• Journal of Korean Institute of Industrial Engineers
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• v.39 no.5
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• pp.361-366
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• 2013

Prediction of process parameters is very important in parameter design. If predictions are fairly accurate, the quality improvement process will be useful to save time and reduce cost. The concept of dual response approach based on response surface methodology has widely been investigated. Dual response approach may take advantages of optimization modeling for finding optimum setting of input factor by separately modeling mean and variance responses. This study proposes an alternative dual response approach based on machine learning techniques instead of statistical analysis tools. A hybrid neural network-genetic algorithm has been proposed for the purpose of parameter design. A neural network is first constructed to model the relationship between responses and input factors. Mean and variance responses correspond to output nodes while input factors are used for input nodes. Using empirical process data, process parameters can be predicted without performing real experimentations. A genetic algorithm is then applied to find the optimum settings of input factors, where the neural network is used to evaluate the mean and variance response. A drug formulation example from pharmaceutical industry has been studied to demonstrate the procedures and applicability of the proposed approach.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.277-282
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• 2006

It is well known that Kalman filtering is an optimal real-time data fusion method for GPS/INS integration. However, it has some limitations in terms of stability, adaptability and observability. A Kalman filter can perform optimally only when its dynamic model is correctly defined and the noise statistics for the measurement and process are completely known. It is found that estimated Kalman filter states could be influenced by several factors, including vehicle dynamic variations, filter tuning results, and environment changes, etc., which are difficult to model. Neural networks can map input-output relationships without apriori knowledge about them; hence a proper designed neural network is capable of learning and extracting these complex relationships with enough training. This paper presents a GPS/INS integrated system that combines Kalman filtering and neural network algorithms to improve navigation solutions during GPS outages. An Extended Kalman filter estimates INS measurement errors, plus position, velocity and attitude errors etc. Kalman filter states, and gives precise navigation solutions while GPS signals are available. At the same time, a multi-layer neural network is trained to map the vehicle dynamics with corresponding Kalman filter states, at the same rate of measurement update. After the output of the neural network meets a similarity threshold, it can be used to correct INS measurements when no GPS measurements are available. Selecting suitable inputs and outputs of the neural network is critical for this hybrid method. Detailed analysis unveils that some Kalman filter states are highly correlated with vehicle dynamic variations. The filter states that heavily impact system navigation solutions are selected as the neural network outputs. The principle of this hybrid method and the neural network design are presented. Field test data are processed to evaluate the performance of the proposed method.

• Environmental and Resource Economics Review
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• v.15 no.1
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• pp.27-50
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• 2006

We estimate $CO_2$ emissions in Korea industry, 1990 and 2000 using a commodity- by-industry IO model ($CO_2$ hybrid IO mode]). Estimated $CO_2$ emissions in industries include both $CO_2$ emissions from direct and indirect consumption. The results show that total $CO_2$ emissions has increased by 51.6 million TC (Tonne of Carbon) from 64.4 million TC in 1990 to 115.5 million TC in 2000. By applying the structural decomposition analysis technique, we decompose change of $CO_2$ emissions in Korea industry between the period 1990~2000. In the decomposition, we figure out two contributing factors, changes in $CO_2$ coefficient and changes in final demand. The latter is further decomposed as growth effects and structural effects. We also estimated each factor's contribution to the changes in $CO_2$ emissions in industries between 1990~2000. The analysis can be used as a useful resource for policy makers in improving the effectiveness of $CO_2$ emissions mitigation policy.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.9
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• pp.531-538
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• 2005

This paper proposes an expert system which is able to enhance the accuracy and productivity by determining the test strategy based on heuristic rules for test of the hybrid electronic circuit board producted massively in production line. The test heuristic rules are obtained from test system designer, test experts and experimental results. The guarding method separating the tested device with circumference circuit of the device is adopted to enhance the accuracy of measurements in the test of analog devices. This guarding method can reduce the error occurring due to the voltage drop in both the signal input line and the measuring line by utilizing heuristic rules considering the device impedance and the parallel impedance. Also, PSA(Parallel Signature Analysis) technique Is applied for test of the digital devices and circuits. In the PSA technique, the real-time test of the high integrated device is possible by minimizing the test time forcing n bit output stream from the tested device to LFSR continuously. It is implemented in Visual C++ computer language for the purpose of the implementation of the inference engine using the dynamic memory allocation technique, the interface with the electronic circuit database and the hardware direct control. Finally, the effectiveness of the builded expert system is proved by simulating the several faults occurring in the mounting process the electronic devices to the surface of PCB for a typical hybrid electronic board and by identifying the results.

• Journal of Power Electronics
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• v.19 no.1
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• pp.220-233
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• 2019

This work aims to study and analyze the various operating modes of universal power converter which is powered by solar and thermoelectric generators. The proposed converter is operated in a DC-DC (buck or boost mode) and DC-AC (single phase) inverter with high efficiency. DC power sources, such as solar photovoltaic (SPV) panels, thermoelectric generators (TEGs), and Li-ion battery, are selected as input to the proposed converter according to the nominal output voltage available/generated by these sources. The mode of selection and output power regulation are achieved via control of the metal-oxide semiconductor field-effect transistor (MOSFET) switches in the converter through the modified stepped perturb and observe (MSPO) algorithm. The MSPO duty cycle control algorithm effectively converts the unregulated DC power from the SPV/TEG into regulated DC for storing energy in a Li-ion battery or directly driving a DC load. In this work, the proposed power sources and converter are mathematically modelled using the Scilab-Xcos Simulink tool. The hardware prototype is designed for 200 W rating with a dsPIC30F4011 digital controller. The various output parameters, such as voltage ripple, current ripple, switching losses, and converter efficiency, are analyzed, and the proposed converter with a control circuit operates the converter closely at 97% efficiency.

• Korean Management Science Review
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• v.29 no.1
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• pp.33-56
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• 2012

Domestic LCD TV market is composed of two groups of products produced by major firms and small and medium enterprises. The major companies make the price relatively high, but the other makes lower in the same sizes. The model of the low price products does not make consumers choice when they choose LCD TV. This makes the questions of capability between difference price products. The reason above mentioned, the firms that include group of comparatively lower price, are worried about not increasing sale because of prejudice. This study is to find any interrelationship and evaluate the efficiency between the products using performance, exterior and brand power of product. In order to do this, a hybrid AHP/DEA evaluation model for comparison/valuation of LCD TV products is developed. The proposed process is; first, to derive hierarchy structure of LCD TV evaluation criteria using axiomatic design, second, to calculate the score of each LCD TV product through AHP analysis including weight calculation of evaluation criteria, and last, to evaluate the efficiency of LCD TV product by applying DEA by defining product scores as output and prices as input. It concludes that the high price products shows good efficiency, but there are some products with good exterior and brand power, not performance, also presenting good efficiency.

• Journal of Mechanical Science and Technology
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• v.16 no.4
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• pp.454-467
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• 2002

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. Toidentifythelocation and depth of a crack in a structure, a method is presented in this paper which uses neuro-fuzzy-evolutionary technique, that is, Adaptive-Network-based Fuzzy Inference System (ANFIS) solved via hybrid learning algorithm (the back-propagation gradient descent and the least-squares method) and Continuous Evolutionary Algorithms (CEAs) solving sir ale objective optimization problems with a continuous function and continuous search space efficiently are unified. With this ANFIS and CEAs, it is possible to formulate the inverse problem. ANFIS is used to obtain the input(the location and depth of a crack) - output(the structural Eigenfrequencies) relation of the structural system. CEAs are used to identify the crack location and depth by minimizing the difference from the measured frequencies. We have tried this new idea on beam structures and the results are promising.

• Journal of electromagnetic engineering and science
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• v.14 no.1
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• pp.15-24
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• 2014

A compact dual-band three-way metamaterial power divider is proposed that has three in-phase outputs. Fully printed composite rightand left-handed (CRLH) unequal and equal power dividers are first implemented for 900-MHz and 2.4-GHz bands with the power-division ratios of 2:1 and 1:1, respectively. An initial 1:1:1 power divider is then achieved by incorporating the input of the two-way equal block into an output of the unequal block, and trimming the interconnection parameters. The condition of an identical phase at the three outputs of the power divider is then met by devising a hybrid CRLH phase-shift line to compensate for the different phase errors at the two frequencies. This scheme is confirmed by predicting the performance of the power divider with circuit analysis and full-wave simulation and measuring the fabricated prototype. They results show agreement; the in-phase outputs as well as the desirable power-division are accomplished and outdo the conventional techniques.

• Journal of Internet Computing and Services
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• v.17 no.5
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• pp.51-58
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• 2016

The unprecedented power of cloud computing (CC) that enables free sharing of confidential data records for further analysis and mining has prompted various security threats. Thus, supreme cyberspace security and mitigation against adversaries attack during data mining became inevitable. So, privacy preserving data mining is emerged as a precise and efficient solution, where various algorithms are developed to anonymize the data to be mined. Despite the wide use of generalized K-anonymizing approach its protection and truthfulness potency remains limited to tiny output space with unacceptable utility loss. By combining L-diversity and (${\alpha}$,k)-anonymity, we proposed a hybrid K-anonymity data relocation algorithm to surmount such limitation. The data relocation being a tradeoff between trustfulness and utility acted as a control input parameter. The performance of each K-anonymity's iteration is measured for data relocation. Data rows are changed into small groups of indistinguishable tuples to create anonymizations of finer granularity with assured privacy standard. Experimental results demonstrated considerable utility enhancement for relatively small number of group relocations.

• The Transactions of the Korean Institute of Power Electronics
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• v.25 no.1
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• pp.44-53
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• 2020

A bridgeless single-stage AC-DC converter for wireless power charging systems is proposed. This converter is composed of a PFC stage and a three-level hybrid DC-DC stage. The proposed converter can control the wide output voltage (200-450 V_DC) by the variable link voltage and the pulse-width voltage applied to the primary resonant circuit due to the phase-shifted modulation at a fixed switching frequency. Moreover, the input power factor and the total harmonic distortion can be improved by using the proposed converter. A 1 kW prototype was fabricated and validated through experimental results and analysis.