• Review of KIISC
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• v.26 no.6
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• pp.42-50
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• 2016

Critical infrastructure (CI) such as the electrical grid, transportation systems and water resource systems are controlled by Industrial Control and SCADA (Supervisory Control and Data Acquisition) networks. During the last few years, cyber attackers have increasingly targeted such CI systems. This is of great concern because successful attacks have wide ranging impact and can cause widespread destruction and loss of life. As a result, there is a critical requirement to develop enhanced algorithms and tools to detect cyber threats for SCADA networks. Such tools have key differences with the tools utilized to detect cyber threats in regular IT networks. This paper discusses key factors which differentiate network security for SCADA networks versus regular IT networks. The paper also presents various approaches used for SCADA security and some of the advancements in the area.

• ETRI Journal
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• v.5 no.2
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• pp.17-28
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• 1983

This paper deals with the problem of optimally controlling traffic flows in urban transportation traffic networks. For this, a nonlinear discrete-time model of urban traffic network is first suggested in order to handle the phenomenon of traffic flows such as oversaturatedness and/or undersaturatedness. Then an optimal control problem is formulated and a hierarchical optimization technique is applied, which is based upon a prediction-type two-level method of Hirvonen and Hakkala.

• Earthquakes and Structures
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• v.26 no.2
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• pp.87-96
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• 2024

This paper proposes a logistic multinomial regression approach to model the spatial cross-correlation of damage probabilities among different damage states in an expanded transportation network. Utilizing Bayesian theory and the multinomial logistic model, we analyze the damage states and probabilities of bridges while incorporating damage correlation. This correlation is considered both between bridges in a network and within each bridge's damage states. The correlation model of damage probabilities is applied to the seismic assessment of a portion of Tehran's transportation network, encompassing 26 bridges. Additionally, we introduce extra daily traffic time (EDTT) as an operational parameter of the transportation network and employ the shortest path algorithm to determine the path between two nodes. Our results demonstrate that incorporating the correlation of damage probabilities reduces the travel time of the selected network. The average decrease in travel time for the correlated case compared to the uncorrelated case, using two selected EDTT models, is 53% and 71%, respectively.

• Transportation Technology and Policy
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• v.12 no.2
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• pp.13-20
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• 2015

• Journal of Korean Society of Transportation
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• v.17 no.2
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• pp.127-135
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• 1999

Most existing progression bandwidth models maximize the single or multi weighted sum of bandwidths in the both directions to improve traffic mobility on an arterial, but they cannot be applied to general networks. Even though a few models formulating a looped network problem cannot be applied to networks have not loops. Also they have some defects in optimizing phase sequences. Therefore, the objective of this study is to develope a mathematical formulation of the synchronization problem for a general traffic network. The goal is achieved successfully by introducing the signal phasing for each movement and expanding the mixed integer linear programming of MAXBAND. The experiments indicate that the proposed model can formulate the general traffic network problem mere efficiently than any other model. In conclusion, this model may optimize signal time to smooth progression in the general networks.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.565-567
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• 2022

질병을 앓고 있는 환자는 상태에 따라 병실, 주거지, 요양원 등 조호환경 내 생활 시 의료 인력의 지속적인 추적 및 관찰을 통해 신체에 이상이 생긴 경우 이를 감지하고, 신속하게 조치할 수 있도록 해야 한다. 의료 인력이 직접 환자를 확인하는 방법은 의료 인력의 반복적인 노동이 요구되며 실시간으로 환자를 확인해야 한다는 특성상 의료 인력이 상주해야 하기에 이는 곧, 의료 인력의 부족과 낭비로 이어진다. 해당 문제 해결을 위해 의료 인력을 대신하여 조호환경 내 환자의 상태를 실시간으로 모니터링할 수 있는 딥러닝 모델들이 연구되고 있다. 딥러닝 모델은 데이터의 수가 많을수록 강인한 모델을 설계할 수 있으며, 데이터셋의 배경, 객체의 특징 분포 등 다양한 조건에 영향을 받기 때문에 학습에 필요한 도메인을 가지는 많은 양의 전처리된 데이터를 수집해야 한다. 따라서, 조호환경 내 환자에 대한 데이터셋이 필요하지만, 공개된 데이터셋의 경우 양이 매우 적으며 이를 반전, 회전기법 등을이용할 경우 데이터의 수를 늘릴 수 있지만, 같은 분포의 특징을 가지는 데이터가 생성되기에 데이터 증강 기법을 단순하게 적용하면 딥러닝 모델의 과적합을 야기한다. 또한, 조호환경 내 이미지 데이터셋은 얼굴 노출과 같은 개인정보가 포함 될 수 있으며 이를 보호하기 위해 정보들을 비식별화 해야 한다는 문제점이 있다. 따라서 본 논문에서는 조호환경에서 수집된 데이터 증강을 위한 Style-Generative Adversarial Networks 기법을 적용하여 조호환경 데이터셋 수집에 효과적인 증강 기법을 제안한다.

• Journal of Korean Society of Transportation
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• v.12 no.3
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• pp.29-47
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• 1994

Although subway system continues to be the backbone of transportation systems in a city like Seoul, there will still be areas across the city where subway services are not avaliable. Interest has steadily grown to fill this missing routes in overall urban transportation system. Light Rail Transit (L.R.T) system has been recently thought to be an appropriate mode of transportation by businessmen, professionals and transportation industry. In this regards, the purpose of this study is to explore whether L.R.T can be a feasible form of urban rail mode in the context of Seoul. First, the study develops the mathematical models to derive optimum route networks and stations. Integer Programming is employed to determine whether alternative routes are financially viable from the viewpoint of revenue maximization principles. Second, mathematical models developed are applied to Yoido area in order to examine the validity of model structures. The models constructed turns out be capable of handling alternative routes and stations. Application of models are successfully carried out to derive financially feasible set of routes and stations.

• Proceedings of the KOR-KST Conference
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• 1994.10b
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• pp.5-23
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• 1994

• Proceedings of the KOR-KST Conference
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• 1999.10a
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• pp.53-58
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• 1999

• Proceedings of the KOR-KST Conference
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• 1995.05b
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• pp.252-272
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• 1995