• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1353-1369
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• 2023

In the event of a disaster accident at sea, the scale of damage will vary due to weather effects such as wind, currents, and tidal waves, and it is obligatory to minimize the scale of damage by establishing appropriate control plans through quick on-site identification. In particular, it is difficult to identify pollutants that exist in a thin film at sea surface due to their relatively low viscosity and surface tension among pollutants discharged into the sea. Therefore, this study aims to develop an algorithm to detect suspended pollutants on the sea surface in RGB images using imaging equipment that can be easily used in the field, and to evaluate the performance of the algorithm using input data obtained from actual waters. The developed algorithm uses image enhancement techniques to improve the contrast between the intensity values of pollutants and general sea surfaces, and through histogram analysis, the background threshold is found,suspended solids other than pollutants are removed, and finally pollutants are classified. In this study, a real sea test using substitute materials was performed to evaluate the performance of the developed algorithm, and most of the suspended marine pollutants were detected, but the false detection area occurred in places with strong waves. However, the detection results are about three times better than the detection method using a single threshold in the existing algorithm. Through the results of this R&D, it is expected to be useful for on-site control response activities by detecting suspended marine pollutants that were difficult to identify with the naked eye at existing sites.

• Journal of the Korean Society of Radiology
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• v.85 no.1
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• pp.138-146
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• 2024

Purpose To evaluate whether the image quality of chest radiographs obtained using a camera-type portable X-ray device is appropriate for clinical practice by comparing them with traditional mobile digital X-ray devices. Materials and Methods Eighty-six patients who visited our emergency department and underwent endotracheal intubation, central venous catheterization, or nasogastric tube insertion were included in the study. Two radiologists scored images captured with traditional mobile devices before insertion and those captured with camera-type devices after insertion. Identification of the inserted instruments was evaluated on a 5-point scale, and the overall image quality was evaluated on a total of 20 points scale. Results The identification score of the instruments was 4.67 ± 0.71. The overall image quality score was 19.70 ± 0.72 and 15.02 ± 3.31 (p < 0.001) for the mobile and camera-type devices, respectively. The scores of the camera-type device were significantly lower than those of the mobile device in terms of the detailed items of respiratory motion artifacts, trachea and bronchus, pulmonary vessels, posterior cardiac blood vessels, thoracic intervertebral disc space, subdiaphragmatic vessels, and diaphragm (p = 0.013 for the item of diaphragm, p < 0.001 for the other detailed items). Conclusion Although caution is required for general diagnostic purposes as image quality degrades, a camera-type device can be used to evaluate the inserted instruments in chest radiographs.

• Journal of Dairy Science and Biotechnology
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• v.32 no.1
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• pp.17-29
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• 2014

GRAS probiotics can be used to modulate intestinal microbiota and to alleviate various gastrointestinal disorders. In several recent studies, researchers have explored the potential expansion and usability of probiotics to reduce the risk factors associated with diseases, including obesity, hypercholesterolemia, arterial hypertension, hyperhomocysteinemia, and oxidative stress. In this review, our aim was to clarify the mechanism underlying interactions between hosts (animal or human) and probiotics and the beneficial effects of probiotics on human health.

• The Transactions of the Korea Information Processing Society
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• v.4 no.12
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• pp.3159-3174
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• 1997

This paper reports a research to develop a methodology and a tool for understanding of very large and complex real-time software. The methodology and the tool mostly developed by the author are called the Architecture-based Real-time Software Understanding (ARSU) and the Software Re/reverse-engineering Environment (SRE) respectively. Due to size and complexity, it is commonly very hard to understand the software during reengineering process. However the research facilitates scalable re/reverse-engineering of such real-time software based on the architecture of the software in three-dimensional perspectives: structural, functional, and behavioral views. Firstly, the structural view reveals the overall architecture, specification (outline), and the algorithm (detail) views of the software, based on hierarchically organized parent-chi1d relationship. The basic building block of the architecture is a software Unit (SWU), generated by user-defined criteria. The architecture facilitates navigation of the software in top-down or bottom-up way. It captures the specification and algorithm views at different levels of abstraction. It also shows the functional and the behavioral information at these levels. Secondly, the functional view includes graphs of data/control flow, input/output, definition/use, variable/reference, etc. Each feature of the view contains different kind of functionality of the software. Thirdly, the behavioral view includes state diagrams, interleaved event lists, etc. This view shows the dynamic properties or the software at runtime. Beside these views, there are a number of other documents: capabilities, interfaces, comments, code, etc. One of the most powerful characteristics of this approach is the capability of abstracting and exploding these dimensional information in the architecture through navigation. These capabilities establish the foundation for scalable and modular understanding of the software. This approach allows engineers to extract reusable components from the software during reengineering process.

• Journal of Plant Biotechnology
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• v.40 no.4
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• pp.210-216
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• 2013

Efficient regeneration methods and transformation system are a priority for successful application of genetic engineering to vegetative propagated plants such as grape (Vitis labrusca L.). This research is to establish shoot regeneration system from plant explants for 'Campbell Early', 'Tamnara', 'Heukgoosul', 'Heukbosek' using two types of plant growth regulators supplemented to medium. The highest adventitious shoot regeneration rate of 5% was achieved on a medium containing of Murashige and Skoog (MS) inorganic salts and Linsmaier and Skoog (LS) vitamins, 2 mg/L of TDZ and 0.1 mg/L of IBA. Leaf tissue of 'Campbell Early', was co-cultivated with Agrobacterium strains, LBA4404 containing the vector pBI121 carrying with CaMV 35S promoter, gus gene as reporter gene and resistance to kanamycin as selective agent, the other Agrobacterium strains, GV3101 containing the vector pB7 WG2D carrying with mPAP1-D gene. mPAP1-D is a regulatory genes of the anthocyanin biosynthetic pathway. 'Campbell Early' harboring mPAP1-D gene was readily able to be selected by red color due to anthocyanin accumulation in the transformed shoot. These results might be helpful for further studies to enhance the transformation efficiency in grape.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.1-17
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• 2015

In this paper, we report what we have observed with regards to a prediction model for the military based on enlisted men's internal(cumulative records) and external data(SNS data). This work is significant in the military's efforts to supervise them. In spite of their effort, many commanders have failed to prevent accidents by their subordinates. One of the important duties of officers' work is to take care of their subordinates in prevention unexpected accidents. However, it is hard to prevent accidents so we must attempt to determine a proper method. Our motivation for presenting this paper is to mate it possible to predict accidents using enlisted men's internal and external data. The biggest issue facing the military is the occurrence of accidents by enlisted men related to maladjustment and the relaxation of military discipline. The core method of preventing accidents by soldiers is to identify problems and manage them quickly. Commanders predict accidents by interviewing their soldiers and observing their surroundings. It requires considerable time and effort and results in a significant difference depending on the capabilities of the commanders. In this paper, we seek to predict accidents with objective data which can easily be obtained. Recently, records of enlisted men as well as SNS communication between commanders and soldiers, make it possible to predict and prevent accidents. This paper concerns the application of data mining to identify their interests, predict accidents and make use of internal and external data (SNS). We propose both a topic analysis and decision tree method. The study is conducted in two steps. First, topic analysis is conducted through the SNS of enlisted men. Second, the decision tree method is used to analyze the internal data with the results of the first analysis. The dependent variable for these analysis is the presence of any accidents. In order to analyze their SNS, we require tools such as text mining and topic analysis. We used SAS Enterprise Miner 12.1, which provides a text miner module. Our approach for finding their interests is composed of three main phases; collecting, topic analysis, and converting topic analysis results into points for using independent variables. In the first phase, we collect enlisted men's SNS data by commender's ID. After gathering unstructured SNS data, the topic analysis phase extracts issues from them. For simplicity, 5 topics(vacation, friends, stress, training, and sports) are extracted from 20,000 articles. In the third phase, using these 5 topics, we quantify them as personal points. After quantifying their topic, we include these results in independent variables which are composed of 15 internal data sets. Then, we make two decision trees. The first tree is composed of their internal data only. The second tree is composed of their external data(SNS) as well as their internal data. After that, we compare the results of misclassification from SAS E-miner. The first model's misclassification is 12.1%. On the other hand, second model's misclassification is 7.8%. This method predicts accidents with an accuracy of approximately 92%. The gap of the two models is 4.3%. Finally, we test if the difference between them is meaningful or not, using the McNemar test. The result of test is considered relevant.(p-value : 0.0003) This study has two limitations. First, the results of the experiments cannot be generalized, mainly because the experiment is limited to a small number of enlisted men's data. Additionally, various independent variables used in the decision tree model are used as categorical variables instead of continuous variables. So it suffers a loss of information. In spite of extensive efforts to provide prediction models for the military, commanders' predictions are accurate only when they have sufficient data about their subordinates. Our proposed methodology can provide support to decision-making in the military. This study is expected to contribute to the prevention of accidents in the military based on scientific analysis of enlisted men and proper management of them.

• Journal of Korean Society of Forest Science
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• v.98 no.4
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• pp.379-391
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• 2009

This study was carried out to classify forest vegetation structure of Mt. Munsu and Mt. Okseok from May to September in 2008 using phytosociological analysis methodology of Z-M school under the purpose of furnishing basic materials for rational and scientific forest management. Total of one hundred five study sites (quadrats) was investigated in the area. Quercus mongolica community group was divided into 5 communities such as Pinus densiflora for. erecta community, Hydrangea serrata for. acuminata community, Salix gracilistyla community, Pinus koraiensis community and Larix kaempferi community. Pinus densiflora for. erecta community was subdivided into Rhododendron micranthum group, Quercus variabilis group and Pinus densiflora for. erecta typical group. Hydrangea serrata for. acuminata community also into Ligularia fischeri group, Deutzia glabrata group (into Juglans mandshurica subgroup, Prunus maackii subgroup and Callicarpa japonica subgroup). Accordingly, the vegetation of the study areas could be described as 1 community group, 5 communities, 5 groups, and 3 subgroups and as 10 units in total. Classified vegetation units were highly correlated with altitude and topography. According the analysis of interspecific association, it was shown as three types which were coincident with differential species and character species on the constancy table.

• Journal of Life Science
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• v.25 no.8
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• pp.903-909
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• 2015

Loop-mediated isothermal amplification (LAMP), a PCR-based diagnostic method, is based on autocycling strand displacement DNA synthesis in the presence of exonuclease-negative Bst DNA polymerase under isothermal conditions. With the help of four specific primers that recognize six different sequences of a target DNA, LAMP has high specificity in pathogenic identification in a short time. Hence, in the present study, LAMP is used as a diagnostic tool in the identification of the most dreadful aquatic pathogenic species, Vibrio alginolyticus, and to develop species-specific LAMP primers and optimization of LAMP reaction conditions such as annealing temperature, elongation time, and other PCR chemical concentrations, including MgSO₄, dNTPs, Betaine, and Bst polymerase. The optimized LAMP primers were also checked for specificity with other Vibrio species, which showed that the designed primers were very specific to V. alginolyticus After the first introduction of a species name like this one, the first part (“Vibrio” in this case) should be abbreviated to only the first letter.only. These are usually the most harmful pathogens of the Vibrio species that appear in shrimp and crabs. The results also revealed that the LAMP assay could be 10-fold more sensitive than conventional PCR in detecting V. alginolyticus. This could be the first report on using a rapid and highly sensitive technique, the LAMP assay, in the effective diagnosis of the pathogenic bacteria V. alginolyticus, which could help in the early detection of diseases, particularly in aquaculture.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.2
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• pp.687-697
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• 2014

This study ranges from planning phase to the detailed design phase of steel box girder bridge and proposes ways to generate semantic information of components through Industry Foundation Classes (IFC), a data model for Building Information Modeling (BIM). The classification of components of steel box girder bridge was performed to define information items required for identifying semantic information based on IFC, and spatial information items based on topology and physical information items based on functions of components were classified to create additional properties that does not support IFC by applying user-defined property set within the IFC framework. Steel box girder bridge information model based on IFC was implemented through BIM software and semantic information input interface, which was developed in this study to examine the effectiveness of the additionally created user-defined property. Furthermore, the quantity take-off of components was performed through information model of steel box girder bridge, and the applicability of the proposed method was tested by comparing the quantity take-off based on design document with the result.

• Spatial Information Research
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• v.18 no.5
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• pp.37-45
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• 2010

AT(Aerial Triangulation) is the essential procedure for creating orthophoto and transforming coordinates on the photographs into the real world coordinates utilizing GCPs (Ground Control Point) which is obtained by field survey and the external orientation factors from GPS/INS as a reference coordinates. In this procedure, all of the GCPs can be collected from field survey using GPS and Total Station, or obtained from digital maps. Collecting GCPs by field survey is accurate than GCPs from digital maps; however, lots of manpower should be put into the collecting procedure, and time and cost as well. On the other hand, in the case of obtaining GCPs from digital maps, it is very difficult to secure the required accuracy because almost things at each stage in the collecting procedure should rely on the subjective judgement of the performer. In this study, the results from three methods have been compared for the accuracy assessment in order to know if the results of each case is within the allowance error: for the perceivable objects such as road boarder, speed bumps, constructions etc., 1) GCPs selection utilizing the unique LiDAR intensity value reflected from such objects, 2) using LiDAR DSM and 3) GCPs from field survey. And also, AT and error analysis have been carried out w ith GCPs obtained by each case.