• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.8
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• pp.1045-1056
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• 1995

The purpose of multiple alarm processing is to give the operator the correct information and perception of the malfunction present in the plant. In this thesis, an APS(Alarm Processing System) is studied for fossil power plants. This APS is based on a cause-consequence trees in the knowledge representation aspect for alarm and plant and adapts alarm filtering methods using fired time information in the decision aspect. Through the cause-consequence trees and filtering methods, the Alarm Processing System finds the cause alarm among the fired multiple alarms and calculates the cause degree which represents the possibility of a fault occurring in the instruments of the plant with the information of fired alarm. The knowledge base is built via interviews and questionaries with the expert operators on the Seoul power plant unit 4. Finally, the validity of the studied APS is shown via simulations.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.3
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• pp.80-87
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• 1998

This paper presents and online scheme for fuzzy modelling of nonlinear systems, based on the model adjustment technique and the genetic algorithm technique. The fuzzy model is characterized by fuzzy "if-then" rules which represent locally linear input-output relations whose consequence parts are defined as subsystems of a nonlinear sysem. The discrete-time model for each subsystem is obtained to deal with initalization and unmeasurable signal problems in online estimation and the final output of the fuzzy model is computed from the outputs of the discrete-time models. Then, the parameters of both the premise and consequence parts of the fuzzy model are adjusted by a genetic algorithm. A set of simulation works is carried out to demonstrate the effectiveness of the proposed method.ed method.

• Asia-Pacific Journal of Business
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• v.4 no.1
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• pp.15-24
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• 2013

This paper traces the issue of key account management success which has regarded as a pressing concern of many companies' sales efforts at the organizational business-to-business context. Based on the extensive review of extant literatures, we introduced a theoretical framework that covers the antecedents and consequence of key account management success. We theorized the conditions under which organizational and relational factors influence the success of key account management approach. We endeavor to develop research propositions for each construct and provide necessary suggestions to isolate a platform for future empirical research. Beyond this span, an improved understanding from this framework will help developing policies for successful key account management approach.

• Steel and Composite Structures
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• v.14 no.4
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• pp.379-395
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• 2013

Aim of this paper is to apply to a steel truss bridge a methodology that takes into account the consequences of extreme loads on structures, focusing on the influence that the loss of primary elements has on the structural load bearing capacity. In this context, the topic of structural robustness, intended as the capacity of a structure to withstand damages without suffering disproportionate response to the triggering causes while maintaining an assigned level of performance, becomes relevant. In the first part of this study, a brief literature review of the topics of structural robustness, collapse resistance and progressive collapse takes place, focusing on steel structures. In the second part, a procedure for the evaluation of the structural response and robustness of skeletal structures under impact loads is presented and tested in simple structures. Following that, an application focuses on a case study bridge, the extensively studied I-35W Minneapolis steel truss bridge. The bridge, which had a structural design particularly sensitive to extreme loads, recently collapsed for a series of other reasons, in part still under investigation. The applied method aims, in addition to the robustness assessment, at increasing the collapse resistance of the structure by testing alternative designs.

• Journal of the Korean Society of Safety
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• v.30 no.6
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• pp.164-173
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• 2015

There exists required safety integrity level (SIL) to assure safety in accordance with international standards for every electrical / electronics / control equipment or systems with safety related functions. The SIL is allocated from lowest level (level 0) to highest level (level 4). In order to guarantee certain safety level that is internationally acceptable, application of methodology for SIL allocation and demonstration based on related international standards is required. However, application standard differs from every industry in domestic or international for application on mythology for allocation and demonstration of SIL. Application or assessment is not easy since absence on clear criteria or common definition. This research studied not only fundamental concept of SIL required to guarantee safety in accordance with international standards for safety related equipment and system, but different types of methodologies for SIL allocation. Specifically, SIL allocation for Platform Screen Door system of railway is studied applying methodology of severity of accidents and risk graph among different methodologies for SIL allocation.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.372-372
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• 2000

In this paper, we propose Neuro Fuzzy Polynomial Networks(NFPN) based on Polynomial Neural Network(PNN) and Neuro-Fuzzy(NF) for model identification of complex and nonlinear systems. The proposed NFPN is generated from the mutually combined structure of both NF and PNN. The one and the other are considered as the premise part and consequence part of NFPN structure respectively. As the premise part of NFPN, NF 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. As the consequence part of NFPN, 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. NFPN is available effectively for multi-input variables and high-order polynomial according to the combination of NF with PNN. Accordingly it is possible to consider the nonlinearity characteristics of process and to get better output performance with superb predictive ability. In order to evaluate the performance of proposed models, we use the nonlinear function. The results show that the proposed FPNN can produce the model with higher accuracy and more robustness than any other method presented previously.

• ETRI Journal
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• v.37 no.6
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• pp.1231-1241
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• 2015

In this study, we investigate the relationship between emotions and the physiological responses, with emotion recognition, using the proposed fuzzy information granulation-based neural network (FIGNN) for boredom, pain, and surprise emotions. For an analysis of the physiological responses, three emotions are induced through emotional stimuli, and the physiological signals are obtained from the evoked emotions. To recognize the emotions, we design an FIGNN recognizer and deal with the feature selection through an analysis of the physiological signals. The proposed method is accomplished in premise, consequence, and aggregation design phases. The premise phase takes information granulation using fuzzy c-means clustering, the consequence phase adopts a polynomial function, and the aggregation phase resorts to a general fuzzy inference. Experiments show that a suitable methodology and a substantial reduction of the feature space can be accomplished, and that the proposed FIGNN has a high recognition accuracy for the three emotions using physiological signals.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.14 no.4
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• pp.423-434
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• 2016

The importance of severe nuclear accidents and probabilistic safety assessment (PSA) were brought to international attention with the occurrence of severe nuclear accidents caused by the extreme natural disaster at Fukushima Daiichi nuclear power plant in Japan. In Korea, studies on level 3 PSA had made little progress until recently. The code systems of level 3 PSA, MACCS2 (MELCORE Accident Consequence Code System 2, US), COSYMA (COde SYstem from MAria, EU) and OSCAAR (Off-Site Consequence Analysis code for Atmospheric Releases in reactor accidents, JAPAN), were reviewed in this study, and the disadvantages and limitations of MACCS2 were also analyzed. Experts from Korea and abroad pointed out that the limitations of MACCS2 include the following: MACCS2 cannot simulate multi-unit accidents/release from spent fuel pools, and its atmospheric dispersion is based on a simple Gaussian plume model. Some of these limitations have been improved in the updated versions of MACCS2. The absence of a marine and aquatic dispersion model and the limited simulating range of food-chain and economic models are also important aspects that need to be improved. This paper is expected to be utilized as basic research material for developing a Korean code system for assessing off-site consequences of severe nuclear accidents.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.8
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• pp.561-570
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• 2004

In this paper, new architectures and comprehensive design methodologies of Genetic Algorithms(GAs) based Genetically optimized Neurofuzzy Networks(GoNFN) are introduced, and a series of numeric experiments are carried out. The proposed GoNFN is based on the rule-based Neurofuzzy Networks(NFN) with the extended structure of the premise and the consequence parts of fuzzy rules being formed within the networks. The premise part of the fuzzy rules are designed by using space partitioning in terms of fuzzy sets defined in individual variables. In the consequence part of the fuzzy rules, three different forms of the regression polynomials such as constant, linear and quadratic are taken into consideration. The structure and parameters of the proposed GoNFN are optimized by GAs. GAs being a global optimization technique determines optimal parameters in a vast search space. But it cannot effectively avoid a large amount of time-consuming iteration because GAs finds optimal parameters by using a given space. To alleviate the problems, the dynamic search-based GAs is introduced to lead to rapidly optimal convergence over a limited region or a boundary condition. In a nutshell, the objective of this study is to develop a general design methodology o GAs-based GoNFN modeling, come up a logic-based structure of such model and propose a comprehensive evolutionary development environment in which the optimization of the model can be efficiently carried out both at the structural as well as parametric level for overall optimization by utilizing the separate or consecutive tuning technology. To evaluate the performance of the proposed GoNFN, the models are experimented with the use of several representative numerical examples.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.3
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• pp.585-592
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• 2017

Most sewer lines buried in the city are likely to be collapsed due to serious aging. Also, due to the high concentration of development and high population density and traffic, the collapse of the sewer will cause enormous social and economic damage. Therefore, proactive maintenance is required to prevent accidents caused by deteriorated sewer pipe. In order to utilize limited budget effectively, risk-based prioritization methods should be proposed that simultaneously consider the consequence of failure and the probability of failure. In this study, the method of risk-based prioritization of sewer was examined by reviewing various cases of overseas studies and applied to the urban sub-catchment. First, the impact factors that can be secured through the sewer GIS DB in Seoul were derived, and the weight, sub-criteria, and impact score of each impact factor were determined and the consequence of failure was calculated by weight sum method. In addition, the probability of failure was calculated by dividing the service life by the estimated useful life, and the consequence of failure and the probability of failure were classified into five grades by the Jenks natural breaks classification method. The prioritization method was applied to sub-catchment in the Seoul to derive a risk matrix and a risk grade. As a result, 26% of all subjects were selected as the inspection priority subjects with 4-5 risk grade. Therefore, using the risk-based CCTV prioritization methodology, it will be possible to systematically determine the objects that need investigation first.