• Korean Circulation Journal
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• v.52 no.9
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• pp.680-696
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• 2022

Background and Objectives: Circular RNAs were known to play vital role in myocardial ischemia reperfusion injury (MIRI), while the role of CircZNF609 in MIRI remains unclear. This study was aimed to investigate the function of CircZNF609 in MIRI. Methods: Hypoxia/reoxygenation (H/R) model was established to mimic MIRI in vitro. Quantitative polymerase chain reaction was performed to evaluate gene transcripts. Cellular localization of CircZNF609 and miR-214-3p were visualized by fluorescence in situ hybridization. Cell proliferation was determined by CCK-8. TUNEL assay and flow cytometry were applied to detect apoptosis. Lactate dehydrogenase was determined by commercial kit. ROS was detected by DCFH-DA probe. Direct interaction of indicated molecules was determined by RIP and dual luciferase assays. Western blot was used to quantify protein levels. In vivo model was established to further test the function of CircZNF609 in MIRI. Results: CircZNF609 was upregulated in H/R model. Inhibition of CircZNF609 alleviated H/R induced apoptosis, ROS generation, restored cell proliferation in cardiomyocytes and human umbilical vein endothelial cells. Mechanically, CircZNF609 directly sponged miR-214-3p to release PTGS2 expression. Functional rescue experiments showed that miR-214-3p/PTGS2 axis was involved in the function of circZNG609 in H/R model. Furthermore, data in mouse model revealed that knockdown of CircZNF609 significantly reduced the area of myocardial infarction and decreased myocardial cell apoptosis. Conclusions: CircZNF609 aggravated the progression of MIRI via targeting miR-214-3p/PTGS2 axis, which suggested CircZNF609 might act as a vital modulator in MIRI.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.119-142
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• 2015

With the explosive growth in the volume of information, Internet users are experiencing considerable difficulties in obtaining necessary information online. Against this backdrop, ever-greater importance is being placed on a recommender system that provides information catered to user preferences and tastes in an attempt to address issues associated with information overload. To this end, a number of techniques have been proposed, including content-based filtering (CBF), demographic filtering (DF) and collaborative filtering (CF). Among them, CBF and DF require external information and thus cannot be applied to a variety of domains. CF, on the other hand, is widely used since it is relatively free from the domain constraint. The CF technique is broadly classified into memory-based CF, model-based CF and hybrid CF. Model-based CF addresses the drawbacks of CF by considering the Bayesian model, clustering model or dependency network model. This filtering technique not only improves the sparsity and scalability issues but also boosts predictive performance. However, it involves expensive model-building and results in a tradeoff between performance and scalability. Such tradeoff is attributed to reduced coverage, which is a type of sparsity issues. In addition, expensive model-building may lead to performance instability since changes in the domain environment cannot be immediately incorporated into the model due to high costs involved. Cumulative changes in the domain environment that have failed to be reflected eventually undermine system performance. This study incorporates the Markov model of transition probabilities and the concept of fuzzy clustering with CBCF to propose predictive clustering-based CF (PCCF) that solves the issues of reduced coverage and of unstable performance. The method improves performance instability by tracking the changes in user preferences and bridging the gap between the static model and dynamic users. Furthermore, the issue of reduced coverage also improves by expanding the coverage based on transition probabilities and clustering probabilities. The proposed method consists of four processes. First, user preferences are normalized in preference clustering. Second, changes in user preferences are detected from review score entries during preference transition detection. Third, user propensities are normalized using patterns of changes (propensities) in user preferences in propensity clustering. Lastly, the preference prediction model is developed to predict user preferences for items during preference prediction. The proposed method has been validated by testing the robustness of performance instability and scalability-performance tradeoff. The initial test compared and analyzed the performance of individual recommender systems each enabled by IBCF, CBCF, ICFEC and PCCF under an environment where data sparsity had been minimized. The following test adjusted the optimal number of clusters in CBCF, ICFEC and PCCF for a comparative analysis of subsequent changes in the system performance. The test results revealed that the suggested method produced insignificant improvement in performance in comparison with the existing techniques. In addition, it failed to achieve significant improvement in the standard deviation that indicates the degree of data fluctuation. Notwithstanding, it resulted in marked improvement over the existing techniques in terms of range that indicates the level of performance fluctuation. The level of performance fluctuation before and after the model generation improved by 51.31% in the initial test. Then in the following test, there has been 36.05% improvement in the level of performance fluctuation driven by the changes in the number of clusters. This signifies that the proposed method, despite the slight performance improvement, clearly offers better performance stability compared to the existing techniques. Further research on this study will be directed toward enhancing the recommendation performance that failed to demonstrate significant improvement over the existing techniques. The future research will consider the introduction of a high-dimensional parameter-free clustering algorithm or deep learning-based model in order to improve performance in recommendations.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.1-23
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• 2018

From the 21st century, various high-quality services have come up with the growth of the internet or 'Information and Communication Technologies'. Especially, the scale of E-commerce industry in which Amazon and E-bay are standing out is exploding in a large way. As E-commerce grows, Customers could get what they want to buy easily while comparing various products because more products have been registered at online shopping malls. However, a problem has arisen with the growth of E-commerce. As too many products have been registered, it has become difficult for customers to search what they really need in the flood of products. When customers search for desired products with a generalized keyword, too many products have come out as a result. On the contrary, few products have been searched if customers type in details of products because concrete product-attributes have been registered rarely. In this situation, recognizing texts in images automatically with a machine can be a solution. Because bulk of product details are written in catalogs as image format, most of product information are not searched with text inputs in the current text-based searching system. It means if information in images can be converted to text format, customers can search products with product-details, which make them shop more conveniently. There are various existing OCR(Optical Character Recognition) programs which can recognize texts in images. But existing OCR programs are hard to be applied to catalog because they have problems in recognizing texts in certain circumstances, like texts are not big enough or fonts are not consistent. Therefore, this research suggests the way to recognize keywords in catalog with the Deep Learning algorithm which is state of the art in image-recognition area from 2010s. Single Shot Multibox Detector(SSD), which is a credited model for object-detection performance, can be used with structures re-designed to take into account the difference of text from object. But there is an issue that SSD model needs a lot of labeled-train data to be trained, because of the characteristic of deep learning algorithms, that it should be trained by supervised-learning. To collect data, we can try labelling location and classification information to texts in catalog manually. But if data are collected manually, many problems would come up. Some keywords would be missed because human can make mistakes while labelling train data. And it becomes too time-consuming to collect train data considering the scale of data needed or costly if a lot of workers are hired to shorten the time. Furthermore, if some specific keywords are needed to be trained, searching images that have the words would be difficult, as well. To solve the data issue, this research developed a program which create train data automatically. This program can make images which have various keywords and pictures like catalog and save location-information of keywords at the same time. With this program, not only data can be collected efficiently, but also the performance of SSD model becomes better. The SSD model recorded 81.99% of recognition rate with 20,000 data created by the program. Moreover, this research had an efficiency test of SSD model according to data differences to analyze what feature of data exert influence upon the performance of recognizing texts in images. As a result, it is figured out that the number of labeled keywords, the addition of overlapped keyword label, the existence of keywords that is not labeled, the spaces among keywords and the differences of background images are related to the performance of SSD model. This test can lead performance improvement of SSD model or other text-recognizing machine based on deep learning algorithm with high-quality data. SSD model which is re-designed to recognize texts in images and the program developed for creating train data are expected to contribute to improvement of searching system in E-commerce. Suppliers can put less time to register keywords for products and customers can search products with product-details which is written on the catalog.

• The Korean Journal of Rehabilitation Nursing
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• v.4 no.1
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• pp.46-57
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• 2001

This study was done to investigate of instrumental activities of daily living(IADL) and quality of life and their relationships between the elderly. Data were collected from 150 elderly home residents. The data were collected from December 1st to December 20th, 2000. Structured questionnaires developed by Lawton & Brody and by Ro were adopted to measure IADL and Quality of life. Data were analyzed for percentage, means, t-test, ANOVA and Parson correlation coefficients using the SPSS program. The results were as follows: 1. The average score of the level of IADL was $20.68{\pm}2.98$ ($M{\pm}SD$) with a range of 7-26. 2. The average score of the level of Quality of life was 2. $96{\pm}0.25$ ($M{\pm}SD$). In the average score of each lower area, highest score was 3.22 for neighbor relationship and family relationship and then 3.00 for self-esteem, 2.95 for economic status, 2.86 for emotional status, and 2.85, lowest score, for physical condition and function. 3. Comparing IADL and Quality of life with general characteristics, IADL showed that there were significant difference in age(t=2.927, p=0.036) and separated children contact frequency(t=2.482, p=0.046), while Quality of life showed that there were significant difference in spouse existence(t=2.334, p=0.021), religion(t=4.089, p=0.008), family style(t=3.285, p=0.040), children number living together(t=5.332, p=0.006), communication with separated children frequency(t=4.129, p=0.003), and separated children contact frequency(t=3.908, p=0.005). 4. There was also significant positive correlation between IADL and Quality of life. The above results show that neighbor relationship and family relationship which have greatly an influence on IADL and Quality of life are very important. The elderly should be helped to satisfy their basic desire and show their potential living together with the younger generation interdependently without being isolated from family and society. Therefore, the nursing strategy that enhance IADL and Quality of life are needed and the nursing strategy that can improve IADL and Quality of life of Elderly Home Residents should be developed.

• Korean Journal of Construction Engineering and Management
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• v.17 no.5
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• pp.78-88
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• 2016

Recently BIM technology has been expanded for using in construction project. However its spread has been delayed than the initial expectations, due to the high-cost of BIM infrastructure development, the lack of regulations, the lack of process and so forth. In design phase, especially, collaboration based on BIM system has being a key factor for successful next generation building project. Through the analysis of current research trend about IT technologies, virtualization and BIM service, data exchange such as drawing, 3D model, object data, properties using cloud computing and virtual server system is defined as a most successful solution. In various industrial fields, cloud computing technology is utilized as a promising solution which can reduce time and cost of hardware infrastructure. Among the cloud computing technology, VDI is receiving a great deal of attention from it market as an essential part cloud computing. VDI enables to host multiple individual virtual machines by using hypervisor. It has an advantage to easy main device management. Therefore, this study implements a step-by-step user's DaaS by analyzing the desktop resource data of the workers from Pre-design phase to Schematic design, Design develop and Construction design phase. It also develops BIM environment based on test of BIM modeler and designers in architectural design firm. The goal of the study is to enable the cloud computing BIM server. It provides cost saving, high-performance quality of working environment and cooperation's convenience and high security when doing BIM work in small and medium sized architectural design firm.

• Journal of Plant Biotechnology
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• v.37 no.3
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• pp.305-312
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• 2010

During a last decade, the introduced traits in commercialized GM crops have been diversified from a simple trait such as herbicide resistance gene or insectresistance gene which are related to the crop production into more complicated traits such as modification of fatty acid or essential amino acid composition, modified coloring pattern of flower. In addition, it was investigated that several other GM crops bearing more refined traits expected to lead next generation are also awaiting for risk assessment (RA) or under field test for the preparation of RA in the near future. These GM crops include abiotic stress resistance including drought or cold, increased biomass, production of bioethanol or diesel, production of pharmaceuticals or functional materials for industrial. In particular, in 2008 and 2009, it was reported that the highest number of GM crops for molecular farming are under developed in laboratory or green house level in all the world. Likewise, in Korea, 171 events from 49 plant species are under developed to introduce several important traits. At present, about 10 events are under field test to select elite lines for RA application. For the first time, herbicide resistance turfgrass developed by Korean research team has been submitted for RA and currently under requested for additional data. Moreover, GM rice resistant to leaf roll (folder) disease is expected as a next event to be submitted for RA application.

• Journal of the Korean Society of School Health
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• v.15 no.2
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• pp.205-218
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• 2002

Objectives : Because elementary school children are sensitive and prevalent to dental caries, oral health care program for the elementary school children (ESOHCP) should be met the first priority for the national oral health care program. This study was performed to proposed the guidelines for executing the efficient ESOHCP through the evaluation of present oral health care and education status based on the attitudes and opinions of health teachers. Methods : Subjects were 181 health teachers those are a part of the total 273 elementary school health teachers in Busan. From April to June 2001, questionnaire survey on the teacher's attitude and opinion, present status of oral health care and education in their own school was done. Data was analyzed by $\chi^2$-test, t-test, ANOVA using SAS (ver 6.21) program. Results : Mean age of the teachers was 40 years (24~58 years) and mean scale of the subject school was 32 classes (5~58 classes). Above 90% of them agreed with the necessity and importance of ESOHCP, but actual level of concerning was lower. They gained the informations about oral health mainly from media (33%), PC net (26%), academic society (25%), and more used internet (p=0.012) in younger generation. Though most of them (96%) had a specified school dentist, only 58% had the experience of periodic oral health examinations in their own school. The major experienced ESOHCP was fluoride brushing and contest to choose the best healthy teeth. Oral health education given by the teachers was not professional but their own. About half (42%) of the teachers had never taken education during last one year. Major education materials were VTR tape (79%), teeth model (64%), CD (55%), booklet (50%), etc., and the teachers' preference was also VTR tape (43%) and CD (41%). When they need education materials, they frequently request to dentist's association (36%), academic society (35%), but rarely to dental clinics or dentists (6%). They prefer that two times (46%) of annual oral health education, with the contents of regular brushing (53%), but lower regular visit to clinics (13%). The interest to oral health care (p=0.016) increased with teacher's age. And, they agreed regular students education in case of higher interest(p=0.044). Intention about join in the model school program was decreased with scale of school (p=0.002). Conclusions : This result showed that the present status of ESOHCP is still insufficient. It considered that the health teachers' interest and role is most important for the maintenance and success of ESOHCP. The professional and efficient education program would be focused on the health teachers to induce drive on ESOHCP.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.11 no.5
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• pp.79-91
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• 2008

Research was initiated to investigate germination characteristics of creeping bentgrass (CB, Agrostis palustris Huds.). Seven varieties of CB were evaluated with different experiments. An alternative environment condition requiring for a CB germination test by International Seed Testing Association (ISTA) was applied in the Experiment I, consisting of 8-hr light at $25^{\circ}C$ and 16-hr dark at $15^{\circ}C$(ISTA conditions). Experiment II was conducted under a room temperature condition of 5 to $25^{\circ}C$(natural conditions). In each experiment, data such as seed germinating vigor, early germination characteristics, germination speed and germination peak time were measured. Significant differences were observed in seed germinating vigor, early germination characteristics, germination speed and germination peak time. Seed germinating vigor was variable with different environments and varieties. It was 61.50 to 98.25% under ISTA conditions and 55.00 to 98.50% under natural conditions. There were considerable variations in early germination characteristics among CB varieties according to different conditions. Early germination characteristics indicated that all varieties were 1 to 4 days faster in germination under ISTA conditions, when compared with natural conditions. The germination speed, measured as days to seed germination of 70% and 90%, was much faster with Penn A-1, Penn A-4 and Penncross under ISTA conditions. But it was even faster with L-93 and Penncross when grown under natural conditions. Differences were also observed in germination peak time with varieties and growing conditions. It was 0.57 to 2.86 days under ISTA conditions and 0.74 to 1.74 days under natural conditions. Regardless of the environment conditions, the shortest variety was L-93 and the longest one T-1. Considering germinating vigor, early germination characteristics, germination speed and germination peak time, Penn A-1, Penn A-4 and Penncross were regarded as excellent varieties under ISTA conditions in terms of early establishment characteristics, while L-93, Penn A-1 and Penncross under natural conditions. These results suggest that an intensive germination test be needed prior to planting, for the early germinating vigor, germination speed and germination peak time. Also, a proper variety selection and comprehensive site analysis for the growing environmental conditions should be done before golf course construction.

• Korean Journal of Animal Reproduction
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• v.27 no.4
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• pp.325-331
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• 2003

This study was performed to test the cellulose digestibility using the transgenic pigs harboring cellulose degradation gene D (CelD). After delivered offsprings between normal pig and transgenic swine, DNA was isolated from piglets tail for PCR analysis. In first generation, five out of 65 piglets showed CelD positive. Unfortunately, four CelD-positive pigs were died during growing, but one survived pig was used as a transgenic founder to produce F$_1$ descendents. Among 3 F$_1$ transgenic pigs produced, one died and the remaining two pigs were used to test the fiber digest efficiency. An assorted feed was composite of 5％ fiber with other ingredients. The feed of 3 kg per day was provided to the pigs including transgenic founders and littermate controls. The manure quantity was measured daily for a month, and all manures were dried for three days to analysis nitrogen, phosphate and fiber concentrations. The fiber digestion efficiencies of the transgenic F$_1$ pigs showed approximately 10％ higher than those of control pigs. Fiber digestion was not greatly improved in transgenic pigs as it had been expected approximately 30％. Nitrogen concentration of transgenic pig's manure was slowly decreased compare to the control pigs. Because there were only two transgenic pigs tested, a large number of transgenic pigs may be necessary to obtain more reliable data. Breeding of animals to obtain sufficient transgenic pigs subjected for a further study is on progress. Taken together, this study demonstrated successful production of transgenic pigs with increase of cellulose digestibility in the porcine feed.

• YAKHAK HOEJI
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• v.52 no.2
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• pp.137-146
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• 2008

Even though driving under the influence of drug (DUID) is a worldwide problem, we, Korea has no regulation system yet except for alcohol, and there are little cases reported related to DUID. In order to investigate the type of abused drugs for drivers in Korea, we tried to analyze controlled and non-controlled drugs in alcohol-positive blood samples. 275 whole bloods, which were positive for alcohol on the roadside test, were collected from the police for two months ($Nov.{\sim}Dec.$ 2006). The analytical strategy was constituted of three steps: First, alcohol in blood samples were confirmed and quantified by gas chromatography. Second, controlled drugs were screened by $Evidence_{investigator}\;^{TM}$ (Randox, U.K.) as preliminary test. It was based on immunoassay by biochip array analyzer. Nine groups of drug abuse were screened: amphetamines, methamphetamines, cannabis, cocaine, opiates, barbiturates, methadone, benzodiazepines I (oxazepam) & II (lorazepam). Finally, confirmation of these drugs was performed by GC-MS. Blood samples were extracted by solid-phase extraction by $RapidTrace^{TM}$ (Zymark, U.S.A.). After trimethylsilyl (TMS) derivatization, eluates were analyzed to GC-MS. Total 49 drugs were investigated in this study including controlled drugs, antidepressants, 1st generation antihistamines, dextromethorphan, nalbuphine, ketamine, etc. For rapid detection, we developed the automated identification system. It was made up a new software, "DrugMan", modified Chemstation data analysis menu and newly developed macro modules. A series of peak selection, identification and reporting of the results were performed automatically by this system. Concentrations of alcohol in 275 blood samples were ranged from 0.011 to 0.249% (average, 0.119%). Among 149 blood samples, just six samples (4.0%) were showed positive results to the immunoassay: one methamphetamine and five benzodiazepines group I. By GC-MS confirmation, only benzodiazepines were detected and methamphetamine was not detected from immunoassay positive blood sample. Besides these drugs, 5 chlorpheniramines, dextromethorphan, diazepam, doxylamine, ibuprofen, lidocaine and topiramate were also detected in whole bloods by GC-MS. Conclusively, the frequency of drug abuse for Korean drivers was relatively low. There was none case which illegal drug was detected. However these results were limited to alcohol positive blood samples, so it is necessary to analyze more samples including alcohol negative blood.