• Journal of Korean Society of Forest Science
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• v.94 no.6
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• pp.431-440
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• 2005

Location, height and clear-length of individual tree can be measured directly by LiDAR Remote Sensing, and dbh(diameter at breast height) can be estimated indirectly by tree height measured by LiDAR. In addition, stand volume and stand biomass are computed from estimated growth factors. In this study, each estimated growth factor was compared to the field measurements to validate accuracy. The coefficient of determination of total tree heights was 0.66 for total trees, 0.68 for Pinus koraiensis, 0.66 for Larix leptolepis and 0.60 for Quercus spp. The coefficient of determination of clear-length was 0.79 for total trees, 0.73 for Pinus koraiensis, 0.79 for Larix leptolepis, 0.68 for Quercus spp. The coefficient of determination of dbh predicted was 0.73 for Pinus koraiensis, 0.73 for Larix leptolepis and 0.85 for Quercus spp. Moreover The coefficient of determination of basal area was 0.82 for Pinus koraiensis, 0.92 for Larix leptolepis and 0.95 for Quercus spp. Biomass per ha computed by growth factor using LiDAR was 40,306 dm/ha for Pinus koraiensis, 94,150 tdm/ha for Larix leptolepis and 94,481 tdm/ha for Quercus spp. by species.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.65-65
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• 2002

In remote sensing, images are acquired over the same area by sensors of different spectral ranges (from the visible to the microwave) and/or with different number, position, and width of spectral bands. These images are generally partially redundant, as they represent the same scene, and partially complementary. For many applications of image classification, the information provided by a single sensor is often incomplete or imprecise resulting in misclassification. Fusion with redundant data can draw more consistent inferences for the interpretation of the scene, and can then improve classification accuracy. The common approach to the classification of multisensor data as a data fusion scheme at pixel level is to concatenate the data into one vector as if they were measurements from a single sensor. The multiband data acquired by a single multispectral sensor or by two or more different sensors are not completely independent, and a certain degree of informative overlap may exist between the observation spaces of the different bands. This dependence may make the data less informative and should be properly modeled in the analysis so that its effect can be eliminated. For modeling and eliminating the effect of such dependence, this study employs a strategy using self and conditional information variation measures. The self information variation reflects the self certainty of the individual bands, while the conditional information variation reflects the degree of dependence of the different bands. One data set might be very less reliable than others in the analysis and even exacerbate the classification results. The unreliable data set should be excluded in the analysis. To account for this, the self information variation is utilized to measure the degrees of reliability. The team of positively dependent bands can gather more information jointly than the team of independent ones. But, when bands are negatively dependent, the combined analysis of these bands may give worse information. Using the conditional information variation measure, the multiband data are split into two or more subsets according the dependence between the bands. Each subsets are classified separately, and a data fusion scheme at decision level is applied to integrate the individual classification results. In this study. a two-level algorithm using hierarchical clustering procedure is used for unsupervised image classification. Hierarchical clustering algorithm is based on similarity measures between all pairs of candidates being considered for merging. In the first level, the image is partitioned as any number of regions which are sets of spatially contiguous pixels so that no union of adjacent regions is statistically uniform. The regions resulted from the low level are clustered into a parsimonious number of groups according to their statistical characteristics. The algorithm has been applied to satellite multispectral data and airbone SAR data.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.251-264
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• 2008

One of the crucial elements to fully facilitate the various benefits of intelligent transportation systems (ITS) is to obtain more reliable traffic monitoring in real time. To date, point and section-based traffic measurements have been available through existing surveillance technologies, such as loops and automatic vehicle identification (AVI) systems. However, seamless and more reliable traffic data are required for more effective traffic information provision and operations. Technology advancements including vehicle tracking and wireless communication enable the acceleration of the availability of individual vehicle travel information. This study presents a UBIquitous PRObe vehicle Surveillance System (UBIPROSS) using vehicle-to-vehicle (V2V) wireless communications. Seamless vehicle travel information, including origin-destination information, speed, travel times, and other data, can be obtained by the proposed UBIPROSS. A set of parameters associated with functional requirements of the UBIPROSS, which include the market penetration rate (MPR) of equipped vehicles, V2V communication range, and travel time update interval, are investigated by a Monte Carlo simulation- (MCS) based evaluation framework. In addition, this paper describes prototypical implementation. Field test results and identified technical issues are also discussed. It is expected that the proposed system would be an invaluable precursor to develop a next-generation traffic surveillance system.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.59-66
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• 2016

This paper presents an empirical evaluation on dimensionality reduction strategies by which dissimilarity-based classifications (DBC) can be implemented efficiently. In DBC, classification is not based on feature measurements of individual objects (a set of attributes), but rather on a suitable dissimilarity measure among the individual objects (pair-wise object comparisons). One problem of DBC is the high dimensionality of the dissimilarity space when a lots of objects are treated. To address this issue, two kinds of solutions have been proposed in the literature: prototype selection (PS)-based methods and dimension reduction (DR)-based methods. In this paper, instead of utilizing the PS-based or DR-based methods, a way of performing DBC in Eigen spaces (ES) is considered and empirically compared. In ES-based DBC, classifications are performed as follows: first, a set of principal eigenvectors is extracted from the training data set using a principal component analysis; second, an Eigen space is expanded using a subset of the extracted and selected Eigen vectors; third, after measuring distances among the projected objects in the Eigen space using $l_p$-norms as the dissimilarity, classification is performed. The experimental results, which are obtained using the nearest neighbor rule with artificial and real-life benchmark data sets, demonstrate that when the dimensionality of the Eigen spaces has been selected appropriately, compared to the PS-based and DR-based methods, the performance of the ES-based DBC can be improved in terms of the classification accuracy.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.543-551
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• 2006

Recently efforts to extract information about forests by using remote sensing techniques for efficient forest management have progressed actively. In terms of extraction of tree information using single remote sensing data, however, the accuracy of tree recognition and the quantity of extracted information is limited. The objective of this study is to carry out tree modeling in domestic environment applying the latest core technique for tree modeling using color aerial photographs and LiDAR data and to estimate the result of tree modeling. A small-scale coniferous forest was investigated in Daejeon. It was 0.77 that the $R^2$ of accuracy test of tree numbers that estimated with color aerial photography and LiDAR data. In terms of tree height, there was no difference between the estimated value and the field measurements in the case of the group accuracy test of the recently unchanged area. Moreover $R^2$ was 0.83 in the case of the individual accuracy test.

• Food Engineering Progress
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• v.22 no.4
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• pp.381-385
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• 2018

Various rheological methods to measure the hardness of instant cooked rice by a texture analyzer were investigated and compared. Specifically, instant white rice samples with a wide range of hardness were subjected to four different rheological tests with disk, cylinder, rod, and cone probe whose results were inter-correlated. All the measurements demonstrated that the hardness of instant rice was reduced with increasing moisture content and showed negatively linear relationships. Out of the four tests applied in this study, the highest coefficient of correlation ($R^2=0.9268$) was observed distinctly in the cone probe test, where both compressive and shear forces can be applied to deform individual rice grains. However, the cylinder probe test had the lowest coefficient of correlation ($R^2=0.7247$) because it may be ineffective in causing direct deformation of individual rice grains. Furthermore, when the hardness values (N) were converted to stress (Pa), highly linear correlations ($R^2{\approx}0.99$) were observed between the tests with similar probe geometry and force application.

• Journal of Korean Society of Forest Science
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• v.66 no.1
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• pp.82-94
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• 1984

The variation of stomatal density and stomatal length of four species of oaks was studied for the purpose of examining the differences among populations and among individual trees within population. Nine populations of Quercus mongolica, four populations of Q. serrata and Q. variabilis respectively, and three populations of Q. acutissima were selected in the natural stands of oaks distributed through the whole country. Twelve leaves were sampled from each of 20 trees from each population. The length of 20 stomata and ten replications of stomatal density were measured from collodion replicas of each leaf under a microscope. Average stomatal densities and lengths ranged through $600-1000/mm^2$ and $19-26{\mu}m$ respectively in all of the species studied. The stomatal densities and lengths presented significant differences statistically at the level of 1 or 5% among populations and among individual trees within population in all the species. Quercus mongolica, especially, showed large variation among populations, while Q. variabilis did very narrow variation compared to the other species. The coefficients of variation of stomatal densities and lengths among individual trees within population exhibited small values of 3.7-12.0% and 1.4-5.3% respectively in all the populations of the species. The average stomatal densities of Q. mongolica showed statistically significant correlation of multiple correlation coefficient of $R_{df{\cdot}2.6}=0.868^*$ and multiple regression equation of $Y=0.041X_1(G.M.T.S.)+0.489X_2(G.M.H.S.)+22.37$ with the sum of growing season mean daily temperature and the sum of growing season mean daily humidity of the stand studied. However the average stomatal lengths showed no relation with the same meteological variables. The figures of frequency distribution of the measurements of leaves or the mean values of individual trees did not show normal distribution curves in some populations. The curves, as well as the results of ANOVA, exhibited the differences among populations.

• The Journal of the Korean dental association
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• v.50 no.7
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• pp.420-430
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• 2012

Purpose: The purpose of this study was to measure the absorbed dose and to calculate the effective dose for full-mouth periapical radiography using the portable dental x-ray machine and panoramic radiography Material and Method: Thermoluminescent chips were placed at 25sites throughout the layers of the head and neck of a tissue-equivalent human skull phantom. The man phantom was exposed with the portable dental x-ray machine and panoramic unit. During full-mouth periapical radiography the exposure setting was 60 kVp, 2 mA and 0.15 ~ 0.25 seconds, while during panoramic radiography the selected exposure setting was 72 kVp, 8 mA and 18 seconds. Absorbed dose measurements were obtained and equivalent doses to individual organs were summed using ICRP 103 to calculate of effective dose. Result: In the full-mouth periapical radiography, the highest absorbed dose was recorded at the mandible body follow with submandibular glands and cheek. Using panoramic unit, the highest absorbed dose was parotid glands and the following was back of neck and submandibular glands. The effective dose in full-mouth periapical radiography using portable dental x-ray machine was 46 ${\mu}Sv$. In panoramic radiography, the effective dose was 38 ${\mu}pSv$. Conclusion: It was recommended to panoramic radiography for general check in the head and neck area because that the effect dose in the panoramic radiography was lower than the dose in the full-mouth periapical radiography using portable dental x-ray machine.

• Asian-Australasian Journal of Animal Sciences
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• v.5 no.3
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• pp.465-468
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• 1992

Urinary purine derivatives and creatinine excretion was measured in a total of 4 white Alpine sheep. They were given diets 718 to 1060 g/kg dry matter (DM) of roughage. The crude protein content of this diets was on average $93.87{\pm}5.57g$ in kg DM. Purine derivatives-N excretion increased linearly with incremental DM intake and was significantly correlated (n = 16) with amounts of digestible organic matter (DOM) intake: allantoin-N (mg) = 1.205 (${\pm}0.070$) $\times$ DOM (g) - 136.709 (${\pm}37.399$), r = 0.9770, RSD = 22.97; uricacid-N (mg) = 0.131 (${\pm}0.041$) $\times$ DOM (g) + 11.380 (${\pm}21.881$), r = 0.6306, RSD = 13.44; Hypoxanthine-N (mg) = 0.049 (${\pm}0.014$) $\times$ DOM (g) - 28.640 (${\pm}7.708$), r = 0.6544, RSD = 4.73; total purine derivatives-N (mg) = 1.385 (${\pm}0.083$) $\times$ DOM (g) - 90.261 (${\pm}44.552$), r = 0.9706, RSD = 27.47. Microbial protein synthesis per kg DOM was estimated of 113 g. The urinary creatinine-N excretion was on average 9.10 mg/kg live weight (LW) with a standard error of 0.12 mg creatinine-N per kg LW. The excretion of creatinine excreton was not related to feed intake. Daily creatinine excretion (mg/d) was calculated from individual LW measurements and the average creatinine excretion (mg/kg LW). It was possible to predict the daily urinary purine derivatives excretion (r = 0.9720 for allantoin, r = 0.9886 for total purine derivatives) from the ratio of purine derivatives (mg/100 ml) and creatinine (mg/100 ml) in the urine and the daily creatinine excretion.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.22 no.4
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• pp.397-410
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• 2000

Skeletal class III had been classified by the position of the maxilla, the mandible, the maxillary alveolus, the mandibular alveolus and vertical development. This morphologic approach is simple and useful for clinical use, but it is insufficient to permit understanding of the pathophysiology of dysmorphoses. The author hypothesizes that there are different patterns of mutual relation of the skeletal components which have contributed pathologic equilibrium of skeletal class III. The purpose of this study are threefold: 1) to classify skeletal class III in subgroups, which can show the architectural characteristics of the deformity, 2) to analyse the craniofacial architecture of each subgroup on etio-pathogenic basis, and 3) to characterize and visualize the pattern as a prototype. Materials used in this study were lateral cephalograms of 106 skeletal class III adults, which were analysed with modified Delaire's architectural and structural analysis. Linear and angular measurements of the individual subject were obtained and cluster analysis was used for the subgrouping. Data were evaluated for verification of the statistical significances. The following results were obtained. 1. By the modified Delaire's architectural and structural analysis and cluster analysis, skeletal class III adults were classified into 7 clusters and presented as prototypes, which could show the pathophysiology of the skeletal architecture 2. There was significant relationship in measurement variables of each cluster, which could reflect characteristics of the skeletal pattern of growth. 3. The flexure of cranial base had a close relationship to the anterior rotational growth of the maxilla and contributes to understand the etio-pathology of skeletal class III. 4. The proportion of craniospinal area in cranial depth, craniocervical angle and vertical position of point Om had a close relationship to rotational growth of the mandible and direction of condylar growth. They contribute to understand the etio-pathology of skeletal class III. In summary, the cranium and the craniocervical area must be considered in diagnosis and treatment planning of dentofacial deformity. And the occlusal plane can be considered as a representative which shows the mutual relationships of the skeletal components.