• Journal of the Korea Society for Simulation
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• v.7 no.2
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• pp.125-136
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• 1998

To upgrade railway traffic density without any change of signal block length between stations on existing railway lines, a new signalling system of train control "the pattern control technique" is suggested. It needs very little change to computerize the cab signal using transponders. A computer simulation system is developed to experiment the new control method. The new signalling system shows much increase of the railway traffic efficiency. The train head-way time by the fixed signalling system and the new pattern control system is analyzed. The pattern control technique shows 35% increasement of trair operation under same condition of railway and trains.nd trains.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.6B
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• pp.1048-1058
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• 1999

This paper compares some architectures to achieve the optimized WDM architecture for all optical transport network, the comparison is presented in terms of the number of required wavelength and LT. These architecture types are PPWDM, SHWDM, DHWDM and fully optical WDM. Topology is a static ring network where the routing pattern is fixed and traffic pattern has uniform demand. This paper also proposes an algorithm for the wavelength assignment for a folly optical WDM ring network which has full mesh traffic pattern. The algorithm is based on heuristic algorithm which assigns traffic connections according to their respective shortest path. Traffic described here that is to be passed through can be routed directly within the optical layer instead of having the higher layer to handle it.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.4
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• pp.138-144
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• 2014

Now, Autonomous unmanned vehicle has become an issue in next generation technology. 2D Laser scanner as the distance measurement sensor is used. 2D Laser scanner detects the distance of 80m, measured angle is -5 to 185 degree. Laser scanner detects only the plane, but using motor swings. As a result, traffic signs detect and analyze patterns. Traffic signs when driving at low speed, shape of the detected pattern is very similar. By shaking the laser scanner, traffic signs and other obstacles became clear distinction.

• KNOM Review
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• v.24 no.1
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• pp.20-28
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• 2021

Extensive use of social media applications and mobile devices continues to increase data traffic. Social media applications generate an endless and massive amount of multimedia traffic, specifically video traffic. Many social media platforms such as YouTube, Daily Motion, and Netflix generate endless video traffic. On these platforms, only a few popular videos are requested many times as compared to other videos. These popular videos should be cached in the user vicinity to meet continuous user demands. MEC has emerged as an essential paradigm for handling consistent user demand and caching videos in user proximity. The problem is to understand how user demand pattern varies with time. This paper analyzes three publicly available datasets, MovieLens 20M, MovieLens 100K, and The Movies Dataset, to find the user request pattern over time. We find hourly, daily, monthly, and yearly trends of all the datasets. Our resulted pattern could be used in other research while generating and analyzing the user request pattern in MEC-based video caching scenarios.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1998.06a
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• pp.975-978
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• 1998

• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.19-28
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• 2015

In this paper, we proposed an algorithm for the identification of relieving or worsening current traffic congestion using historic traffic congestion patterns. Historical congestion patterns were placed in an adjacency list. The patterns were constructed to represent spatial and temporal length for status of a congested road. Then, we found information about historical traffic congestions that were similar to today's traffic congestion and will use that information to show how to change traffic congestion in the future. The most similar pattern to current traffic status among the historical patterns corresponded to starting section of current traffic congestion. One of our experiment results had average error when we compared identified changes of the congestion for one of the sections in the congestion road by using our proposal and real traffic status. The average error was 15 minutes. Another result was for the long congestion road consisting of several sections. The average error for this result was within 10 minutes.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.4
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• pp.268-276
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• 2015

A ship's sailing route or plan is determined by the master as the decision maker of the vessel, and depends on the characteristics of the navigational environment and the conditions of the ship. The trajectory, which appears as a result of the ship's navigation, is monitored and stored by a Vessel Traffic Service center, and is used for an analysis of the ship's navigational pattern and risk assessment within a particular area. However, such an analysis is performed in the same manner, despite the different navigational environments between coastal areas and the harbor limits. The navigational environment within the harbor limits changes rapidly owing to construction of the port facilities, dredging operations, and so on. In this study, a support vector machine was used for processing and modeling the trajectory data. A K-fold cross-validation and a grid search were used for selecting the optimal parameters. A complicated traffic route similar to the circumstances of the harbor limits was constructed for a validation of the model. A group of vessels was composed, each vessel of which was given various speed and course changes along a specified route. As a result of the machine learning, the optimal route and voyage data model were obtained. Finally, the model was presented to Vessel Traffic Service operators to detect any anomalous vessel behaviors. Using the proposed data modeling method, we intend to support the decision-making of Vessel Traffic Service operators in terms of navigational patterns and their characteristics.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.8
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• pp.1970-1975
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• 1996

The characteristics of data traffic on the Ethernet LAN are investigated on the basis of measurements. The analysis on the arrival pattern of packets on the network is found not to be a Poission process but to be Weibull distributions. An analysis of network traffic, packet arrivals are found to exhibit a 'source locality'. It is observed that file transfers are reponsible for about 92% of the traffic on the network. Our results will be useful for modelling purposes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1630-1636
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• 2022

The results of current method of traffic sign detection gets hindered by environmental conditions and the traffic sign's condition as well. Therefore, in this paper, we propose a method of improving detection performance of damaged traffic signs by utilizing Hopfield Network and Fuzzy Max-Min Neural Network. In this proposed method, the characteristics of damaged traffic signs are analyzed and those characteristics are configured as the training pattern to be used by Fuzzy Max-Min Neural Network to initially classify the characteristics of the traffic signs. The images with initial characteristics that has been classified are restored by using Hopfield Network. The images restored with Hopfield Network are classified by the Fuzzy Max-Min Neural Network onces again to finally classify and detect the damaged traffic signs. 8 traffic signs with varying degrees of damage are used to evaluate the performance of the proposed method which resulted with an average of 38.76% improvement on classification performance than the Fuzzy Max-Min Neural Network.

• Korean Journal of Hazardous Materials
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• v.6 no.2
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• pp.68-76
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• 2018

This study aims to provide a methodological framework to estimate the travel demand of hazardous materials transporting vehicles by link and analyze daily traffic patterns on an expressway to develop safety roadway management strategies. Traffic volume of hazardous material vehicles is counted through the on-site investigation at twenty-five tollgates on the expressway, and their demands by a link are predicted through origin-destination flows estimation. The result shows that the number of the domestic hazardous materials vehicles is approximately 51,207 vehicles per day and it indicates that hazardous materials transport vehicles account for 1.5% of total daily traffic on the internal expressway and 6.2% of total cargo traffic volumes. This study roughly estimated how many hazardous materials vehicles pass through the expressway segment. Thus it is expected to be utilized for establishing a systematic highway management strategy in the future by calculating the traffic volume of the hazardous material vehicles traveling on the interstate expressway.