• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.6
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• pp.4137-4146
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• 2015

The scale and required functionality of modern systems have increased and become more complicated. To successfully carry out the systems development projects, appropriate systems engineering (SE) and project management (PM) activities are required for the underlying process. In a system development organization, it is an effort to secure the SE & PM capability by adopting the CMMI is an evaluation model of improvement and ability of SE&PM process. To achieve the goal each organization establishes and uses its own organizational standard process, which satisfies the business characteristics. However, in practice, due to the lack of sufficient understanding on the interrelationship among different CMMI process areas, there still exist some difficulties with constructing organization processes. In systems development, the activities of SE are closely related with those of PM. Thus, the processes of SE and PM need to be fully integrated and explicitly linked to each other in order to complete the projects successfully. In this paper, we propose a SE&PM integration process architecture of organization that can be utilized in the system development organization is referenced in the construction of CMMI-based organizational process.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.648-652
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• 2017

The industrial network policies of a country play an important role in both present and future economic development. This network is very important for the development of Korea. This paper employs a model for the Korean Network.Section 2 identifies network theory as a theoretical background. Additionally, the process model for the network is developed. In the third section, research methods are detailed. In section 4, a network model based on the industrial estate with regard to innovation networks is formed. Finally, limitations of the study and the conclusions are discussed.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.2
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• pp.152-159
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• 2005

This paper describes the application of a model-based system design method critical to complex intelligent systems, PSARE, to a welding robot development to define its top level architecture. The PSARE model consists of requirement model which describes the core processes(function) of the system, enhanced requirement model which adds technology specific processes to requirement model and allocates them to architecture model, and architecture model which describes the structure and interfaces and flows of the modules of the system. This paper focuses on the detailed procedure and method rather than the detailed domain model of the welding robot. In this study, only the top level architecture of a welding robot was defined using the PSARE method. However, the method can be repeatedly applied to the lower level architecture of the robot until the process which the robot should perform can be clearly defined. The enhanced data flow diagram in this model separates technology independent processes and technology specific processes. This approach will provide a useful base not only for improvement of a class of welding robots but also for development of increasingly complex intelligent real-time systems.

• Nuclear Engineering and Technology
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• v.54 no.2
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• pp.644-652
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• 2022

During the pyroprocessing operation, various signals can be collected by process monitoring (PM). These signals are utilized to diagnose process states. In this study, feasibility of using PM for nuclear safeguards of electrorefining operation was examined based on the use of machine learning for detecting off-normal operations. The off-normal operation, in this study, is defined as co-deposition of key elements through reduction on cathode. The monitored process signal selected for PM was cathode potential. The necessary data were produced through electrodeposition experiments in a laboratory molten salt system. Model-based cathodic surface area data were also generated and used to support model development. Computer models for classification were developed using a series of recurrent neural network architectures. The concept of transfer learning was also employed by combining pre-training and fine-tuning to minimize data requirement for training. The resulting models were found to classify the normal and the off-normal operation states with a 95% accuracy. With the availability of more process data, the approach is expected to have higher reliability.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.1
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• pp.33-38
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• 2006

In this paper, we propose a new architecture of Fuzzy Polynomial Neural Networks(FPNN) by means of genetically optimized Fuzzy Polynomial Neuron(FPN) and discuss its comprehensive design methodology involving mechanisms of genetic optimization, especially Genetic Algorithms(GAs). The conventional FPNN developed so far are based on mechanisms of self-organization and evolutionary optimization. The design of the network exploits the extended Group Method of Data Handling(GMDH) with some essential parameters of the network being provided by the designer and kept fixed throughout the overall development process. This restriction may hamper a possibility of producing an optimal architecture of the model. The proposed FPNN gives rise to a structurally optimized network and comes with a substantial level of flexibility in comparison to the one we encounter in conventional FPNNs. It is shown that the proposed advanced genetic algorithms based Fuzzy Polynomial Neural Networks is more useful and effective than the existing models for nonlinear process. We experimented with Medical Imaging System(MIS) dataset to evaluate the performance of the proposed model.

• Journal of Biosystems Engineering
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• v.43 no.3
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• pp.229-236
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• 2018

Purpose: Makgeolli is a traditional alcoholic beverage made from rice with a fermentation starter called "nuruk." The concentration of alcohol in makgeolli depends on the temperature of the fermentation tank. It is important to monitor the alcohol concentration to manage the makgeolli production process. Methods: Data were collected from 84 makgeolli fermentation tanks over a year period. Independent variables included the temperatures of the tanks and the room where the tanks were located, as well as the quantity, acidity, and water concentration of the source. Software for the multilayer perceptron model (MLP) was written in Python using the Scikit-learn library. Results: Many models were created for which the optimization converged within 100 iterations, and their coefficients of determination $R^2$ were considerably high. The coefficient of determination $R^2$ of the best model with the training set and the test set were 0.94 and 0.93, respectively. The fact that the difference between them was very small indicated that the model was not overfitted. The maximum and minimum error was approximately 2% and the total MSE was 0.078%. Conclusions: The MLP model could help predict the alcohol concentration and to control the production process of makgeolli. In future research, the optimization of the production process will be studied based on the model.

• Journal of Powder Materials
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• v.28 no.6
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• pp.478-482
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• 2021

The effect of the process conditions of high-velocity oxygen fuel (HVOF) thermal spray coating on the porosity of the coating layer is investigated. HVOF coating layers are formed by depositing amorphous FeMoCrBC powder. Oxygen pressure varies from 126 to 146 psi and kerosene pressure from 110 to 130 psi. The Microstructural analysis confirms its porosity. Data analysis is performed using experimental data. The oxygen pressure-kerosene pressure ratio is found to be a key contributor to the porosity. An empirical model is proposed using linear regression analysis. The proposed model is then validated using additional test data. We confirm that the oxygen pressure-kerosene pressure ratio exponentially increases porosity. We present a porosity prediction model relationship for the oxygen pressure-kerosene pressure ratio.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2004.08a
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• pp.175-183
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• 2004

In hot strip rolling, a capability for precisely predicting roll force is crucial for sound process control. In the past, on-line prediction models have been developed mostly on the basis of Orowan's theory and its variation. However, the range of process conditions in which desired prediction accuracy could be achieved was rather limited, mainly due to many simplifying assumptions inherent to Orowan's theory. As far as the prediction accuracy is concerned, a rigorously formulated finite element(FE) process model is perhaps the best choice. However, a FE process model in general requires a large CPU time, rendering itself inadequate for on-line purpose. In this report, we present a FE-based on-line prediction model applicable to precision process control in a finishing mill(FM). Described was an integrated FE process model capable of revealing the detailed aspects of the thermo-mechanical behavior of the roll-strip system. Using the FE process model, a series of process simulation was conducted to investigate the effect of diverse process variables on some selected non-dimensional parameters characterizing the thermo-mechanical behavior of the strip. Then, it was shown that an on-line model for the prediction of roll force could be derived on the basis of these parameters. The prediction accuracy of the proposed model was examined through comparison with measurements from the hot strip mill.

• Journal of Technology Innovation
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• v.13 no.1
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• pp.247-263
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• 2005

Prior research in R8ED innovation in Korea has been centered around the 'three-stage development model,' which hypothesizes that the Korean innovation process goes from the introduction (of foreign technology) stage, through assimilation stage to the final modification stage. As Korean economy shifts from traditional industry-led development to innovation-centric development, such an approach loses sight of the whole picture. The current study argues that a new framework is required for adequate analysis on newly arising innovative patterns in Korea, emphasizing source technology development and technology leader strategy. For this purpose, we propose the 'Jigsaw Puzzle Model' of technology development, which is then verified by an in-depth analysis on the innovation processes of 3 representative IT products of Korea, DRAM, TH LCD, and CDMA. The model suggests that Korean innovation model is a dynamic, efficient amalgamation of foreign-acquired and dependent technologies, based on internally accumulated technological resources. The model explains better how Korean firms are achieving a rapid catch-up of technological gaps with advanced nations and are able to transfer from the technology follower to the leader position.

• Journal of the Korea Institute of Building Construction
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• v.13 no.2
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• pp.159-168
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• 2013

Construction projects have become increasingly complex in recent years, resulting in substantial safety hazards and frequent fall accidents. In an attempt to prevent fall accidents, various safety management systems have been developed. These systems have mainly been evaluated qualitatively and subjectively by practitioners or supervisors, and there are few tools that can be used to quantitatively evaluate the performance of safety management systems. We propose an expertise-based safety performance evaluation model (EXSPEM), which integrates a fuzzy approach-based analytic hierarchy process and a regression approach. The proposed model uses S-shaped curves to represent the degree of contribution by subjective expertise and is verified by a genetic algorithm. To illustrate its practical application, EXSPEM was applied to evaluate the safety performance of a newly developed real-time mobile detector monitoring system. It is expected that this model will be a helpful tool for systematically evaluating the application of a robust safety control and management system in a complex construction environment.