The author conducted a records research named 'daily life and records.' The purpose of the research was to find an archive, if possible, that would be effective in promoting exchange and cooperation among people in their daily lives, and to distinguish what type of archive it would be, as well as how to let it naturally take place in their ordinary lives. For 4 months (August-December 2019) with 100 college students in their 20s, trial and error were repeated. There was no separate laboratory for the research, and it used regular school hours at universities. Although it is true that there was a control through power by the college system, the plot was centered on the sunshine policy. To human being there is a voluntary and positive attitude. If anyone begins to take this attitude it is difficult to stop such action. Through emotional support, this voluntary action was encouraged to take root. The experiment was an attempt to doubt the obvious, and to search for something new. From afar, this may seem irrelevant to archives. However, for the author who is a professional archivist, it was a time of records through control by Records principles. By organizing into a form of story, its archival implications are observed.
Journal of the Korean Association of Geographic Information Studies
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v.15
no.1
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pp.197-210
/
2012
The KOrea Multi-Purpose SATellite(KOMPSAT)-2 has a capability to provide a cross-track stereo imagery using two different orbits for generating various spatial information. However, in order to fully realize the potential of the KOMPSAT-2 stereo imagery in terms of mapping, various tests are necessary. The purpose of this study is to evaluate the possibility of mapping using the KOMPSAT-2 stereo imagery. For this, digital plotting was conducted based on the stereoscopic images. Also the Digital Elevation Model(DEM) and an ortho-image were generated using digital plotting results. An accuracy of digital plotting, DEM, and ortho-image were evaluated by comparing with the existing data. Consequently, we found that horizontal and vertical error of the modeling results based on the Rational Polynomial Coefficient(RPC) was less than 1.5 meters compared with the Global Positioning System(GPS) survey results. The maximum difference of vertical direction between the plotted results in this study and the existing digital map on the scale of 1/5,000 was more than 5 meters according as the topographical characteristics. Although there were some irregular parallax on the images, we realized that it was possible to interpret and plot at least seventy percent of the layer which was required the digital map on the scale of 1/5,000. Also an accuracy of DEM, which was generated based on the digital plotting, was compared with the existing LiDAR DEM. We found that the ortho-images, which were generated using the extracted DEM in this study, sufficiently satisfied with the requirement of the geometric accuracy for an ortho-image map on the scale of 1/5,000.
Journal of Korean Society for Geospatial Information Science
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v.24
no.1
/
pp.89-98
/
2016
In this paper, we proposed an automated areal feature matching method based on geometric similarity without user intervention and is applied into areal features of many-to-many relation, for confusion of spatial data-sets of different scale and updating cycle. Firstly, areal feature(node) that a value of inclusion function is more than 0.4 was connected as an edge in adjacency matrix and candidate corresponding areal features included many-to-many relation was identified by multiplication of adjacency matrix. For geometrical matching, these multiple candidates corresponding areal features were transformed into an aggregated polygon as a convex hull generated by a curve-fitting algorithm. Secondly, we defined matching criteria to measure geometrical quality, and these criteria were changed into normalized values, similarity, by similarity function. Next, shape similarity is defined as a weighted linear combination of these similarities and weights which are calculated by Criteria Importance Through Intercriteria Correlation(CRITIC) method. Finally, in training data, we identified Equal Error Rate(EER) which is trade-off value in a plot of precision versus recall for all threshold values(PR curve) as a threshold and decided if these candidate pairs are corresponding pairs or not. To the result of applying the proposed method in a digital topographic map and a base map of address system(KAIS), we confirmed that some many-to-many areal features were mis-detected in visual evaluation and precision, recall and F-Measure was highly 0.951, 0.906, 0.928, respectively in statistical evaluation. These means that accuracy of the automated matching between different spatial data-sets by the proposed method is highly. However, we should do a research on an inclusion function and a detail matching criterion to exactly quantify many-to-many areal features in future.
Background: Studying the ecosystem carbon cycle requires analysis of interrelationships between soil respiration (Rs) and the environment to evaluate the balance. Various methods and instruments have been used to measure Rs. The closed chamber method, which is currently widely used to determine Rs, creates a closed space on the soil surface, measures $CO_2$ concentration in the inner space, and calculates Rs from the increase. Accordingly, the method is divided into automatic or manual chamber methods (ACM and MCM, respectively). However, errors of these methods and differences in instruments are unclear. Therefore, we evaluated the characteristics and difference of Rs values calculated using both methods with actual data. Results: Both methods determined seasonal variation patterns of Rs, reflecting overall changes in soil temperature (Ts). ACM clearly showed detailed changes in Rs, but MCM did not, because such small changes are unknown as Rs values are collected monthly. Additionally, Rs measured using MCM was higher than that using ACM and differed depending on measured plots, but showed similar tendencies with all measurement times and plots. Contrastingly, MCM Rs values in August for plot 4 were very high compared with ACM Rs values because of soil disturbances that easily occur during MCM measurements. Comparing Rs values calculated using monthly means with those calculated using MCM, the ACM calculated values for monthly averages were higher or lower than those of similar measurement times using the MCM. The difference between the ACM and MCM was attributed to greater or lesser differences. These Rs values estimated the carbon released into the atmosphere during measurement periods to be approximately 57% higher with MCM than with ACM, at 5.1 and $7.9C\;ton\;ha^{-1}$, respectively. Conclusion: ACM calculated average values based on various Rs values as high and low for measurement periods, but the MCM produced only specific values for measurement times as representative values. Therefore, MCM may exhibit large errors in selection differences during Rs measurements. Therefore, to reduce this error using MCM, the time and frequency of measurement should be set to obtain Rs under various environmental conditions. Contrastingly, the MCM measurement is obtained during $CO_2$ evaluation in the soil owing to soil disturbance caused by measuring equipment, so close attention should be paid to measurements. This is because the measurement process is disturbed by high $CO_2$ soil concentration, and even small soil disturbances could release high levels into the chamber, causing large Rs errors. Therefore, the MCM should be adequately mastered before using the device to measure Rs.
Kim, Eun-Sook;Kim, Kyoung-Min;Lee, Jung-Bin;Lee, Seung-Ho;Kim, Chong-Chan
Journal of Korean Society of Forest Science
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v.100
no.3
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pp.455-465
/
2011
In order to assess and mitigate climate change, the role of forest biomass as carbon sink has to be understood spatially and quantitatively. Since existing forest statistics can not provide spatial information about forest resources, it is needed to predict spatial distribution of forest biomass under an alternative scheme. This study focuses on developing an upscaling method that expands forest variables from plot to landscape scale to estimate spatially explicit aboveground biomass(AGB). For this, forest stand variables were extracted from National Forest Inventory(NFI) data and used to develop AGB regression models by tree species. Dominant/codominant height and crown density were used as explanatory variables of AGB regression models. Spatial distribution of AGB could be estimated using AGB models, forest type map and the stand height map that was developed by forest type map and height regression models. Finally, it was estimated that total amount of forest AGB in Danyang was 6,606,324 ton. This estimate was within standard error of AGB statistics calculated by sample-based estimator, which was 6,518,178 ton. This AGB upscaling method can provide the means that can easily estimate biomass in large area. But because forest type map used as base map was produced using categorical data, this method has limits to improve a precision of AGB map.
The adsorption of Acid Fuchsin (AF) on granular activated carbon (GAC) was investigated for isothermal adsorption and kinetics and thermodynamic parameters by experimenting with the initial concentration, contact time, temperature, and pH of the dye as adsorption parameters. In the pH effect experiment, the adsorption of AF on activated carbon showed a bathtub type with increased adsorption at pH 3 and 11. The adsorption equilibrium data of AF fit well with the Freundlich isotherm model, and the calculated separation factor (1/n) value was found in which activated carbon can effectively remove AF. The pseudo-second-order kinetic model fits well within 7.88% of the error percent in the adsorption process. According to Weber and Morris's model plot, it was divided into two straight lines. The intraparticle diffusion rate was slow because the stage 2 (intraparticle diffusion) slope was smaller than that of stage 1 (boundary layer diffusion). Therefore, it was confirmed that the intraparticle diffusion was a rate-controlling step. The activation energy of AF (13.00 kJ mol-1) corresponded to the physical adsorption process (5 - 40 kJ mol-1). The free energy change of the AF adsorption by activated carbon showed negative values at 298-318 K. As the spontaneity increased with increasing temperature. The adsorption of AF was an endothermic reaction (ΔH = 22.65 kJ mol-1).
Jina Hur;Jae-Pil Cho;Kyo-Moon Shim;Sera Jo;Yong-Seok Kim;Min-Gu Kang;Chan-Sung Oh;Seung-Beom Seo;Eung-Sup Kim
Korean Journal of Agricultural and Forest Meteorology
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v.25
no.4
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pp.404-414
/
2023
In this study, digital climate maps with high-resolution (1km, daily) for the period of 1981 to 2020 were produced for the use as reference data within the procedures for statistical downscaling of climate change scenarios. Grid data for the six climate variables including maximum temperature, minimum temperature, precipitation, wind speed, relative humidity, solar radiation was created over Korean Peninsula using statistical downscaling model, so-called IGISRM (Improved GIS-based Regression Model), using global reanalysis data and in-situ observation. The digital climate data reflects topographical effects well in terms of representing general behaviors of observation. In terms of Correlation Coefficient, Slope of scatter plot, and Normalized Root Mean Square Error, temperature-related variables showed satisfactory performance while the other variables showed relatively lower reproducibility performance. These digital climate maps based on observation will be used to downscale future climate change scenario data as well as to get the information of gridded agricultural weather data over the whole Korean Peninsula including North Korea.
The use of low-toxic, hypoallergenic, and environmentally friendly natural pigments has increased. With growing interest in health, research on natural extracts containing beneficial substances for the human body is actively underway. In this study, natural pigments were extracted from sprout barley using a solvent extraction method and CCD-RSM was used to optimize the extraction process. The experiment's independent variables included extraction temperature, alcohol/ultra-pure volume ratio, and extraction time. The response variables were set to achieve a target chromaticity (L = 45, a = -35, b = 45), and to maximize DPPH radical scavenging activity evaluating the antioxidant capacity. The statistical significance of the main effect, interaction effect, and effect on the response value was evaluated and analyzed through the F and P values for the regression equation variables calculated using RSM optimization. Additionally, the reliability of the experiment was also confirmed through the P values of the probability plot graph. The extraction conditions for optimizing the four reaction values are 76.1 vol.% alcohol/ultra pure water volume ratio, an extraction temperature of 52.9 ℃ , and an extraction time of 49.6 min. Under these conditions, the theoretical values of the reaction values are L = 45.4, a = -36.8, and b = 45.0 DPPH radical scavenging activity = 30.9%. When the actual experiment was conducted under these optimal extraction conditions and analyzed, the measured values were L = 46.2, a = -36.1, and b = 48.2, and antioxidant capacity = 31.1% with an average error rate of 2.9%.
Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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2001.06a
/
pp.1031-1031
/
2001
The mammary gland is made up of remarkably sensitive tissue, which has the capability of producing a large volume of secretion, milk, under normal or healthy conditions. When bacteria enter the gland and establish an infection (mastitis), inflammation is initiated accompanied by an influx of white cells from the blood stream, by altered secretory function, and changes in the volume and composition of secretion. Cell numbers in milk are closely associated with inflammation and udder health. These somatic cell counts (SCC) are accepted as the international standard measurement of milk quality in dairy and for mastitis diagnosis. NIR Spectra of unhomogenized composite milk samples from 14 cows (healthy and mastitic), 7days after parturition and during the next 30 days of lactation were measured. Different multivariate analysis techniques were used to diagnose the disease at very early stage and determine how the spectral properties of milk vary with its composition and animal health. PLS model for prediction of somatic cell count (SCC) based on NIR milk spectra was made. The best accuracy of determination for the 1100-2500nm range was found using smoothed absorbance data and 10 PLS factors. The standard error of prediction for independent validation set of samples was 0.382, correlation coefficient 0.854 and the variation coefficient 7.63%. It has been found that SCC determination by NIR milk spectra was indirect and based on the related changes in milk composition. From the spectral changes, we learned that when mastitis occurred, the most significant factors that simultaneously influenced milk spectra were alteration of milk proteins and changes in ionic concentration of milk. It was consistent with the results we obtained further when applied 2DCOS. Two-dimensional correlation analysis of NIR milk spectra was done to assess the changes in milk composition, which occur when somatic cell count (SCC) levels vary. The synchronous correlation map revealed that when SCC increases, protein levels increase while water and lactose levels decrease. Results from the analysis of the asynchronous plot indicated that changes in water and fat absorptions occur before other milk components. In addition, the technique was used to assess the changes in milk during a period when SCC levels do not vary appreciably. Results indicated that milk components are in equilibrium and no appreciable change in a given component was seen with respect to another. This was found in both healthy and mastitic animals. However, milk components were found to vary with SCC content regardless of the range considered. This important finding demonstrates that 2-D correlation analysis may be used to track even subtle changes in milk composition in individual cows. To find out the right threshold for SCC when used for mastitis diagnosis at cow level, classification of milk samples was performed using soft independent modeling of class analogy (SIMCA) and different spectral data pretreatment. Two levels of SCC - 200 000 cells/$m\ell$ and 300 000 cells/$m\ell$, respectively, were set up and compared as thresholds to discriminate between healthy and mastitic cows. The best detection accuracy was found with 200 000 cells/$m\ell$ as threshold for mastitis and smoothed absorbance data: - 98% of the milk samples in the calibration set and 87% of the samples in the independent test set were correctly classified. When the spectral information was studied it was found that the successful mastitis diagnosis was based on reviling the spectral changes related to the corresponding changes in milk composition. NIRS combined with different ways of spectral data ruining can provide faster and nondestructive alternative to current methods for mastitis diagnosis and a new inside into disease understanding at molecular level.
Urbanization causes urban floods and urban heat island in the summer, so it is necessary to understanding the changes of the thermal environment through urban climate and energy balance. This can be explained by the energy balance, but in urban areas, unlike the typical energy balance, the storage heat flux saved in the building or artificial land cover should be considered. Since the environment of each city is different, there is a difficulty in applying the method of retrieving the storage heat flux of the previous research. Especially, most of the previous studies are focused on the overseas cities, so it is necessary to study the storage heat retrieval suitable for various land cover and building characteristics of the urban areas in Korea. Therefore, the object of this study, it is to derive the regression formula which can quantitatively retrieve the storage heat using the data of the area where various surface types exist. To this end, nonlinear regression analysis was performed using net radiation and surface temperature data as independent variables and flux tower based storage heat estimates as dependent variables. The retrieved regression coefficients were applied to each independent variable to derive the storage heat retrieval regression formula. As a result of time series analysis with flux tower based storage heat estimates, it was well simulated high peak at day time and the value at night. Moreover storage heat retrieved in this study was possible continuous retrieval than flux tower based storage heat estimates. As a result of scatter plot analysis, accuracy of retrieved storage heat was found to be significant at $50.14Wm^{-2}$ and bias $-0.94Wm^{-2}$.
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