• Convergence Security Journal
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• v.22 no.2
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• pp.105-114
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• 2022

This paper is presents an intelligent control system that visualizes the direction of arrival for hearing impaired using personal mobility, and aims to recognize and prevent dangerous situations caused by sound such as alarm sounds and crack sounds on roads. The position estimation method of sound source uses a machine learning classification model characterized by generalized correlated phase transformation based on time difference of arrival. In the experimental environment reproducing the road situations, four classification models learned after extracting learning data according to wind speeds 0km/h, 5.8km/h, 14.2km/h, and 26.4km/h were compared with grid search cross validation, and the Muti-Layer Perceptron(MLP) model with the best performance was applied as the optimal algorithm. When wind occurred, the proposed algorithm showed an average performance improvement of 7.6-11.5% compared to the previous studies.

• Journal of Internet of Things and Convergence
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• v.8 no.1
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• pp.17-22
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• 2022

This paper is a study on the self-powered wireless bus information and disaster information system based on Internet of Things (IoT). The existing bus information system supplies power and communication by cable, which causes a problem of increased installation cost and limited installation site due to cable burial. To solve this problem, a self-powered wireless bus information and disaster information system was proposed. The proposed system provides bus arrival information. Furthermore, in the event of a disaster such as a natural disaster, it can also reduce confusion and damage by notifying the disaster information through the system's speaker. In this study, a self-powered system using a solar module was proposed. As data are transmitted and received through wireless WiFi or LTE, the installation cost can be reduced and the problem of installation location restrictions can be solved.

• Journal of the Korea Computer Graphics Society
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• v.30 no.4
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• pp.1-10
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• 2024

In the fields of computer animation and robotics, reaching a destination while avoiding obstacles has always been a difficult task. Moreover, generating appropriate motions while planning a route is even more challenging. Recently, academic circles are actively conducting research to generate character motions by modifying and utilizing VAE (Variational Auto-Encoder), a data-based generation model. Based on this, in this study, the latent space of the MVAE model is learned using a reinforcement learning method[1]. With the policy learned in this way, the character can arrive its destination while avoiding both static and dynamic obstacles with natural motions. The character can easily avoid obstacles moving in random directions, and it is experimentally shown that the performance is improved, and the learning time is greatly reduced compared to existing approach.

• Journal of the Korean Geographical Society
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• v.49 no.4
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• pp.525-545
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• 2014

This study seeks to clarify the influence of the stage migration which has proceeded through generations, on the population growth of local cities in the case of Jeollabuk-do. For this, setting to baby boomer as parents generation and echo boomer as their children, this study traces each generation's birth, distribution and the process of selective migration using aggregate level data. And the stage migration is analyzed by O-D, divided into three regions in each; Jeollabuk-do rural areas, Jeollabuk-do cities and other provinces. The major findings of this study are as follows. First, it was estimated that the number of the baby boomer births in Jeollabuk-do rural areas was seven times more numerous than in cities. Second, both rural and urban born baby boomers overwhelmingly moved into other provinces, especially Seoul metropolitan area and metropolis in their selective migration processes. However, there was also migration stream from rural areas to cities in Jeollabuk-do and the amount of this stream was approximately equal to the amount of outflux from cities in Jeollabuk-do to other provinces. Third, due to baby boomers' stage migration, from rural to urban, echo boomers were born in cities more than in rural areas. Fourth, urban born echo boomers still have moved into other provinces just like their parents generation in selective migration process. But comparing with baby boomer, the number of echo boomers influx from rural areas to cities has decreased. Consequentially the population of echo boomer in Jeollabuk-do cities also has decreased. Finally, the stage migration has been a basic cause of the social growth of urban population, and also influenced on the natural growth, closely connected with migrants' life course, such as marriage, childbirth and rearing. Therefore, this study concludes that the stage migration through generations is one of the crucial factor to understand the population growth in local cities.

• Journal of the Korean association of regional geographers
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• v.7 no.3
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• pp.107-120
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• 2001

This study is concerned with providing a reliable procedure of calibrating a set of places specific distance parameters and with applying it to U.S. inter-State migration flows between 1985 and 1900. It attempts to conform to recent advances in quantitative geography that are characterized by an integration of ESDA(exploratory spatial data analysis) and local statistics. ESDA aims to detect the spatial clustering and heterogeneity by visualizing and exploring spatial patterns. A local statistic is defined as a statistically processed value given to each location as opposed to a global statistic that only captures an average trend across a whole study region. Whereas a global distance parameter estimates an averaged level of the friction of distance, place-specific distance parameters calibrate spatially varying effects of distance. It is presented that a poisson regression with an adequately specified design matrix yields a set of either origin-or destination-specific distance parameters. A case study demonstrates that the proposed model is a reliable device of measuring a spatial dimension of migration, and that place-specific distance parameters are spatially heterogeneous as well as spatially clustered.

• Journal of the Society of Disaster Information
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• v.20 no.2
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• pp.339-350
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• 2024

Purpose: This study analyzes accessibility of 10 hydrogen charging stations in Seoul and identifies areas that were difficult to access. The purpose is to re-analyze accessibility by adding a new location in terms of equity and safety of location placement, and then draw implications by comparing the improvement effects. Method: By applying the location-allocation model and the service area model based on network analysis of the ArcGIS program, areas with weak access were identified. The location selection method applied the 'Minimize Facilities' method in consideration of the need for rapid arrival to insufficient hydrogen charging stations. The limit distance for arrival within a specific time was analyzed by applying the average vehicle traffic speed(23.1km/h, Seoul Open Data Square) in 2022 to three categories: 3,850m(10minutes), 5,775m(15minutes), 7,700m(20minutes). In order to minimize conflicts over the installation of hydrogen charging stations, special standards of the Ministry of Trade, Industry and Energy applied to derive candidate sites for additional installation of hydrogen charging stations among existing gas stations and LPG/CNG charging stations. Result: As a result of the analysis, it was confirmed that accessibility was significantly improved by installing 5 new hydrogen charging stations at relatively safe gas stations and LPG/CNG charging stations in areas where access to the existing 10 hydrogen charging stations is weak within 20 minutes. Nevertheless, it was found that there are still areas where access remains difficult. Conclusion: The location allocation model is used to identify areas where access to hydrogen charging stations is difficult and prioritize installation, decision-making to select locations for hydrogen charging stations based on scientific evidence can be supported.

• Economic and Environmental Geology
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• v.57 no.2
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• pp.161-175
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• 2024

Aggregate typically refers to sand and gravel formed by the transportation of rocks in rivers or artificially crushed, constituting a core resource in the construction industry. Gyeongsangbuk-do, the largest administrative area in South Korea, produces various sources of gravel, including forest, land (excluding other sources), river, and crushed stone. As of 2022, it has extracted approximately 6.96 million cubic meters of aggregate, with permitted production totaling around 4.07 million cubic meters and reported production of about 2.88 million cubic meters. The aggregate demand in Gyeongsangbuk-do is estimated to be 12.39 million cubic meters according to the estimation method in Ready-Mix Concrete. From the supply perspective, about 120 extraction sites are operational, with most municipalities maintaining an appropriate balance between aggregate demand and supply. However, in some areas, there is inbound and outbound transportation of aggregate to neighboring regions. Regions with significant inbound and outbound aggregate transportation in Gyeongsangbuk-do are areas connected to Daegu Metropolitan City and Pohang City along the Gyeongbu rail line, showing a high correlation with population distribution. Gyeongsangbuk-do faces challenges such as population decline, aging rural areas, and insufficient balanced regional development. Analysis using GIS reveals these trends in gravel demand and supply. Currently in this study, Gyeongsangbuk-do meets its demand for aggregate through the supply of various aggregate sources, maintaining stable aggregate procurement. River and terrestrial aggregates may be sustained as short-term supply strategies due to the difficulty of longterm development. Considering the reliance on raw material supply for selective crushing, it suggests the need for raw material management to maintain stability. Gyeongsangbuk-do highlights quarries in the forest as an important resource for sustainable aggregate supply, advocating for the development of large-scale aggregate quarries as a long-term alternative. These research findings are expected to provide valuable insights for formulating strategies for sustainable management and stable utilization of aggregate resources.

• Journal of the Korea Society for Simulation
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• v.28 no.4
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• pp.57-65
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• 2019

Recently, the Korean military has been drastically reducing its active-duty troops due to rapid demographic changes and the reconciliatory mode between the two Koreas. Under these circumstances, the wartime reserve forces play an important role. In times of war, a successful personal mobilization is critical especially in early combat stage. Previous research has been carried out using insufficient data collected only within the military and there have been limitations on empirical analysis due to changes in the designation methods for personal mobilization. This study analyzes how much of the reserve forces can be filled at the prescribed time by analyzing the transportation route of the reserve forces in wartime by utilizing military-related data and credit card usage data of the reserve forces residing in Yong-in city. The analysis showed that all reserve forces could not be called up within the prescribed time. In particular, Gangwon Province has shown results of less than 70 percent call-ups, and could cause serious weakening of combat capabilities in the early stages of the war. The main reasons could be the difference between the actual residence and the residence address and the excessive time caused by the traffic congestion.

• Journal of Astronomy and Space Sciences
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• v.25 no.4
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• pp.383-394
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• 2008

We examine geoeffective directional parameters of coronal mass ejections (CMEs). We select 30 front-side halo CMEs from SOHO LASCO CMEs whose speed is larger than 1000km/s and longitude is less than ${\pm}30^{\circ}$. These are thought to be the most plausible candidate of geoeffective CMEs. We examine the relation between CMEs directional parameters (Earthward direction, eccentricity, ${\Delta}$ distance and central angle parameter) and the minimum value of the Dst index. We have found that the Earthward direction parameter has a good correlation with the Dst index, the eccentricity parameter has a much better correlation with the Dst index. The bo distance and central angle parameter has a poor correlation with the Dst index. It's, however, well correlated with the Dst index in very strong geomagnetic storms. Most of CMEs causing very strong storms (Dst ${\leq}$-200nT) are found to have large Earthward direction parameter $({\geq}0.6)$, small eccentricity, bo distance and central angle parameters $(E{\leq}0.4,\;{\Delta}X\;and\;sin\;{\theta}{\leq}0.2)$. These directional parameters are very important parameters that control the geoeffectiveness of very fast front-side halo CMEs.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.237-246
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• 2020

this paper, a data modeling method based on decision-making conditions is proposed for making combat and battlefield management systems to be intelligent, which are also a decision-making support system. A picture of a robot seeing and perceiving like humans and arriving a point it wanted can be understood and be felt in body. However, we can't find an example of implementing a decision-making which is the most important element in human cognitive action. Although the agent arrives at a designated office instead of human, it doesn't support a decision of whether raising the market price is appropriate or doing a counter-attack is smart. After we reviewed a current situation and problem in control & command of military, in order to collect a big data for making a machine staff's advice to be possible, we propose a data modeling prototype based on decision-making conditions as a method to change a current control & command system. In addition, a decision-making tree method is applied as an example of the decision making that the reformed control & command system equipped with the proposed data modeling will do. This paper can contribute in giving us an insight of how a future AI decision-making staff approaches to us.