• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.561-570
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• 2010

The purpose of this study is to develop an Android smartphone app providing analysis capabilities of remote sensing images, by using mobile browsing open sources of gvSIG, open source remote sensing software of OTB and open source DBMS of PostgreSQL. In this app, five kinds of remote sensing algorithms for filtering, segmentation, or classification are implemented, and the processed results are also stored and managed in image database to retrieve. Smartphone users can easily use their functions through graphical user interfaces of app which are internally linked to application server for image analysis processing and external DBMS. As well, a practical tiling method for smartphone environments is implemented to reduce delay time between user's requests and its processing server responses. Till now, most apps for remotely sensed image data sets are mainly concerned to image visualization, distinguished from this approach providing analysis capabilities. As the smartphone apps with remote sensing analysis functions for general users and experts are widely utilizing, remote sensing images are regarded as information resources being capable of producing actual mobile contents, not potential resources. It is expected that this study could trigger off the technological progresses and other unique attempts to develop the variety of smartphone apps for remote sensing images.

• Journal of Ecology and Environment
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• v.47 no.3
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• pp.118-133
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• 2023

Background: Free-living amoebae (FLA) are widely distributed in freshwater, seawater, soil, and extreme environments, and play a critical role as feeders on diverse preys in the ecosystem. Also, some FLA can become opportunistic pathogens in animals including humans. The taxa Amoebozoa and Heterolobosea are important amoeboid groups associated with human pathogens. However, the identification and habitat of amoebae belonging to Amoebozoa and Heterolobosea remain poorly reported in the Republic of Korea. This study highlights the first record for identification and source of four amoebae including putative pathogens in the Republic of Korea. Results: In the present study, four previously reported FLA were isolated from freshwaters in Sangju Gonggeomji Reservoir (strain GO001), one of the largest reservoirs during the Joseon Dynasty period, and along the Nakdong River, the largest river in the Republic of Korea (strains NR5-2, NR12-1, and NR14-1) for the first time. Microscopic observations and 18S rDNA phylogenetic trees revealed the four isolated strains to be Acanthamoeba polyphaga (strains NR5-2 and NR12-1), Tetramitus waccamawensis (strain GO001), and Naegleria australiensis (strain NR14-1). Strains NR5-2 and NR12-1 might be the same species and belonged to the morphological Group 2 and the T4 genotype of Acanthamoeba. Strain GO001 formed a clade with T. waccamawensis in 18S rDNA phylogeny, and showed morphological characteristics similar to previously recorded strains, although the species' flagellate form was not observed. Strain NR14-1 had the typical morphology of Naegleria and formed a strongly supported clade with previously recorded strains of N. australiensis in phylogenetic analysis of 18S rDNA sequences. Conclusions: On the bases of morphological and molecular analyses, four strains of FLA were newly observed and classified in the Republic of Korea. Three strains belonging to the two species (A. polyphaga and N. australiensis) isolated from the Nakdong River have the potential to act as opportunistic pathogens that can cause fatal diseases (i.e. granulomatous amoebic encephalitis, Acanthamoeba Keratitis, and meningoencephalitis) in animals including humans. The Nakdong River in the Republic of Korea may provide a habitat for potentially pathogenic amoebae, but additional research is required to confirm the true pathogenicity of these FLA now known in the Republic of Korea.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.11
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• pp.247-249
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• 2020

In the era of the 4th industrial revolution, the demand for convergence between ICT technologies is increasing in various fields. Accordingly, a new term that combines data, network, and artificial intelligence technology, DNA (Data, Network, AI) is in use. and has recently become a hot topic. DNA has various potential technology to be able to develop intelligent application in the real world. Therefore, this paper introduces the reviewed papers on the service image placement mechanism based on the logical fog network, the mobility support scheme based on machine learning for Industrial wireless sensor network, the prediction of the following BCI performance by means of spectral EEG characteristics, the warning classification method based on artificial neural network using topics of source code and natural language processing model for data visualization interaction with chatbot, related on DNA technology.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.11
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• pp.1649-1657
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• 2006

In order to find an alternative source of inoculum to caecal content for studying the fermentation activity of rabbit hindgut, caecal content and faeces of 25 hybrid Hyla rabbits were used as inocula for an in vitro gas production trial. About 1 g of three substrates (dehydrated alfalfa meal, dehydrated beet pulp, barley) was weighed, in quadruplicate per inoculum, in 120 ml bottles; 75 ml of anaerobic medium and 4 ml of reducing solution were added and bottles were placed at $39^{\circ}C$. Caecal content and faeces were diluted respectively 1:2 (CI) and 1:8 (FI) with anaerobic medium and were introduced in the respective bottles (10 ml). Gas production was recorded 20 times at 2-24 h intervals throughout fermentation (96 h). The fermentation characteristics (i.e. degraded organic matter, OMd; potential gas production, A; fermentation rate, Rmax; time at which it is reached, Tmax; pH, volatile fatty acid, VFA) were studied by inoculum and feedstuffs. The feedstuffs, according to their chemical composition, showed very different fermentation characteristics. In particular, OMd, A and Rmax allowed feedstuff classification as follows: barley>beet pulp>alfalfa. The inocula differ (p<0.05) in Tmax, were higher for CI (15.53 vs. 11.96 h) and in VFA production. In particular, CI produced higher levels of acetate (38.9 vs. 33.4 mM/g OM incubated, p<0.01) and isobutyrate (0.72 vs. 0.42, p<0.01) but less propionate (7.1 vs. 10.3, p<0.01) and butyrate (11.3 vs. 14.0, p<0.01). However, the trend of gas production, similar for the inocula according to the fermented substrate, and the good regression equation to estimate some caecal fermentation parameters from faeces suggest that, after standardisation, the faeces could be used as an alternative inoculum for gas tests in rabbit.

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.3
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• pp.1-15
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• 1999

This study was carried out to find out the way to build a comprehensive wetland ecosystem database using the technique of remote sensing and geographic information system. A Landsat TM image taken in May 17, 1997 was used for the primary source for the image analysis. Field surveys were conducted March to September of 1998 to help image analysis and examine the results. An actual wetland vegetation map was created based on the field survey. A Landsat TM image was analyzed by unsupervised and supervised classification methods and finally categorized into such 5 classes as Phragmites australis community, mixed community, sand beach, Scirpus trigueter community and non-vegetation intertidal area. Wetland basemap was developed for the overall accuracy assesment in wetland mapping. Vegetation index map of wetland vegetation was developed using NDVI(normalized difference vegetation index). The map of wetland productivity was developed based on the productivity of Phragmites australis and the relationship to the proximity of adjacent water bodies. The map of potential vegetation succession map was also developed based on the experience and knowledge of the field biologists. Considering these results, it is possible to use the remote sensing and GIS techniques for producing wetland ecosystem database. This study indicated that these techniques are very effective for the development of the national wetland inventory in Korea.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.652-656
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• 2006

Bibliographic information retrieval systems require bibliographic data such as authors, organizations, source of publication to be uniquely identified using keys. In particular, when authors are represented simply as their names, users bear the burden of manually discriminating different users of the same name. Previous approaches to resolving the problem of same-name authors rely on bibliographic data such as co-author information, titles of articles, etc. However, these methods cannot handle the case of single author articles, or the case when articles do not have common terms in their titles. To complement the previous methods, this study introduces a classification-based approach using similarity between full-text of articles. Experiments using recent domestic proceedings showed that the proposed method has the potential to supplement the previous meta-data based approaches.

• Korean Journal of Environment and Ecology
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• v.33 no.1
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• pp.116-123
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• 2019

This study focused on defining concepts such as biology push (biology-based biomimicry) and technology pull (technology problem-based biomimicry) in the multidisciplinary field of ecological imitation and analyzing the status of related research and technology at the domestic and international levels. From an ecological point of view, biomimicry is defined as ecological mimicry in which ideas obtained through classification and investigation of principles of biology and ecology are applied to the concepts of engineering and technology. We also defined the biology push as the ecological imitation based on biological characteristics starting from an ecological viewpoint and technology pull as the ecological imitation based on technical problems starting from technical needs. Although biomimicry studies often focus on the technology development by finding stable and eco-friendly source materials from biological and ecological characteristics, we wanted to emphasize the unlimited potential of research of biomimicry that can begin with an idea based on biological and ecological characteristics. This study presents the need to develop the research and technology further based on the biological and ecological viewpoints that can contribute to future sustainable development.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.1
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• pp.50-61
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• 2010

This study was carried out to find out the way to build a comprehensive wetland ecosystem database using the technique of remote sensing and Geographic Information System. A Landsat TM image (taken in Oct. 30, 2002), Kompsat-2 images (Jan. 17, 2008 & Nov. 20, 2008), LiDAR(Mar. 1, 2009) were used for the primary source for the image analysis. Field surveys were conducted March to August of 2009 to help image analysis and examine the results. An actual wetland vegetation map was created based on the field survey. Satellite images were analyzed by unsupervised and supervised classification methods and finally categorized into such classes as Phragmites australis community, mixed community, sand beach, Scirpus planiculmis community and non-vegetation intertidal area. The map of wetland productivity was developed based on the productivity of Phragmites australis and the relationship to the proximity of adjacent water bodies. The developed 3 dimensional wetland map showed such several potential applications as flood inundation, birds flyway viewsheds and benthos distribution. Considering these results, we concluded that it is possible to use the remote sensing and GIS techniques for producing wetland ecosystem spatial database and these techniques are very effective for the development of the national wetland inventory in Korea.

• Journal of The Korean Association For Science Education
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• v.44 no.3
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• pp.231-248
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• 2024

This study developed a chatbot for first-year high school students, employing open-source software and the Korean Sentence-BERT model for AI-powered document classification. The chatbot utilizes the Sentence-BERT model to find the six most similar Q&A pairs to a student's query and presents them in a carousel format. The initial dataset, built from online resources, was refined and expanded based on student feedback and usability throughout over the operational period. By the end of the 2023 academic year, the chatbot integrated a total of 30,819 datasets and recorded 3,457 student interactions. Analysis revealed students' inclination to use the chatbot when prompted by teachers during classes and primarily during self-study sessions after school, with an average of 2.1 to 2.2 inquiries per session, mostly via mobile phones. Text mining identified student input terms encompassing not only science-related queries but also aspects of school life such as assessment scope. Topic modeling using BERTopic, based on Sentence-BERT, categorized 88% of student questions into 35 topics, shedding light on common student interests. A year-end survey confirmed the efficacy of the carousel format and the chatbot's role in addressing curiosities beyond integrated science learning objectives. This study underscores the importance of developing chatbots tailored for student use in public education and highlights their educational potential through long-term usage analysis.