• Title/Summary/Keyword: traffic characteristic data

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Mailing List Characteristic from Electronic Mail

  • Khaitiyakun, N.;Khunkitti, A.
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.917-921
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    • 2004
  • Principle of mailing list was distributed messages to all subscribers in one time. But mailing list operation has constructed a network traffic problem. Because mailing list manager distributed mails without concentrate on subscriber network. If our network has many of subscribers, there will be redundant data in traffic channel. Submailing list has purpose to reduce problems. Analyses of mailing list characteristic in electronic mail were a feature of submailing list system, which manage by human hand (Network Administrator). That will cause trouble for network traffic if Network Administrator could not seek for mailing list characteristic from e-mails in due time. This article will present ideas and recognize methodology for automatic working in submailing list system. Recognize step begin with capture process, which use to trap e-mail information from transfer channel. Next process is preparing raw data into recognition format. Then the third one is recognize part and find out confidential factor. The last process is make decision and determine which electronic mail has properties of mailing list characteristic. Afterward deliver result to submailing list for carry on.

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A Study for Parking Characteristic of Parking Operation Method (주차장 운영방식에 따른 주차특성 분석)

  • Jung, Ki-Soo;Lee, Young-Woo
    • Journal of the Korean Society of Industry Convergence
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    • v.13 no.1
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    • pp.5-13
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    • 2010
  • Industrialization and urbanization occurred-traffic delay, traffic accident and parking problem etc.-variety of transportation problems. Parking problem is one of the transportation problem then transportation engineers would get involved in trying to solve parking problem. A way to overcome a variety of parking problems needs preliminary data for conditions of parking but it lacks the preliminary data to do so. Thus this study analyzed a characteristic of a parking through a field survey for parking in Daegu Metropolitan City. This study analyzed parking characteristic of parking operation method. This study result reveals difference between a toll parking and a no charge parking characteristic. Thus a close examination for a toll parking characteristic and a no charge parking characteristic is a prerequisite for a rational parking policy.

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On the efficient transmission of video stream using characteristic information (특성 정보를 이용한 비디오 스트림의 효율적 전송)

  • 강수용;염헌영
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.21 no.9
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    • pp.2328-2340
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    • 1996
  • Until now, the transmission of data for VOD(Video on Demenad) was based on a real time modelling of video data. Markow Modulated Fluid Sources(MMFS) and Markow Modulated Poisson Sources(MMPS) are the most widely used modelling methods. But the charactersitics of the VBR(Variable Bit Rate) signal prevents modelling from actually being "real-time". Also these methods call for the use of large buffers for the abolishment of cell loss. These modelling methods are, of course, useful i case of teleconferences where a real time modelling of video traffic is inevitable, but they are insufficient in cases where the characteristic infomation of video traffic can be obtained beforehand-cases such as VOD. Video data is speial in that if one file is preprocessed all other products can simply be copied from that onepreprocessed file. This characteristic helps reduce the overhead arising from the job of drawing out characteristic information to almost zero. But still, compared to the existing real time modelling method data transmission using characteristic information succeeds in raising the efficiency of data transmission. In tis paper we will outline a method of dta transmission which use the characteristic information of each video stream, and evaluate this method through some experiments.periments.

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STUDY ON DESIGN AND APPLICATION FOR TRAFFIC THEMATIC MAP LEVEL 1 DATA

  • Kim, Soo-Ho;Ahn, Ki-Seok;Kim, Moon-Gie
    • Proceedings of the KSRS Conference
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    • 2008.10a
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    • pp.262-265
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    • 2008
  • We design level 1 traffic thematic map for common data structure. Level 1 means the road that can passing cars. If public office and private company use this form, they can save amount of money from overlapping update. And widely use of traffic analysis, navigation and traffic information system. For design common data structure we compared several data structure(traffic thematic map, ITS standard node/link, Car navigation map), and generalization these characteristic data. After generalization we considered about application parts. It can use of public part(traffic analysis, road management, accident management) and private part(car navigation, map product, marketing by variable analysis) etc.

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Analysis of the Characteristic of Railroad(level-crossing) Accident Frequency (철도 건널목 사고의 발생빈도 특성분석 연구)

  • Park, Jun-Tae;Kang, Pal-Moon;Park, Sung-Ho
    • Journal of the Korean Society of Safety
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    • v.29 no.2
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    • pp.76-81
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    • 2014
  • Railroad traffic accident consists of train accident, level-crossing accident, traffic death and injury accident caused by train or vehicle, and it is showing a continuous downward trend over a long period of time. As a result of the frequency comparison of train accidents and level-crossing accidents using the railway accident statistics data of Railway Industry Information Center, the share of train accident is over 90% in the 1990s and 80% in the 2000s more than the one of level-crossing accidents. In this study, we investigated time series characteristic and short-term prediction of railroad crossing, as well as seasonal characteristic. The analysis data has been accumulated over the past 20 years by using the frequency data of level-crossing accident, and was used as a frequency data per month and year. As a result of the analysis, the frequency of accident has the characteristics of the seasonal occurrence, and it doesn't show the significant decreasing trend in a short-term.

Extrapolation of extreme traffic load effects on bridges based on long-term SHM data

  • Xia, Y.X.;Ni, Y.Q.
    • Smart Structures and Systems
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    • v.17 no.6
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    • pp.995-1015
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    • 2016
  • In the design and condition assessment of bridges, it is usually necessary to take into consideration the extreme conditions which are not expected to occur within a short time period and thus require an extrapolation from observations of limited duration. Long-term structural health monitoring (SHM) provides a rich database to evaluate the extreme conditions. This paper focuses on the extrapolation of extreme traffic load effects on bridges using long-term monitoring data of structural strain. The suspension Tsing Ma Bridge (TMB), which carries both highway and railway traffic and is instrumented with a long-term SHM system, is taken as a testbed for the present study. Two popular extreme value extrapolation methods: the block maxima approach and the peaks-over-threshold approach, are employed to extrapolate the extreme stresses induced by highway traffic and railway traffic, respectively. Characteristic values of the extreme stresses with a return period of 120 years (the design life of the bridge) obtained by the two methods are compared. It is found that the extrapolated extreme stresses are robust to the extrapolation technique. It may owe to the richness and good quality of the long-term strain data acquired. These characteristic extremes are also compared with the design values and found to be much smaller than the design values, indicating conservative design values of traffic loading and a safe traffic-loading condition of the bridge. The results of this study can be used as a reference for the design and condition assessment of similar bridges carrying heavy traffic, analogous to the TMB.

A Study on Road Characteristic Classification using Exploratory Factor Analysis (탐색적 요인분석을 이용한 도로특성분류에 관한 연구)

  • Cho, Jun-Han;Kim, Seong-Ho;Rho, Jeong-Hyun
    • Journal of Korean Society of Transportation
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    • v.26 no.3
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    • pp.53-66
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    • 2008
  • This research is to the establishment of a conceptual framework that supports road characteristic classification from a new point of view in order to complement of the existing road functional classification and examine of traffic pattern. The road characteristic classification(RCC) is expected to use important performance criteria that produced a policy guidelines for transportation planning and operational management. For this study, the traffic data used the permanent traffic counters(PTCs) located within the national highway between 2002 and 2006. The research has described for a systematic review and assessment of how exploratory factor analysis should be applied from 12 explanatory variables. The optimal number of components and clusters are determined by interpretation of the factor analysis results. As a result, the scenario including all 12 explanatory variables is better than other scenarios. The four components is produced the optimal number of factors. This research made contributions to the understanding of the exploratory factor analysis for the road characteristic classification, further applying the objective input data for various analysis method, such as cluster analysis, regression analysis and discriminant analysis.

Self-Similarity Characteristic in Data traffic (데이터 트래픽 Self-Similar 특성에 관한 연구)

  • 장우현;오행석
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2000.10a
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    • pp.272-277
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    • 2000
  • The classical queuing analysis has been tremendously useful in doing capacity planning and performance prediction, However, in many real-world cases. it has found that the predicted results form a queuing analysis differ substantially hem the actual observed performance. Specially, in recent years, a number of studies have demonstrated that for some environments, the traffic pattern is self-similar rather than Poisson. In this paper, we study these self-similar traffic characteristics and the definition of self-similar stochastic processes. Then, we consider the examples of self-similar data traffic, which is reported from recent measurement studies. Finally, we wish you that it makes out about the characteristics of actual data traffic more easily.

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Mobile Communications Data traffic using Self-Similarity Characteristic (Self-Similar 특성을 이용한 이동전화 데이터 트래픽 특성)

  • 이동철;양성현;김기문
    • Journal of the Korea Computer Industry Society
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    • v.3 no.7
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    • pp.915-920
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    • 2002
  • The classical queuing analysis has been tremendously useful in doing capacity planning and performance prediction. However, in many real-world cases. it has found that the predicted results form a queuing analysis differ substantially from the actual observed performance. Specially, in recent years, a number of studies have demonstrated that for some environments, the traffic pattern is self-similar rather than Poisson. In this paper, we study these self-similar traffic characteristics and the definition of self-similar stochastic processes. Then, we consider the examples of self-similar data traffic, which is reported from recent measurement studies. Finally, we wish yon that it makes out about the characteristics of actual data traffic more easily.

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Self-Similarity Characteristic in Data traffic (Self-Similar특성을 이용한 데이터 트래픽 특성에 관한 연구)

  • 이동철;김기문;김동일
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2001.05a
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    • pp.173-178
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    • 2001
  • The classical queuing analysis has been tremendously useful in doing capacity planning and performance prediction. However, in many real-world cases. it has found that the predicted results form a queuing analysis differ substantially from the actual observed performance. Specially, in recent years, a number of studies have demonstrated that for some environments, the traffic pattern is self-similar rather than Poisson. In this paper, we study these self-similar traffic characteristics and the definition of self-similar stochastic processes. Then, we consider the examples of self-similar data traffic, which is reported from recent measurement studies. Finally, we wish you that it makes out about the characteristics of actual data traffic more easily.

  • PDF