• Title/Summary/Keyword: Short Traffic

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The Clinical Studies for Muscle Energy Techniques on Patients with Nuchal Pain Caused by Traffic Accidents (교통사고로 유발된 경항통 환자의 근에너지기법(MET)의 효과에 대한 임상적 연구)

  • Jeon, Tae-Dong;Lee, Han-Gil;Hong, Seo-Yuong;Heo, Dong-Seok;Yoon, Il-Ji
    • Journal of Korean Medicine Rehabilitation
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    • v.19 no.1
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    • pp.125-134
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    • 2009
  • Objectives : The purpose of this study is to find out the effects of muscle energy techniques on nuchal pain caused by traffic accidents. Methods : The 20 patients were divided into 2 groups: group A was treated except muscle energy techniques and group B was treated with muscle energy techniques. Both groups were treated with acupunture treatment, physical theraphy and herbal medication. Patients were evaluated by McGill Pain Questionnaire-Short Form(SF-MPQ), Pain Disability Index(PDI) and Neck Disability Index(NDI) in traffic accident patients. Results : 1. Both Group were significantly decreased in sensory of SF-MPQ, VAS, PDI and NDI after 7 days of treatment. 2. Group B compared with the Group A was significantly decresed in VAS, PDI after 7 days of treatment. Conclusions : We found out that muscle energy techniques is considered to be effective and useful on nuchal pain caused by traffic accidents.

Forecasting Methodology of the Radio Spectrum Demand (무선자원 서비스 수요예측 방안)

  • Kim Jeom-Gu;Jang Hee-Seon;shin Hyun-Cheul
    • The Journal of Information Technology
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    • v.5 no.4
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    • pp.173-183
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    • 2002
  • In this paper, we propose an efficient forecasting methodology of the mid and long-term frequency demand in Korea. The methodology consists of the following three steps: classification of basic service group, calculation of effective traffic, and frequency forecasting. Based on the previous studies, we classify the services into wide area mobile, short range radio, fixed wireless access and digital video broadcasting in the step of the classification of basic service group. For the calculation of effective traffic, we use the measures of erlang and bps. The step of the calculation of effective traffic classifies the user and basic application, and evaluates the effective traffic. Finally, in the step of frequency forecasting, different methodology will be proposed for each service group.

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A study on improving the evaluation of motorway functions using Trip Length Frequency Distribution(TLFD) (통행거리빈도분포를 활용한 고속도로 기능 평가 개선 연구)

  • Kwon, Ceholwoo;Yoon, Byoungjo
    • Journal of Urban Science
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    • v.11 no.2
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    • pp.9-17
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    • 2022
  • The purpose of this study is to develop an index for evaluating the function of a new motorway using the travel distance frequency distribution (TLFD) calculated using the vehicle travel route big data, and to overcome the limitations of the evaluation through the existing traffic volume. The mobility evaluation index of motorways was developed by applying it to the TLFD data table in 2019. The smaller the value of the mobility evaluation index of the link is calculated, the more it is a link with mainly short-distance travel, and the higher the value of the mobility evaluation index, the more it means a link with mainly long-distance travel. The accessibility evaluation index was calculated through the result of the mobility evaluation index of all motorways developed, and all motorways were grouped into three groups using K-means clustering. Group A was found to exist inside a large city and consisted of motorways with many short-distance traffic, Group B was investigated as acting as an arterial between groups, and Group C was classified as a motorway consisting mainly of long-distance traffic connecting large cities and large cities. This study is significant in developing a new motorway function evaluation index that can overcome the limitations of motorway function evaluation through the existing traffic volume. It is expected that this study can be a reasonable comprehensive indicator in the operation and planning process of motorways.

Migration and Energy Aware Network Traffic Prediction Method Based on LSTM in NFV Environment

  • Ying Hu;Liang Zhu;Jianwei Zhang;Zengyu Cai;Jihui Han
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.3
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    • pp.896-915
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    • 2023
  • The network function virtualization (NFV) uses virtualization technology to separate software from hardware. One of the most important challenges of NFV is the resource management of virtual network functions (VNFs). According to the dynamic nature of NFV, the resource allocation of VNFs must be changed to adapt to the variations of incoming network traffic. However, the significant delay may be happened because of the reallocation of resources. In order to balance the performance between delay and quality of service, this paper firstly made a compromise between VNF migration and energy consumption. Then, the long short-term memory (LSTM) was utilized to forecast network traffic. Also, the asymmetric loss function for LSTM (LO-LSTM) was proposed to increase the predicted value to a certain extent. Finally, an experiment was conducted to evaluate the performance of LO-LSTM. The results demonstrated that the proposed LO-LSTM can not only reduce migration times, but also make the energy consumption increment within an acceptable range.

Determination of Base Capacity Values for Short-Term Freeway Work Zone (고속도로 단기공사구간 기본용량 결정에 관한 연구)

  • Kim, Sang Gu;Hong, Gil Seong
    • Journal of Korean Society of Transportation
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    • v.31 no.1
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    • pp.37-46
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    • 2013
  • Lane closure in freeway work zone due to maintenance and repair of freeway facilities results in abrupt change of traffic flow. Sudden change of traffic flow results strong interactions among vehicles, and reduces capacity compared to the ordinary traffic condition. Such capacity reduction is likely to cause congestion, traffic queues, and economic loss cost. This study aims to determine the base capacity for a short-term freeway work zone that can be used to establish a work zone schedule in advance without any traffic impact. First, the research collected detector data and schedule data of road works on all freeways in Korea. Second, the research determined 23 study sites finding the capacity values of work zone after matching two kinds of data. All study sites had varying characteristics regarding traffic flow being adjacent to work zone during road works. The capacity values were reviewed in terms of lane closure configuration, the types of work, and design speed. Finally, research proposed capacity values for a short-term freeway work zone with the design speeds of 100 kph, 120 kph and 1,700 pcphpl, 1,750 pcphpl, respectively.

A Priority Scheme for IEEE 802.11 Wireless LAN

  • Jang, Yeong-Min
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.12B
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    • pp.1996-2002
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    • 2000
  • This paper investigates a priority scheme for IEEE 802.11 Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA) protocol in order to provide short access times for priority frames (e.g. time-deadline traffic) even when the overall traffic on the wireless channel is heavy. Under the compatibility constraint for the IEEE 802.11 wireless LANs, two priority systems are simulated: no priority (current IEEE 802.11 standard) for time-deadline traffics and dynamic time-deadline priority. We evaluate algorithms to improve the time-deadline traffic performance using discrete event simulation (DES)

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A Short-Term Traffic Information Prediction Model Using Bayesian Network (베이지안 네트워크를 이용한 단기 교통정보 예측모델)

  • Yu, Young-Jung;Cho, Mi-Gyung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.4
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    • pp.765-773
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    • 2009
  • Currently Telematics traffic information services have been various because we can collect real-time traffic information through Intelligent Transport System. In this paper, we proposed and implemented a short-term traffic information prediction model for giving to guarantee the traffic information with high quality in the near future. A Short-term prediction model is for forecasting traffic flows of each segment in the near future. Our prediction model gives an average speed on the each segment from 5 minutes later to 60 minutes later. We designed a Bayesian network for each segment with some casual nodes which makes an impact to the road situation in the future and found out its joint probability density function on the supposition of GMM(Gaussian Mixture Model) using EM(Expectation Maximization) algorithm with training real-time traffic data. To validate the precision of our prediction model we had conducted various experiments with real-time traffic data and computed RMSE(Root Mean Square Error) between a real speed and its prediction speed. As the result, our model gave 4.5, 4.8, 5.2 as an average value of RMSE about 10, 30, 60 minutes later, respectively.

Modern Telecommunications Media and Strategy for Intelligent Transportation System (지능형물류교통시스팀을 위한 첨단 정보통신기술과 향후 추진 전략)

  • 김성수
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.20 no.43
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    • pp.91-97
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    • 1997
  • The objective of a traffic management system is to promote safe driving, low pollution, short travel time, and optimized traffic flow by naturally distributing the flow of traffic through the use of suitable telecommunications media. Such traffic management systems will be improved by integrating dynamic traffic data and two-way communication media because cars can work as sensors. The purpose of this paper is to help organizations trying to select the correct telecommunications media for minimal-cost investment options without loss of functionality. The wireless communications for an intelligent transportation system (ITS) are introduced in this paper. We describe which kind of telecommunication media are suitable. FM broadcast type media or cellular phone can be recommended to provide real time traffic and roadway conditions in the first stage of ITS, because existing broadcast base station or cellular network facilities can be used. It is expected that cellular radio network or satellites are used for communication. Finally, the strategy and deployment plan of an ITS are described based on selections of telecommunication media in Korea.

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Development of Traffic Accident Forecasting Model in Pusan (부산시 교통사고예측모형의 개발)

  • 이일병;임현정
    • Journal of Korean Society of Transportation
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    • v.10 no.3
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    • pp.103-122
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    • 1992
  • The objective of this research is to develop a traffic accident forecasting model using traffic accident data in pusan from 1963 to 1991 and then to make short-term forecasts('93~'94) of traffic accidents in pusan. In this research, several forecasting models are developed. They include a multiple regression model, a time-series ARIMA model, a Logistic curve model, and a Gompertz curve model. Among them, the model which shows the most significance in forecasting accuracy is selected as the traffic accident forecasting model. The results of this research are as followings. 1. The existing model such as Smeed model which was developed for foreign countries shows only 47.8% explanation for traffic accident deaths in Korea. 2. A nonliner regression model ($R^2$=0.9432) and a Logistic curve model are appeared to be th gest forecasting models for the number of traffic accidents, and a Logistic curve model shows th most significance in predicting the accident deaths and injuries. 3. The forecasting figures of the traffic accidents in pusan are as followings: . In 1993, 31, 180 accidents are predicted to happen, and 430 persons are predicted to be deaths and 29, 680 persons are predicated to be injuries. . In 1994, 33, 710 accidents are predicted to happen, and 431.persons are predicted to be deat! and 30, 510 persons are predicted to be injuried. Therefore, preventive measures against traffic accidents are certainly required.

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Methodology for Developing a Predictive Model for Highway Traffic Information Using LSTM (LSTM을 활용한 고속도로 교통정보 예측 모델 개발 방법론)

  • Yoseph Lee;Hyoung-suk Jin;Yejin Kim;Sung-ho Park;Ilsoo Yun
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.5
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    • pp.1-18
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    • 2023
  • With the recent developments in big data and deep learning, a variety of traffic information is collected widely and used for traffic operations. In particular, long short-term memory (LSTM) is used in the field of traffic information prediction with time series characteristics. Since trends, seasons, and cycles differ due to the nature of time series data input for an LSTM, a trial-and-error method based on characteristics of the data is essential for prediction models based on time series data in order to find hyperparameters. If a methodology is established to find suitable hyperparameters, it is possible to reduce the time spent in constructing high-accuracy models. Therefore, in this study, a traffic information prediction model is developed based on highway vehicle detection system (VDS) data and LSTM, and an impact assessment is conducted through changes in the LSTM evaluation indicators for each hyperparameter. In addition, a methodology for finding hyperparameters suitable for predicting highway traffic information in the transportation field is presented.