• Journal of Distribution Science
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• v.14 no.2
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• pp.65-72
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• 2016

Purpose - Recently on-the-job training (OJT) has become the most preferred training and development method with the emergence of the concept that workplace is the best place where learning take place. But many researchers argue that OJT is not helpful for the performance of organization because OJT is not systematic and mostly depend on quality of trainer. Since Jacobs & McGriffin introduced S-OJT (structured OJT), there has been plenty of researches. But most of the researches have focused mainly on employee's attitude and organizational performance caused by S-OJT and neglected a holistic approach of S-OJT as a system. S-OJT need to be analyzed comprehensively to understand training performance because S-OJT is operated as a system consist of input, process, and organizational context. Although S-OJT may create unintended consequences, there were few researches to explore them. Thus, the purpose of this study is to identify the critical success factors for S-OJT and to find unintended consequences of it. Research design, data and methodology - We conducted a case study on M business unit of A company which developed and has been implementing S-OJT program for years. We designed and prepared the process, collected and analyzed data for the study. We set the theoretical framework to analyze the case after reviewing theories and previous studies on S-OJT. We collected and analyzed internal reports and interview results of the employees of the M business unit. We tried to collect as many information as possible to secure the validity of the research results. Results - The critical success factors identified in the study are as follow. First, it is important to select and train proper trainers for S-OJT. Second, it is needed to develop structured training module. Third, organization have to use effective communication system like on-line community. Forth, trainer should have proper skills for training such as facilitating skill, coaching skill, and delivering skill etc. Fifth, proper learning place is needed. Sixth, organizational support is important especially, immediate supervisor support and concern is critical. Eleventh, it is needed to consider situational contexts. Among them, overload to the trainer will affect the effectiveness of S-OJT. In this study, we found an additional unintended consequence. "To teach is the best way to learn." Experience as a trainer give employee an opportunity to organize one's knowledge and skill and to attain facilitation skill, coaching skill, and relation skill. Thus, organization may use S-OJT to train the potential talent. Conclusions - Many organizations introduced S-OJT to train the newcomers because S-OJT drew attention as an important tool to develop employees. Following this trend, there has been increasing number of researches to find the results of S-OJT and identify the determinants of S-OJT success. However, most of the researches concentrated on finding effects of some factors neglecting holistic approach. This study tried to identify critical success factors affecting effectiveness of S-OJT by using case study and find additional unintended consequence. The results of the study will be useful for organizations which have a plan to adopt S-OJT.

• The Journal of Industrial Distribution & Business
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• v.11 no.8
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• pp.31-38
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• 2020

Purpose: This study uses 'Autoregressive Integrated Moving Average Model' to predict the impact of a sharp drop in the base rate due to COVID-19 at the present time when government policies for stabilizing house prices are in progress. The purpose of this study is to predict implications for the direction of the government's house policy by predicting changes in house transaction prices and house rental prices after a sharp cut in the base rate. Research design, data, and methodology: The ARIMA intervention model can build a model without additional information with just one time series. Therefore, it is a time-series analysis method frequently used for short-term prediction. After the subprime mortgage, which had shocked since the global financial crisis in April 2007, the bank's interest rate in 2020 is set at a time point close to zero at 0.75%. After that, the model was estimated using the interest rate fluctuations for the Bank of Korea base interest rate, the house transaction price index, and the house rental price index as event variables. Results: In predicting the change in house transaction price due to interest rate intervention, the house transaction price index due to the fall in interest rates was predicted to change after 3 months. As a result, it was 102.47 in April 2020, 102.87 in May 2020, and 103.21 in June 2020. It was expected to rise in the short term. In forecasting the change in house rental price due to interest rate intervention, the house rental price index due to the drop in interest rate was predicted to change after 3 months. As a result, it was 97.76 in April 2020, 97.85 in May 2020, and 97.97 in June 2020. It was expected to rise in the short term. Conclusions: If low interest rates continue to stimulate the contracted economy caused by COVID-19, it seems that there is ample room for house transaction and rental prices to rise amid low growth. Therefore, In order to stabilize the house price due to the low interest rate situation, it is considered that additional measures are needed to suppress speculative demand.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.2 s.308
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• pp.40-47
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• 2006

This paper proposes a multitoning method using threshold modulation of MJBNM(Modified Jointly Blue Noise Mask) for banding artifacts reduction. As banding artifacts in multitoning appear as uniform dot distributions around the intermediate output levels, such multitone output results in discontinuity and visually unpleasing patterns in smooth transition regions. Therefore, to reduce these banding artifacts, the proposed method rearranges the dot distribution by introducing pixels in the neighborhood of output levels that occurs banding artifacts. First of all principal cause of banding artifacts are analyzed using mathematical description. Based on this analytical result, a threshold modulation technique of MJBNM which takes account of chrominance error and correlation between channels is applied. The original threshold range of MJBNM is first scaled linearly sot that the minimum and maximum of the scaled range include two pixel more than adjacent two output levels that cover an input value. In an input value is inside the vicinity of any intermediate output levels produce banding artifacts, the output is set to one of neighboring output levels based on the pointwise comparison result according to threshold modulation parameter that determines the dot density and distribution. In this case, adjacent pixels are introduced at the position where the scaled threshold values are located between two output levels and the minimum and maximum threshold values. Otherwise, a conventional multitoning method is applied. As a result, the proposed method effectively decreased the appearance of banding artifacts around the intermediate output levels. To evaluate the quality of the multitone result, HVS-WRMSE according to gray level for gray ramp image and S-CIELAB color difference for color ramp image are compared with other methods.

• Journal of Internet Computing and Services
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• v.11 no.6
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• pp.13-20
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• 2010

This paper presents a measure to classify healthy persons and Parkinson disease patients from the foot pressure of healthy persons and that of Parkinson disease patients using gait analysis based characteristics extraction and Neural Network with Weighted Fuzzy Membership Functions (NEWFM). To extract the inputs to be used in NEWFM, in the first step, the foot pressure data provided by the PhysioBank and changes in foot pressure over time were used to extract four characteristics respectively. In the second step, wavelet coefficients were extracted from the eight characteristics extracted from the previous stage using the wavelet transform (WT). In the final step, 40 inputs were extracted from the extracted wavelet coefficients using statistical methods including the frequency distribution of signals and the amount of variability in the frequency distribution. NEWFM showed high accuracy in the case of the characteristics obtained using differences between the left foot pressure and the right food pressure and in the case of the characteristics obtained using differences in changes in foot pressure over time when healthy persons and Parkinson disease patients were classified by extracting eight characteristics from foot pressure data. Based on these results, the fact that differences between the left and right foot pressures of Parkinson disease patients who show a characteristic of dragging their feet in gaits were relatively smaller than those of healthy persons could be identified through this experiment.

• Journal of Life Science
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• v.24 no.5
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• pp.532-542
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• 2014

This study describe seasonal patterns in the variation of phytoplankton frequency in the water surface and basal layers and their spatial distributions at seven stations in Hwadang-ri, Goseng-gun in 2013. The phytoplankton community at Hwadang-ri was very diverse, with 60 taxa identified, representing three classes. Diatoms (Bacillariophyceae) exhibited the greatest diversity, with 41 taxa identified. These were followed by the dinoflagellates Dinophyceae, Cryptophyceae, and Eugenophyceae, with 16 taxa, two taxa, and one taxon, respectively. Water surfaces were shown with the relative individual density or abundance across areas. Except in January, Shannon-Weaver indices of diversity of the water surface layer were lower than those of the basal layer. In addition, evenness indices of the basal layer were higher than those of the water surface layer, except in January. For the community as a whole, the values of ${\beta}$-diversity were low for the seven stations: 1.125 for the water surface layer and 1.481 for the basal layer. Seasonal values for ${\beta}$-diversity were similar at the seven stations: 1.725 for the water surface layer and 1.347 for the basal layer. The phytoplankton community showed high taxonomic homogeneity in all four seasons, in addition to similar trends in seasonal development at depths in the same stations. However, the size distribution of the abundance and biomass showed a statistically significant west-east difference.

• Journal of fish pathology
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• v.20 no.3
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• pp.201-209
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• 2007

Viral hemorrhagic septicemia (VHS) is one of the most serious viral disease of farmed rainbow trout and some marine fishes in Europe and North America. It has been reported in various marine fish species of Asian countries and induced cause mass mortality in Japanese flounder (Paralichthys olivaceus) culturing in Korea. The aims of this study were to monitor VHSV in wild marine fishes and to give critical information for controling the disease through prophylactic methods. Prevalence of the viral disease, geological distribution and reservoir of the virus were investigated using wild marine fishes captured in southern coast and east china sea for two years. (Reverse Transcriptase Polymerase Chain Reaction) RT-PCR results showed that VHSV were detected in 17 (10.6%) out of 160 fish. G gene sequences of viral strains isolated in this study were closely related to that of a reference strain, KVHS01-1, belonging to VHSV genotype Ⅰ. The results suggest that some of wild marine fishes are VHSV carriers and may spread the pathogen directly to fish farmed in coastal area.

• Journal of fish pathology
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• v.20 no.3
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• pp.211-220
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• 2007

Red sea bream iridovirus disease (RSIVD) cause massive economic losses in marine aquaculture industry in Korea. The causative agent of this disease (RSIV) infects a wide range of fish species. The aims of this study were to monitor RSIV in wild marine fishes and to give critical information for controling the disease through prophylactic methods. Prevalence of the viral disease, geological distribution and reservoir of the virus were investigated using wild marine fishes captured in southern coast and east china sea for two years. (Polymerase Chain Reaction) PCR results showed that RSIV were detected in 39 (24.3%) out of 160 fish. MCP gene sequences of viral strains isolated in this study were closely related to that of a reference strain, red seabream-K, belonging to Megalocytivirus subgroup Ⅲ. The results suggest that some of wild marine fishes are RSIV carriers and may spread the pathogen directly to fish farmed in coastal area.

• Korean Journal of Weed Science
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• v.17 no.3
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• pp.262-268
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• 1997

The experiment was carried out to obtain the basic information of weed control in lowland rice field in Gyeongbug province. The results were as follows : In weed distribution on life cycle, annual weed was occupied by 56.5% and perennials were 43.5%, respectively. In morphological distribution of weeds, grass weed was 25.2%, sedges was 12.3% and broad leaf weeds was 62.5%. In particular, weed occurrence of grass weed was much more increased than that of 1971 and 1981 year. Dominant weed species was Echinochloa crusgralli, Sagittaria trifolia, Eleocharis kuroguwai and Monochoria vaginalis in plain land, mid alpine area, and cold salty wind area. Dominant weeds was approximately similar occurrence in normal soil and poorly drained soil Gelds, but sandy soil field was not. Echinochloa crusgalli was dominant in hand transplanting and direct seeding on dry paddy field. Meanwhile, in machine transplanting, Sagittaria trifolia and Ludwigia prostrate were dominant, and occurrence of Echinochloa crusgalli was increased to delaying transplanting. As a result, major dominant weed was Echinochloa crusgalli, Sagittaria trifolia, Ludwigia prostrate, Eleocharis kuroguwai, and Monochoria vaginalis in terms of predominance.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.403-410
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• 2004

Recently, studies of image analysis, as the preprocessing stage for medical image analysis or image retrieval, are actively carried out. This paper intends to propose a way of utilizing color components for image retrieval. For image retrieval, it is based on color components, and for analysis of color, CLCM (Color Level Co-occurrence Matrix) and statistical techniques are used. CLCM proposed in this paper is to project color components on 3D space through geometric rotate transform and then, to interpret distribution that is made from the spatial relationship. CLCM is 2D histogram that is made in color model, which is created through geometric rotate transform of a color model. In order to analyze it, a statistical technique is used. Like CLCM, GLCM (Gray Level Co-occurrence Matrix)[1] and Invariant Moment [2,3] use 2D distribution chart, which use basic statistical techniques in order to interpret 2D data. However, even though GLCM and Invariant Moment are optimized in each domain, it is impossible to perfectly interpret irregular data available on the spatial coordinates. That is, GLCM and Invariant Moment use only the basic statistical techniques so reliability of the extracted features is low. In order to interpret the spatial relationship and weight of data, this study has used Principal Component Analysis [4,5] that is used in multivariate statistics. In order to increase accuracy of data, it has proposed a way to project color components on 3D space, to rotate it and then, to extract features of data from all angles.

• Journal of Internet Computing and Services
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• v.9 no.5
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• pp.117-130
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• 2008

This paper proposes a stable and robust method to distinct the color similarity for clothes using the LBG algorithm under various light sources, Since the conventional methods, such as the histogram intersection and the accumulated histogram, are profoundly sensitive to the changing of light environments, the distinction of color similarity for the same cloth can be different due to the complicated light sources. To reduce the effects of the light sources, the properties of hue and saturation which consistently sustain the characteristic of the color under the various changes of light sources are analyzed to define the characteristic of the color distribution. In a two-dimensional space determined by the properties of hue and saturation, the LBG algorithm, a non-parametric clustering approach, is applied to examine the color distribution of images for each clothes. The color similarity of images is defined by the average of Euclidean distance between the mapping clusters which are calculated from the result of clustering of both images. To prove the stability of the proposed method, the results of the color similarity between our method and the traditional histogram analysis based methods are compared using a dozen of cloth examples that obtained under different light environments. Our method successively provides the classification between the same cloth image pair and the different cloth image pair and this classification of color similarity for clothe images obtains the 91.6% of success rate.