• Journal of Korea Multimedia Society
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• v.13 no.11
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• pp.1728-1738
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• 2010

Pyeon-gyeong, similar to Chinese Bianqing, is a Korean traditional lithophone with multiple stone chimes. Due to the temperature- and humidity-insensitive characteristics of its material, pumice stone, the instrument provides highly stable pitch and therefore has played a key role in Korean traditional court music. By reason of having absolute pitch, it is an important part of the research on the standard pitch and scale system of korean traditional music, but as an instrument, the study on the sound characteristics and worth is not making satisfactory progress, to date. This research is an analysis paper for physical modeling synthesis of pyeongyeong. Through this study, we will determine the original characteristics of the timbre of pyeongyeong as a unique korean traditional percussion, and investigate these characteristics objectively, based on the music acoustics by scientific analysis. Furthermore, this study will be used as an important basic material for physical modeling synthesis of pyeongyeong, and also make a huge contribution to the cultural applicability by the vitalization of graft onto the various artistic creation field, through the comprehension of the timbre of pyeongyeong as an instrument.

• 한국연소학회:학술대회논문집
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• 2001.11a
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• pp.169-178
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• 2001

Among the recent research ideas to reduce hydrocarbon emissions emitted from SI engines till light-off of catalyst since cold start are those exploiting non-thermal plasma technique and photo-catalyst that draws recent attention by virtue of its successful application to practical use to clean up the atmosphere using the feature of its relative independence on temperature. Based on the previous research results obtained with model exhaust gases using an experimental emissions reduction system that utilizes the non-thermal plasma and photo-catalyst technique, further investigation was conducted on a production N/A 1.5 liter DOHC engine during cold start to warm-up. For the effects of non-thermal plasma-photocatalyst combined reactor, 10% concentration reduction was achieved with the fuel component paraffins, and the large increase in non-fuel paraffinic components and acetylene concentrations were similar to those of base condition. However the absolute value was locally a bit higher than those of base condition since the products was made from the dissociation and decomposition of highly branched paraffins by plasma-photocatalyst reactor. Olefinic components were highly decomposed by about 75%, due to these excellent decompositions of olefins which have relatively high MIR values, and the SR value was 1.87 that is 30% reduction from that of base condition, then, the photochemical reactivity was lowered.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.27 no.6
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• pp.283-292
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• 2015

A model of apartment heating load in a district heating system could be useful in the management and utilization of energy resources, since it could predict energy usage and so could assist in the efficient use of energy resources. The heating load in a district heating system varies in a highly nonlinear manner and is subject to many different factors, such as heating area, number of people living in that complex, and ambient temperature. Thus there are few published papers with accurate models of heating load, especially in domestic literature. This work is concerned with the modeling of apartment heating load in a district heating system in winter, using the reduced least square support vector machine (LS-SVM), and with the purpose of using the model to predict heating energy usage in domestic city area. We collected 23,856 pieces of data on heating energy usage over a 12-week period in winter, from 12 heat exchangers in five apartments. Half of the collected data were used to construct the heating load model, and the other half were used to test the model's accuracy. The model was able to predict the heating energy usage pattern rather accurately. It could also estimate the usage of heating energy within of mean absolute percentage error. This implies that the model prediction accuracy needs to be improved further, but it still could be considered as an acceptable model if we consider the nonlinearity and uncertainty of apartment heating energy usage in a district heating system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.25-30
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• 2016

It is critical to forecast the maximum daily and monthly demand for power with as little error as possible for our industry and national economy. In general, long-term forecasting of power demand has been studied from both the consumer's perspective and an econometrics model in the form of a generalized linear model with predictors. Time series techniques are used for short-term forecasting with no predictors as predictors must be predicted prior to forecasting response variables and containing estimation errors during this process is inevitable. In previous researches, seasonal exponential smoothing method, SARMA (Seasonal Auto Regressive Moving Average) with consideration to weekly pattern Neuron-Fuzzy model, SVR (Support Vector Regression) model with predictors explored through machine learning, and K-means clustering technique in the various approaches have been applied to short-term power supply forecasting. In this paper, SARMA and intervention model are fitted to forecast the maximum power load daily, weekly, and monthly by using the empirical data from 2011 through 2013. $ARMA(2,\;1,\;2)(1,\;1,\;1)_7$ and $ARMA(0,\;1,\;1)(1,\;1,\;0)_{12}$ are fitted respectively to the daily and monthly power demand, but the weekly power demand is not fitted by AREA because of unit root series. In our fitted intervention model, the factors of long holidays, summer and winter are significant in the form of indicator function. The SARMA with MAPE (Mean Absolute Percentage Error) of 2.45% and intervention model with MAPE of 2.44% are more efficient than the present seasonal exponential smoothing with MAPE of about 4%. Although the dynamic repression model with the predictors of humidity, temperature, and seasonal dummies was applied to foretaste the daily power demand, it lead to a high MAPE of 3.5% even though it has estimation error of predictors.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.16 no.1
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• pp.159-170
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• 2013

The effect of climate change on urban woody plants remains difficult to predict in urban areas. Depending on its tolerances, a plant species may stay and survive or stay with slowly declining remnant populations under a changing climate. To predict those vulnerabilities on urban woody plants, this study suggests a basic bioclimatic envelop model of heat requirements, cold tolerance, chilling requirements and moisture requirements that are well documented as the 'climatic niche'. Each component of the 'climatic niche' is measured by the warmth index, the absolute minimum temperature, the number of chilling weeks and the water balance. Regarding the utility of the developed model, the selected urban plant's present probabilities are suggested in the future climate of Seoul. Both Korea and Japan's thermal thresholds are considered for a plant's optimal climatic niche. By considering the thermal thresholds of these two regions for the same species, the different responses observed will reflect the plant's 'hardening' process in a rising climate. The model illustrated that the subpolar plants Taxus cuspidata and Ulmus davidiana var. japonica are predicted to have low suitability in Seoul. The temperate plants Zelkova serrata and Pinus densiflora, which have a broad climatic niche, exhibited the highest present probability in the future. The subtropical plants Camellia japonica and Castanopsis cuspidata var. sieboldii may exhibit a modest growth pattern in the late 21C's future climatic period when an appropriate frost management scheme is offered. The model can be used to hypothesize how urban ecosystems could change over time. Moreover, the developed model can be used to establish selection guidelines for urban plants with high levels of climatic adaptability.

• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.218.1-218.1
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• 2014

In order to measure the absolute plasma density, various probes are proposed and investigated and microwave probes are widely used for its advantages (Insensitivity to thin non-conducting material deposited by processing plasmas, High reliability, Simple process for determination of plasma density, no complicate assumptions and so forth). There are representative microwave probes such as the cutoff probe, the hairpin probe, the impedance probe, the absorption probe and the plasma transmission probe. These probes utilize the microwave interactions with the plasma-sheath and inserted structure (probe), but frequency range used by each probe and specific mechanisms for determining the plasma density for each probe are different. In the recent studies, behaviors of each microwave probe with respect to the plasma parameters of the plasma density, the pressure (the collision frequency), and the sheath width is abundant and reasonably investigated, whereas relative diagnostic characteristics of the probes by a comparative study is insufficient in spite of importance for comprehensive applications of the probes. However, experimental comparative study suffers from spatially different plasma characteristics in the same discharge chamber, a low-reproducibility of ignited plasma for an uncertainty in external discharge parameters (the power, the pressure, the flow rate and so forth), impossibility of independently control of the density, the pressure, and the sheath width as well as expensive and complicate experimental setup. In this paper, various microwave probes are simulated by finite-different time-domain simulation and the error between the input plasma density in FDTD simulations and the measured that by the unique microwave spectrums of each probe is obtained under possible conditions of plasma density, pressure, and sheath width for general low-temperature plasmas. This result shows that the each probe has an optimum applicable plasma condition and reliability of plasma density measurement using the microwave probes can be improved by the complementary use of each probe.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.10
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• pp.6860-6868
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• 2015

In this study, we consider a problem of forecasting daily city gas demand of Korea. Forecasting daily gas demand is a daily routine for gas provider, and gas demand needs to be forecasted accurately in order to guarantee secure gas supply. In this study, we analyze the time series of city gas demand in several ways. Data analysis shows that primary factors affecting the city gas demand include the demand of previous day, temperature, day of week, and so on. Incorporating these factors, we developed a multiple linear regression model. Also, we devised a sampling procedure that selectively collects the past data considering the characteristics of the city gas demand. Test results on real data exhibit that the MAPE (Mean Absolute Percentage Error) obtained by the proposed method is about 2.22%, which amounts to 7% of the relative improvement ratio when compared with the existing method in the literature.

• Journal of Korean Society on Water Environment
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• v.25 no.6
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• pp.922-934
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• 2009

The transport of contaminants and spatial variation in a deep reservoir are certainly governed by the thermal structure of the reservoir. There has been continuous efforts to utilize three-dimensional (3D) hydrodynamic and water quality models for supporting reservoir management, but the efforts to validate the models performance using extensive field data were rare. The study was aimed to evaluate a 3D hydrodynamic model, ELCOM, in Daecheong Reservoir for simulating heat fluxes and stratification processes under hydrological years of 2001, 2006, 2008, and to assess the impact of internal wave on the reservoir mixing. The model showed satisfactory performance in simulating the water temperature profiles: the absolute mean errors at R3 (Hoenam) and R4 (Dam) sites were in the range of $1.38{\sim}1.682^{\circ}C$. The evaporative and sensible heat losses through the reservoir surface were maximum during August and January, respectively. The net heat flux ($H_n$) was positive from February to September, while the stratification formed from May and continued until September. Instant vertical mixing was observed in the reservoir during strong wind events at R4, and the model reasonably reproduced the mixing events. A digital low-pass filter and zero crossing method was used to evaluate the potential impact of wind-driven internal wave on the reservoir mixing. The results indicated that most of the wind events occurred in 2001, 2006, 2008 were not enough to develop persistent internal wave and effective mixing in the reservoir. ELCOM is a suitable 3D model for supporting water quality management of the deep and stratified reservoirs.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.6
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• pp.1556-1571
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• 1993

Nitrogen oxides ($NO_x$) are air pollutants which are generated from the combustion of fossil fuels. Stage combustion is an effective method to reduce $NO_x$ emissions. The effects of $NO_x$ reduction by stage combustion in a pilot scale combustor(6.6kW) have been investigated using propane gas flames laden with NH$_{3}$ as Fuel-N. The results in this study are follows; (1) $NO_x$ emissions are dependent on the reducing environment of fuel-rich zone regardless of total air ratio. The maximum $NO_x$ reduction is at the stoichiometric ratio of 0.8 to 0.9 in the reducing zone. (2) $NO_x$ reduction is maximum when burnout air is injected at the point where the oxygen in reducing zone is almost consumed. (3) $NO_x$ reduction is dependent upon the temperature of reducing zone with best effect above 950.deg. C in the reducing zone. (4) The fuel stage combustion is more effective to reduce $NO_x$ formation in the wide range of stoichiometric ratio than two stage combustion. (5) The results of this study could be utilized mainly in a design strategy for low $NO_x$ emission from the combustion of high fuel-nitrogen in energy sources ratio than as an indication of the absolute levels of $NO_x$ which can be achieved by stage combustion techniques in large scale facilities.

• Journal of Pharmaceutical Investigation
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• v.22 no.3
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• pp.197-204
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• 1992

A gas chromatographic method using nitrogen phosphorous selective detection was developed for simultaneous determination of haloperidol and its metabolite, reduced haloperidol, in human plasma. Combelen was used as internal standard, The method involved extraction and trimethylsilylation followed by the injection of $2-4\;{\mu}l$ of benzene layer, which was used to dissolve the trimethylsilylated derivatives of haloperidol and reduced haloperidol, onto SE-54 column [5% phenyl methyl silica fused capillary column, $16m{\times}0.22\;mm$ $(I.D.){\times}0.33\;{\mu}m$ (coated thickness)]. The temperature of column oven was programmed from $200^{\circ}C\;to\;300^{\circ}C$ at the increase rate of $10^{\circ}C/min and also the temperatures of injector and detector were set at $300^{\circ}C$. Helium was used as carrier gas and its flow rate was maintained at 30 ml/min. The detection was conducted with nitrogen phosphorous selective detector. The retention times for combelen, reduced haloperidol and haloperidol were found to be 9.14, 9.75 and 9.99 min, respectively. The detection limits for haloperidol and reduced haloperidol in human plasma were both 0.2 ng/ml. The coefficients of variation of the intra-assay were generally low (below 9.8%). The mean absolute recoveries of added haloperidol and reduced haloperidol from plasma were 72% and 84%, respectively. No interferences from endogenous substances were found.