• Tuberculosis and Respiratory Diseases
• /
• v.44 no.2
• /
• pp.349-359
• /
• 1997

Background : The signal pathways and their precise roles for acute respiratory distress syndrome caused by endotoxin (ETX) has not been established. Since there has been several in vitro experiments suggesting that activation of protein kinase C (PKC) pathway may be responsible for endotoxin-induced inflammatory reaction, we performed in vivo experiments in the rats with the hypothesis that PKC-inhibition can effectively prevent endotoxin-induced acute lung injury. Methods : We studied the role of PKC in ETX-induced ALI using PKC inhibitor (staurosporine, STP) in the rat Specific pathogen free male Sprague-Dawley weighted from 165 to 270g were used for the study. Animals were divided into the normal control (NC)-, vehicle control (VC)-, ETX-, PMA (phorbolmyristateacetate)-, STP+PMA-, and STP+ETX-group. PMA (50mg/kg) or ETX (7mg/kg) was instilled through polyethylen catheter after aseptic tracheostomy with and without STP (0.2mg/kg)-pretreatment STP was injected via tail vein 30min before intratracheal injection (IT) of PMA or ETX. Bronchoalveolar lavage (BAL) was done 3-or 6-hrs after IT of PMA or ETX respectively, to measure protein concentration, total and differential cell counts. Results : The results were as follows. The protein concentrations in BALF in the PMA- and ETX-group were very higher than that of VC-group (p<0.001). When animals were pretreated with STP, the %reduction of the protein concentration in BALF was $64.8{\pm}8.5$ and $30.4{\pm}2.5%$ in the STP+PMA- and STP+ETX-group, respectively (p = 0.028). There was no difference in the total cell counts between the PMA-and VC-group (p = 0.26). However the ETX-group showed markedly increased total cell counts as compared to the VC- (p = 0.003) and PMA-group (p = 0.0027), respectively. The total cell counts in BALF were not changed after pretreatment with STP compared to the PMA- (p = 0.22) and ETX-group (p = 0.46). The percentage of PMN, but not alveolar macrophage, was significantly elevated in the PMA-, and ETX-group. Especially in the ETX-group, the percentage of PMN was 17 times higher than that of PMA (p < 0.001). The differential cell counts was not different between the PMA and STP+PMA On the contrary the STP+ETX-group showed decreased percentage of PMN (p = 0.016). There was no significant relationship between the protein concentration and the total or differential cell counts in each group. Conclusion : Pretreatment with PKC-inhibitor (staurosporine) partially but significantly inhibited ETX-induced ALI.

• Tuberculosis and Respiratory Diseases
• /
• v.47 no.6
• /
• pp.824-835
• /
• 1999

Background: Sleep-related breathing disorders are commonly found in patients with chronic renal failure and particularly, sleep apnea may have an influence on the long-term mortality rates in these patients. Maintenance hemodialysis is the mainstay of medical measures for correcting the metabolic derangements of chronic renal failure but it is uncertain whether it may alleviate sleep disorders including sleep apnea. Methods: Forty seven patients on maintenance hemodialysis were surveyed with the sleep questionnaire about their clinical symptoms related to sleep disorders. Among them, 15 patients underwent the polysomnography and their blood levels of urea nitrogen, creatinine, electrolytes and the arterial blood gases in the nights before and following hemodialysis were measured. Results: Forty(85.1%) of the 47 patients complained of the symptoms associated with sleep-wake cycle disturbances, 55.3% experienced snoring and 27.7% reported witnessed apneas. The duration of REM sleep increased significantly in the nights after hemodialysis compared to the nights without hemodialysis(p<0.05) and the percentage of total sleep time comprising NREM sleep decreased significantly in the nights following hemodialysis compared to the nights before hemodialysis(p<0.05). The percentage of total sleep time consisting of the stage 1 and 2 NREM sleep showed the trend for a decrease in the nights after hemodialysis(p=0.051), while the percentage of total sleep time comprising the stage 3 and 4 NREM sleep did not change between nights. The obstructive sleep apnea was more predominant type than the central one in both nights and there were no differences in the apnea index and the apnea-hypopnea index between the nights. The decrease in the blood level of urea nitrogen, creatinine, potassium and phosphorus was observed after hemodialysis(p<0.05), but the differences of parameters measured during polysomnography between the nights did not correlate with the changes of biochemical factors obtained on the two nights. Arterial blood gas analysis showed that pH was significantly greater in the nights after hemodialysis than in the nights before hemodialysis(p<0.05), but there were no correlations between the parameters examined during polysomnography and the parameters of arterial blood gas analysis(p<0.05). Conclusion: These results suggest that chronic renal failure is an important systemic disorder which is strongly associated with sleep disorders. Maintenance hemodialysis, although it is a widely accepted measure to treat chronic renal failure, did not significantly modulate the sleep architecture and the severity of sleep apnea. Thus, taking the patients with chronic renal failure into account, it is advisable to try not only to find a substantial way for correcting metabolic derangements but also to consider the institution of more effective treatments for sleep disorders.

• Journal of Global Scholars of Marketing Science
• /
• v.20 no.3
• /
• pp.269-277
• /
• 2010

Previous studies have shown that the most important factor affecting customer loyalty in the service industry is service quality. However, on the subject of whether service quality has a direct or indirect effect on customer loyalty, scholars' views apparently vary. Some studies suggest that service quality has a direct and fundamental influence on customer loyalty (Bai and Liu, 2002). However, others have shown that service quality not only directly affects customer loyalty, it also has an indirect impact on customer loyalty by influencing customer satisfaction and perceived value (Cronin, Brady, and Hult, 2000). Currently, there are few domestic articles that specifically address the relationship between service quality and customer loyalty in the mobile communication industry. Moreover, research has studied customer loyalty as a whole variable, rather than breaking it down further into multiple dimensions. Based on this analysis, this paper summarizes previous study results, establishes an effect mechanism model among service quality, customer satisfaction, and customer loyalty in the mobile communication industry, and presents a statistical test on model assumptions by using customer investigation data from Heilongjiang Mobile Company. It provides theoretical guidance for mobile service management based on the discussion of the hypothesis test results. For data collection, the sample comprised mobile users in Harbin city, and the survey was taken by random sampling. Out of a total of 300 questionnaires, 276 (92.9%) were recovered. After excluding invalid questionnaires, 249 remained, for an effective rate of 82.6 percent for the study. Cronbach's ${\alpha}$ coefficient was adapted to assess the scale reliability, and validity testing was conducted on the questionnaire from three aspects: content validity, construct validity. and convergent validity. The study tested for goodness of fit mainly from the absolute and relative fit indexes. From the hypothesis testing results, overall, four assumptions have not been supported. The ultimate affective relationship of service quality, customer satisfaction, and customer loyalty is demonstrated in Figure 2. On the whole, the service quality of the communication industry not only has a direct positive significant effect on customer loyalty, it also has an indirect positive significant effect on customer loyalty through service quality; the affective mechanism and extent of customer loyalty are different, and are influenced by each dimension of service quality. This study used the questionnaires of existing literature from home and abroad and tested them in empirical research, with all questions adapted to seven-point Likert scales. With the SERVQUAL scale of Parasuraman, Zeithaml, and Berry (1988), or PZB, as a reference point, service quality was divided into five dimensions-tangibility, reliability, responsiveness, assurance, and empathy-and the questions were simplified down to nineteen. The measurement of customer satisfaction was based mainly on Fornell (1992) and Wang and Han (2003), ending up with four questions. Based on the study’s three indicators of price tolerance, first choice, and complaint reaction were used to measure attitudinal loyalty, while repurchase intention, recommendation, and reputation measured behavioral loyalty. The collection and collation of literature data produced a model of the relationship among service quality, customer satisfaction, and customer loyalty in mobile communications, and China Mobile in the city of Harbin in Heilongjiang province was used for conducting an empirical test of the model and obtaining some useful conclusions. First, service quality in mobile communication is formed by the five factors mentioned earlier: tangibility, reliability, responsiveness, assurance, and empathy. On the basis of PZB SERVQUAL, the study designed a measurement scale of service quality for the mobile communications industry, and obtained these five factors through exploratory factor analysis. The factors fit basically with the five elements, indicating the concept of five elements of service quality for the mobile communications industry. Second, service quality in mobile communications has both direct and indirect positive effects on attitudinal loyalty, with the indirect effect being produced through the intermediary variable, customer satisfaction. There are also both direct and indirect positive effects on behavioral loyalty, with the indirect effect produced through two intermediary variables: customer satisfaction and attitudinal loyalty. This shows that better service quality and higher customer satisfaction will activate the attitudinal to service providers more active and show loyalty to service providers much easier. In addition, the effect mechanism of all dimensions of service quality on all dimensions of customer loyalty is different. Third, customer satisfaction plays a significant intermediary role among service quality and attitudinal and behavioral loyalty, indicating that improving service quality can boost customer satisfaction and make it easier for satisfied customers to become loyal customers. Moreover, attitudinal loyalty plays a significant intermediary role between service quality and behavioral loyalty, indicating that only attitudinally and behaviorally loyal customers are truly loyal customers. The research conclusions have some indications for Chinese telecom operators and others to upgrade their service quality. Two limitations to the study are also mentioned. First, all data were collected in the Heilongjiang area, so there might be a common method bias that skews the results. Second, the discussion addresses the relationship between service quality and customer loyalty, setting customer satisfaction as mediator, but does not consider other factors, like customer value and consumer features, This research will be continued in the future.

• Journal of Intelligence and Information Systems
• /
• v.18 no.3
• /
• pp.137-152
• /
• 2012

In the generation of Web 2.0, as many users start to make lots of web contents called user created contents by themselves, the World Wide Web is overflowing by countless information. Therefore, it becomes the key to find out meaningful information among lots of resources. Nowadays, the information retrieval is the most important thing throughout the whole field and several types of search services are developed and widely used in various fields to retrieve information that user really wants. Especially, the legal information search is one of the indispensable services in order to provide people with their convenience through searching the law necessary to their present situation as a channel getting knowledge about it. The Office of Legislation in Korea provides the Korean Law Information portal service to search the law information such as legislation, administrative rule, and judicial precedent from 2009, so people can conveniently find information related to the law. However, this service has limitation because the recent technology for search engine basically returns documents depending on whether the query is included in it or not as a search result. Therefore, it is really difficult to retrieve information related the law for general users who are not familiar with legal terms in the search engine using simple matching of keywords in spite of those kinds of efforts of the Office of Legislation in Korea, because there is a huge divergence between everyday words and legal terms which are especially from Chinese words. Generally, people try to access the law information using everyday words, so they have a difficulty to get the result that they exactly want. In this paper, we propose a term mapping methodology between everyday words and legal terms for general users who don't have sufficient background about legal terms, and we develop a search service that can provide the search results of law information from everyday words. This will be able to search the law information accurately without the knowledge of legal terminology. In other words, our research goal is to make a law information search system that general users are able to retrieval the law information with everyday words. First, this paper takes advantage of tags of internet blogs using the concept for collective intelligence to find out the term mapping relationship between everyday words and legal terms. In order to achieve our goal, we collect tags related to an everyday word from web blog posts. Generally, people add a non-hierarchical keyword or term like a synonym, especially called tag, in order to describe, classify, and manage their posts when they make any post in the internet blog. Second, the collected tags are clustered through the cluster analysis method, K-means. Then, we find a mapping relationship between an everyday word and a legal term using our estimation measure to select the fittest one that can match with an everyday word. Selected legal terms are given the definite relationship, and the relations between everyday words and legal terms are described using SKOS that is an ontology to describe the knowledge related to thesauri, classification schemes, taxonomies, and subject-heading. Thus, based on proposed mapping and searching methodologies, our legal information search system finds out a legal term mapped with user query and retrieves law information using a matched legal term, if users try to retrieve law information using an everyday word. Therefore, from our research, users can get exact results even if they do not have the knowledge related to legal terms. As a result of our research, we expect that general users who don't have professional legal background can conveniently and efficiently retrieve the legal information using everyday words.

• Journal of Intelligence and Information Systems
• /
• v.20 no.2
• /
• pp.137-148
• /
• 2014

Recommender system has become one of the most important technologies in e-commerce in these days. The ultimate reason to shop online, for many consumers, is to reduce the efforts for information search and purchase. Recommender system is a key technology to serve these needs. Many of the past studies about recommender systems have been devoted to developing and improving recommendation algorithms and collaborative filtering (CF) is known to be the most successful one. Despite its success, however, CF has several shortcomings such as cold-start, sparsity, gray sheep problems. In order to be able to generate recommendations, ordinary CF algorithms require evaluations or preference information directly from users. For new users who do not have any evaluations or preference information, therefore, CF cannot come up with recommendations (Cold-star problem). As the numbers of products and customers increase, the scale of the data increases exponentially and most of the data cells are empty. This sparse dataset makes computation for recommendation extremely hard (Sparsity problem). Since CF is based on the assumption that there are groups of users sharing common preferences or tastes, CF becomes inaccurate if there are many users with rare and unique tastes (Gray sheep problem). This study proposes a new algorithm that utilizes Social Network Analysis (SNA) techniques to resolve the gray sheep problem. We utilize 'degree centrality' in SNA to identify users with unique preferences (gray sheep). Degree centrality in SNA refers to the number of direct links to and from a node. In a network of users who are connected through common preferences or tastes, those with unique tastes have fewer links to other users (nodes) and they are isolated from other users. Therefore, gray sheep can be identified by calculating degree centrality of each node. We divide the dataset into two, gray sheep and others, based on the degree centrality of the users. Then, different similarity measures and recommendation methods are applied to these two datasets. More detail algorithm is as follows: Step 1: Convert the initial data which is a two-mode network (user to item) into an one-mode network (user to user). Step 2: Calculate degree centrality of each node and separate those nodes having degree centrality values lower than the pre-set threshold. The threshold value is determined by simulations such that the accuracy of CF for the remaining dataset is maximized. Step 3: Ordinary CF algorithm is applied to the remaining dataset. Step 4: Since the separated dataset consist of users with unique tastes, an ordinary CF algorithm cannot generate recommendations for them. A 'popular item' method is used to generate recommendations for these users. The F measures of the two datasets are weighted by the numbers of nodes and summed to be used as the final performance metric. In order to test performance improvement by this new algorithm, an empirical study was conducted using a publically available dataset - the MovieLens data by GroupLens research team. We used 100,000 evaluations by 943 users on 1,682 movies. The proposed algorithm was compared with an ordinary CF algorithm utilizing 'Best-N-neighbors' and 'Cosine' similarity method. The empirical results show that F measure was improved about 11% on average when the proposed algorithm was used