• Journal of the Korean Institute of Landscape Architecture
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• v.32 no.4
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• pp.28-38
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• 2004

Korean goral (Nemorhaedus caudatus raddeanus) is one of the endangered species in Korea, and the rugged terrain of the Soraksan National Park (373㎢) is a critical habitat for the species. But the goral population is threatened by habitat fragmentation caused by roads and hiking trails. The objective of this study was to develop a potential habitat suitability model for Korean goral in the park, and the model was based on the concepts of fuzzy set theory and multi-criteria evaluation. The process of the suitability modeling could be divided into three steps. First, data for the modeling was collected by using field work and a literature survey. Collected data included 204 points of GPS data obtained through a goral trace survey and through the number of daily visitors to each hiking trail during the peak season of the park. Second, fuzzy set theory was employed for building a GIS data base related to environmental factors affecting the suitability of the goral habitat. Finally, a multiple-criteria evaluation was performed as the final step towards a goral habitat suitability model. The results of the study were as follows. First, characteristics of suitable habitats were the proximity to rock cliffs, scattered pine (Pinus densiflora) patches, ridges, the elevation of 700∼800m, and the aspect of south and southeast. Second, the habitat suitability model had a high classification accuracy of 93.9％ for the analysis site, and 95.7％ for the validation site at a cut off value of 0.5. Finally, 11.7％ of habitatwith more than 0.5 of habitat suitability index was affected by roads and hiking trails in the park.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.9
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• pp.419-424
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• 2016

Named entity recognition is required to improve the retrieval accuracy of patent documents or similar patents in the claims and patent descriptions. In this paper, we proposed an automatic named entity recognition for patents by using a conditional random field that is one of the best methods in machine learning research. Named entity recognition system has been constructed from the training set of tagged corpus with 660,000 words and 70,000 words are used as a test set for evaluation. The experiment shows that the accuracy is 93.6% and the Kappa coefficient is 0.67 between manual tagging and automatic tagging system. This figure is better than the Kappa coefficient 0.6 for manually tagged results and it shows that automatic named entity tagging system can be used as a practical tagging for patent documents in replacement of a manual tagging.

• Smart Structures and Systems
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• v.25 no.1
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• pp.23-35
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• 2020

It is important to take into account the thermal behavior in assessing the structural condition of bridges. An effective method of studying the temperature effect of long-span bridges is numerical simulation based on the solar radiation models. This study aims to develop a time-varying solar radiation model which can consider the real-time weather changes, such as a cloud cover. A statistical analysis of the long-term monitoring data is first performed, especially on the temperature data between the south and north anchors of the bridge, to confirm that temperature difference can be used to describe real-time weather changes. Second, a defect in the traditional solar radiation model is detected in the temperature field simulation, whereby the value of the turbidity coefficient t_u is subjective and cannot be used to describe the weather changes in real-time. Therefore, a new solar radiation model with modified turbidity coefficient γ is first established on the temperature difference between the south and north anchors. Third, the temperature data of several days are selected for model validation, with the results showing that the simulated temperature distribution is in good agreement with the measured temperature, while the calculated results by the traditional model had minor errors because the turbidity coefficient t_u is uncertainty. In addition, the vertical and transverse temperature gradient of a typical cross-section and the temperature distribution of the tower are also studied.

• Geophysics and Geophysical Exploration
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• v.19 no.2
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• pp.84-90
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• 2016

The validation of performance test for newly developed or old-used sensor is very important in the earthquake monitoring and seismology using earthquake data. Especially the frequency response of the sensor is mainly used to correct the earthquake data. The technique of the calculation of phase and amplitude with Hilbert transformation for earthquake data that is filtered with band limited frequency in time domain is applied to calculate the frequency response of the sensor. This technique was tested for the acceleration sensors, CMG-5T of 1g and 2g installed on the vibration table at the laboratory and we could obtain satisfactory result. Tohoku large earthquake in 2011 observed at the station SNU that has accelerometer, ES-T and seismometer, STS-2 operated by KIGAM was also used to test the field data applicability. We could successfully get the low frequency response of broad band sensor, STS-2. The technique by using band limited frequency filter and Hilbert transformation showed the superior frequency response to the frequency spectrum ratio method for noisy part in data.

• Journal of the Korean Solar Energy Society
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• v.31 no.6
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• pp.8-22
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• 2011

Investigations on modeling methods of a CFD wind resource prediction program, WindSim for a ccurate predictions of wind speeds were performed with the field measurements. Meteorological Masts having heights of 40m and 50m were installed at two different sites in complex terrain. The wind speeds and direction were monitored from sensors installed on the masts and recorded for one year. Modeling parameters of WindSim input variables for accurate predictions of wind speeds were investigated by performing cross predictions of wind speeds at the masts using the measured data. Four parameters that most affect the wind speed prediction in WindSim including the size of a topographical map, cell sizes in x and y direction, height distribution factors, and the roughness lengths were studied to find out more suitable input parameters for better wind speed predictions. The parameters were then applied to WindSim to predict the wind speed of another location in complex terrain in Korea for validation. The predicted annual wind speeds were compared with the averaged measured data for one year from meteorological masts installed for this study, and the errors were within 6.9%. The results of the proposed practical study are believed to be very useful to give guidelines to wind engineers for more accurate prediction results and time-saving in predicting wind speed of complex terrain that will be used to predict annual energy production of a virtual wind farm in complex terrain.

• Wind and Structures
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• v.4 no.3
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• pp.177-196
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• 2001

At present the most popular turbulence models used for engineering solutions to flow problems are the $k-{\varepsilon}$ and Reynolds stress models. The shortcoming of these models based on the isotropic eddy viscosity concept and Reynolds averaging in flow fields of the type found in the field of Wind Engineering are well documented. In view of these shortcomings this paper presents the implementation of a non-linear model and its evaluation for flow around a building. Tests were undertaken using the classical bluff body shape, a surface mounted cube, with orientations both normal and skewed at $45^{\circ}$ to the incident wind. Full-scale investigations have been undertaken at the Silsoe Research Institute with a 6 m surface mounted cube and a fetch of roughness height equal to 0.01 m. All tests were originally undertaken for a number of turbulence models including the standard, RNG and MMK $k-{\varepsilon}$ models and the differential stress model. The sensitivity of the CFD results to a number of solver parameters was tested. The accuracy of the turbulence model used was deduced by comparison to the full-scale predicted roof and wake recirculation zone lengths. Mean values of the predicted pressure coefficients were used to further validate the turbulence models. Preliminary comparisons have also been made with available published experimental and large eddy simulation data. Initial investigations suggested that a suitable turbulence model should be able to model the anisotropy of turbulent flow such as the Reynolds stress model whilst maintaining the ease of use and computational stability of the two equations models. Therefore development work concentrated on non-linear quadratic and cubic expansions of the Boussinesq eddy viscosity assumption. Comparisons of these with models based on an isotropic assumption are presented along with comparisons with measured data.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.320-326
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• 2016

From the perspective of climate-smart agriculture, it is becoming more critical to accurately estimate the amount of greenhouse gas emissions in the agricultural sector. In order to accurately ascertain the methane emissions from rice paddies, which account for a significant portion of the emission from the agricultural sector, we used the data from the 2010 Agriculture, Forestry and Fisheries Census, the revised water management scaling factors and their calculation program. In order to facilitate the analyses and understanding, the results were mapped using the ArcGIS software. The fact that the validation of the mapped values against the actual field measurements at one site showed little difference encourages the necessity to further this study. The administrative districts-based map of methane emission can help clearly identify the regional differences. Furthermore, the analysis of their major controlling factors will provide important scientific basis for the practical policy makings for methane mitigation.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.2
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• pp.17-25
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• 2006

In the present study, a 2-D chimera technique for overlapped bodies in relative motion is developed using unstructured triangular meshes. The solid boundary nodes located next to the intersecting point between bodies are merged to the intersecting point to assure accurate representation of the intersecting region. In order to assign proper value of flow variables at the nodes located out of the computational field, interpolation is conducted for non-active nodes. For validation, the motions of a NACA64A006 airfoil and a NACA0012 airfoil with a plane flap are computed and the results are compared with other simulations. The motion of a launching missile ejected from a NACA0012 airfoil is also simulated.

• Korean Journal of Remote Sensing
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• v.26 no.1
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• pp.47-57
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• 2010

The aim of this study is to detect landslide using digital aerial photography and apply the landslide to landslide susceptibility mapping by artificial neural network (ANN) and geographic information system (GIS) at Jinbu area where many landslides have occurred in 2006 by typhoon Ewiniar, Bilis and Kaemi. Landslide locations were identified by visual interpretation of aerial photography taken before and after landslide occurrence, and checked in field. For landslide susceptibility mapping, maps of the topography, geology, soil, forest, lineament, and landuse were constructed from the spatial data sets. Using the factors and landslide location and artificial neural network, the relative weight for the each factors was determinated by back-propagation algorithm. As the result, the aspect and slope factor showed higher weight in 1.2-1.5 times than other factors. Then, landslide susceptibility map was drawn using the weights and finally, the map was validated by comparing with landslide locations that were not used directly in the analysis. As the validation result, the prediction accuracy showed 81.44%.

• Korean Journal of Social Welfare Studies
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• v.49 no.3
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• pp.87-114
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• 2018

While social desirability has been neglected in the field of social work research in Korea, social work articles published in foreign journals have tried to identify respondents with a high level of social desirability and to control the effect of social desirability. The Social Desirability Scale (SDS-24) is the first social desirability scale developed by a Korean research is composed of two factors, self deception and impression management. This study was conducted to improve its practicability by evaluating its psychometric properties with social work practitioners and students. The findings of this study are satisfactory. The factor structure of the Social Desirability Scale (SDS-24) was confirmed and its reliability and validity were satisfactory. The advantage of the Social Desirability Scale (SDS-24) is that it includes items related to Korean culture. The ways of using Social Desirability Scale (SDS-24) in social work research are provided.