• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.1
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• pp.151-157
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• 2019

This study is about the process capability index (PCI). In this study, we introduce several indices including the index $C_{PR}$ and present the characteristics of the $C_{PR}$ as well as its validity. The difference between the other indices and the $C_{PR}$ is the way we use to estimate the standard deviation. Calculating the index, most indices use sample standard deviation while the index $C_{PR}$ uses range R. The sample standard deviation is generally a better estimator than the range R. But in the case of the panel process, the $C_{PR}$ has more consistency than the other indices at the point of non-conforming ratio which is an important term in quality control. The reason why the $C_{PR}$ using the range has better consistency is explained by introducing the concept of 'flatness ratio'. At least one million cells are present in one panel, so we can't inspect all of them. In estimating the PCI, it is necessary to consider the inspection cost together with the consistency. Even though we want smaller sample size at the point of inspection cost, the small sample size makes the PCI unreliable. There is 'trade off' between the inspection cost and the accuracy of the PCI. Therefore, we should obtain as large a sample size as possible under the allowed inspection cost. In order for $C_{PR}$ to be used throughout the industry, it is necessary to analyze the characteristics of the $C_{PR}$. Because the $C_{PR}$ is a kind of index including subgroup concept, the analysis should be done at the point of sample size of the subgroup. We present numerical analysis results of $C_{PR}$ by the data from the random number generating method. In this study, we also show the difference between the $C_{PR}$ using the range and the $C_P$ which is a representative index using the sample standard deviation. Regression analysis was used for the numerical analysis of the sample data. In addition, residual analysis and equal variance analysis was also conducted.

• Journal of Korean Society on Water Environment
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• v.28 no.2
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• pp.202-212
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• 2012

Due to the deterioration of water supply network and the deficiency of raw water, the water utility of local governments have performed various projects to improve their revenue water ratio. However, it is very difficult to estimate the cost for maintaining the revenue water ratio at higher level after completing the project, because local governments have different conditions affecting the operating and maintenance cost of water supply network. The purpose of this study is to present a procedure to estimate the operating and maintenance cost required to maintain the target revenue water ratio of the water supply network. For this purpose, we estimated the cost used only for operation and maintenance of water supply network of 164 local governments with the aid of K-Mean Clustering Analysis and the data from 40 representative local governments. Then, the regression analysis was performed to find relationship between revenue water ratio and the operating and maintenance cost with two different data sets generated by two classification methods; the first method classifies the local governments by means of k-means clustering, and the other classifies the local governments according to the index standardized by the operating and maintenance cost per unit length of water mains per revenue water ratio. The results shows that the method based on the index standardized by the cost and revenue water ratio of each government produces more reliable results for finding regression equations between revenue water ratio and the operating and maintenance cost only for water supply network. The estimated regression equations for each group can be used to estimate the cost required to keep the target revenue water ratio of the local government.

• The KIPS Transactions:PartD
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• v.18D no.4
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• pp.225-236
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• 2011

Various applications of LBS (Location Based Services) are being developed to provide the customized service depending on user's location with progress of wireless communication technology and miniaturization of personalized device. To effectively process an amount of vehicles' location data, LBS requires the techniques such as vehicle observation, data communication, data insertion and search, and user query processing. In this paper, we propose the historical location index, GIP-FB (Group Insertion tree with Flexible Buffer Node) and the flexible buffer node technique to adjust the cost of data insertion and search. the designed GIP+ based index employs the buffer node and the projection storage to cut the cost of insertion and search. Besides, it adjusts the cost of insertion and search by changing the number of line segments of the buffer node with user defined time interval. In the experiment, the buffer node size influences the performance of GIP-FB by changing the number of non-leaf node of the index. the proposed flexible buffer node is used to adjust the performance of the historical location index depending on the applications of LBS.

• Physical Therapy Korea
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• v.9 no.1
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• pp.43-51
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• 2002

Physiological Cost Index (PCI) of walking has been widely used to predict oxygen consumption in healthy subjects or patients. The purpose of this study was to evaluate the predictability of physiological cost index of walking for the amount of exercise and cardiac function. Walking exercise was conducted in 67 healthy children (age 4-12) with a self-selected comfortable walking speed on the level surface. Walking speed was calculated, and heart rate was measured before and immediately after the walking. PCI was calculated for statistical analysis. The results were as follows; 1) The walking speed tends to increase and PCI of walking tends to decrease with age. There was significant difference in walking speed and PCI of walking among three age groups (p<.05). The change of walking heart rate tends to decrease with age, however, there was no significant difference among three age groups. 2) Linear regression equation between walking speed and age was 'Y (walking speed) = 2.124X (age) + 48.286' ($R^2$=.337), (p=.00). 3) The walking heart rate tends to decrease with age. Linear regression equation between walking heart rate and age was 'Y (walking heart rate) = 143.346 - 2.63X (age)' ($R^2$=.3425), (p=.00). 4) The walking heart rate decreased as body surface area (BSA) increased. Linear regression equation between walking heart rate and BSA was 'Y (walking heart rate) = 149.830 - 27.115X (BSA)' ($R^2$=.3066), (p=.00). In conclusion, these equations and PCI could be useful to quantify the variation of energy expenditure of children with pathological gait when compared with age-matched healthy children.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.72-76
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• 2015

Capital project benchmarking requires an effective cost normalization process to compare cost performance of projects accomplished in different time and location. Existing cost normalization approaches have been established based on the assumption that all required information for cost normalization is fully identified once a project is completed. Cost normalization, however, is sometimes required to evaluate phase-level outcomes of an ongoing project where the required information is not fully available. This paper aims to provide a cost normalization procedure for phase-based performance assessment. The procedure consists of three normalization steps: currency conversion, location adjustment, and time adjustment considering various scenarios where the required information is not fully identified. This paper also presents how the cost normalization procedure has been applied to the 10-10 Performance Assessment Program, which is a phase-based performance assessment system developed by the Construction Industry Institute (CII). Both researchers and industrial professionals can apply the cost normalization procedure to studies and practices regarding to cost estimation, feasibility analysis, and performance assessment.

• The KIPS Transactions:PartD
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• v.13D no.4 s.107
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• pp.477-490
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• 2006

Existing index structures need very much update cost because they repeat delete and insert operations in order to update continuously moving objects. In this paper, we propose a new index structure which reduces the update cost of continuously moving objects. The proposed index structure consists of a space partitioning index structure that stores the location of the moving objects and an auxiliary index structure that directly accesses to their current positions. In order to increase the fanout of the node, it stores not the real partitioning area but kd-tree as the information about the child node of the node. In addition, we don't traverse a whole index structure, but access the leaf nodes directly and accomplish a bottom-up update strategy for efficiently updating the positions of moving objects. We show through the various experiments that our index structure outperforms the existing index structures in terms of insertion, update and retrieval.

• 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 Korean Society of Steel Construction
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• v.15 no.2
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• pp.147-157
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• 2003

The application in steel structures is increasing the mill sheet for the weathering steels by minimum maintenance cost in a life cycle cost. These have been collected and statistically analyzed to investigate chemical compositions, mechanical properties, weldability indices, weathering index and impact absorbed energy. From this study, although the band of dispersion in chernical compositions, mechanical properties and impact absorbed energy of the weathering steels appeared a little larger, the results revealed that these values have adequately satisfied the standard values of the Korean Standard. Furthermore, it was found that the weldability indices and the weathering index for the weathering steels have respectively satisfied the value prescribed by the Japanese Highway Specification and ASTM.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.1090-1097
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• 2008

This study conducted the decision method of lateral flow in abutment structures founded on the soft soils and the reliability analysis on the foundation pile for abutment. On the basis of the results, this study proposed the reliability design model. Reliability analysis was conducted by applying second moment method, point estimation method, and expected total cost minimization to lateral movement index, lateral movement decision index, modified lateral movement decision index, and circular failure safety factor for the decision criteria of lateral flow. The reliability index by analysis method had a similar tendency each other. Point estimation method was found as a practical method in the aspect of convenience because it could conduct the analysis only by mean and standard deviation as well as the partial derivative on random variables was not necessary. Optimum reliability index and optimum safety according to increasing in failure factors and load ratio were analyzed and loads and resistance factors of the design criteria of optimum reliability were estimated. It presented rational design model which can consider construction level and stability and economical efficiency overall.

• Health Policy and Management
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• v.3 no.1
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• pp.84-101
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• 1993

The current method of rate adjustment is based on the evaluation of the financial performance of hospitals. The method has the disadvantages such as too complicated, expensive process as well as low reliability due to small sample size. This study, therefore, develops a new model for the rate adjustment with the use of the composite index. In addition to that, it examines the validity of the model by comparing the result of the new method with that of the conventional method. The idea of the new model comes from the Medicare Economic Index(MEI) on which physician fees for the Medicare patients are adjusted periodically in the United States. Medical costs are classified into three groups : labor costs, materials and other expenses. Labor costs are subdivided into physicians and other personnels. Materials are subdivided into drugs and others. Other expenses are subdivided into 5 items. Macro economic indices are selected for each cost item in order to reflect the cost inflation during the specific period. Then the composite index which integrate all items according to the ration of each item in the total costs is calculated. The result from the application of empirical data to the new model is very similar to that of the current method. Furthermore, this method is very simple and also to easy to get social concensus. This model can be replaced the current method based on the analysis of the financial performance for the adjustment of medical fees.