• 한국전산유체공학회:학술대회논문집
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• 2003.08a
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• pp.82-87
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• 2003

Post-processing programs play an important role in the CFD data visualization and analysis. A variety of post-processing softwares have been developed and are being used in the CFD community. Developing a good quality of post-processing program requires dedication and efforts. In this paper an experience obtained through previous studies and developing post-processing programs are introduced which includes data structure and visualization algorithms.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.301-312
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• 2017

Quality evaluation and control represent increasingly important concerns for construction quality management. There is an evident need for a standard data model to be used as the basis for computer-aided quality management. This study focuses on how to realize evaluation of construction quality based on BIM and database technology. In this paper, the reinforced concrete main structure is taken as an example, and the BP neural network evaluation model is established by inquiring current construction quality acceptance specification and evaluation standard. Furthermore, IFC standard is extended to integrate quality evaluation information and realize the mapping of evaluation information in BIM model, contributing to the visualization and transfer sharing of evaluation information. Furthermore, the conceptual entity model is designed to build quality evaluation database, and this paper select MySQL workbench system to achieve the establishment of the database. This study is organized to realize the requirement of visualization and data integration on construction quality evaluation which makes it more effective, convenient, intuitive, easy to find quality problems and provide more comprehensive and reliable data for the quality management of construction enterprises and official construction administratiors.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.1
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• pp.13-19
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• 2019

The accuracy of machine learning is greatly affected by amount of learning data and quality of data. Collecting existing Web-based learning data has danger that data unrelated to actual learning can be collected, and it is impossible to secure data transparency. In this paper, we propose a method for collecting data directly in parallel by blocks in a block - chain structure, and comparing the data collected by each block with data in other blocks to select only good data. In the proposed system, each block shares data with each other through a chain of blocks, utilizes the All-reduce structure of Parallel-SGD to select only good quality data through comparison with other block data to construct a learning data set. Also, in order to verify the performance of the proposed architecture, we verify that the original image is only good data among the modulated images using the existing benchmark data set.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.1848-1852
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• 2008

Maintenance of quality of the compaction is accomplished with the plate load test and density management in roadbed. With the different structure differently the quality of roadbed evaluates indirectly as density and bearing capacity. Control of quality of the compaction very importance but the maintenance of quality is managed still so far with the paper. Recognizes the importance of maintenance of quality from the present paper consequently, and develops a data base one maintenance of quality system with hereafter is expected with the fact that the big help will become in DATA BASE system roadbed plan which is continuous and maintenance of quality.

• The Journal of Society for e-Business Studies
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• v.18 no.4
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• pp.83-105
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• 2013

There are two ways to assess data quality : measurement of data itself and assessment of data quality management process. Recently maturity assessment of data quality management process is used to ensure and certify the data quality level of an organization. Following this trend, the paper presents the process reference model which is needed to assess data quality management process maturity. First, the overview of assessment model for data quality management process maturity is presented. Second, the process reference model that can be used to assess process maturity is proposed. The structure of process reference model and its detail processes are developed based on the process derivation approach, basic principles of data quality management and the basic concept of process reference model in SPICE. Furthermore, characteristics of the proposed model are described compared with ISO 8000-150 processes.

• Journal of Korean Society for Quality Management
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• v.40 no.3
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• pp.337-346
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• 2012

Purpose: A Control chart is one of the important statistical process control tools that can improve processes by reducing variability and defects. Methods: In the present study, we propose the local $T^2$ multivariate control chart that can efficiently detect abnormal observations by considering the local pattern of the in-control observations. Results: A simulation study has been conducted to examine the property of the proposed control chart and compare it with existing multivariate control charts. Conclusion: The results demonstrate the usefulness and effectiveness of the proposed control chart.

• 한국정보디스플레이학회:학술대회논문집
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• 2000.01a
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• pp.13-14
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• 2000

21.6" a-Si:H TFT array for direct conversion X-ray detector with 2480 by 3072 pixel is successfully developed. To obtain good X-ray image quality, novel structure, storage on BCB structure, is proposed. The structure reduces the parasitic capacitance of data line, one of the main sources of signal noise. Also, the structure shows higher failure resistance against defects than that of the old design.

• Asian Journal of Innovation and Policy
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• v.9 no.1
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• pp.12-35
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• 2020

Quality performance information has been regarded as a significant step toward managing public performance. Although a correlation between the quality of information and its actual usage among managers in high-accountability policy areas has been found, quality performance information has not been properly provided to practitioners. This study takes an Institutional Analysis and Development approach to assess an appropriate institutional framework that facilitates state agencies and academics to coproduce this information. Based on a conceptual framework, we analyze a public information system of the Workforce Data Quality Initiative in Ohio and carry out a content analysis with NVIVO. It is found that arrangements that can manage the incentive dynamic in this process may help to align heterogeneous stakeholders in a mutually supportive fashion. Also, the research agenda and information resulted from being coproduced for management and academic purposes, simultaneously. This use of administrative data sheds light on how quality performance information can be coproduced under an appropriate institutional arrangement between administration and research communities. It is suggested that accessibility to the information system among various stakeholders should be improved.

• 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.

• Journal of Distribution Science
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• v.11 no.12
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• pp.51-62
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• 2013

Purpose - A pre-study on service quality-based customer value is conducted with the path structure (perceived value of service quality→customer satisfaction→behavior intention) based on the hierarchical model of service quality including interaction and outcome quality, physical environment quality and the SERVQUAL model of process quality, namely, reliability, responsiveness, assurance, empathy, and tangibles. In addition, customer value in the service industry is studied by dividing into the two-way structure of utilitarian and emotional values. This study classifies customer values of family restaurants through the customer value model based on the 4×4 matrix needs system of Jeon and Kim (2009). It illustrates the path structure of customer value→customer satisfaction→behavior intention targeting college students in order to generalize the customer value system of family restaurants. Research design, data, and methodology - This study established seven hypotheses based on the relationship between each type of customer value (food quality, convenience, social, emotional, interior quality, service encounter, and purchasing) and customer satisfaction, and the relationship between customer satisfaction and behavior intention. The study data were collected from students in the Department of Business and Tourism at Kimpo University. In all, 294 survey papers were returned of the 300 distributed: 253 pieces were used in the final analysis excluding 41 with insufficient and less effective answers. For statistical analysis, the statistics software package SPSS 15.0 was used. Results - The results of the analysis are as follows: first, the customer values of family restaurants are classified by seven customer values: goods quality value, emotional value, convenience value, social value, purchasing value, service encounter value, and inner quality value. Second, emotional value, purchasing value, service encounter value, and inner quality value had positive impact on customer satisfaction. In particular, purchasing value through being included in functional value was not classified in the previous study; however, this study could classify and generalize this value in a new way. Finally, customer satisfaction had a positive impact on behavior intention. This showed that college students had behavior intention - repurchase intention and word-of-mouth - because they could be content with the food items on the menu and the service provided by employees. Conclusions - The main points based on the above-mentioned results are as follows. This study with college students as study subjects could be classified into four dimensions, namely, generic value, usage value, purchasing value, and physical value and seven sub-dimensions on customer values of family restaurants based on a 4×4 matrix needs system. Then, to confirm its generalization, the path structure of customer value→customer satisfaction→behavior intention was verified. While existing pre-studies used simplified values by classifying restaurant values largely as utilitarian value and hedonic value, this study classified various forms of customer value, and that customer value especially could be expanded by adding purchasing value. As a result, it is shown that marketers need to diversify their customer services because this study proved that customer values can be classified in various ways based on customer needs.