• Journal of information and communication convergence engineering
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• v.19 no.3
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• pp.188-197
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• 2021

In military operations, an accurate localization system is required to navigate soldiers to their destinations, even in non-GPS environments. The global positioning system is a commonly used localization method, but it is difficult to maintain the robustness of GPS-based localization against jamming of signals. In addition, GPS-based localization cannot provide important terrain information such as obstacles. With the widespread use of embedded sensors, sensor-based pedestrian tracking schemes have become an attractive option. However, because of noisy sensor readings, pedestrian tracking systems using motion sensors have a major drawback in that errors in the estimated displacement accumulate over time. We present a group-based standalone system that creates terrain maps automatically while also locating soldiers in mountainous terrain. The system estimates landmarks using inertial sensors and utilizes split group information to improve the robustness of map construction. The evaluation shows that our system successfully corrected and combined the drift error of the system localization without infrastructure.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.1122-1140
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• 2024

The importance of indoor positioning has grown in numerous application areas such as emergency response, logistics, and industrial automation. In ships, indoor positioning is also needed to provide services to passengers on board. Due to the complex structure and dynamic nature of ship environments, conventional positioning techniques have limitations in providing accurate positions. Compared to other indoor positioning technologies, Bluetooth 5.1-based indoor positioning technology is highly suitable for ship environments. Bluetooth 5.1 attains centimeter-level positioning accuracy by collecting In-phase and Quadrature (IQ) samples from wireless signals. However, distorted IQ samples can lead to significant errors in the final estimated position. Therefore, we propose an indoor positioning method for ships that utilizes a Deep Neural Network (DNN) combined with IQ fingerprint maps to overcome the challenges associated with accurate location detection within the ship. The results indicate that the accuracy of our proposed method can reach up to 97.76%.

• Journal of Climate Change Research
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• v.4 no.2
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• pp.177-188
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• 2013

In this research, forest cover distribution change, forest volume and carbon stock in Yongin-city, Gyeonggi procince were estimated focused on the forest of Yongin-City using forest type map and HyTAG model in relation to climate change. Present forest volume of Yongin-city was estimated using the data from $5^{th}$ Forest Type Map and Korean National Forest Inventory (NFI). And for the future 100 years potential forest distribution by 10-year interval were estimated using HyTAG model. Forest volume was also calculated using algebraic differences form of the growth model. According to the $5^{th}$ Forest Type Map, present needleleaf forest occupied 37.8% and broadleaf forest 62.2% of forest area. And the forest cover distribution after 30 years would be changed to 0.13% of needleleaf forest and 99.97% of broadleaf forest. Finally, 60 years later, whole forest of Yongin-city would be covered by broad-leaf forest. Also the current forest carbon stocks was measured 1,773,862 tC(56.79 tC/ha) and future carbon stocks after 50 years was predicted to 4,432,351 tC(141.90 tC/ha) by HyTAG model. The carbon stocks after 100 years later was 6,884,063 tC (220.40 tC/ha). According to the HyTAG model prediction, Pinus koraiensis, Larix kaempferi, Pinus rigida, and Pinus densiflora are not suitable to the future climate of 10-year, 30-year, 30-year, and 50-year later respectively. All Quercus spp. was predicted to be suitable to the future climate.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.1-23
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• 2014

Market forecasting aims to estimate the sales volume of a product or service that is sold to consumers for a specific selling period. From the perspective of the enterprise, accurate market forecasting assists in determining the timing of new product introduction, product design, and establishing production plans and marketing strategies that enable a more efficient decision-making process. Moreover, accurate market forecasting enables governments to efficiently establish a national budget organization. This study aims to generate a market growth curve for ICT (information and communication technology) goods using past time series data; categorize products showing similar growth patterns; understand markets in the industry; and forecast the future outlook of such products. This study suggests the useful and meaningful process (or methodology) to identify the market growth pattern with quantitative growth model and data mining algorithm. The study employs the following methodology. At the first stage, past time series data are collected based on the target products or services of categorized industry. The data, such as the volume of sales and domestic consumption for a specific product or service, are collected from the relevant government ministry, the National Statistical Office, and other relevant government organizations. For collected data that may not be analyzed due to the lack of past data and the alteration of code names, data pre-processing work should be performed. At the second stage of this process, an optimal model for market forecasting should be selected. This model can be varied on the basis of the characteristics of each categorized industry. As this study is focused on the ICT industry, which has more frequent new technology appearances resulting in changes of the market structure, Logistic model, Gompertz model, and Bass model are selected. A hybrid model that combines different models can also be considered. The hybrid model considered for use in this study analyzes the size of the market potential through the Logistic and Gompertz models, and then the figures are used for the Bass model. The third stage of this process is to evaluate which model most accurately explains the data. In order to do this, the parameter should be estimated on the basis of the collected past time series data to generate the models' predictive value and calculate the root-mean squared error (RMSE). The model that shows the lowest average RMSE value for every product type is considered as the best model. At the fourth stage of this process, based on the estimated parameter value generated by the best model, a market growth pattern map is constructed with self-organizing map algorithm. A self-organizing map is learning with market pattern parameters for all products or services as input data, and the products or services are organized into an $N{\times}N$ map. The number of clusters increase from 2 to M, depending on the characteristics of the nodes on the map. The clusters are divided into zones, and the clusters with the ability to provide the most meaningful explanation are selected. Based on the final selection of clusters, the boundaries between the nodes are selected and, ultimately, the market growth pattern map is completed. The last step is to determine the final characteristics of the clusters as well as the market growth curve. The average of the market growth pattern parameters in the clusters is taken to be a representative figure. Using this figure, a growth curve is drawn for each cluster, and their characteristics are analyzed. Also, taking into consideration the product types in each cluster, their characteristics can be qualitatively generated. We expect that the process and system that this paper suggests can be used as a tool for forecasting demand in the ICT and other industries.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.17-25
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• 2017

Owing to recent climate change, the scale of rainfall tends to increase gradually and the risk of flooding has increased. Therefore, the importance of improving the levee management and disaster response is increasing. Levee management in Korea is carried out at the level of damage recovery after the occurrence of damage. Therefore, it is necessary to develop a technology for predicting and managing the levee safety with proactive river management. In this study, a method to estimate the safety against erosion and overflow was suggested. A map of levee safety that can be used as basic data is presented by displaying the levee safety on the map. The levee erosion safety was calculated as the ratio of the internal and external force for each shore type. The levee overflow safety was calculated as the ratio of the maximum conveyance and design flood. The maximum conveyance was a discharge when the level of the river was equal to the level of the levee crown. The levee safety was classified into 5 grades: very safe, safe, normal, dangerous, and very dangerous. As a research area from downstream of Nam River Dam to Nakdong River Junction, the levee safety against erosion and overflow was estimated for all levees and all cross-sections of the river. The levee safety was displayed on a map using GIS. Through the levee safety map as a result of this study, the levee safety can be observed intuitively. Using the levee safety map, a maintenance plan for a river can be easy to build. This levee safety map can be used to help determine the priority of investment for efficient budget used.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.366-372
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• 2019

The PRISM model has been used to estimate precipitation in South Korea where observation data are readily available at a large number of weather station. However, it is likely that the PRISM model would result in relatively low reliability of precipitation estimates in North Korea where weather data are available at a relatively small number of weather stations. Alternatively, a hybrid method has been developed to estimate the precipitation distribution in area where availability of climate data is relatively low. In the hybrid method, Regression coefficients between the precipitation-terrain relationships are applied to a low-resolution precipitation map produced using the PRISM. In the present study, a hybrid approach was applied to North Korea for estimation of precipitation distribution at a high spatial resolution. At first, the precipitation distribution map was produced at a low-resolution (2,430m) using the PRISM model. Secondly, a deviation map was prepared calculating difference between altitudes of synoptic stations and virtual terrains produced using 270m-resolution digital elevation map (DEM). Lastly, another deviation map of precipitation was obtained from the maps of virtual precipitation produced using observation data from the synoptic weather stations and both synoptic and automated weather station (AWS), respectively. The regression equation between precipitation and terrain was determined using these deviation maps. The high resolution map of precipitation distribution was obtained applying the regression equation to the low-resolution map. It was found that the hybrid approach resulted in better representation of the effects of the terrain. The precipitation distribution map for the hybrid approach had similar spatial pattern to that for the existing method. It was estimated that the mean annual cumulative precipitation of entire territory of North Korea was 1,195mm with a standard deviation of 253mm.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.5
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• pp.1421-1433
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• 2014

In this study, appropriate probability distribution and parameter estimation method were selected to perform snowfall frequency analysis. Generalized Extreme Value (GEV) and Probability Weighted Moment Method (PWMM) appeared to be the best fit for snowfall frequency analysis in Korea. Snowfall frequency analysis applying GEV and PWMM were performed for 69 stations in Korea. Peak snowfall corresponding to recurrence intervals were estimated based on frequency analysis while snow loads were calculated using the estimated peak snowfall and specific weight of snow. Design snow load map was developed using 100-year recurrence interval snow load of 69 stations through Kriging of ArcGIS. The 2009 Korean Building Code and Commentary for design snow load was assessed by comparing the design snow loads which calculated in this study. As reflected in the results, most regions are required to increase the design snow loads. Thus, design snow loads and the map were developed from based on the results. The developed design snow load map is expected to be useful in the design of building structures against heavy snow loading throughout Korea most especially in ungaged areas.

• Journal of Broadcast Engineering
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• v.19 no.3
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• pp.362-371
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• 2014

Blur variation caused by camera de-focusing provides a proper cue for depth estimation. Depth from Defocus (DFD) technique calculates the blur amount present in an image considering that blur amount is directly related to scene depth. Conventional DFD methods use two defocused images that might yield the low quality of an estimated depth map as well as a reconstructed infocused image. To solve this, a new DFD methodology based on infocused and defocused images is proposed in this paper. In the proposed method, the outcome of Subbaro's DFD is combined with a novel edge blur estimation method so that improved blur estimation can be achieved. In addition, a saliency map mitigates the ill-posed problem of blur estimation in the region with low intensity variation. For validating the feasibility of the proposed method, twenty image sets of infocused and defocused images with 2K FHD resolution were acquired from a camera with a focus control in the experiments. 3D stereoscopic image generated by an estimated depth map and an input infocused image could deliver the satisfactory 3D perception in terms of spatial depth perception of scene objects.

• Journal of the Korean GEO-environmental Society
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• v.17 no.9
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• pp.21-28
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• 2016

The purpose of this study is to compare the three areas that each estimated by using three different river topographic maps. For construction of river topographic maps, the data used in this study are ASTER, SRTM and a 1:5,000 scale digital map data sets in 14 streams of the Cheongdo-gun and Uiseong-gun. HEC-GeoRAS, RAS Mapper, and RiverCAD model are applied for the flooding area analysis using observed data and design rainfalls. The result of analysis is to compare observed flooding area based on the flood plain maps with estimated inundation area by hydraulic models and constructed river topographic maps. The results of this study are as follows; Flooding area by HEC-GeoRAS model is similar to the inundation area of flood plain map and appears in order of RAS Mapper, and RiverCAD model in all watersheds. Flood inundation area by SRTM DEM is similar to the result of 1:5,000 scale digital map in all watersheds and all analysis models. The SRTM DEM shows the most similarity to the digital map than ASTER DEM in all of the watershed scale and analysis models. HEC-GeoRAS and RiverCAD model are efficient models for flood inundation analysis in small watershed and HEC-GeoRAS and Ras Mapper model are efficient in medium to large watershed.

• Journal of Korea Water Resources Association
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• v.32 no.4
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• pp.457-467
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• 1999

No complete methods for estimating soil loss, included by rain storms, from a small watershed are available yet, and the best recommended method is to use measured data from the watershed. When no measured data is available from the watershed, empirical models for estimating the soil loss, such as the Universal Soil Loss Equation(USLE), is well recommended in practice. For using this equation, it is necessary to estimated the rainfall erosivity, commonly expressed as R, of the watershed. In this study, first we collected data of the probable rainfalls with the return periods of 2, 5, 10, 20, 30, 50, 80, 100, 200, and 500-yr and with the duration hours of 0.5, 1, 2, 3, 6, 12, and 24-hr. Using this data, we calculated the design values for R for the return period of 24-hr at each major rainfall-measuring station nationwide. Then we constructed the iso-erodent map of Korea for each return period of the 24-hr design storm. This study shows that the 24-hr duration iso-erodent map of the 5-yr return period is very similar to the annual average iso-erodent map of Korea. This study also shows that the 24-hr duration R-values of a certain return period can be estimated by multiplying certain parameters, obtained from this study, to the 24-hr duration R-values for the 5-yr return period or the annual average R-values. Finally, the R-values of the design storm with the 24-hr return period obtained from this study can be used for designing the settling basins at small watersheds.