• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.7
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• pp.3245-3250
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• 2011

This study introduces a threat level assessment model adapting Fuzzy theories in order to help make decisions for better covering quantitative factors and qualitative ones together. The threat is classified into three major categories - one resulting from navigational condition, another from target vessel specification and the other from external decision environment. The threat levels by each category are examined by a fuzzy inference, and its corresponding weights are assigned via fuzzy measures. Finally the high level threat measures become integrated via a Choquet Fuzzy Integral method into ultimate threat level indicators.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3230-3255
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• 2022

Causality mining in NLP is a significant area of interest, which benefits in many daily life applications, including decision making, business risk management, question answering, future event prediction, scenario generation, and information retrieval. Mining those causalities was a challenging and open problem for the prior non-statistical and statistical techniques using web sources that required hand-crafted linguistics patterns for feature engineering, which were subject to domain knowledge and required much human effort. Those studies overlooked implicit, ambiguous, and heterogeneous causality and focused on explicit causality mining. In contrast to statistical and non-statistical approaches, we present Bidirectional Encoder Representations from Transformers (BERT) integrated with Multi-level Feature Networks (MFN) for causality recognition, called BERT+MFN for causality recognition in noisy and informal web datasets without human-designed features. In our model, MFN consists of a three-column knowledge-oriented network (TC-KN), bi-LSTM, and Relation Network (RN) that mine causality information at the segment level. BERT captures semantic features at the word level. We perform experiments on Alternative Lexicalization (AltLexes) datasets. The experimental outcomes show that our model outperforms baseline causality and text mining techniques.

• Korea Journal of Hospital Management
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• v.11 no.4
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• pp.37-62
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• 2006

This study investigates the antecedents of knowledge sharing behavior focusing on the individual level factors in an assumption that the behavior is initiated from the individual level decisions. A hypothesis that the relation between personality trait and behavior is mediated by the social-cognitive constructs contained in the Theory of Planned Behavior(TPB) is tested. For the study, we suggest a TPB extended model that extends original TPB model by including conscientiousness facet of FFM(Five Factor Model). This study uses a cross-sectional design. Data were collected from a self-reported survey on 197 nurses in a tertiary hospital. The results showes a significant positive relationship between the conscientiousness facet of FFM and knowledge sharing behavior. In the TPB extended model, the conscientiousness facet has significant direct effects on all the constructs of original TPB model. Of the TPB exogenous constructs, the social norm construct alone has a significant effect on intention and the perceived behavioral has a direct significant effect on the knowledge sharing behavior. These results confirm the importance of conscientiousness in predicting knowledge sharing behavior and clarify the characteristics of knowledge sharing behavior as a contextual, job oriented behavior in a workplace. We conclude that personality trait as conceptualized in the FFM needs to be integrated into TPB model in explaining the knowledge sharing behavior. Based on these results theoretical and practical implications are discussed.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.137-149
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• 2019

Traffic emissions are the main cause of environmental pollution in cities and respiratory problems amongst people. This study developed a model based on an integration of support vector regression (SVR) algorithm and geographic information system (GIS) to map traffic carbon monoxide (CO) concentrations and produce prediction maps from micro level to macro level at a particular time gap in a day in a very densely populated area (Utara-Selatan Expressway-NKVE, Kuala Lumpur, Malaysia). The proposed model comprised two models: the first model was implemented to estimate traffic CO concentrations using the SVR model, and the second model was applied to create prediction maps at different times a day using the GIS approach. The parameters for analysis were collected from field survey and remote sensing data sources such as very-high-resolution aerial photos and light detection and ranging point clouds. The correlation coefficient was 0.97, the mean absolute error was 1.401 ppm and the root mean square error was 2.45 ppm. The proposed models can be effectively implemented as decision-making tools to find a suitable solution for mitigating traffic jams near tollgates, highways and road networks.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.2
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• pp.92-104
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• 2015

In order to analyze the impacts of climate change, a time and space integrated model was developed in this study using system dynamics and GIS. The model built was used to carry out a simulation on the inundation impact on A-gu of Busan Metropolitan city resulting from the sea level rise scenario of IPCC and storm surge, which is the worst case. Through this, the flooded area and population until 2100 were predicted. Also, the result and significance of each alternative was reviewed improving the model by establishing alternative scenarios of protection, accommodation and retreat as plans of reaction to sea level rise. The combination of system dynamics and GIS has advantages of how the diverse variables change until the target year can be traced and, accordingly, not only the results but also the processes of spatial change can be examined by calculating the value of change process at each time step. The synergy of this model presumed to be a foothold for solving problems which are becoming difficult to predict due to increase in uncertainty and complexity such as the support for decision making for urban resilience to natural disasters.

• Journal of Advanced Navigation Technology
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• v.22 no.2
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• pp.133-140
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• 2018

In recent years, model-based design techniques have been used as a way to support cost reduction and safety certification in the development of avionics systems. In order to support performance analysis and safety analysis of aircraft and avionics equipment (item) using model based design, we developed a multi-domain simulation environment that inter-works with heterogeneous simulators. We present a multi-domain simulation environment that can verify air data computers and integrated multi-function probes at the aircraft level. The model was developed by Simulink and the flight simulator X-Plane 10 was used to verify the model at the aircraft level. Avionics model functions were tested at the aircraft level and the air data errors of the model and flight simulator were measured within 0.1%.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.1
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• pp.165-172
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• 2017

Machines are physically or chemically degenerated by continuous usage. One of the results of this degeneration is the process mean shift. Under the process mean shift, production cost, failure cost and quality loss function cost are increasing continuously. Therefore a periodic preventive resetting the process is necessary. We suppose that the wear level is observable. In this case, process mean shift problem has similar characteristics to the maintenance policy model. In the previous studies, process mean shift problem has been studied in several fields such as 'Tool wear limit', 'Canning Process' and 'Quality Loss Function' separately or partially integrated form. This paper proposes an integrated cost model which involves production cost by the material, failure cost by the nonconforming items, quality loss function cost by the deviation between the quality characteristics from the target value and resetting the process cost. We expand this process mean shift problem a little more by dealing the process variance as a function, not a constant value. We suggested a multiplier function model to the process variance according to the analysis result with practical data. We adopted two-side specification to our model. The initial process mean is generally set somewhat above the lower specification. The objective function is total integrated costs per unit wear and independent variables are wear limit and initial setting process mean. The optimum is derived from numerical analysis because the integral form of the objective function is not possible. A numerical example is presented.

• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1614-1622
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• 2014

A novel equivalent flux sliding-mode observer (SMO) is proposed for dual three-phase interior permanent magnet synchronous motor (DT-IPMSM) drive system in this paper. The DT-IPMSM has two sets of Y-connected stator three-phase windings spatially shifted by 30 electrical degrees. In this method, the sensorless drive system employs a flux SMO with soft phase-locked loop method for rotor speed and position estimation, not only are low-pass filter and phase compensation module eliminated, but also estimation accuracy is improved. Meanwhile, to get the regulator parameters of current control, the inner current loop is realized using a decoupling and diagonal internal model control algorithm. Experiment results of 2MW-level DT-IPMSM drives system show that the proposed method has good dynamic and static performances.

• Journal of electromagnetic engineering and science
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• v.16 no.1
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• pp.44-51
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• 2016

A commercial $0.25{\mu}m$ GaN process is used to implement 6-18 GHz wideband power amplifier (PA) monolithic microwave integrated circuits (MMICs). GaN HEMTs are advantageous for enhancing RF power due to high breakdown voltages. However, the large-signal models provided by the foundry service cannot guarantee model accuracy up to frequencies close to their maximum oscillation frequency ($F_{max}$). Generally, the optimum output load point of a PA varies severely according to frequency, which creates difficulties in generating watt-level output power through the octave bandwidth. This study overcomes these issues by the development of in-house large-signal models that include a thermal model and by applying distributed L-C output load matching to reactive matched amplifiers. The proposed GaN PAs have successfully accomplished output power over 5 W through the octave bandwidth.

• Journal of Korean Society of Transportation
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• v.32 no.6
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• pp.675-685
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• 2014

This paper develops a differentiated pricing strategy over each segment of expressways based on the second-best pricing method for reducing congestion. To this end, a bi-level problem is proposed, in which the upper level of the model is formulated to determine toll level of each segment for minimizing traffic congestion, whereas the lower level of the model is formulated as a variable demand assignment problem. The sensitivity analysis based algorithm is took placed to find optimal solutions of upper level model. An application of the proposed model uses the modified Sioux-Falls network. The results show that the segment-based differentiated pricing strategy performs better than the existing uniform pricing strategy in reducing traffic congestion. This study can be applied as a demand management method to relieve disutility of excessively congested segments of expressways.