• Journal of Institute of Control, Robotics and Systems
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• v.18 no.12
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• pp.1090-1095
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• 2012

In this paper, we propose a model-based fault diagnosis method applied to vibration data. The fault detection is performed by comparing estimated parameters with normal parameters and deciding if the observed changes can be explained satisfactorily in terms of noise or undermodelling. The key feature of this method is that it accounts for the effects of noise and model mismatch. And we aslo design a classifier for the fault isolation by applying the multiclass SVM (Support Vector Machine) to the estimated parameters. The proposed fault detection and isolation methods are applied to an engine vibration data to show a good performance. The proposed fault detection method is compared with a signal-based fault detection method through a performance analysis.

• MALSORI
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• no.47
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• pp.131-140
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• 2003

We propose a new method of generating client models for HMM based text-dependent speaker verification system with only a small amount of training data. To make a client model, statistical methods such as segmental K-means algorithm are widely used, but they do not guarantee the quality or reliability of a model when only limited data are avaliable. In this paper, we propose a blind speech segmentation based on level building DTW algorithm as an alternative method to make a client model with limited data. In addition, considering the fact that voiced sounds have much more speaker-specific information than unvoiced sounds and energy of the former is higher than that of the latter, we also propose a new score evaluation method using the observation probability raised to the power of weighting factor estimated from the normalized log energy. Our experiment shows that the proposed methods are superior to conventional HMM based speaker verification system.

• Journal of Information Technology Applications and Management
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• v.26 no.3
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• pp.19-27
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• 2019

In this study, we propose a methodology for predicting the movie audience based on movie information that can be easily acquired before opening and effectively distinguishing qualitative variables. In addition, we constructed a model to estimate the number of movie audiences at the time of data acquisition through the configured variables. Another purpose of this study is to provide a criterion for categorizing success of movies with qualitative characteristics. As an evaluation criterion, we used information gain ratio which is the node selection criterion of C4.5 algorithm. Through the procedure we have selected 416 movie data features. As a result of the multiple linear regression model, the performance of the regression model using the variables selection method based on the information gain ratio was excellent.

• The Journal of Information Systems
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• v.29 no.1
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• pp.93-111
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• 2020

Purpose The purpose of this paper is to observe the relative priorities of importances among the modified versions of Block chain system, being based on AHP decision support model which should be also proposed in this paper. Design/methodology/approach Four versions modified from the beginning of Block chain were divided into Public& Permissionless, Private&Permissionless, Public&Permissioned and Private&Permissioned types. Five criteria for evaluating the four versions whether the version were suitable for Medical information system were introduced from five factors of Technologies Accept Model, which were Security, Availability, Variety, Reliability and Economical efficiency. We designed Decision support model based on AHP which would select the best alternative version suitable for introducing the Block chain technology into the medical information systems. We established the objective of the AHP model into finding the best choice among the four modified versions. First low layer of the model contains the five factors which consisted of Security, Availability, Variety, Reliability and Economical efficiency. Second low layer of the model contains the four modified versions which consisted Public&Permissionless, Private&Permissionless, Public&Permissioned and Private& Permissioned types. The structural questionnaire based on the AHP decision support model was designed and used to survey experts of medical areas. The collected data by the question investigation was analyzed by AHP analysis technique. Findings The importance priority of Security was highest among five factors of Technologies Accept Mode in the first layer. The importance priority of Private&Permissioned type was highest among four modified versions of Block chain technologies in second low layer. The second importance priority was Private&Permissionless type. The strong point of Private&Permissioned type is to be able to protect personal information and have faster processing speeds. The advantage of Private& Permissionless type is to be also able to protect personal information as well as from forging and altering transaction data. We recognized that it should be necessary to develop new Block chain technologies that would enable to have faster processing speeds as well as from forging and altering transaction data.

• Korean Medical Education Review
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• v.23 no.1
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• pp.56-67
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• 2021

Educational program evaluation can improve the quality of the curriculum, instructional methods, and resources and provide useful data for making educational decisions and policies. Developing and implementing a program evaluation system is essential in competency-based medical education. The purpose of this study was to explore and establish an educational program evaluation system adapting an integrated program evaluation model to promote competency-based medical education. First, an Educational Evaluation Committee was organized, consisting of faculty, staff members, and students. The committee established an integrated program evaluation model, combining Stufflebeam's Context, Input, Process, and Product (CIPP) model of a process-oriented approach and Kirkpatrick's four-level model of an outcome-oriented approach. Kirkpatrick's model was applied to the product evaluation of the CIPP model. The committee then developed evaluation criteria, indicators, and data collection methods according to the components of the CIPP model and the four levels (reaction, learning, behavior, and results) of Kirkpatrick's model, and collected and analyzed data. Finally, the committee reported the results of evaluation to a Medical Education Quality Improvement Committee, and the results were used to improve the curriculum and student selection. To enhance the quality of education, identifying educational deficiencies and developing various elements of education in a balanced way through educational evaluation will be needed. Furthermore, it will be necessary to listen to opinions of various stakeholders, work with all members involved in education, and communicate with decision-makers in the process of educational evaluation.

• The Journal of Information Systems
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• v.33 no.1
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• pp.207-226
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• 2024

Purpose This study aims to develop a job model for data convergent talents to meet the rapidly changing demands of the data industry. To create a job model, we first define and categorize data convergent talents with balanced competencies in data technology and domain knowledge, and then develop a job model by investigating job areas, scope, activities, and competencies. Design/methodology/approach The research is conducted using the following procedures and methodology. First, we conduct a current status survey on data talent demand, data talent policies, data talent programs, and curricula at home and abroad; second, we collect opinions on the jobs and competencies required for data convergent talents and curricula for talent development through in-depth interview with experts; and third, we present the job areas and job activities of data convergent talents derived from the previous status survey and expert opinions based on the National Competency Standards(NCS). Findings The research findings indicate that there are total of six job roles for data convergent talents, including data scientist, data planner, data architect, data developer, data engineer, and data analyst. It was observed that each of these roles requires the development of common competencies within their respective fields, followed by a need for further specialization into specific competencies within each professional domain.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.241-246
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• 2008

Design of a high-speed railway line requires collaboration of heterogeneous application systems and of engineers with different background. Object-based 3D models with metadata can be a shared information model for the effective collaborative design. In this paper, railway infrastructure information model is proposed to enable integrated and inter-operable works throughout the life-cycle of the railway infrastructures, from planning to maintenance. In order to develop the model, object-based 3-D models were built for a 10km railway among Korea high-speed railway lines. The model has basically three information layers for designers, contractors and an owner, respectively. Prestressed concrete box-girders are the most common superstructure of bridges. The design information layer has metadata on requirements, design codes, geometry, analysis and so on. The construction layer has data on drawings, real data for material and products, schedules and so on. The maintenance layer for the owner has the final geometry, material data, products and their suppliers and so on. These information has its own data architecture which is derived from similar concept of product breakdown structure(PBS) and work breakdown structure(WBS). The constructed RIIM for the infrastructures of the high-speed railway was successfully applied to various areas such as design check, structural analysis, automated estimation, construction simulation, virtual viewing, and digital mock-up. The integrated information model can realize virtual construction system for railway lines and dramatically increase the productivity of the whole engineering process.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.4
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• pp.389-395
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• 2015

According to much research on cognitive science, the impact of the scene-context on human visual search in real-world images could be as important as the saliency. Therefore, this study proposed a method of Adaptive Control of Thought-Rational (ACT-R) modeling of visual search in real-world images, based on saliency and scene-context. The modeling method was developed by using the utility system of ACT-R to describe influences of saliency and scene-context in real-world images. Then, the validation of the model was performed, by comparing the data of the model and eye-tracking data from experiments in simple task in which subjects search some targets in indoor bedroom images. Results show that model data was quite well fit with eye-tracking data. In conclusion, the method of modeling human visual search proposed in this study should be used, in order to provide an accurate model of human performance in visual search tasks in real-world images.

• Journal of Korean Society of Water and Wastewater
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• v.27 no.1
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• pp.139-146
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• 2013

A process diagnosis method for membrane water treatment plant was developed using a constant flux membrane fouling model. This diagnosis method can be applied to a real-field membrane-based water treatment plant as an early alarming system for membrane fouling. The constant flux membrane fouling model was based on the simplest equation form to describe change in trans-membrane pressure (TMP) during the filtration cycle from a literature. The model was verified using a pilot-scale microfiltraton (MF) plant with two commercial MF membrane modules (72 m2 of membrane area). The predicted TMP data were produced using the model, where the modeling parameters were obtained by the least square method using the early plant data and modeling equations. The diagnosis was carried out by comparing the predicted TMP data (as baseline) and real plant data. As a result of the case study, the diagnsis method worked pretty well to predict the early points where fouling started to occur.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2286-2304
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• 2022

Blockchain is a distributed ledger that combines technologies such as cryptography, consensus mechanism, peer-to-peer transmission, and time stamping. The rapid development of blockchain has attracted attention from all walks of life, but storage scalability issues have hindered the application of blockchain. In this paper, a scalable blockchain storage model based on Distributed Hash Table (DHT) and the InterPlanetary File System (IPFS) was proposed. This paper introduces the current research status of the scalable blockchain storage model, as well as the basic principles of DHT and the InterPlanetary File System. The model construction and workflow are explained in detail. At the same time, the DHT network construction mechanism, block heat identification mechanism, new node initialization mechanism, and block data read and write mechanism in the model are described in detail. Experimental results show that this model can reduce the storage burden of nodes, and at the same time, the blockchain network can accommodate more local blocks under the same block height.