• 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.

• Journal of the Korean GEO-environmental Society
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• v.13 no.12
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• pp.17-25
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• 2012

In this study, dielectrical constant of the ground was measured using TDR method and correlated with water contents and density of ground. In order to evaluate the applicability as a cavity exploration, model experiments were carried out to analyze the effects of cavity size on the dielectrical constant. Test result indicated that dielectrical constant of the ground tended to linearly increase with the increase in water contents and density, which can be represented in a certain relational expression. Also, the dielectrical constant of ground varied sensitively with the cavity size of ground. The results conclude that the dielectrical constant, water contents and density of the ground proved to have a correlation among them, and the dielectrical constant is expected to be a basic data on cavity exploration.

• Journal of the Korean Society of Costume
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• v.63 no.3
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• pp.46-60
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• 2013

With a goal of establishing a marketing strategy which allows businesses to hold a dominant position in beauty service industry, this study has attempted to investigate causal relations among behavioral intentions by customer satisfaction once service recovery strategy is recovered depending on customers' emotional responses against service failure. In order to provide relevant data to make correct decisions during management and marketing planning so that better customer satisfaction can be achieved in the beauty service industry, the results of the previous studies on service failure and recovery strategy in the beauty service industry have been examined. Then after selecting i) the efforts to recover service failure, ii) satisfaction after recovery and iii) behavioral intention after satisfaction as causal variables, the relation among these variables were verified using a structural equation model. As a result, an appropriate recovery strategy which is developed after service failure makes customers have positive behavioral intentions when customer satisfaction is achieved just as described in previous studies. Furthermore, it is a critical fact which helps businesses keep their customers in a mature market, where it is hard to attract new customers and create long-term profit. This study empirically supports information on how service failure and related variables occur in the beauty service industry. It is significant in that it has helped beauty service providers build service recovery-related strategies.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.113-121
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• 2020

Multi-criteria stock selection is a critical issue for effective investment since the improper stock investment might cause many problems affecting investors negatively. Investors need a range of financial indicators while they are choosing the optimal set of stocks to invest. This study aims to rank the stock of agriculture companies indexed on the Vietnam Stock Exchange Market. The data of 13 agriculture companies during the 2016-2019 periods was analyzed by analytical hierarchy process (AHP) integrated with grey relational analysis (GRA), multi-objective optimization ratio analysis (MOORA), and technique for order performance by similarity to ideal solution (TOPSIS). The AHP method is employed to determine the weights of the proposed financial ratios, and GRA, TOPSIS, and MOORA approaches are used to obtain final ranking. The results indicated that HSL is the top stock with the highest rank and GRA, MOORA, and TOPSIS rankings have strong correlation values between 0.78-1. The findings suggest that the integrated model could be implemented effectively to specific analysis of industries such as oil and gas, textiles, food, and electronics in future research. Further, other techniques like COPRAS, KEMIRA, and EDAS could be employed to evaluate the financial performance of other companies to solve investment problems.

• Asia pacific journal of information systems
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• v.8 no.1
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• pp.43-64
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• 1998

Cooperative query answering is a research effort to develop a fault-tolerant and intelligent database system using the semantic knowledge base constructed from the underlying database. Such knowledge base has two aspects of usage. One is supporting the cooperative query answering process for providing both an exact answer and neighborhood information relevant to a query. The other is supporting ongoing maintenance of the knowledge base for accommodating the changes in the knowledge content and database usage purpose. Existing studies have mostly focused on the cooperative query answering process but paid little attention to the dynamic knowledge base maintenance. This paper proposes a multi-level knowledge representation framework called Knowledge Abstraction Hierarchy(KAH) that can not only support cooperative query answering but also permit dynamic knowledge maintenance, On the basis of the KAH, a knowledge abstraction database is constructed on the relational data model and accommodates diverse knowledge maintenance needs and flexibly facilitates cooperative query answering. In terms of the knowledge maintenance, database operations are discussed for the cases where either the internal contents for a given KAH change or the structures of the KAH itself change. In terms of cooperative query answering, four types of vague queries are discussed, including approximate selection, approximate join, conceptual selection, and conceptual join. A prototype system has been implemented at KAIST and is being tested with a personnel database system to demonstrate the usefulness and practicality of the knowledge abstraction database in ordinary database application systems.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.855-863
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• 2020

The purpose of this study is to investigate the impacts of two different kinds of interactivity, such as user-to-user and user-to-media interaction, on the relationship between SNS motivation and online word of mouth (WOM). An online survey was conducted with SNS users in Korea. Using the convenience-sampling method, 300 surveys were collected and 295 were used in the actual analysis after excluding data with careless responses or missing values. Hypotheses were tested using Structure Equation Model (SEM) and path analysis by using AMOS22. The results indicate that four different SNS motivations (self-expression, relational, fun, and browsing motivation) have a partially significant positive effect on perceived user-to-user and user-to-media interaction in SNS. Although both user-to-user interactivity and user-to-media interactivity were found to have a significant effect on online word of mouth, by comparing the standardized regression coefficients in these relationships, it was found that user-to-user interactivity has a greater effect on online WOM than user-to-media interactivity. These results show that the motivated SNS users want to express their desire to communicate with other users in contrast than their desire to learn media functions when motivated SNS users reveal their personalities, knowledge, and abilities. Theoretical and managerial implications are discussed.

• Korean Journal of Child Studies
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• v.9 no.2
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• pp.133-156
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• 1988

This study investigated developmental change with reference to continuity theory in the acquisition of concepts of kin relation, task difficulty with reference to cognitive complexity, and interrelationships in the performance of cognitive tasks of kinship concepts with reference to cognitive parallelism. The subjects consisted of 6-, 8-, 10, and 12-year-old randomly selected children attending kindergartens or elementary schools in Seoul. The schools were located in various residental areas regarded as either middle or lower class. The 81 boys and 80 girls participated in 3 experiments on classification, seriation, and grouping. The instrument for the classification, seriation, and grouping tasks was composed of 10 10cm black on white line drawings of the head and upper torso area of persons in kin relationship. The data was analyzed with MANOVA. A significant age effect was found in the 3 quasi- experiments. There were significant effects on task difficulty. The biosocial power distribution indirectly influenced children's acquisition of kin relational concepts; that is, children performed better in male-kin than in female-kin tasks. There was a high correlation in performance between the 3 cognitive tasks. These findings support the continuity theory (except for seriation), a model which arranges kin-names in order of cognitive load, the centric status of men in society, and the theory of cognitive developmental parallelism.

• The Journal of Information Systems
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• v.25 no.1
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• pp.201-223
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• 2016

Purpose As social network games (SNG) enjoy rapid growth in the market and become a major sector of the gaming industry, it is of great interest to examine the how users continuously use SNG. In SNG, the users' social interaction is the most prominent advantage of the social network, as well as the entertainment afforded by the game. This study explores the relationship between altruism, which is considered the most prominent characteristic of SNS, and the continuance usage intention, as well as the moderating role of social capital. Based on social capital theory and organizational citizenship behavior, this research model considers social bonding and bridging that are divided by social capital. Design/methodology/approach An AMOS analysis based on survey data from 223 SNG users indicated that SNG with greater altruism enhance social capital (social bonding, social bridging), which is related to the user's satisfaction and the continuance intention of SNG. Findings Social bonding is positively related to the user's satisfaction with SNG. In other words, social bridging positively affects the continuous usage intention of SNG. These findings help managers in developing and implementing altruistic relationships and social capital for continuous usage of SNG.

• Journal of the Society of Naval Architects of Korea
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• v.31 no.3
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• pp.38-46
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• 1994

The role of CIMS(Computer Integrated Manufacturing Systems) is to integrate various applications throughout a product's life cycle. STEP is an international effort to standardize information models and interfaces so that independently developed applications can be easily integrated. A prototype for the Ship CIMS is built using STEP. In this prototype, the information model defined by EXPRESS is translated into database schemas. In this paper, we explain the operation of this prototype using the examples from two application programs, i.e., the Block Division System and the Erection System which are used for the process planning of ship manufacturing. As an example. Real data stored in a relational database system(Oracle) is presented in this paper.

• Journal of Families and Better Life
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• v.31 no.1
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• pp.129-147
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• 2013

The primary focus of the study assesses how individual spouses' and their partners' marital adjustment influence their own and their mental health. The study also examines whether this influence was mediated by the relationship with their adult-children. Data were collected from 271 dyads of elderly couples by using a self-report questionnaire. Marital adjustment was measured in terms of intimacy and comparison level of marriage. Mental health was measured in terms of depressive mood, anxiety, and somatization. The Actor-Partner Interdependence Model (APIM) analysis revealed that marital adjustment was positively associated with one's own mental health and with one's own relationship with their adult-children, but not with their partner's. On the other hand, the relationship with adult-children was positively associated with one's own and with their partner's mental health. Furthermore, analysis of the mediating model using APIM indicated that marital adjustment through one's own adult-children relationship had direct and indirect effects on one's own mental health. It is interesting to note that the wives' mental health were directly influenced by their partners' relationship with adult-children. However, the effect of the husbands' mental health was not significant. These findings highlight dyadic interdependence among spouses' perceptions of marital and adult-children relationship with their mental health. The results suggest implications for educators and clinicians working with elderly couples to improve their psychological and relational health.