• KEPCO Journal on Electric Power and Energy
• /
• v.5 no.3
• /
• pp.165-171
• /
• 2019

The steam turbine used in nuclear power plant is modeled for the purpose of verification of control system rather than the operator education. The valves, reheater and generator are modeled also and integrated into the simulator. After that, the operation data and the designed data such as heat balance diagram are utilized to identify the model parameters. It was evident that model outputs of developed simulator are very close to the measured operating ones. The simulator within dynamic model was used to verify and validate the whole control system together with field instruments. And the target plant has been operating long time.

• Structural Engineering and Mechanics
• /
• v.34 no.4
• /
• pp.525-539
• /
• 2010

Polymer matrix composites are widely used in many engineering applications as they can be customized to meet a desired performance while not only maintaining low cost but also reducing weight. Polymers can experience viscoelastic-viscoplastic response when subjected to external loadings. Various reinforcements and fillers are added to polymers which bring out more complexity in analyzing the timedependent response. This study formulates an integrated micromechanical model and finite element (FE) analysis for predicting effective viscoelastic-viscoplastic response of polymer based hybrid composites. The studied hybrid system consists of unidirectional short-fiber reinforcements and a matrix system which is composed of solid spherical particle fillers dispersed in a homogeneous polymer constituent. The goal is to predict effective performance of hybrid systems having different compositions and properties of the fiber, particle, and matrix constituents. A combined Schapery's viscoelastic integral model and Valanis's endochronic viscoplastic model is used for the polymer constituent. The particle and fiber constituents are assumed linear elastic. A previously developed micromechanical model of particle reinforced composite is first used to obtain effective mechanical properties of the matrix systems. The effective properties of the matrix are then integrated to a unit-cell model of short-fiber reinforced composites, which is generated using the FE. The effective properties of the matrix are implemented using a user material subroutine in the FE framework. Limited experimental data and analytical solutions available in the literatures are used for comparisons.

• The KIPS Transactions:PartD
• /
• v.11D no.4
• /
• pp.765-774
• /
• 2004

In order to integrate heterogeneous biological information sources, it is necessary to define the view that represents unified viewpoint for the multiple sources by hiding heterogeneity of the data. We present an XML-based view definition model and show Its operating principles in designing the middleware system to integrate biological information sources. This model supports the user-defined XML view to increase flexibility in constructing the integration system and execute integrated queries on higher level ion. Based on the view-definition model, we present a wrapping model for relational database systems and web resources as well as an application program.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
• /
• v.29 no.3
• /
• pp.163-168
• /
• 2003

Three-dimensional solid model has not been widely used in surgical prediction of orthognathic surgery because frequent artifacts from occlusal restorations or prosthesis limited the usefulness of simulated surgery involving occlusion. We prepared three-dimensional(3D) solid model from CT data and integrated the 3D solid model with dental cast using a face-bow transfer technique combined with skeletal reference measurement and confirmation with cephalometric radiographs. With this simple and easy method, it was possible to predict bony interference between the proximal and distal segment of the mandible so that we can prevent condylar displacement after sagittal split ramus osteotomy of the mandible with prominent asymmetry. The method error was within 2mm and it seemed to be useful in preoperative planning for maxillofacial surgery with maxillo-mandibular occlusal change.

• Journal of the Society of Naval Architects of Korea
• /
• v.55 no.3
• /
• pp.222-235
• /
• 2018

The hydrocarbon gas leak in the offshore plant can cause large accidents and lead to significant damages to human, property and environment. For prevention of fire or explosion accidents from gas leak, a SIS(Safety Instrumented System) should be installed. In the early stage of the offshore design, required SIL(Safety Integrated Level) is determined and reliability analysis is performed to verify the design in reliability aspects. This study collected data, information related to reliability analysis and created knowledge model of safety design for the offshore system with MBSE(Model-Based Systems Engineering) concept. Knowledge model could support safety engineer's design tasks as the guidance of reliability analysis procedure of safety design and make good conversation with other engineers in yard, class, company, etc.

• Journal of Distribution Science
• /
• v.19 no.8
• /
• pp.25-35
• /
• 2021

Purpose: This study aims to propose an integrated MCDM model to support the qualified personnel selection in the distribution science. Research design, data, and methodology: The integrated approach of AHP and TOPSIS was employed to address the personnel selection problem. The AHP method was used to define the weights of the selection criteria, whereas the TOPSIS was applied to rank alternatives. The proposed model was then applied into a leading logistics company to select the best alternatives to be the sales deputy manager. Results: The results showed that Candidate 3 is the most qualified personnel for the sales deputy manager position as he is ranked first in the order of preference for recruitment. Conclusions: The proposed model provides the decision makers with more effective and time-saving methods than conventional ones. Therefore, the model can be applied to personnel selection around the world. In terms of theoretical contribution, this study proposes a personnel selection model for choosing the most appropriate candidates. In addition, the study adds to the theory of human resources management and logistics management the full set of personnel selection criteria including education, experience, skills, health, personality traits and foreign language.

• Design & Manufacturing
• /
• v.15 no.3
• /
• pp.1-6
• /
• 2021

An artificial neural network model based on a deep learning algorithm is known to be more accurate than humans in image classification, but there is still a limit in the sense that there needs to be a lot of training data that can be called big data. Therefore, various techniques are being studied to build an artificial neural network model with high precision, even with small data. The transfer learning technique is assessed as an excellent alternative. As a result, the purpose of this study is to develop an artificial neural network system that can classify burr images of light guide plate products with 99% accuracy using transfer learning technique. Specifically, for the light guide plate product, 150 images of the normal product and the burr were taken at various angles, heights, positions, etc., respectively. Then, after the preprocessing of images such as thresholding and image augmentation, for a total of 3,300 images were generated. 2,970 images were separated for training, while the remaining 330 images were separated for model accuracy testing. For the transfer learning, a base model was developed using the NASNet-Large model that pre-trained 14 million ImageNet data. According to the final model accuracy test, the 99% accuracy in the image classification for training and test images was confirmed. Consequently, based on the results of this study, it is expected to help develop an integrated AI production management system by training not only the burr but also various defective images.

• Journal of Korean Society of Archives and Records Management
• /
• v.2 no.1
• /
• pp.119-131
• /
• 2002

The study designs and implements a KORMARC/EAD integrated system for the Myongji Digital Library Collections. The purpose of this paper is to design the metadata to Myongji Korean History Collections to provide digital information of high quality to clients, and to develop and implement a model for managing digital library collections. In order to test the model and the quality of the derived metadata, we built a metadata management system, which is connected to the existing KORMARC system. The system consists of two modules- a retrieval and an input module. While in the retrieve mode, one can retrieve KORMARC records of books and archival items, with links to modified EAD files for archival items or to image files for books, in the input mode, one can type two types of data such as a catalog data and an inventory data. Finally, we evaluated the proposed system via mail questionnaires, and propose three suggestions to make this system a much more comprehensive and effective system.

• Journal of Intelligence and Information Systems
• /
• v.21 no.1
• /
• pp.29-45
• /
• 2015

Response modeling is a well-known research issue for those who have tried to get more superior performance in the capability of predicting the customers' response for the marketing promotion. The response model for customers would reduce the marketing cost by identifying prospective customers from very large customer database and predicting the purchasing intention of the selected customers while the promotion which is derived from an undifferentiated marketing strategy results in unnecessary cost. In addition, the big data environment has accelerated developing the response model with data mining techniques such as CBR, neural networks and support vector machines. And CBR is one of the most major tools in business because it is known as simple and robust to apply to the response model. However, CBR is an attractive data mining technique for data mining applications in business even though it hasn't shown high performance compared to other machine learning techniques. Thus many studies have tried to improve CBR and utilized in business data mining with the enhanced algorithms or the support of other techniques such as genetic algorithm, decision tree and AHP (Analytic Process Hierarchy). Ahn and Kim(2008) utilized logit, neural networks, CBR to predict that which customers would purchase the items promoted by marketing department and tried to optimized the number of k for k-nearest neighbor with genetic algorithm for the purpose of improving the performance of the integrated model. Hong and Park(2009) noted that the integrated approach with CBR for logit, neural networks, and Support Vector Machine (SVM) showed more improved prediction ability for response of customers to marketing promotion than each data mining models such as logit, neural networks, and SVM. This paper presented an approach to predict customers' response of marketing promotion with Case Based Reasoning. The proposed model was developed by applying different weights to each feature. We deployed logit model with a database including the promotion and the purchasing data of bath soap. After that, the coefficients were used to give different weights of CBR. We analyzed the performance of proposed weighted CBR based model compared to neural networks and pure CBR based model empirically and found that the proposed weighted CBR based model showed more superior performance than pure CBR model. Imbalanced data is a common problem to build data mining model to classify a class with real data such as bankruptcy prediction, intrusion detection, fraud detection, churn management, and response modeling. Imbalanced data means that the number of instance in one class is remarkably small or large compared to the number of instance in other classes. The classification model such as response modeling has a lot of trouble to recognize the pattern from data through learning because the model tends to ignore a small number of classes while classifying a large number of classes correctly. To resolve the problem caused from imbalanced data distribution, sampling method is one of the most representative approach. The sampling method could be categorized to under sampling and over sampling. However, CBR is not sensitive to data distribution because it doesn't learn from data unlike machine learning algorithm. In this study, we investigated the robustness of our proposed model while changing the ratio of response customers and nonresponse customers to the promotion program because the response customers for the suggested promotion is always a small part of nonresponse customers in the real world. We simulated the proposed model 100 times to validate the robustness with different ratio of response customers to response customers under the imbalanced data distribution. Finally, we found that our proposed CBR based model showed superior performance than compared models under the imbalanced data sets. Our study is expected to improve the performance of response model for the promotion program with CBR under imbalanced data distribution in the real world.

• Journal of KSNVE
• /
• v.10 no.5
• /
• pp.792-799
• /
• 2000

Aircraft noise in the vicinity of Kimpo international airport has damaged to large number of people who live in communities. This paper investigates noise exposed area due to aircraft flight based on prediction modeling program INM and flight path data. Especially effect on route for aircraft has been considered. Ti also examines noise impact for various flight modes, such as a thrust cutback climb method.