• Asia-Pacific Journal of Business
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• v.13 no.3
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• pp.245-259
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• 2022

Purpose - Studies have been continuously carried out by researchers so far to clarify the factors influencing employee's incivility at work. However, the behavior of employees who are the target of incivility not much has been revealed which behavior affects the experience of incivility. Among them, it is interesting that the effect of OCB, a representative of employees' positive behavior in the workplace, on their experienced incivility has not been investigated. Therefore, this study attempted to clarify the relationship between OCB and experienced incivility that previous studies have not yet discovered. Design/methodology/approach - In the process, the concept of profile similarity was introduced and based on this, it was assumed that the OCB profile similarity between individual and colleagues, not the absolute level of OCB, would affect the experienced incivility and demonstrated this. The analysis was conducted by applying the survey data obtained from 205 employees to hierarchical regression analysis. Findings - As a result of the analysis, it was examined that the absolute OCB value used in previous studies did not significantly affect the experienced incivility, but the higher the similarity level, the less experienced incivility. The implications obtained based on this and future research directions are discussed together in the conclusion. Research implications or Originality - This study is the first one that considers OCB's profile similarity as a antecedent of experienced incivility. OCB profile similarity concept was only treated as a theoretical issue even in very early stage of OCB research stream, but this study examines the significant effect of OCB profile similarity. Moreover, behavioral antecedents of experienced incivility has not been identified well, but this study finds out that OCB can be a behavioral antecedent of experienced incivility.

• Journal of Korean Society of Environmental Engineers
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• v.32 no.2
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• pp.121-130
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• 2010

Metals and sulfate can be considerably dissolved at low pH condition in the acid mine drainage(AMD) and it would make an environmental problems. There are only few of acid mine drainage treatment systems in Korea which are operating, but these still have an effect on the surrounding stream. In this study, quantification of indicator microorganisms was conducted to judge the environmental impact of AMD on microflora by quantitative real-time PCR in the drainage samples of four mines and the water samples of each surrounding stream. Two species of iron reducing bacteria(Rhodoferax ferrireducens T118 and Acidiphilium cryptum JF-5) were selected for indicator bacteria based on 16S rRNA cloning analysis, and sulfate reducing bacteria(Desulfosporosinus orientus), iron and sulfur oxidizing bacteria(Acidothiobacillus ferrooxidans) and iron oxidizing bacteria(Leptosprillum ferrooxidans) were included into indicator since these were found in the previous studies on the mining area. Thereafter, the comparative analysis of four mines were established by the microbiological variation index and it was determined that the biological environment effect of AMD is highest in Samtan mine which doesn t contain treatment system by the value.

• Environmental Mutagens and Carcinogens
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• v.26 no.4
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• pp.125-132
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• 2006

Previous studies showed that epigallocatechin gallate(EGCG) have substantial effects of suppressing the N-methyl-N'-nitro-N-nitrosoguanidine(MNNG)-initiated cell transformation process on the bases of foci formation frequency and loss of anchorage dependency. In this study we tried to clarify the molecular mechanism of suppressing the cell transformation process. Mouse cell line balb/c 3T3 A31-1-1 was exposed 2 days to MNNG followed by 15 days 12-O-tetradecanoylphorbol-13-acetate(TPA) treatment for our transformation process. EGCG was added after the time point of 24 hours exposure to TPA and incubated for 19 days. 2029 genes were selected in our transformation process that showed fold change value of 1.5 or more in the microarray gene expression analysis covering the mouse full genome. These genes were found to be involved mainly in the cell cycle pathway, focal adhesion, adherens junction, TGE-$\beta$ signaling, apoptosis, lysine degradation, insulin signaling, ECM-receptor interaction. Among the genes, we focused on the 631 genes(FC>0.5) reciprocally affected by EGCG treatment. Our study suggest that EGCG down-regulate the gene expressions of up stream signaling factors such as nemo like kinase with MAPK activity and PI3-Kinase, Ras GTPase and down stream factors such as cyclin D1, D2, H, T2, cdk6.

• Korean Journal of Environmental Biology
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• v.27 no.2
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• pp.183-190
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• 2009

Characterization of the analysis of forest vegetation, soil environmental conditions and water quality were performed from March 2003 to March 2007. The two basins were characterized by cultivated area (Kaesim reservoir) and mountain area (Jangchan reservoir), and divided into eleven small basins, where dynamics of pollutants, forest vegetation and soil environmental conditions were surveyed. The vegetation can be divided into 10 types by $Z\ddot{u}rich$-Montpellier school's method. Pearson coefficients between vegetation type and water quality were correlated with dissolved oxygen (DO) in the Quercus variabilis community at the 5% level and total phosphorus (TP) in the Larix leptolepis plantation at the 1% level. Especially total phosphorous and total nitrogen increased in small basins where the proportion of cultivated and residential area increased. The analysis of influences of pollutant discharge on water quality showed that pollutant charge was very low in forest land area ($Y_{T-P}$=-0.0017X+0.2215, r=0.16, $Y_{COD}$=- 0.0395X+8.5051 r=0.47). The soil types of western area were comparatively simple, but those of eastern area were complicated with regosols, red-yellow soils, lithosoles, etc. The pH, total solid (TS) and volatile substance (VS) of the forest and agricultural land soils collected in each site were 5.4~6.9, 75.8~80.2%, and 3.80%~5.80%, respectively. According to the analytical result of soil environmental conditions, heavy metal contents fell short to the mean value of natural conditions. Runoff amount (Y) and depth of topsoil (X) were negatively correlated, $Y_{ron}=-1.0088X_{top}+35.378$ (r=0.68). The correlation was much lower in up-stream but much higher in down-stream, because permeation into soil particle was larger on down-stream due to its more or less gentle slope. Pearson coefficients between soil pH and water pH were statistically significant at 1% level.

• Journal of Korean Society for Quality Management
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• v.44 no.3
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• pp.639-648
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• 2016

Purpose: Existing precedent studies include success factors of individual management innovation activities constantly. However, those studies have limitations about the common key success factors of individual management innovation activities. Methods: For this study, we investigate the key success factors using literature research of the most typical management innovation activities adopted and implemented by many companies in Korea, such as 6sigma, TQM, Lean 6sigma, ERP, TPM, BPR, Project Management, System Engineering. Factors emerging repeatedly was combined into common factors and inherent factors that are necessary for the success of individual management innovation activities are designated to essential factors. Results: 'Essential factors for Six Sigma' consist of 5 items. Black belt operating system, personnel management system linkage, the correct management of the data, perform improvement projects associated with financial performance financial result, linked to financial performance improvement project, project progress management. 'Essential factors of TQM' are arranged 4 items. Quality team's independence and role, goal-setting, Quality Information System, corporate's philosophy of quality first. 'Essential factors of Lean Six Sigma' are the selection of value stream which is based on the customer needs and the value creation and identify the project based on the selected value in the company. 'Essential factors of ERP' are investigated 6 items. Ongoing system maintenance and upgrades, the measurement and support of user satisfaction, the operating systems and the policies for the maintenance, IT infrastructure, change adaption condition monitoring, focusing on improving business performance. 'Essential factors for TPM' are arranged 4 items. Motivated and energetic Bottom-Up, CEO's recognition of the importance facility management, long-term perspective of necessity and ongoing patience. 'Essential factors for BPR' are the pursuit of change process and the staff's sense of crisis management. 'Essential factors for Project Management' are the strategy that reduce the risk management skills through risk management and the understanding and organized management for the project participant's needs. 'Essential factors for System Engineering' consist of 2 items. The first is the design for the best balanced system with pre-analysis about the compromise the cost, schedule and the performance. The second is the analysis of large problem into small problems which can solved. We have found the solution considering components of the interface through the systematic perspective. Conclusion: Common factors and essential factors presented in this study will properly help to introduce the individual management innovation activities for the each business sector and implement management innovation. After this study, new literature research that reflect new studies should accomplish steadily.

• Journal of Soil and Groundwater Environment
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• v.12 no.5
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• pp.86-97
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• 2007

The principal component analysis was performed to identify the general characteristics of groundwater level changes from 202 deep and 112 shallow wells monitoring data, respectively, which came from the National Groundwater Monitoring Stations operated by KWATER with time spans of 156 continuous weeks from 2003 to 2005. Eight principal components, which accounted for 80% of the variability of the original time series, were extracted for water levels of shallow and deep monitoring wells. As a result of cluster analysis using the loading value of three principal components for shallow wells, shallow monitoring wells were divided into 3 groups which were characterized with a response time to rainfall (Group 1: 4.6 days, Group 2: 24.1 days, Group 3: 1.4 days), average long-term trend of water level (Group 1: $2.05{\times}10^{-4}$ m/day, Group 2: $-7.85{\times}10^{-4}$ m/day, Group 3: $-3.51{\times}10^{-5}$ m/day) and water level difference (Group 1 < Group 2 < Group 3). Additionally, they showed significant differences according to a distance to the nearest stream from well (Group 3 < Group 2 < Group 1), topographic slope of well site (Group 3: plain region, Group 1: mountainous region) and groundwater recharge rate (Group 3 < Group 2 < Group 1) with a p-value of 0.05.

• Journal of KIISE:Databases
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• v.37 no.1
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• pp.1-11
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• 2010

Recently, there has been a growing interest in the processing of continuous queries over multiple data streams. When the arrival rates of tuples exceed the memory capacity of the system, a load shedding technique is used to avoid the system becoming overloaded by dropping some subset of input tuples. In this paper, we propose an effective load shedding algorithm for multi-way windowed joins over multiple data streams. Most previous load shedding algorithms estimate the productivity of each tuple, i.e., the number of join output tuples produced by the tuple, based on its "join attribute value" and drop tuples with the lowest productivity. However, the productivity of a tuple cannot be accurately estimated from its join attribute value when the join attribute values are unique and do not repeat, or the distribution of the join attribute values changes over time. For these cases, we estimate the productivity of a tuple based on its "arrival order" on data streams, rather than its join attribute value. The proposed method can effectively estimate the productivity of a tuple even when the productivity of a tuple cannot be accurately estimated from its join attribute value. Through extensive experiments and analysis, we show that our proposed method outperforms the previous methods in terms of effectiveness and efficiency.

• Journal of KIISE
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• v.43 no.12
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• pp.1396-1403
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• 2016

In streaming data analysis where underlying data distribution may be changed or the concept of interest can drift with the progress of time, the ability to adapt to concept drift can be very powerful especially in the process of incremental learning. In this paper, we develop a general framework for an adaptive incremental classifier on data stream with concept drift. A distribution, representing the performance pattern of a classifier, is constructed by utilizing the distance between the confidence score of a classifier and a class indicator vector. A hypothesis test is then performed for concept drift detection. Based on the estimated p-value, the weight of outdated data is set automatically in updating the classifier. We apply our proposed method for two types of linear discriminant classifiers. The experimental results on streaming data with concept drift demonstrate that the proposed adaptive incremental learning method improves the prediction accuracy of an incremental classifier highly.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.4
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• pp.163-176
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• 1993

A methodology based on the influence coefficient algorithm was established for the optimal calibration of QUAL2E reaction coefficients. It was applied to the stream sections from the Chungju Dam to the downstream end of the South Han River. A water budget analysis using the monthly records of reservoir inflows and outflows in 1990 was made to determine tributary inflows. Estimated tributary inflows were used, together with the monthly records of water quality measurements in 1990, for the calibration of reaction coefficients. Simulated quality constituents were chl.a. nitrogen cycles, phosphorus cycles. BOD and DO. A sensitivity analysis was made to determine significant reaction coefficients, and as a result 11 reaction coefficients were selected as calibration parameters. The influence coefficient algorithm applied to the calibration of QUAL2E reaction coefficients proved to be a useful one yielding a rapid convergence. Each calibration parameter converged to an optimum value within 3 iterations.

• Journal of Korea Water Resources Association
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• v.38 no.3 s.152
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• pp.245-257
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• 2005

The purpose of the present study is examining the changes of runoff characteristics and extracting hydrologic parameters by applying ModClark model on grid divided watershed. Bocheong stream basin in Geum River system, one of the representative watersheds of IHP projects, is selected. Hydrology-based topographical informations are calculated using GIS data in the HEC-GeoHMS V1.1 extension in Arcview 3.2. The ModClark model requires precipitation data in a gridded format. The gridded data must be recorded in the HEC Data Storage System file format. Therefore, kriging method was used to interpolate the point values to create a grid that gives each cell over the entire watershed a precipitation value. Hec-DSSVue program was used to create DSS file for the rain gage data. The completed HEC-HMS model was calibrated for use in simulating three measured storm events and cell size of 10000m, 5000m, 2000m, 1000m was chosen for the application. As the result of applying distributed rainfall-runoff model to analyze relatively good agreement for peak discharge, runoff volume and peak time.