• Journal of agricultural medicine and community health
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• v.9 no.1
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• pp.83-108
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• 1984

Out of a total of 58 species of helminthic and protozoan parasitic infections in Korea, so far 38 species were reported as intestinal parasites of man. Quite a few species of the intestinal parasitic infections have long been prevalent throughout the country and this has been a significant public health problem. In this paper, current status and transition of the intestinal parasitic infections in the past years were presented. Chronological reviewing of data show background and prospects of change in the prevalence of infections. In the national prevalence survey on parasitic infections conducted once every five years since 1971, stool examinations were done by both cellophane thick smear and brine flotation techniques. Every egg positive case of Ascaris lumbricoides and Clonorchis sinensis was further examined by Stoll's dilution egg counting technique. In 1981, perianal swab using adhesive cellulose tape was added for Enterobius infection. For protozoan cyst examination conducted by province and city in '81, fecal specimens were fixed in SAF solution and examined by the formalin-ether concentration technique. High prevalence of parasitic infection in ana before the 1960s can be easily understood from the data given by the Ministry of Health and Social Affairs in 1967. From a parasite control point of view, the 1960s was the preparatory period particularly for control of soil-transmitted helminthiasis. Several organizations which have contributed to parasite control were founded in this period and the prevention law of parasitic infections was passed in '66. In the '70s, overall prevalence rates of the common intestinal parasitic infections, which were highly prevalent in the past were turned into reduction phase for the first time. The '80s can be said to be an active control period of parasitic infections. Intestinal helminths According to the reports of the national prevalence survey on parasitic infections, the prevalence of helminthic infections was 84.3%(number of person examined:24,887) in '71, 63.2%(27,178) in '76, and 41.1%(35,018) in '81. By area, the prevalence rate in '81 was 35.1%(20,569) in urban areas and 49.6%(14,447) in rural areas. Intestinal nematodes Ascaris lumbricoides The prevalence of Ascaris infection has decreased significantly in recent years. Among students, the prevalence was 55.4%, in '69 and decreased to 4.7% in '83. In the national prevalence surveys, the prevalence decreased to 13.0% in '81 from 54.9% in '71. By area, the prevalence decreased to 8.5% in '81 from 46.4% in '71 in urban area and 19.4% in '81 from 59.6% in '71 in rural area. By age, the prevalence has become in recent years relatively even in all age groups, although higher prevalence used to be seen in young age groups of around 10 years old, particulary in the highly prevalent rural areas. By sex, the prevalence was higher in the female than in the male. Unfertilized egg positive rates among the ascariasis cases increased gradually up to 55.4% on the average in '81. The intensity of the infection was also significantly decreased. Trichuris trichiura Trichuris infection had also decreased to 23.4% in '81 from 65.4% in '71. By area, the decreasing tendency of the prevalence became faster in urban areas than in the rural areas. The prevalence in urban and rural areas in '71 was 69.7%, and 63.1% respectively and decreased to 19.5% and 29.0% respectively in '81. By age, the prevalence reached a peak at the 10-14 age group and showed relatively even distribution throughout all age groups. By sex, the prevalence was close in young age groups, but in the 30s or over age group, especially in rural area, the prevalence was significantly higher in the female than in the male. The prevalence has much fluctuated depending in the area. The prevalence in rural areas surveyed in the '80s shows a range between 20.9% and 73.7% by locality. It is anticipated that the prevalence of Trichuris infection will drop more rapidly, when mass treatment is conducted. Hookworms Hookworm infection by mostly Ancylostoma duodenale and a few by Necator americanus has decreased to a negligible levels in recent years. In the national prevalence surveys, the prevalence was 10.7% in '71, 2.2% in '76, and 0.5% in '81. The prevalence was higher in rural areas than in urban areas. Wide application of multi-specific anthelminthics in the ascariasis control programmes conducted in the past decade appear to have been effective against hookworm infection. Trichostrongylus orientalis As in the case with hookworm infection, the prevalence of Trichostrongylus infection has reached a negligible levels. In the national prevalence surveys, the prevalence was 7.7% in '71, 1.0% in '76 and 0.2% in '81. Enterobius vermicularis In the national prevalence survey in '81, the egg positive rate was 12.0%. Higher prevalence is expected when examined repeatedly. The prevalence rate was 10.3% in urban area and 14.6% in rural area. In recent surveys conducted in rural areas among schoolchildren, the prevalence was 32.4% in Gimhae Gun in '82 and 64.1% in Yeongyang Gun in '83. By age, the egg positive rate was higher in young age groups of around 10 and sharply decreased in age groups of around 20 and then somewhat increased again in middle age groups. By sex, the prevalence was higher in the female than in the male. Strongyloides stercoralis Strongyloides stercoralis infection has rarely been found in Korea. Three cases were reported in 1914. And 0.1-0.5% were found infected out of 2,642 persons examined at the prisoner-of-war camp on Geojedo in 1956. One case was reported in '54 and '82, respectively. Anisakis spp. No systematic survey has been conducted for anisakiasis In Korea. So far, only several cases have been found 1 case in Seoul in '71, 5 cases in Busan in '81 and 1 case in Busan in '84. Intestinal trematodes Metagonimus yokogawai In the national prevalence survey conducted in 1981, the egg positive rate was 1.24% on the average. High endemic areas are located in the southwestern part of Korea. The prevalence in Hadong Gun was 29.1% on the average in '79. In a survey conducted in 76, the prevalence was 44.0% in Gwangyang, 55.0% in Gogseung and 29.0% in Gurye. The infection is closely correlated with raw sweetfish consumption in these areas. Other intestinal trematodes A human case of Heterophyes heterophyes was reported in 1914. Several species were reported in the '80s : 17 cases of Fibricola seoulensis, 9 cases of Pygidiopsis summa, 8 cases of Heterophyes heterophyes nocens, 1case of Heterophyopsis continua, 2 cases of Stellantchasmus falcatus, 1 case of Stictodora sp., 1 case of Echinostoma hortense, and 4 cases of Echinochasmus japonicus. As the intermediate hosts, snakes and frogs play a role for F.seoulensis and fish for the rest of the species. Intestinal cestodes Taenia saginata and T. solium Egg positive rates in the national prevalence survey were 0.7% in '76 and 1.1% in '81. The prevalence in '81 was 0.6% in urban area and 1.8% in rural area. The proglottid positive rate in Jeju Do was 19.2% on the average. On Udo, Jeju Do in 1983, the egg positive rate among the inhabitants was 2.9%. Hymenolepis nana In the national prevalence survey, egg positive rates were 0.6% in '76 and 0.4% in '81. No difference was seen in the prevalence by area and sex. Hymenolepis diminuta Infected cases were reported : 3 in '64 and I in '66. Egg positive rate in '81 was 0.01% in the national prevalence survey. Diphylobothrium latum So far, about 30 cases have been reported. The cases have been reported more frequently in recent surveys. Mesocestoides sp. A case was reported from a hospitalized patient in Seoul in '67. Spirometra erinacei Two cases were reported in '84 following reidentification of the adult worms collected in '74. Intestinal protozoa Out of a total of 23 species of human protozoan infections in Korea, 13 species were reported as intestinal protozoa : Entamoeba histolytica, E coli, Endolimax nana, Iodamoeba b$\ddot{u}$tschlii, Dientamoeba fragilis, Giardia lamblia, Chilomastix mesnilii, Embadomonas sp., Enteromonas hominis, Trichomonas hominis, Isospora belli, I. Hominis(Sarcocystis hominis), and Balantidium coli. Since the first report on intestinal protozoan infections in 1925, there have been quite a few survey data on the prevalence of the infection. It was found reviewing the data chronologically that up to the early '70s the infection was prevalent around a 30-50%. After that, the protozoan cyst positive rate has shown the tendency of gradual decrease throughout the country. Protozoan cyst survey conducted in Seoul and several provinces in 1981 revealed infection rates of 8.9%(1,310) in Gangweondo, 10.7%(1,703) in Gyenggi Do, 11.7%(1,032) in Jeonra Buk Do, 9.1%(4,116) in Jeonra Nam Do, and 1.4%(5,275) in Seoul. Entamoeba histolytica In the survey conducted by province in '81, the cyst positive rate was 0.8% in Gangweon-do, 0.3% in Gyeonggi Do, 1.4% in both Jeonra Buk Do and Jeonra Nam Do, and 0.2% in Seoul. Giardia lamblia In the survey by province in '81, cyst positive rates were 2.2% in both Gyeonggi Do and Jeonra Buk Do, 1.9% in Jeonra Nam Do, 0.5% in Gangweon Do, and 0.9% in Seoul. Balantidium coli Two cases were reported. One in 1930 and the other in '74. Isospora belli and I. Hominis(Sarcocystis hominis) Isospora belli was reported : 1 case in '56 and 3 cases in '66. I. Hominis, recently identified to be synonymous with Sarcocystis hominis, was reported : 3 cases in '66. Other intestinal protozoa The protozoan parasites other than the above mentioned are generally treated as commensal, although some of them are considered to be pathogenic. The data of '81 show that about 10% of the inhabitants are still infected with protozoa.

• Clinical and Experimental Reproductive Medicine
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• v.23 no.3
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• pp.247-268
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• 1996

It has been known for a long time that gonadotropins and steroid hormones play a pivotal role in a series of reproductive biological phenomena including the maturation of ovarian follicles and oocytes, ovulation and implantation, maintenance of pregnancy and fetal growth & development, parturition and mammary development and lactation. Recent investigations, however, have elucidated that in addition to these classic hormones, multiple growth factors also are involved in these phenomena. Most growth factors in reproductive organs mediate the actions of gonadotropins and steroid hormones or synergize with them in an autocrine/paracrine manner. The insulin-like growth factor(IGF) system, which is one of the most actively investigated areas lately in the reproductive organs, has been found to have important roles in a wide gamut of reproductive phenomena. In the present communication, published literature pertaining to the intrauterine IGF system will be reviewed preceded by general information of the IGF system. The IGF family comprises of IGF-I & IGF-II ligands, two types of IGF receptors and six classes of IGF-binding proteins(IGFBPs) that are known to date. IGF-I and IGF-II peptides, which are structurally homologous to proinsulin, possess the insulin-like activity including the stimulatory effect of glucose and amino acid transport. Besides, IGFs as mitogens stimulate cell division, and also play a role in cellular differentiation and functions in a variety of cell lines. IGFs are expressed mainly in the liver and messenchymal cells, and act on almost all types of tissues in an autocrine/paracrine as well as endocrine mode. There are two types of IGF receptors. Type I IGF receptors, which are tyrosine kinase receptors having high-affinity for IGF-I and IGF-II, mediate almost all the IGF actions that are described above. Type II IGF receptors or IGF-II/mannose-6-phosphate receptors have two distinct binding sites; the IGF-II binding site exhibits a high affinity only for IGF-II. The principal role of the type II IGF receptor is to destroy IGF-II by targeting the ligand to the lysosome. IGFs in biological fluids are mostly bound to IGFBP. IGFBPs, in general, are IGF storage/carrier proteins or modulators of IGF actions; however, as for distinct roles for individual IGFBPs, only limited information is available. IGFBPs inhibit IGF actions under most in vitro situations, seemingly because affinities of IGFBPs for IGFs are greater than those of IGF receptors. How IGF is released from IGFBP to reach IGF receptors is not known; however, various IGFBP protease activities that are present in blood and interstitial fluids are believed to play an important role in the process of IGF release from the IGFBP. According to latest reports, there is evidence that under certain in vitro circumstances, IGFBP-1, -3, -5 have their own biological activities independent of the IGF. This may add another dimension of complexity of the already complicated IGF system. Messenger ribonucleic acids and proteins of the IGF family members are expressed in the uterine tissue and conceptus of the primates, rodents and farm animals to play important roles in growth and development of the uterus and fetus. Expression of the uterine IGF system is regulated by gonadal hormones and local regulatory substances with temporal and spatial specificities. Locally expressed IGFs and IGFBPs act on the uterine tissue in an autocrine/paracrine manner, or are secreted into the uterine lumen to participate in conceptus growth and development. Conceptus also expresses the IGF system beginning from the peri-implantation period. When an IGF family member is expressed in the conceptus, however, is determined by the presence or absence of maternally inherited mRNAs, genetic programming of the conceptus itself and an interaction with the maternal tissue. The site of IGF action also follows temporal (physiological status) and spatial specificities. These facts that expression of the IGF system is temporally and spatially regulated support indirectly a hypothesis that IGFs play a role in conceptus growth and development. Uterine and conceptus-derived IGFs stimulate cell division and differentiation, glucose and amino acid transport, general protein synthesis and the biosynthesis of mammotropic hormones including placental lactogen and prolactin, and also play a role in steroidogenesis. The suggested role for IGFs in conceptus growth and development has been proven by the result of IGF-I, IGF-II or IGF receptor gene disruption(targeting) of murine embryos by the homologous recombination technique. Mice carrying a null mutation for IGF-I and/or IGF-II or type I IGF receptor undergo delayed prenatal and postnatal growth and development with 30-60% normal weights at birth. Moreover, mice lacking the type I IGF receptor or IGF-I plus IGF-II die soon after birth. Intrauterine IGFBPs generally are believed to sequester IGF ligands within the uterus or to play a role of negative regulators of IGF actions by inhibiting IGF binding to cognate receptors. However, when it is taken into account that IGFBP-1 is expressed and secreted in primate uteri in amounts assessedly far exceeding those of local IGFs and that IGFBP-1 is one of the major secretory proteins of the primate decidua, the possibility that this IGFBP may have its own biological activity independent of IGF cannot be excluded. Evidently, elucidating the exact role of each IGFBP is an essential step into understanding the whole IGF system. As such, further research in this area is awaited with a lot of anticipation and attention.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.1-20
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• 2013

Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.53-77
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• 2015

Mobile commerce provides a convenient shopping experience in which users can buy products without the constraints of time and space. Mobile commerce has already set off a mega trend in Korea. The market size is estimated at approximately 15 trillion won (KRW) for 2015, thus far. In the Korean market, social commerce and open market are key components. Social commerce has an overwhelming open market in terms of the number of users in the Korean mobile commerce market. From the point of view of the industry, quick market entry, and content curation are considered to be the major success factors, reflecting the rapid growth of social commerce in the market. However, academics' empirical research and analysis to prove the success rate of social commerce is still insufficient. Henceforward, it is to be expected that social commerce and the open market in the Korean mobile commerce will compete intensively. So it is important to conduct an empirical analysis to prove the differences in user experience between social commerce and open market. This paper is an exploratory study that shows a comparative analysis of social commerce and the open market regarding user experience, which is based on the mobile users' reviews. Firstly, this study includes a collection of approximately 10,000 user reviews of social commerce and open market listed Google play. A collection of mobile user reviews were classified into topics, such as perceived usefulness and perceived ease of use through LDA topic modeling. Then, a sentimental analysis and co-occurrence analysis on the topics of perceived usefulness and perceived ease of use was conducted. The study's results demonstrated that social commerce users have a more positive experience in terms of service usefulness and convenience versus open market in the mobile commerce market. Social commerce has provided positive user experiences to mobile users in terms of service areas, like 'delivery,' 'coupon,' and 'discount,' while open market has been faced with user complaints in terms of technical problems and inconveniences like 'login error,' 'view details,' and 'stoppage.' This result has shown that social commerce has a good performance in terms of user service experience, since the aggressive marketing campaign conducted and there have been investments in building logistics infrastructure. However, the open market still has mobile optimization problems, since the open market in mobile commerce still has not resolved user complaints and inconveniences from technical problems. This study presents an exploratory research method used to analyze user experience by utilizing an empirical approach to user reviews. In contrast to previous studies, which conducted surveys to analyze user experience, this study was conducted by using empirical analysis that incorporates user reviews for reflecting users' vivid and actual experiences. Specifically, by using an LDA topic model and TAM this study presents its methodology, which shows an analysis of user reviews that are effective due to the method of dividing user reviews into service areas and technical areas from a new perspective. The methodology of this study has not only proven the differences in user experience between social commerce and open market, but also has provided a deep understanding of user experience in Korean mobile commerce. In addition, the results of this study have important implications on social commerce and open market by proving that user insights can be utilized in establishing competitive and groundbreaking strategies in the market. The limitations and research direction for follow-up studies are as follows. In a follow-up study, it will be required to design a more elaborate technique of the text analysis. This study could not clearly refine the user reviews, even though the ones online have inherent typos and mistakes. This study has proven that the user reviews are an invaluable source to analyze user experience. The methodology of this study can be expected to further expand comparative research of services using user reviews. Even at this moment, users around the world are posting their reviews about service experiences after using the mobile game, commerce, and messenger applications.

• Korean journal of applied entomology
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• v.12 no.3
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• pp.93-107
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• 1973

Garlic (Allium sativum L.) is an important vegetable crop for the Korean people and has long been cultivated extensively in Korea. More recently it has gained importance as a source of certain pharmaceuticals. This additional use has also contributed to the increasing demand for Korean garlic. Garlic has been propagated vegetatively for a long time without control measures against virus diseases. As a result it is presumed that most of the garlic varieties in Korea may have degenerated. The production of virus-free plants offers the most feasible way to control the virus diseases of garlic. However, little is known about garlic viruses both domestically and in foreign countries. More basic information regarding garlic viruses is needed before a sound approach to the control of these diseases can be developed. Currently garlic mosaic disease is most prevalent in plantings throughout Korea and is considered to be the most important disease of garlic in Korea. Because of this importance, studies were initiated to isolate and characterize the garlic mosaic virus. Symptom expression in test plants, physical properties, purification, serological reaction and morphological characteristics of the garlic mosaic virus were determined. Results of these studies are summarized as follows. 1. Surveys made throughout the important garlic growing areas in Korea during 1970-1972 revealed that most of the garlic plants were heavily infected with mosaic disease. 2. A strain of garlic mosaic virus was obtained from infected garlic leaves and transmitted mechanically to Chenopodium amaranticolor by single lesion isolation technique. 3. The symptom expression of this garlic mosaic virus isolate was examined on 26 species of test plants. Among these, Chenopodium amaranticolor, C. quince, C. album and C. koreanse expressed chlorotic local lesions on inoculated leaves 11-12 days after mechanical inoculation with infective sap. The remaining 22 species showed no symptoms and no virus was recovered from them whet back-inoculated to C. amaranticolor. 4. Among the four species of Chtnopodium mentioned above, C. amaranticolor and C. quinoa appear to be the most suitable local lesion test plants for garlic mosaic virus. 5. Cloves and top·sets originating from mosaic infected garlic plants were $100\%$ infected with the same virus. Consequently the garlic mosaic virus is successively transmitted through infected cloves and top-sets. 6. Garlic mosaic virus was mechanically transmitted to C, amaranticolor when inoculations were made with infective sap of cloves and top-sets. 7. Physical properties of the garlic mosaic virus as determined by inoculation onto C. amaranticolor were as follows. Thermal inactivation point: $65-70^{\circ}C$, Dilution end poiut: $10^-2-10^-3$, Aging in vitro: 2 days. 8. Electron microscopic examination of the garlic mosaic virus revealed long rod shaped particles measuring 1200-1250mu. 9. Garlic mosaic virus was purified from leaf materials of C. amaranticolor by using two cycles of differential centrifugation followed by Sephadex gel filtration. 10. Garlic mosaic virus was successfully detected from infected garlic cloves and top-sets by a serological microprecipitin test. 11 Serological tests of 150 garlic cloves and 30 top-sets collected randomly from seperated plants throughout five different garlic growing regions in Korea revealed $100\%$ infection with garlic mosaic virus. Accordingly it is concluded that most of the garlic cloves and top-sets now being used for propagation in Korea are carriers of the garlic mosaic virus. 12. Serological studies revealed that the garlic mosaic virus is not related with potato viruses X, Y, S and M. 13. Because of the difficulty in securing mosaic virus-free garlic plants, direct inoculation with isolated virus to the garlic plants was not accomplished. Results of the present study, however, indicate that the virus isolate used here is the causal virus of the garlic mosaic disease in Korea.

• Journal of Chest Surgery
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• v.32 no.7
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• pp.603-612
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• 1999

Background : It has been documented that brief repetitive periods of ischemia and reperfusion (ischemic preconditioning, IP) enhances the recovery of post-ischemic contractile function and reduces infarct size after a longer period of ischemia. Many mechanisms have been proposed to explain this process. Recent studies have suggested that transient increase in the intracellular calcium may have triggered the activation of protein kinase C(PKC); however, there are still many controversies. Accordingly, the author performed the present study to test the hypothesis that preconditioning with high concentration of calcium before sustained subsequent ischemia(calcium preconditioning) mimics IP by PKC activation. Material and Method : The isolated hearts from the New Zealand White rabbits(1.5∼2.0 kg body weight) Method: The isolated hearts from the New Zealand White rabbits(1.5∼2.0 kg body weight) were perfused with Tyrode solution by Langendorff technique. After stabilization of baseline hemodynamics, the hearts were subjected to 45-minute global ischemia followed by a 120-minute reperfusion with IP(IP group, n=13) or without IP(ischemic control, n=10). IP was induced by single episode of 5-minute global ischemia and 10-minute reperfusion. In the Ca2+ preconditioned group, perfusate containing 10(n=10) or 20 mM(n=11) CaCl2 was perfused for 10 minutes after 5-minute ischemia followed by a 45-minute global ischemia and a 120-minute reperfusion. Baseline PKC was measured after 50-minute perfusion without any treatment(n=5). Left ventricular function including developed pressure(LVDP), dP/dt, heart rate, left ventricular end-diastolic pressure(LVEDP) and coronary flow(CF) was measured. Myo car ial cytosolic and membrane PKC activities were measured by 32P-${\gamma}$-ATP incorporation into PKC-specific pepetide. The infarct size was determined using the TTC (tetrazolium salt) staining and planimetry. Data were analyzed using one-way analysis of variance(ANOVA) variance(ANOVA) and Tukey's post-hoc test. Result: IP increased the functional recovery including LVDP, dP/dt and CF(p<0.05) and lowered the ascending range of LVEDP(p<0.05); it also reduced the infarct size from 38% to 20%(p<0.05). In both of the Ca2+ preconditioned group, functional recovery was not significantly different in comparison with the ischemic control, however, the infarct size was reduced to 19∼23%(p<0.05). In comparison with the baseline(7.31 0.31 nmol/g tissue), the activities of the cytosolic PKC tended to decrease in both the IP and Ca2+ preconditioned groups, particularly in the 10 mM Ca2+ preconditioned group(4.19 0.39 nmol/g tissue, p<0.01); the activity of membrane PKC was significantly increased in both IP and 10 mM Ca2+ preconditioned group (p<0.05; 1.84 0.21, 4.00 0.14, and 4.02 0.70 nmol/g tissue in the baseline, IP, and 10 mM Ca2+ preconditioned group, respectively). However, the activity of both PKC fractions were not significantly different between the baseline and the ischemic control. Conclusion: These results indicate that in isolated Langendorff-perfused rabbit heart model, calcium preconditioning with high concentration of calcium does not improve post-ischemic functional recovery. However, it does have an effect of limiting(reducing) the infart size by ischemic preconditioning, and this cardioprotective effect, at least in part, may have resulted from the activation of PKC by calcium which acts as a messenger(or trigger) to activate membrane PKC.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.89-105
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• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.1-8
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• 2013

Data mining techniques are used to find important and meaningful information from huge databases, and pattern mining is one of the significant data mining techniques. Pattern mining is a method of discovering useful patterns from the huge databases. Frequent pattern mining which is one of the pattern mining extracts patterns having higher frequencies than a minimum support threshold from databases, and the patterns are called frequent patterns. Traditional frequent pattern mining is based on a single minimum support threshold for the whole database to perform mining frequent patterns. This single support model implicitly supposes that all of the items in the database have the same nature. In real world applications, however, each item in databases can have relative characteristics, and thus an appropriate pattern mining technique which reflects the characteristics is required. In the framework of frequent pattern mining, where the natures of items are not considered, it needs to set the single minimum support threshold to a too low value for mining patterns containing rare items. It leads to too many patterns including meaningless items though. In contrast, we cannot mine any pattern if a too high threshold is used. This dilemma is called the rare item problem. To solve this problem, the initial researches proposed approximate approaches which split data into several groups according to item frequencies or group related rare items. However, these methods cannot find all of the frequent patterns including rare frequent patterns due to being based on approximate techniques. Hence, pattern mining model with multiple minimum supports is proposed in order to solve the rare item problem. In the model, each item has a corresponding minimum support threshold, called MIS (Minimum Item Support), and it is calculated based on item frequencies in databases. The multiple minimum supports model finds all of the rare frequent patterns without generating meaningless patterns and losing significant patterns by applying the MIS. Meanwhile, candidate patterns are extracted during a process of mining frequent patterns, and the only single minimum support is compared with frequencies of the candidate patterns in the single minimum support model. Therefore, the characteristics of items consist of the candidate patterns are not reflected. In addition, the rare item problem occurs in the model. In order to address this issue in the multiple minimum supports model, the minimum MIS value among all of the values of items in a candidate pattern is used as a minimum support threshold with respect to the candidate pattern for considering its characteristics. For efficiently mining frequent patterns including rare frequent patterns by adopting the above concept, tree based algorithms of the multiple minimum supports model sort items in a tree according to MIS descending order in contrast to those of the single minimum support model, where the items are ordered in frequency descending order. In this paper, we study the characteristics of the frequent pattern mining based on multiple minimum supports and conduct performance evaluation with a general frequent pattern mining algorithm in terms of runtime, memory usage, and scalability. Experimental results show that the multiple minimum supports based algorithm outperforms the single minimum support based one and demands more memory usage for MIS information. Moreover, the compared algorithms have a good scalability in the results.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.185-202
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• 2012

.Since the value of information has been realized in the information society, the usage and collection of information has become important. A facial expression that contains thousands of information as an artistic painting can be described in thousands of words. Followed by the idea, there has recently been a number of attempts to provide customers and companies with an intelligent service, which enables the perception of human emotions through one's facial expressions. For example, MIT Media Lab, the leading organization in this research area, has developed the human emotion prediction model, and has applied their studies to the commercial business. In the academic area, a number of the conventional methods such as Multiple Regression Analysis (MRA) or Artificial Neural Networks (ANN) have been applied to predict human emotion in prior studies. However, MRA is generally criticized because of its low prediction accuracy. This is inevitable since MRA can only explain the linear relationship between the dependent variables and the independent variable. To mitigate the limitations of MRA, some studies like Jung and Kim (2012) have used ANN as the alternative, and they reported that ANN generated more accurate prediction than the statistical methods like MRA. However, it has also been criticized due to over fitting and the difficulty of the network design (e.g. setting the number of the layers and the number of the nodes in the hidden layers). Under this background, we propose a novel model using Support Vector Regression (SVR) in order to increase the prediction accuracy. SVR is an extensive version of Support Vector Machine (SVM) designated to solve the regression problems. The model produced by SVR only depends on a subset of the training data, because the cost function for building the model ignores any training data that is close (within a threshold ${\varepsilon}$) to the model prediction. Using SVR, we tried to build a model that can measure the level of arousal and valence from the facial features. To validate the usefulness of the proposed model, we collected the data of facial reactions when providing appropriate visual stimulating contents, and extracted the features from the data. Next, the steps of the preprocessing were taken to choose statistically significant variables. In total, 297 cases were used for the experiment. As the comparative models, we also applied MRA and ANN to the same data set. For SVR, we adopted '${\varepsilon}$-insensitive loss function', and 'grid search' technique to find the optimal values of the parameters like C, d, ${\sigma}^2$, and ${\varepsilon}$. In the case of ANN, we adopted a standard three-layer backpropagation network, which has a single hidden layer. The learning rate and momentum rate of ANN were set to 10%, and we used sigmoid function as the transfer function of hidden and output nodes. We performed the experiments repeatedly by varying the number of nodes in the hidden layer to n/2, n, 3n/2, and 2n, where n is the number of the input variables. The stopping condition for ANN was set to 50,000 learning events. And, we used MAE (Mean Absolute Error) as the measure for performance comparison. From the experiment, we found that SVR achieved the highest prediction accuracy for the hold-out data set compared to MRA and ANN. Regardless of the target variables (the level of arousal, or the level of positive / negative valence), SVR showed the best performance for the hold-out data set. ANN also outperformed MRA, however, it showed the considerably lower prediction accuracy than SVR for both target variables. The findings of our research are expected to be useful to the researchers or practitioners who are willing to build the models for recognizing human emotions.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.147-157
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• 2013

With the advent of the digital environment that can be accessed anytime, anywhere with the introduction of high-speed network, the free distribution and use of digital content were made possible. Ironically this environment is raising a variety of copyright infringement, and product images used in the online shopping mall are pirated frequently. There are many controversial issues whether shopping mall images are creative works or not. According to Supreme Court's decision in 2001, to ad pictures taken with ham products is simply a clone of the appearance of objects to deliver nothing but the decision was not only creative expression. But for the photographer's losses recognized in the advertising photo shoot takes the typical cost was estimated damages. According to Seoul District Court precedents in 2003, if there are the photographer's personality and creativity in the selection of the subject, the composition of the set, the direction and amount of light control, set the angle of the camera, shutter speed, shutter chance, other shooting methods for capturing, developing and printing process, the works should be protected by copyright law by the Court's sentence. In order to receive copyright protection of the shopping mall images by the law, it is simply not to convey the status of the product, the photographer's personality and creativity can be recognized that it requires effort. Accordingly, the cost of making the mall image increases, and the necessity for copyright protection becomes higher. The product images of the online shopping mall have a very unique configuration unlike the general pictures such as portraits and landscape photos and, therefore, the general image watermarking technique can not satisfy the requirements of the image watermarking. Because background of product images commonly used in shopping malls is white or black, or gray scale (gradient) color, it is difficult to utilize the space to embed a watermark and the area is very sensitive even a slight change. In this paper, the characteristics of images used in shopping malls are analyzed and a watermarking technology which is suitable to the shopping mall images is proposed. The proposed image watermarking technology divide a product image into smaller blocks, and the corresponding blocks are transformed by DCT (Discrete Cosine Transform), and then the watermark information was inserted into images using quantization of DCT coefficients. Because uniform treatment of the DCT coefficients for quantization cause visual blocking artifacts, the proposed algorithm used weighted mask which quantizes finely the coefficients located block boundaries and coarsely the coefficients located center area of the block. This mask improves subjective visual quality as well as the objective quality of the images. In addition, in order to improve the safety of the algorithm, the blocks which is embedded the watermark are randomly selected and the turbo code is used to reduce the BER when extracting the watermark. The PSNR(Peak Signal to Noise Ratio) of the shopping mall image watermarked by the proposed algorithm is 40.7~48.5[dB] and BER(Bit Error Rate) after JPEG with QF = 70 is 0. This means the watermarked image is high quality and the algorithm is robust to JPEG compression that is used generally at the online shopping malls. Also, for 40% change in size and 40 degrees of rotation, the BER is 0. In general, the shopping malls are used compressed images with QF which is higher than 90. Because the pirated image is used to replicate from original image, the proposed algorithm can identify the copyright infringement in the most cases. As shown the experimental results, the proposed algorithm is suitable to the shopping mall images with simple background. However, the future study should be carried out to enhance the robustness of the proposed algorithm because the robustness loss is occurred after mask process.