• Atmosphere
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• v.31 no.2
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• pp.241-249
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• 2021

A smart city utilizes data collected from various sensors through the internet of things (IoT) and improves city operations across the urban area. Recently substantial research is underway to examine all aspects of data that requires for the smart city operation. Atmospheric data are an essential component for successful smart city implementation, including Urban Air Mobility (UAM), infrastructure planning, safety and convenience, and traffic management. Unfortunately, the current level of conventional atmospheric data does not meet the needs of the new city concept. New and innovative approaches to developing high spatiotemporal resolution of observational and modeling data, resolving the complex urban structure, are expected to support the future needs. The geographic information system (GIS) integrates the atmospheric data with the urban structure and offers information system enhancement. In this study we proposed the necessity and applicability of the high resolution urban meteorological dataset based on heavy fog cases in the smart city region (e.g., Sejong and Pusan) in Korea.

• Journal of Korean Society of Forest Science
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• v.100 no.4
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• pp.540-547
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• 2011

This study was conducted to compare classification accuracy by tree species using QuickBird imagery for pixel- and segment-based classifications that have been mostly applied to classify land covers. A total of 398 points was used as training and reference data. Based on this points, the points were classified into fourteen land cover classes: four coniferous and seven deciduous tree species in forest classes, and three non-forested classes. In pixel-based classification, three images obtained by using raw spectral values, three tasseled indices, and three components from principal component analysis were produced. For the both classification processes, the maximum likelihood method was applied. In the pixel-based classification, it was resulted that the classification accuracy with raw spectral values was better than those by the other band combinations. As resulted that, the segment-based classification with a scale factor of 50% provided the most accurate classification (overall accuracy:76% and ${\hat{k}}$ value:0.74) compared to the other scale factors and pixel-based classification.

• Journal of agriculture & life science
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• v.51 no.4
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• pp.139-147
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• 2017

This study was carried out in order to reduce the amount of sawdust for recycling the generated manure from livestock farms, and to investigate the effects on the reducing usage of sawdust and quality of produced compost. To do this, a cylindrical horizontal composting device were used in the experiments and compost was analyzed for judging produce compost quality. The experiment was carried out separately under different cases of operational control conditions. The first case was produced by using sawdust and pig manure mixture(Test-1); the second case was produced by using sawdust, pig manure and the previously produced compost(Test-2). In the second case, Except for some heavy metal content, The water content and C/N ratio were found to be suitable for fertilizer process specification of the RDA(Rural Development Administration) and it was found to reduce the sawdust 1.25tons usage.

• Journal of Apiculture
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• v.32 no.3
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• pp.253-259
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• 2017

Propolis, natural antibacterial agent, which has been used traditional medicine across the globe, is resinous mixture to include abundant bioactive substances. In present study, we investigated antimicrobial activity according to quality characteristics of propolis collected from 9 different regions in Korea. Antimicrobial activity was evaluated by measuring growth inhibition zone using agar well diffusion method against Streptococcus mutans. Constituents analysis of propolis samples were measured through total phenolic contents, total flavonoid contents and quantitative analysis of major compound (pinocembrin) by ultra performance liquid chromatography. As a result, 9 different propolis (10mg/mL) and pinocembrin (1mg/mL) showed antimicrobial activity that has growth inhibition zone more than 11.9mm on S. mutans. The total flavonoid contents of 8 different propolis excluding Jeju island were in compliance with standard of health functional food in Korea and were found to affect antimicrobial activity on S. mutans when contained over 10mg/g. In addition, when content of pinocembrin in propolis was ranged from 12mg/g to 32mg/g, each propolis excluding Jeju island exhibited antimicrobial activity alike. These results indicate that pinocembrin plays a important role for antimicrobial activity of propolis collected from 8 different regions in Korea, and that it can be used as basic data for standardization of Korean propolis.

• Food Engineering Progress
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• v.22 no.4
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• pp.309-314
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• 2018

In recent years, interest in halal authentication from the domestic food and cosmetics field has been growing for advances into the overseas halal market. For halal authentication, the product must not contain haram ingredients derived from pig, dog, human, GMO, etc. In this study, the presence of haram ingredients in plant extracts (carrot, oyster mushroom, and pine needle) treated with papain and bromelain and cosmetics (mask pack and cream) containing these extracts were analyzed by PCR to confirm whether these cosmetics were suitable for halal authentication. Detection limits of the PCR method that specifically detected template DNA of human, pig, dog, and GMO were $1.29{\times}10^3$, $1.14{\times}10^3$, $1.24{\times}10^2$ and $2.02{\times}10^3copies/tube$, respectively. PCR was not inhibited by the plant extracts or cosmetic ingredients. Results of PCR for the plant extracts or cosmetics containing these extracts were all negative. This PCR method could be used to rapidly identify the presence of haram ingredients in raw materials or final products during the manufacturing process of food and cosmetics.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.2
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• pp.125-137
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• 2007

This paper proposes a new scheme to provide the location privacy of sources in Wireless Sensor Networks (WSNs). Because the geographical location of a source sensor reveals contextual information on an 'event' in WSN, anonymizing the source location is an important issue. Despite abundant research efforts, however, about data confidentiality and authentication in WSN, privacy issues have not been researched well so far. Moreover, many schemes providing the anonymity of communication parties in Internet and Ad-hoc networks are not appropriate for WSN environments where sensors are very resource limited and messages are forwarded in a hop-by-hop manner through wireless channel. In this paper, we first categorize the type of eavesdroppers for WSN as Global Eavesdropper and Compromising Eavesdropper. Then we propose a novel scheme which provides the anonymity of a source according to the types of eavesdroppers. Furthermore, we analyze the degree of anonymity of WSN using the entropy-based modeling method. As a result, we show that the proposed scheme improves the degree of anonymity compared to a method without any provision of anonymity and also show that the transmission range plays a key role to hide the location of source sensors.

• Journal of Digital Convergence
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• v.18 no.12
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• pp.29-36
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• 2020

The background of this study is that machine learning administrative services are recently attracting attention as a major policy tool for non-face-to-face administrative services in the post-corona era. This study investigated the types of work expected to be effective when introducing machine learning administrative services for Seoul Metropolitan Government officials who are piloting machine learning administrative services. The research method is a machine that can be introduced by organizational unit by distributing and collecting questionnaires for Seoul administrative organizations that have performed machine learning-based administrative services for one month in July 2020 targeting Seoul public officials using machine learning-based administrative services. By analyzing the learning administration service and application service, the business characteristics of each machine learning administration service type such as supervised learning work type, unsupervised learning work type, and reinforced learning work type were analyzed. As a result of the research analysis, it was found that there were significant differences in the characteristics of administrative tasks by supervised and unsupervised learning areas. In particular, it was found that the reinforcement learning domain contains the most appropriate business characteristics for machine learning administrative services. Implications were drawn. The results of this study can be provided as a reference material to practitioners who want to introduce machine learning administration services, and can be used as basic data for research to researchers who want to study machine learning administration services in the future.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.375-388
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• 2021

This paper aims to help prevent the spread of COVID-19 by analyzing confirmed cases of COVID-19 in Daejeon. A high volume of visitors, downtown areas, and psychological fatigue with prolonged social distancing were considered as risk factors associated with the spread of COVID-19. We considered the weekly confirmed cases in each administrative district as a response variable. Explanatory variables were the number of passengers getting off at a bus station in each administrative district and the elapsed time since the Korean government had imposed distancing in daily life. We employed a mixed-effects zero-inflated Poisson regression model because the number of cases was repeatedly measured with excess zero-count data. We conducted k-means clustering to identify three groups of administrative districts having different characteristics in terms of the number of bars, the population size, and the distance to the closest college. Considering that the number of confirmed cases might vary depending on districts' characteristics, the clustering information was incorporated as a categorical explanatory variable. We found that Covid-19 was more prevalent as population size increased and a district is downtown. As the number of passengers getting off at a downtown district increased, the confirmed cases significantly increased.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.349-356
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• 2021

Since the 1960s, traffic infrastructure, such as bridges, has increased rapidly in Korea as urbanization and industrialization progressed due to economic growth. As the scale of the bridge becomes larger, stability analysis of the superstructure of the bridge is being conducted actively, but scour stability analysis for the substructure of the bridge has not been conducted sufficiently. This study is a basic investigation to prevent large-scale disasters caused by scouring in bridge piers. A simple linear regression model was used to analyze the scour depth calculated through seventeen scour depth calculation formulae, and the scour depth measured through hydraulic model experiments. As a result, the Coleman (1971) formula was the best method among the scour depth calculation formulae, and the Froehlich (1987) formula was the most effective method for calculating the scour depth. In addition, a review using a simple regression model confirmed that the scour depth calculation formulae of CSU (1993), Coleman (1971), and Froehlich (1987) can predict a similar scour depth by reflecting domestic stream characteristics. This study can calculate the scour depth reflecting the environmental conditions of Korea in future stream design.

• Food Engineering Progress
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• v.23 no.1
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• pp.62-68
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• 2019

In this study, the physical and sensorial properties of the meat analog were studied for the purpose of improving sensory preference and mimicking animal meat. The meat analog was made with different types of liquid materials such as oil, water, lecithin, polysorbate 80, or the emulsion of these components. At the aspect of density, the sample mixed with oil was higher than the sample mixed with water. Cooking loss value was higher at the sample with water than the sample with oil and this was the result opposite to the liquid holding capacity analysis. Also, texture profile analysis result showed that the samples with medium chain triglycerides (MCT) oil only showed the highest values in all attributes except for adhesiveness. Principal component analysis was carried out to analyze sensorial properties and it showed that the overall acceptance was high when the juiciness and softness increased. This result was highly related with the addition of emulsion. Therefore, emulsion technology can be a good candidate for improving the quality of meat analog and for mimicking the taste of animal meat.