• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.517-526
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• 2004

In the resent years, the early evaluation of concrete quality, construction and maintenance has been considered as all is of major concern due to the increase of loading and the degradation of structures related with time. This paper presents evaluation of structural safety performance using measured data of construction, on the basis of a field measurements for the prevention of unreliable concrete works. Measurements analyzed in this paper are early quality condition and performance assessment, serviceability performance by cracks and deflection, rating performance by loading, durability performance by chloride attack and carbonation. Thus, a quantitative assessment model of resistance capacity was developed here to meet the requirement for deteriorated concrete structures. The model focuses on damage mechanical of concrete structures deteriorated by initial damage factors for concrete quality and environment factors such as chloride and carbonation attacks. These results could provide useful information for concrete structures interested in design, construction and maintenance.

• Journal of Environmental Impact Assessment
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• v.20 no.5
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• pp.705-716
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• 2011

For the efficient discovery of knowledge and information from the observed systems, data mining techniques can be an useful tool for the prediction of water quality at intake station in rivers. Deterioration of water quality can be caused at intake station in dry season due to insufficient flow. This demands additional outflow from dam since some extent of deterioration can be attenuated by dam reservoir operation to control outflow considering predicted water quality. A seasonal occurrence of high ammonia nitrogen ($NH_3$-N) concentrations has hampered chemical treatment processes of a water plant in Geum river. Monthly flow allocation from upstream dam is important for downstream $NH_3$-N control. In this study, prediction models of water quality based on multiple regression (MR), artificial neural network and data mining methods were developed to understand water quality variation and to support dam operations through providing predicted $NH_3$-N concentrations at intake station. The models were calibrated with eight years of monthly data and verified with another two years of independent data. In those models, the $NH_3$-N concentration for next time step is dependent on dam outflow, river water quality such as alkalinity, temperature, and $NH_3$-N of previous time step. The model performances are compared and evaluated by error analysis and statistical characteristics like correlation and determination coefficients between the observed and the predicted water quality. It is expected that these data mining techniques can present more efficient data-driven tools in modelling stage and it is found that those models can be applied well to predict water quality in stream river systems.

• Korean Journal of Soil Science and Fertilizer
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• v.37 no.6
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• pp.357-364
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• 2004

Modern agriculture depending on chemicals such as fertilizers and pesticides gave rise to questions about long-term sustainability of agriculture in relation to degradation of soil quality. Improving soil quality is prerequisite to sustain biological productivity, maintain environmental quality, and promote plant and animal health. Assessment and monitoring of the health and quality of soil is necessary to provide opportunity to evaluate and redesign soil management system for sustainability. To develop the soil quality assessment method, we collected national data on soil properties of paddy and upland and attempted to evaluate the data in aspect of soil quality by the process of selecting a minimum data set (MDS), scoring the soil properties and calculating soil quality index (SQI) integrating the score of each soil property. This approximation indicated that soil quality index was in the order of paddy soil, upland soil and plastic film house soil.

• Particle and aerosol research
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• v.7 no.1
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• pp.31-44
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• 2011

The hourly volatile organic compounds(VOCs) concentrations between 2005 and 2008 at Bulgwang photochemical assessment monitoring station were investigated to establish a method for quality assurance and quality control(QA/QC) procedure. Systematic error, erratic error, and random error, which was manifested by outlier and highly fluctuated data, were checked and removed. About 17.3% of the raw data were excluded according to the proposed QA/QC procedure. After QA/QC, relative standard deviation for representing 15 species concentrations decreased from 94.7-548.0% to 63.4-125.8%, implying the QA/QC procedure is proper. For further evaluation about the adequacy of QA/QC procedure, principal components analysis(PCA) was carried out. When the data after QA/QC procedure was used for PCA, the extracted principal components were different from the result from the raw data and could logically explain the major emission sources(gasoline vapor, vehicle exhaust, and solvent usage). The QA/QC procedure based on the concept of errors is inferred to proper to be applied on VOCs. However, an additional QA/QC step considering the relationship between species in the atmosphere needs to be further considered.

• Journal of Environmental Impact Assessment
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• v.18 no.2
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• pp.59-67
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• 2009

Water quality of the Lake Youngrang in the Sokcho City is eutrophic. Jangcheon is the largest inflow source to the lake. Major pollutant sources are stormwater runoff from resort areas and various land uses in the Jangcheon watershed. A storm sewer on the southern end of the lake is also an important pollution source. In this study, water quality modelling for Lake Youngrang was carried out considering the rainfall-runoff pollution loads from the watershed. The rainfall-runoff curves and the rainfall-runoff pollutant load curves were derived from the rainfall-runoff survey data during the recent 4 years. The rainfall-runoff pollution loads and flow from the Jangcheon watershed and the storm sewer were estimated using the two kinds of curves, and they were used as the flow and the boundary data of the WASP model. With the measured water quality data of the year 2005 and 2006, WASP model was calibrated. Non-point pollution control measures such as wet pond and infiltration trench were considered as the alternative for water quality management of the lake. The predicted water quality were compared with those under the present condition, and the improvement effect of the lake water quality were analyzed.

• Journal of Korean Society for Quality Management
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• v.42 no.1
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• pp.111-127
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• 2014

Purpose: Simple part or equipment is necessary TRA(Technology Readiness Assessment) or MRA(Manufacturing Readiness Assessment). But sole maturity like TRA, MRA has limit complex systems or SoS(System of System). Especially complex weapon system need from the System Maturity Point of view. This research shows necessity of SRA(System Readiness Assessment). Methods: In case of complex systems, it is essential to SRA(System Readiness Assessment). For the purpose of calculating SRL(System Readiness Level), TRL and IRL must be calculated. And then SRL can obtain know from equation of TRL and IRL. To prove SRA effectiveness, it is calculated SRL of JTDLS(Joint Tactical DataLink System) programs. Results: SRA procedure is proposed and case study shows as examples of JTDLS programs. Although result of TRA is TRL6, result of SRA is not 0.6. From this research, we can know necessity of SRA. Especially complex systems or SoS(System of System) is essential to SRA. Conclusion: SRA(System Readiness Assessment) is required to overcome limitation of sole maturity and to achieve a successful acquisition of high quality weapon system. This research intended to suggest SRA procedure and case study in complex defense system.

• Journal of Biomedical Engineering Research
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• v.44 no.2
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• pp.118-124
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• 2023

Many recent studies have reported that the quality of input learning data was vital to the detection of regions of interest. However, due to a lack of research on the quality of learning data on lesion detetcting using gastroscopy, we aimed to quantify the impact of quality difference in endoscopic images to lesion detection models using Image Quality Assessment (IQA) algorithms. Through IQA methods such as BRISQUE (Blind/Referenceless Image Spatial Quality Evaluation), Laplacian Score, and PSNR (Peak Signal-To-Noise) algorithm on 430 sheets of high quality data (HQD) and 430 sheets of low quality data (PQD), we showed that there were significant differences between high and low quality images in lesion detecting through BRISQUE and Laplacian scores (p<0.05). The PSNR value showed 10.62±1.76 dB on average, illustrating the lower lesion detection performance of PQD than HQD. In addition, F1-Score of HQD showed higher detection performance at 77.42±3.36% while F1-Score of PQD showed 66.82±9.07%. Through this study, we hope to contribute to future gastroscopy lesion detection assistance systems that involve IQA algorithms by emphasizing the importance of using high quality data over lower quality data.

• Journal of Korean Society for Quality Management
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• v.41 no.4
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• pp.623-635
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• 2013

Purpose: The recent major recalls of hazardous products caused consumer product safety acts to be strengthen worldwide. Although the recall system of hazardous products in Korea has been operating based on Framework Act on Product Safety since 2011, the evaluation of product risk has been relied on not the results of objective incident data but the results of illegal product investigations. The purpose of this paper is to propose a product risk assessment model for Korea using injury data. Methods: The authors derived Korea's risk assessment method by analysing the advantages and disadvantages of the most widely used models in advanced countries such as EU's RAPEX RAG and Janpan's R-MAP. In this study, the level of relative frequency and severity of injury are determined based on the objective incident data and the length of hospitalization respectively. In addition, the injury data occurred during 2011 is applied to the proposed risk assessment model for case study. Results: The data analysed in this paper can be classified as high risk, medium risk, low risk, acceptable risk, and safe products through the matrix f rom the combination of the relative frequency and the severity derived. Conclusion: The proposed risk assessment model in this study has advantage obtaining reliable objective results because it uses actual injury data and redeems the drawbacks of the existing models used in advanced countries. Furthermore, because the proposed model shows the high risk products among many, it is expected to be useful especially for customs whose main job is inspecting the imported goods and the government when selecting the target product groups for safety investigation.

• Journal of Environmental Impact Assessment
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• v.6 no.1
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• pp.111-119
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• 1997

This study was carried out to suggest the best statistical test which may be used to quantify the change of water quality between two groups. Traditional t-test may not be used in cases where the normality of underlying population distribution is not assured. Three non-parametric tests which are based on the relative order of the measurements, were studied to find out the applicability in water quality data analysis. The sign test is based on the sign of the deviation of the measurement from the median value, and the binomial distribution table is used. The signed rank test utilizes not only the sign but also the magnitude of the deviation. The Wilcoxon rank-sum test which is basically same as Mann-Whitney test, tests the mean difference between two independent samples which may have missing data. Among the three non-parametric tests studied, the singed rank test was found out to be applicable in the quantification of the change of water quality between two samples.

• International Journal of Quality Innovation
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• v.8 no.3
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• pp.35-45
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• 2007

This paper describes the development of a scale for measuring top management commitment towards continual quality performance improvement in small and medium-sized enterprises (SMEs). A set of self-assessment questions of the ISO 9004: 2000 Standard was used to assess the adoption status of quality management practices. This paper investigates the inter-item reliability and the content validity of the Quality Management Principles Scale (QMPS) in an integrated improvement process in SMEs. An empirical study was conducted to acquire senior management views on the use of the QMPS in manufacturing sectors in Trinidad and Tobago. Based on 328 responses from 110 SMEs, statistical software packages were used to analyse the empirical data and determine the reliability and validity of the QMPS. The paper contributes to develop a self-assessment scale that can be used to measure top management commitment. It is anticipated that the findings would provide practical insights for evaluating the levels of maturity on performance improvement in SMEs.