• Journal of the Society of Disaster Information
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• v.19 no.1
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• pp.216-230
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• 2023

Purpose: The purpose is to prevent accidents by predicting disasters through the analysis of near-miss. Method: In this study, a near-miss literature review and data were collected at construction sites, and a questionnaire survey was conducted to use logistic regression analysis and decision tree analysis to classify the possibility of near-miss connection. Result: As a result of analyzing the effects of near-miss types on mental, physical, and safety habits and behaviors, the factor with a high influence on the body is the need for near-miss management, the type of job is electricity·information communication, and health status in order, and the mental factor is the construction scale The influence was high, and the factors with the highest influence on the habit behavior factors were analyzed in the order of experience, number of serious injuries, and occupation in order of illusion, inappropriate work instructions, and body parts. Through decision tree analysis, factors and patterns that affect the possibility of a near-miss being a surprise accident were identified. Conclusion: Construction site officials consider the observation of near-miss and mentally and physically. Specific management of the relevance of physical aspects to near-miss should be implemented, and a work environment in which serious accidents are reduced is expected through personnel allocation, work plans, work procedures and methods, and feedback so that inappropriate work instructions do not lead to near-miss.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.166-178
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• 2023

This study aims to introduce and assess CNN Deep Learning methods to analyze visual landscape images on social media with embedded user perceptions and experiences. This study analyzed visual landscape images by focusing on a healing place. For the study, seven adjectives related to healing were selected through text mining and consideration of previous studies. Subsequently, 50 evaluators were recruited to build a Deep Learning image. Evaluators were asked to collect three images most suitable for 'healing', 'healing landscape', and 'healing place' on portal sites. The collected images were refined and a data augmentation process was applied to build a CNN model. After that, 15,097 images of 'healing' and 'healing landscape' on portal sites were collected and classified to analyze the visual landscape of a healing place. As a result of the study, 'quiet' was the highest in the category except 'other' and 'indoor' with 2,093 (22%), followed by 'open', 'joyful', 'comfortable', 'clean', 'natural', and 'beautiful'. It was found through research that CNN Deep Learning is an analysis method that can derive results from visual landscape image analysis. It also suggested that it is one way to supplement the existing visual landscape analysis method, and suggests in-depth and diverse visual landscape analysis in the future by establishing a landscape image learning dataset.

• Geophysics and Geophysical Exploration
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• v.11 no.4
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• pp.350-360
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• 2008

Electrical resistivity is one of physical property of the earth and measured by electrical resistivity survey, electrical resistivity logging and laboratory test. Recently, electrical resistivity is widely used in determination of rock quality in support pattern design of road and railway tunnel construction sites. To get more reliable rock quality data from electrical resistivity, it needs a lot of test and study on correlation of resistivity and rock quality. Firstly, we did rock property test in laboratory, such as P wave velocity, Young's modulus, uniaxial compressive strength (UCS) and electrical resistivity. We correlate each test results and we found out that electrical resistivity has highly related to P wave velocity, Young's modulus and UCS. Next, we accomplished electrical resistivity survey in field site and carried out electrical resistivity logging at in-situ area. We also performed rock classification, such as RQD, RMR and Q-system and we correlate electrical resistivity to RMR data. We found out that electrical resistivity logging data are highly correlate to RMR. Also we found out that electrical resistivity survey data are lower than electrical resistivity logging data when there are faults or fractures. And it cause electrical resistivity survey data to lowly correlate to RMR.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.32-49
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• 2010

Site characterization on geological and geotechnical conditions was performed for evaluating the earthquake ground motions associated with seismic site effects at a small urbanized area, Hongseong, where structural damages were recorded by an earthquake of magnitude 5.0 on October 7, 1978. In the field, various geotechnical site investigations composed of borehole drillings and seismic tests for obtaining shear wave velocity profile were carried out at 16 sites. Based on the geotechnical data from site investigation and additional collection in and near Hongseong, an expert system on geotechnical information was implemented with the spatial framework of GIS. For practical application of the GIS-based geotechnical information system to assess the earthquake motions in a small urban area, spatial seismic zoning maps on geotechnical parameters, such as the bedrock depth and the site period ($T_G$), were created over the entire administrative district of Hongseong town, and the spatial distributions of seismic vulnerability potentials were intuitively examined. Spatial zonation was also performed to determine site coefficients for seismic design by adopting a site classification system based on $T_G$. A case study of seismic zonation in the Hongseong area verified that the GIS-based site investigation was very useful for regional prediction of earthquake ground motions in a small urbanized inland area.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.1-7
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• 2018

The purpose of this study is to compare and analyze the response time of three mobile portal sites in Korea using distributions. The research subjects are the mobile portal site of Naver, Daum, and Nate. The experiment period is six years from April 18, 2012 when mobile portals started to activate, to April 17, 2018. The number of experiments is 4,060. Histograms and percentages were used for the distribution comparisons. For the theoretical comparison, Chi-Square test is adopted as a parametric method, and Kolmogorov-Smirnov test is as a nonparametric method. Naver was the fastest of all four methods, the next was Nate, the next was the slowest. The same result was obtained in terms of average response speed. These results are in contradiction to the results of the wired portal. Naver is a strategy to increase the response speed in accordance with the characteristics of media. Daum is a strategy to increase the contents at the cost of response speed. As for classification, we divide the response time into "Comfortable", "Tolerable", "Feedback", "Leave" according to response time. The ratio of more than 7 seconds that users leave called as "Leave" is 1.18% for Naver, 11.70% for Daum, and 1.5% for Nate. As Daum is overwhelmingly high, the response time is very much in need of improvement. In addition, we show the response time of three mobile portals needs to be reduced We hope that the results of this paper will facilitate technology competition to increase the response speed of mobile portals.

• Journal of Soil and Groundwater Environment
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• v.20 no.7
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• pp.61-69
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• 2015

This study was performed to provide fundamental data to establish the new soil pollution standards and the soil contamination management plans in a rational manner. The distribution characteristics of new soil contaminants such as barium (Ba) and chromium (Cr) in soils (n=140) were investigated in relation to land-use classification and geological features. Also, the sequential extraction test was conducted to evaluate fate and mobility of new soil contaminants. The soil samples taken from 140 sites were analyzed to survey distribution levels of selected new soil contaminants. The average concentration and range for hazardous metals (Ba, Cr) were Ba 128.946 (26.757~489.587) mg/kg, Cr 30.121 (2.579~132.783) mg/kg. Based on land use classification, the highest Ba concentration was found in factory soils, followed by dry field and park soils, while Cr concentration was highest in rice paddy soils, followed by dry field and factory soils. Within 10 geological units investigated the highest Ba and Cr concentrations were observed in the soils from Okcheon group and metamorphic rocks, respectively. The BCR (European Community Bureau of Reference) sequential extraction was conducted to identify chemical distributional existence of 2 elements of soils from each geological unit. Ba in soils is mainly assumed to exists as reducible form (such as BaSO₄, BaCO₃) and Cr in soils mainly is assumed to exist as residual form (such as Cr₂O₃, Cr_xFe_1-x(OH)₃(x < 1)).

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.8
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• pp.3727-3731
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• 2016

Background: The most common type of ocular lymphoma is non-Hodgkin lymphoma (NHL), categorized into two groups: indolent (slow growing) and aggressive (rapid growing). Differentiating benign reactive lymphoid hyperplasia (RLH) from malignant ocular adnexal lymphoma (OAL) is challenging. Histopathology, immunohistochemistry (IHC) and flow cytometry have been used as diagnostic tools in such cases. Materials and Methods: In this retrospective case series, from 2002 to 2013 at Farabi Eye Center, 110 patients with ocular lymphoproliferative disease were enrolled. Prevalence, anatomical locations, mean age at diagnosis and the final diagnosis of the disease with IHC were assessed. Comparison between previous pathologic diagnoses and results of IHC was made. Immunoglobulin light chains and B-cell and T-cell markers and other immuno-phenotyping markers including CD20, CD3, CD5, CD23, CD10, CYCLIND1 and BCL2 were evaluated to determine the most accurate diagnosis. The lymphomas were categorized based on revised European-American lymphoma (REAL) classification. Results: Mean age ${\pm}$ SD (years) of the patients was $55.6{\pm}19.3$ and 61% were male. Patients with follicular lymphoma, large B-cell lymphoma or chronic lymphocytic leukemia/small cell lymphoma (CLL/SLL) tended to be older. Nine patients with previous diagnoses of low grade B-cell lymphoma were re-evaluated by IHC and the new diagnoses were as follows: extranodal marginal zone lymphoma(EMZL) (n=1), SLL(n=1), mantle cell lymphoma (MCL) (n=3), reactive lymphoid hyperplasia RLH (n=2). Two cases were excluded due to poor blocks. Flow cytometry reports in these seven patients revealed SLL with positive CD5 and CD23, MCLwith positive CD5 and CyclinD1 and negative CD23, EMZL with negative CD5,CD23 and CD10. One RLH patient was negative for Kappa/Lambda and positive for CD3 and CD20 and the other was positive for all of the light chains, CD3 and CD20. Orbit (49.1%), conjunctiva (16.1%) and lacrimal glands (16.1%) were the most common sites of involvement. Conclusions: Accurate pathological classification of lesions is crucial to determine proper therapeutic approaches. This can be achieved through precise histologic and IHC analyses by expert pathologists.

• Korean Journal of Environment and Ecology
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• v.12 no.2
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• pp.119-130
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• 1998

The purposes of this study were to investigate vegetation structure and to present management plan of mountain type green space in Kangwhado, Inchon. The actual vegetation in survey sites(11,331ha) was divided into 19 community types. It was consisted of secondary forest(92.32%) which was Quercus acutissima, Pinus densiflora-Q. acutissima, and Q. mongolica community so on. Artificial planting forest area, such as Robinia pseudoacacia and Pinus rigida forest and others, was 5.40%(612ha) and it was less than cases in other cities in the Metropolitan area. According to the classification by TWINSPAN, 57 survey plots were divided into seven community types; P rigida(community A), Q. acutissima(community B) P. densiflora-Q. acutissima(community C), Q. acutissima-P. densiflora (community D), P. densiflora-Carpinus laxiflora-Q. serrata-Q. acutissima(community E), Q. serrata-Q. mongolica(community F), and Zelkova serrata-Acer mono(community G). From this result, ecological succession trend of vegetation in this area seems to be change from P. densiflora forest through Q. acutissima forest to Q. mongolica, Q. serrata, and C. laxiflora forest. It was similar to the ordinary successional trend of temperate deciduous forest in middle area, Korea. In addition, this study area was showed acid soil(pH 4.17). Therefore, there is a need for managing the soil environment for effective vegetation management.

• Journal of the Earthquake Engineering Society of Korea
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• v.11 no.1 s.53
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• pp.45-57
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• 2007

The mean shear wave velocity to the depth of 30 m (Vs30) derived from the western Vs is the current site classification criterion for determining the design seismic ground motion taking into account the site amplification potential. In order to evaluate the Vs30 at a site, a shear wave velocity (Vs) Profile extending to at least 30 m in depth must be acquired from in-situ seismic test. In many cases, however, the resultant depth of the Vs profile may not extend to 30 m, owing to the unfavorable field condition and the limitation of adopted testing techniques. In this study, the Vs30 and the mean shear wave velocity to a depth shallower, than 30 m (VsDs) were computed from the Vs profiles more than 30 m in depth obtained by performing various seismic tests at total 72 sites in Korea, and a correlation between Vs30 and VsDs was drawn based on the computed mean Vs data. In addition, a method for extrapolating the Vs profile from shallow depth to 30 m was developed by building a shape curve based on the average data of all Vs profiles. For evaluating the Vs30 from the shallow Vs profiles, both the methods using VsDs and shape curve result in less bias than the simplest method of extending the lowermost Vs equally to 30 m in depth, and are usefully applicable particularly in the cases of the Vs profiles extending to at least 10 m in depth.

• The KIPS Transactions:PartB
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• v.8B no.5
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• pp.455-462
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• 2001

The World Wide Web has become one of the major services provided through Internet. When searching the vast web space, users use bookmarking facilities to record the sites of interests encountered during the course of navigation. One of the typical problems arising from bookmarking is that the list of bookmarks lose coherent organization when the the becomes too lengthy, thus ceasing to function as a practical finding aid. In order to maintain the bookmark file in an efficient, organized manner, the user has to classify all the bookmarks newly added to the file, and update the folders. This paper introduces our learning agent called BClassifier that automatically classifies bookmarks by analyzing the contents of the corresponding web documents. The chief source for the training examples are the bookmarks already classified into several bookmark folders according to their subject by the user. Additionally, the web pages found under top categories of Yahoo site are collected and included in the training examples for diversifying the subject categories to be represented, and the training examples for these categories as well. Our agent employs naive Bayesian learning method that is a well-tested, probability-based categorizing technique. In this paper, the outcome of some experimentation is also outlined and evaluated. A comparison of naive Bayesian learning method alongside other learning methods such as k-Nearest Neighbor and TFIDF is also presented.