and straits. This paper aims to formulate a simulation model for estimating the dynamic traffic flow per area in the Korea coastal waterway. The model consists of the algorithm constrined by the statistical movement of ships and the observed data, the regression analysis and the traffic network evaluations. The processed results of traffic flow except fishing vessel are summarized as follows ; 1) In 2000, the traffic congestions per area are estimated, in proportion of ship's number (tonnage), as Busan area 22.3%(44.5%), Yeosu area 19.8%(11.2%), Wando-Jeju area18.1%(6.8%), Mokpo area 14.9%(9.9%), Gunsan area 9.1%(9.3%), Inchon area 8.1%(7.7%), Pohang area 5.5%(8.5%), and Donghae area 2.2%(2.1%). 2) For example in Busan area, the increment of traffic volume per annum is estimated 4, 102 ships (23 million tons) and the traffic flow in 2000 is evaluated 158, 793 ships (687 million tons). 3) consequently, the increment of traffic volume in Busan area is found the largest and followed by Yeosu, Wando-Jeju area. Also, the traffic flow per area in 2000 has the same order.

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System Visibility of Universal Middleware Pervasive Memorial Engine (시스템 가시성평가를 위한 유니버설미들웨어기반 Pervasive Memorial Engine 연구)

  • Lee, Hae-Jun;Hwang, Chi-Gon;Yoon, Chang-Pyo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.11
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    • pp.2115-2120
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    • 2017
  • Presently, It is required to change convergence the role of hardware system and software technology that promoted trust of In-Vehicle for integrated complex system visibility evaluation. There is possibility for the period system can invoke unpredictable confusing blank state. The blank state systems have ecosystem characteristics that are supplied, maintained and operated through the complex interactions of technology and culture. Using universal middleware can support the life-cycle model and increase the visibility of complex systems and prepare for confusing situations. In this study, based on universal middleware, data and service dynamic standardized modules were evaluated to support stable system visibility platform. The system visibility module consists of Intelligent Pervasive Cloud module, Memorial Service module and Life Cycler connection module. In addition, the analysis results are supported by various network application service standards through platform independent system and architecture.

PC-SAN: Pretraining-Based Contextual Self-Attention Model for Topic Essay Generation

  • Lin, Fuqiang;Ma, Xingkong;Chen, Yaofeng;Zhou, Jiajun;Liu, Bo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.8
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    • pp.3168-3186
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    • 2020
  • Automatic topic essay generation (TEG) is a controllable text generation task that aims to generate informative, diverse, and topic-consistent essays based on multiple topics. To make the generated essays of high quality, a reasonable method should consider both diversity and topic-consistency. Another essential issue is the intrinsic link of the topics, which contributes to making the essays closely surround the semantics of provided topics. However, it remains challenging for TEG to fill the semantic gap between source topic words and target output, and a more powerful model is needed to capture the semantics of given topics. To this end, we propose a pretraining-based contextual self-attention (PC-SAN) model that is built upon the seq2seq framework. For the encoder of our model, we employ a dynamic weight sum of layers from BERT to fully utilize the semantics of topics, which is of great help to fill the gap and improve the quality of the generated essays. In the decoding phase, we also transform the target-side contextual history information into the query layers to alleviate the lack of context in typical self-attention networks (SANs). Experimental results on large-scale paragraph-level Chinese corpora verify that our model is capable of generating diverse, topic-consistent text and essentially makes improvements as compare to strong baselines. Furthermore, extensive analysis validates the effectiveness of contextual embeddings from BERT and contextual history information in SANs.

An Action Unit co-occurrence constraint 3DCNN based Action Unit recognition approach

  • Jia, Xibin;Li, Weiting;Wang, Yuechen;Hong, SungChan;Su, Xing
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.3
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    • pp.924-942
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    • 2020
  • The facial expression is diverse and various among persons due to the impact of the psychology factor. Whilst the facial action is comparatively steady because of the fixedness of the anatomic structure. Therefore, to improve performance of the action unit recognition will facilitate the facial expression recognition and provide profound basis for the mental state analysis, etc. However, it still a challenge job and recognition accuracy rate is limited, because the muscle movements around the face are tiny and the facial actions are not obvious accordingly. Taking account of the moving of muscles impact each other when person express their emotion, we propose to make full use of co-occurrence relationship among action units (AUs) in this paper. Considering the dynamic characteristic of AUs as well, we adopt the 3D Convolutional Neural Network(3DCNN) as base framework and proposed to recognize multiple action units around brows, nose and mouth specially contributing in the emotion expression with putting their co-occurrence relationships as constrain. The experiments have been conducted on a typical public dataset CASME and its variant CASME2 dataset. The experiment results show that our proposed AU co-occurrence constraint 3DCNN based AU recognition approach outperforms current approaches and demonstrate the effectiveness of taking use of AUs relationship in AU recognition.