• Journal of Plant Biotechnology
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• v.43 no.3
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• pp.347-358
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• 2016

Brassinosteroid (BR), a plant steroid hormone, plays key roles in numerous growth and developmental processes as well as tolerance to both abiotic and biotic stress. To understand the biological networks involved in BR-mediated signaling pathways and stress tolerance, we performed comparative genome-wide transcriptome analysis of a constitutively activated BR bes1-D mutant with an Agilent Arabidopsis $4{\times}44K$ oligo chip. As a result, we newly identified 1,091 (562 up-regulated and 529 down-regulated) significant differentially expressed genes (DEGs). The combination of GO enrichment and protein network analysis revealed that stress-related processes, such as metabolism, development, abiotic/biotic stress, immunity, and defense, were critically linked to BR signaling pathways. Among the identified gene sets, we confirmed more than a 6-fold up-regulation of NB-ARC and FLS2 in bes1-D plants. However, some genes, including TIR1, TSA1 and OCP3, were down-regulated. Consistently, BR-activated plants showed higher tolerance to drought stress and pathogen infection compared to wild-type controls. In this study, we newly developed a useful, comprehensive method for large-scale identification of critical network and gene sets with global transcriptome analysis using a microarray. This study also showed that gain of function in the bes1-D gene can regulate the adaptive response of plants to various stressful conditions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.4
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• pp.317-324
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• 2015

GNSS was firstly proposed for application in weather forecasting in the mid-1980s. It has continued to demonstrate the practical uses in GNSS meteorology, and other relevant researches are currently being conducted. Precipitable Water Vapor (PWV), calculated based on the GNSS signal delays due to the troposphere of the Earth, represents the amount of the water vapor in the atmosphere, and it is therefore widely used in the analysis of various weather phenomena such as monitoring of weather conditions and climate change detection. In this study we calculated the PWV through the meteorological information from an Automatic Weather Station (AWS) as well as GNSS data processing of a Continuously Operating Reference Station (CORS) in order to analyze the heavy snowfall of the Ulsan area in early 2014. Song’s model was adopted for the weighted mean temperature model (T_m), which is the most important parameter in the calculation of PWV. The study period is a total of 56 days (February 2013 and 2014). The average PWV of February 2014 was determined to be 11.29 mm, which is 11.34% lower than that of the heavy snowfall period. The average PWV of February 2013 was determined to be 10.34 mm, which is 8.41% lower than that of not the heavy snowfall period. In addition, certain meteorological factors obtained from AWS were compared as well, resulting in a very low correlation of 0.29 with the saturated vapor pressure calculated using the empirical formula of Magnus. The behavioral pattern of PWV has a tendency to change depending on the precipitation type, specifically, snow or rain. It was identified that the PWV showed a sudden increase and a subsequent rapid drop about 6.5 hours before precipitation. It can be concluded that the pattern analysis of GNSS PWV is an effective method to analyze the precursor phenomenon of precipitation.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.2
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• pp.51-60
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• 2021

Modern society is becoming more informed and intelligent with the development of digital technology, in which humans, objects, and networks relate with each other. In accordance with the changing times, a garden system has emerged that makes it easy to supply the ideal temperature, humidity, sunlight, and moisture conditions to grow plants. Therefore, this study attempted to grasp the concept, perception, and trends of smart gardens, a recent concept. To achieve the purpose of this study, previous studies and text mining were used, and the results are as follows. First, the core characteristics of smart gardens are new gardens in which IoT technology and gardening techniques are fused in indoor and outdoor spaces due to technological developments and changes in people's lifestyles. As technology advances and the importance of the environment increases, smart gardens are becoming a reality due to the need for living spaces where humans and nature can co-exist. With the advent of smart gardens, it will be possible to contribute to gardens' vitalization to deal with changes in garden-related industries and people's lifestyles. Second, in current research related to smart gardens and users' experiences, the technical aspects of smart gardens are the most interesting. People value smart garden functions and technical aspects that enable a safe, comfortable, and convenient life, and subjective uses are emerging depending on individual tastes and the comfort with digital devices. Third, looking at the usage behavior of smart gardens, they are mainly used in indoor spaces, with edible plants are being grown. Due to the growing importance of the environment and concerns about climate change and a possible food crisis, the tendency is to prefer the cultivation of plants related to food, but the expansion of garden functions can satisfying users' needs with various technologies that allow for the growing of flowers. In addition, as users feel the shapes of smart gardens are new and sophisticated, it can be seen that design is an essential factor that helps to satisfy users. Currently, smart gardens are developing in terms of technology. However, the main components of the smart garden are the combination of humans, nature, and technology rather than focusing on growing plants conveniently by simply connecting potted plants and smart devices. It strengthens connectivity with various city services and smart homes. Smart gardens interact with the landscape of the architect's ideas rather than reproducing nature through science and technology. Therefore, it is necessary to have a design that considers the functions of the garden and the needs of users. In addition, by providing citizens indoor and urban parks and public facilities, it is possible to share the functions of communication and gardening among generations targeting those who do not enjoy 'smart' services due to age and bridge the digital device and information gap. Smart gardens have potential as a new landscaping space.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.163-176
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• 2014

Social media is becoming the platform for users to communicate their activities, status, emotions, and experiences to other people. In recent years, microblogs, such as Twitter, have gained in popularity because of its ease of use, speed, and reach. Compared to a conventional web blog, a microblog lowers users' efforts and investment for content generation by recommending shorter posts. There has been a lot research into capturing the social phenomena and analyzing the chatter of microblogs. However, measuring television ratings has been given little attention so far. Currently, the most common method to measure TV ratings uses an electronic metering device installed in a small number of sampled households. Microblogs allow users to post short messages, share daily updates, and conveniently keep in touch. In a similar way, microblog users are interacting with each other while watching television or movies, or visiting a new place. In order to measure TV ratings, some features are significant during certain hours of the day, or days of the week, whereas these same features are meaningless during other time periods. Thus, the importance of features can change during the day, and a model capturing the time sensitive relevance is required to estimate TV ratings. Therefore, modeling time-related characteristics of features should be a key when measuring the TV ratings through microblogs. We show that capturing time-dependency of features in measuring TV ratings is vitally necessary for improving their accuracy. To explore the relationship between the content of microblogs and TV ratings, we collected Twitter data using the Get Search component of the Twitter REST API from January 2013 to October 2013. There are about 300 thousand posts in our data set for the experiment. After excluding data such as adverting or promoted tweets, we selected 149 thousand tweets for analysis. The number of tweets reaches its maximum level on the broadcasting day and increases rapidly around the broadcasting time. This result is stems from the characteristics of the public channel, which broadcasts the program at the predetermined time. From our analysis, we find that count-based features such as the number of tweets or retweets have a low correlation with TV ratings. This result implies that a simple tweet rate does not reflect the satisfaction or response to the TV programs. Content-based features extracted from the content of tweets have a relatively high correlation with TV ratings. Further, some emoticons or newly coined words that are not tagged in the morpheme extraction process have a strong relationship with TV ratings. We find that there is a time-dependency in the correlation of features between the before and after broadcasting time. Since the TV program is broadcast at the predetermined time regularly, users post tweets expressing their expectation for the program or disappointment over not being able to watch the program. The highly correlated features before the broadcast are different from the features after broadcasting. This result explains that the relevance of words with TV programs can change according to the time of the tweets. Among the 336 words that fulfill the minimum requirements for candidate features, 145 words have the highest correlation before the broadcasting time, whereas 68 words reach the highest correlation after broadcasting. Interestingly, some words that express the impossibility of watching the program show a high relevance, despite containing a negative meaning. Understanding the time-dependency of features can be helpful in improving the accuracy of TV ratings measurement. This research contributes a basis to estimate the response to or satisfaction with the broadcasted programs using the time dependency of words in Twitter chatter. More research is needed to refine the methodology for predicting or measuring TV ratings.

• Journal of the Korean Society of Food Culture
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• v.6 no.4
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• pp.421-432
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• 1991

This study was conducted to investigate the intake of a kind of Gom-Tang (Beef soup made with internal organs and bone), which is the Korean traditional food, and factors affecting the eating behavior of customers. Two hundred male customers of a H Korean Restaurant specialized in Gom-Tang, which is a well-known restaurant in Seoul, were surveyed from June 26 to 29, 1990. The results were shown as follows. (1) ${\ulcorner}$Frequency of intake${\lrcorner}$ and ${\ulcorner}$preference${\lrcorner}$ were very high. Those who took a kind of Gom-Tang ${\ulcorner}$more than once a week${\lrcorner}$ were 66.5% of the subjects. Those who evaluated ${\ulcorner}$good${\lrcorner}$ for the taste and flavor were 86.5% and 59.0% of the subjects, respectively. (2) The reasons why they chose a kind of Gom-Tang from among many Korean traditional foods were ${\ulcorner}$preference${\lrcorner}$ and ${\ulcorner}$phygiological condition${\lrcorner}$ in ${\ulcorner}$high frequency of intake${\lrcorner}$ group. ${\ulcorner}$Phygiological condition${\lrcorner}$ was more critical factor than ${\ulcorner}$preference${\lrcorner}$ in ${\ulcorner}$low frequency of intake${\lrcorner}$ group. (3) The effect of the intake of a kind of Gom-Tang on health was evaluated as ${\ulcorner}$healthy${\lrcorner}$ (80.5%). ${\ulcorner}$No effect${\lrcorner}$ and ${\ulcorner}$harmful${\lrcorner}$ were 30.5% and 6.5%, respectively. (4) ${\ulcorner}$High frequency of intake${\lrcorner}$ group, mainly more than 50 years of age, had a high ${\ulcorner}$preference${\lrcorner}$ and ${\ulcorner}$food knowledge${\lrcorner}$ as well as positive ${\ulcorner}$eating behavior${\lrcorner}$ and ${\ulcorner}$healthy state${\lrcorner}$, ${\ulcorner}$Middle frequency of intake${\lrcorner}$ group, mainly the forties, had a high ${\ulcorner}$preference${\lrcorner}$, but had less positive ${\ulcorner}$eating behavior${\lrcorner}$ than ${\ulcorner}$high frequency of intake${\lrcorner}$ group. ${\ulcorner}$Low frequency of intake${\lrcorner}$ group, mainly the twenties and thirties, had a medial ${\ulcorner}$preference${\lrcorner}$. They took a kind of Gom-Tang for reasons of ${\ulcorner}$on the recommendation of friends${\lrcorner}$ better than ${\ulcorner}$preference${\lrcorner}$. Foregoing results showed that ${\ulcorner}$a kind of Gom-Tang${\lrcorner}$ was a typical food recognized as ${\ulcorner}$healthy${\lrcorner}$ as well as ${\ulcorner}$delicious${\lrcorner}$. This may suggest that ${\ulcorner}$a kind of Gom-Tang${\lrcorner}$ is a candidate for the effective food on nutritional education.