• Journal of the Korean Society for Library and Information Science
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• v.54 no.3
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• pp.237-262
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• 2020

Part-time instructors are contributing to the production of excellent human resources through education and research, strengthening research competitiveness, and national and social knowledge and academic development. Therefore, academic and research information services for part-time instructors are essential for their educational and research activities. In this study, researcher suggested various methods for providing efficient educational and academic information services by surveying and analyzing their information environment, information needs, and educational and academic information recognition and usage behavior by applying the survey method to part-time instructors.

• Korea Information Processing Society Review
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• v.5 no.1
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• pp.62-74
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• 1998

This paper deals with developing a remote & real-time Computer-Aided Logistics Support (CALS) Systems through Information Super-Highway. A prototype of CALS is designed and implemented considering the environment of Information Super Highway. The concept of CSCW based virtual enterprise is discussed in con-nection with the four different activities. development of remote & virtual equipment controller remote-monitoring & inspection real time tracking of logistics information and web-based bidding and delivery system. A real implemented system is demonstrated under the Infor-mation Super-Highway with the corresponding software and hardware configuration.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.4 no.3 s.8
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• pp.51-59
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• 2005

To improve the quality of bus service, providing bus ravel time information to passenger through station screen. Generally, bus travel time information predict by using previous bus data such as neural network, Kalman filtering, and moving average algorithms. However, when they got a difficulty about bus travel time information because of the missing previous bus data, they use pattern data. Generally, nevertheless the difference of range is big. Hence in this research to calculate the bus travel time information when the bus information is missed, use queue detector's data which set up in link. The application of several factors which influence in bus link travel time, we used CORSIM Version 5.1 simulation package.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.559-564
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• 2006

The purpose of this study is to minimize negative effect of VMS travel time information service by sensitivity analysis, which forecasts the change in link traffic volume. As a result, strategies for providing travel information that can change driving patterns for minimizing travel time were found. The framework for analysis is recently expanded with the application of game theory. According to the experiment, the algorithm generated for travel time information service reduces total travel time and yields travel patterns that is very close to the system optimization. Also, this study found that the route the travel time service information is provided about could play the important role.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4349-4371
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• 2019

Moldable parallel tasks are widely used in different areas, such as weather forecast, biocomputing, mechanical calculation, and so on. Considering the deadline and the speedup, scheduling moldable parallel tasks becomes a difficulty. Past work majorly focuses on the LA (List Algorithms) or OMA (Optimizing the Middle Algorithms). Different from prior work, our work normalizes execution time and makes all tasks have the same scope in normalized execution time: [0,1], and then according to the normalized execution time, a method is used to search for the reference execution time without considering the deadline of tasks. According to the reference execution time, we get an initial scheduling result based on AFCFS (Adaptive First Comes First Served) policy. Finally, a heuristic approach is used to improve the performance of the initial scheduling result. We call our method HSRET (a Heuristic Scheduling method based on Reference Execution Time). Comparisons to other methods show that HSRET has good performance in AWT (Average Waiting Time), AET (Average Execution Time), and PUT (Percentages of Unfinished Tasks).

• Journal of Korean Society of Transportation
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• v.35 no.4
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• pp.348-359
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• 2017

Recently, various public transportation activation policies are being implemented in order to mitigate traffic congestion in metropolitan areas. Especially in the metropolitan area, the bus information system has been introduced to provide information on the current location of the bus and the estimated arrival time. However, it is difficult to predict the travel time due to repetitive traffic congestion in buses passing through complex urban areas due to repetitive traffic congestion and bus bunching. The previous bus travel time study has difficulties in providing information on route travel time of bus users and information on long-term travel time due to short-term travel time prediction based on the data-driven method. In this study, the path based long-term bus travel time prediction methodology is studied. For this purpose, the training data is composed of 2015 bus travel information and the 2016 data are composed of verification data. We analyze bus travel information and factors affecting bus travel time were classified into departure time, day of week, and weather factors. These factors were used into clusters with similar patterns using self organizing map. Based on the derived clusters, the reference table for bus travel time by day and departure time for sunny and rainy days were constructed. The accuracy of bus travel time derived from this study was verified using the verification data. It is expected that the prediction algorithm of this paper could overcome the limitation of the existing intuitive and empirical approach, and it is possible to improve bus user satisfaction and to establish flexible public transportation policy by improving prediction accuracy.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.1
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• pp.56-73
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• 2019

Probe-based systems have been gaining popularity in advanced traveler information systems. However, the high possibility of providing inaccurate travel-time information due to the inherent time-lag phenomenon is still an important issue to be resolved. To mitigate the time-lag problem, different prediction techniques have been applied, but the techniques are generally regarded as less effective for travel times with high variability. For this reason, current 5-min aggregated data have been commonly used for real-time travel-time provision on highways with high travel-time fluctuation. However, the 5-min aggregation interval itself can further increase the time-lags in the real-time travel-time information equivalent to 5 minutes. In this study, a new scheme that uses both individual probe and 5-min aggregated travel times is suggested to provide reliable real-time travel-time information. The scheme utilizes individual probe data under congested conditions and 5-min aggregated data under uncongested conditions, respectively. As a result of an evaluation with field data, the proposed scheme showed the best performance, with a maximum reduction in travel-time error of 18%.

• Journal of Environmental Impact Assessment
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• v.20 no.2
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• pp.217-226
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• 2011

This paper was inspired by the fact that Real-time Traffic Information Service could play a key role in reducing incomplete combustion time remarkably since it can provide traffic jam information in real-time basis. Emission characteristics of experimental engines were studied with variable travel distances and speed of car in terms of traffic information provided. 12 Km distance road of Susung district in Daegu is taken as an experimental area to examine this new approach. The emission was tested while the driving was done at 8 AM, 3 PM, 6 PM which represents various traffic conditions. The reduced emission has been measured for a travel distance running at different loads (conventional shortest route and Real-time Traffic Information) and various loads (CO, VOC and NOx) are all inventoried and calculated in terms of existing emission factors. The emission has been shown to reduce linearly with travel distance : carbon monoxide (20.56%), VOC (29.21%), NOx(8.86%).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3112-3127
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• 2018

Since time series clustering is performed without prior information, it is used for exploratory data analysis. In particular, clusters of time series with similar shapes can be used in various fields, such as business, medicine, finance, and communications. However, existing time series clustering algorithms have a problem in that time series with different shapes are included in the clusters. The reason for such a problem is that the existing algorithms do not consider the limitations on the size of the generated clusters, and use a dimension reduction method in which the information loss is large. In this paper, we propose a method to alleviate the disadvantages of existing methods and to find a better quality of cluster containing similarly shaped time series. In the data preprocessing step, we normalize the time series using z-transformation. Then, we use piecewise aggregate approximation (PAA) to reduce the dimension of the time series. In the clustering step, we use density-based spatial clustering of applications with noise (DBSCAN) to create a precluster. We then use a modified K-means algorithm to refine the preclusters containing differently shaped time series into subclusters containing only similarly shaped time series. In our experiments, our method showed better results than the existing method.

• JSTS:Journal of Semiconductor Technology and Science
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• v.17 no.2
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• pp.252-259
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• 2017

In this paper, we propose a novel method for extracting an accurate depth of a trap that causes RTS(Random Telegraph Signal) noise. The error rates of the trap depth rely on the mean time constants and its ratio. Here, we determined how many data of the capture and emission time constant are necessary in order to reduce the trap depth error caused by an inaccurate mean time constant. We measured the capture and emission time constants up to 100,000 times in order to ensure that the samples had statistical meaning. As a result, we demonstrated that at least 1,000 samples are necessary to satisfy less than 10% error for trap depth. This result could be used to improve the accuracy of RTS noise analysis.