• Journal of the Korean Professional Engineers Association
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• v.37 no.4
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• pp.43-47
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• 2004

The unanimous of adoption of the intergovernmental agreement on the Asian Highway network by 32 member countries was a significant event and the Asian Highway project has entered into a new phase with a giant momentum. In an era of globalization, the availability of transport linkages and services is a prerequistite for countries to fully participate in the globalizing economy. The Asian Highway is one of initiatives of ESCAP to promote international transport in the region. With a total coverage of over 140,000kilometers, the asian highway network will be playing a vital role in bringing peoples together through both trade and travel.

• Annual Conference on Human and Language Technology
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• 2017.10a
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• pp.159-162
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• 2017

Long Short-Term Memory Recurrent Neural Network(LSTM RNN)는 순차 데이터 모델링에 적합한 딥러닝 모델이다. Bidirectional LSTM RNN(BiLSTM RNN)은 RNN의 그래디언트 소멸 문제(vanishing gradient problem)를 해결한 LSTM RNN을 입력 데이터의 양 방향에 적용시킨 것으로 입력 열의 모든 정보를 볼 수 있는 장점이 있어 자연어처리를 비롯한 다양한 분야에서 많이 사용되고 있다. Highway Network는 비선형 변환을 거치지 않은 입력 정보를 히든레이어에서 직접 사용할 수 있게 LSTM 유닛에 게이트를 추가한 딥러닝 모델이다. 본 논문에서는 Highway Network를 한국어 의미역 결정에 적용하여 기존 연구 보다 더 높은 성능을 얻을 수 있음을 보인다.

• 한국어정보학회:학술대회논문집
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• 2017.10a
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• pp.159-162
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• 2017

Long Short-Term Memory Recurrent Neural Network(LSTM RNN)는 순차 데이터 모델링에 적합한 딥러닝 모델이다. Bidirectional LSTM RNN(BiLSTM RNN)은 RNN의 그래디언트 소멸 문제(vanishing gradient problem)를 해결한 LSTM RNN을 입력 데이터의 양 방향에 적용시킨 것으로 입력 열의 모든 정보를 볼 수 있는 장점이 있어 자연어처리를 비롯한 다양한 분야에서 많이 사용되고 있다. Highway Network는 비선형 변환을 거치지 않은 입력 정보를 히든레이어에서 직접 사용할 수 있게 LSTM 유닛에 게이트를 추가한 딥러닝 모델이다. 본 논문에서는 Highway Network를 한국어 의미역 결정에 적용하여 기존 연구 보다 더 높은 성능을 얻을 수 있음을 보인다.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1014-1019
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• 2005

In this paper, a neural network technique for automatic steering control of a four wheel drive autonomous highway snowplow vehicle is presented. Controllers are designed by the LQR method based on the vehicle model. Then, neural network is used as an auxiliary controller to minimize lateral tracking error under the presence of load. Simulation studies of LQR control and neural network control are conducted for the vehicle model under a virtual snowplowing situation. Tracking performances are also compared for two and four wheeled steering vehicles.

• Journal of the Korea Society for Simulation
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• v.27 no.4
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• pp.9-18
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• 2018

This paper proposes new algorithms of accessibility indices to analyze the connectivity of the Korean highway network. First of all, we find a transportation network that presents Korea's highway network in graphs in 2011 and 2017. And we analyze and compare the nation's highway network in 2011 and 2017 using concepts such as associated number, the relative distance, the accessibility, the degree of connectivity, the index of dispersion, the diameter of graph theory. To do this, an algorithm is presented which can easily obtain various accessibility indices from a given transportation network. Using the simulation results of this study, we can find city that is the center of traffic in the highway transportation network. In addition, cities that are included in the network but are relatively underdeveloped can be found and used as basic data for enhancing the connectivity of the nationwide traffic in the future. Moreover, the proposed algorithms of accessibility indices, which are modeled on highway transport networks, can help identify the accessibility space structure of each city and provide criteria for efficient and reasonable selection of alternatives in various regional planning processes, including transportation.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.85-91
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• 2021

Some sections of the highway are closed due to disasters and accidents. In this situation, it analyzes what kind of situation occurs due to functional failure in the highway network. The domestic highway network can be expressed as a graph. Blocking some sections of the highway can turn into a national disaster. In this paper, we analyze the robustness of the domestic highway network. The robustness of expressways refers to the degree to which the traffic conditions of the domestic expressway network deteriorate due to the blockage of some sections. The greater the robustness, the smaller the effect of some blocking appears. This study is used to evaluate the congestion level of one section of the transportation network, and a value obtained by dividing the section traffic volume (V) by the section traffic volume (C) is used. This study analyzes the robustness of highways by using the actual traffic volume data of the departure and arrival points of domestic highways, and analyzes the changes in traffic volume due to partial blockage through experimental calculations. Although this analysis cannot reflect the exact reality of domestic highways, it is judged to be sufficient for the purpose of confirming the basic robustness of the overall network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5669-5684
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• 2018

The new mobile edge network architecture has been required for an increasing amount of traffic, quality requirements, advanced driver assistance system for autonomous driving and new cloud computing demands on highway. This article proposes a hierarchical cloud computing architecture to enhance performance by using adaptive data load distribution for buses that play the role of edge computing server. A vehicular dynamic cloud is based on wireless architecture including Wireless Local Area Network and Long Term Evolution Advanced communication is used for data transmission between moving buses and cars. The main advantages of the proposed architecture include both a reduction of data loading for top layer cloud server and effective data distribution on traffic jam highway where moving vehicles require video on demand (VOD) services from server. Through the description of real environment based on NS-2 network simulation, we conducted experiments to validate the proposed new architecture. Moreover, we show the feasibility and effectiveness for the connected car media service on highway.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1759-1772
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• 2023

Chinese named entity recognition (NER) is a challenging work that seeks to find, recognize and classify various types of information elements in unstructured text. Due to the Chinese text has no natural boundary like the spaces in the English text, Chinese named entity identification is much more difficult. At present, most deep learning based NER models are developed using a bidirectional long short-term memory network (BiLSTM), yet the performance still has some space to improve. To further improve their performance in Chinese NER tasks, we propose a new NER model, IDCNN-BiLSTM-Highway, which is a combination of the BiLSTM, the iterated dilated convolutional neural network (IDCNN) and the highway network. In our model, IDCNN is used to achieve multiscale context aggregation from a long sequence of words. Highway network is used to effectively connect different layers of networks, allowing information to pass through network layers smoothly without attenuation. Finally, the global optimum tag result is obtained by introducing conditional random field (CRF). The experimental results show that compared with other popular deep learning-based NER models, our model shows superior performance on two Chinese NER data sets: Resume and Yidu-S4k, The F1-scores are 94.98 and 77.59, respectively.

• Journal of Korea Multimedia Society
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• v.16 no.2
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• pp.180-189
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• 2013

The SMART Highway project combines road construction with advanced technology and vehicle telecommunications. Its expected outcome is a world-leading intelligent road that is green, fast, and comfortable. A vehicular ad-hoc network(VANET) is the core technology of the SMART Highway, whose transport operation is based on road vehicles. The VANET is a next-generation networking technology that enables wireless communication between vehicles or between vehicles and a road side unit(RSU). In the VANET system, a vehicle accident is likely to cause a serious disaster. Therefore, some information on safety is essential to serve as the key exchange protocol for communication between vehicles. However, the key exchange scheme of the general network proposed for a fast-moving communication environment is unsuitable for vehicles. In this paper, communication between multiple vehicles more efficient and secure key exchange at the vehicle certification by signcryption is proposed.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.18-24
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• 2022

State highway agencies (SHAs) typically apply a competitive procurement procedure to select contractors for their design-bid-build projects. Since the level of competition affects construction bid prices and project outcomes, the Federal Highway Agency (FHWA) suggests SHAs seek ways to improve competition among contractors continuously. However, they rarely conduct an empirical assessment of the current competition level necessary to identify room for improvement. Besides the number of bidders on a project, other factors such as winning or losing rates among the contractors in previous projects can also indicate the degree of competition; only a few contractors may have won the majority of the projects in a specific region. However, few studies have investigated such factors. This paper proposes a network analysis-based approach to evaluating contractor competition levels of highway projects using historical bid tabulation data. The proposed method provides insights into overall competition levels, the determination of competitive contractors, and winning rate distribution among contractors.