• Journal of agriculture & life science
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• v.46 no.1
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• pp.9-16
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• 2012

This study was conducted to scientifically analyze on the trends of cultivation area and production, and to detect the suitable site for Morus alba cultivation in forest of Buan-gun for effective cultivation. During last 3 years, the cultivation area of M. alba has steadily been increased, and the mulberry production of Jeollabuk-do has been researched as the greatest in Korea. Especially Buan-gun has the largest cultivation area of M. alba. On the other hand, as the result of detecting the suitable site for M. alba cultivation by factors of altitude, aspect, slope, soil texture, and organism content using GIS, there was the 663 ha suitable site of the total of 16,608 ha. In this area, Byeonsan-myeon, Sangseo-myeon, and Jinseo-myeon were included with the largest area, therefore, it was considered that these were the favorable regions for the expansion of M. alba cultivation area. The result of this study would be expected to be used as the effective information when establishing the expansion plan for M. alba cultivation area focused on the forest of Buan-gun in the future.

• Journal of KIISE:Software and Applications
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• v.36 no.3
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• pp.236-243
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• 2009

With advances in topic detection and tracking(TDT), automatic trend analysis from a collection of time-stamped documents, like patents, news papers, and blog pages, is a challenging research problem. Past research in this area has mainly focused on showing a trend line over time of a given concept by measuring the strength of trend-associated term frequency information. for detection of emerging trends, either a simple criterion such as frequency change was used, or an overall comparison was made against a training data. We note that in order to show most salient trends detected among many possibilities, it is critical to devise a ranking function. To this end, we define four properties(change, persistency, stability and volume) of trend lines drawn from frequency information, to quantify various aspects of trends, and propose a method by which trend lines can be ranked. The properties are examined individually and in combination in a series of experiments for their validity using the ranking algorithm. The results show that a judicious combination of the four properties is a better indicator for salient trends than any single criterion used in the past for ranking or detecting emerging trends.

• Journal of Breast Cancer
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• v.21 no.4
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• pp.363-370
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• 2018

Purpose: Breast cancer is the most commonly occurring cancer among women worldwide, and therefore, improved approaches for its early detection are urgently needed. As microRNAs (miRNAs) are increasingly recognized as critical regulators in tumorigenesis and possess excellent stability in plasma, this study focused on using miRNAs to develop a method for identifying noninvasive biomarkers. Methods: To discover critical candidates, differential expression analysis was performed on tissue-originated miRNA profiles of 409 early breast cancer patients and 87 healthy controls from The Cancer Genome Atlas database. We selected candidates from the differentially expressed miRNAs and then evaluated every possible molecular signature formed by the candidates. The best signature was validated in independent serum samples from 113 early breast cancer patients and 47 healthy controls using reverse transcription quantitative real-time polymerase chain reaction. Results: The miRNA candidates in our method were revealed to be associated with breast cancer according to previous studies and showed potential as useful biomarkers. When validated in independent serum samples, the area under curve of the final miRNA signature (miR-21-3p, miR-21-5p, and miR-99a-5p) was 0.895. Diagnostic sensitivity and specificity were 97.9% and 73.5%, respectively. Conclusion: The present study established a novel and effective method to identify biomarkers for early breast cancer. And the method, is also suitable for other cancer types. Furthermore, a combination of three miRNAs was identified as a prospective biomarker for breast cancer early detection.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.9
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• pp.889-895
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• 2011

In recent days, some techniques to prevent from radar detection have been applied on aircraft system. RWR(Radar Warning Receiver) can be used for estimating the source location of the aircraft which emits radar pulse. Current existing method of localizing radar pulse emission source is using AOA(Angle Of Arrival) and most techniques are focused on finding exact AOA to find exact location. In this case, however, the exact AOA does not always result in finding exact source location while target aircraft is moving fast. In this paper, a localization method using the phase delay of the radar pulse's low frequency applies and so a scanning method for the interest area does in order to estimate exact source location by using phase delay.

• Korean Journal of Remote Sensing
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• v.36 no.2_1
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• pp.179-197
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• 2020

Topographic normalization reduces the terrain effects on reflectance by adjusting the brightness values of the image pixels to be equal if the pixels cover the same land-cover. Topographic effects are induced by the imaging conditions and tend to be large in high mountainousregions. Therefore, image analysis on mountainous terrain such as estimation of wildfire damage assessment requires appropriate topographic normalization techniques to yield accurate image processing results. However, most of the previous studies focused on the evaluation of topographic normalization on satellite images with moderate-low spatial resolution. Thus, the alleviation of topographic effects on multi-temporal high-resolution images was not dealt enough. In this study, the evaluation of terrain normalization was performed for each band to select the optimal technical combinations for rapid and accurate wildfire damage assessment using PlanetScope images. PlanetScope has considerable potential in the disaster management field as it satisfies the rapid image acquisition by providing the 3 m resolution daily image with global coverage. For comparison of topographic normalization techniques, seven widely used methods were employed on both pre-fire and post-fire images. The analysis on bi-temporal images suggests the optimal combination of techniques which can be applied on images with different land-cover composition. Then, the vegetation index was calculated from the images after the topographic normalization with the proposed method. The wildfire damage detection results were obtained by thresholding the index and showed improvementsin detection accuracy for both object-based and pixel-based image analysis. In addition, the burn severity map was constructed to verify the effects oftopographic correction on a continuous distribution of brightness values.

• Journal of Digital Convergence
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• v.10 no.10
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• pp.215-220
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• 2012

This paper proposes a ontology of tree structure approach for adaptive object recognition in a situation-variant environment. In this paper, we introduce a new concept, ontology of tree structure ontology, for context sensitivity, as we found that many developed systems work in a context-invariant environment. Due to the effects of illumination on a supreme obstinate designing context-sensitive recognition system, we have focused on designing such a context-variant system using ontology of tree structure. Ontology can be defined as an explicit specification of conceptualization of a domain typically captured in an abstract model of how people think about things in the domain. People produce ontologies to understand and explain underlying principles and environmental factors. In this research, we have proposed context ontology, context modeling, context adaptation, and context categorization to design ontology of tree structure based on illumination criteria. After selecting the proper light-ontology domain, we benefit from selecting a set of actions that produces better performance on that domain. We have carried out extensive experiments on these concepts in the area of object recognition in a dynamic changing environment, and we have achieved enormous success, which will enable us to proceed on our basic concepts.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.11
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• pp.5551-5556
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• 2012

Cytological examination is widely used as a diagnostic tool because of the ease of collecting cells from the involved area. However, the diagnostic yield of cytological examination is unsatisfactory; the reasons include sampling error, poorly prepared samples, small numbers of malignant cells, and low grades of cellular atypia. In this study, we focused on the high infectivity of adenovirus towards epithelial cells and applied the luciferase-expressing adenoviral vector to a new cancer cell detection tool. In addition, adenoviral infectivity was enhanced by modifying viral fiber proteins. The sensitivity of the diagnostic tool was tested using the NCI-H1299 lung cancer cell line, and validated in body fluid samples from cancer patients with a variety of etiology. Results showed that the adenovirus efficiently transfected NCI-H1299 with high sensitivity. Only 10 cancer cells were sufficient for detection of luciferase signals. In body fluid samples, the adenovirus confirmed the diagnosis for malignant and benign cancer, but not in non-epithelial cell derived samples. This study provides proof-of-concept for a more reliable and sensitive diagnostic tool for epithelium-derived cancer.

• Spatial Information Research
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• v.19 no.5
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• pp.1-11
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• 2011

This study mainly focused on the method of accurately extracting damage information in the im agery change detection process using the constructed high resolution aerial im agery. Bongwha-gun in Gyungsangbuk-do which had been severely damaged from a localized torrential downpour at the end of July, 2008 was selected as study area. This study utilized aerial im agery having photographing scale of 30cm gray image of pre-disaster and 40cm color image of post-disaster. In order to correct errors from the differences of the image resolution of pre-/post-disaster and time series, the prelim inary phase of image processing techniques such as normalizing, contrast enhancement and equalizing were applied to reduce errors. The extent of the damage was calculated using one to one comparison of the intensity of each pixel of pre-/post-disaster im aged. In this step, threshold values which facilitate to extract the extent that damage investigator wants were applied by setting difference values of the intensity of pixel of pre-/post-disaster. The accuracy of optimal image processing and the result of threshold values were verified using the error matrix. The results of the study enabled the early exaction of the extents of the damages using the aerial imagery with identical characteristics. It was also possible to apply to various damage items for imagery change detection in case of utilizing multi-band im agery. Furthermore, more quantitative estimation of the dam ages would be possible with the use of numerous GIS layers such as land cover and cadastral maps.

• The Journal of Engineering Geology
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• v.26 no.2
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• pp.223-233
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• 2016

This study establishes a commercialization strategy for technology that can monitor and detect landslides in real time. An effective commercialization strategy was sought through both qualitative and quantitative analyses. The qualitative analysis considered the business environment in detail, while the quantitative analysis examined technologically strong and weak areas by visualizing the links between IPC (International Patent Classification) code structure and patent applicants. The results from both analyses are considered together, with particular attention paid to the business environment. The resulting integrated analysis comprehensively explores the degree of technological development and the current state of real-time monitoring and detection technology for landslides. The integrated analysis identified complementary assets in the business environment, as there is strong development and many research entities in this area. This suggests positive reinforcement for commercialization with two sub-strategies: (1) exploring demand with complementary assets, and (2) providing technology information for explored demand, which should facilitate successful commercialization. Exploiting this positive reinforcement for technology commercialization could reduce the high uncertainty of the technology and the market, and thus increase the probability of successful commercialization. It is also expected to contribute to long-term success by strengthening collaboration between the supply and demand sides.

• Journal of Environmental Impact Assessment
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• v.32 no.2
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• pp.94-111
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• 2023

In order to establish an effective management strategy for invasive species early detection and regular monitoring are required to assess their introduction or dispersal. Environmental DNA (eDNA) is actively applied to evaluate the fauna including the presence of invasive species as it has high detection sensitivity and can detect multiple species simultaneously. In Korea, the applicability evaluation of metabarcoding is being conducted mainly on fish, and research on other taxa is insufficient. Therefore, this study identified the feasibility of detecting invasive species in Korea using eDNA metabarcoding. In addition, to confirm the possibility of detection by taxa, the detection of target species was evaluated using four universal primers (MiFish, MiMammal, Mibird, Amp16S) designed for fish, mammals, birds, and amphibians. As a result, target species (Trachemys scripta, 3 sites; Cervus nippon, 3 sites; Micropterus salmoides, 7 sites; Rana catesbeiana, 4 sites) were detected in 17 of the total 55 sites. Even in the selection of dense sampling sites within the study area, there was a difference in the detection result by reflecting the ecological characteristics of the target species. A comparison of community structures (species richness, abundance and diversity) based on the presence of invasive species focused on M.salmoides and T.scripta, showed higher diversity at the point where invasive species were detected. Also, 1 to 4 more species were detected and abundance was also up to 1.7 times higher. The results of invasive species detection through metabarcoding and the comparison of community structures indicate that the accumulation of large amounts of monitoring data through eDNA can be efficiently utilized for multidimensional ecosystem evaluation. In addition, it suggested that eDNA can be used as major data for evaluation and prediction, such as tracking biological changes caused by artificial and natural factors and environmental impact assessment.