• ETRI Journal
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• v.45 no.4
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• pp.650-665
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• 2023

A novel smart metering technique capable of anomaly detection was proposed for real-time home power management system. Smart meter data generated in real-time were obtained from 900 households of single apartments. To detect outliers and missing values in smart meter data, a deep learning model, the autoencoder, consisting of a graph convolutional network and bidirectional long short-term memory network, was applied to the smart metering technique. Power management based on the smart metering technique was executed by multi-objective optimization in the presence of a battery storage system and an electric vehicle. The results of the power management employing the proposed smart metering technique indicate a reduction in electricity cost and amount of power supplied by the grid compared to the results of power management without anomaly detection.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.51-56
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• 2006

Biases embedded in numerical weather precipitation forecasts by the RDAPS model was determined, quantified and corrected. The ultimate objective is to eventually enhance the reliability of reservoir operation by Korean Water Resources Corporation (KOWACO), which is based on precipitation-driven forecasts of stream flow. Statistical post-processing, so called MOS (Model Output Statistics) was applied to RDAPS to improve their performance. The Artificial Neural Nwetwork (ANN) model was applied for 4 cases of 'Probability of Precipitation (PoP) for wet and dry season' and 'Quantitative Precipitation Forecasts (QPF) for wet and dry season'. The reduction on the large systematic bias was especially remarkable. The performance of both networks may be improved by retraining, probably every month. In addition, it is expected that performance of the networks will improve once atmospheric profile data are incorporated in the analysis. The key to the optimal performance of ANN is to have a large data set relevant to the predictand variable. The more complex the process to be modeled by the ANN, the larger the data set needs to be.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1994.10a
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• pp.288-294
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• 1994

A study of prediction and qualification techniques for structure borne booming noise is presented in this paper. Result from acoustic normal mode finite element analysis of a 1/2 size vehicle cavity sample model is compared to the that from an experiment. Coupled structural-acoustic analysis is performed on a 1/4 size vehicle cavity sample model surrounded by 2 mm thick normal steel plates. Interior noise levels around passensger's ear position are predicted and reduced by structural modification based on panel participation factor analysis about the sample cavity model. Futhermore, optimization technique in application of anti-vibration pad is studied.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.698-700
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• 2003

This paper presents a model and analysis techniques for a unilateral external fixator to achieve fracture reduction and deformity correction in long bones precisely. through fixator joint adjustment. Combining the kinematic analysis with a graphic model of the tibia and the fixator allowed 3D simulation and visualization of the adjustments required to reduce fracture or correct bone deformity after osteotomy. The model and analysis technique can be used for fixator evaluation and clinical application planning.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.4
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• pp.583-589
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• 1987

A new approximation method is proposed for the linear model reduction of high order dynamic systems. This mehtod is based upon the denominator table(D-table) and time moment-matching technique. The denominator table(D-table) is used to obtain the denominator polynomial of reduced-order model, and the numerator polynomial is obtained by time moment-matching method. This proposed method does not require the calculation of the alpha-beta expansion and reciprocal transformation which should be calculadted by Routh approximation method. The advantages of the proposed method are that it is computationally every attractive better than Routh approximation method and the reduced model is stable Il the original system is stable.

• Journal of Korea Multimedia Society
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• v.22 no.7
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• pp.749-758
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• 2019

This paper proposes a data augmentation algorithm to improve the performance of DNN(Deep Neural Network) based speech enhancement. Many deep learning models are exploring algorithms to maximize the performance in limited amount of data. The most commonly used algorithm is the data augmentation which is the technique artificially increases the amount of data. For the effective data augmentation algorithm, we used a formant enhancement method that assign the different weights to the formant frequencies. The DNN model which is trained using the proposed data augmentation algorithm was evaluated in various noise environments. The speech enhancement performance of the DNN model with the proposed data augmentation algorithm was compared with the algorithms which are the DNN model with the conventional data augmentation and without the data augmentation. As a result, the proposed data augmentation algorithm showed the higher speech enhancement performance than the other algorithms.

• KIEAE Journal
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• v.14 no.6
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• pp.65-73
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• 2014

Due to the Climate change and resource shortage by global warming, various problems are rising and getting worse around the world. Many countries are doing the considerable efforts to reduce greenhouse gas emissions. The government of South Korea also plans to decrease greenhouse gas emission, the various pilot projects are underway, which includes obligation of energy efficiency 1st rating and greenhouse gas target management system of public buildings. In particular, luxurious government office buildings and energy-wasting public building have issued and emerged as a social problem. Energy efficiency improvement of the existing public office buildings are becoming an important issue recently. This study is proposed the step-by-step energy improvement model according to the building energy efficiency rate in order to reduce the energy consumption. To attain this end, I set up a base model by analyzing the current architectural conditions of the existing public office buildings and grasped the specific properties of building energy consumption through energy simulations. Furthermore, I suggested phased reduction prototypes for the reduction target of energy consumption by applying the methods of the zero energy building plan. This study is expecting that prototypes would give directions when it comes to planning the implementation policy of phased building plan factors, according the building energy consumption reduction goal in the existing public office buildings which are the subject of building energy target management system.

• Journal of Korean Society of Water and Wastewater
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• v.35 no.2
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• pp.113-120
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• 2021

High voltage impulse (HVI) has been gained attention as an alternative technique that could control the CaCO₃ scale problems encountered in water main, pipe, cooling tower and heat exchanger vessels. The aim of this study was to investigate the effect of electric field (E) and contact time (t) of HVI on reduction of Ca²⁺ concentration at two different temperatures of 25℃ and 60℃. A kinetic model on the effect of E and t was investigated too. As the E and t increased, the Ca²⁺ concentration decreased more than that of the control (= no HVI). The Ca²⁺ concentration decreased up to 81% at 15 kV/cm at 60℃, which was nearly 2 times greater than the control. With these experimental data-set of reduction of Ca²⁺ concentration under different E and t, the kinetic model was developed. The relationship between E and t required to reduce the concentration of Ca²⁺ by 30% was modeled at each temperature. The empirical model equations were; E^0.83· t = 60.3 at 25℃ and E^0.08· t = 1.1 at 60℃. These equations state the products of Eⁿ and t is always constant, which means that the required contact time can be reduced in accordance with the increment of E and vice versa.

• Geosystem Engineering
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• v.21 no.6
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• pp.335-343
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• 2018

Alkali-surfactant polymer flooding has become an important technique to improve oil recovery following the development of oil fields while the function of emulsification in enhanced oil recovery is rarely considered in the existing mathematical model for numerical simulation. In this paper, the mechanism of improving the recovery of the emulsification was analyzed in ASP flooding, and a relatively perfect mathematical model with deep filtration-theory was established, in which oil-water volume equation, saturation equation, viscosity equation, and permeability reduction equation are included. The new model is used to simulate the actual block of an oil field; the simulated results of the new model and an old model without considering the emulsification are compared with the actual well history. It is found that new model which is easy to be realized in numerical simulation has a high precision fitting, and the effect of adding oil and decreasing water is obvious. The sensitivity of emulsification was analyzed, and the results show that the water reducing funnel becomes wider and the rate of water cut decreases rapidly with the increase of emulsifying capacity, and then the rate of recovery slows down. The effect of increasing oil and decreasing water is better, and the degree of recovery increases. The emulsification of the ASP flooding is maintained at a moderate level, which corresponds to ${\Phi}=0.2$ in the new model, and the emulsification is applied to realize the general mathematical quantitative description, so as to better guide the oilfield development.

• Communications for Statistical Applications and Methods
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• v.18 no.2
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• pp.219-227
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• 2011

In this paper, we proposed a generalized bivariate negative binomial distribution allowing heterogeneous dispersions on two dependent variables based on a trivariate reduction technique. In this model, we propose the score and LR tests for testing the equality of dispersions and compare the efficiencies of the proposed tests using a Monte Carlo study. The Monte Carlo study shows that the proposed score and LR tests prove to be an efficient test for the equality of dispersions in the view of the significance level and power. However, the score test is easier to compute than the LR test and it shows a slightly better performance than the LR test from the Monte Carlo study, we suggest the use of score tests for testing the equality of dispersions on two dependent variables. In addition, an empirical example is provided to illustrate the results.