• Proceedings of KOSOMES biannual meeting
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• 2006.11a
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• pp.217-219
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• 2006

This study focused an water quality response to land-based pollution loads and the appropriate pollutant load reduction in Chinhae Bay using an eco-hydrodynamic model. Land-based discharge foam urban areas, industrial complex and sewage treatment plant was the greatest contributor to cause red-tide blooms and summer hypoxia. Tidal currents velocity af the ebb tide was about 10 cm/s stronger than that of the flood tide. A residual current was simulated to. have a slightly complicated pattern with ranging from 0.1 to. 2.7 cm/s. In Masan Bay, pollutant materials cannot flaw from the inner to the outer bay easily because af residual currents flaw southward at surface and northward at the bottom. The simulation results of COD distribution showedhigh concentrations aver 3 mg/L in the inner part of Masan Bay related pollutant discharge, and charge, and lower levels less than 1.5mg/L in the central part of Chinhae Bay. For improvement water quality in Chinhae Bay, it is necessary to reduce the organic and inorganic loads from paint sources by mare than 50% and ameliorate severe polluted sediment.

• Smart Structures and Systems
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• v.6 no.4
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• pp.373-388
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• 2010

The updated finite element model of K$\ddot{o}$m$\ddot{u}$rhan Highway Bridge on the Firat River located on the $51^{st}$ km of Elazi$\breve{g}$-Malatya highway is obtained by using analytical and experimental results. The 2D and 3D finite element model of the bridge is created by using SAP2000 structural analyses software, and the dynamic characteristics of the bridge are determined analytically. The experimental measurements are carried out by Operational Modal Analysis Method under traffic induced vibrations and the dynamic characteristics are obtained experimentally. The vibration data are gathered from the both box girder and the deck of the bridge, separately. Due to the expansion joint in the middle of the bridge, special measurement points are selected when experimental test setups constitute. Measurement duration, frequency span and effective mode number are determined by considering similar studies in literature. The Peak Picking method in the frequency domain is used in the modal identification. At the end of the study, analytical and experimental dynamic characteristic are compared with each other and the finite element model of the bridge is updated by changing some uncertain parameters such as material properties and boundary conditions. Maximum differences between the natural frequencies are reduced from 10% to 2%, and a good agreement is found between natural frequencies and mode shapes after model updating.

• Journal of Advanced Navigation Technology
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• v.21 no.1
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• pp.145-152
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• 2017

As a popularization of small UAS to have improved flight performance and easiness of controlling, the UAS industry is increased and also small UAS is to be a new threat for airspace security of national strategic infrastructure. Rising the new threat makes the negative side effect of small UAS operation. This phenomena brought to new R&D needs "defense system" for small UAS/UAV - called Anti-Drone. The paper addressed case study of defects, accidents and threats by small UAS/UAV as world wide level, and research and development trend of UAS defense system as each technical category - CONOP (Concept of Operation), identification/recognition method and control/supremacy techniques. As a result, this suggests the direction what and where drone defense system should be applied first and required for Korean society in the view of society system (regime) and a point of view for minimizing side effect as UAS popularization.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.3
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• pp.395-404
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• 2013

A pattern matching algorithm plays an important role in traffic identification and classification based on predefined patterns for intrusion detection and prevention. As attacks become prevalent and complex, current patterns are written using regular expressions, called regexes, which are expressed into the deterministic finite automata(DFA) due to the guaranteed worst-case performance in pattern matching process. Currently, because of the increased complexity of regex patterns and their large number, memory-efficient DFA from states reduction have become the mainstay of pattern matching process. However, most of the previous works have focused on reducing only the number of states on a single automaton, and thus there still exists a state blowup problem under the large number of patterns. To solve the above problem, we propose a new state compression algorithm that merges states on multiple automata. We show that by merging states with the same input character on multiple automata, the proposed algorithm can lead to a significant reduction of the number of states in the original DFA by as much as 40.0% on average.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.7
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• pp.378-388
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• 2000

In this paper, we propose Fuzzy Polynomial Neural Networks(FPNN) based on Polynomial Neural Networks(PNN) and Fuzzy Neural Networks(FNN) for model identification of complex and nonlinear systems. The proposed FPNN is generated from the mutually combined structure of both FNN and PNN. The one and the other are considered as the premise part and consequence part of FPNN structure respectively. As the consequence part of FPNN, PNN is based on Group Method of Data Handling(GMDH) method and its structure is similar to Neural Networks. But the structure of PNN is not fixed like in conventional Neural Networks and self-organizing networks that can be generated. FPNN is available effectively for multi-input variables and high-order polynomial according to the combination of FNN with PNN. Accordingly it is possible to consider the nonlinearity characteristics of process and to get better output performance with superb predictive ability. As the premise part of FPNN, FNN uses both the simplified fuzzy inference as fuzzy inference method and error back-propagation algorithm as learning rule. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using genetic algorithms. And we use two kinds of FNN structure according to the division method of fuzzy space of input variables. One is basic FNN structure and uses fuzzy input space divided by each separated input variable, the other is modified FNN structure and uses fuzzy input space divided by mutually combined input variables. In order to evaluate the performance of proposed models, we use the nonlinear function and traffic route choice process. The results show that the proposed FPNN can produce the model with higher accuracy and more robustness than any other method presented previously. And also performance index related to the approximation and prediction capabilities of model is evaluated and discussed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.6
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• pp.1365-1374
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• 2010

The maritime traffic is more complex these days. It is more hard for the small fishing ships to navigated in shores. The requirements for the navigate information system to protect the sea environments and support the small fishing ships are more increased. However, the Inmarsat communication system is too burden to the fishermen with the expensive terminal and call fees. We propose the wireless digital fishing information network which use the existing MF/HF SSB communications system by connecting I-PHONE, PDA, NetBook, Notebook, PC, etc with the PSK31 method and AIS(Automatic Identification System) on the MF/HF radio Band.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.4
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• pp.41-55
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• 1995

In this paper, an optimal idenfication method using fuzzy-neural networks is proposed for modeling of nonlinear complex systems. The proposed fuzzy-neural modeling implements system structure and parameter identification using the intelligent schemes together wlth optimization theory, linguistic fuzzy implication rules, and neural networks(NNs) from input and output data of processes. Inference type for this fuzzy-neural modeling is presented as simplified inference. To obtain optimal model, the learning rates and momentum coefficients of fuzzy-neural networks(FNNs) are tuned automatically using improved modified complex method and modified learning algorithm. For the purpose of its application to nonlinear processes, data for route choice of traffic problems and those for activateti sluge process of sewage treatment system are used for the purpose of evaluating the performance of the proposed fuzzy-neural network modeling. The results show that the proposed method can produce the intelligence model with higher accuracy than other works achieved previously.

• Journal of the Ergonomics Society of Korea
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• v.32 no.1
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• pp.59-68
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• 2013

Objective: The purpose of this paper is to introduce a task complexity model combining task design aspects and complexity dimensions and to explain an approach to identifying and organizing task complexity factors based on the model. Background: Task complexity is a critical concept in describing and predicting human performance in complex systems such as nuclear power plants(NPPs). In order to understand the nature of task complexity, task complexity factors need to be identified and organized in a systematic manner. Although several methods have been suggested for identifying and organizing task complexity factors, it is rare to find an analytical approach based on a theoretically sound model. Method: This study regarded a task as a system to be designed. Three levels of design ion, which are functional, behavioral, and structural level of a task, characterize the design aspects of a task. The behavioral aspect is further classified into five cognitive processing activity types(information collection, information analysis, decision and action selection, action implementation, and action feedback). The complexity dimensions describe a task complexity from different perspectives that are size, variety, and order/organization. Combining the design aspects and complexity dimensions of a task, we developed a model from which meaningful task complexity factors can be identified and organized in an analytic way. Results: A model consisting of two facets, each of which is respectively concerned with design aspects and complexity dimensions, were proposed. Additionally, twenty-one task complexity factors were identified and organized based on the model. Conclusion: The model and approach introduced in this paper can be effectively used for examining human performance and human-system interface design issues in NPPs. Application: The model and approach introduced in this paper could be used for several human factors problems, including task allocation and design of information aiding, in NPPs and extended to other types of complex systems such as air traffic control systems as well.

• Environmental Mutagens and Carcinogens
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• v.15 no.2
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• pp.131-139
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• 1995

Air suspedned particulates are the most serious factor among air pollutants in Seoul and their extracts have been revealed to be pulmonary carcinogenes. Air particulates were collected at a site representative of the high traffic area of Seoul from December 1993 to May 1994. Polycyclic aromatic hydrocarbons (PAHs) and nitroarenes in organic extracts of air particulates were determined by gas chromatography and mutagenicity of particle extracts was evaluated by the pre-incubation procedure with Salmonella typhirnurium TA98 and TA 98NR. The average concentration of total suspended particulates and inhalable (less than 10 $\mu$m) particulates were 169.63 $\mu g/m^3$, 141.92 $\mu g/m^3$, respectively. The relative contribution of organic matters was highest in neutral fraction and was lowest in basic fraction. Among identified 20 PAHs, the level of PAHs with 4-benzen ring i.e., pyrene, benzo(a)anthracene and chrysene were much higher than the PAHs with higher ring numbers. The mutagenicity of air particulates was much higher in the presence of rat liver microsomai fraction (S9 mixture) than that observed in its absence, which indicates that air particulates contained both direct and indirect mutagens. Nitroarenes in this study were not almost detected but mutagenicity of their fraction was higher. These results are represent to research for the identification of nitroarenes in the forward study.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.310-315
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• 2014

The domestic maritime environment shows higher frequency of maritime accidents amidst greater traffic volume arising from increasing international seaborne trade and maritime leisure activities. To reduce such maritime accidents, there exist various kinds of safety navigation devices in the ship bridge aimed to mitigate burdens of navigators and support their accurate decision making. Amongst is the AIS considered very important, which is an automatic tracking system to assist understanding of the circumstances in the vicinity by receiving information of other ships and also sending its own; where the information contains errors initially, however, such wrong information is periodically transmitted, accordingly giving rise to hindrance sometimes in decision making by shore operators or ship navigators at sea. This study is to propose the error data and field management algorithm using fuzzy theory toward improving reliability and accuracy in ship related information received from AIS.