• STI Policy Review
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• v.1 no.2
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• pp.51-68
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• 2010

This paper compares OECD nations by developing a comprehensive evaluation index that examines the efforts and achievements of countries toward Low-Carbon Green Growth. The input-process-output of a Low-Carbon Society system is in dynamic competition with that of a High-Carbon Society system. The model used in this study of the comprehensive evaluation index for Low-Carbon Green Growth was comprised of Large indices such as Input, Process, and Output. The Input and Output consisted of 'Social-economic' and 'Physical-ecological' Middle indices while the Process was made up of 'Stimulation mechanisms' and 'Participation of stakeholders and Knowledge flow' Middle indices. In order to calculate the comprehensive evaluation index, our model gave a weight to each indicator/index and applied a weighted arithmetic mean. Korea ranked $15^{th}$ out of 30 OECD nations in the comprehensive evaluation that analyzed Input ($14^{th}$), Process ($18^{th}$), and Output ($17^{th}$). The top five nations were Switzerland, Sweden, Denmark, Germany, and France; while Japan was $8^{th}$ and the USA $26^{th}$.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.543-545
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• 2019

The AQI index has been developed and used to guide the action of particulate matter. Information on the AQI index can be easily provided to the general public, and various services are provided based on the AQI index. As services are provided, accurate AQI index prediction is needed. In this paper, we design the classification model using the circular neural network to predict the AQI index of particulate matter. For the evaluation of the designed model, compare the AQI index of the actual particulate matter with the predicted value.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.64-71
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• 2002

This research developed construction cost forecasting model using Building Construction Cost Index, time series analysis and Artificial Neural Networks. By this model, we could calculate the forecasted values of construction cost precisely and efficiently. And we also could find out that the standard deviation of forecasted values is 0.375 and it is a very exact result, so the standard deviation is just 0.33 percent of 112.28, the average of Building Construction Cost Index. And it show more exact forecasting result in comparison with Time Series Analysis.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.2
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• pp.399-407
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• 1996

A fuzzy learning algorithm to get the optimal fuzzy rules is presented in this paper. The algorithm introduces a reference model to generate a desired output and a performance index funtion instead of the performance index table. The performance index funtion is a cost function based on the error and error-rate between the reference and plant output. The cost function is minimized by a gradient method and the control input is also updated. In this case, the control rules which generate the desired response can be obtained by changing the portion of the error-rate in the cost funtion. In SISO(Single-Input Single- Output)plant, only by the learning delay, it is possible to experss the plant model and to get the desired control rules. In the long run, this algorithm gives us the good control rules with a minimal amount of prior informaiton about the environment.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2001.10a
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• pp.220-223
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• 2001

This study was carried out to developed that appraisement model of Potential Productivity Index (PPI). PPI model was used Farmland Productivity Index(FPI) and Labor Productivity Index(LPI) by GIS, and PPI model applied to farm land consolidation region which has been completed recently. FPI was determined by overlapping Poly Grid of the soil properties at the analyzed project region. LPI was estimated by addition productive wages ratio of total direct productive cost. Addition productive wages was determined by GIS Network analysis of working distance between farm house to paddy and each paddy. PPI variation of each the analyzed paddy of Masu and Weoncheon region was $0.967{\sim}0.712,\;0.986{\sim}0.780$ respectively, and could be showed relative largely PPI value. PPI will provide basic element for large scaling and gathering of farm land and a substitute lot of farm land consolidation, and will be maximize productivity of paddy.

• Proceedings of the Korean Association for Survey Research Conference
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• 2000.11a
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• pp.7-19
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• 2000

Much effort has been made to reliably measure customer satisfaction in the industry. Considering different ways of measuring and indexing satisfaction, the research on customer satisfaction warrants further development. We examined the major customer satisfaction indices along with the prior research stream of satisfaction, focusing on ACSI (American Customer Satisfaction Index). We, then, presented the empirical results of customer satisfaction model, using the data collected toward some public services provided by Seoul Metropolitan Government-owned businesses, which implied the usefulness of ACSI model. Finally, we discussed the study findings and limitations.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.254-258
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• 2014

This paper presents the performance analysis results of a short line fault interruption of a gas circuit breaker, particularly a self-blast type breaker. Hot gas flow analysis was carried out using a CFD calculation combined with the arc model and nozzle ablation model. To evaluate the interruption performance, the index function was defined using the pressure in the heating chamber and the density above the arc region. The simulation and test results showed that the gas flow field and suitable choice of an interruption performance index can be used to predict the interruption characteristics and provide guidelines for designing self-blast breakers with a higher interruption capability.

• The Journal of Society for e-Business Studies
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• v.7 no.2
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• pp.21-38
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• 2002

Document retrieval (DR) has been a serious issue for long in the field of Office Information Management. Nowadays, our daily work is becoming heavily dependent on the usage of information collected from the internet, and the DR methods on the Web has become an important issue which is studied more than any other topic by many researchers. The main purpose of this study is to develop a model to manage business documents by integrating three major methodologies used in the field of electronic library and information retrieval: Metadata, Thesaurus, and Index/Reversed Index. In addition, we have added a new concept of eDocument, which consists of metadata about unit documents and/or unit document themselves. eDocument is introduced as a way to utilize existing document sources. The core concepts and structures of the model were introduced, and the architecture of the eDocument management system has been proposed. Test (simulation) result of the model and the direction for the future studies were also mentioned.

• Communications for Statistical Applications and Methods
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• v.23 no.3
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• pp.251-258
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• 2016

It is important to verify the identity of plant-based multivitamins prepared with a natural-concept and popular for daily consumption because they are easily purchased in markets with imperfect information. For this study, a generalized partially double-index model (GPDIM) was employed as a main statistical method to identify the contribution of vitamins and phytochemicals to antioxidant potentials using data on antioxidant capacities and chemical fingerprinting. A bootstrapping approach via sufficient dimension reduction is adopted to estimate the two unknown coefficient vectors in the GPDIM. Fifth order polynomial regressions are fitted to measure the contributions of vitamins and phytochemicals after estimating the coefficient vectors with the two double indices.

• 한국데이터정보과학회:학술대회논문집
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• 2005.04a
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• pp.83-126
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• 2005

Single-index models have found applications in econometrics and biometrics, where multidimensional regression models are often encountered. Here we propose a nonparametric estimation approach that combines wavelet methods for non-equispaced designs with Bayesian models. We consider a wavelet series expansion of the unknown regression function and set prior distributions for the wavelet coefficients and the other model parameters. To ensure model identifiability, the direction parameter is represented via its polar coordinates. We employ ad hoc hierarchical mixture priors that perform shrinkage on wavelet coefficients and use Markov chain Monte Carlo methods for a posteriori inference. We investigate an independence-type Metropolis-Hastings algorithm to produce samples for the direction parameter. Our method leads to simultaneous estimates of the link function and of the index parameters. We present results on both simulated and real data, where we look at comparisons with other methods.