• Korean Journal of Environment and Ecology
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• v.35 no.5
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• pp.490-502
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• 2021

This study was conducted to analyze the current status of fish fauna and characteristics of the fish community according to the habitat of Woraksan National Park, Korea. The spatially balanced sampling selected 20 stations from major streams of Woraksan National Park, and three surveys were conducted in each season. The physical environments of the habitat were mostly mountain streams (Aa), with large stones and gravels scattered over the stream. The average altitude of the habitat was 304.4 m, and the average depth of water was 40.3 cm, being less than 1 m in most cases, and the river water level was distributed from 3rd to 5th streams. The principal component analysis of the physical environmental factors by habitat showed that the substrate properties differed according to the altitude. The survey identified a total of 2,183 individuals in 16 species belonging to 7 families. The dominant species was Zacco koreanus(86.2%), and the subdominant species was Rhynchocypris oxycephalus(3.8%). Pseudopungtungia tenuicorpa, classified as the endangered wildlife II, was the first endangered legally protected species found in this survey. Analysis of the rank abundance curve model in the fish community showed the Zipf model at 9 out of 20 points, the Lognormal model in 3 points, and the Preemption model in 4 points. The remaining 4 habitats showed only one species and were not analyzed. The canonical correspondence analysis of 20 stations and fish species was performed to understand the characteristics of the fish community according to environmental factors. The fish communities were divided according to differences in habitat environment by the altitude.

• International Journal of Computer Science & Network Security
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• v.24 no.9
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• pp.30-40
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• 2024

Building an accurate 3-D spatial road network model has become an active area of research now-a-days that profess to be a new paradigm in developing Smart roads and intelligent transportation system (ITS) which will help the public and private road impresario for better road mobility and eco-routing so that better road traffic, less carbon emission and road safety may be ensured. Dealing with such a large scale 3-D road network data poses challenges in getting accurate elevation information of a road network to better estimate the CO₂ emission and accurate routing for the vehicles in Internet of Vehicle (IoV) scenario. Clustering and regression techniques are found suitable in discovering the missing elevation information in 3-D spatial road network dataset for some points in the road network which is envisaged of helping the public a better eco-routing experience. Further, recently Explainable Artificial Intelligence (xAI) draws attention of the researchers to better interprete, transparent and comprehensible, thus enabling to design efficient choice based models choices depending upon users requirements. The 3-D road network dataset, comprising of spatial attributes (longitude, latitude, altitude) of North Jutland, Denmark, collected from publicly available UCI repositories is preprocessed through feature engineering and scaling to ensure optimal accuracy for clustering and regression tasks. K-Means clustering and regression using Support Vector Machine (SVM) with radial basis function (RBF) kernel are employed for 3-D road network analysis. Silhouette scores and number of clusters are chosen for measuring cluster quality whereas error metric such as MAE ( Mean Absolute Error) and RMSE (Root Mean Square Error) are considered for evaluating the regression method. To have better interpretability of the Clustering and regression models, SHAP (Shapley Additive Explanations), a powerful xAI technique is employed in this research. From extensive experiments , it is observed that SHAP analysis validated the importance of latitude and altitude in predicting longitude, particularly in the four-cluster setup, providing critical insights into model behavior and feature contributions SHAP analysis validated the importance of latitude and altitude in predicting longitude, particularly in the four-cluster setup, providing critical insights into model behavior and feature contributions with an accuracy of 97.22% and strong performance metrics across all classes having MAE of 0.0346, and MSE of 0.0018. On the other hand, the ten-cluster setup, while faster in SHAP analysis, presented challenges in interpretability due to increased clustering complexity. Hence, K-Means clustering with K=4 and SVM hybrid models demonstrated superior performance and interpretability, highlighting the importance of careful cluster selection to balance model complexity and predictive accuracy.

• Journal of the Korean Solar Energy Society
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• v.30 no.5
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• pp.100-106
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• 2010

The purpose of this study is to predict the effective sky temperature on Osan City during the summer. The north latitude, east longitude of Osan City is $37^{\circ}06'$ and $127^{\circ}02'$. The altitude from the sea level is 48m. Empirical relations of the effective sky temperature suggested by Duffie and Beckman are compared on clear days. For the effective sky temperature prediction, data measured by the Korea Meteorological Administration is used as an input to the Bliss model. Both Hottel and Krondratyev model are used to calculate the water vapor emissivity. The results using Hottel's model match well with the empirical relation proposed by Bliss. The results show maximum, minimum, and average values depending on water vapor emissivity model. The maximum deviation is about 10K and is due to total emissivity model.

• Journal of Korea Water Resources Association
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• v.41 no.11
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• pp.1153-1162
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• 2008

The use of radar rainfall for hydrological appraisal has been a challenge due to the limitations in raw data generation followed by the complex analysis needed to come up with precise data interpretation. In this study, RAIDOM (RAdar Image DigitalizatiOn Method) has been developed to convert synthetic radar CAPPI(Constant Altitude Plan Position Indicator) image data from Korea Meteorological Administration into digital format in order to come up with a more practical and useful radar image data. RAIDOM was used to examine a severe local rainstorm that occurred in July 2006 as well as two other separate events that caused heavy floods on both upper and mid parts of the HanRiver basin. A distributed model was developed based on the available radar rainfall data. The Flood Hydrograph simulation has been found consistent with actual values. The results show the potentials of RAIDOM and the distributed model as tools for flood prediction. Furthermore, these findings are expected to extend the usefulness of radar rainfall data in hydrological appraisal.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.27-29
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• 2007

The visual implementation of 3-dimensional national environment is focused by the requirement and importance in the fields such as, national development plan, telecommunication facility deployment plan, railway construction, construction engineering, spatial city development, safety and disaster prevention engineering. The currently used DEM system using contour lines, which embodies national geographic information based on the 2-D digital maps and facility information has limitation in implementation in reproducing the 3-D spatial city. Moreover, this method often neglects the altitude of the rail way infrastructure which has narrow width and long length. There it is needed to apply laser measurement technique in the spatial target object to obtain accuracy. Currently, the LiDAR data which combines the laser measurement skill and GPS has been introduced to obtain high resolution accuracy in the altitude measurement. In this paper, we first investigate the LiDAR based researches in advanced foreign countries, then we propose data a generation scheme and an algorithm for the optimal manage and synthesis of railway facility system in our 3-D spatial terrain information. For this object, LiDAR based height data transformed to DEM, and the realtime unification of the vector via digital image mapping and raster via exactness evaluation is transformed to make it possible to trace the model of generated 3-dimensional railway model with long distance for 3D tract model generation.

• Journal of the Korean Society of Propulsion Engineers
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• v.7 no.1
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• pp.49-56
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• 2003

A steady-state performance simulation program using $EASY5^{(R)}$ on the turboprop engine was developed through in this study. The PT6A-62 turboprop engine which is the power plant of the first Korean basic trainer KT-1, was selected for this study. In order to evaluate the proposed perfrmance model the analysis results of $EASY5^{(R)}$ model were compared with the simulated results by the GASTURB program, which is well blown commercially for the simulation performance analysis at various cases. The first case was the uninstalled condition with various altitudes from ground to 30000ft and flight Mach No. 0. The second case was the install condition with various altitude from ground to M at the maximum take off and the ECS (Environmental Control System) OFF conditions. The third case was install condition with the altitude range from 5000 ft to 1000ft and Mach No. 0.1 to 0.3 at maximum ECS operating condition. It was confirm that the results by the $EASY5^{(R)}$ model were well agreed with those by GASTURB within maximum 5.0%

• Spatial Information Research
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• v.15 no.2
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• pp.135-146
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• 2007

The purpose of this study was to ascertain and analyze environmental factors of subgenus Lycoctonum in Korea for conservation and management of rare high land plant species by GIS. We derived the habitat model of Lycoctonum from GPS coordination, habitat factors and digital topology maps. Suitable altitude fur the subgenus Lycoctonum is from 470m to 1320m, and northern slopes(between 15.5 and 36 degrees) are ideal for the Lycoctonum populations. In addition to altitude, slope and aspect, deciduous forest and approximation to water source were found as important factor. Using GIS and the Lycoctonum habitat model, we overlaid elevation, aspect, slope and land cover layers and analyzed buffer from the water source on two topology maps, Yang-Soo and Mock-Dong. After making prediction map for Lycoctonum habitat, we verified the existence of Lycoctonum populations on the predicted sites through field survey. Through this research, we're convinced that GIS software is powerful tool for plants conservation, such as finding unknown habitat or selecting alternative habitat.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.2 no.1
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• pp.1-14
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• 2021

The study has been carried out with an objective to prepare Siberian roe deer habitat potential maps in South Korea based on three geographic information system-based models including frequency ratio (FR) as a bivariate statistical approach as well as convolutional neural network (CNN) and long short-term memory (LSTM) as machine learning algorithms. According to field observations, 741 locations were reported as roe deer's habitat preferences. The dataset were divided with a proportion of 70:30 for constructing models and validation purposes. Through FR model, a total of 10 influential factors were opted for the modelling process, namely altitude, valley depth, slope height, topographic position index (TPI), topographic wetness index (TWI), normalized difference water index, drainage density, road density, radar intensity, and morphological feature. The results of variable importance analysis determined that TPI, TWI, altitude and valley depth have higher impact on predicting. Furthermore, the area under the receiver operating characteristic (ROC) curve was applied to assess the prediction accuracies of three models. The results showed that all the models almost have similar performances, but LSTM model had relatively higher prediction ability in comparison to FR and CNN models with the accuracy of 76% and 73% during the training and validation process. The obtained map of LSTM model was categorized into five classes of potentiality including very low, low, moderate, high and very high with proportions of 19.70%, 19.81%, 19.31%, 19.86%, and 21.31%, respectively. The resultant potential maps may be valuable to monitor and preserve the Siberian roe deer habitats.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.3
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• pp.433-440
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• 2022

High Altitude Long Endurance(HALE) solar powered UAV is the vehicle that flies for a long time as solar power energy sources. It can be used to replace satellites or provide continuous service because it can perform long-term missions at high altitudes. Due to the property of the mission, it is very important for HALE solar powered UAV to have maximum flight time. It is required for mission performance to fly at high altitudes continuously except a return for temporary maintenance. Therefore mission availability time analysis is a critical factor in the commercialization of HALE solar powered UAV. In this paper, we presented an analytic model and logic for available time analysis based on the design parameters of HALE solar powered UAV. This model can be used to analyze the possibility of applying UAV according to the UAV's mission in concept design before the UAV detail design stage.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.12
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• pp.1035-1047
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• 2015

Wind tunnel experiment and computational analysis have been carried out to evaluate the performance of propeller for scale electric-powered HALE UAV, named EAV-2H+. Performance curves are measured for three propellers and their adequacy for EAV-2H+ installation is examined through consideration of operating conditions. Decline in performance coefficients is observed in low rpm region. Also, the effect of transition tape on propeller performance is measured and analyzed. The computational performance analyses are carried out by using commercial CFD program. The thrust and power coefficient from computations show good agreement with experimental results. Performance coefficients are compared and the influence of measurement device which contributes to discrepancy of the results is examined. Transition SST model is confirmed to yield the tendency of performance decline in low rpm range, similar to experimental observation. The decrease in aerodynamic performance of blade element due to low Reynolds number is identified to cause the decline in propeller performance. Analyses for high altitude conditions confirms degradation in propeller performance.