• The Journal of the Korea Contents Association
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• v.5 no.6
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• pp.378-385
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• 2005

Mistaking normal packets for harmful traffic may not offer service in conformity with the intention of attacker with harmful traffic, because it is not easy to classify network traffic for normal service and it for DDoS(Distributed Denial of Service) attack. And in the IPv6 environment these researches on harmful traffic are weak. In this dissertation, hosts in the IPv6 environment are attacked by NETWOX and their attack traffic is monitored, then the statistical information of the traffic is obtained from MIB(Management Information Base) objects used in the IPv6. By adapting the ESM(Exponential Smoothing Method) to this information, a normal traffic boundary, i.e., a threshold is determined. Input traffic over the threshold is thought of as attack traffic.

• Journal of the Korean Society of Safety
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• v.27 no.4
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• pp.108-114
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• 2012

Traffic Accident Merging Index(TAMI) is developed for TMACS(Traffic Safety Information Management Complex System). TAMI is calculated by combining 'Severity Index' and 'Frequency'. This paper suggest the accurate TAMI prediction model by time series forecasting. Preventing the traffic accident by accurately predicting it in advance can greatly improve road traffic safety. Searches the model which minimizes the error of 230 local self-governing groups. TAMI of 2007~2009 years data predicts TAMI of 2010. And TAMI of 2010 compares an actual index and a prediction index. And the error is minimized the constant where selects. Exponential Smoothing model was selected. And smoothing constant was decided with 0.59. TAMI Forecasting model provides traffic next year safety information of the local government.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.5
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• pp.2009-2019
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• 2013

Traffic volumes are the important basic data which are directly used for transportation network planning, highway design, highway management and so forth. They are collected by two types of collection methods, one of which is the continuous traffic counts and the other is the short duration traffic counts. The continuous traffic counts are conducted for 365 days a year using the permanent traffic counter and the short duration traffic counts are conducted for specific day(s). In case of the continuous traffic counts the missing of data occurs due to breakdown or malfunction of the counter from time to time. Thus, the diverse imputation methods have been developed and applied so far. In this study the applied exponential smoothing method, in which the data from the days before and after the missing day are used, is proposed and compared with other imputation methods. The comparison shows that the applied exponential smoothing method enhances the accuracy of imputation when the coefficient of traffic volume variation is low. In addition, it is verified that the variation of traffic volume at the site is an important factor for the accuracy of imputation. Therefore, it is necessary to apply different imputation methods depending upon site and time to raise the reliability of imputation for missing traffic values.

• Journal of Internet of Things and Convergence
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• v.8 no.1
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• pp.53-58
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• 2022

Smoothing is a transmission plan that converts video data stored at a variable bit rate into a constant bit rate. In the study of [6-7], when a data rate increase is required, the frame with the smallest increase is set as the start frame of the next transmission rate section, when a data tate decrease is required. the frame with the largest decrease is set as the start frame of the next transmission rate section, And the smoothing algorithm was proposed and performance was evaluated in an environment where network traffic is not considered. In this paper, the smoothing algorithm of [6-7] evaluates the adaptive CBA algorithm and performance with minimum frame rate, average frame rate, and frame rate variation from 512KB to 32MB with E.T 90 video data in an environment that considers network traffic. As a result of comparison, the smoothing algorithm of [6-7] showed superiority in the comparison of the minimum refresh rate.

• Journal of Communications and Networks
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• v.5 no.3
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• pp.258-265
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• 2003

Transmission of continuous media streams has been a challenging problem of multimedia service. Lots of works have been done trying to figure out the best solution for this problem, and some works presented the optimal solution for transmitting the stored video using smoothing schemes applied to each individual stream. But those smoothing schemes considered only one stream, not the whole streams being serviced, to apply themselves, which could only achieve local optimum not the global optimum. Most of all, they did not exploit statistical multiplexing gain that can be obtained before smoothing. In this paper, we propose a new smoothing scheme that deals with not an individual stream but the whole streams being serviced simultaneously to achieve the optimal network bandwidth utilization and maximize the number of streams that can be serviced simultaneously. We formally proved that the proposed scheme not only provides deterministic QoS for each client but also maximizes number of clients that can be serviced simultaneously and hence achieves maximum utilization of transmission bandwidth.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4887-4907
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• 2017

Accurate traffic flow forecasting is critical to the development and implementation of city intelligent transportation systems. Therefore, it is one of the most important components in the research of urban traffic scheduling. However, traffic flow forecasting involves a rather complex nonlinear data pattern, particularly during workday peak periods, and a lot of research has shown that traffic flow data reveals a seasonal trend. This paper proposes a new traffic flow forecasting model that combines seasonal relevance vector regression with the hybrid chaotic simulated annealing method (SRVRCSA). Additionally, a numerical example of traffic flow data from The Transportation Data Research Laboratory is used to elucidate the forecasting performance of the proposed SRVRCSA model. The forecasting results indicate that the proposed model yields more accurate forecasting results than the seasonal auto regressive integrated moving average (SARIMA), the double seasonal Holt-Winters exponential smoothing (DSHWES), and the relevance vector regression with hybrid Chaotic Simulated Annealing method (RVRCSA) models. The forecasting performance of RVRCSA with different kernel functions is also studied.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.9
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• pp.2326-2333
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• 2009

In the adaptable bandwidth allocation technique, a transmission plan for variable rate video data is made by smoothing algorithms such as CBA algorithm and the data is sent by the transmission plan considering network traffic. But the CBA algorithm, the MCBA algorithm, MVBA algorithm and the other smoothing algorithms produce a transmission plan where the size of the increasing interval of transmission rate is generally larger than the size of the decreasing interval. And the transmission rate in CBA algorithm, the MCBA algorithm, the MVBA algorithm is changed in overflow curve during the increasing interval of transmission rate. This may cause many frames to be discarded when available transmission rate is larger than transmission rate by the transmission plan. In this paper, the smoothing algorithm, where transmission rate is changed in the middle of underflow curve and overflow curve to decrease the number of discarded frames, but the transmission rate increases at the minimum, and the CBA algorithm, the MCBA algorithm, the MVBA algorithm are applied to a transmission plan in the adaptable bandwidth allocation technique, and the minimum frame rates, the average frame rates, the variation of frame rates, and the numbers of discarded frames are compared in among algorithms.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.99-102
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• 1998

As multimedia communication services have been widely spreading, the amount of video traffic is rapidly increasing in B-ISDN environment based on the ATM technology. The image quality of MPEG services is very sensitive to the cell losses in ATM network, since each cell contains information needed at decoding process. Since the number of cells in each frame of MPEG is variable, this video smoothing technology need to prepare a buffer for no overflow or underflow at the transmission, requires that some number of cells be taken to the buffer in client before the playback of video. To ensure the high quality image of video, the video smoothing is scheduled by a Group of Picture unit. In this paper, we then apply the theory to reds nightmare encoded in MPEG, and find minimum smoothing buffer size, initial buffer size. It can be used to study the smoothing of stored video.

• Korea Trade Review
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• v.44 no.2
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• pp.51-62
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• 2019

This study predicts the future world seaborne trade volume with econometrics methods using 23-year time series data provided by Clarksons. For this purpose, this study uses simple regression analysis, exponential smoothing method and seemingly unrelated regression model (SUR Model). This study is meaningful in that it predicts worldwide total seaborne trade volume and seaborne traffic in four major items (container, bulk, crude oil, and LNG) from 2019 to 2023 as there are few prior studies that predict future seaborne traffic using recent data. It is expected that more useful references can be provided to trade related workers if the analysis period was increased and additional variables could be included in future studies.

• Current Optics and Photonics
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• v.2 no.1
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• pp.7-14
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• 2018

As a sophisticated detection technology, LIDAR has been widely employed to probe low-altitude windshear. Due to the drawbacks of the traditional ramp algorithm, the alarm accuracy of the LIDAR has not been satisfactory. Aiming at settling this matter, a novel method is proposed on the basis of improved signal smoothing and second windshear detection, which essentially acts as a combination of ramp algorithm and segmentation approach, involving the human factor as well as signal fluctuations. Experiments on the real and artificial signals verify our approach.