• Korean Journal of Construction Engineering and Management
• /
• v.15 no.4
• /
• pp.119-127
• /
• 2014

This study aims to determine whether or not the input output life cycle assessment (I-O LCA) model can be used to assess the carbon dioxide (CO2) emission of buildings in initial planning phase. To ensure this end, this study proposed I-O LCA model which is the simplified LCA model and Hybrid LCA model which is the detailed LCA model, and then assessed and compared the CO2 emission of six case projects (three apartment complexes and three educational facilities) using the two LCA model. The results of the case study showed that the CO2 emissions assessed by the I-O LCA is significantly similar to the CO2 emission assessed by the Hybrid LCA model. The similarity of results from both LCA models was 78.2-86.3% in apartment complexes and 59.9-84.8% in educational facilities. However, the CO2 emissions from I-O LCA model were smaller than the CO2 emissions from Hybrid LCA model in case study. Nevertheless, the case study showed that the I-O LCA model was capable of assessing the CO2 emission of buildings quite appropriately although the I-O LCA model is the simplified LCA model which considers only the construction cost. The I-O LCA model is expected to be a useful tool for assessing the CO2 emission of buildings in initial planning phase.

• Communications for Statistical Applications and Methods
• /
• v.17 no.2
• /
• pp.141-151
• /
• 2010

Hybrid fuzzy regression analysis is used for integrating randomness and fuzziness into a regression model. Least squares support vector machine(LS-SVM) has been very successful in pattern recognition and function estimation problems for crisp data. This paper proposes a new method to evaluate hybrid fuzzy linear and nonlinear regression models with crisp inputs and fuzzy output using weighted fuzzy arithmetic(WFA) and LS-SVM. LS-SVM allows us to perform fuzzy nonlinear regression analysis by constructing a fuzzy linear regression function in a high dimensional feature space. The proposed method is not computationally expensive since its solution is obtained from a simple linear equation system. In particular, this method is a very attractive approach to modeling nonlinear data, and is nonparametric method in the sense that we do not have to assume the underlying model function for fuzzy nonlinear regression model with crisp inputs and fuzzy output. Experimental results are then presented which indicate the performance of this method.

• Journal of Power Electronics
• /
• v.15 no.5
• /
• pp.1178-1189
• /
• 2015

A non-isolated Multiple Input Converter (MIC) with an input port, two storage ports and a load port is proposed. The synthesis of the proposed four port converter with its switch realization is presented. A steady state analysis of each operating mode with a small-signal model is derived, and a stability analysis is done. A mode selection controller is proposed to automatically choose a specific operating mode based on the voltage levels of the different source and storage units. In addition, a voltage control loop is used to regulate the output voltage. A 200W prototype is built with a TMS320F28027 DSP controller to test the feasibility of the operating modes. Simulation and experimental results show the ability of the proposed converter to handle multiple inputs either individually or simultaneously.

• Proceedings of the Korea Society for Industrial Systems Conference
• /
• 1997.03a
• /
• pp.235-246
• /
• 1997

Hybrid fuzzy gain scheduling controller is composed of a PD control and a fuzzy control for taking the advantage of each scheme. The key structure of the hybrid fuzzy gain scheduling control scheme is so called a switch which calculates weighting values between the fuzzy controller and the PD controller. However, due to the requirement of the switch , the hybrid fuzzy gain scheduling control scheme needs extra fuzzy logic processing, thus the structure is complicated. and requires more calculation time. To eliminate the drawbacks, a new hybrid fuzzy gain scheduling control scheme is proposed in this paper. In the proposed scheme, the membership function, for calculating of weithting value, and the input and output membership functions are combined. Thus the proposed hybrid scheme does not require switch for calculation of weighting value, and as a result, the calculation time is faster and the structure is more simple than the existing hybrid controller. Computer simulation results for an inverted pendulum model under Pole-Placement PID controller, fuzzy gain scheduling controller,existing hybrid controller , and proposed hybrid controller are compared to demonstrate the good property of the proposed hybrid controller.

• International Journal of Aeronautical and Space Sciences
• /
• v.16 no.4
• /
• pp.510-519
• /
• 2015

Concerning the issue of high-dimensions, hybrid uncertainties of randomness and intervals including implicit and highly nonlinear limit state function, reliability analysis based on the hybrid uncertainty reliability mode combining with back propagation neural network (HU-BP neural network) is proposed in this paper. Random variables and interval variables are as input layer of the neural network, after the training and approximation of the neural network, the response variables are obtained through the output layer. Reliability index is calculated by solving the optimization model of the most probable point (MPP) searching in the limit state band. Two numerical cases are used to demonstrate the method proposed in this paper, and finally the method is employed to solving an engineering problem of the aerospace friction plate. For this high nonlinear, small failure probability problem with interval variables, this method could achieve a good analysis result.

• Environmental and Resource Economics Review
• /
• v.13 no.3
• /
• pp.441-468
• /
• 2004

We estimate carbon embodied in the export goods of Korea. A commodity-by-industry IO model ($CO_2$ hybrid IO model) is constructed for the estimation. In the model, all monetary units of energy commodities are converted to physical unit, carbon tons. Results show that total $CO_2$ embodied in the exports of non-energy goods of Korea equals 51.18 million carbon ton or 44% of total $CO_2$ emissions in Korea in 2000. Overall carbon intensity of export goods is estimated as 0.227 carbon ton per million Won. These findings suggest Korea's responsibility on global warming may be imputed to the countries who import and consume Korean goods. It is in accordance with the user pay principle. It is also argued that if UNFCCC impose the burden of $CO_2$ mitigation on importing countries rather than exporting countries, we can prevent '$CO_2$ emission leakages' effectively.

• The Journal of the Korea Contents Association
• /
• v.12 no.11
• /
• pp.295-302
• /
• 2012

The display industry plays an important role in the entire Korean economy. Few empirical research has analyzed the efficiency of display companies although it is necessary to measure the management efficiency for more efficient operation and more strengthening competitiveness of them. The purpose of this paper is to measure and analyze their efficiency of the Korean listed display companies using a hybrid ANP and DEA model. In this paper, we analyzed the 44 listed companies consisted of 7 listed on KOSPI and 37 listed on KOSDAQ at the end of 2010. In order to determine the input and output variables of DEA, the ANP model was applied to evaluate the importance of input and output variables. The benchmarking companies and efficiency value for the display firms with inefficiency were also provided to improve the their efficiency.

• Journal of Biomedical Engineering Research
• /
• v.28 no.6
• /
• pp.768-776
• /
• 2007

A new type of the fluid circulation blood pressure simulator was proposed to enhance the blood pressure simulator used for the development and evaluation of automatic sphygmomanometers. Various pressure waveform of fluid flowing in the pipe was reproduced by operating the proportional control valve after applying a pressure on the fluid in pressurized oil tank. After that, appropriate fluid was supplied by operating the proportional control valve, which enabled to reproduce various pressure wave of the fluid flowing in the tube. To accomplish this work, the mathematical model was carefully reviewed in cooperating with the proposed simulator. After modeling the driving signal as input signal and the pressure in internal tube as output signal, the simulation on system parameters such as internal volume, cross-section of orifice and supply pressure, which are sensitive to dynamic characteristic of system, was accomplished. System parameters affecting the dynamic characteristic were analyzed in the frequency bandwidth and also reflected to the design of the plant. The performance evaluator of fluid dynamic characteristic using proportional control signal was fabricated on the basis of obtained simulation result. An experimental apparatus was set-up and measurements on the dynamic characteristic, nonlinearity, and rising and falling response was carried out to verify the characteristic of the fluid dynamic model. Controller was designed and thereafter, simulation was performed to control the output signal with respect to the reference input in the fluid dynamic model using the proposed proportional control valve. Hybrid controller combined with an proportional controller and feed-forward controller was fabricated after applying a disturbance observer to the control plant. Comparison of the simulations between the conventional proportional controller and the proposed hybrid simulator indicated that even though the former showed good control performance.

• Journal of Information Management
• /
• v.37 no.1
• /
• pp.57-81
• /
• 2006

The new service of Korean public library, ASK_a service model suggests a new management practice in collaborative digital reference services. The model has three functions: input transaction, process transaction, and output transaction. The best form for input is the web form. The best form for process is a model with a hybrid type of public libraries(hierarchical and lateral type). The output suggests the archiving policy for gathering the query-answer data. The core of this model is providing an advanced information service to its users through cooperation with public libraries and external manpower.

• Journal of Intelligence and Information Systems
• /
• v.19 no.2
• /
• pp.125-140
• /
• 2013

We call a data set in which the number of records belonging to a certain class far outnumbers the number of records belonging to the other class, 'imbalanced data set'. Most of the classification techniques perform poorly on imbalanced data sets. When we evaluate the performance of a certain classification technique, we need to measure not only 'accuracy' but also 'sensitivity' and 'specificity'. In a customer churn prediction problem, 'retention' records account for the majority class, and 'churn' records account for the minority class. Sensitivity measures the proportion of actual retentions which are correctly identified as such. Specificity measures the proportion of churns which are correctly identified as such. The poor performance of the classification techniques on imbalanced data sets is due to the low value of specificity. Many previous researches on imbalanced data sets employed 'oversampling' technique where members of the minority class are sampled more than those of the majority class in order to make a relatively balanced data set. When a classification model is constructed using this oversampled balanced data set, specificity can be improved but sensitivity will be decreased. In this research, we developed a hybrid model of support vector machine (SVM), artificial neural network (ANN) and decision tree, that improves specificity while maintaining sensitivity. We named this hybrid model 'hybrid SVM model.' The process of construction and prediction of our hybrid SVM model is as follows. By oversampling from the original imbalanced data set, a balanced data set is prepared. SVM_I model and ANN_I model are constructed using the imbalanced data set, and SVM_B model is constructed using the balanced data set. SVM_I model is superior in sensitivity and SVM_B model is superior in specificity. For a record on which both SVM_I model and SVM_B model make the same prediction, that prediction becomes the final solution. If they make different prediction, the final solution is determined by the discrimination rules obtained by ANN and decision tree. For a record on which SVM_I model and SVM_B model make different predictions, a decision tree model is constructed using ANN_I output value as input and actual retention or churn as target. We obtained the following two discrimination rules: 'IF ANN_I output value <0.285, THEN Final Solution = Retention' and 'IF ANN_I output value ${\geq}0.285$, THEN Final Solution = Churn.' The threshold 0.285 is the value optimized for the data used in this research. The result we present in this research is the structure or framework of our hybrid SVM model, not a specific threshold value such as 0.285. Therefore, the threshold value in the above discrimination rules can be changed to any value depending on the data. In order to evaluate the performance of our hybrid SVM model, we used the 'churn data set' in UCI Machine Learning Repository, that consists of 85% retention customers and 15% churn customers. Accuracy of the hybrid SVM model is 91.08% that is better than that of SVM_I model or SVM_B model. The points worth noticing here are its sensitivity, 95.02%, and specificity, 69.24%. The sensitivity of SVM_I model is 94.65%, and the specificity of SVM_B model is 67.00%. Therefore the hybrid SVM model developed in this research improves the specificity of SVM_B model while maintaining the sensitivity of SVM_I model.