• Journal of the Korean Institute of Landscape Architecture
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• v.24 no.4
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• pp.1-22
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• 1997

This paper was focused on the efficient management of landscape woody plants, and concerned itself with their important role in the urban environment. Based on the philosophy that there is nothing that can be done without an inventory, the purpose of this study was to develop an inventory system and iris proper application to a site for establishing a management plan Two different approaches were used, The first was to make a newly structured inventory system through collecting, analyzing, and evaluating various types of inventories used in Korea, the U. S. A., and Japan. The second approach was to apply a newly designed inventory system to the case study area. using GIS 'as a tool of spacial analysis and statistics for making decisions. The results could be summarized as follows; 1. In Korea, most of the Landscape Woozy Plants Inventories had datas which represented possession of trees, and only the work which they had done according to their traditional ways, There was no data related to the conditions, management needs, and site conditions of individual trees, This is essential information for organizing an inventory system . 2. There needs to be data which is balanced, containing tree characteristics and site characteristics. Through such information the management needs could be adjusted properly. The inventory list described in this paper was determined by botanical identity, placement condition, condition of tree, and types of work for maintaining as well as improving the condition of each tree One of the most important things was to determine the location data of each tree so as to compare data with other trees. The data gained from the field survey still had some problems because of lack of scientific method for supporting objective views, and because of actual situations, especially in the field of evaluating site conditions and management needs. All data should be revised to fit a computer data management system , if possible 3. The GIS(Geographic Information System) application showed good performance in handling inventory data for decision making. All the data used for the GIS application was divided into location and non-spatial data. Using the location data, it was easy to find the exact location of each tree on the monitor and on the maps generated by the computer even in the actual managed trite, along with various attribute data. Therefore it could be said that the entire management plan should start from data of individual trees with their exact locations, for making concrete management goals through actual budget planning.

• Journal of Environmental Science International
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• v.22 no.12
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• pp.1579-1587
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• 2013

This study was performed to evaluate the asbestos exposure levels and to calculate excess lifetime cancer risk (ELCR) for the risk assessment of the asbestos fibers released from asbestos-cement slate roofing (ASR) building. Total number of ASR buildings was into 21,267 in Busan, and 82.03 percent of the buildings was residential houses, and 43.61 percent of the buildings was constructed in 1970s. For this study, ten buildings were selected randomly among the ASR buildings. The range of airborne asbestos concentration in the selected ten ASR buildings was from 0.0016 to 0.0067 f/mL, and the concentration around no-admitted ASR buildings was higher than that around admitted buildings. The ELCR based on US EPA IRIS (integrated risk information system) model is within 3.5E-05 ~ 1.5E-04 levels, and the ELCR of no-admitted ASR buildings was higher than 1.0E-04 (one person per million) level that is considered a more aggressive approach to mitigate risk. These results indicate that the cancer risk from ASR buildings is higher than other buildings, and systematic public management is required for control of no-admitted ASR buildings within near future.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.104.1-104.1
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• 2011

We present a catalog of infrared supernova remnants (SNRs) in the Large Magellanic Cloud (LMC). We have searched the Spitzer archival data for infrared counterparts to all 45 known SNRs in the LMC, and identified 21 which is 47% of the known SNRs. Seven of them are newly detected: SNR 0450-70.9, SNR in N4, N103B, DEM L241, DEM L249, DEM L316A, and DEM L316B. All newly discovered SNRs show emission at several IRAC 3.4, 4.5, 5.8, and 8.0 micron bands and/or MIPS 24 and 70 micron bands. Most SNRs show shell structures. We derive infrared fluxes of these newly detected SNRs. The catalog contains general information of each SNR such as location, age, and SN type together with AKARI and/or Spitzer fluxes. For the entire SNR sample, we examine their infrared colors and the possible correlation of the infrared fluxes with the fluxes at other wavelengths. For the newly detected SNRs except the SNR in N4, we also performed follow-up imaging observations of [Fe II] 1.644 micron line using IRIS2 mounted on the Anglo Australian Telescope. Three out of six SNRs show [Fe II] emission corresponding to their infrared shells. [Fe II] knots are also detected in N103B which show good spatial correlation to infrared emission seen at Spitzer images as well as knotty $H{\alpha}$ emission. We investigate the characteristics and origin of the infrared emission in individual SNRs, and discuss the environmental and evolutionary effects.

• Journal of Environmental Health Sciences
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• v.40 no.5
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• pp.397-406
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• 2014

Objectives: Perchloroethylene (PCE) is a volatile chemical widely used as a solvent in the dry-cleaning and textile processing industries. It was evaluated as Group 2 "probably carcinogenic to humans" by the Integrated Risk Information System (IRIS) of the United State Environmental Protection Agency (U.S. EPA) in 2012. In order to provide a scientific basis for establishing risk management measures for chemicals on the national priority substances list, aggregate risk assessment was conducted for PCE, included in the top-10 substances. Methods: We conducted the investigation and monitoring of PCE exposure (e.g., exposure scenario, detection levels, and exposure factors, etc.) and assessed its multi-media (e.g., outdoor air, indoor air, and ground water) exposure risk with a deterministic and probabilistic approach. Results: In human risk assessment (HRA), the level of human exposure was higher in the younger age group. The exposure level through inhalation at home was the highest among the exposure routes. Outdoor air or uptake of drinking water represented less than 1% of total contributions to PCE exposure. These findings suggested that the level of risk was negligible since the Hazard Index (HI) induced by HRA was below one among all age groups, with a maximum HI value of 0.17 when reasonable maximum exposure was applied. Conclusion: In conclusion, it was suggested that despite low exposure risk, further studies are needed considering main sources, including occupational exposure.

• Journal of the Korean Society for information Management
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• v.23 no.2
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• pp.265-285
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• 2006

In text categorization a certain level of correctness of labels assigned to training documents is assumed without solid knowledge on that of real-world collections. Our research attempts to explore the quality of pre-assigned subject categories in a real-world collection, and to identify the relationship between the quality of category assignment in training set and text categorization performance. Particularly, we are interested in to what extent the performance can be improved by enhancing the quality (i.e., correctness) of category assignment in training documents. A collection of 1,150 abstracts in computer science is re-classified by an expert group, and divided into 907 training documents and 227 test documents (15 duplicates are removed). The performances of before and after re-classification groups, called Initial set and Recat-1/Recat-2 sets respectively, are compared using a kNN classifier. The average correctness of subject categories in the Initial set is 16%, and the categorization performance with the Initial set shows 17% in $F_1$ value. On the other hand, the Recat-1 set scores $F_1$ value of 61%, which is 3.6 times higher than that of the Initial set.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.2 s.302
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• pp.101-112
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• 2005

As we perceive the world as 3-dimensional through our two eyes, we can extract 3-dimensional information from stereo images obtained from two or more cameras. Since stereo images have a large amount of data, with recent advances in digital video coding technology, efficient compression algorithms have been developed for stereo images. In order to compress stereo images and to obtain 3-D information such as depth, we find disparity vectors by using disparity estimation algorithm generally utilizing pixel differences between stereo pairs. However, it is not unusual to have stereo images having different intensity values for several reasons, such as incorrect control of the iris of each camera, disagreement of the foci of two cameras, orientation, position, and different characteristics of CCD (charge-coupled device) cameras, and so on. The intensity differences of stereo pairs often cause undesirable problems such as incorrect disparity vectors and consequent low coding efficiency. By compensating intensity differences between left and right images, we can obtain higher coding efficiency and hopefully reduce the perceptual burden of brain to combine different information incoming from two eyes. We propose several methods of intensity compensation such as local intensity compensation, global intensity compensation, and hierarchical intensity compensation as very simple and efficient preprocessing tool. Experimental results show that the proposed algerian provides significant improvement in coding efficiency.

• Journal of KIISE:Software and Applications
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• v.32 no.11
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• pp.1021-1028
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• 2005

The general solution for classification and regression problems can be found by matching and modifying matrices with the information in real world and then these matrices are teaming in neural networks. This paper treats primary space as a real world, and dual space that Primary space matches matrices using kernel. In practical study, there are two kinds of problems, complete system which can get an answer using inverse matrix and ill-posed system or singular system which cannot get an answer directly from inverse of the given matrix. Further more the problems are often given by the latter condition; therefore, it is necessary to find regularization parameter to change ill-posed or singular problems into complete system. This paper compares each performance under both classification and regression problems among GCV, L-Curve, which are well known for getting regularization parameter, and kernel methods. Both GCV and L-Curve have excellent performance to get regularization parameters, and the performances are similar although they show little bit different results from the different condition of problems. However, these methods are two-step solution because both have to calculate the regularization parameters to solve given problems, and then those problems can be applied to other solving methods. Compared with UV and L-Curve, kernel methods are one-step solution which is simultaneously teaming a regularization parameter within the teaming process of pattern weights. This paper also suggests dynamic momentum which is leaning under the limited proportional condition between learning epoch and the performance of given problems to increase performance and precision for regularization. Finally, this paper shows the results that suggested solution can get better or equivalent results compared with GCV and L-Curve through the experiments using Iris data which are used to consider standard data in classification, Gaussian data which are typical data for singular system, and Shaw data which is an one-dimension image restoration problems.

• Journal of The Korean Society of Grassland and Forage Science
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• v.27 no.3
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• pp.173-182
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• 2007

The purpose of this study was to compared the early growth pattern, stem, leaf and root weight, DM yield, flowering characteristics and preference for selection of turf type grasses and wild flower species in mixtures combination for wildflower pasture. The experimental design included five species of turf grasses and 11 species of wildflower : turf type grass species{Kentucky bluegrass(Midnight), tall fescue(Millennium), perennial ryegrass(Palmer III), redtop(Barricuda) and creeping bentgrass(Crenshaw)}, wildflower species {Chrysanthemum leucanthemum L. Coreopsis lanceolata L., Rudbeckia bicolor Nutt.., Dianthus chinensis L., Chrysanthemum lindicum L., Lotus corniculatus var. Japonicus Regel, Veronica linariaefolia Pallas, Aster koraiensis Nakai., Chrysanthemum zanadskii var. latilobum (Maxim.) Kitamura, Lythrum anceps Makino and Iris pallassi var. chinensis Lodd}. The field trials were carried out on the experimental pasture plots of Chungnam National University from January 2005 to December 2006. The appropriate species of turf grass which have a mixture possibility with wildflower are thought to be Kentucky bluegrass. Compared with Kentucky bluegrass, on the other hand, species such as Chrysanthemum leucanthemum L., Lotus corniculatus var. Japonicus Regel, Chrysanthemum zanadskii var. latilobum Maxim.) Kitamura and Lythrum anceps Makino have shown advantageous aspects of fast early growth pattern and highly weights of stem, leaf and root. Futhermore, these wild flowers were in harmony and no overlap on flower color, flowering periods and flowering longevity, and highly preference by Korean native goats. For the establishment of wildflower pasture in Korea, therefore, it is important to select the appropriate species of turf glasses, which have a weak competition against wild flowers, and then to make mixture combination of those turf glasses with the various wild flowers which have a strong competition against turf glasses but have a different anthesis characteristics among themselves.

• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.275-284
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• 2008

With increases in recent security requirements, biometric technology such as fingerprints, faces and iris recognitions have been widely used in many applications including door access control, personal authentication for computers, internet banking, automatic teller machines and border-crossing controls. Finger vein recognition uses the unique patterns of finger veins in order to identify individuals at a high level of accuracy. This paper proposes new device and methods for touchless finger vein recognition. This research presents the following five advantages compared to previous works. First, by using a minimal guiding structure for the finger tip, side and the back of finger, we were able to obtain touchless finger vein images without causing much inconvenience to user. Second, by using a hot mirror, which was slanted at the angle of 45 degrees in front of the camera, we were able to reduce the depth of the capturing device. Consequently, it would be possible to use the device in many applications having size limitations such as mobile phones. Third, we used the holistic texture information of the finger veins based on a LBP (Local Binary Pattern) without needing to extract accurate finger vein regions. By using this method, we were able to reduce the effect of non-uniform illumination including shaded and highly saturated areas. Fourth, we enhanced recognition performance by excluding non-finger vein regions. Fifth, when matching the extracted finger vein code with the enrolled one, by using the bit-shift in both the horizontal and vertical directions, we could reduce the authentic variations caused by the translation and rotation of finger. Experimental results showed that the EER (Equal Error Rate) was 0.07423% and the total processing time was 91.4ms.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.317-326
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• 2024

Biometric recognition is a technology that determines whether a person is identified by extracting information on a person's biometric and behavioral characteristics with a specific device. Cyber threats such as forgery, duplication, and hacking of biometric characteristics are increasing in the field of biometrics. In response, the security system is strengthened and complex, and it is becoming difficult for individuals to use. To this end, multiple biometric models are being studied. Existing studies have suggested feature fusion methods, but comparisons between feature fusion methods are insufficient. Therefore, in this paper, we compared and evaluated the fusion method of multiple biometric models using fingerprint, face, and iris images. VGG-16, ResNet-50, EfficientNet-B1, EfficientNet-B4, EfficientNet-B7, and Inception-v3 were used for feature extraction, and the fusion methods of 'Sensor-Level', 'Feature-Level', 'Score-Level', and 'Rank-Level' were compared and evaluated for feature fusion. As a result of the comparative evaluation, the EfficientNet-B7 model showed 98.51% accuracy and high stability in the 'Feature-Level' fusion method. However, because the EfficietnNet-B7 model is large in size, model lightweight studies are needed for biocharacteristic fusion.