• Journal of Plant Biotechnology
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• v.43 no.1
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• pp.91-98
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• 2016

The growth area of living modified (LM) cotton has steadily increased every year, since its first commercialization in 1996. Development of environmental risk assessment tools and techniques for LM cotton is required for ecosystem safety. We therefore developed multiplex PCR assays for simultaneous detection of two (MON15985, MON531) and four (GHB614, LLCOTTON25, MON88913 and MON1445) LM cotton events approved in Korea, with event specific primer pairs. The PCR reactions were optimized by using event specific primers of six LM cottons at various concentrations. The reactions allows amplification of estimated amplicons of MON15985 (214 bp), MON531 (270 bp), GHB614 (119 bp), LLCOTTON25 (164 bp), MON88913 (276 bp), and MON1445 (389 bp) from multiplex PCR reactions. The multiplex PCR assay developed allowed that two annealing steps (15 cycles at $55^{\circ}C$ and 25 cycles at $60^{\circ}C$) were performed for amplification of distinguished two LM cottons, and only one annealing step (50 cycles at $60^{\circ}C$) was necessary for tetraplex PCR. Primer extension step of all PCR reactions was skipped for time-effective amplification. Our methods suggest that two multiplex PCR assays can be cost-effective and a rapid diagnostic tool for environmental LMO monitoring of six LM cottons.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.213-225
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• 2010

Data mining has empowered the managers who are charge of the tasks in their company to present personalized and differentiated marketing programs to their customers with the rapid growth of information technology. Most studies on customer' response have focused on predicting whether they would respond or not for their marketing promotion as marketing managers have been eager to identify who would respond to their marketing promotion. So many studies utilizing data mining have tried to resolve the binary decision problems such as bankruptcy prediction, network intrusion detection, and fraud detection in credit card usages. The prediction of customer's response has been studied with similar methods mentioned above because the prediction of customer's response is a kind of dichotomous decision problem. In addition, a number of competitive data mining techniques such as neural networks, SVM(support vector machine), decision trees, logit, and genetic algorithms have been applied to the prediction of customer's response for marketing promotion. The marketing managers also have tried to classify their customers with quantitative measures such as recency, frequency, and monetary acquired from their transaction database. The measures mean that their customers came to purchase in recent or old days, how frequent in a period, and how much they spent once. Using segmented customers we proposed an approach that could enable to differentiate customers in the same rating among the segmented customers. Our approach employed support vector regression to forecast the purchase amount of customers for each customer rating. Our study used the sample that included 41,924 customers extracted from DMEF04 Data Set, who purchased at least once in the last two years. We classified customers from first rating to fifth rating based on the purchase amount after giving a marketing promotion. Here, we divided customers into first rating who has a large amount of purchase and fifth rating who are non-respondents for the promotion. Our proposed model forecasted the purchase amount of the customers in the same rating and the marketing managers could make a differentiated and personalized marketing program for each customer even though they were belong to the same rating. In addition, we proposed more efficient learning method by separating the learning samples. We employed two learning methods to compare the performance of proposed learning method with general learning method for SVRs. LMW (Learning Method using Whole data for purchasing customers) is a general learning method for forecasting the purchase amount of customers. And we proposed a method, LMS (Learning Method using Separated data for classification purchasing customers), that makes four different SVR models for each class of customers. To evaluate the performance of models, we calculated MAE (Mean Absolute Error) and MAPE (Mean Absolute Percent Error) for each model to predict the purchase amount of customers. In LMW, the overall performance was 0.670 MAPE and the best performance showed 0.327 MAPE. Generally, the performances of the proposed LMS model were analyzed as more superior compared to the performance of the LMW model. In LMS, we found that the best performance was 0.275 MAPE. The performance of LMS was higher than LMW in each class of customers. After comparing the performance of our proposed method LMS to LMW, our proposed model had more significant performance for forecasting the purchase amount of customers in each class. In addition, our approach will be useful for marketing managers when they need to customers for their promotion. Even if customers were belonging to same class, marketing managers could offer customers a differentiated and personalized marketing promotion.

• The Korean Journal of Nuclear Medicine
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• v.36 no.6
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• pp.344-356
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• 2002

Purpose: RBC blood pool SPECT has been used to diagnose focal liver lesion such as hemangioma owing to its high specificity. However, low spatial resolution is a major limitation of this modality. Recently, ordered subset expectation maximization (OSEM) has been introduced to obtain tomographic images for clinical application. We compared this new modified iterative reconstruction method, OSEM with conventional filtered back projection (FBP) in imaging of liver hemangioma. Materials and Methods: Sixty four projection data were acquired using dual head gamma camera in 28 lesions of 24 patients with cavernous hemangioma of liver and these raw data were transferred to LINUX based personal computer. After the replacement of header file as interfile, OSEM was performed under various conditions of subsets (1,2,4,8,16, and 32) and iteration numbers (1,2,4,8, and 16) to obtain the best setting for liver imaging. The best condition for imaging in our investigation was considered to be 4 iterations and 16 subsets. After then, all the images were processed by both FBP and OSEM. Three experts reviewed these images without any information. Results: According to blind review of 28 lesions, OSEM images revealed at least same or better image quality than those of FBP in nearly all cases. Although there showed no significant difference in detection of large lesions more than 3 cm, 5 lesions with 1.5 to 3 cm in diameter were detected by OSEM only. However, both techniques failed to depict 4 cases of small lesions less than 1.5 cm. Conclusion: OSEM revealed better contrast and define in depiction of liver hemangioma as well as higher sensitivity in detection of small lesions. Furthermore this reconstruction method dose not require high performance computer system or long reconstruction time, therefore OSEM is supposed to be good method that can be applied to RBC blood pool SPECT for the diagnosis of liver hemangioma.

• Korean Journal of Environment and Ecology
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• v.36 no.6
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• pp.592-602
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• 2022

This study aimed to check habitat distribution and analyze influencing factors by analyzing the mating calls of Auritibicen intermedius inhabiting limited locations in South Korea by applying bioacoustic detection techniques. The study sites were 20 protection areas nationwide. The mating call analysis period was 4 years from 2017 to 2021, excluding 2020. The bioacoustic recording system installed at each study site collected recordings of mating calls every day for 1 minute per hour. Climate data received from the Meteorological Agency, such as temperature, humidity, rainfall, cloudiness, and sunshine, were analyzed. The results of this study identified A. intermedius habitat only in four national parks in the highlands of Gangwon Province (Mt. Seorak, Mt. Odae, Mt. Chiak, and Mt. Taebak) out of 20 study sites. During the four years of study, the mating call period of A. intermedius was between August 5 and September 28, and the duration of the mating call was 31 to 52 days. The temperature analysis during the appearance period of A. intermedius showed that A. intermedius mainly produced mating calls at temperatures between 13.1℃ and 35.3℃, and the average temperature during the circadian cycle of mating calls (09:00 to 16:00) was 24.4 to 24.9℃. The analysis of the circadian cycle of mating calls at four study sites where A. intermedius appeared in 2019 showed that A. intermedius produced mating calls from 06:00 to 16:00 and that they peaked around 11:00 to 12:00. During the appearance period of A. intermedius, four species appeared in common: Hyalessa maculaticollis, Meimuna opalifera, Graptopsaltria nigrofuscata, and Suisha coreana. A logistic regression analysis confirmed that sunlight was the environmental factor affecting the mating call of A. intermedius. Regarding interspecific influence, it was confirmed that A. intermedius exchanged interspecific influence with 4 other common species (H. maculaticollis, M. opalifera, G. nigrofuscata, and S. coreana). The above results confirmed that A. intermedius habitats were limited in the highlands of Gangwon Province highlands in Korea and produced mating calls at a lower temperature compared to other species. These results can be used as basic data for future research on A. intermedius in Korea.

• Journal of Korea Water Resources Association
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• v.56 no.8
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• pp.497-508
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• 2023

Agricultural reservoirs are crucial structures for water resources monitoring especially in Korea where the resources are seasonally unevenly distributed. Optical and Synthetic Aperture Radar (SAR) satellites, being utilized as tools for monitoring the reservoirs, have unique limitations in that optical sensors are sensitive to weather conditions and SAR sensors are sensitive to noises and multiple scattering over dense vegetations. In this study, we tried to improve water body detection accuracy through optical-SAR data fusion, and quantitatively analyze the complementary effects. We first detected water bodies at Edong, Cheontae reservoir using the Compact Advanced Satellite 500(CAS500), Kompsat-3/3A, and Sentinel-2 derived Normalized Difference Water Index (NDWI), and SAR backscattering coefficient from Sentinel-1 by K-means clustering technique. After that, the improvements in accuracies were analyzed by applying K-means clustering to the 2-D grid space consists of NDWI and SAR. Kompsat-3/3A was found to have the best accuracy (0.98 at both reservoirs), followed by Sentinel-2(0.83 at Edong, 0.97 at Cheontae), Sentinel-1(both 0.93), and CAS500(0.69, 0.78). By applying K-means clustering to the 2-D space at Cheontae reservoir, accuracy of CAS500 was improved around 22%(resulting accuracy: 0.95) with improve in precision (85%) and degradation in recall (14%). Precision of Kompsat-3A (Sentinel-2) was improved 3%(5%), and recall was degraded 4%(7%). More precise water resources monitoring is expected to be possible with developments of high-resolution SAR satellites including CAS500-5, developments of image fusion and water body detection techniques.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.949-965
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• 2023

In this study, we propose a method to monitor the surface area of agricultural reservoirs in South Korea using Sentinel-1 synthetic aperture radar images and the deep learning model, Swin Transformer. Utilizing the Google Earth Engine platform, datasets from 2017 to 2021 were constructed for seven agricultural reservoirs, categorized into 700 K-ton, 900 K-ton, and 1.5 M-ton capacities. For four of the reservoirs, a total of 1,283 images were used for model training through shuffling and 5-fold cross-validation techniques. Upon evaluation, the Swin Transformer Large model, configured with a window size of 12, demonstrated superior semantic segmentation performance, showing an average accuracy of 99.54% and a mean intersection over union (mIoU) of 95.15% for all folds. When the best-performing model was applied to the datasets of the remaining three reservoirsfor validation, it achieved an accuracy of over 99% and mIoU of over 94% for all reservoirs. These results indicate that the Swin Transformer model can effectively monitor the surface area of agricultural reservoirs in South Korea.

• Tuberculosis and Respiratory Diseases
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• v.47 no.3
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• pp.321-330
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• 1999

Background : Early diagnosis and proper antibiotic treatment are very important in the management of ventilator-associated pneumonia (VAP) because of its high mortality. Bronchoscopy with a protected specimen brush (PSB) has been considered the standard method to isolate the causative organisms of VAP. However, this method burdens consumer economically to purchase a PSB. Another useful method for the diagnosis of VAP is quantitative cultures of aspirated specimens through bronchoscopic bronchoalveolar lavage (BAL), for which the infusion of more than 120 m1 of saline has been recommended for adequate sampling of a pulmonary segment. However, occasionally it leads to deterioration of the patient's condition. We studied the diagnostic efficacy of minibronchoalveolar lavage (miniBAL), which retrieves only 25 ml of BAL fluid, in the isolation of causative organisms of VAP. Methods: We included 38 consecutive patients (41 cases) suspected of having VAP on the basis of clinical evidence, who had received antibiotics before the bronchoscopy. The two diagnostic techniques of PSB and miniBAL, which were performed one after another at the same pulmonary segment, 'were compared prospectively. The cut-off values for quantitative cultures to define causative bacteria of VAP were more than $10^3$ colony-forming units (cfu)/ml for PSB and more than $10^4$ cfu/ml for BAL. Results: The amount of instilled normal saline required to retrieve 25 ml of BAL fluid was $93{\pm}32 ml$ (mean${\pm}$SD). The detection rate of causative agents was 46.3% (19/41) with PSB and 43.9% (18/41) with miniBAL. The concordance rate of PSB and miniBAL in the bacterial culture was 85.4% (35/41). Although arterial blood oxygen saturation dropped significantly (p<0.05) during ($92{\pm}10%$) and 10 min after ($95{\pm}3%$) miniBAL compared with the baseline ($97{\pm}3%$), all except 3 cases were within normal ranges. The significantly elevated heart rate during ($l25{\pm}24$/min, p<0.05) miniBAL compared with the baseline ($1l1{\pm}22$/min) recovered again in 10 min after ($111{\pm}26$/min) miniBAL. Transient hypotension was developed during the procedure in two cases. The procedure was stopped in one case due to atrial flutter. Conclusion: MiniBAL is a safe and effective technique to detect the causative organisms of VAP.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1031-1031
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• 2001

The mammary gland is made up of remarkably sensitive tissue, which has the capability of producing a large volume of secretion, milk, under normal or healthy conditions. When bacteria enter the gland and establish an infection (mastitis), inflammation is initiated accompanied by an influx of white cells from the blood stream, by altered secretory function, and changes in the volume and composition of secretion. Cell numbers in milk are closely associated with inflammation and udder health. These somatic cell counts (SCC) are accepted as the international standard measurement of milk quality in dairy and for mastitis diagnosis. NIR Spectra of unhomogenized composite milk samples from 14 cows (healthy and mastitic), 7days after parturition and during the next 30 days of lactation were measured. Different multivariate analysis techniques were used to diagnose the disease at very early stage and determine how the spectral properties of milk vary with its composition and animal health. PLS model for prediction of somatic cell count (SCC) based on NIR milk spectra was made. The best accuracy of determination for the 1100-2500nm range was found using smoothed absorbance data and 10 PLS factors. The standard error of prediction for independent validation set of samples was 0.382, correlation coefficient 0.854 and the variation coefficient 7.63%. It has been found that SCC determination by NIR milk spectra was indirect and based on the related changes in milk composition. From the spectral changes, we learned that when mastitis occurred, the most significant factors that simultaneously influenced milk spectra were alteration of milk proteins and changes in ionic concentration of milk. It was consistent with the results we obtained further when applied 2DCOS. Two-dimensional correlation analysis of NIR milk spectra was done to assess the changes in milk composition, which occur when somatic cell count (SCC) levels vary. The synchronous correlation map revealed that when SCC increases, protein levels increase while water and lactose levels decrease. Results from the analysis of the asynchronous plot indicated that changes in water and fat absorptions occur before other milk components. In addition, the technique was used to assess the changes in milk during a period when SCC levels do not vary appreciably. Results indicated that milk components are in equilibrium and no appreciable change in a given component was seen with respect to another. This was found in both healthy and mastitic animals. However, milk components were found to vary with SCC content regardless of the range considered. This important finding demonstrates that 2-D correlation analysis may be used to track even subtle changes in milk composition in individual cows. To find out the right threshold for SCC when used for mastitis diagnosis at cow level, classification of milk samples was performed using soft independent modeling of class analogy (SIMCA) and different spectral data pretreatment. Two levels of SCC - 200 000 cells/$m\ell$ and 300 000 cells/$m\ell$, respectively, were set up and compared as thresholds to discriminate between healthy and mastitic cows. The best detection accuracy was found with 200 000 cells/$m\ell$ as threshold for mastitis and smoothed absorbance data: - 98% of the milk samples in the calibration set and 87% of the samples in the independent test set were correctly classified. When the spectral information was studied it was found that the successful mastitis diagnosis was based on reviling the spectral changes related to the corresponding changes in milk composition. NIRS combined with different ways of spectral data ruining can provide faster and nondestructive alternative to current methods for mastitis diagnosis and a new inside into disease understanding at molecular level.

• Journal of Sericultural and Entomological Science
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• v.16 no.1
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• pp.85-92
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• 1974

Many of studies on the transovarial transmission of occult virus and their activation due to various stresses such as cold or heat treatment, chemical feeding, and nutritional deficiency, etc., in the silkworm, Bombyx mori L. have been made, but any attempts have been not made to control virus diseases by detection of the occult virus-carried moths in the production of silkworm egg of hybrids, because of difficulty to detect occult virus in any stage. Therefore, it may be worth while to disclose whether a sublethal infection of the moths from which active virus are detectable, has the same level of induction rate as that of occult virus activation, thus to apply its results for the reduction of the occurence of virus diseases in silkworm rearing. For these purposes, the following experiment was conducted as one of preliminary steps. In this study, investigations on the generation-to-generation transmission of occult virus and a sublethal infection, and the role of chromosomal gene of the host, Jam 103 and Jam 104 in the Previous generation, and Jam 103 x Jam 103 and Jam 104 f Jam 104 in the next generation were made for the induction of virus diseases due to the transmitted virus. The frequency of cytoplasmic polyhedrosis due to the induction in the F$_1$ generation was markedly higher in the cross-batches, male$\times$female and male$\times$female in which inoculated individuals were used as fem ale parents than in the cross-batches, male$\times$female and male$\times$female in which virus has been not inoculated or inoculated only to male in the previous generation. The tendency of increasing rate was observed in any treatments; such as the inoculations of cytoplasmic polyhedrosis virus (10$\^$5/, 10$\^$6/ 10$\^$7, and 10$\^$8//ml ill different concentration of inocula) , cold-treatment (5$^{\circ}C$, 12hrs or 24hrs), and formalin-feeding treatment (2％ or 3％). The shape of polyhedra (tetragonal in outline) examined in the F, larvae was identified as that of the inoculated polyhedra with partial application of immunofluorescent techniques. These results suggests that the cytoplasmic polyhedrosis virus in B. meri L. are transmitted to the next generation through the egg, apparently in the occult state. And the experimental results of various cross-batches revealed the egg cytoplasm plays an important part i the transmission of the occult virus of the cytoplasmic polyhedrosis virus,

• Analytical Science and Technology
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• v.23 no.1
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• pp.1-14
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• 2010

It is of importance that all countries in worldwide, including EU and China, have adopted the Restrictions on the use of certain Hazardous Substances (RoHS) for all electronics. IEC62321 document, which was published by the International Electronics Committee (IEC) can have conflicts with the standards in the market. On the contrary Publicly Accessible Specification (PAS) for sampling published by IEC TC111 can be adopted for complementary application. In this work, we tried to find a route to disassemble and disjoint cellular phone sample, based on PAS and compare the screening methods available in the market. For this work, the cellular phone produced in 2001, before the regulation was born, was chosen for better detection. Although X-ray Fluorescence (XRF) showed excellent performance for screening, fast and easy handling, it can give information on the surface, not the bulk, and have some limitations due to significant matrix interference and lack of variety of standards for quantification. It means that screening with XRF sometimes requires supplementary tool. There are several techniques available in the market of analytical instruments. Laser ablation (LA) ICP-MS, energy dispersive (ED) XRF and scanning electron microscope (SEM)-energy dispersive X-ray (EDX) were demonstrated for screening a cellular phone. For quantitative determination, graphite furnace atomic absorption spectrometry (GF-AAS) was employed. Experimental results for Pb in a battery showed large difference in analytical results in between XRF and GF-AAS, i.e., 0.92% and 5.67%, respectively. In addition, the standard deviation of XRF was extremely large in the range of 23-168%, compared with that in the range of 1.9-92.3% for LA-ICP-MS. In conclusion, GF-AAS was required for quantitative analysis although EDX was used for screening. In this work, it was proved that LA-ICP-MS can be used as a screening method for fast analysis to determine hazardous elements in electrical products.