• Korean Journal of Computational Design and Engineering
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• v.21 no.2
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• pp.111-121
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• 2016

The plant equipment usually has a long life cycle. During its O&M (Operation & Maintenance) phase, since the occurrence of an accident of offshore plant equipment causes catastrophic damage, it is necessary to make more efforts for managing critical offshore equipment. Nowadays due to the emerging ICTs (Information Communication Technologies) and sensor technologies, it is possible to gather the health status data of important offshore equipment and their environment data, which leads to much concern on CBM (Condition-Based Maintenance). In this study, we will propose an approach to estimate the remaining lifetime of an offshore plant equipment (pump tower) based on gathered ocean environment data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.1
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• pp.77-85
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• 2020

Currently, life-cycle cost analysis methods are introduced to maintain large infrastructure facilities in Korea. However, there are not many cases in which maintenance models are applied that reflect conditions such as the location of a facility and its surroundings. In order to establish an appropriate maintenance strategy, a cost prediction, deterioration model, and a decision model reflecting uncertainty should be established. In this study, an economic analysis model was developed for long-term cost planning and management based on user decisions based on maintenance methods and judgment criteria for painting specifications applied to power generation structures. The performance of the paintwork was assessed through the paint deterioration test for the application of the economic analysis model, and the results of the economic analysis according to the applied paint specifications (Urethan, polysiloxane, fluorine) were verified by applying the proposed economic analysis model. In this study, it is believed that the selection of the repair cycle and evaluation methods applied with the development model rather than the performance of the painting can be expected to be used as basic data for the maintenance cycle, even if it is not limited to the painting.

• Journal of Plant Biotechnology
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• v.50
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• pp.127-136
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• 2023

Water scarcity decreases the rate of photosynthesis and, consequently, the yield of banana plants (Musa spp). In this study, transcriptome analysis was performed to identify photosynthesis-related genes in banana plants and determine their expression profiles under water stress conditions. Banana plantlets were in vitro cultured on Murashige and Skoog agar medium with and without 10% polyethylene glycol and marked as BP10 and BK. Chlorophyll contents in the plant shoots were determined spectrophotometrically. Two cDNA libraries generated from BK and BP10 plantlets, respectively, were used as the reference for transcriptome data. Gene ontology (GO) enrichment analysis was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) and visualized using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway prediction. Morphological observations indicated that water deficiency caused chlorosis and reduced the shoot chlorophyll content of banana plantlets. GO enrichment identified 52 photosynthesis-related genes that were affected by water stress. KEGG visualization revealed the pathways related to the 52 photosynthesisr-elated genes and their allocations in four GO terms. Four, 12, 15, and 21 genes were related to chlorophyll biosynthesis, the Calvin cycle, the photosynthetic electron transfer chain, and the light-harvesting complex, respectively. Differentially expressed gene (DEG) analysis using DESeq revealed that 45 genes were down-regulated, whereas seven genes were up-regulated. Four of the down-regulated genes were responsible for chlorophyll biosynthesis and appeared to cause the decrease in the banana leaf chlorophyll content. Among the annotated DEGs, MaPNDO, MaPSAL, and MaFEDA were selected and validated using quantitative real-time PCR.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.3
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• pp.1-7
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• 1999

An important task for any software project manager is to be able to predict and control project size. Unfortunately, there is comparatively little work that deals with the problem of building prediction methods for software size in fourth-generation languages and database projects. In this paper, we propose a new estimation method for estimating for software size based on minimum relative error(MRE) criterion. The characteristic of the proposed method is insensitive to the extreme values of the observed measures which can be obtained early in the development life cycle. In order to verify the performance of the proposed estimation method for software size in terms of both quality of fit and predictive quality, the experiments has been conducted for the dataset Ⅰ and Ⅱ, respectively. For the data set Ⅰ and Ⅱ, our proposed prediction method was shown to be superior to the traditional method LS and RLS in terms of both the quality of fit and predictive quality when applied to data obtained from actual software development projects.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.5
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• pp.543-551
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• 2015

In this paper, Used on the bridge and ship, investigate the physical relationship of aluminium plate girders(A6082-T6) considering the marine environment. Plate girder will experience the patch loading such as moving load, surcharge in the product life cycle. The ultimate strength of aluminum plate girders subjected to these loads applied multiple numerical model and performed the elasto-plastic large deflection series analysis and was proposed the predicted formula for regression analysis. The predicted formula was shown by the relationship of ultimate strength and slenderness. If the slenderness is low(0-2.3), it causes a 9 % error, and If the slenderness is higher(2.3-4.0), it causes a 1-2 % error. Therefore, the propriety of proposed prediction formular was found to be assess rationally.

• Journal of the Korea Institute of Building Construction
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• v.10 no.2
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• pp.41-50
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• 2010

This study presented a model that can enable a reliability analysis for the repair and replacement cycle of a building by using background repair and replacement data and expert opinion as foundation data and applying Monte Carlo Simulation. The presented model offers the time of the repair and replacement of building elements for the period of a year, and supports the prediction of repair and replacement and expenses demand in advance while planning the maintenance of a building. In addition, the model will significantly reduce the risks to the building owner with regard to maintenance decisions. In addition, when a person in charge of the maintenance of large-scale building assets is having difficulties making decisions regarding the repair and replacement of existing building elements due to a lack of background data to support a long-term policy on the repair and replacement requirements, an engineering solution that can ensure the adequacy of this is provided. In summary, it can be largely divided into three study results. First, a method of estimating the repair and replacement cycle that can deal with the development of a construction system was developed. Second, a probabilistic methodology that can quantify the risk of the repair and replacement cycle was proposed. Third, the proposed model can be used as a means of supporting designer and constructor in making decisions for the life cycle plan of a building during a construction project.

• Journal of the Korean Institute of Gas
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• v.27 no.2
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• pp.71-78
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• 2023

In general, electric submersible pumps (ESPs), which have an average life of 1.0 to 1.5 years, experience a decrease in performance and a reduction in life of the pump depending on oil and gas reservoir characteristics and operating conditions in wells. As the result, the failure of ESP causes high well workover costs due to retrieval and installation, and additional costs due to shut down. In this study, a flow loop system was designed and established to predict the life of ESP in long­term operation of oil and gas wells, and the life cycle data of ESP from the time of installation to the time of failure was acquired and analyzed. Among the data acquired from the system, flow rate, inlet and outlet temperature and pressure, and the data of the vibrator installed on the outside of ESP were analyzed, and then the performance status according to long-term operation was classified into five stages: normal, advice I, advice II, maintenance, and failed. Through the experiments, it was found that there was a difference in the data trend by stage during the long­term operation of the ESP, and then the condition of the ESP was diagnosed and the failure of the pump was predicted according to the operating time. The results derived from this study can be used to develop a failure prediction program and data analysis algorithm for monitoring the condition of ESPs operated in oil and gas wells.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.4
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• pp.1651-1664
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• 2013

Precise analysis on deterioration processes of road pavements is not so simple matter due to severe uncertainty originated from a lot of explanatory variables engaged in. For those reasons, most analytical models for pavement deterioration prediction have often preferred to probabilistic approaches than deterministic models. However, the general probabilistic approaches that treat overall characteristics of population or entire sample would not be suitable for providing detail or localized information on their changing process. Considering the aspects, this paper aimed to suggest a stochastic disaggregation method to analyze the localized deterioration speeds and its variances changed by time and condition states. In addition, life expectancies and their uncertainty were estimated by probabilistic algorithm using the disaggregated stochastic process. For an empirical study, pavement inspection data (crack) accumulated from 2003 to 2010 from Korean national highway network was applied. This study can contribute to securing reliability of life cycle cost analysis, which is one of the primary analyses in road asset management, with much advanced deterioration forecasting functions. In addition, it would be meaningful trials as fundamental research for preventive maintenance strategy that demands essential understanding on changing process of the deterioration speed of pavement.

• Journal of the Korean Wood Science and Technology
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• v.49 no.2
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• pp.122-133
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• 2021

The radon gas from nature mainly considers a cause of radon problems, and it is closely affect human life cycle. Korean yellow residual soil, Hwangtoh, widely used as a building material, is considered to be one of major sources of indoor radon. However, there have, as yet, been no studies about radon from Hwangtoh in mass market brands. Here, we investigated the indoor radon concentrations and exhalation rates in four Hwangtohs from different brand names and regional features. The Closed Chamber Method (CCM) conducted by a Continuous Radon Monitor (CRM) has been used for the rates of radon exhalation. Based on equations of previous references, the indoor radon concentrations were deducted. As a result, the radon surface exhalation rates resulted in the 1.4208 to 3.0293 Bq·㎡·h-1 range. Significant differences were found among Hwangtohs according to production regions. Materials with higher radon concentration required a longer time to reach a quasi-steady state in a given environment, in other words, the number of half-life cycles increased from a set starting point. The experimentally identified Hwangtohs demonstrated its safety for construction purposes. There exists, so far, a possibility to exert influence radon emanation due to unidentified factors. Therefore, it is necessary to corroborate with more research by increasing the number of Hwangtohs, considering the other references reported high radon exhalation rates. In addition, it is highly recommended that the radon exhalation rates should be measured for all building materials for preventing human health before the material usage.

• Journal of Animal Science and Technology
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• v.55 no.6
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• pp.489-500
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• 2013

Daily milk yields on test days were estimated using morning or afternoon partial milk yields collected by official agencies and the accuracy of the estimates was determined. Test-day data for milk yields consisted of 3,156,734 records of AM/PM partial milking measurements of 255,437 milking Holstein cows from 3,708 farms collected from December 2008 to April 2013. A linear regression model (LRM) was applied to estimate daily milk yields using alternate AM/PM milk yield records within lactation stages, milking intervals, and parities on every daily milk yield. The alternate statistical approach was a non-linear hierarchical model (NHM) in which Brody's growth function was implemented by reflecting an animal's physiological milk production cycle. When compared with LRM, daily milk yields predicted by the NHM were assumed to be functionally related to day in milk (or lactation) stage, milking intervals, and partial milk yields. Since the results were in terms of accuracies based on comparisons of different statistical models, accuracies of estimates of daily milk yields by NHM were close to those determined by the LRM. The average of these accuracies was 0.94 for AM partial milk yields and 0.93 for PM partial milk yields for first calving cows. However, the accuracies of AM/PM milk yield estimations from cows under a calving stage higher than the first parity were 0.96 and 0.95, respectively. Correlations between the estimated daily milk yields and the actual daily milk yields ranged from 0.96~0.98. These accuracies were lower for unbalanced AM/PM milking intervals and the first calving cows. Overall, prediction of daily milk yields by NHM would be more appropriate than by LRM due to its flexibility under different milk yield-related circumstances, which provides an idea of the functional relationship between milking intervals and days in milk with daily milk yields from statistical viewpoints.