• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.3
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• pp.17-32
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• 2023

In recent years, the need for social ventures that aim to grow while solving social problems through the efficiency and effectiveness of commercial organizations in the market has increased, while there is a limit to how much the government and the public can do to solve social problems. Against this background, the number of social venture startups is increasing in the domestic startup ecosystem, and interest in impact investors, which are investors in social ventures, is also increasing. Therefore, this research utilized judgment analysis technology to objectively analyze the validity and weight of judgment information based on the cognitive process and decision-making environment in the investment decision-making of impact investors. We proceeded with the research by constructing three classifications; first, investment priorities at the initial investment stage for financial benefit and return on investment as an investor, second, the political skills of the entrepreneurs (teams) for the social impact and ripple power, and social venture coexistence and solidarity, third, the social mission of a social venture that meets the purpose of an impact investment fund. As a result of this research, first of all, the investment decision-making priorities of impact investors are the expertise of the entrepreneur (team), the potential rate of return when the entrepreneur (team) succeeds, and the social mission of the entrepreneur (team). Second, impact investors do not have a uniform understanding of the investment decision-making factors, and the factors that determine investment decisions are different, and there are differences in the degree of the weighting. Third, among the various investment decision-making factors of impact investment, "entrepreneur's (team's) networking ability", "entrepreneur's (team's) social insight", "entrepreneur's (team's) interpersonal influence" was relatively lower than the other four factors. The practical contribution through this research is to help social ventures understand the investment determinant factors of impact investors in the process of financing, and impact investors can be expected to improve the quality of investment decision-making by referring to the judgment cases and analysis of impact investors. The academic contribution is that it empirically investigated the investment priorities and weighting differences of impact investors.

• Journal of Venture Innovation
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• v.7 no.1
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• pp.1-15
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• 2024

This study aims to elucidate the characteristics of big tech platform companies' sports content business in an environment of rapid digital transformation. Specifically, this study examines the market structure of big tech platform companies with a focus on Amazon, revealing the role of sports content within this structure through an analysis of Amazon's sports marketing business and provides an outlook on the sports content business of big tech platform companies. Based on two-sided market platform business models, big tech platform companies incorporate sports content as a strategy to enhance the value of their platforms. Therefore, sports content is used as a tool to enhance the value of their platforms and to consolidate their monopoly position by maximizing profits by increasing the synergy of platform ecosystems such as infrastructure. Amazon acquires popular live sports broadcasting rights on a continental or national basis and supplies them to its platforms, which not only increases the number of new customers and purchasing effects, but also provides IT solution services to sports organizations and teams while planning and supplying various promotional contents, thus creates synergy across Amazon's platforms including its advertising business. Amazon also expands its business opportunities and increases its overall value by supplying live sports contents to Amazon Prime Video and Amazon Prime, providing technical services to various stakeholders through Amazon Web Services, and offering Amazon Marketing Cloud services for analyzing and predicting advertisers' advertising and marketing performance. This gives rise to a new paradigm in the sports marketing business in the digital era, stemming from the difference in market structure between big tech companies based on two-sided market platforms and legacy global companies based on one-sided markets. The core of this new model is a business through the development of various contents based on live sports streaming rights, and sports content marketing will become a major field of sports marketing along with traditional broadcasting rights and sponsorship. Big tech platform global companies such as Amazon, Apple, and Google have the potential to become new global sports marketing companies, and the current sports marketing and advertising companies, as well as teams and leagues, are facing both crises and opportunities.

• Journal of Life Science
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• v.34 no.8
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• pp.558-566
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• 2024

The potential therapeutic effects of Kaempferia Parviflora ethanol extract (KPE) on osteoarthritis were investigated using the human chondrocyte cell line (CHON-001) to explore its application in functional foods. The CHON-001 cells were pre-treated with either 1 ㎍/ml or 5 ㎍/ml of KPE before exposure to 10 ng/ml of IL-1β to induce osteoarthritis. Results showed that KPE treatment significantly suppressed IL-1β-induced TNF-α production by 66% and 50% at concentrations of 1 ㎍/ml and 5 ㎍/ml KPE, respectively. In addition, COX-2 protein expression was reduced by 26% and 34% compared to control levels. The preservation of chondrocyte-specific matrix proteins, aggrecan, and collagen type II, was notable, with aggrecan and mRNA levels maintained by 5% and 8%, and collagen II levels preserved by 62% and 47% at the same KPE concentrations. This preservation is likely due to the reduced expression of MMP1 and MMP13, enzymes responsible for matrix protein degradation. Overall, the current results suggest that KPE may protect chondrocytes from IL-1β-induced osteoarthritis by suppressing TNF-α production and COX-2 expression while preserving critical matrix proteins like aggrecan and collagen II by suppressing the expressions of their degrading enzymes (MMP-1 and MMP-13). Therefore, KPE holds promise as a candidate for developing functional foods aimed at reducing osteoarthritis.

• Journal of Distribution Research
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• v.15 no.3
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• pp.111-137
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• 2010

The basic purpose of this study is to investigate perceived quality and service personal value affecting the result of long-term relationship between service buyers and suppliers. This research presented a constructive model(perceived quality affecting the service personal value and the moderate effect of NFC) in the on off line and then propose the research model base on prior researches and studies about relationships among components of service. Data were gathered from respondents who visit at the education service market. For this study, Data were analyzed by AMOS 7.0. We integrate the literature on services marketing with researches on personal values and perceived quality. The SERPVAL scale presented here allows for the creation of a common ground for assessing service personal values, giving a clear understanding of the key value dimensions behind service choice and usage. It will lead to a focus of future research in services marketing, extending knowledge in the field and stimulating further empirical research on service personal values. At the managerial level, as a tool the SERPVAL scale should allow practitioners to evaluate and improve the value of a service, and consequently, to define strategies and actions to address services for customers based on their fundamental personal values. Through qualitative and empirical research, we find that the service quality construct conforms to the structure of a second-order factor model that ties service quality perceptions to distinct and actionable dimensions: outcome, interaction, and environmental quality. In turn, each has two subdimensions that define the basis of service quality perceptions. The authors further suggest that for each of these subdimensions to contribute to improved service quality perceptions, the quality received by consumers must be perceived to be reliable, responsive, and empathetic. Although the service personal value may be found in researches that explore individual values and their consequences for consumer behavior, there is no established operationalization of a SERPVAL scale. The inexistence of an established scale, duly adapted in order to understand and analyze personal values behind services usage, exposes the need of a measurement scale with such a purpose. This need has to be rooted, however, in a conceptualization of the construct being scaled. Service personal values can be defined as a customer's overall assessment of the use of a service based on the perception of what is achieved in terms of his own personal values. As consumer behaviors serve to show an individual's values, the use of a service can also be a way to fulfill and demonstrate consumers'personal values. In this sense, a service can provide more to the customer than its concrete and abstract attributes at both the attribute and the quality levels, and more than its functional consequences at the value level. Both values and services literatures agree, that personal value is the highest-level concept, followed by instrumental values, attitudes and finally by product attributes. Purchasing behaviors are agreed to be the end result of these concepts' interaction, with personal values taking a major role in the final decision process. From both consumers' and practitioners' perspectives, values are extremely relevant, as they are desirable goals that serve as guiding principles in people's lives. While building on previous research, we propose to assess service personal values through three broad groups of individual dimensions; at the self-oriented level, we use (1) service value to peaceful life (SVPL) and, at the social-oriented level, we use (2) service value to social recognition (SVSR), and (3) service value to social integration (SVSI). Service value to peaceful life is our first dimension. This dimension emerged as a combination of values coming from the RVS scale, a scale built specifically to assess general individual values. If a service promotes a pleasurable life, brings or improves tranquility, safety and harmony, then its user recognizes the value of this service. Generally, this service can improve the user's pleasure of life, since it protects or defends the consumer from threats to life or pressures on it. While building upon both the LOV scale, a scale built specifically to assess consumer values, and the RVS scale for individual values, we develop the other two dimensions: SVSR and SVSI. The roles of social recognition and social integration to improve service personal value have been seriously neglected. Social recognition derives its outcome utility from its predictive utility. When applying this underlying belief to our second dimension, SVSR, we assume that people use a service while taking into consideration the content of what is delivered. Individuals consider whether the service aids in gaining respect from others, social recognition and status, as well as whether it allows achieving a more fulfilled and stimulating life, which might then be revealed to others. People also tend to engage in behavior that receives social recognition and to avoid behavior that leads to social disapproval, and this contributes to an individual's social integration. This leads us to the third dimension, SVSI, which is based on the fact that if the consumer perceives that a service strengthens friendships, provides the possibility of becoming more integrated in the group, or promotes better relationships at the social, professional or family levels, then the service will contribute to social integration, and naturally the individual will recognize personal value in the service. Most of the research in business values deals with individual values. However, to our knowledge, no study has dealt with assessing overall personal values as well as their dimensions in a service context. Our final results show that the scales adapted from the Schwartz list were excluded. A possible explanation is that although Schwartz builds on Rokeach work in order to explore individual values, its dimensions might be especially focused on analyzing societal values. As we are looking for individual dimensions, this might explain why the values inspired by the Schwartz list were excluded from the model. The hierarchical structure of the final scale presented in this paper also presents theoretical implications. Although we cannot claim to definitively capture the dimensions of service personal values, we believe that we come close to capturing these overall evaluations because the second-order factor extracts the underlying commonality among dimensions. In addition to obtaining respondents' evaluations of the dimensions, the second-order factor model captures the common variance among these dimensions, reflecting the respondents' overall assessment of service personal values. Towards this fact, we expect that the service personal values conceptualization and measurement scale presented here contributes to both business values literature and the service marketing field, allowing for the delineation of strategies for adding value to services. This new scale also presents managerial implications. The SERPVAL dimensions give some guidance on how to better pursue a highly service-oriented business strategy. Indeed, the SERPVAL scale can be used for benchmarking purposes, as this scale can be used to identify whether or not a firms' marketing strategies are consistent with consumers' expectations. Managerial assessment of the personal values of a service might be extremely important because it allows managers to better understand what customers want or value. Thus, this scale allows us to identify what services are really valuable to the final consumer; providing knowledge for making choices regarding which services to include. Traditional approaches have focused their attention on service attributes (as quality) and service consequences(as service value), but personal values may be an important set of variables to be considered in understanding what attracts consumers to a certain service. By using the SERPVAL scale to assess the personal values associated with a services usage, managers may better understand the reasons behind services' usage, so that they may handle them more efficiently. While testing nomological validity, our empirical findings demonstrate that the three SERPVAL dimensions are positively and significantly associated with satisfaction. Additionally, while service value to social integration is related only with loyalty, service value to peaceful life is associated with both loyalty and repurchase intent. It is also interesting and surprising that service value to social recognition appears not to be significantly linked with loyalty and repurchase intent. A possible explanation is that no mobile service provider has yet emerged in the market as a luxury provider. All of the Portuguese providers are still trying to capture market share by means of low-end pricing. This research has implications for consumers as well. As more companies seek to build relationships with their customers, consumers are easily able to examine whether these relationships provide real value or not to their own lives. The selection of a strategy for a particular service depends on its customers' personal values. Being highly customer-oriented means having a strong commitment to customers, trying to create customer value and understanding customer needs. Enhancing service distinctiveness in order to provide a peaceful life, increase social recognition and gain a better social integration are all possible strategies that companies may pursue, but the one to pursue depends on the outstanding personal values held by the service customers. Data were gathered from 284 respondents in the korean discount store and online shopping mall market. This research proposed 3 hypotheses on 6 latent variables and tested through structural equation modeling. 6 alternative measurements were compared through statistical significance test of the 6 paths of research model and the overall fitting level of structural equation model. and the result was successful. and Perceived quality more positively influences service personal value when NFC is high than when no NFC is low in the off-line market. The results of the study indicate that service quality is properly modeled as an antecedent of service personal value. We consider the research and managerial implications of the study and its limitations. In sum, by knowing the dimensions a consumer takes into account when choosing a service, a better understanding of purchasing behaviors may be realized, guiding managers toward customers expectations. By defining strategies and actions that address potential problems with the service personal values, managers might ultimately influence their firm's performance. we expect to contribute to both business values and service marketing literatures through the development of the service personal value. At a time when marketing researchers are challenged to provide research with practical implications, it is also believed that this framework may be used by managers to pursue service-oriented business strategies while taking into consideration what customers value.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.71-84
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• 2013

Log data, which record the multitude of information created when operating computer systems, are utilized in many processes, from carrying out computer system inspection and process optimization to providing customized user optimization. In this paper, we propose a MongoDB-based unstructured log processing system in a cloud environment for processing the massive amount of log data of banks. Most of the log data generated during banking operations come from handling a client's business. Therefore, in order to gather, store, categorize, and analyze the log data generated while processing the client's business, a separate log data processing system needs to be established. However, the realization of flexible storage expansion functions for processing a massive amount of unstructured log data and executing a considerable number of functions to categorize and analyze the stored unstructured log data is difficult in existing computer environments. Thus, in this study, we use cloud computing technology to realize a cloud-based log data processing system for processing unstructured log data that are difficult to process using the existing computing infrastructure's analysis tools and management system. The proposed system uses the IaaS (Infrastructure as a Service) cloud environment to provide a flexible expansion of computing resources and includes the ability to flexibly expand resources such as storage space and memory under conditions such as extended storage or rapid increase in log data. Moreover, to overcome the processing limits of the existing analysis tool when a real-time analysis of the aggregated unstructured log data is required, the proposed system includes a Hadoop-based analysis module for quick and reliable parallel-distributed processing of the massive amount of log data. Furthermore, because the HDFS (Hadoop Distributed File System) stores data by generating copies of the block units of the aggregated log data, the proposed system offers automatic restore functions for the system to continually operate after it recovers from a malfunction. Finally, by establishing a distributed database using the NoSQL-based Mongo DB, the proposed system provides methods of effectively processing unstructured log data. Relational databases such as the MySQL databases have complex schemas that are inappropriate for processing unstructured log data. Further, strict schemas like those of relational databases cannot expand nodes in the case wherein the stored data are distributed to various nodes when the amount of data rapidly increases. NoSQL does not provide the complex computations that relational databases may provide but can easily expand the database through node dispersion when the amount of data increases rapidly; it is a non-relational database with an appropriate structure for processing unstructured data. The data models of the NoSQL are usually classified as Key-Value, column-oriented, and document-oriented types. Of these, the representative document-oriented data model, MongoDB, which has a free schema structure, is used in the proposed system. MongoDB is introduced to the proposed system because it makes it easy to process unstructured log data through a flexible schema structure, facilitates flexible node expansion when the amount of data is rapidly increasing, and provides an Auto-Sharding function that automatically expands storage. The proposed system is composed of a log collector module, a log graph generator module, a MongoDB module, a Hadoop-based analysis module, and a MySQL module. When the log data generated over the entire client business process of each bank are sent to the cloud server, the log collector module collects and classifies data according to the type of log data and distributes it to the MongoDB module and the MySQL module. The log graph generator module generates the results of the log analysis of the MongoDB module, Hadoop-based analysis module, and the MySQL module per analysis time and type of the aggregated log data, and provides them to the user through a web interface. Log data that require a real-time log data analysis are stored in the MySQL module and provided real-time by the log graph generator module. The aggregated log data per unit time are stored in the MongoDB module and plotted in a graph according to the user's various analysis conditions. The aggregated log data in the MongoDB module are parallel-distributed and processed by the Hadoop-based analysis module. A comparative evaluation is carried out against a log data processing system that uses only MySQL for inserting log data and estimating query performance; this evaluation proves the proposed system's superiority. Moreover, an optimal chunk size is confirmed through the log data insert performance evaluation of MongoDB for various chunk sizes.

• Tuberculosis and Respiratory Diseases
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• v.56 no.1
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• pp.51-66
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• 2004

Objectives : The matrix metalloproteinases (MMPs) that participate in the extracellular matrix metabolism play a important role in the progression of pulmonary fibrosis. The effects of the MMPs are regulated by several factors including Th-1 cytokines, $interferon-{\gamma}$ ($IFN-{\gamma}$). Up to now, $IFN-{\gamma}$ is known to inhibit pulmonary fibrosis, but little is known regarding the exact effect of $IFN-{\gamma}$ on the regulation of the MMPs. This study investigated the effects of $interferon-{\gamma}$ on the pulmonary fibrosis and the expression of the lung MMP-2,-9, TIMP-1,-2, and Th-2 cytokines in aa rat model of bleomycin induced pulmonary fibrosis. Materials and methods : Male, specific pathogen-free Sprague-Dawley rats were subjected to an intratracheal bleomycin instillation. The rats were randomized to a saline control, a bleomycin treated, and a bleomycin+$IFN-{\gamma}$ treated group. The bleomycin+$IFN-{\gamma}$ treated group was subjected to an intramuscular injection of $IFN-{\gamma}$ for 14 days. At 3, 7, 14, and 28 days after the bleomycin instillation, the rats were sacrificed and the lungs were harvested. In order to evaluate the effects of the $IFN-{\gamma}$ on lung fibrosis and inflammation, the lung hydroxyproline content, inflammation and fibrosis score were measured. Western blotting, zymography and reverse zymography were performed at 3, 7, 14, 28 days after bleomycin instillation in order to evaluate the MMP-2,-9, and TIMP-1,-2 expression level. ELISA was performed to determine the IL-4 and IL-13 level in a lung homogenate. Results : 1. 7 days after bleomycin instillation, inflammatory changes were more severe in the bleomycin+$IFN-{\gamma}$ group than the bleomycin group (bleomycin group : bleomycin+$IFN-{\gamma}$ group=$2.08{\pm}0.15:2.74{\pm}0.29$, P<0.05), but 28 days after bleomycin instillation, lung fibrosis was significantly reduced as a result of the $IFN-{\gamma}$ treatment (bleomycin group : bleomycin+$IFN-{\gamma}$ group=$3.94{\pm}0.43:2.64{\pm}0.13$, P<0.05). 2. 28 days after bleomycin instillation, the lung hydroxyproline content was significantly reduced as a result of $IFN-{\gamma}$ treatment (bleomycin group : bleomycin+$IFN-{\gamma}$ group=$294.04{\pm}31.73{\mu}g/g:194.92{\pm}15.51{\mu}g/g$, P<0.05). 3. Western blotting showed that the MMP-2 level was increased as a result of the bleomycin instillation and highest in the 14 days after bleomycin instillation. 4. In zymography, the active forms of MMP-2 were significantly increased as a result of the $IFN-{\gamma}$ treatment 3 days after the bleomycin instillation, bleomycin+$IFN-{\gamma}$ group (bleomycin group : bleomycin+$IFN-{\gamma}$ group=$209.63{\pm}7.60%:407.66{\pm}85.34%$, P<0.05), but 14 days after the bleomycin instillation, the active forms of MMP-2 were significantly reduced as a result of the $IFN-{\gamma}$ treatment (bleomycin group : bleomycin+$IFN-{\gamma}$ group=$159.36{\pm}20.93%:97.23{\pm}12.50%$, P<0.05). 5. The IL-4 levels were lower in the bleomycin and bleomycin+$IFN-{\gamma}$ groups but this was not significant, and the IL-13 levels showed no difference between the experiment groups. Conclusion : The author found that lung inflammation was increased in the early period but the pulmonary fibrosis was inhibited in the late stage as a result of $IFN-{\gamma}$. The inhibition of pulmonary fibrosis by $IFN-{\gamma}$ appeared to be associated with the inhibition of MMP-2 activation by $IFN-{\gamma}$. Further studies on the mechanism of the regulation of MMP-2 activation and the effects of MMP-2 activation on pulmonary fibrosis is warranted in the future.

• 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.

• Investigative Magnetic Resonance Imaging
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• v.8 no.2
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• pp.79-85
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• 2004

Purpose : To evaluate the usefulness and reproducibility of $^1H$ MRS in different 1.5 T MR machines with different coils to compare the SNR, scan time and the spectral patterns in different brain regions in normal volunteers. Materials and Methods : Localized $^1H$ MR spectroscopy ($^1H$ MRS) was performed in a total of 10 normal volunteers (age; 20-45 years) with spectral parameters adjusted by the autoprescan routine (PROBE package). In all volunteers, MRS was performed in a three times using conventional MRS (Signa Horizon) with 1 channel coil and upgraded MRS (Echospeed plus with EXCITE) with both 1 channel and 8 channel coil. Using these three different machines and coils, SNRs of the spectra in both phantom and volunteers and (pre)scan time of MRS were compared. Two regions of the human brain (basal ganglia and deep white matter) were examined and relative metabolite ratios (NAA/Cr, Cho/Cr, and mI/Cr ratios) were measured in all volunteers. For all spectra, a STEAM localization sequence with three-pulse CHESS $H_2O$ suppression was used, with the following acquisition parameters: TR=3.0/2.0 sec, TE=30 msec, TM=13.7 msec, SW=2500 Hz, SI=2048 pts, AVG : 64/128, and NEX=2/8 (Signa/Echospeed). Results : The SNR was about over $30\%$ higher in Echospeed machine and time for prescan and scan was almost same in different machines and coils. Reliable spectra were obtained on both MRS systems and there were no significant differences in spectral patterns and relative metabolite ratios in two brain regions (p>0.05). Conclusion : Both conventional and new MRI systems are highly reliable and reproducible for $^1H$ MR spectroscopic examinations in human brains and there are no significant differences in applications for $^1H$ MRS between two different MRI systems.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.169-196
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• 2017

The fourth industrial revolution represents a revolutionary change in the business environment and its ecosystem, which is a fusion of Information Technology (IT) and other industries. In line with these recent changes, the Ministry of Employment and Labor of South Korea announced 'the Fourth Industrial Revolution Leader Training Program,' which includes five key support areas such as (1) smart manufacturing, (2) Internet of Things (IoT), (3) big data including Artificial Intelligence (AI), (4) information security, and (5) bio innovation. Based on this program, we can get a glimpse of the South Korean government's efforts and willingness to emit leading human resource with advanced IT knowledge in various fusion technology-related and newly emerging industries. On the other hand, in order to nurture excellent IT manpower in preparation for the fourth industrial revolution, the role of educational institutions capable of providing high quality IT education services is most of importance. However, these days, most IT educational institutions have had difficulties in providing customized IT education services that meet the needs of consumers (i.e., learners), without breaking away from the traditional framework of providing supplier-oriented education services. From previous studies, it has been found that the provision of customized education services centered on learners leads to high satisfaction of learners, and that higher satisfaction increases not only task performance and the possibility of business application but also learners' recommendation intention. However, since research has not yet been conducted in a comprehensive way that consider both antecedent and consequent factors of the learner's satisfaction, more empirical research on this is highly desirable. With the advent of the fourth industrial revolution, a rising interest in various convergence technologies utilizing information technology (IT) has brought with the growing realization of the important role played by IT-related education services. However, research on the role of IT education service quality in the context of IT education is relatively scarce in spite of the fact that research on general education service quality and satisfaction has been actively conducted in various contexts. In this study, therefore, the five dimensions of IT education service quality (i.e., tangibles, reliability, responsiveness, assurance, and empathy) are derived from the context of IT education, based on the SERVPERF model and related previous studies. In addition, the effects of these detailed IT education service quality factors on learners' educational satisfaction and their work application/recommendation intentions are examined. Furthermore, the moderating roles of learner position (i.e., practitioner group vs. manager group) and participation motivation (i.e., voluntary participation vs. involuntary participation) in relationships between IT education service quality factors and learners' educational satisfaction, work application intention, and recommendation intention are also investigated. In an analysis using the structural equation model (SEM) technique based on a questionnaire given to 203 participants of IT education programs in an 'M' IT educational institution in Seoul, South Korea, tangibles, reliability, and assurance were found to have a significant effect on educational satisfaction. This educational satisfaction was found to have a significant effect on both work application intention and recommendation intention. Moreover, it was discovered that learner position and participation motivation have a partial moderating impact on the relationship between IT education service quality factors and educational satisfaction. This study holds academic implications in that it is one of the first studies to apply the SERVPERF model (rather than the SERVQUAL model, which has been widely adopted by prior studies) is to demonstrate the influence of IT education service quality on learners' educational satisfaction, work application intention, and recommendation intention in an IT education environment. The results of this study are expected to provide practical guidance for IT education service providers who wish to enhance learners' educational satisfaction and service management efficiency.

• Tuberculosis and Respiratory Diseases
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• v.48 no.4
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• pp.478-486
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• 2000

Background : In acute lung injury, alveolar macrophages play a pivotal role in the inflammatory process during the initiation phase and in the reconstruction and fibrosis process during the later phase. Recently, it has been proven that alveolar macrophages are constituted by morphologically, biochemically and immunologically heterogenous cell subpopulations. The possibility of alterations to these characteristics of the alveolar macrophage population during lung disease has been raised. To investigate such a possibility a hyperoxic rat lung model was made to check the distributional and morphological changes of rat alveolar macrophage subpopulation in acute hyperoxic lung injury. Method : Alveolar macrophage were lavaged from normal and hyperoxic lung injury rats and separated by discontinuous gradients of percoll. After cell counts of each density fraction were accessed, the morphomeric analysis of alveolar macrophages was performed on cytocentrifuged preparations by transmission electron micrograph. Result : 1. The total alveolar macrophage cell count significantly increased up to 24 hours after hyperoxic challenge (normal control group $171.6{\pm}24.1{\times}10^5$, 12 hour group $194.8{\pm}17.9{\times}10^5$, 24 hour group $207.6{\pm}27.1{\times}10^5$, p<0.05). oHoHH However the 48 hour group ($200.0{\pm}77.8{\times}10^5$) did not show a significant difference. 2. Alveolar septal thickness significantly increased up to 24 hours after hyperoxic challenge(normal control group $0.7{\pm}0.2{\mu}m$, 12 hour group $1.5{\pm}0.4{\mu}m$, 24 hour group $2.3{\pm}0.4{\mu}m$, p<0.05). However the 48 hour group did not show further change ($2.5{\pm}0.4{\mu}m$). Number of interstitial macrophage markedly increased at 24 hour group. 3. Hypodense fraction(fraction 1 and fraction 2) of alveolar macrophage showed a significant increase following hyperoxic challenge ($\beta=0.379$.$\beta=0.694$. p<0.05) ; however, fraction 3 was rather decreased following the hyperoxic challenge($\beta=0.815$. p<0.05), and fraction 4 showed an irregular pattern. 4. Electron microscopic observation of alveolar macrophage from each fraction revealed considerable morphologic heterogeneity. Cells of the most dense subfraction(fraction 4) were small, round, and typically highly ruffled with small membrane pseudopods. Cells of the least dense fraction (fraction 1) were large and showed irregular eccentric nucleus and high number of heterogenous inclusions. Conclusion : In conclusion, these results suggest that specific hypodense alveolar macrophage subpopulation may play a an important role in an acute hyperoxic lung injury model But further study, including biochemical and immunological function of these subpopulations, is needed.