• Asian Journal of Atmospheric Environment
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• v.10 no.2
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• pp.67-79
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• 2016

The forecasting of air pollution is an important and popular topic in environmental engineering. Due to health impacts caused by unacceptable particulate matter (PM) levels, it has become one of the greatest concerns in metropolitan cities like Karaj City in Iran. In this study, the concentration of $PM_{2.5}$ was predicted by applying a multilayer percepteron (MLP) neural network, a radial basis function (RBF) neural network and a Markov chain model. Two months of hourly data including temperature, NO, $NO_2$, $NO_x$, CO, $SO_2$ and $PM_{10}$ were used as inputs to the artificial neural networks. From 1,488 data, 1,300 of data was used to train the models and the rest of the data were applied to test the models. The results of using artificial neural networks indicated that the models performed well in predicting $PM_{2.5}$ concentrations. The application of a Markov chain described the probable occurrences of unhealthy hours. The MLP neural network with two hidden layers including 19 neurons in the first layer and 16 neurons in the second layer provided the best results. The coefficient of determination ($R^2$), Index of Agreement (IA) and Efficiency (E) between the observed and the predicted data using an MLP neural network were 0.92, 0.93 and 0.981, respectively. In the MLP neural network, the MBE was 0.0546 which indicates the adequacy of the model. In the RBF neural network, increasing the number of neurons to 1,488 caused the RMSE to decline from 7.88 to 0.00 and caused $R^2$ to reach 0.93. In the Markov chain model the absolute error was 0.014 which indicated an acceptable accuracy and precision. We concluded the probability of occurrence state duration and transition of $PM_{2.5}$ pollution is predictable using a Markov chain method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.1030-1033
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• 2002

In this study, it is important that we have an understanding of the metal flow for manufacturing condenser tube in porthole die extrusion, because this need to provide for household appliances market that is expected to grow into the major market of the cooling system hereafter. Condenser tube is mainly manufactured by conform exclusion. However, this method was not satisfied a series of the needs for manufacturing condenser tube as compared with porthole die extrusion. The deforming skill recently is required high-productivity, high-accuracy and reducing lead-time, thus it is essential to substitute conform exclusion by porthole die exclusion. Porthole die extrusion has many advantages such as improvement of productivity, reduction of production cost etc. In general, the porthole die extrusion process consists of three stages(dividing, welding and forming stages). In order to obtain the detailed mechanics, to assist in the design of proper die shapes and sizes, and to improve the quality of products, porthole die extrusion should be analyzed in as non-steady state as possible during the entire process to evaluate detailed metal flow, temperature distribution, welding pressure and extrusion lead, and therm stress analysis was practiced to obtain effective stress and elastic deformation value. A analytical results provide useful information the optimal design of the porthole die for condenser tube.

• Journal of the Korean Society of Tobacco Science
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• v.30 no.2
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• pp.117-124
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• 2008

A solid phase microextraction (SPME) method in combination with gas chromatography/mass spectrometric techniques was used for the extraction and quantification of 12 selected agrochemical residues in tobacco. The parameters such as the type of SPME fiber, adsorption/desorption time and the extraction temperature affecting the precision and accuracy of the SPME method were investigated and optimized. Among three types of fibers investigated, polyacrylate (PA), polydimethylsiloxane (PDMS) and polydimethylsiloxane-divinylbenzene (PDMS-DVB), PDMS fiber was selected for the extractions of the agrochemicals. The SPME device was automated and on-line coupled to a gas chromatograph with a mass spectrometer. Mass spectrometry (MS) was used and two different instruments, a quadrupole MS and triple quadrupole MS-MS mode, were compared. The performances of the two GC-MS instruments were comparable in terms of linearity (in the range of 0.01$\sim$0.5 $\mu$g/mL) and sensitivity (limits of detection were in the low ng/mL range). The triple quadrupole MS-MS instrument gave better precision than that of quadrupole MS system, but generally the relative standard deviations for replicates were acceptable for both instruments (< 15%). The LODs was fully satisfied the requirements of the CORESTA GRL. Recoveries of 12 selected agrochemicals in tobacco yielded more than 80% and reproducibility was found to be better than 10% RSD so that SPME procedure could be applied to the quantitative analysis of agrochemical residues in tobacco.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.87-90
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• 2005

The FORMOSAT-3/COSMIC mission is a micro satellite mission to deploy a constellation of six micro satellites at low Earth orbits. The final mission orbit is of an altitude of 750-800 lan. It is a collaborative Taiwan-USA science experiment. Each satellite consists of three science payloads in which the GPS occultation experiment (GOX) payload will collect the GPS signals for the studies of meteorology, climate, space weather, and geodesy. The GOX onboard FORMOSAT -3 is designed as a GPS receiver with 4 antennas. The fore and aft limb antennas are installed on the front and back sides, respectively, and as well as the two precise orbit determination (POD) antennas. The precise orbit information is needed for both the occultation inversion and geodetic research. However, the instrument associated errors, such as the antenna phase center offset and even the different cable delay due to the geometric configuration of fore- and aft-positions of the POD antennas produce error on the orbit. Thus, the focus of this study is to investigate the impact of POD antenna parameter on the determination of precise satellite orbit. Furthermore, the effect of the accuracy of the determined satellite orbit on the retrieved atmospheric and ionospheric parameters is also examined. The CHAMP data, the FORMOSAT-3 satellite and orbit parameters, the Bernese 5.0 software, and the occultation data processing system are used in this work. The results show that 8 cm error on the POD antenna phase center can result in ~8 cm bias on the determined orbit and subsequently cause 0.2 K deviation on the retrieved atmospheric temperature at altitudes above 10 lan.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1156-1156
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• 2001

This work aimed to prove the feasibility of NIR spectroscopy to detect vegetable protein isolates (soy, pea and wheat) in milk powder. Two hundred and thirty-nine samples of genuine and adulterated milk powder (NIZO, Ede, NL) were analysed by NIRS using an InfraAlyzer 500 (Bran+Luebbe). NIR spectra were collected at room temperature, and data were processed by using Sesame Software (Bran+Luebbe). Separated calibrations for each non-milk protein added, in the range of 0-5%, were calculated. NIR data were processed by using Sesame Software (Bran+Luebbe). Prediction and validation were made by using a set of samples not included into the calibration set. The best calibrations were obtained by the PLSR. The type of data pre-treatment (normalisation, 1$\^$st/ derivative, etc..) was chosen to optimize the calibration parameters. NIRS technique was able to predict with good accuracy the percentage of each vegetable protein added to milk powder (soy: R$^2$ 0.994, SEE 0.193, SEcv 0.301, RMSEPall 0.148; pea: R$^2$ 0.997, SEE 0.1498, SEcv 0.207, RMSEPall 0.148, wheat: R$^2$ 0.997, SEE 0.1418, SEcv 0.335, RMSEPall 0.149). Prediction results were compared to those obtained using other two techniques: capillary electrophoresis and competitive ELISA. On the basis of the known true values of non-vegetable protein contents, the NIRS was able to determine more accurately than the other two techniques the percentage of adulteration in the analysed samples.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.3
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• pp.1488-1494
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• 2011

In this paper, we propose an algorithm using linear regression model that forecasts the demand of heated water in winter. To supply heated water to apartments, stores and office buildings, Korea District Heating Corp.(KDHC) operates boilers including electric power generators. In order to operate facilities generating heated water economically, it is essential to forecast daily demand of heated water with accuracy. Analysis of history data of Kangnam Branch of KDHC in 2006 and 2007 reveals that heated water supply on previous day as well as temperature are the most important factors to forecast the daily demand of heated water. When calculated by the proposed regression model, mean absolute percentage error for the demand of heated water in winter of the year 2006 through 2009 does not exceed 3.87%.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.6
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• pp.1235-1240
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• 2019

It is well known that the ground water level changes rapidly before and after the earthquake, and the variation of ground water level prediction is used to predict the earthquake. In this paper, we predict the ground water level in Miryang City using ANFIS algorithm for earthquake prediction. For this purpose, this paper used precipitation and temperature acquired from National Weather Service and data of underground water level from Rural Groundwater Observation Network of Korea Rural Community Corporation which is installed in Miryang city, Gyeongsangnam-do. We measure the prediction accuracy using RMSE and MAPE calculation methods. As a result of the prediction, the periodic pattern was predicted by natural factors, but the change value of ground water level was changed by other variables such as artificial factors that was not detected. To solve this problem, it is necessary to digitize the ground water level by numerically quantifying artificial variables, and to measure the precipitation and pressure according to the exact location of the observation ball measuring the ground water level.

• Journal of the Korean earth science society
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• v.24 no.6
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• pp.533-548
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• 2003

The prevailing wind phenomenon around Pohang in winter was investigated by using surface and vertical observatory datas and a numerical simulation was carried out to analyse this phenomenon using RAMS. Direction of the prevailing wind was westerly at upper atmosphere. However, near the surface, southwestern wind prevailed in winter. Using the RAMS to simulate a winter wind system numerically, it was found out that this phenomenon was strongly affected by the geographical features such as directions of coastline and low level valley, and distributions of land and sea. To investigate the accuracy of the model results, wind speed, temperature and wind direction of typical continuous southwestern wind occurring days were compared with observation data. Analyzing the characteristics of local circulation system was very hard because of horizontally sparse observation data. But from the result above, a numerical simulation using the RAMS, which satisfies the spatial high resolution, will provide more accurate results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.4
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• pp.948-953
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• 2015

Recently, the finger vein recognition based on NIR and CCD sensor camera is investigating the technology to identify a personal using by biometrics. The performance difference of finger vein recognition is generated according to methods that are to separate the vein and background from noises such as finger thickness, ambient light, skin temperature, etc. To improve these problems, in this study, we are proposing the methods for rotation, ROI extraction, and enhancement of vein image captured by NIR LED and CCD camera, and were evaluated performances of these methods. In results of the experiment, the accuracy of the proposed method for image rotation and ROI extraction was 99.8%. And the proposed filter bank method in vein enhancement has shown better performance than retinex algorithm. The proposed method for results of these experimentations will provide better recognition rate when applied to the preprocessing of finger vein recognition.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.3
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• pp.493-507
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• 2018

Due to high spatio-temporal variability of amount and optical/microphysical properties of atmospheric aerosols, satellite-based observations have been demanded for spatiotemporal monitoring the major aerosols. Observations of the heavy aerosol episodes and determination on the dominant aerosol types from a geostationary satellite can provide a chance to prepare in advance for harmful aerosol episodes as it can repeatedly monitor the temporal evolution. A new geostationary observation sensor, namely the Advanced Himawari Imager (AHI), onboard the Himawari-8 platform, has been observing high spatial and temporal images at sixteen wavelengths from 2016. Using observed spectral visible reflectance and infrared brightness temperature (BT), the algorithm to find major aerosol type such as volcanic ash (VA), desert dust (DD), polluted aerosol (PA), and clean aerosol (CA), was developed. RGB color composite image shows dusty, hazy, and cloudy area then it can be applied for comparing aerosol detection product (ADP). The CALIPSO level 2 vertical feature mask (VFM) data and MODIS level 2 aerosol product are used to be compared with the Himawari-8/AHI ADP. The VFM products can deliver nearly coincident dataset, but not many match-ups can be returned due to presence of clouds and very narrow swath. From the case study, the percent correct (PC) values acquired from this comparisons are 0.76 for DD, 0.99 for PA, 0.87 for CA, respectively. The MODIS L2 Aerosol products can deliver nearly coincident dataset with many collocated locations over ocean and land. Increased accuracy values were acquired in Asian region as POD=0.96 over land and 0.69 over ocean, which were comparable to full disc region as POD=0.93 over land and 0.48 over ocean. The Himawari-8/AHI ADP algorithm is going to be improved continuously as well as the validation efforts will be processed by comparing the larger number of collocation data with another satellite or ground based observation data.