• Journal of Information Technology Applications and Management
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• v.11 no.1
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• pp.117-135
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• 2004

Since human decision making behavior is likely to follow nonlinear strategy, it is conjectured that the human decision making behavior can be modeled better by nonlinear models than by linear models. All that linear models can do is to approximate rather than model the decision behavior. This study attempts to test this conjecture by analyzing human decision making behavior and combining the results of the analysis with predictive performance of both linear models and nonlinear models. In this way, this study can examine the relationship between the predictive performance of models and the existence of valid nonlinear strategy in decision making behavior. This study finds that the existence of nonlinear strategy in decision making behavior is highly correlated with the validity of the decision (or the human experts). The second finding concerns the significant correlations between the model performance and the existence of valid nonlinear strategy which is detected by Lens Model. The third finding is that as stronger the valid nonlinear strategy becomes, the better nonlinear models predict significantly than linear models. The results of this study bring an important concept, validity of nonlinear strategy, to modeling human experts. The inclusion of the concept indicates that the prior analysis of human judgement may lead to the selection of proper modeling algorithm. In addition, lens Model Analysis is proved to be useful in examining the valid nonlinearity in human decision behavior.

• Korean Journal of Veterinary Research
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• v.46 no.2
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• pp.159-164
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• 2006

A stochastic simulation model incorporated with Reed-Frost approach was derived for evaluating diagnostic performance of a test used for a screening program of an infectious disease. The Reed-Frost model was used to characterize the within-herd spread of the disease using a hypothetical example. Specifically, simulation model was aimed to estimate the number infected animals in an infected herd, in which imperfect serologic tests are performed on samples taken from herds and to illustrate better interpreting survey results at herd-level when uncertainty inevitably exists. From a risk analysis point of view, model output could be appropriate in developing economic impact assessment models requiring probabilistic estimates of herd-level performance in susceptible populations. The authors emphasize the importance of knowing the herd-level diagnostic performance, especially in performing emergency surveys in which immediate control measures should be taken following the survey. In this context this model could be used in evaluating efficacy of a survey program and monitoring infection status in the area concerned.

• Korea Journal of Hospital Management
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• v.14 no.2
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• pp.21-40
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• 2009

The importance-performance analysis (IPA) is a widely used analytical technique that produces a priority of managerial attention for the customer satisfaction. This study attempted to compare various different approaches of IPA such as direct and indirect measurement of importance, and traditional four quadrants grid model and diagonal grid model of IPA. Data on 17 inpatient service quality attributes were collected from 234 inpatients of a general hospital. Eight IPA grids were produced to compare the result of each model. Based on the study results the strength and weakness of each model were discussed, and a set of recommendations for practical application of the IPA in hospital settings was suggested.

• Journal of Information Technology and Architecture
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• v.10 no.4
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• pp.467-478
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• 2013

The necessity of research for EA service and performance is surfacing while nation-level and individual agency level performances utilizing Government-wide EA information. In this study, performance model for EA service has been developed categorizing characteristic elements of EA as service. And weight differences between quality items that constitute performance model have been calculated using AHP analysis method. To achieve the stated, SERVQUAL applied performance model for EA service has been developed working through logical reasoning and a broad range of theoretical studies concerning EA service. Moreover, relative weight differences between quality items that constitute the model have been calculated. The results of weight analysis find that importance differences between quality items in order of significance are as follows: EA administrator > EA information > EA education > EA policy > EA operating system. This study, as the nation's first research to graft the public-sector EA service onto SERVQUAL Model that is capturing remarkable attention, has considerable practical and theoretical implications.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.1721-1726
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• 2004

Heat rate is a representative index to estimate the performance of turbine cycle in nuclear power plant. Accuracy of heat rate calculation is dependent on the accuracy of measurement for plant status variables. Uncertainty of heat rate can be modeled using uncertainty propagation model. We developed practical estimation model of heat rate uncertainty using the propagation and regression model. The uncertainty model is used in the performance analysis system developed for the operating nuclear power plant.

• Journal of Korean Society for Quality Management
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• v.47 no.2
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• pp.295-314
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• 2019

Purpose: This study aims to investigate the factors affecting productivity performance for Korean SMEs of manufacturing which had obtained the certification of Productivity Management System(PMS) that is a Korean assessment program for enhancing maturity of company's management systems. Methods: The proposed model is based on the PMS model. The valid 759 data registered from 2010 to 2018 year was analyzed using SEM analysis for testing hypotheses. Results: The results are as follows. First, Leadership affects the five core sub-system processes positively, but doesn't a significant Business Performance directly. Secondly, HRM, Customer & Market Analysis, and Process Management excluding Productivity Development and Measurement Analysis and Knowledge Management have a significant effect on Business Performance. Lastly, when examining the mediation effect, Process Development, Customer & Market Analysis, and HRM have indirectly effect between Leadership and Business Performance. Conclusion: This study results suggest not only the role of leadership to improve productivity performance of SME, but also which core processes are focused and differentiated.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.1
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• pp.25-39
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• 2018

In this paper, an integrated analysis model for evaluating the underwater acoustic performance of the multilayered acoustic coatings containing visco-elastic composite layers with hollow glass microspheres is described. The model uses the effective medium theory considering the acoustic scattering and resonance effects of the inclusions. Also, the model incorporates the compressive deformation mechanism associated with hydrostatic pressure. The technique developed in this work was used as the acoustic layer design and performance analysis tools for the practical hull coatings and acoustic baffles in Korean next generation submarines.

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.268-273
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• 2021

In this paper, we propose a sentiment analysis model that improves performance on small-scale data. A sentiment analysis model for small-scale data is proposed and verified through experiments. To this end, we propose Bagging-Bi-GRU, which combines Bi-GRU, which learns GRU, which is a variant of LSTM (Long Short-Term Memory) with excellent performance on sequential data, in both directions and the bagging technique, which is one of the ensembles learning methods. In order to verify the performance of the proposed model, it is applied to small-scale data and large-scale data. And by comparing and analyzing it with the existing machine learning algorithm, Bi-GRU, it shows that the performance of the proposed model is improved not only for small data but also for large data.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.24 no.6
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• pp.538-544
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• 2012

Analysis of thermal performance is required for the economic operation of turbine cycle of power plant. We developed corrective model of main feed water flow which is the most important parameter for the precise analysis of turbine cycle performance. Classification model for the identification of feed water flow measurement status was applied to increase the suitability of the corrective model. We used neural network and support vector machine to develop estimation model of main feed water flow with more generalization capability. The estimation model can be used practically to evaluate corrective performance of turbine cycle plant.

• Journal of Korea Multimedia Society
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• v.18 no.11
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• pp.1367-1374
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• 2015

In this paper, we propose a model which can prioritize the performance improvement work by analyzing the major risks and their influence, which can cause performance degradation in the system and show an example of a performance improvement using this model. In presentation-tier, as a result of log data analysis before and after the performance improvement of key processes which handle financial transactions, this model brought the CPU utilization and memory enhancement in the performance improvement work of the financial system which was carried out by applying the proposed model. It has been confirmed that the entire end-user can be accommodated. In the web-tier, the available memory increased by 200MB and we were able to improve the server restart(Recycling) that was sustained in the existing system. In the business logic-tier, we have been able to see better figures after performance improvements through the graph which analyzes the log collected with the key performance counters such as CPU%, Batch Requests/sec. In the data-tier, it has been confirmed that CPU usage and standby operation were reduced and the throughput was found to increase.