• Journal of Korean Port Research
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• v.13 no.2
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• pp.313-322
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• 1999

Pusan the principal port of South Korea, has opened its door since 1876. Currently, the four-stage port construction project is under way to handle ever-growing marine transportation volume. While the port unloading capabilities are increasing the infrastructure to deal with all the transportation volume failed to catch up with them. Accordingly the city had to suffer from worst traffic congestion on due to the increasing container traffic volume causing logistical costs to rise. This study was designed to inspect the enforcement of infrastructure construction plan and suggest systematical and effective ways to improve the plan. The study focused on :\circled1The decision-making procedure, \circled2Financial resource for the plan, \circled3Effectiveness of the project enforcement, and \circled4Who will be in charge of the project. As a result from the study, these followings were suggested to improve the plan. First, Pusan Port Infrastructure consisting of (Inter-city Free way, Belt Highway and Outer Highway) should be immediately legally-regulation project. Second, the method to finance the project should be deter-mined and investment consultation among the central government the city government and private sector should be also made. Measures to make the central government budget allocation for the project mandatory should be discussed. Third, Effectiveness of the project can be doubled by gradually or partialyl opening the routes based on long-term or short-term operating plans. Fourth, The organizer of the project should be appointed, or a special task-force team in charge of the plan can be formed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5D
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• pp.485-496
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• 2010

An increase in number of vehicles owned by individuals worsens the conditions of parking in residential areas. So to speak, the pedestrians' safety is seriously threatened by illegally parked vehicles on the residential area roads. As a result, the number of vehicle-to-pedestrian accidents has been increasing annually. Also, illegal parking on arterial roads is increasingly becoming common, especially by cooommercial trucks. However, no solution has been found to reduce or eliminate accidents caused by vehicles illegally parked on readside. The result of this study provides the solutions to enhance the safety of residential area roads and arterial roads, from viewpoints of both long-term and short-term, by collecting data about the status of illegal parking and addressing critical problems.

• Journal of Communications and Networks
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• v.9 no.3
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• pp.265-273
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• 2007

This paper expands an analytical performance model of 802.11 to accurately estimate throughput and energy demand of 802.11-based wireless sensor network (WSN) when sensor nodes employ Reed-Solomon (RS) codes, one of block forward error correction (FEC) techniques. This model evaluates these two metrics as a function of the channel bit error rate (BER) and the RS symbol size. Since the basic recovery unit of RS codes is a symbol not a bit, the symbol size affects the WSN performance even if each packet carries the same amount of FEC check bits. The larger size is more effective to recover long-lasting error bursts although it increases the computational complexity of encoding and decoding RS codes. For applying the extended model to WSNs, this paper collects traffic traces from a WSN consisting of two TIP50CM sensor nodes and measures its energy consumption for processing RS codes. Based on traces, it approximates WSN channels with Gilbert models. The computational analyses confirm that the adoption of RS codes in 802.11 significantly improves its throughput and energy efficiency of WSNs with a high BER. They also predict that the choice of an appropriate RS symbol size causes a lot of difference in throughput and power waste over short-term durations while the symbol size rarely affects the long-term average of these metrics.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.169-176
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• 2021

Maritime monitoring requirements have been beyond human operators capabilities due to the broadness of the coverage area and the variety of monitoring activities, e.g. illegal migration, or security threats by foreign warships. Abnormal vessel movement can be defined as an unreasonable movement deviation from the usual trajectory, speed, or other traffic parameters. Detection of the abnormal vessel movement requires the operators not only to pay short-term attention but also to have long-term trajectory trace ability. Recent advances in deep learning have shown the potential of deep learning techniques to discover hidden and more complex relations that often lie in low dimensional latent spaces. In this paper, we propose a deep autoencoder-based clustering model for automatic detection of vessel movement anomaly to assist monitoring operators to take actions on the vessel for more investigation. We first generate gridded trajectory images by mapping the raw vessel trajectories into two dimensional matrix. Based on the gridded image input, we test the proposed model along with the other deep autoencoder-based models for the abnormal trajectory data generated through rotation and speed variation from normal trajectories. We show that the proposed model improves detection accuracy for the generated abnormal trajectories compared to the other models.

• ETRI Journal
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• v.39 no.4
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• pp.546-557
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• 2017

In a long term evolution-advanced (LTE-A) system, the traffic overload of machine type communication devices is a challenge because too many devices attempt to access a base station (BS) simultaneously in a short period of time. We discuss the challenge of the gap between the theoretical maximum throughput and the actual throughput. A gap occurs when the BS cannot change the number of preambles for a random access channel (RACH) until multiple numbers of RACHs are completed. In addition, a preamble partition approach is proposed in this paper that uses two groups of preambles to reduce this gap. A performance evaluation shows that the proposed approach increases the average throughput. For 100,000 devices in a cell, the throughput is increased by 29.7% to 114.4% and 23.0% to 91.3% with uniform and Beta-distributed arrivals of devices, respectively.

• Proceedings of the KOR-KST Conference
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• 1998.10a
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• pp.21-30
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• 1998

본 연구는 기존 구간 속도 예측기법의 고찰을 통하여 검지기에서 올라오는 교통제어변수를 이용하여 구간 속도 예측모형을 연구하는데 목적이 있다. 이를 위한 교통 제어변수로는 연속류 제어에서 통상적으로 사용되는 교통량, 점유율, 밀도, 속도 등을 사용한다. 공간적 범위로는 서울 올림픽대로의 17개의 영상 검지기 중 #3과 #16검지기에서 올라오는 속도, 점유율, 교통량 자료를 토대로 1998년 6월 11일 오전 7시부터 11시까지의 4시간동안 예측을 실시하며 Historical Traffic Pattern과 시험차량, 자동차 번호판 조사를 통한 구간 실측조사 자료를 토대로 예측을 위한 자료를 구축한다. 기존의 예측기법인 시계열 분석, 신경망 이론, 평활법과 칼만필터링을 고찰하였고, 가장 좋은 예측력을 보여주는 기법은 칼만필터링 모형이었다. 이를 토대로 Case Study를 통해 여러 구간의 다주기 예측을 통해 단기간(short-term)의 구간 속도를 예측하고 각 해당 검지기별 실측자료를 통해 비교분석을 실시하였다. 결과적으로 도출된 칼만필터링 모형의 다주기 예측을 통한 구간 통행속도의 예측이 기존의 구간 통행속도 산출 방법보다 더 나은 예측력을 보여주고 있다.

• Journal of the Korean Society for Railway
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• v.8 no.6 s.31
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• pp.602-609
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• 2005

In this paper, we consider the train-fleet assignment problem to determine fleet assignment and seat allocation synchronously. An integer programming model of the problem and a decomposition-based solution approach are developed to handle short-term period deterministic orgin-destination demands. The primary objective used in the developed model is to maximize the total number of passengers transported during peak load periods, such as Chuseok national holiday period. Thus, in developing the model we choose to profit-pursuing system. We also show how the proposed model can be readily modified to incorporate profit-maximization. Using the empirical data sets provided by a Korean railroad company, we have tested the proposed solution approach and carried out various comparison analyses by varying traffic demand patterns and train schedules. The computational experiments reveal that the proposed solutions approach produces high quality solutions in reasonable computation time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.1B
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• pp.38-47
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• 2008

The system test was accomplished in delivery time for a suitable of various requirements at the software market. Especially, critical faults must be detected and removed for a close main functions and users against target system. In generally, proposed test methods are executed with a calendar time, not a competitive and effectiveness method as selective software testing. These methods are inapplicable to short term test or early system development stage. Moreover, it's accompanied by heavy cost. Overcoming of these problems, must attempted to new software test method role of core function in the system test. Selective software testing method is decided to mixing with the three-information such as a frequency, complexity of use scenario and fault impact. Using this information, searching a fatal error and usefully system test for an executed test scenario. In this paper, we have proposed new test method and verified testing results for the detection of critical faults or search a fatal errors with a system main function.

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.199-209
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• 2008

This paper is described the concepts and limitations for the traditional directional design hour volume estimation. The main objective of this paper is to establish an estimation method of probabilistic directional design hour volume in order to improve the limitation for the traditional approach method. To express the traffic congestion of specific road segment, this paper proposed the link travel time as the probability that the road capacity can accommodate a certain traffic demand at desired service level. Also, the link travel time threshold was derived from chance-constrained stochastic model. Such successive probabilistic process could determine optimal ranked design hour volume and directional design hour volume. Therefore, the probabilistic directional design hour volume can consider the traffic congestion and economic aspect in road planning and design stage. It is hoped that this study will provide a better understanding of various issues involved in the short term prediction of directional design hourly volume on different types of roads.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.7
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• pp.297-306
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• 2017

Citizens want more accurate forecast information using Bus Information System. However, most bus information systems that use an average based short-term prediction algorithm include many errors because they do not consider the effects of the traffic flow, signal period, and halting time. In this paper, we try to improve the precision of forecast information by analyzing the influencing factors of the error, thereby making the convenience of the citizens. We analyzed the influence factors of the error using BIS data. It is shown in the analyzed data that the effects of the time characteristics and geographical conditions are mixed, and that effects on halting time and passes speed is different. Therefore, the halt time is constructed using Generalized Additive Model with explanatory variable such as hour, GPS coordinate and number of routes, and we used Hidden Markov Model to construct a pattern considering the influence of traffic flow on the unit section. As a result of the pattern construction, accurate real-time forecasting and long-term prediction of route travel time were possible. Finally, it is shown that this model is suitable for travel time prediction through statistical test between observed data and predicted data. As a result of this paper, we can provide more precise forecast information to the citizens, and we think that long-term forecasting can play an important role in decision making such as route scheduling.