• Journal of the Korean earth science society
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• v.36 no.3
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• pp.210-221
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• 2015

The terrain features and surface characteristics are the most important elements not only in meteorological modeling but also in air quality modeling. The diurnal evolution of local climate over complex terrain may be significantly controlled by the ground irregularities. Such topographic features can affect a thermally driven flow, either directly by causing changes in the wind direction or indirectly, by inducing significant variations in the ground temperature. Over a complex terrain, these variations are due to the nonuniform distribution of solar radiation, which is highly determined by the ground geometrical characteristics, i.e. slope and orientation. Therefore, the accuracy of prediction of regional scale circulation is strong associated with the accuracy of land-use and topographic information in meso-scale circulation assessment. The objective of this work is a numerical simulation using MM5-A2C model with the detailed topography and land-use information as the surface boundary conditions of the air flow field in mountain regions. Meteorological conditions estimated by MM5-A2C command a great influence on the dispersion of mountain areas with the reasonable feature of topography where there is an important difference in orographic forcing.

• Korean Journal of Food Science and Technology
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• v.20 no.1
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• pp.6-12
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• 1988

To improve the individual packaging method and extend the shelf life of mackerel (Scomber japonicus), salted and unsalted mackerel fillets were packaged in laminated plastic film bag (Nylon/PE: $20{\mu}m/40{\mu}m,\;12{\times}15$ cm) filled with $CO_2$ gas, in vacuum, and stored at O and/or $5^{\circ}C$. The other samples were packaged in plastic foam trays, overwrapped with oxygen permeable film (control), and stored at same temperature. Volatile basic nitrogen (VBN), trimethylamine (TMA), histamine (HM) and viable cell counts (VCC) were progressed with the increasing of storage time, but thiobarbituric acid (TBA) values decreased gradually after reaching at a maximum peak in 5-9 days. Judging from 4 chemical components, VBN was the most available component in quality judgement of mackerel fillets and its upper limiting content was 25 mg%. Regression equation for shelf life prediction of mackerel fillets with sensory evaluation and VBN component was determined.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.260-266
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• 2009

Non-revenue water reduction(NRW) technologies are implemented to evaluate and manage leakages scientifically in water distribution systems under local governments. A development of quantitative leakage indicator by measuring minimum night flow, pressure control policy by installation of PRV(pressure reducing valve) and the establishment of leakage prevention schemes by residual life modeling of deteriorated water pipes are reviewed and studied. Estimation models of allowable leakage are developed by measuring and analyzing minimum night flow at residential and commercial area in Nonsan city, which is suggested from UK water industry and can improve an existing leakage indicator for the evaluation of non-revenue water. Also, pressure control method is applied and analyzed to Uti distribution area in Sacheon city in the operation aspect. As results, $466\;m^3/day$ of leakage can be reduced and it is expected that 113million won of annual cost can be saved. In the part of corrosion velocity and residual life assessment, non-linear prediction models of residual thickness are proposed by assessment of corrosion velocity based on exposure years, soil and water quality etc., since the deteriorated water pipe play a major role to increase leakage. It is expected that collection data and analyzing results can be applied effectively and positively to reduce non-revenue water by accumulating surveying data and verifying the results in the business field of water distribution systems under local governments.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1161-1161
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• 2001

Rapid cost-effective methods of measuring wood quality are extremely important to tree improvement programs where it is necessary to test large numbers of trees. Non-destructive sampling of a forest can be achieved by using increment cores generally removed at breast height. At CSIRO Forestry and Forest Products methods for the rapid, non-destructive measurement of wood properties and wood chemistry based on increment core samples have been developed. In this paper the application of near infrared (NIR) spectroscopy to the prediction of a range solid wood properties, including density, longitudinal modulus of elasticity (E$\sub$L/) and microfibril angle (MFA), is described. Experiments conducted on individual species (Eucalyptus delegatensis and Pinus radiata), the two species combined and a number of mixed species from several genera are reported. NIR spectra were obtained from the radial/longitudinal face of each sample and used to develop calibrations for the measured physical properties. When the individual species were used the relationships between laboratory determined data and NIR fitted data were good in all cases. Coefficients of determination (R$^2$) ranging from 0.77 for MFA to 0.93 for stick density were obtained for E. delegatensis and R$^2$ ranging from 0.68 for MFA to 0.94 for strip density were obtained for P. radiata. The calibration statistics for the combined E. delegatensis and P. radiata samples were similar to those found for the individual species. As these results indicated that it might be possible to produce general calibrations based on samples from a number of species of a single genus or samples from a number of different genera, a wide range of species was subsequently tested. Good relationships were obtained for both density and E$\sub$L/. These calibrations had R$^2$ that were slightly lower than those determined using individual species and standard errors that were higher. The mixed species calibrations, when applied to the E. delegatensis and P. radiata sample sets, provided good estimates of density (stick and strip) and E$\sub$L/. The results demonstrated that a mixed species calibration, that encompasses wide variation in terms of, wood anatomy, chemistry and physical properties, could be used to rank trees. Experiments reported in this paper demonstrate that solid wood properties can be estimated by NIR spectroscopy. The method offers a rapid and non-destructive alternative to traditional methods of analysis and is applicable to large-scale non-destructive forest resource assessment, and to tree breeding and silvicultural programs.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1061-1061
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• 2001

The scope of precision agriculture is to reach the put up cultivation goals by adjusting inputs as precise as possible after what is required by the soil and crop potentials, on a high spatial resolution. Consequently, precision agriculture is also often called site specific agriculture. Regulation of field inputs “on the run” has been made possible by the GPS (Geographical Position System)-technology, which gives the farmer his exact real time positioning in the field. The general goal with precision agriculture is to apply inputs where they best fill their purpose. Thus, resources could be saved, and nutrient losses as well as the impact on the environment could be minimized without lowering total yields or putting product quality at risk. As already indicated the technology exists to regulate the input based on beforehand decisions. However, the real challenge is to provide a reliable basis for decision-making. To support high spatial resolution, extensive sampling and analysis is required for many soil and plant characteristics. The potential of the NIR-technology to provide rapid, low cost analyses with a minimum of sample preparation for a multitude of characteristics therefore constitutes a far to irresistible opportunity to be un-scrutinized. In our work we have concentrated on soil-analysis. The instrument we have used is a Bran Lubbe InfraAlyzer 500 (1300-2500 nm). Clay- and organic matter-contents are soil constituents with major implications for most properties and processes in the soil system. For these constituents we had a 3000-sample material provided. High performance models for the agricultural areas in Sweden have been constructed for clay-content, but a rather large reference material is required, probably due to the large variability of Swedish soils. By subdividing Sweden into six areas the total performance was improved. Unfortunately organic matter was not as easy to get at. Reliable models for larger areas could not be constructed. However, through keeping the mineral fraction of the soil at minimal variation good performance could be achieved locally. The influence of a highly variable mineral fraction is probably one of the reasons for the contradictory results found in the literature regarding organic matter content. Tentative studies have also been performed to elucidate the potential performance in contexts with direct operational implications: lime requirement and prediction of plant uptake of soil nitrogen. In both cases there is no definite reference method, but there are numerous indirect, or indicator, methods suggested. In our study, field experiments where used as references and NIR was compared with methods normally used in Sweden. The NIR-models performed equally or slightly better as the standard methods in both situations. However, whether this is good enough is open for evaluation.

• Atmosphere
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• v.25 no.2
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• pp.221-233
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• 2015

Pollen is closely related to health issues such as allergenic rhinitis and asthma as well as intensifying atopic syndrome. Information on current and future spatio-temporal distribution of allergenic pollen is needed to address such issues. In this study, the Community Multiscale Air Quality Modeling (CMAQ) was utilized as a base modeling system to forecast pollen dispersal from oak trees. Pollen emission is one of the most important parts in the dispersal modeling system. Areal emission factor was determined from gridded areal fraction of oak trees, which was produced by the analysis of the tree type maps (1:5000) obtained from the Korea Forest Service. Daily total pollen production was estimated by a robust multiple regression model of weather conditions and pollen concentration. Hourly emission factor was determined from wind speed and friction velocity. Hourly pollen emission was then calculated by multiplying areal emission factor, daily total pollen production, and hourly emission factor. Forecast data from the KMA UM LDAPS (Korea Meteorological Administration Unified Model Local Data Assimilation and Prediction System) was utilized as input. For the verification of the model, daily observed pollen concentration from 12 sites in Korea during the pollen season of 2014. Although the model showed a tendency of over-estimation in terms of the seasonal and daily mean concentrations, overall concentration was similar to the observation. Comparison at the hourly output showed distinctive delay of the peak hours by the model at the 'Pocheon' site. It was speculated that the constant release of hourly number of pollen in the modeling framework caused the delay.

• Atmosphere
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• v.28 no.1
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• pp.99-112
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• 2018

In this study, the accuracy of ocean analysis data, which are produced from the Korea Meteorological Administration (KMA) Nucleus for European Modelling of the Ocean/Variational Data Assimilation (NEMO/NEMOVAR, hereafter NEMO) system and the HYbrid Coordinate Ocean Model/Navy Coupled Ocean Data Assimilation (HYCOM/NCODA, hereafter HYCOM) system, was evaluated using various oceanic observation data from March 2015 to February 2016. The evaluation was made for oceanic thermal environments in the tropical Pacific, the western North Pacific, and the Korean peninsula. NEMO generally outperformed HYCOM in the three regions. Particularly, in the tropical Pacific, the RMSEs (Root Mean Square Errors) of NEMO for both the sea surface temperature and vertical water temperature profile were about 50% smaller than those of HYCOM. In the western North Pacific, in which the observational data were not used for data assimilation, the RMSE of NEMO profiles up to 1000 m ($0.49^{\circ}C$) was much lower than that of HYCOM ($0.73^{\circ}C$). Around the Korean peninsula, the difference in RMSE between the two models was small (NEMO, $0.61^{\circ}C$; HYCOM, $0.72^{\circ}C$), in which their errors show relatively big in the winter and small in the summer. The differences reported here in the accuracy between NEMO and HYCOM for the thermal environments may be attributed to horizontal and vertical resolutions of the models, vertical coordinate and mixing scheme, data quality control system, data used for data assimilation, and atmosphere forcing. The present results can be used as a basic data to evaluate the accuracy of NEMO, before it becomes the operational model of the KMA providing real-time ocean analysis and prediction data.

• The Korean Journal of Applied Statistics
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• v.28 no.6
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• pp.1275-1288
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• 2015

A microscale weather analysis module (about 1km or less) is a microscale numerical weather prediction model designed for operational forecasting and atmospheric research needs such as radiant energy, thermal energy, and humidity. The accuracy of the module is directly related to the usefulness and quality of real-time microscale weather information service in the metropolitan area. This paper suggests an object based verification method useful for spatio-temporal evaluation of the accuracy of the microscale weather analysis module. The method is a graphical method comprised of three steps that constructs a lattice field of evaluation statistics, merges and identifies objects, and evaluates the accuracy of the module. We develop lattice fields using various evaluation spatio-temporal statistics as well as an efficient object identification algorithm that conducts convolution, masking, and merging operations to the lattice fields. A real data application demonstrates the utility of the verification method.

• 한국신재생에너지학회:학술대회논문집
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• 2011.05a
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• pp.127.1-127.1
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• 2011

In this paper, ZnO:Al thin films with c-axis preferred orientation were prepared on Soda lime glass substrates by RF magnetron sputtering technique. AZO thin film were prepared in order to clarify optimum conditions for growth of the thin film depending upon process, and then by changing a number of deposition conditions and substrate temperature conditions variously, structural and electrical characteristics were measured. For the manufacture of the AZO were vapor-deposited in the named order. It is well-known that post-annealing is an important method to improve crystal quality. For the annealing process, the dislocation nd other defects arise in the material and adsorption/decomposition occurs. The XRD patterns of the AZO films deposited with grey theory prediction design, annealed in a vacuum ambient($2.0{\times}10-3$Torr)at temperatures of 200, 300, 400 and $500^{\circ}C$ for a period of 30min. The diffraction patterns of all the films show the AZO films had a hexagonal wurtzite structure with a preferential orientation along the c-axis perpendicular to the substrate surface. As can be seen, the (002)peak intensities of the AZO films became more intense and sharper when the annealing temperature increased. On the other hand, When the annealing temperature was $500^{\circ}C$ the peak intensity decreased. The surface morphologies and surface toughness of films were examined by atomic force microscopy(AFM, XE-100, PSIA). Electrical resistivity, Gall mobility and carrier concentration were measured by Hall effect measuring system (HL5500PC, Accent optical Technology, USA). The optical absorption spectra of films in the ultraviolet-visibleinfrared( UV-Vis-IR) region were recorder by the UV spectrophotometer(U-3501, Hitachi, Japan). The resistivity, carrier concentration, and Hall mobility of ZnS deposited on glass substrate as a function of post-annealing.

• Journal of Biosystems Engineering
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• v.43 no.2
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• pp.148-159
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• 2018

Purpose: Unmanned air vehicle (UAV) remote sensing was applied to test various vegetation indices and make prediction models of protein content of rice for monitoring grain quality and proper management practice. Methods: Image acquisition was carried out by using NIR (Green, Red, NIR), RGB and RE (Blue, Green, Red-edge) camera mounted on UAV. Sampling was done synchronously at the geo-referenced points and GPS locations were recorded. Paddy samples were air-dried to 15% moisture content, and then dehulled and milled to 92% milling yield and measured the protein content by near-infrared spectroscopy. Results: Artificial neural network showed the better performance with $R^2$ (coefficient of determination) of 0.740, NSE (Nash-Sutcliffe model efficiency coefficient) of 0.733 and RMSE (root mean square error) of 0.187% considering all 54 samples than the models developed by PR (polynomial regression), SLR (simple linear regression), and PLSR (partial least square regression). PLSR calibration models showed almost similar result with PR as 0.663 ($R^2$) and 0.169% (RMSE) for cloud-free samples and 0.491 ($R^2$) and 0.217% (RMSE) for cloud-shadowed samples. However, the validation models performed poorly. This study revealed that there is a highly significant correlation between NDVI (normalized difference vegetation index) and protein content in rice. For the cloud-free samples, the SLR models showed $R^2=0.553$ and RMSE = 0.210%, and for cloud-shadowed samples showed 0.479 as $R^2$ and 0.225% as RMSE respectively. Conclusion: There is a significant correlation between spectral bands and grain protein content. Artificial neural networks have the strong advantages to fit the nonlinear problem when a sigmoid activation function is used in the hidden layer. Quantitatively, the neural network model obtained a higher precision result with a mean absolute relative error (MARE) of 2.18% and root mean square error (RMSE) of 0.187%.