• International Journal of Highway Engineering
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• v.17 no.6
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• pp.11-18
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• 2015

PURPOSES : The purpose of this thesis is to evaluate the effectiveness of an active noise cancellation (ANC) system in reducing the traffic noise level against frequencies from the predictive model developed by previous research. The predictive model is based on ISO 9613-2 standards using the Noble close proximity (NCPX) method and the pass-by method. This means that the use of these standards is a powerful tool for analyzing the traffic noise level because of the strengths of these methods. Traffic noise analysis was performed based on digital signal processing (DSP) for detecting traffic noise with the pass-by method at the test site. METHODS : There are several analysis methods, which are generally divided into three different types, available to evaluate traffic noise predictive models. The first method uses the classification standard of 12 vehicle types. The second method is based on a standard of four vehicle types. The third method is founded on 5 types of vehicles, which are different from the types used by the second method. This means that the second method not only consolidates 12 vehicle types into only four types, but also that the results of the noise analysis of the total traffic volume are reflected in a comparison analysis of the three types of methods. The constant percent bandwidth (CPB) analysis was used to identify the properties of different frequencies in the frequency analysis. A-weighting was applied to the DSP and to the transformation process from analog to digital signal. The root mean squared error (RMSE) was applied to compare and evaluate the predictive model results of the three analysis methods. RESULTS : The result derived from the third method, based on the classification standard of 5 vehicle types, shows the smallest values of RMSE and max and min error. However, it does not have the reduction properties of a predictive model. To evaluate the predictive model of an ANC system, a reduction analysis of the total sound pressure level (TSPL), dB(A), was conducted. As a result, the analysis based on the third method has the smallest value of RMSE and max error. The effect of traffic noise reduction was the greatest value of the types of analysis in this research. CONCLUSIONS : From the results of the error analysis, the application method for categorizing vehicle types related to the 12-vehicle classification based on previous research is appropriate to the ANC system. However, the performance of a predictive model on an ANC system is up to a value of traffic noise reduction. By the same token, the most appropriate method that influences the maximum reduction effect is found in the third method of traffic analysis. This method has a value of traffic noise reduction of 31.28 dB(A). In conclusion, research for detecting the friction noise between a tire and the road surface for the 12 vehicle types needs to be conducted to authentically demonstrate an ANC system in the Republic of Korea.

• Journal of Information Technology and Architecture
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• v.10 no.1
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• pp.101-111
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• 2013

Internet traffic volume has been increasing rapidly due to popularization of various smart devices and Internet development. In particular, HTTP-based traffic volume of smart devices is increasing rapidly in addition to desktop traffic volume. The increased mobile traffic can cause serious problems such as network overload, web security, and QoS. In order to solve these problems of the Internet overload and security, it is necessary to accurately detect applications. Traditionally, well-known port based method is utilized in traffic classification. However, this method shows low accuracy since P2P applications exploit a TCP/80 port, which is used for the HTTP protocol; to avoid firewall or IDS. Signature-based method is proposed to solve the lower accuracy problem. This method shows higher analysis rate but it has overhead of signature generation. Also, previous signature-based study only analyzes applications in HTTP protocol-level not application-level. That is, it is difficult to identify application name. Therefore, previous study only performs protocol-level analysis. In this paper, we propose a signature generation method to classify HTTP-based traffics in application-level using the characteristics of typical semi HTTP header. By applying our proposed method to campus network traffic, we validate feasibility of our method.

• Journal of Korean Society of Transportation
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• v.20 no.1
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• pp.39-52
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• 2002

Traffic data by vehicle classification is difficult for mutual exchange of data due to the different vehicle classification from each other by the data sources; as a result, application of the data is very limited. In Particular. in case of TCS vehicle classification in national highways, passenger car, van and truck are mixed in one category and the practical usage is very low. The research standardize the vehicle classification to convert other data and develop the model which can estimate national highway traffic data by the standardized vehicle classification from the raw traffic data obtained at the highway tollgates. The tollgates are categorized into several groups by their features and the model estimates traffic data by the standardized vehicle classification by using the point estimation and bootstrap algorithm. The result indicates that both of the two methods above have the significant level. When considering the bias of the extreme value by the sample size, the bootstrap algorithm is more sophisticated. Using result of this study, we is expect the usage improvement of TCS data and more specific comparison between the freeway traffic investigation and link volume on freeway using the TCS data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.5B
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• pp.348-356
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• 2012

The application traffic analysis is getting more and more challenging due to the huge amount of traffic from high-speed network link and variety of applications running on wired and wireless Internet devices. Multi-level combination of various analysis methods is desired to achieve high completeness and accuracy of analysis results for a real-time analysis system, while requires much of processing burden on the contrary. This paper proposes a novel architecture for a real-time traffic analysis system which improves the processing performance on multi-core CPU environment. The main contribution of the proposed architecture is an efficient parallel processing mechanism with multiple threads of various analysis methods. The feasibility of the proposed architecture was proved by implementing and deploying it on our campus network.

• Annual Conference of KIPS
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• 2009.11a
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• pp.475-476
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• 2009

응용 레벨 트래픽 분류를 위한 다양한 방법 중 페이로드 시그니쳐 기반 분석 방법은 높은 정확성과 분석률을 보인다. 하지만 현재의 인터넷 기반의 응용 프로그램은 사용자의 요구사항을 만족시키고 안정적인 서비스를 제공하기 위해 빠른 속도로 변화하고 있어서 지속적으로 높은 분류 성능을 보장할 수 없다. 따라서 본 논문에서는 페이로드 시그니쳐 기반의 분석 방법을 기반으로 응용 프로그램의 변화, 출현에 유연하게 대처 가능한 시그니쳐 관리 시스템을 제안한다. 또한 시그니쳐 관리 시스템을 학내망에 적용하고 실시간으로 트래픽을 분석하여 그 타당성을 증명한다.

• Annual Conference of KIPS
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• 2009.04a
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• pp.1288-1291
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• 2009

네트워크 트래픽 모니터링과 분석은 엔터프라이즈 네트워크의 효율적인 운영과 안정적 서비스를 제공하기 위한 필수적인 요소이다. 다양한 트래픽 분석 방법 중 시그니쳐 기반의 분석 방법은 가장 높은 분석률을 보이지만 모든 시그니쳐를 수작업으로 추출하기 때문에 응용프로그램의 변화와 출현에 유연하게 대응하지 못한다. 따라서 본 논문에서는 응용프로그램 시그니쳐 생성 과정의 단점을 보완할 수 있는 시그니쳐 자동 생성 시스템을 제안한다. 응용프로그램 시그니쳐는 페이로드 내의 고유한 바이트 시퀀스로 정의하며 응용프로그램이 발생시키는 모든 트래픽을 대상으로 추출한다. 또한 생성 시스템의 실효성을 증명할 수 있는 검증 시스템 및 검증 네트워크를 제시한다.

• Journal of the Ergonomics Society of Korea
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• v.35 no.5
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• pp.371-381
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• 2016

Objective:This study aims to evaluate the features of heart rate variability (HRV) and respiratory signals as indices for a driver's drowsiness and waking status in order to develop the classification model for a driver's drowsiness and waking status using those features. Background: Driver's drowsiness is one of the major causal factors for traffic accidents. This study hypothesized that the application of combined bio-signals to monitor the alertness level of drivers would improve the effectiveness of the classification techniques of driver's drowsiness. Method: The features of three heart rate variability (HRV) measurements including low frequency (LF), high frequency (HF), and LF/HF ratio and two respiratory measurements including peak and rate were acquired by the monotonous car driving simulation experiments using the photoplethysmogram (PPG) and respiration sensors. The experiments were repeated a total of 50 times on five healthy male participants in their 20s to 50s. The classification model was developed by selecting the optimal measurements, applying a binary logistic regression method and performing 3-fold cross validation. Results: The power of LF, HF, and LF/HF ratio, and the respiration peak of drowsiness status were reduced by 38%, 22%, 31%, and 7%, compared to those of waking status, while respiration rate was increased by 3%. The classification sensitivity of the model using both HRV and respiratory features (91.4%) was improved, compared to that of the model using only HRV feature (89.8%) and that using only respiratory feature (83.6%). Conclusion: This study suggests that the classification of driver's drowsiness and waking status may be improved by utilizing a combination of HRV and respiratory features. Application: The results of this study can be applied to the development of driver's drowsiness prevention systems.

• Journal of Korean Society of Transportation
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• v.18 no.3
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• pp.101-112
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• 2000

The Purpose of this Paper was to revise the method of USHCM and to establish new method for level of service analysis on two-lane rural highways. For this Purpose, total delay rate was selected as new MOE for level of service, replacing the present Percent time delay. This result showed that total delay rate was more effective for considering the effects of traffic flows, auxiliary lane, and vertical tirade. The application of total delay rate could resolve the Problems in the USHCM method, such as too wide ranges for level of service D and E, and the use of different Procedures for level of service analysis of general terrain segment and specific grade Procedures. The research results are as follows First, a new method for level of service analysis on two-lane rural highways was developed using the total delay rate. Second, a new classification for level of service was developed and a consistent method applicable for general terrain segment and specific tirade Procedures was developed. Third, the desired speed on two-lane rural highways was determined as 85km/h.