• Proceedings of the Safety Management and Science Conference
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• 2011.04a
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• pp.701-705
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• 2011

The paper reviews Cronbaha's coefficient to measure a single source of error. On the contrary to classical measurement theory, the generalizability study can be used in the social survey design to calculate Generalizability Index (GI) and Dependability Index (DI) for measuring multiple sources of errors of behavior evaluation. The study proposes application guidelines to implement R:($A{\times}B$) mixed models that are composed of random factor and fixed factor.

• Journal of Korea Multimedia Society
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• v.20 no.5
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• pp.791-799
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• 2017

With the development of the internet of things, sensor and device are can be applied to various scenario. Overall improving of the dependability index of internet of things is the ultimate goal. And reliability aims to increase the success rate of internet of things service delivery. Many studies about internet of things system have been made on the system to assess a dependability for providing reliable service to user, but it has difficult to reflect the user context for evaluating the device reliability. Also, most do not consider the availability of content information. In this paper, it proposed dependable device searching system in the internet of things environment. This system evaluates device dependability based on device status and measured data. Through the proposed system, it can be provided reliable context information for user-centric service.

• Journal of the Korea Safety Management & Science
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• v.6 no.2
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• pp.103-114
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• 2004

IEC 60300 series, the international standards on reliability management system are newly developed and introduced rapidly worldwide. In order to meet this fast-changing situation, it is necessary to apply them to the Korean industries effectively. It includes the establishment of the infrastructure such as documentation of Korean Standards, introduction of test equipments and test manuals, accreditation of the certification bodies and training of the specialists etc. IEC 60300 is upgraded management system of the ISO 9000 and ISO 14000. In this regard, the Korean companies which were certified with the ISO 9000 or 14000 should endeavor to find new strategies and methods to be certified with IEC 60300. This paper introduces a Quantitative method of estimating the level of the reliability management system by applying the MIR(Maturity Index on Reliability) technique. This enables the estimation of the operation level of the system and can upgrade the maturity level of it.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.124-127
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• 2006

IEC 60300 is an advanced Dependability Management System(DMS) designed for highly qualified company. ISO/TS 16949 is an Quality Management System enforced reliability activities. It is now hot issue how to set up and implement DMS. This paper presents an approach for implementing Dependability Management System(IEC 60300) based on Quality Management System(ISO/TS16949). We analyse the difference and relationship between these two systems, and suggest an quantitative method for evaluating DMS by introducing MIR(Maturity Index for Reliability). Finally we analyse the level of reliability activities in these systems by MIR.

• Journal of Korean Society for Quality Management
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• v.44 no.2
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• pp.277-296
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• 2016

Purpose: Propose model to diagnose and assess National Defense Industry and quality management by investigating and analyzing established standard model. Methods: Research on established internal model including MB, EQA and JQA model and make standard index for quality index extraction and quantitative index to test objectively for internal state. Results: Extract advantage and disadvantage by performance of National Defense Industry level diagnose and build foundation for quality management policy and road map. Conclusion: Due to result of diagnostic assesment of quality management of national defense industry, dependability, SCQM and safety part shows vulnerability and require improvement and support.

• Geomechanics and Engineering
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• v.36 no.2
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• pp.111-119
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• 2024

In the realm of rock excavation projects, precise estimation of the drilling rate index stands as a pivotal factor in strategic planning and cost assessment. This study introduces and evaluates two pioneering computational intelligence models designed for the prognostication of the drilling rate index, a pivotal parameter with direct implications for cost estimation in rock excavation projects. These models, denoted as the Relevance Vector Regression (RVR) optimized with the Invasive Weed Optimization algorithm (IWO) (RVR-IWO model) and the RVR integrated with the Shuffled Frog Leaping algorithm (SFL) (RVR-SFL model), represent a groundbreaking approach to forecasting drilling rate index. The RVR-IWO and RVR-SFL models were meticulously devised to harness the capabilities of computational intelligence and optimization techniques for drilling rate index estimation. This research pioneers the integration of IWO and SFL with RVR, constituting an unprecedented effort in forecasting drilling rate index. The primary objective of this study was to gauge the precision and dependability of these models in forecasting the drilling rate index, revealing significant distinctions between the two. In terms of predictive precision, the RVR-IWO model emerged as the superior choice when compared to the RVR-SFL model, underscoring the remarkable efficacy of the Invasive Weed Optimization algorithm. The RVR-IWO model delivered noteworthy results, boasting a Variance Account for (VAF) of 0.8406, a Mean Squared Error (MSE) of 0.0114, and a Squared Correlation Coefficient (R²) of 0.9315. On the contrary, the RVR-SFL model exhibited slightly lower precision, yielding an MSE of 0.0160, a VAF of 0.8205, and an R2 of 0.9120. These findings serve to highlight the potential of the RVR-IWO model as a formidable instrument for drilling rate index prediction, particularly within the framework of rock excavation projects. This research not only makes a significant contribution to the realm of drilling engineering but also underscores the broader adaptability of the RVR-IWO model in tackling an array of challenges within the domain of rock engineering. Ultimately, this study advances the comprehension of drilling rate index estimation and imparts valuable insights into the practical implementation of computational intelligence methodologies within the realm of engineering projects.

• Journal of Gifted/Talented Education
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• v.23 no.5
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• pp.671-695
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• 2013

This study provides an illustrative example of using the multivariate generalizability theory. Specifically, it investigates relative effects of each error source, and finds optimal measurement conditions for the number of items within each content domain that maximizes the reliability-like coefficients, such as a generalizability coefficient and an index of dependability. The method is based on teacher recommendation letters and self-introduction letters, using an analytic scoring method in the context of selection of mathematically gifted students by observation and nomination. This study analyzed data from the 2011 academic year in the science education institute for the gifted, which is attached to the university located in the Seoul metropolitan area. It should be noted that the optimal scoring structures of this study are not generalizable to other selection instruments. However, the methodology applied in this study can be utilized to find optimal measurement conditions for the number of raters, the number of content domains, and the number of items in other selection instruments self-developed by many institutions including: the education institutes for the gifted at provincial offices of education, gifted classes, and the science education institutes for the gifted attached to universities in general. In addition, the methodology will provide bases for making informed decisions in selection instruments of the gifted based on measurement traits.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.5
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• pp.808-813
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• 2011

This study was conducted to reduce the dependability of farmers on chemical fertilizers for rice cultivation. Soil chemical and biological properties were monitored before experiment and at the time of harvesting. The results showed that EC, available $SiO_2$, and exchangeable $Ca^{2+}$ were decreased at the time of harvesting while pH, OM, and exchangeable $K^+$ and $Mg^{2+}$ were remain unchanged, compared with soil before experiment. Population of aerobic bacteria, Bacillus sp., and fungi were also increased at the time of harvesting in the paddy field, compared with before fertilization, in the treatment of 50% soil-testing fertilizer+ 50% compost. Concentrations of N, P, and K in rice leaves increased with the fertilizers application, maximum increase was recorded in 50% soil-testing fertilizer+ 50% compost. Non-significant difference was observed in the morphological parameters of rice among the treatments. The chlorophyll contents of rice leaf increased in a similar fashion up to 60 days, thereafter, sharp decrease was observed in all the treatments. Maximum yield (per 10a) was recorded in the field treated with 50% soil-testing fertilizer+ 50% compost followed by standard applied fertilizer, 70% soil-testing fertilizer+ 30% compost, soil-testing fertilizer and unfertilized plot. Amylose content showed non-significant difference within the treatments. Protein content increased with the use of fertilizers and best protein content was recorded in the treatment of 50% soil-testing fertilizer+ 50% compost. It was concluded that the amount of the chemical fertilizer used was directly proportional to the protein content of rice grain. However, the palatability of rice grown in unfertilized field was better than the treatments but minimum yield was obtained. Hence, the treatment of 50% soil-testing fertilizer+ 50% compost, was the best among the fertilizer combinations for rice cultivation as supported by the yield, protein and palatability index.