• Asian Journal of Atmospheric Environment
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• v.7 no.1
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• pp.25-37
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• 2013

Open biomass burning (excluding biofuels) is an important contributor to air pollution in the Asian region. Estimation of emissions from fires, however, has been problematic, primarily because of uncertainty in the size and location of sources and in their temporal and spatial variability. Hence, more comprehensive tools to estimate wildfire emissions and that can characterize their temporal and spatial variability are needed. Furthermore, an emission processing system that can generate speciated, gridded, and temporally allocated emissions is needed to support air-quality modeling studies over Asia. For these reasons, a biomass-burning emissions modeling system based on satellite imagery was developed to better account for the spatial and temporal distributions of emissions. The BlueSky Framework, which was developed by the USDA Forest Service and US EPA, was used to develop the Asian biomass-burning emissions modeling system. The sub-models used for this study were the Fuel Characteristic Classification System (FCCS), CONSUME, and the Emissions Production Model (EPM). Our domain covers not only Asia but also Siberia and part of central Asia to assess the large boreal fires in the region. The MODIS fire products and vegetation map were used in this study. Using the developed modeling system, biomass-burning emissions were estimated during April and July 2008, and the results were compared with previous studies. Our results show good to fair agreement with those of GFEDv3 for most regions, ranging from 9.7 % in East Asia to 52% in Siberia. The SMOKE modeling system was combined with this system to generate three-dimensional model-ready emissions employing the fire-plume rise algorithm. This study suggests a practicable and maintainable methodology for supporting Asian air-quality modeling studies and to help understand the impact of air-pollutant emissions on Asian air quality.

• Smart Media Journal
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• v.3 no.1
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• pp.9-15
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• 2014

In these days, along with the extreme popularity of online social network services, it becomes an important problem understanding the role of social network in the research of message dissemination. Past studies of message dissemination over online social network services mostly consider the coverage of message dissemination and the methods to maximize it. But, these works lack of the consideration of the impact of multi channel social network, which has multiple communication channel with distinct properties of message transfer and various users with distinct channel preferences. In this paper, the new message dissemination model over multi-modal multi-channel social network, the Delay Weighted Independent Cascade Model, is proposed. The proposed model considers various channels including online social network service, email, SMS messaging, phone and mouth-to-mouth and their distinct message transfer properties. In order to consider the various user properties, the different value of probability of forwarding a message and the different preference of communication channel is considered. Moreover, the proposed model considers the distribution of user location and allows to analyze the properties of message dissemination under various scenarios. Based on the proposed model, a message dissemination simulator is generated and the message disseminations on various scenarios are analyzed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.1
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• pp.121-130
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• 2010

As the development of wireless environment and portable devices, navigation companies need more spatial information for Location Based Service and so they are investing heavily in this part. But my country have constructed lots of spatial dataset during the NGIS project, and then we can reduce costs by using constructed spatial dataset. The integration method of each building information between e-AIS and KLIS-rn is linked to designed mapping table by main building numbers and auxiliary cadastral number. e-AIS and KLIS-rn are integrated by the feature matching between CAD data and KLIS-rn. Due to the limitation of test data, more accuracy test will be required with various data sets.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.63-68
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• 2017

In this paper, Distance recognition measurement using distance calculation correction algorithm, was realization through LED dimming control. The calculation values for the RSSI average filtering and the RSSI feedback filtering were calculated and applied to reduce the error of the RSSI value measured from a long distance. It was confirmed that the RSSI values through the average filtering and the RSSI values measured by setting the coefficient value of the feedback filtering to 0.5 were ranged from -61 dBm to - 52.5 dBm, which shows irregular and high values decrease slightly as much as about -2 dBm to -6 dBm as compared to general measurements. A distance calculation correction algorithm to improve the accuracy was applied, which confirmed that as the distance increases, the range of errors decreases. In conclusion, unstable signals were corrected using the RSSI measurement result filtering, and the distance calculation correction algorithm was applied and performed to reduce the range of errors. In addition, RGB colors were implemented by LED to indicate the distance determination and the signal stability.

• The Research Journal of the Costume Culture
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• v.21 no.2
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• pp.167-182
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• 2013

The purposes of this study were to identify dimensions of shopping orientation and preferences of fashion trade areas, to test differences in the preference factors and usage levels of fashion trade areas as determined by shopping orientation and demographic characteristics. Questionnaires were administered to 406 adults in their twenties and thirties visited major fashion trade area in Seoul. The results of the study were as follows. First, five groups were identified based on shopping orientation: combined value-oriented group, convenience-oriented group, hedonic value trend-oriented group, economic-value oriented group and brand-oriented group. Second, the most frequently visited trade area was Myungdong, and there were significant differences in the usage levels of the trade areas except Dongdaemun, Samsung station COEX, Jamsil and Gangnam Express Bus Terminal among the groups determined by shopping orientation. Sinsa Garosoogil, Apgujeong Chungdam and Samsung Station COEX were preferred by hedonic value trend-oriented group. Daehakro and Myungdong were preferred by combined value-oriented group and convenience-oriented group. Third, significant differences were also found in all groups in the preference factors of the trade area as determined by shopping orientation groups when purchasing clothing. Forth, female preferred Gangnam Express Bus Station and Jamsil than male did. Those who in their early twenties preferred Daehakro and Myungdong the most and those who in early thirties and late twenties concerned service policy the most. The results imply that the consumers tend to visit the nearest fashion trade area by their residence(or work, school) and consider the location and accessibility of the trade area as the most important factor.

• The KIPS Transactions:PartA
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• v.15A no.2
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• pp.101-110
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• 2008

Ubiquitous computing has extended the computer system into the whole physical space and has ushered the emergence of more dynamic distributed systems. This environment require unique QoS parameters for various devices, resources and user requirements. In this paper, we propose a new hybrid QoS management model which defines a static-dynamic QoS parameter that is more appropriate to the ubiquitous computing environment. This model consists of the QoS Control Management Module(QoS CMM) in the client side and the Resource QoS Management Module (RQoS MM) in the server side. The RQoS MM deals with the static QoS parameters and the whole QoS control of the distributed control(QoS CMM) in order to minimize server load in cases of multiple communication. Finally, we present the experimental result of our location based application using a graphical user interface that shows the multimedia service execution of selected client device types such as desktop PC, notebook and PDA.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.341-348
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• 2014

The advance in web accessibility with dissemination of smart phones gives rise to rapid increment of users on social network platforms. Many research projects are in progress to detect events using Twitter because it has a powerful influence on the dissemination of information with its open networks, and it is the representative service which generates more than 500 million Tweets a day in average; however, existing studies to detect events has been used TFIDF algorithm without any consideration of the various conditions of tweets. In addition, some of them detected predefined events. In this paper, we propose the RTFIDF VT algorithm which is a modified algorithm of TFIDF by reflecting features of Twitter. We also verified the optimal section of TF and DF for detecting events through the experiment. Finally, we suggest a system that extracts result-sets of places and related keywords at the given specific time using the RTFIDF VT algorithm and validated section of TF and DF.

• Journal of Digital Convergence
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• v.12 no.3
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• pp.243-248
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• 2014

Recently, solar energy is expanding to combination of computing in real time by tracking the position of the sun to estimate the angle of inclination and make up freshly correcting a part of the solar radiation. Solar power is need that reliably linked technology to power generation system renewable energy in order to efficient power production that is difficult to output predict based on the position of the sun rise. In this paper, we analysis of prediction model for solar power generation to estimate the predictive value of solar power generation in the development of real-time weather data. Photovoltaic power generation input the correction factor such as temperature, module characteristics by the solar generator module and the location of the local angle of inclination to analyze the predictive power generation algorithm for the prediction calculation to predict the final generation. In addition, the proposed model in real-time national weather service forecast for medium-term and real-time observations used as input data to perform the short-term prediction models.

• YAKHAK HOEJI
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• v.52 no.6
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• pp.507-513
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• 2008

The purpose of this study is to analyze the factors affecting financial performance of community pharmacies after the implementation of the new drug policy in Korea: separation of drug prescription and dispensing (SPD). The online survey questionnaires were sent to the active pharmacists of the total 20,633 community pharmacies in Korea and 1,147 pharmacists responded to the survey (the response rate was 5.5%). The questionnaire asked simple financial data in order to compare their financial performances before and after the policy. With the SPSS package (version 12.0), two levels of data analysis were used: 1) descriptive statistics to see the financial status of the pharmacies; and 2) multiple regression analysis to find the factors. {or A multiple regression method was used for the data analysis.} The finding illustrated that the average net benefit of the pharmacies was 4,870 thousand won in August 2006, and the major factors affecting the net benefit were the location of pharmacy (geographical proximity to medical institutions), number of prescriptions, drug management services for patients, chain pharmacy membership. The findings of this study suggest that service improvement for patients, revitalization of non-prescription drug sales, professional management will contribute to promote community based pharmacy business.

• The Journal of Bigdata
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• v.5 no.1
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• pp.209-225
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• 2020

This study tried to establish a base level for the form of ginseng in order to prevent fraud in which novice consumers, who have no information on ginseng and mountain ginseng, regard ginseng as mountain ginseng. To that end, researchers designed a service design in which when a consumer takes a picture of ginseng with an APP dedicated to a smartphone, the photo is sent remotely and the determined results are sent to the consumer based on machine learning data. In order to minimize the difference between the data set in the research process and the background color, location, size, illumination, and color temperature of the mountain ginseng when consumers took pictures through their smartphones, the filming box exclusively for consumers was designed. Accordingly, the collection of mountain ginseng samples was made under the same controlled environment and setting as the designed box. This resulted in a 100% predicted probability from the CNN(VGG16) model using a sample that was about one-tenth less than widley required in machine learning.