• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.301-308
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• 2022

Algae is an indispensable primary producer in the ecosystem by supplying energy to consumers in the aquatic ecosystem, and is largely divided into green algae, blue-green algae, and diatoms. In the case of blue-green algae, the water temperature rises, which occurs in the summer and overgrows, which is the main cause of the algae bloom. Recently, the change in the occurrence time and frequency of the algae bloom is increasing due to climate change. Existing algae survey methods are performed by collecting water and measuring through sensors, and time, cost and manpower are limited. In order to overcome the limitations of these existing monitoring methods, research has been conducted to perform remote monitoring using spectroscopic devices such as multispectral and hyperspectral using satellite image, UAV, etc. In this study, we tried to confirm the possibility of species classification of remote monitoring through laboratory-scale experiments through algal culture and river water collection. In order to acquire hyperspectral images, a hyperspectral sensor capable of analyzing at 400-1000 nm was used. In order to extract the spectral characteristics of the collected river water for classification of algae species, filtration was performed using a GF/C filter to prepare a sample and images were collected. Radiation correction and base removal of the collected images were performed, and spectral information for each sample was extracted and analyzed through the process of extracting spectral information of algae to identify and compare and analyze the spectral characteristics of algae, and remote sensing based on hyperspectral images in rivers and lakes. We tried to review the applicability of monitoring.

• Korean Journal of Remote Sensing
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• v.33 no.2
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• pp.189-199
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• 2017

Thisstudy quantitatively analyzed the research trendsin the use ofICT ofthe environmental field using the text mining technique. To that end, the study collected 359 papers published in the past two decades(1996-2015)from the National Digital Science Library (NDSL) using 38 environment-related keywords and 16 ICT-related keywords. It processed the natural languages of the environment and ICT fields in the papers and reorganized the classification system into the unit of corpus. It conducted the text mining analysis techniques of frequency analysis, keyword analysis and the association rule analysis of keywords, based on the above-mentioned keywords of the classification system. As a result, the frequency of the keywords of 'general environment' and 'climate' accounted for 77 % of the total proportion and the keywords of 'public convergence service' and 'industrial convergence service' in the ICT field took up approximately 30 % of the total proportion. According to the time series analysis, the researches using ICT in the environmental field rapidly increased over the past 5 years (2011-2015) and the number of such researches more than doubled compared to the past (1996-2010). Based on the environmental field with generated association rules among the keywords, it was identified that the keyword 'general environment' was using 16 ICT-based technologies and 'climate' was using 14 ICT-based technologies.

• Journal of Intelligence and Information Systems
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• v.14 no.3
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• pp.59-76
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• 2008

In this paper, we propose an agent architecture called L-CAA that is quite effective in real-time dynamic environments. L-CAA is an extension of CAA, the behavior-based agent architecture which was also developed by our research group. In order to improve adaptability to the changing environment, it is extended by adding reinforcement learning capability. To obtain stable performance, however, behavior selection and execution in the L-CAA architecture do not entirely rely on learning. In L-CAA, learning is utilized merely as a complimentary means for behavior selection and execution. Behavior selection mechanism in this architecture consists of two phases. In the first phase, the behaviors are extracted from the behavior library by checking the user-defined applicable conditions and utility of each behavior. If multiple behaviors are extracted in the first phase, the single behavior is selected to execute in the help of reinforcement learning in the second phase. That is, the behavior with the highest expected reward is selected by comparing Q values of individual behaviors updated through reinforcement learning. L-CAA can monitor the maintainable conditions of the executing behavior and stop immediately the behavior when some of the conditions fail due to dynamic change of the environment. Additionally, L-CAA can suspend and then resume the current behavior whenever it encounters a higher utility behavior. In order to analyze effectiveness of the L-CAA architecture, we implement an L-CAA-enabled agent autonomously playing in an Unreal Tournament game that is a well-known dynamic virtual environment, and then conduct several experiments using it.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.17 no.2
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• pp.59-75
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• 2012

The species composition of plankton is essential to understand the material and energy cycling within marine ecosystem. It also provides the useful information for understanding the properties of marine environments due to its sensitivity to the physicochemical characteristics and variability of water masses. In this study we adopted metagenomics to evaluate eukaryotic plankton species diversity from coastal waters off Busan. Characteristics of water masses at sampling sites is expected to be very complex due to the mixing of various water masses; Nakdong River runoff, Changjiang diluted water (CDW), South Sea coastal water, and Tsushima warm current. 18S rDNA clone libraries were constructed from surface waters at the three sites off Busan. Clone libraries revealed 94 unique phylotypes from 370 clones; Dinophyceae(42 phylotypes), Ciliophora(15 phylotypes), Bacillariophyta(7 phylotypes), Chlorophyta(2 phylotypes), Haptophyceae(1 phylotype), Metazoa(Arthropoda( 17 phylotypes), Chaetognatha(1 phylotypes), Cnidaria(2 phylotypes), Chordata(1 phylotype)), Rhizaria (Acantharea(2 phylotypes), Polycystinea(1 phylotype)), Telonemida(1 phylotype), Fungi(2 phylotypes). The difference in species diversity at the closely located three sites off Busan may be attributed to the various physicochemical properties of water masses at these sites by the mixture of water masses of various origins. Metagenomic study of species composition may provide useful information for understanding marine ecosystem of coastal waters with various physicochemical properties in the near feature.

• Informatization Policy
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• v.29 no.2
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• pp.106-126
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• 2022

The digital divide issue is re-emerging in step with the rapid progress of digital transformation. Recently, the discussion of the digital divide is expanding to the point that the difference in digital access and use competency deepens economic and social inequality and discrimination. Notably, the phenomenon of the exclusion and alienation of the elderly from society is a serious matter to be addressed. Accordingly, this research was conducted to provide practical help in minimizing the digital divide through its understanding among the elderly. To this end, both the accomplished capital accumulated and experienced in the course of life and their attitudes toward technology in relation to digital competence capital by the elderly were examined in three dimensions. This analysis was conducted using the results of the '2020 The Report on the Digital Divide'. The target group of the analysis comprised 653 seniors aged 65 and above. As a result of the analysis, digital competence capital among the elderly was affected by both various types of accomplished capital such as educational, income, social, and emotional capital and digital device use attitude. Based on this, this study proposed measures to bridge the digital divide among the elderly.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.219-240
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• 2023

Conversational AI which allows users to interact with satisfaction is a long-standing research topic. To develop conversational AI, it is necessary to build training data that reflects real conversations between people, but current Korean datasets are not in question-answer format or use honorifics, making it difficult for users to feel closeness. In this paper, we propose a conversation dataset (KOMUChat) consisting of 30,767 question-answer sentence pairs collected from online communities. The question-answer pairs were collected from post titles and first comments of love and relationship counsel boards used by men and women. In addition, we removed abuse records through automatic and manual cleansing to build high quality dataset. To verify the validity of KOMUChat, we compared and analyzed the result of generative language model learning KOMUChat and benchmark dataset. The results showed that our dataset outperformed the benchmark dataset in terms of answer appropriateness, user satisfaction, and fulfillment of conversational AI goals. The dataset is the largest open-source single turn text data presented so far and it has the significance of building a more friendly Korean dataset by reflecting the text styles of the online community.

• Science of Emotion and Sensibility
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• v.21 no.2
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• pp.15-28
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• 2018

The purpose of this study was to conduct eye-tracking experiments to target large spaces and to analyze the characteristics of pupil gaze by gender. By analyzing the change of pupil size in the eye-tracking experiment, we suggest a template for objective and scientific analyses of gender observation data. Additionally, based on the difference between gender and time to pupil size change, we noted the characteristic of time that gather the visual perception data information and showed that females attend to interesting elements of visual information one to two seconds slower than males. In the initial "$1sec{\rightarrow}2sec$", the pupil size has been increased in leap condition of male and in fixed condition of female. In addition, if condition limits to fixed observation to view the change rates on gender then the pupil size of female was larger than male before 9 seconds, while male's pupil size was larger after 9 seconds. This indicates that females obtain visual information through a relatively larger pupil size during the first 1-8 seconds after stimulus presentation, while males acquire it between 10-15 seconds after input. However, based on the result that the pupil size of female was larger than male on the change of observation time, the pupil size movement on female was energized to watch more interest element after a certain period of time.

• Journal of the Korean Society for information Management
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• v.28 no.3
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• pp.335-353
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• 2011

This study examines how and which direction respondents who participated in 5-point Likert scale surveys change their initial responses when they are given an identical second survey after certain treatments. The research employs three identical questionnaires (first, second and third surveys) to analyze survey results based on group differences, kinds of treatment, survey purposes, and response change direction and the degree. This paper concludes that, first, it is significant that specialist groups do not change their initial responses compared to a general librarian group. Second, there are no differences by survey purpose; however, participants tend to change their initial responses by others' opinions rather than by previous use experiences. Third, participants who initially answered positively tend not to change their responses, and most participants who answered negatively change their initial responses in a positive direction. Fourth, when there are changes, participants change their initial responses by less than two points, and most of them change by one point. Finally, the hypothesis that middle responses change most and that participants who respond at both ends do not change their opinion was rejected by the finding that participants who answered on the negative end tend to change their initial responses in a positive direction.

• Journal of Digital Convergence
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• v.19 no.8
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• pp.33-42
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• 2021

As smartphone-based tourism platforms have become active, policy establishment and service enhancement using review data are being made in various fields. In the case of the preceding studies using tourism review data, most of the studies centered on domestic tourists were conducted, and in the case of foreign tourist studies, studies were conducted only on data collected in some languages and text mining techniques. In this study, 3,515 review data written by foreigners were collected by designating the "Daegu attractions" keyword through the online review site. And LDA-based topic modeling was performed to derive tourism topics. The spatial approach through global and local spatial autocorrelation analysis for each topic can be said to be different from previous studies. As a result of the analysis, it was confirmed that there is a global spatial autocorrelation, and that tourist destinations mainly visited by foreigners are concentrated locally. In addition, hot spots have been drawn around Jung-gu in most of the topics. Based on the analysis results, it is expected to be used as a basic research for spatial analysis based on local government foreign tourism policy establishment and topic modeling. And The limitations of this study were also presented.

• Horticultural Science & Technology
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• v.28 no.6
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• pp.1025-1038
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• 2010

Carrot ($Daucus$ $carota$ L. var. $sativa$) is one of the most widely used crops in the world. Moreover it is an important crop because of its high content of ${\beta}$-carotene, well-known as the precursor of vitamin A carotenoid. However, seed-hair which is generated in epidermal cell of seeds inhibits absorption and germination. For that reason, carrot seeds are commercialized after mechanical hair removal process. To overcome such cumbersome weaknesses, new breeding program for developing hairless-seed carrot cultivar has been needed. Therefore, in this study, cDNA libraries from seeds of short-hair seed phenotype CT-ATR615 OP 666-13line and hairy seed CT-ATR615 OP-CK1-9 line were constructed and expression patterns related to generation of seed-hair were analyzed by comparison of EST sequences. Differential EST sequence results between two lines were classified into FunCat functional categories based on the results of BlastX search. Higher expression quantities belonging to metabolic category were shown on short-hair seed line than hairy-seed one. Differential expression quantities between those two lines in the protein folding and stabilization, subcellular localization categories were supposed to contribute variously on the generation of seed-hair. We confirmed 50 and 59 SSR sites, and 2 SNP sites by analyzing EST sequences in two lines; thereafter, we designed SNP and SSR primer sets from these EST sequence information as a molecular marker. These markers are thought to be used in research of molecular markers for classification of carrot family and related to various traits, as well as seed-hair characteristic.