• Journal of Sasang Constitutional Medicine
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• v.7 no.2
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• pp.183-212
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• 1995

In order to investigate the influence of four Sasang prescriptions, $So{\breve{u}}min$ P'almunjat'ang(SPG), $So{\breve{u}}min$ Sltibimikwanjungt'ang(SSK), $T^{\prime}ae{\breve{u}}min$ $Chowis{\breve{u}}ngch^{\prime}{\breve{o}}ngt^{\prime}ang$(TCS), and $T^{\prime}ae{\breve{u}}min$ $Ch^{\prime}{\breve{o}}ngp^{\prime}yesagant^{\prime}ang$(TCP), on the activity of the autonomic nervous system in the rats exposed to noise and vibration stress, the contents of catecholamines in the urine, body temperature, heart rate, blood pressure, and stomach mucosa change were checked in this experiment. The results obtained were as follows; 1. On the 7th and 12th days from the beginning, the experimental indexes of the controled group were increased more than those of the normal group, and it meant that the noise and vibration stress induced an autonomic nervous system disorder in rats. 2. The urine-epinephrine contents in all experimental groups were decreased more than in the controled group, and in the Tcs and the Tcp groups those were significantly decreased on the 7th and 12th days. 3. The urine-norepinephrine contents in the SPK, TCS, and the TCP groups were significantly decreased on the 7th day, and in the TCS and the SPG groupsthose were significantly decredsed on the 12th day. 4. The urine-dopamine contents in the TCS group were significantlly decreased on the 12th day. 5. The body temperaature was decreased significantly in the SPG and the SSK groups on the 7th day. 6. The heart rate was significantly decreased in the SPG group on the 7th day, and it was decreased significantly in the SPG and the SSK groups on the 12th day. 7. The blood pressure was decreased in ghe SPG group significantly on the 7th day. 8. The stomach mucosa remarkably recovered from gastric ulcers in the SPG group and significantly recorvered in the other groups on the 7th day. From the above findings, th could be assumed that Taeumin and Soumin prescriptions had some significant influence on the control of the autonomic nervous system in the rats that recieved stress.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.6
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• pp.1873-1879
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• 2014

There are various methodologies to forecast the travel time using real-time data but the K-nearest neighborhood (KNN) method in general is regarded as the most one in forecasting when there are enough historical data. The objective of this study is to evaluate applicability of KNN method. In this study, real-time and historical data of toll collection system (TCS) traffic flow and the dedicated short range communication (DSRC) link travel time, and the historical path travel time data are used as input data for KNN approach. The proposed method investigates the path travel time which is the nearest to TCS traffic flow and DSRC link travel time from real-time and historical data, then it calculates the predicted path travel time using weight average method. The results show that accuracy increased when weighted value of DSRC link travel time increases. Moreover the trend of forecasted and real travel times are similar. In addition, the error in forecasted travel time could be further reduced when more historical data could be available in the future database.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1767-1770
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• 2003

This paper proposes an efficient network architecture for reflective memory system (RMS). Using this architecture, the time for broadcasting a shared-data to all nodes can be significantly shortened. The device named topology conversion switch (TCS) is implemented to realize the network architecture. The implemented TCS is applied to the ethernet based real time control network (ERCnet) to evaluate the performance.

• STI Policy Review
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• v.1 no.1
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• pp.1-21
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• 2010

To achieve the "low carbon green growth" vision, the first step is securing core technologies. Therefore, S&T policy direction for green technology development is urgently needed. As of 2008, investment in green technology (GT) development hovered around 10% of the government's total R&D budget. Thus, the Korean government developed a plan to increase that percentage to 15%, by 2013. To develop reasonable investment strategies for green technology development, targeted strategies that reflect technology and market changes by green technology area are needed. However, the overall planning and coordination of national GT development is currently split among, approximately, 10 government ministries. To establish an efficient green technology development system, the so-called "Green Technology R&D Council" should be launched in collaboration with the Presidential Committee on Green Growth and the National Science and Technology Council. Furthermore, to build a solid foundation for commercializing the outcomes of GT development projects and promote GT transfer, the government should undertake two initiatives. First, the government should reinforce GT R&D performance management, by establishing a GT R&D performance management and evaluation system. Second, the government should implement the "customized packaged support for promoting green technology business rights and commercialization" and present "e-marketplace for market-oriented green technologies". Creating a pan-ministerial policy for GT development policy would necessitate restructuring the HR(Human Resources) development system, which is currently separated by technology area. Based upon mid/long-term HR supply and demand forecasts, the government should design differentiated HR development projects, continuously evaluate those projects, and reflect the evaluation results in future policy development. Finally, to create new GT-related industries, the "Green TCS (Testing, Certification, and Standards) System" needs to be implemented. For objective evaluation and diffusion of R&D results by green technology area, a common standardization plan for testing, analysis, and measurement, like the "Green TCS", should be developed and integrated.

• International Journal of Highway Engineering
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• v.16 no.5
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• pp.99-108
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• 2014

PURPOSES : The travel times of expressway buses have been estimated using the travel time data between entrance tollgates and exit tollgates, which are produced by the Toll Collections System (TCS). However, the travel time data from TCS has a few critical problems. For example, the travel time data include the travel times of trucks as well as those of buses. Therefore, the travel time estimation of expressway buses using TCS data may be implicitly and explicitly incorrect. The goal of this study is to improve the accuracy of the expressway bus travel time estimation using DSRC-based travel time by identifying the appropriate analysis period of input data. METHODS : All expressway buses are equipped with the Hi-Pass transponders so that the travel times of only expressway buses can be extracted now using DSRC. Thus, this study analyzed the operational characteristics as well as travel time patterns of the expressway buses operating between Seoul and Dajeon. And then, this study determined the most appropriate analysis period of input data for the expressway bus travel time estimation model in order to improve the accuracy of the model. RESULTS : As a result of feasibility analysis according to the analysis period, overall MAPE values were found to be similar. However, the MAPE values of the cases using similar volume patterns outperformed other cases. CONCLUSIONS : The best input period was that of the case which uses the travel time pattern of the days whose total expressway traffic volumes are similar to that of one day before the day during which the travel times of expressway buses must be estimated.

• Journal of Korean Society of Transportation
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• v.35 no.6
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• pp.525-544
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• 2017

With the advent of the big data era, the interest in the development of land using traffic data has increased significantly. However, the current research on traffic big data lingers around organizing or calibrating the data only. In this research, a novel method for discovering the hidden values within the traffic data through data mining is proposed. Considering the fact that traffic data and network structures have similarities, network analysis algorithms are used to find valuable information in the actual traffic volume data. The PageRank and HITS algorithms are then employed to find the centralities. While conventional methods present centralities based on uncomplicated traffic volume data, the proposed method provides more reasonable centrality locations through network analysis. Since the centrality locations that we have found carry detailed spatiotemporal characteristics, such information can be used as an objective basis for making policy decisions.

• Transactions of the Korean Society of Automotive Engineers
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• v.5 no.2
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• pp.120-126
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• 1997

In this study, an effective estimation method of wheel acceleration is presented. The wheel acceleration is mainly used in the ABS(anti-lick brake system) and the TCS(traction control system). The wheel acceleration is a derivative term of the wheel speed which is generally measured by the wheel speed sensors. The results of a simple differentiation of the signal and an observation of the signal by Kalman filter show that Kalman filter has better performance than the simple differentiation. The differentiated sine signal which is contaminated with random noise shows a rugged signal compared with the signal which is filtered by the Kalman filter. The covariance of the differentiated signal is higher than that of the Kalman-filtered signal, too. The presented Kalman filter technique shows an effective way of solution to get the estimated wheel acceleration value which is sufficient to be applied to ABS or TCS control algorithms.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.209-220
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• 2022

With the worldwide spread of African swine fever, interest in livestock epidemics has increased. Livestock transport vehicles are the main cause of the spread of livestock epidemics, but there are no empirical quarantine procedures and standards related to the mobility of livestock transport vehicles in South Korea. This study extracted the trajectory of livestock-related vehicles using the facility-visit history data from the Korea Animal Health Integrated System and the DTG (Digital Tachograph) data from the Korea Transportation Safety Authority. The results are presented as exposure indices aggregating the link-time occupancy of each vehicle. As a result, 274,519 livestock-related vehicle trajectories were extracted, and the exposure values by link and zone were derived quantitatively. This study highlights the need for prior monitoring of livestock transport vehicles and the establishment of post-disaster prevention policies.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.475-476
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• 2007

• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.151-162
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• 2002

The object of this study is to develop an operating time prediction model for expressways using toll collection data. A Prediction model based on modular neural network model was developed and tested using real data. Two toll collection system(TCS) data set. Seoul-Suwon section for short range and Seoul-Daejeon section for long range, in Kyongbu expressway line were collected and analyzed. A time series analysis on TCS data indicated that operating times on both ranges are in reasonable prediction ranges. It was also found that prediction for the long section was more complex than that for the short section. However, a long term prediction for the short section turned out to be more difficult than that for the long section because of the higher sensitivity to initial condition. An application of the suggested model produced accurate prediction time. The features of suggested prediction model are in the requirement of minimum (3) input layers and in the ability of stable operating time prediction.