• Journal of the Korea Organic Resources Recycling Association
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• v.31 no.4
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• pp.13-28
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• 2023

This study assessed the biochemical methane potential (B_u-P) of three grass species-Poa pratensis (PP), Zoysia japonica (ZJ), and Agrostis stolonifera (AS). B_u-P values were determined as 0.330 Nm³/kg-VS_added for PP, 0.297 Nm³/kg-VS_added for ZJ, and 0.261 Nm³/kg-VS_added for AS. Notably, PP exhibited superior suitability for methane production. The investigation also examined the impact of silage storage duration on PP grass clippings, revealing a 19% decline in B_u-P from an initial value of 0.269 Nm³/kg-VS_added on day 0 to 0.217 Nm³/kg-VS_added on day 180. Throughout the storage period, there were significant increases in neutral detergent fiber (NDF), acid detergent fiber (ADF), and crude protein (CP) contents, rising from 67.59%, 39.68%, and 3.02% on day 0 to 77.12%, 54.65%, and 6.24% on day 180, respectively. These findings highlight the influence of storage duration on the anaerobic digestibility of PP grass clippings. To effectively utilize grass clippings as a renewable resource for methane production, further studies considering factors such as initial moisture content, pretreatment methods, and potential effects of residual pesticides are necessary to optimize anaerobic digestion efficiency for herbaceous biomass.

• Journal of the Korean earth science society
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• v.45 no.2
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• pp.157-171
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• 2024

The purposes of this study were: (1) to revalidate the revised Systems Thinking Measuring Instrument (Re_STMI) reported by Lee et al. (2024) among Vietnamese high school students and (2) to investigate the differences in systems thinking abilities between Korean and Vietnamese high school students. To achieve this, data from 234 Vietnamese high school students who responded to translated Re_STMI consisting of 20 items and an Scale consisting of 20 items were used. Validity analysis was conducted through item response analysis (Item Reliability, Item Map, Infit and Outfit MNSQ, DIF between male and female) and exploratory factor analysis (principal axis factor analysis using Promax). Furthermore, structural equation modeling was employed with data from 475 Korean high school students to verify the latent mean analysis. The results were as follows: First, in the item response analysis of the 20 translated Re_STMI items in Vietnamese, the Item Reliability was .97, and the Infit MNSQ ranged from .67 to 1.38. The results from the Item Map and DIF analysis align with previous findings. In the exploratory factor analysis, all items were loaded onto intended sub-factors, with sub-factor reliabilities ranging from .662 to .833 and total reliability at .876. Confirmatory factor analysis for latent mean analysis between Korean and Vietnamese students yielded acceptable model fit indices (χ²/df: 2.830, CFI: .931, TLI: .918, SRMR: .043, RMSEA: .051). Lastly, the latent mean analysis between Korean and Vietnamese students revealed a small effect size in systems analysis, mental models, team learning, and shared vision factors, whereas a medium effect size was observed in personal mastery factors, with Vietnamese high school students showing significantly higher results in systems thinking. This study confirmed the reliability and validity of the Re_STMI items. Furthermore, international comparative studies on systems thinking using Re_STMI translated into Vietnamese, English, and other languages are warranted in the context of students' systems thinking analysis.

• Journal of Distribution Research
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• v.16 no.4
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• pp.65-93
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• 2011

As relationship between buyer and seller has been brought closer and long-term relationship has been more important in B2B markets, the importance of service and service convenience increases as well as product. In homogeneous markets, where service offerings are similar and therefore not key competitive differentiator, providing greater convenience may enable a competitive advantage. Service convenience, as conceptualized by Berry et al. (2002), is defined as the consumers' time and effort perceptions related to buying or using a service. For this reason, B2B customers are interested in how fast the service is provided and how much save non-monetary cost like time or effort by the service convenience along with service quality. Therefore, this study attempts to investigate the impact of service convenience on relationship factors such as relationship satisfaction, relationship commitment, and relationship performance. The purpose of this study is to find out whether service convenience can be a new antecedent of relationship quality and relationship performance. In addition, this study tries to examine how five-dimensional service convenience constructs (decision convenience, access convenience, transaction convenience, benefit convenience, post-benefit convenience) affect customers' relationship satisfaction, relationship commitment, and relationship performance. The service convenience comprises five fundamental components - decision convenience (the perceived time and effort costs associated with service purchase or use decisions), access convenience(the perceived time and effort costs associated with initiating service delivery), transaction convenience(the perceived time and effort costs associated with finalizing the transaction), benefit convenience(the perceived time and effort costs associated with experiencing the core benefits of the offering) and post-benefit convenience (the perceived time and effort costs associated with reestablishing subsequent contact with the firm). Earlier studies of perceived service convenience in the industrial market are none. The conventional studies that have dealt with service convenience have usually been made in the consumer market, or they have dealt with convenience aspects in the service process. This service convenience measure for consumer market can be useful tool to estimate service quality in B2B market. The conceptualization developed by Berry et al. (2002) reflects a multistage, experiential consumption process in which evaluations of convenience vary at each stage. For this reason, the service convenience measure is good for B2B service environment which has complex processes and various types. Especially when categorizing B2B service as sequential stage of service delivery like Kumar and Kumar (2004), the Berry's service convenience measure which reflect sequential flow of service deliveries suitable to establish B2B service convenience. For this study, data were gathered from respondents who often buy business service and analyzed by structural equation modeling. The sample size in the present study is 119. Composite reliability values and average variance extracted values were examined for each variable to have reliability. We determine whether the measurement model supports the convergent validity by CFA, and discriminant validity was assessed by examining the correlation matrix of the constructs. For each pair of constructs, the square root of the average variance extracted exceeded their correlations, thus supporting the discriminant validity of the constructs. Hypotheses were tested using the Smart PLS 2.0 and we calculated the PLS path values and followed with a bootstrap re-sampling method to test the hypotheses. Among the five dimensional service convenience constructs, four constructs (decision convenience, transaction convenience, benefit convenience, post-benefit convenience) affected customers' positive relationship satisfaction, relationship commitment, and relationship performance. This result means that service convenience is important cue to improve relationship between buyer and seller. One of the five service convenience dimensions, access convenience, does not affect relationship quality and performance, which implies that the dimension of service convenience is not important factor of cumulative satisfaction. The Cumulative satisfaction can be distinguished from transaction-specific customer satisfaction, which is an immediate post-purchase evaluative judgment or an affective reaction to the most recent transactional experience with the firm. Because access convenience minimizes the physical effort associated with initiating an exchange, the effect on relationship satisfaction similar to cumulative satisfaction may be relatively low in terms of importance than transaction-specific customer satisfaction. Also, B2B firms focus on service quality, price, benefit, follow-up service and so on than convenience of time or place in service because it is relatively difficult to change existing transaction partners in B2B market compared to consumer market. In addition, this study using partial least squares methods reveals that customers' satisfaction and commitment toward relationship has mediating role between the service convenience and relationship performance. The result shows that management and investment to improve service convenience make customers' positive relationship satisfaction, and then the positive relationship satisfaction can enhance the relationship commitment and relationship performance. And to conclude, service convenience management is an important part of successful relationship performance management, and the service convenience is an important antecedent of relationship between buyer and seller such as the relationship commitment and relationship performance. Therefore, it has more important to improve relationship performance that service providers enhance service convenience although competitive service development or service quality improvement is important. Given the pressure to provide increased convenience, it is not surprising that organizations have made significant investments in enhancing the convenience aspect of their product and service offering.

• Korean small business review
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• v.31 no.2
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• pp.85-102
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• 2009

With the continued globalization of world markets, transfer pricing has become one of the dominant sources of controversy in international taxation. Transfer pricing is the process by which a multinational corporation calculates a price for goods and services that are transferred to affiliated entities. Consider a Korean electronic enterprise that buys supplies from its own subsidiary located in China. How much the Korean parent company pays its subsidiary will determine how much profit the Chinese unit reports in local taxes. If the parent company pays above normal market prices, it may appear to have a poor profit, even if the group as a whole shows a respectable profit margin. In this way, transfer prices impact the taxable income reported in each country in which the multinational enterprise operates. It's importance lies in that around 60% of international trade involves transactions between two related parts of multinationals, according to the OECD. Multinational enterprises (hereafter MEs) exert much effort into utilizing organizational advantages to make global investments. MEs wish to minimize their tax burden. So MEs spend a fortune on economists and accountants to justify transfer prices that suit their tax needs. On the contrary, local governments are not prepared to cope with MEs' powerful financial instruments. Tax authorities in each country wish to ensure that the tax base of any ME is divided fairly. Thus, both tax authorities and MEs have a vested interest in the way in which a transfer price is determined, and this is why MEs' international transfer prices are at the center of disputes concerned with taxation. Transfer pricing issues and practices are sometimes difficult to control for regulators because the tax administration does not have enough staffs with the knowledge and resources necessary to understand them. The authors examine transfer pricing practices to provide relevant resources useful in designing tax incentives and regulation schemes for policy makers. This study focuses on identifying the relevant business and environmental factors that could influence the international transfer pricing of MEs. In this perspective, we empirically investigate how the management perception of related variables influences their choice of international transfer pricing methods. We believe that this research is particularly useful in the design of tax policy. Because it can concentrate on a few selected factors in consideration of the limited budget of the tax administration with assistance of this research. Data is composed of questionnaire responses from foreign firms in Korea with investment balances exceeding one million dollars in the end of 2004. We mailed questionnaires to 861 managers in charge of the accounting departments of each company, resulting in 121 valid responses. Seventy six percent of the sample firms are classified as small and medium sized enterprises with assets below 100 billion Korean won. Reviewing transfer pricing methods, cost-based transfer pricing is most popular showing that 60 firms have adopted it. The market-based method is used by 31 firms, and 13 firms have reported the resale-pricing method. Regarding the nationalities of foreign investors, the Japanese and the Americans constitute most of the sample. Logistic regressions have been performed for statistical analysis. The dependent variable is binary in that whether the method of international transfer pricing is a market-based method or a cost-based method. This type of binary classification is founded on the belief that the market-based method is evaluated as the relatively objective way of pricing compared with the cost-based methods. Cost-based pricing is assumed to give mangers flexibility in transfer pricing decisions. Therefore, local regulatory agencies are thought to prefer market-based pricing over cost-based pricing. Independent variables are composed of eight factors such as corporate tax rate, tariffs, relations with local tax authorities, tax audit, equity ratios of local investors, volume of internal trade, sales volume, and product life cycle. The first four variables are included in the model because taxation lies in the center of transfer pricing disputes. So identifying the impact of these variables in Korean business environments is much needed. Equity ratio is included to represent the interest of local partners. Volume of internal trade was sometimes employed in previous research to check the pricing behavior of managers, so we have followed these footsteps in this paper. Product life cycle is used as a surrogate of competition in local markets. Control variables are firm size and nationality of foreign investors. Firm size is controlled using dummy variables in that whether or not the specific firm is small and medium sized. This is because some researchers report that big firms show different behaviors compared with small and medium sized firms in transfer pricing. The other control variable is also expressed in dummy variable showing if the entrepreneur is the American or not. That's because some prior studies conclude that the American management style is different in that they limit branch manger's freedom of decision. Reviewing the statistical results, we have found that managers prefer the cost-based method over the market-based method as the importance of corporate taxes and tariffs increase. This result means that managers need flexibility to lessen the tax burden when they feel taxes are important. They also prefer the cost-based method as the product life cycle matures, which means that they support subsidiaries in local market competition using cost-based transfer pricing. On the contrary, as the relationship with local tax authorities becomes more important, managers prefer the market-based method. That is because market-based pricing is a better way to maintain good relations with the tax officials. Other variables like tax audit, volume of internal transactions, sales volume, and local equity ratio have shown only insignificant influence. Additionally, we have replaced two tax variables(corporate taxes and tariffs) with the data showing top marginal tax rate and mean tariff rates of each country, and have performed another regression to find if we could get different results compared with the former one. As a consequence, we have found something different on the part of mean tariffs, that shows only an insignificant influence on the dependent variable. We guess that each company in the sample pays tariffs with a specific rate applied only for one's own company, which could be located far from mean tariff rates. Therefore we have concluded we need a more detailed data that shows the tariffs of each company if we want to check the role of this variable. Considering that the present paper has heavily relied on questionnaires, an effort to build a reliable data base is needed for enhancing the research reliability.

• Korean Journal of Culture and Social Issue
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• v.12 no.5_spc
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• pp.45-79
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• 2006

The purpose of this paper was to review the results of the subjective well-being(swb) studies performed by Hahn and coworkers in Korean culture. As the correlates of swb, we dealt with demographic/individual difference variables, intrapersonal variables, interpersonal process variables, and Korean cultural variables. We proposed that the components of swb were consisted of quality of life(cognitive swb) and overall happy feelings about one's own life(emotional swb). It was also assumed that a measure of total swb could be calculated by summated mean of cognitive swb and emotional swb measures. The data of the swb studies were analyzed and interpreted according to the above three measures of swb. The results of a nationwide survey(Hahn, 2004) from age of 19 to 75 years ald(n=2,230) showed significant simple correlation coefficients between the following demographic/individual difference variables and swb: Gender difference in swb was found(total swb r=.08, p<.001; life satisfaction r=.10, p<.001; overall emotional swb r=.05, p<.05). Men were happier than women in terms of all three measures of swb. It was also found that women appeared to experience greater positive and negative emotions. Correlation between age and emotional swb(r=.09, p<.001) was significant, but life satisfaction was not significant(r=.04, n.s). Correlations between economic status and swb were also significant(total swb r =.23, p<.001; life satisfaction r=.15 p<.001; overall emotional swb r=.15, p<.001l). Although existence of father was negatively related to emotional swb(r=-.05, p<.05), the existence of mother was not related to any of swb measures. Similarly existence of brothers was related positively to overall emotional swb, but existence of sisters was not. Though existence of son was not related to swb, daughter contributed negatively to swb(total swb -.12, p<.01; life satisfaction -.09, p<.05; emotional swb r=-.12, p<.01). We assumed that family member-in-Iaw also contributed to swb because the extended dose social networks were important in Korean culture. The results showed that the following family member-in-law variables were related to swb: Parents-in-law(total swb r=.11, p<.01; life satisfaction r=.10, p<.01; emotional swb r=.10, p<.01), father-in-law(total swb r=.11, p<.01; life satisfaction r=.11, p<.01; emotional swb r=.06, n.s). The result suggested that especially father-in-law contributed to swb through financial and social support. Correlations between emotional experiences in everyday life and swb were also presented. The range of correlation coefficients between the positive emotion measures and swb were r=.30~.48(p<.001) when the above two measures obtained at same time. But the range decreased to r=.19~32(p<.001) when the swb measure was obtained 9 month later longitudinally. Intercorrelations between positive emotional experience; and life satisfaction were r=.37~58(p<.001) when two measures were obtained at same time. We also examined the effects of the intrapersonal cognitive responses to the most stressful life event upon swb. The results of nationwide survey(n=1,021) showed that self-disclosure(total swb r=.09, p<.010; life satisfaction r=.10, p<.01; emotional swb r=.07, p<.01), rumination(total swb r=-.17, p<.001), thought avoidance(total swb r=.12, p<.001; life satisfaction r=-.08; emotional swb r=-.12, p<.001) and suppression(total swb r=-.13, p<.001; life satisfaction r=-.08, p<.05: emotional swb r=-.13, p<.001) contributed to swb. It was also suggested that mismatch between self-guide and regulatory focus contributed negatively to emotional swb. It was also found that social comparison motives and fulfillment of the motives contributed to swb. The results of a survey research(n=363 college students) revealed that the higher the general social comparison motive, the lower the swb(total swb r=-.15, P<.01: life satisfaction r=-.17. p<.01; emotional swb r=-.10, p<.05). It was also found that satisfaction level of self-evalution motive contributed positively to swb(total swb r=-.14. p<.01: life satisfaction r=-.12, p<.05; emotional swb r=.15, p<.001). Both of self-improvement motive(r=.13, p<.05) and satisfaction level of self-improvement motive(r=.12, p<.05) contributed positively to emotional swb, respectively. The above results suggested that swb was depended upon the interaction effect of social comparison motive; and level of fulfillment of the motives. We also reported the significant multiple predictors of swb in a sample of age from 60years to 89years olds. The results of multiple regression analysis showed that the significant multiple predictors of swb were past illness(β=.174, p<.001), economic status(β=.418, p<.001), marital satisfaction(β=.0841, p<.001), satisfaction of offsprins(β=.065, p<.01), expectation level of social support from offsprings(β=-.049, p<.001), and negative emotions(β=-.454. p<.001) among 16 social psychological factors. It was also found that swb was an important multiple predictors of physical health. This finding was replicated in a longitudinal study. Both of positive and negative emotional experiences were significant multiple predictors of physical health one year later. The results of the discriminant analysis showed both of total swb and positive emotional experiences contributed to discriminate the happy and healthy olds from unhappy and unhealthy olds. We paper also examined the effects of the nonnative social behaviors upon swb in Korean culture. The main hypotheses of the study(Hahn, 2006, in press) was that the important nonnative behaviors would influence on swb through both of the mediation processes of adjustment to social relationships and psychological stress. The survey data were collected from 2,129 adults age of 19 to 75, from 7 regional areas in Korea. The results of the study revealed that almost all of correlation coefficients between 15 normative social behaviors and the above three criteria w-ere significant. The fitness test results of the covariance structural equation model showed that all of the fitness indices were satisfactory (GFI=.974, AGFI=.909, NNFI=.922, NFI=.973, CFI=.974. RMR=.049, RMSEA=.073). The results of the analysis revealed that the following five path coeffi6ents from behaviors to social adjustment were significant; behavior tor family and family members(t=5.87, p<.001), courteous behavior(t=4.39, p<.001), faithful behavior (t=2.15. p<.05). collectivistic behavior(t=8.31, p<.001). Seven path coefficients from the normative behaviors to psychological stress were significant; behavior for family and family members (t=-4.63, p<.001), faithful behavior(t=-3.86, p<.001). suppression of emotional expression(t=3.99, p<.001), trustworthy and dependable behavior(t=-2.21, p<.05), collectivistic behavior(t=3.72, p<.001), effortful and diligent behavior(t=2.94, p<.001), husbandry and saving behavior(t=3.40, p<.001). The above results suggested that four normative behaviors among seven behaviors contributed negatively to psychological stress in current Korean society. The results abo confirmed the hypothesized paths from social adjustment (t=10.40, p<.001) to swb and from psychological stress(t=-19.74, p<.001) to swb. The important results of the study were discussed in terms of the Confucian traditions and recent social changes in Korean culture. Finally limitations of this review paper were discussed and the suggestions for the future study were also proposed.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.127-148
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• 2020

The data center is a physical environment facility for accommodating computer systems and related components, and is an essential foundation technology for next-generation core industries such as big data, smart factories, wearables, and smart homes. In particular, with the growth of cloud computing, the proportional expansion of the data center infrastructure is inevitable. Monitoring the health of these data center facilities is a way to maintain and manage the system and prevent failure. If a failure occurs in some elements of the facility, it may affect not only the relevant equipment but also other connected equipment, and may cause enormous damage. In particular, IT facilities are irregular due to interdependence and it is difficult to know the cause. In the previous study predicting failure in data center, failure was predicted by looking at a single server as a single state without assuming that the devices were mixed. Therefore, in this study, data center failures were classified into failures occurring inside the server (Outage A) and failures occurring outside the server (Outage B), and focused on analyzing complex failures occurring within the server. Server external failures include power, cooling, user errors, etc. Since such failures can be prevented in the early stages of data center facility construction, various solutions are being developed. On the other hand, the cause of the failure occurring in the server is difficult to determine, and adequate prevention has not yet been achieved. In particular, this is the reason why server failures do not occur singularly, cause other server failures, or receive something that causes failures from other servers. In other words, while the existing studies assumed that it was a single server that did not affect the servers and analyzed the failure, in this study, the failure occurred on the assumption that it had an effect between servers. In order to define the complex failure situation in the data center, failure history data for each equipment existing in the data center was used. There are four major failures considered in this study: Network Node Down, Server Down, Windows Activation Services Down, and Database Management System Service Down. The failures that occur for each device are sorted in chronological order, and when a failure occurs in a specific equipment, if a failure occurs in a specific equipment within 5 minutes from the time of occurrence, it is defined that the failure occurs simultaneously. After configuring the sequence for the devices that have failed at the same time, 5 devices that frequently occur simultaneously within the configured sequence were selected, and the case where the selected devices failed at the same time was confirmed through visualization. Since the server resource information collected for failure analysis is in units of time series and has flow, we used Long Short-term Memory (LSTM), a deep learning algorithm that can predict the next state through the previous state. In addition, unlike a single server, the Hierarchical Attention Network deep learning model structure was used in consideration of the fact that the level of multiple failures for each server is different. This algorithm is a method of increasing the prediction accuracy by giving weight to the server as the impact on the failure increases. The study began with defining the type of failure and selecting the analysis target. In the first experiment, the same collected data was assumed as a single server state and a multiple server state, and compared and analyzed. The second experiment improved the prediction accuracy in the case of a complex server by optimizing each server threshold. In the first experiment, which assumed each of a single server and multiple servers, in the case of a single server, it was predicted that three of the five servers did not have a failure even though the actual failure occurred. However, assuming multiple servers, all five servers were predicted to have failed. As a result of the experiment, the hypothesis that there is an effect between servers is proven. As a result of this study, it was confirmed that the prediction performance was superior when the multiple servers were assumed than when the single server was assumed. In particular, applying the Hierarchical Attention Network algorithm, assuming that the effects of each server will be different, played a role in improving the analysis effect. In addition, by applying a different threshold for each server, the prediction accuracy could be improved. This study showed that failures that are difficult to determine the cause can be predicted through historical data, and a model that can predict failures occurring in servers in data centers is presented. It is expected that the occurrence of disability can be prevented in advance using the results of this study.

• 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.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.31-59
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• 2007

We frequently use search engines to find relevant information in the Web but still end up with too much information. In order to solve this problem of information overload, ranking algorithms have been applied to various domains. As more information will be available in the future, effectively and efficiently ranking search results will become more critical. In this paper, we propose a ranking algorithm for the Semantic Web resources, specifically RDF resources. Traditionally, the importance of a particular Web page is estimated based on the number of key words found in the page, which is subject to manipulation. In contrast, link analysis methods such as Google's PageRank capitalize on the information which is inherent in the link structure of the Web graph. PageRank considers a certain page highly important if it is referred to by many other pages. The degree of the importance also increases if the importance of the referring pages is high. Kleinberg's algorithm is another link-structure based ranking algorithm for Web pages. Unlike PageRank, Kleinberg's algorithm utilizes two kinds of scores: the authority score and the hub score. If a page has a high authority score, it is an authority on a given topic and many pages refer to it. A page with a high hub score links to many authoritative pages. As mentioned above, the link-structure based ranking method has been playing an essential role in World Wide Web(WWW), and nowadays, many people recognize the effectiveness and efficiency of it. On the other hand, as Resource Description Framework(RDF) data model forms the foundation of the Semantic Web, any information in the Semantic Web can be expressed with RDF graph, making the ranking algorithm for RDF knowledge bases greatly important. The RDF graph consists of nodes and directional links similar to the Web graph. As a result, the link-structure based ranking method seems to be highly applicable to ranking the Semantic Web resources. However, the information space of the Semantic Web is more complex than that of WWW. For instance, WWW can be considered as one huge class, i.e., a collection of Web pages, which has only a recursive property, i.e., a 'refers to' property corresponding to the hyperlinks. However, the Semantic Web encompasses various kinds of classes and properties, and consequently, ranking methods used in WWW should be modified to reflect the complexity of the information space in the Semantic Web. Previous research addressed the ranking problem of query results retrieved from RDF knowledge bases. Mukherjea and Bamba modified Kleinberg's algorithm in order to apply their algorithm to rank the Semantic Web resources. They defined the objectivity score and the subjectivity score of a resource, which correspond to the authority score and the hub score of Kleinberg's, respectively. They concentrated on the diversity of properties and introduced property weights to control the influence of a resource on another resource depending on the characteristic of the property linking the two resources. A node with a high objectivity score becomes the object of many RDF triples, and a node with a high subjectivity score becomes the subject of many RDF triples. They developed several kinds of Semantic Web systems in order to validate their technique and showed some experimental results verifying the applicability of their method to the Semantic Web. Despite their efforts, however, there remained some limitations which they reported in their paper. First, their algorithm is useful only when a Semantic Web system represents most of the knowledge pertaining to a certain domain. In other words, the ratio of links to nodes should be high, or overall resources should be described in detail, to a certain degree for their algorithm to properly work. Second, a Tightly-Knit Community(TKC) effect, the phenomenon that pages which are less important but yet densely connected have higher scores than the ones that are more important but sparsely connected, remains as problematic. Third, a resource may have a high score, not because it is actually important, but simply because it is very common and as a consequence it has many links pointing to it. In this paper, we examine such ranking problems from a novel perspective and propose a new algorithm which can solve the problems under the previous studies. Our proposed method is based on a class-oriented approach. In contrast to the predicate-oriented approach entertained by the previous research, a user, under our approach, determines the weights of a property by comparing its relative significance to the other properties when evaluating the importance of resources in a specific class. This approach stems from the idea that most queries are supposed to find resources belonging to the same class in the Semantic Web, which consists of many heterogeneous classes in RDF Schema. This approach closely reflects the way that people, in the real world, evaluate something, and will turn out to be superior to the predicate-oriented approach for the Semantic Web. Our proposed algorithm can resolve the TKC(Tightly Knit Community) effect, and further can shed lights on other limitations posed by the previous research. In addition, we propose two ways to incorporate data-type properties which have not been employed even in the case when they have some significance on the resource importance. We designed an experiment to show the effectiveness of our proposed algorithm and the validity of ranking results, which was not tried ever in previous research. We also conducted a comprehensive mathematical analysis, which was overlooked in previous research. The mathematical analysis enabled us to simplify the calculation procedure. Finally, we summarize our experimental results and discuss further research issues.

• Tuberculosis and Respiratory Diseases
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• v.53 no.5
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• pp.497-509
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• 2002

Background : The mechanisms through which cellular activation results in intracellular mycobacterial killing is only partially understood. However, in vitro studies of human immunity to Mycobacterium tuberculosis have been largely modeled on the work reported by Crowle, which is complicated by several factors. The whole blood culture is simple and allows the simultaneous analysis of the relationship between bacterial killing and the effect of effector cells and humoral factors. In this study, we attempted to determine the extent to which M. tuberculosis is killed in a human whole blood culture and to explore the role of the host and microbial factor in this process. Methods : The PPD positive subject were compared to the umbilical cord blood and patients with tuberculosis, diabetes and lung cancer. The culture is performed using heparinized whole blood diluted with a culture medium and infected with a low number of M. avium or M. tuberculosis $H_{37}Ra$ for 4 days by rotating the culture in a $37^{\circ}C$, 5% $CO_2$ incubator. In some experiments, methlprednisolone- or pentoxifyline were used to inhibit the immune response. To assess the role of the T-cell subsets, CD4+, CD8+ T-cells or both were removed from the blood using magnetic beads. The ${\Delta}$ log killing ratio was defined using a CFU assay as the difference in the log number of viable organisms in the completed culture compared to the inoculum. Results : 1. A trend was noted toward the improved killing of mycobacteria in PPD+ subjects comparing to the umbilical cord blood but there was no specific difference in the patients with tuberculosis, diabetes and lung cancer. 2. Methylprednisolone and pentoxifyline adversely affected the killing in the PPD+ subjects umbilical cord blood and patients with tuberculosis. 3. The deletion of CD4+ or CD8+ T-lymphocytes adversely affected the killing of M. avium and M. tuberculosis $H_{37}Ra$ by PPD+ subjects. Deletion of both cell types had an additive effect, particularly in M. tuberculosis $H_{37}Ra$. 4. A significantly improved mycobacterial killing was noted after chemotherapy in patients with tuberculosis and the ${\Delta}$ logKR continuously decreased in a 3 and 4 days of whole blood culture. Conclusion : The in vitro bactericidal assay by human whole blood culture model was settled using a CFU assay. However, the host immunity to M. tuberculosis was not apparent in the human whole blood culture bactericidal assay, and patients with tuberculosis showed markedly improved bacterial killing after anti-tuberculous chemotherapy compared to before. The simplicity of a whole blood culture facilitates its inclusion in a clinical trial and it may have a potential role as a surrogate marker in a TB vaccine trial.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.69-92
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• 2015

The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.