Since the frequency of the earthquake occurrence in Korean peninsular is continuously increasing, the possibility that massive landslides are triggered by earthquake is also growing in Korea. Previously, the landslide is known to be induced by large magnitude earthquake, whose magnitude is larger than 6.0. However, the landslide can be induced by only small magnitude earthquake, especially in the fully saturated soil. Therefore, the susceptibility of landslide caused by small magnitude earthquake in fully saturated soil is analyzed in this study. For that, the topographical and geological characteristics of the site were obtained and managed by GIS software. In the procedure of the study, slope angle, cohesion, friction angle, unit weight of soil were obtained and constructed as a spatial database layer. Combining these data sets in a dynamic model based on Newmark's displacement analysis, the landslide displacements were estimated in each grid cell. In order to check out the possibility of the earthquake induced landslides, the level of the groundwater table is varied from dry to 80% saturated soil. In addition, in order to analyze the effect of the magnitude of earthquake and distance to epicenter, four different earthquakes epicenters were considered in the study area.
Kim, Dong-Wook;Na, Kyung-Gi;Han, Myung-Mook;Kim, Mijoo;Go, Woong;Park, Jun Hyung
Journal of Internet Computing and Services
/
v.19
no.1
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pp.27-35
/
2018
This paper is a study to classify malicious applications in Android environment. And studying the threat and behavioral analysis of malicious Android applications. In addition, malicious apps classified by machine learning were performed as experiments. Android behavior analysis can use dynamic analysis tools. Through this tool, API Calls, Runtime Log, System Resource, and Network information for the application can be extracted. We redefined the properties extracted for machine learning and evaluated the results of machine learning classification by verifying between the overall features and the main features. The results show that key features have been improved by 1~4% over the full feature set. Especially, SVM classifier improved by 10%. From these results, we found that the application of the key features as a key feature was more effective in the performance of the classification algorithm than in the use of the overall features. It was also identified as important to select meaningful features from the data sets.
The choice of an effective indexing method is crucial to guarantee the performance of the spatial join operator which is heavily used in geographical information systems. The $R^*$-tree based method is renowned as one of the most representative indexing methods. In this paper, we propose an efficient spatial join technique based on the DOT(Double Transformation) index, and compare it with the spatial Join technique based on the $R^*$-tree index. The DOT index transforms the MBR of an spatial object into a single numeric value using a space filling curve, and builds the $B^+$-tree from a set of numeric values transformed as such. The DOT index is possible to be employed as a primary index for spatial objects. The proposed spatial join technique exploits the regularities in the moving patterns of space filling curves to divide a query region into a set of maximal sub-regions within which space filling curves traverse without interruption. Such division reduces the number of spatial transformations required to perform the spatial join and thus improves the performance of join processing. The experiments with the data sets of various distributions and sizes revealed that the proposed join technique is up to three times faster than the spatial join method based on the $R^*$-tree index.
Major deficiencies of current automation scheme including various robots for bioproduction include the lack of task adaptability and real time processing, low job performance for diverse tasks, and the lack of robustness of take results, high system cost, failure of the credit from the operator, and so on. This paper proposed a scheme that could solve the current limitation of task abilities of conventional computer controlled automatic system. The proposed scheme is the man-machine hybrid automation via tele-operation which can handle various bioproduction processes. And it was classified into two categories. One category was the efficient task sharing between operator and CCM(computer controlled machine). The other was the efficient interface between operator and CCM. To realize the proposed concept, task of the object identification and extraction of 3D coordinate of an object was selected. 3D coordinate information was obtained from camera calibration using camera as a measurement device. Two stereo images were obtained by moving a camera certain distance in horizontal direction normal to focal axis and by acquiring two images at different locations. Transformation matrix for camera calibration was obtained via least square error approach using specified 6 known pairs of data points in 2D image and 3D world space. 3D world coordinate was obtained from two sets of image pixel coordinates of both camera images with calibrated transformation matrix. As an interface system between operator and CCM, a touch pad screen mounted on the monitor and remotely captured imaging system were used. Object indication was done by the operator’s finger touch to the captured image using the touch pad screen. A certain size of local image processing area was specified after the touch was made. And image processing was performed with the specified local area to extract desired features of the object. An MS Windows based interface software was developed using Visual C++6.0. The software was developed with four modules such as remote image acquisiton module, task command module, local image processing module and 3D coordinate extraction module. Proposed scheme shoed the feasibility of real time processing, robust and precise object identification, and adaptability of various job and environments though selected sample tasks.
Park, Mi Eun;Cho, Jeong Hoon;Kim, Sunyoung;Lee, Sang-Sam;Kim, Jeong Eun;Lee, Hee Choon;Cha, Joo Wan;Ryoo, Sang Boom
Atmosphere
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v.26
no.2
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pp.257-275
/
2016
Asian dust is a seasonal meteorological phenomenon influencing most East Asia, irregularly occurring during spring. Unusual heavy Asian dust event in winter was observed in Seoul, Korea, with up to $1,044{\mu}g\;m^{-3}$ of hourly mean $PM_{10}$, in 22~23 February 2015. Causes of such infrequent event has been studied using both ground based and spaceborne observations, as well as numerical simulations including ECMWF ERA Interim reanalysis, NOAA HYSPLIT backward trajectory analysis, and ADAM2-Haze simulation. Analysis showed that southern Mongolia and northern China, one of the areas for dust origins, had been warm and dry condition, i.e. no snow depth, soil temperature of ${\sim}0^{\circ}C$, and cumulative rainfall of 1 mm in February, along with strong surface winds higher than critical wind speed of $6{\sim}7.5m\;s^{-1}$ during 20~21 February. While Jurihe, China, ($42^{\circ}23^{\prime}56^{{\prime}{\prime}}N$, $112^{\circ}53^{\prime}58^{{\prime}{\prime}}E$) experienced $9,308{\mu}g\;m^{-3}$ of hourly mean surface $PM_{10}$ during the period, the Asian dust had affected the Korean Peninsula within 24 hours traveling through strong north-westerly wind at ~2 km altitude. KMA issued Asian dust alert from 1100 KST on 22nd to 2200 KST on 23rd since above $400{\mu}g\;m^{-3}$ of hourly mean surface $PM_{10}$. It is also important to note that, previously to arrival of the Asian dust, the Korean Peninsula was affected by anthropogenic air pollutants ($NO_3^-$, $SO_4^{2-}$, and $NH_4^+$) originated from the megacities and large industrial areas in northeast China. In addition, this study suggests using various data sets from modeling and observations as well as improving predictability of the ADAM2-Haze model itself, in order to more accurately predict the occurrence and impacts of the Asian dust over the Korean peninsula.
Choi, Chang Heon;Park, Jong Min;Park, So-Yeon;Chun, Minsoo;Han, Ji Hye;Cho, Jin Dong;Kim, Jung-in
Journal of Radiation Protection and Research
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v.42
no.2
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pp.77-82
/
2017
Background: This study aims to predict the midline dose based on the entrance and exit doses from optically stimulated luminescence detector (OSLD) measurements for total body irradiation (TBI). Materials and Methods: For TBI treatment, beam data sets were measured for 6 MV and 15 MV beams. To evaluate the tissue lateral effect of various thicknesses, the midline dose and peak dose were measured using a solid water phantom (SWP) and ion chamber. The entrance and exit doses were measured using OSLDs. OSLDs were attached onto the central beam axis at the entrance and exit surfaces of the phantom. The predicted midline dose was evaluated as the sum of the entrance and exit doses by OSLD measurement. The ratio of the entrance dose to the exit dose was evaluated at various thicknesses. Results and Discussion: The ratio of the peak dose to the midline dose was 1.12 for a 30 cm thick SWP at both energies. When the patient thickness is greater than 30 cm, the 15 MV should be used to ensure dose homogeneity. The ratio of the entrance dose to the exit dose was less than 1.0 for thicknesses of less than 30 cm and 40 cm at 6 MV and 15 MV, respectively. Therefore, the predicted midline dose can be underestimated for thinner body. At 15 MV, the ratios were approximately 1.06 for a thickness of 50 cm. In cases where adult patients are treated with the 15 MV photon beam, it is possible for the predicted midline dose to be overestimated for parts of the body with a thickness of 50 cm or greater. Conclusion: The predicted midline dose and OSLD-measured midline dose depend on the phantom thickness. For in-vivo dosimetry of TBI, the measurement dose should be corrected in order to accurately predict the midline dose.
This paper examines political leaders' image based on the concepts of social identity and distance. These concepts come from the two ideas: (1) Individuals create events to confirm the sentiments that they have about themselves and others in the current situation. (2) During this process structured sets of beliefs (social identity) about attributes of various entities are formed. Statistical analysis of the data from college students in Seoul offers three main findings. First, attributes clustered into four major groups-sociability, responsibility, power and activity. Sociability concerns as sense of approval or disapproval that can elaborated into closeness and intimacy. Responsibility relates to the judgement of morality, public obligation, or other standards. Power refers to social power, physical magnitude and so on. Activity indexes an entity's spontaneity, which can be elaborate into judgements of agency, speed and so on, Second, respondents evaluate negatively political leaders at the dimensions of sociability, responsibility, and activity, They are positively evaluated only at the dimension of power. Third, political leaders who are felt to be closer than others seem to have more political support nowadays.
The purpose of this study is to analyze the factors affecting cooperation between industry and public research institutes, in addition to the effects of cooperation between them; on technological and economic performance of firms. Based on existing research relating to the factors affecting industry-university-research institutes cooperation and the relationship between them and firm performance, this study selected the competence of government-funded research institutes, R&D capabilities and organizational characteristics of firms, and support of government and local governments; as factors influencing cooperation between industry and public research institutes. This study sets seven hypotheses on the relationship between the factors promoting industry-public research institute cooperation, technological performance and economic performance. A questionnaire survey was used to collect data for hypothesis testing and 116 questionnaires were completed and used in this research. The PLS-MGA was used as a method for hypothesis testing. In the analysis results, we found that the competence of government-funded research institutes, organizational characteristics of firms, and the support of government and local governments have a positive impact on cooperation between industry and public research institutes. We also found that the collaboration between industry and public research institutes, positively affects firms' technological performance. In addition, we found that the technological performance of a firm, positively affects a firms' economic performance. On the other hand, firms' R&D capabilities have no significant effect on cooperation between industry and public research institutes, and industry-public research institute cooperation does not directly affect the economic performance of firms.
Oomycetes belong to the kingdom Straminipila, a remarkably diverse group which includes brown algae and planktonic diatoms, although they have previously been classified under the kingdom Fungi. These organisms have evolved both saprophytic and pathogenic lifestyles, and more than 60% of the known species are pathogens on plants, the majority of which are classified into the order Peronosporales (includes downy mildews, Phytophthora, and Pythium). Recent phylogenetic investigations based on DNA sequences have revealed that the diversity of oomycetes has been largely underestimated. Although morphology is the most valuable criterion for their identification and diversity, morphological species identification is time-consuming and in some groups very difficult, especially for non-taxonomists. DNA barcoding is a fast and reliable tool for identification of species, enabling us to unravel the diversity and distribution of oomycetes. Accurate species determination of plant pathogens is a prerequisite for their control and quarantine, and further for assessing their potential threat to crops. The mitochondrial cox2 gene has been widely used for identification, taxonomy and phylogeny of various oomycete groups. However, recently the cox1 gene was proposed as a DNA barcode marker instead, together with ITS rDNA. To determine which out of cox1 or cox2 is best suited as universal oomycete barcode, we compared these two genes in terms of (1) PCR efficiency for 31 representative genera, as well as for historic herbarium specimens, and (2) in terms of sequence polymorphism, intra- and interspecific divergence. The primer sets for cox2 successfully amplified all oomycete genera tested, while cox1 failed to amplify three genera. In addition, cox2 exhibited higher PCR efficiency for historic herbarium specimens, providing easier access to barcoding type material. In addition, cox2 yielded higher species identification success, with higher interspecific and lower intraspecific divergences than cox1. Therefore, cox2 is suggested as a partner DNA barcode along with ITS rDNA instead of cox1. Including the two barcoding markers, ITS rDNA and cox2 mtDNA, the multi-locus phylogenetic analyses were performed to resolve two complex clades, Bremia lactucae (lettuce downy mildew) and Peronospora effuse (spinach downy mildew) at the species level and to infer evolutionary relationships within them. The approaches discriminated all currently accepted species and revealed several previously unrecognized lineages, which are specific to a host genus or species. The sequence polymorphisms were useful to develop a real-time quantitative PCR (qPCR) assay for detection of airborne inoculum of B. lactucae and P. effusa. Specificity tests revealed that the qPCR assay is specific for detection of each species. This assay is sensitive, enabling detection of very low levels of inoculum that may be present in the field. Early detection of the pathogen, coupled with knowledge of other factors that favor downy mildew outbreaks, may enable disease forecasting for judicious timing of fungicide applications.
Bulletin of the Society of Naval Architects of Korea
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v.25
no.4
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pp.7-12
/
1988
The Resistance Committee of Korea Towing Tank Conference extended the Cooperative Experimental Study Program(1985)[1] to perform the geosim tests by exchanging the five different scaled Series 60, $C_B=0.60$ models between the participating organizations and 13 sets of resistance data have been obtained. The test results are compared among the participating towing tanks and also with the results given in the report of the Resistance and Flow Com-identify the mittee of 18th ITTC. The form factor of each model is derived by Prohaska's method to investigate its dependency on $R_n$. On the other hand, at each $F_n$, form factors are also derived by Telfer's method to relation between $F_n$ and form factor. For this hull form, form factors show relatively weak dependency on $R_n$ and strong dependency on $F_n$. And it is also found that dependencies on both have a cross relation. It seems that further study should be continued to understand more clearly the physical phenomena involved in this problem.
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