• Journal of Korean Society of Transportation
• /
• v.24 no.2 s.88
• /
• pp.127-137
• /
• 2006

This Paper Presents a novel incident detection method for using the speed-density difference between detectors. When a incident is happened the downstream traffic condition is mostly lower speed and higher density and the upstream is higher speed and lower density In respect of such characteristics, we can suggest a method for detecting an incident based on the speed-density information provided from detectors. The incident detection method is tested by using the accident data collected from the Cheonan-Nonsan Highway. The results show that suck an incident detection method can analyze the position of accident by comparing the speed-density difference between detectors. The work described in this paper is only at on early stage, in the sense that there are several areas to be further investigated in application of this method. such as setting a critical value for judging the incident. a level of accident wave, a varying Pattern between the incident locations and detectors, etc.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.20 no.6
• /
• pp.26-36
• /
• 2021

In this study, a deep learning model for predicting the queue length was developed using the information collected from the image detector. Then, a multiple regression analysis model, a statistical technique, was derived and compared using two indices of mean absolute error(MAE) and root mean square error(RMSE). From the results of multiple regression analysis, time, day of the week, occupancy, and bus traffic were found to be statistically significant variables. Occupancy showed the most strong impact on the queue length among the variables. For the optimal deep learning model, 4 hidden layers and 6 lookback were determined, and MAE and RMSE were 6.34 and 8.99. As a result of evaluating the two models, the MAE of the multiple regression model and the deep learning model were 13.65 and 6.44, respectively, and the RMSE were 19.10 and 9.11, respectively. The deep learning model reduced the MAE by 52.8% and the RMSE by 52.3% compared to the multiple regression model.

• Korean Journal of Remote Sensing
• /
• v.30 no.4
• /
• pp.511-524
• /
• 2014

In this study, we investigated the statistical occupations and interannual variations of land cover types over Northeast Asian region using the 12 years (2001-2012) MODerate Resolution Imaging Spectroradiometer(MODIS) land cover data sets. The spatial resolution and land cover types of MODIS land cover data sets are 500 m and 17, respectively. The 12-year average shows that more than 80% of the analysis region is covered by only 3 types of land cover, cropland (36.96%), grasslands (23.14%) and mixed forests (22.97%). Whereas, only minor portion is covered by cropland/natural vegetation mosaics (6.09%), deciduous broadleaf forests (4.26%), urban and built-up (2.46%) and savannas (1.54%). Although sampling period is small, the regression analysis showed that the occupations of evergreen needleleaf forests, deciduous broadleaf forests and mixed forests are increasing but the occupations of woody savannas and savannas are decreasing. In general, the pixels where the land cover types are classified differently with year are amount to more than 10%. And the interannual variations in the occupations of land cover types are most prominent in cropland (1.41%), mixed forests (0.82%) and grasslands (0.73%). In addition, the percentage of pixels classified as 1 type for 12 years is only 57% and the other pixels are classified as more than 2 types, even 9 types. The annual changes in the classification of land cover types are mainly occurred at the almost entire region, except for the eastern and northwestern parts of China, where the single type of land cover located. When we take into consider the time scale needed for the land cover changes, the results indicate that the MODIS land cover data sets over the Northeast Asian region should be used with caution.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.4 no.2 s.7
• /
• pp.13-22
• /
• 2005

The purpose of this research is how to estimate the traffic queue length in the signal intersection accurately. The current traffic queue length algorithm in COSMOS has been using the congestion diagram which comes from the speed of an average separated vehicle - using average vehicle length and the occupancy time from loop detectors. So some errors were occurred by the speed estimation method using average vehicle lengths. And Operators had been difficult to optimize some variables for measuring the traffic queue length estimation algorithm in COSMOS. Therefore the traffic queue length estimation algorithm on the basis of the relation between distances and occupancy rates from loop detectors was developed in this thesis. This thesis had the advantage of using occupancy rates which came out from loop detectors easily and no need to optimize some variables for the established algorithm in COSMOS. And the results of testing this algorithm in some sites which had installed COSMOS system showed better results than COSMOS system's results. But it was noted that further studies which carry it out in various sites and under various cases are necessary for applying to actual intersections.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.8 no.2
• /
• pp.14-26
• /
• 2009

This study presented a novel method to estimate travel times under incident conditions. Predictive travel time information was defined and evaluated with the proposed method. The proposed method utilized individual vehicle speeds obtained from global positioning systems (GPS) and inter-vehicle communications(IVC) for more reliable real-time travel times. Individual vehicle trajectory data were extracted from microscopic traffic simulations using AIMSUN. Market penetration rates (MPR) and IVC ranges were explored with the accuracy of travel times. Relationship among travel time accuracy, IVC ranges, and MPR were further identified using regression analyses. The outcomes of this study would be useful to derive functional requirements associated with traffic information systems under forthcoming ubiquitous transportation environment

• Journal of the Microelectronics and Packaging Society
• /
• v.21 no.3
• /
• pp.51-56
• /
• 2014

The reliability of solder joint is significantly affected by the property of surface finish. This paper reports on a study of high speed shear energy and failure mode for Sn-4.0wt%Ag-0.5wt%Cu (SAC405) solder joints with the time of Pd activation. The nodule size of electroless Ni-P deposit increased with increasing the time of Pd activation. The roughness (Ra) of electroless Ni-P deposit decreased with increasing the time of Pd activation. Then, with $HNO_3$ vapor, the quasi-brittle and brittle mode of SAC405 solder joint decreased with increasing the time of Pd activation. This results indicate that the increase in the Pd activation time for Electroless Ni/ Electroless Pd/ Immersion Au (ENEPIG) surface finish play a critical role for improving the robustness of SAC405 solder joint.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.1
• /
• pp.1-9
• /
• 2024

This paper proposes an integration of the ED-H scheduling algorithm, known for optimal real-time scheduling, with the LoRaEnergySim simulator. This integration facilitates the simulation of interactions between real-time scheduling algorithms for tasks with time constraints in Class-A LoRaWAN Class-A devices using a super-capacitor-based energy harvesting system. The time and energy characteristics of LoRaWAN status and state transitions are extracted in a log format, and the task model is structured to suit the time-slot-based ED-H scheduling algorithm. The algorithm is extended to perform tasks while satisfying time constraints based on CPU executions. To evaluate the proposed approach, the ED-H scheduling algorithm is executed on a set of tasks with varying time and energy characteristics and CPU occupancy rates ranging from 10% to 90%, under the same conditions as the LoRaEnergySim simulation results for packet transmission and reception. The experimental results confirmed the applicability of co-simulation by demonstrating that tasks are prioritized based on urgency without depleting the supercapacitor's energy to satisfy time constraints, depending on the scheduling algorithm.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.10 no.2
• /
• pp.289-296
• /
• 2015

Wireless multimedia sensor network senses and transfers mass multimedia data. Also, it is sensitive to latency. This thesis proposes a routing technique based on traffic priority in order to improve the network efficiency by minimizing latency. In addition, it proposes a congestion control mechanism that uses packet service time, packet inter-arrival time, buffer usage, etc. In this thesis, we verified the reduction of packet latency in accordance with the quality level of packet as a result of the performance analysis through the simulation method. Also, we verified that the proposed mechanism maintained a reliable network state by preventing packet loss due to network overload.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2021.11a
• /
• pp.1269-1272
• /
• 2021

급격한 차량 수요의 증가로 인한 주차공간의 부족으로 인력기반 주차관리의 한계점을 이용한 여러 위법 행위가 발생함에 따라 관리자의 정기적인 순찰 및 관리의 필요성이 증가하고 있다. 기존 인력기반 주차관리 시스템은 관리자에게 전적으로 의존하고 있어 관리의 정확도 및 효율성이 비교적 낮다. 본 논문에서는 엣지 컴퓨팅 기반의 클라우드 주차관리 시스템을 제안하며, 이는 효율적인 주차관리를 통한 시간과 노동력 절감에 기여한다. 본 시스템이 제공하는 주요 기능은 다음과 같다. 1) 주차구역 및 주차 차량 정보를 분석하여 입·출차를 관리하고 관리자에게 실시간 주차 현황 정보를 제공한다. 2) 추출된 차량 정보를 바탕으로 부정주차 여부를 감지하여 지정주차 구역 관리를 자동화한다. 3) 관리자에게 시간대별 주차구역 점유율 정보를 제공하여 거주자의 가용 주차공간을 확보한다. 4) 거주자의 선호 주차구역 및 시간대를 파악하여 거주자의 주차 편의성을 제공한다. 위 기능을 통해 기존 주차관리의 비효율성을 개선하고자 한다.

• Proceedings of the Korean Information Science Society Conference
• /
• 2005.11a
• /
• pp.829-831
• /
• 2005

최근 컴포넌트 기반 미들웨어의 최적화에 대한 연구가 활발히 이루어지고 있다. CPU점유율이 높은 어플리케이션의 동시 실행은 시스템에 부하를 주기 때문에, 시스템 성능을 약화시키고 실행중인 어플리케이션에 영향을 준다. 컴포넌트 기반 미들웨어는 여러 개의 재사용 가능한 컴포넌트를 조합하여 어플리케이션을 구성하기 때문에 동적으로 재구성이 가능하다. 본 논문은 컴포넌트 기반 미들웨어가 시스템 상황에 대한 정보를 받아들여 시스템의 상황을 스스로 판단하고 자가치료 또는 시스템의 성능을 최적화시키는 컴포넌트를 선택하는 방법을 제안한다. 상황판단을 위해 유연한 추론이 가능하고, 데이터로부터 자동학습이 가능한 베이지안 네트워크를 사용하였다. 두 시간 가량의 데이터를 리눅스 사용자로부터 획득하여 실험한 결과, 테스트 데이터에 대해 $76.5\%$의 성능을 보였다.