• Journal of the Semiconductor & Display Technology
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• v.20 no.2
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• pp.121-125
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• 2021

Cloud service has the characteristic that it must be always available and that it must be able to respond immediately to user requests. This study suggests a method for constructing a proactive and autonomous quality and performance management system to meet these characteristics of cloud services. To this end, we identify quantitative measurement factors for cloud service quality and performance management, define a structure for applying a time series framework to cloud service application quality and performance management for proactive management, and then use big data and artificial intelligence for autonomous management. The flow of data processing and the configuration and flow of big data and artificial intelligence platforms were defined to combine intelligent technologies. In addition, the effectiveness was confirmed by applying it to the cloud service quality and performance management system through a case study. Using the methodology presented in this study, it is possible to improve the service management system that has been managed artificially and retrospectively through various convergence. However, since it requires the collection, processing, and processing of various types of data, it also has limitations in that data standardization must be prioritized in each technology and industry.

• The Journal of Economics, Marketing and Management
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• v.5 no.2
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• pp.1-9
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• 2017

This study has reviewed the "A survey on the relation between the employees' viewpoint with knowledge management and cultural intelligence among the employees working in Social Security Organization of Ardabil". The present study is functional in terms of objective and the method is descriptive and survey. This has asked the others' ideas and viewpoints concerning a specific subject and has analyzed them. About the nature and the method used, the present research is of correlation research. The population applied in this research includes all employees working in Social Security Organization of Ardabil consisting of 400. The method used for sampling is simple random sampling. To collect the information in the first step of the research the library method has been used. In this research the data has been collected through standard questionnaires. Then, via descriptive and inferential statistics the research data has been characterized and regarding the spatial scaling of the measurement to test the hypothesis the, correlation analysis of Pearson has been used and also to specify the reliability of the questionnaire the Chronbach's Alpha has been taken in use and the SPSS software to analyze the data also. The findings resulted from the study showed that there is a significant relation between the factors concerning employees' efficiency with knowledge management and the cultural intelligence and all hypotheses was confirmed.

• Korean Management Science Review
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• v.12 no.2
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• pp.31-42
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• 1995

The ordering method is used to reduce the fill-ins in interior point methods. In ordering, the data structure plays an important role. In this paper, first, we compare the efficiency and the memory storage requirement of the quotient graph structure and the clique storage. Next, we propose a method of reducing the number of cliques and a data structure for clique storage. Finally, we apply a method of merging rows and absorbing cliques and show the experimental results.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.3
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• pp.69-78
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• 2019

The amount of data is increasing significantly as information and communication technology advances, mobile, cloud computing, the Internet of Things and social network services become commonplace. As the data grows exponentially, there is a growing demand for services that recommend the information that users want from large amounts of data. Collaborative filtering method is commonly used in information recommendation methods. One of the problems with collaborative filtering-based recommendation method is the cold start problem. In this paper, we propose a method to improve the cold start problem. That is, it solves the cold start problem by mapping the item evaluation data that does not exist to the initial user to the automatically generated data from the mobile app. We describe the main contents of the proposed method and explain the proposed method through the book recommendation scenario. We show the superiority of the proposed method through comparison with existing methods.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.4
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• pp.75-84
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• 2014

In this paper, we dealt with feature selection problem of large-scale and high-dimensional biological data such as omics data. For this problem, most of the previous approaches used simple score function to reduce the number of original variables and selected features from the small number of remained variables. In the case of methods that do not rely on filtering techniques, they do not consider the interactions between the variables, or generate approximate solutions to the simplified problem. Unlike them, by combining set covering and clustering techniques, we developed a new method that could deal with total number of variables and consider the combinatorial effects of variables for selecting good features. To demonstrate the efficacy and effectiveness of the method, we downloaded gene expression datasets from TCGA (The Cancer Genome Atlas) and compared our method with other algorithms including WEKA embeded feature selection algorithms. In the experimental results, we showed that our method could select high quality features for constructing more accurate classifiers than other feature selection algorithms.

• Korean Management Science Review
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• v.22 no.2
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• pp.1-12
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• 2005

New method has been widely used for teaching Management Science since the mid of 1990s. The new teaching method is distinguished from traditional method in several aspects. The mowt distintion of the new method is that Excel based approach is used in order to model and analyze quantitative problems. Due to the introduction of Excel based teaching method model formulation and interpretation is more emphasized than algorithms. By using this new method students are expected to be more interested in Management Science class and easily use several Management Science techniques in real world problems. Though Excel based teaching method has become more prevalent, there exist no empirical research to analyze the effectiveness of Excel based teaching method. This paper will empirically analyze how effective Excel based teaching method is. For this purpose survey data are collected fro professors teaching Management Science and analyzed by using t-test.

• Korean Management Science Review
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• v.29 no.2
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• pp.79-90
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• 2012

Focusing on the rapid market penetration of smart phones, the importance of LBS (Location Based Service) is drastically increased. However, traditional GPS method has critical weakness caused by limited availability, such as indoor environment. WPS is newly attractive method as a widely applicable positioning method. In WPS, RSSI (Received Signal Strength Indication) data of all Wi-Fi APs (Access Point) are measured and stored into a huge database. The stored RSSI data in database make single radio fingerprint map. By the radio fingerprint map, we can estimate the actual position of target point. The essential factor of radio fingerprint database is data integrity of RSSI. Because of millions of APs in urban area, RSSI measurement data are seriously contaminated. Therefore, we present the unified filtering method for RSSI measurement data. As the results of filtering, we can show the effectiveness of suggested method in practical positioning system of mobile operator.

• Journal of Korean Society for Quality Management
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• v.32 no.4
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• pp.265-273
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• 2004

We got the growth distance curve by spline smoothing method with observed marketing data and the growth velocity curve by the derivation of the growth distance curve. Using this growth velocity curve, we defined the several characteristic points which describe the variation of marketing data. In this paper, to specify several patterns of marketing data, we suggested characteristic function by using these characteristic points. In addition, we applied characteristic function to the seventeen brands of electric home products data.

• Journal of Korea Multimedia Society
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• v.4 no.6
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• pp.543-553
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• 2001

In this paper, we proposed management strategy of medical image data in order to solve the problem in traditional medical images migration method. As management strategy of medical image data we proposed EAT(Expanded Average Transaction time) data migration method and data storing method based on temporal interrelation. In EAT data migration strategy, we define the dividing criterion which distinguish entity versions to be stored in each storage and also define entity versions to be stored in each storage. We defined degree of overlap and degree of difference for any two entity versions, and integrated those values and described method which place entity versions to storage. In order to compare the number of cluster references when we change rate of temporal queries, the number of cluster references of proposed method is smaller than that of traditional method.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.1
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• pp.61-71
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• 2014

Social networking services have changed the way people communicate. Rapid growth of information generated by social networking services requires effective search methods to give useful results. Over the last decade, social search methods have rapidly evolved. Traditional techniques become unqualified because they ignore social relation data. Existing social recommendation approaches consider social network structure, but social context has not been fully considered. Especially, the friend recommendation is an important feature of SNSs. People tend to trust the opinions of friends they know rather than the opinions of strangers. In this paper, we propose a levelized data processing method for social search in ubiquitous environment. We study previous researches about social search methods in ubiquitous environment. Our method is a new paradigm of levelelized data processing method which can utilize information in social networks, using location and friendship weight. Several experiments are performed and the results verify that the proposed method's performance is better than other existing method.