• Journal of Korean Society on Water Environment
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• v.25 no.3
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• pp.386-393
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• 2009

This study was carried out to assess water quality and to introduce the management measures for water quality improvement with the collected data from 87 agricultural reservoirs in Han river watershed. According to the water quality criteria (WQC) for lake based on the COD, TP, TN and chl.a concentration, 18, 16, 4 and 19 of 87 reservoirs exceed class IV, respectively. Based on the trophic state index (TSI) with chl.a concentration, 51 of selected reservoirs appeared to be eutrophic. Phosphorus was limiting nutrient on algal growth in 58 reservoirs. TP, chl.a and COD concentration in 23 of 49 agricultural reservoirs with chl.a concentration ${\geq}25{\mu}g/L$ and eutrophic exceed class IV by WQC. Also, the mean depth in 21 of 23 reservoirs was below 5m. Our results suggest that advanced wastewater treatment and crop land control in watershed of reservoirs with TP concentration ${\geq}0.1mg/L$ would be a effective tool to improve water quality. Dredging would to be effective measure in reservoirs with mean depth < 5 m and relatively old age. In reservoirs with chl.a concentration ${\geq}50{\mu}g/L$, application of technique such dissolved air flotation (DAF) and P inactivation be effective to improve water quality by removing particulate matters in water column. The management measure to control inflow such as sedimentation basin, Pre-dam and diversion would to be application in reservoirs with shallow depth, while large watershed and surface area.

• Korean Journal of Construction Engineering and Management
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• v.14 no.5
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• pp.131-143
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• 2013

There is the difference of criteria to apply guidelines among the project participants and to depend on the purpose of utilizing BIM models, although modeling criteria are basically provided through BIM guidelines. Therefore, it is quite important to check compliance with guidelines to raise quality of the BIM model. But Quality Checking (QC) items and method for BIM model modeled in accordance with guidelines is not provided. This study suggested QC items and Rule Specifications(RS) for automatic QC. First of all, QC items were derived by analyzing domestic BIM guidelines and a process for structuring natural language is conducted by utilizing flowchart and pseudocode. So, by combining them, RS was suggested. Finally, RS-based case study was conducted by implementing automatic QC process with solibri model checker$^{TM}$. This study will contribute to the improvement of design quality and completeness of BIM model including huge data of 3 dimension. Furthermore, it is necessary to develop BIM guidelines according to the use case and to provide detailed process and standard for QC of BIM model.

• International Journal of Knowledge Content Development & Technology
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• v.10 no.1
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• pp.7-20
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• 2020

For research data to be shared without legal, financial and technical barriers in the Open Science era, data repositories must have the functional requirements asked by DMP and CoreTrustSeal. In order to derive functional requirements for the data repository, this study analyzed the Data Management Plan (DMP) and CoreTrustSeal, the criteria for certification of research data repositories. Deposit, Ethics, License, Discovery, Identification, Reuse, Security, Preservation, Accessibility, Availability, and (Meta) Data Quality, commonly required by DMP and CoreTrustSeal, were derived as functional requirements that should be implemented first in implementing data repositories. Confidentiality, Integrity, Reliability, Archiving, Technical Infrastructure, Documented Storage Procedure, Organizational Infrastructure, (Meta) Data Evaluation, and Policy functions were further derived from CoreTrustSeal. The functional requirements of the data repository derived from this study may be required as a key function when developing the repository. It is also believed that it could be used as a key item to introduce repository functions to researchers for depositing data.

• Journal of Korean Society for Quality Management
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• v.38 no.1
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• pp.85-95
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• 2010

In this paper we propose a product-service valuation model which is usable as a decision-making tool in order to attain a competitive advantage in service in the manufacturing industry. With this purpose, service quality, product quality and costs as valuation criteria are selected. Also, the paper utilizes an AHP model in order to differentiate a fuzzy theory and valuation factors to ensure objectivity in the evaluated results while excluding subjective factors in conducting the product-service valuation. Accordingly, the product-service valuation model and valuated results proposed in this paper are expected to be useful as a basic data for decision-making in order to draw competitive advantage strategies of service in the manufacturing industry.

• Journal of Korean Society for Quality Management
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• v.36 no.4
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• pp.37-46
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• 2008

There are big differences in six sigma projects between manufacturing processes and transactional/service processes. This paper analyzed the differences between the two areas by examining 18 six sigma case studies in Korean companies. To characterize six sigma case studies, step-by-step questions and check criteria were developed based on 12 step DMAIC methodology. On the basis of those characterized data, the differences between two areas were analyzed. Significant differences were found in the number of CTQs, validation of measurement systems, methods to determine improvement objectives, the methods to elicit improvement plans and types of control systems. The most significant difference was that statistical tools were widely used in manufacturing processes, but qualitative tools were used in transactional/service processes during improvement phase.

• Journal of the Korea Fashion and Costume Design Association
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• v.4 no.1
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• pp.131-141
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• 2002

The present study, first, reviews theoretically previous studies about the concept and quality of services as well as tools to measure the quality. Second, it reviews theoretically previous studies about the concept and quality of special services as well as tools to measure the quality. According to the results of reviewing previous studies on service quality, it is considered that the variance among several researchers concerning the measurements of service quality is affected significantly by factors such as the procedures of data collection and analyses utilized in the studies. In addition, the fact that dimensions are different, or some dimensions are not independent, is highly likely to be based on the unique characteristics of business categories, in addition to research procedures. Accordingly, when measuring service quality in future studies, it may be desirable to adapt measuring tools partially for the characteristics of each service category, and to generalize the adjusted tools over the specific category. Especially studies on the quality of special service have been carried out in limited scope so far. Thus, it is required to develop and refine comprehensive and appropriate criteria and detailed questions to measure the quality of fashion education service. Furthermore, studies are necessary with regard to relations among relevant factors such as customers' satisfaction and perception on education service quality after they experience the services.

• Journal of information and communication convergence engineering
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• v.10 no.1
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• pp.11-20
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• 2012

In a marine ubiquitous sensor network (USN) system using expensive sensors in the harsh ocean environment, it is very important to discover failures and devise recovery techniques to deal with such failures. Therefore, in order to perform failure modeling, this study analyzes the USN-based real-time water quality monitoring service of the Gaduri Aqua Farms at Songdo Island of Yeosu, South Korea and devises methods of discovery and recovery of failure by classifying the types of failure into system element failure, communication failure, and data failure. In particular, to solve problems from the perspective of data, this study defines data integrity and data consistency for use in identifying data failure. This study, by identifying the exact type of failure through analysis of the cause of failure, proposes criteria for performing relevant recovery. In addition, the experiments have been made to suggest the duration as to how long the data should be stored in the gateway when such a data failure occurs.

• The Transactions of the Korea Information Processing Society
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• v.3 no.6
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• pp.1553-1567
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• 1996

The numerous applications surface interpolation include the modeling and visualization phenomena. A tetrahedrization is one of pre-processing steps for 4-D space interpolation. The quality of a piecewise linear interpolation 4-D space depends not only on the distribution of the data points in $R^2$, but also on the data values. We show that the quality of approximation can be improved by data dependent tetraheadrization through visualization of 4-D space. This paper discusses Delaunary tetrahedrization method(sphere criterion) and one of the data dependent tetrahedrization methods(least squares fitting criterion). This paper also discusses new data dependent criteria:1) gradient difference, and 2) jump in normal direction derivative.

• Journal of Internet of Things and Convergence
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• v.8 no.1
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• pp.37-43
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• 2022

The fundamental basis of AI technology is learningable data. Recently, the types and amounts of data collected and produced by the government or private companies are increasing exponentially, however, verified data that can be used for actual machine learning has not yet led to it. This study discusses the conditions that data actually can be used for machine learning should meet, and identifies factors that degrade data quality through case studies. To this end, two representative cases of developing a prediction model using public big data was selected, and data for actual problem solving was collected from the public data portal. Through this, there is a difference from the results of applying valid data screening criteria and post-processing. The ultimate purpose of this study is to argue the importance of data quality management that must be most fundamentally preceded before the development of machine learning technology, which is the core of artificial intelligence, and accumulating valid data.

• Health Policy and Management
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• v.19 no.3
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• pp.1-26
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• 2009

Objectives : To identify target areas and set priorities among those areas identified for national quality evaluation. Methods : Target areas were identified from: i) analysis of the national health insurance claims data, mortality and prevalence data ii) various group surveys, including representatives from 22 medical specialty associations, 19 physician associations, QI staffs in hospital, civil organizations, and commissioners of Health Insurance Review and Assessment Service(HIRA) ⅲ) literature reviews and RAM(RAND/UCLA appropriateness method). The priority areas for national quality evaluation represented the full spectrum of health care and the entire life span. The criteria for selecting the priority areas were impact, improvability, and measurability. The priority areas were divided into three categories : short-term, mid-term, long-term. Results: Based on the group surveys and the data analysis, 46 candidates were selected as quality evaluation priority areas. 13 areas were selected as having a short-term priority areas: tuberculosis, community acquired pneumonia, stroke, ischaemic heart disease, diabetes, hypertension, chronic lower respiratory disease(asthma, chronic obstructive pulmonary disease), intensive care unit, emergency room, nosocomial infection, use of antibiotics, multiple medication and renal failure. This results suggested that we need to enlarge the target priority areas to the chronic diseases in short-term. Conclusions: The priority areas identified from the study will assist healthcare quality associated institutions as well as HIRA in selecting quality evaluation areas. It is required to develope and implement strategies for improving the quality of care within the next 5 years.