• Korean Journal of Environmental Agriculture
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• v.41 no.2
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• pp.115-124
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• 2022

BACKGROUND: Methane is a major greenhouse gas attributed to global warming partly contributed by agricultural activities from ruminant fermentation and rice paddy fields. Methanotrophs are microorganisms that utilize methane. Their unique metabolic lifestyle is enabled by enzymes known as methane monooxygenases (MMOs) catalyzing the oxidation of methane to methanol. Rice absorbs, transports, and releases methane directly from soil water to its stems and the micropores and stomata of the plant epidermis. Methylobacterium species associated with rice are dependent on their host for metabolic substrates including methane. METHODS AND RESULTS: Methylobacterium spp. isolated from rice were evaluated for methane oxidation activities and screened for the presence of sMMO mmoC genes. Qualitatively, the soluble methane monooxygenase (sMMO) activities of the selected strains of Methylobacterium spp. were confirmed by the naphthalene oxidation assay. Quantitatively, the sMMO activity ranged from 41.3 to 159.4 nmol min^-1 mg of protein^-1. PCR-based amplification and sequencing confirmed the presence and identity of 314 bp size fragment of the mmoC gene showing over 97% similarity to the CBMB27 mmoC gene indicating that Methylobacterium strains belong to a similar group. CONCLUSION(S): Selected Methylobacterium spp. contained the sMMO mmoC gene and possessed methane oxidation activity. As the putative methane oxidizing strains were isolated from rice and have PGP properties, they could be used to simultaneously reduce paddy field methane emission and promote rice growth.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.869-876
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• 2021

In the field of music, various AI composition methods using machine learning have recently been attempted. However, most of this research has been centered on Western music, and little research has been done on Korean traditional music. Therefore, in this paper, we will create a data set of Korean traditional music, create a melody using three algorithms based on the data set, and compare the results. Three models were selected based on the similarity between language and music, LSTM, Music Transformer and Self Attention. Using each of the three models, a melody generator was modeled and trained to generate melodies. As a result of user evaluation, the Self Attention method showed higher preference than the other methods. Data set is very important in AI composition. For this, a Korean traditional music data set was created, and AI composition was attempted with various algorithms, and this is expected to be helpful in future research on AI composition for Korean traditional music.

• ETRI Journal
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• v.44 no.4
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• pp.573-587
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• 2022

The agricultural sector is completely different from other sectors since it completely relies on various natural and climatic factors. Climate changes have many effects, including lack of annual rainfall and pests, heat waves, changes in sea level, and global ozone/atmospheric CO₂ fluctuation, on land and agriculture in similar ways. Climate change also affects the environment. Based on these factors, farmers chose their crops to increase productivity in their fields. Many existing agricultural ontologies are either domain-specific or have been created with minimal vocabulary and no proper evaluation framework has been implemented. A new agricultural ontology focused on subdomains is designed to assist farmers using Jaccard relative extractor (JRE) and Naïve Bayes algorithm. The JRE is used to find the similarity between two sentences and words in the agricultural documents and the relationship between two terms is identified via the Naïve Bayes algorithm. In the proposed method, the preprocessing of data is carried out through natural language processing techniques and the tags whose dimensions are reduced are subjected to rule-based formal concept analysis and mapping. The subdomain ontologies of weather, pest, and soil are built separately, and the overall agricultural ontology are built around them. The gold standard for the lexical layer is used to evaluate the proposed technique, and its performance is analyzed by comparing it with different state-of-the-art systems. Precision, recall, F-measure, Matthews correlation coefficient, receiver operating characteristic curve area, and precision-recall curve area are the performance metrics used to analyze the performance. The proposed methodology gives a precision score of 94.40% when compared with the decision tree(83.94%) and K-nearest neighbor algorithm(86.89%) for agricultural ontology construction.

• Journal of the Korean GEO-environmental Society
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• v.24 no.5
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• pp.13-20
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• 2023

The Gangneung region has an environment suitable for the formation of organic soil, and there is an alluvial layer in which sedimentary sand layers are distributed on the upper and lower parts of the organic soil. In order to evaluate the seismic safety of the railway roadbed passing through the Gangneung area, a railway roadbed and ground model considering the similarity ratio was fabricated, a shaking table test was conducted, and the seismic stability was evaluated by comparing the effective stress analysis results. The applied seismic waves were artificial seismic waves, Gyeongju seismic waves, Borah seismic waves, Nahanni seismic waves, and Tabas seismic waves. It became. Due to the ground reinforcement effect by jet grouting applied to the lower ground of the new roadbed, the displacement of the new roadbed was found to be reduced from a minimum of 33.7% to a maximum of 56.7% compared to the existing roadbed. The shaking table test results were verified by effective stress analysis using the Finn model of the Flac program, and showed a similar trend to the shaking table test values.

• ALGAE
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• v.38 no.2
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• pp.93-110
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• 2023

Progress in phylogenomic analysis has led to a considerable re-evaluation of former cyanobacterial system, with many new taxa being established at different nomenclatural levels. The family Geminocystaceae is among cyanobacterial taxa recently described on the basis of polyphasic approach. Within this family, there are six genera: Geminocystis, Cyanobacterium, Geminobacterium, Annamia, Picocyanobacterium, and Microcrocis. The genus Geminocystis previously encompassed two species: G. herdmanii and G. papuanica. Herein, a new species G. urbisnovae was proposed under the provision of the International Code of Nomenclature for algae, fungi, and plants (ICN). Polyphasic analysis was performed for five strains from the CALU culture collection (St. Petersburg State University, Russian Federation), and they were assigned to the genus Geminocystis in accordance with high 16S rRNA gene similarity to existing species, as well as because of proximity to these species on the phylogenetic trees reconstructed with RaxML and Bayes methods. Plausibility of their assignment to a separate species of the genus Geminocystis was substantiated with smaller cell size; stenohaline freshwater ecotype; capability to complementary chromatic adaptation of second type (CA2); distinct 16S rRNA gene clustering; sequences and folding of D1-D1' and B box domains of the 16S-23S internal transcribed spacer region. The second objective pursued by this communication was to provide a survey of the family Geminocystaceae. The overall assessment was that, despite attention of many researchers, this cyanobacterial family has been understudied and, especially in the case of the crucially important genus Cyanobacterium, taxonomically problematic.

• Journal of Practical Engineering Education
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• v.14 no.3
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• pp.565-572
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• 2022

Card sorting is a useful data collection method for understanding users' perceptions of relationships between items. In general, card sorting is an intuitive and cost-effective technique that is very useful for user research and evaluation. In this study, the core competencies of each field were used as competency cards used in the next stage of card sorting for course development, and the clustering results were derived by applying the K-means algorithm to cluster the results. As a result of card sorting, competency clustering for core competencies for each occupation in each field was verified based on Participant-Centric Analysis (PCA). For the number of core competency cards for each occupation, the number of participants who agreed appropriately for clustering and the degree of card similarity were derived compared to the number of sorting participants.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.163-177
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• 2024

The fingerprint image quality relies on the clearness of separated ridges by valleys and the uniformity of the separation. The condition of skin still dominate the overall quality of the fingerprint. However, the identification performance of such system is very sensitive to the quality of the captured fingerprint image. Fingerprint image quality analysis and enhancement are useful in improving the performance of fingerprint identification systems. A fuzzy technique is introduced in this paper for both fingerprint image quality analysis and enhancement. First, the quality analysis is performed by extracting four features from a fingerprint image which are the local clarity score (LCS), global clarity score (GCS), ridge_valley thickness ratio (RVTR), and the Global Contrast Factor (GCF). A fuzzy logic technique that uses Mamdani fuzzy rule model is designed. The fuzzy inference system is able to analyse and determinate the fingerprint image type (oily, dry or neutral) based on the extracted feature values and the fuzzy inference rules. The percentages of the test fuzzy inference system for each type is as follow: For dry fingerprint the percentage is 81.33, for oily the percentage is 54.75, and for neutral the percentage is 68.48. Secondly, a fuzzy morphology is applied to enhance the dry and oily fingerprint images. The fuzzy morphology method improves the quality of a fingerprint image, thus improving the performance of the fingerprint identification system significantly. All experimental work which was done for both quality analysis and image enhancement was done using the DB_ITS_2009 database which is a private database collected by the department of electrical engineering, institute of technology Sepuluh Nopember Surabaya, Indonesia. The performance evaluation was done using the Feature Similarity index (FSIM). Where the FSIM is an image quality assessment (IQA) metric, which uses computational models to measure the image quality consistently with subjective evaluations. The new proposed system outperformed the classical system by 900% for the dry fingerprint images and 14% for the oily fingerprint images.

• Korean Circulation Journal
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• v.54 no.1
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• pp.30-39
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• 2024

Background and Objectives: Intravascular ultrasound (IVUS) evaluation of coronary artery morphology is based on the lumen and vessel segmentation. This study aimed to develop an automatic segmentation algorithm and validate the performances for measuring quantitative IVUS parameters. Methods: A total of 1,063 patients were randomly assigned, with a ratio of 4:1 to the training and test sets. The independent data set of 111 IVUS pullbacks was obtained to assess the vessel-level performance. The lumen and external elastic membrane (EEM) boundaries were labeled manually in every IVUS frame with a 0.2-mm interval. The Efficient-UNet was utilized for the automatic segmentation of IVUS images. Results: At the frame-level, Efficient-UNet showed a high dice similarity coefficient (DSC, 0.93±0.05) and Jaccard index (JI, 0.87±0.08) for lumen segmentation, and demonstrated a high DSC (0.97±0.03) and JI (0.94±0.04) for EEM segmentation. At the vessel-level, there were close correlations between model-derived vs. experts-measured IVUS parameters; minimal lumen image area (r=0.92), EEM area (r=0.88), lumen volume (r=0.99) and plaque volume (r=0.95). The agreement between model-derived vs. expert-measured minimal lumen area was similarly excellent compared to the experts' agreement. The model-based lumen and EEM segmentation for a 20-mm lesion segment required 13.2 seconds, whereas manual segmentation with a 0.2-mm interval by an expert took 187.5 minutes on average. Conclusions: The deep learning models can accurately and quickly delineate vascular geometry. The artificial intelligence-based methodology may support clinicians' decision-making by real-time application in the catheterization laboratory.

• Journal of the Korea Society of Computer and Information
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• v.29 no.9
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• pp.39-48
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• 2024

In this study, we propose a method to augment the provided reasoning paths to improve the answer performance and explanatory power of KGQA. In the proposed method, we utilize LLMs and GNNs to retrieve reasoning paths related to the question from the knowledge graph and evaluate reasoning paths. Then, we retrieve the external information related to the question and then converted into triples to answer the question and explain the reason. Our method evaluates the reasoning path by checking inference results and semantically by itself. In addition, we find related texts to the question based on their similarity and converting them into triples of knowledge graph. We evaluated the performance of the proposed method using the WebQuestion Semantic Parsing dataset, and found that it provides correct answers with higher accuracy and more questions with explanations than the reasoning paths by the previous research.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.34 no.1
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• pp.83-96
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• 2016

Through the research and analysis on the vegetation environment, flora of habitats through documentary and field studies over 14 habitats of Euryale ferox Salisbury within Jeollabukdo, with the objective of acquiring the basic data for forming an environment based on plantation of reservoirs that are composed with Euryale ferox, the following results were obtained. 1. The entire flora of the 14 habitats appeared to be 79 families, 211 genus, 298 species, two subspecies, 30 varieties and six forma, thus, a total of 336 taxa was confirmed. Among these, emergent water plants appeared to compose 17 taxa, floating-leaved plants to compose seven taxa including Euryale ferox floating plants to compose five taxa and submerged water plants to compose two taxa. As a result of analyzing the similarity only over the water plants. The lowest similarity rate appeared between Gamdong Reservoir and Aedang Reservoir, as the similarity rate between the two regions appeared to be 0% as a result of the analysis. Floating-leaved plants, lotuses and caltrops, appeared to be equally inhabiting in Hanseongji at Jeongeup and Seoknam Reservoir at Gochang, which showed the highest similarity rate, in addition to Euryale ferox. 2. When examining the appearance frequency of aquatic plants per growth type, Actinostemma lobatum and Phragmites communis, in addition to Euryale ferox each appeared 11 times, showing a high frequency of 78.6% and Trapa japonica, which is a floating-leaved water plant, appeared ten times(71.4%) and Zizania latifolia appeared eight times(57.1%). In addition, the appearance rate appeared to be high in the order of Persicaria thunbergii, Leersia sayanuka, Ceratophyllum demersum, Echinochloa crusgalli var. oryzicola, Scirpus maritimus, and Nelumbo nucifera. 3. The rare plants discovered in the Euryale ferox habitats pursuant to the IUCN evaluation standards was confirmed to be composed of five taxa, with three taxa including the least concerned species(LC), Melothria japonica at Yanggok Reservoir, Hydrocharis dubia at Myeongdeokji and Ottelia alismoides at Daewi Reservoir, in addition to vulnerable species(VU), Utricularia vulgaris at Sangpyeong Reservoir, along with Euryale ferox. 4. Most of the group or community types of the natural habitats of Euryale ferox appeared to be the Euryale ferix community' and the Daewi Reservoir of Gunsan was defined as caltrop + Euryale ferox + Nymphoides indica community. The green coverage ratio of Euryale ferox per natural habitats showed a considerably huge deviation from 0.03 to 36.50 and as the average green coverage ratio was appropriated as 9.8, it can be considered that maintaining the green coverage ratio of Euryale ferox in a 10% level would be advisable when forming a reservoir with Euryale ferox as the key composition species. 5. The vegetation community nearby the natural habitats of Euryale ferox per research subject area appeared to be composed of three Leersia japonica communities, two communities each for Zizania latifolia community and Trapa japonica community and one community each for Nelumbo nucifera community, Nymphoides peltata + Typha orientalis community, Trapa japonica + Nelumbo nucifera community, Hydrocharis dubia community, Leersia japnica + Paspalum distichum var. indutum community and Euryale ferox + Trapa japonica community, showing a slight difference depending on the location conditions of each reservoir. Thus, this result may be suggested as a guideline to apply when allocating the vegetation ratio and the types of floating-leaved plants upon planting plants in reservoirs with Euryale ferox as the main companion species.