• Survey Research
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• v.13 no.1
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• pp.135-158
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• 2012

Korean telephone surveys have been based on landline telephone directory or RDD(Random Digit Dialing) method. These days, however, there has been an increase of the households with no landline, or households with the line but not willing to register in the directory. Moreover, it is hard to contact young people or office workers who are usually staying out of home in the daytime. Due to these issues above, the predictability of election polls gets weaker. Especially, low accessibility to those who stay out of home when the poll's done, results in predictions with positive inclination toward conservatism. A solution to resolve this problem is to contact respondents by using both mobile and landline phones-via landline phone to those who are at home and via mobile phone to those who are out of home in the daytime(Mixed Mode Survey, hereafter MMS). To conduct MMS, 1) we need to obtain the sampling frames for the landline and mobile surveys, and 2) we need to decide the proportion of sample size of both. In this paper, we propose a heuristic method for conducting MMS. The method uses RDD for the landline phone survey, and the access panel list for the mobile phone survey. The proportion of sample sizes between landline and mobile phones are determined based on the 'Lifestyle and Time Use Study' conducted by Statistics Korea. As a case study, 4 election polls were conducted in the periods of the special election for the mayor of Seoul on Oct 26th, 2011. From the initial 3 polls, reactions and responses regarding the issues raised during the survey period were appropriately covered, and the final poll showed a very close prediction to the real election result.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.763-774
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• 2020

Wind data forecasted from the numerical weather prediction (NWP) model is generally used as the first-guess of the target tracking process to obtain the atmospheric motion vectors(AMVs) because it increases tracking accuracy and reduce computational time. However, there is a contradiction that the NWP model used as the first-guess is used again as the reference in the AMVs verification process. To overcome this problem, model-independent first guesses are required. In this study, we propose the AMVs derivation from Lucas and Kanade optical flow method and then using it as the first guess. To retrieve AMVs, Himawari-8/AHI geostationary satellite level-1B data were used at 00, 06, 12, and 18 UTC from August 19 to September 5, 2015. To evaluate the impact of applying the optical flow method on the AMV derivation, cross-validation has been conducted in three ways as follows. (1) Without the first-guess, (2) NWP (KMA/UM) forecasted wind as the first-guess, and (3) Optical flow method based wind as the first-guess. As the results of verification using ECMWF ERA-Interim reanalysis data, the highest precision (RMSVD: 5.296-5.804 ms^-1) was obtained using optical flow based winds as the first-guess. In addition, the computation speed for AMVs derivation was the slowest without the first-guess test, but the other two had similar performance. Thus, applying the optical flow method in the target tracking process of AMVs algorithm, this study showed that the optical flow method is very effective as a first guess for model-independent AMVs derivation.

• Horticultural Science & Technology
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• v.29 no.6
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• pp.633-640
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• 2011

Brassica rapa is an A genome model species for Brassica crop genetics, genomics, and breeding. With the completion of sequencing the B. rapa genome, functional analysis of the genome is forthcoming issue. The expressed sequence tags are fundamental resources supporting annotation and functional analysis of the genome including identification of tissue-specific genes and promoters. As of July 2011, 147,217 ESTs from 39 cDNA libraries of B. rapa are reported in the public database. However, little information can be retrieved from the sequences due to lack of organized databases. To leverage the sequence information and to maximize the use of publicly-available EST collections, the Brassica rapa tissue-specific EST database (BrTED) is developed. BrTED includes sequence information of 23,962 unigenes assembled by StackPack program. The unigene set is used as a query unit for various analyses such as BLAST against TAIR gene model, functional annotation using MIPS and UniProt, gene ontology analysis, and prediction of tissue-specific unigene sets based on statistics test. The database is composed of two main units, EST sequence processing and information retrieving unit and tissue-specific expression profile analysis unit. Information and data in both units are tightly inter-connected to each other using a web based browsing system. RT-PCR evaluation of 29 selected unigene sets successfully amplified amplicons from the target tissues of B. rapa. BrTED provided here allows the user to identify and analyze the expression of genes of interest and aid efforts to interpret the B. rapa genome through functional genomics. In addition, it can be used as a public resource in providing reference information to study the genus Brassica and other closely related crop crucifer plants.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.2
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• pp.219-229
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• 2020

Objective: Considering the physiological and clinical importance of leptin receptor (LEPR) in regulating obesity and the fact that porcine LEPR expression is not known to be controlled by lncRNAs and miRNAs, we aim to characterize this gene as a potential target of SSC-miR-323 and the lncRNA TCONS_00010987. Methods: Bioinformatics analyses revealed that lncRNA TCONS_00010987 and LEPR have SSC-miR-323-binding sites and that LEPR might be a target of lncRNA TCONS_00010987 based on cis prediction. Wild-type and mutant TCONS_00010987-target sequence fragments and wild-type and mutant LEPR 3'-UTR fragments were generated and cloned into pmiRRB-REPORT^TM-Control vectors to construct respective recombinant plasmids. HEK293T cells were co-transfected with the SSC-miR-323 mimics or a negative control with constructs harboring the corresponding binding sites and relative luciferase activities were determined. Tissue expression patterns of lncRNA TCONS_00010987, SSC-miR-323, and LEPR in Anqing six-end-white (AQ, the obese breed) and Large White (LW, the lean breed) pigs were detected by real-time quantitative polymerase chain reaction; backfat expression of LEPR protein was detected by western blotting. Results: Target gene fragments were successfully cloned, and the four recombinant vectors were constructed. Compared to the negative control, SSC-miR-323 mimics significantly inhibited luciferase activity from the wild-type TCONS_00010987-target sequence and wild-type LEPR-3'-UTR (p<0.01 for both) but not from the mutant TCONS_00010987-target sequence and mutant LEPR-3'-UTR (p>0.05 for both). Backfat expression levels of TCONS_00010987 and LEPR in AQ pigs were significantly higher than those in LW pigs (p<0.01), whereas levels of SSC-miR-323 in AQ pigs were significantly lower than those in LW pigs (p<0.05). LEPR protein levels in the backfat tissues of AQ pigs were markedly higher than those in LW pigs (p<0.01). Conclusion: LEPR is a potential target of SSC-miR-323, and TCONS_00010987 might act as a sponge for SSC-miR-323 to regulate LEPR expression.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.95-108
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• 2011

TThis is a study of the personalization method that intelligently adapts the level of clustering considering purchasing index of a customer. In the e-biz era, many companies gather customers' demographic and transactional information such as age, gender, purchasing date and product category. They use this information to predict customer's preferences or purchasing patterns so that they can provide more customized services to their customers. The previous Customer-Segmentation method provides customized services for each customer group. This method clusters a whole customer set into different groups based on their similarity and builds predictive models for the resulting groups. Thus, it can manage the number of predictive models and also provide more data for the customers who do not have enough data to build a good predictive model by using the data of other similar customers. However, this method often fails to provide highly personalized services to each customer, which is especially important to VIP customers. Furthermore, it clusters the customers who already have a considerable amount of data as well as the customers who only have small amount of data, which causes to increase computational cost unnecessarily without significant performance improvement. The other conventional method called 1-to-1 method provides more customized services than the Customer-Segmentation method for each individual customer since the predictive model are built using only the data for the individual customer. This method not only provides highly personalized services but also builds a relatively simple and less costly model that satisfies with each customer. However, the 1-to-1 method has a limitation that it does not produce a good predictive model when a customer has only a few numbers of data. In other words, if a customer has insufficient number of transactional data then the performance rate of this method deteriorate. In order to overcome the limitations of these two conventional methods, we suggested the new method called Intelligent Customer Segmentation method that provides adaptive personalized services according to the customer's purchasing index. The suggested method clusters customers according to their purchasing index, so that the prediction for the less purchasing customers are based on the data in more intensively clustered groups, and for the VIP customers, who already have a considerable amount of data, clustered to a much lesser extent or not clustered at all. The main idea of this method is that applying clustering technique when the number of transactional data of the target customer is less than the predefined criterion data size. In order to find this criterion number, we suggest the algorithm called sliding window correlation analysis in this study. The algorithm purposes to find the transactional data size that the performance of the 1-to-1 method is radically decreased due to the data sparity. After finding this criterion data size, we apply the conventional 1-to-1 method for the customers who have more data than the criterion and apply clustering technique who have less than this amount until they can use at least the predefined criterion amount of data for model building processes. We apply the two conventional methods and the newly suggested method to Neilsen's beverage purchasing data to predict the purchasing amounts of the customers and the purchasing categories. We use two data mining techniques (Support Vector Machine and Linear Regression) and two types of performance measures (MAE and RMSE) in order to predict two dependent variables as aforementioned. The results show that the suggested Intelligent Customer Segmentation method can outperform the conventional 1-to-1 method in many cases and produces the same level of performances compare with the Customer-Segmentation method spending much less computational cost.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.2
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• pp.53-69
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• 2020

The increase of the impermeable area due to industrialization and urban development distorts the hydrological circulation system and cause serious stream drying phenomena. In order to manage this, it is necessary to develop a technology for impact assessment of stream drying phenomena, which enables quantitative evaluation and prediction. In this study, the cause of streamflow reduction was assessed for dam and weir watersheds in the five major river basins of South Korea by using distributed hydrological model DrySAT-WFT (Drying Stream Assessment Tool and Water Flow Tracking) and GIS time series data. For the modeling, the 5 influencing factors of stream drying phenomena (soil erosion, forest growth, road-river disconnection, groundwater use, urban development) were selected and prepared as GIS-based time series spatial data from 1976 to 2015. The DrySAT-WFT was calibrated and validated from 2005 to 2015 at 8 multipurpose dam watershed (Chungju, Soyang, Andong, Imha, Hapcheon, Seomjin river, Juam, and Yongdam) and 4 gauging stations (Osucheon, Mihocheon, Maruek, and Chogang) respectively. The calibration results showed that the coefficient of determination (R²) was 0.76 in average (0.66 to 0.84) and the Nash-Sutcliffe model efficiency was 0.62 in average (0.52 to 0.72). Based on the 2010s (2006~2015) weather condition for the whole period, the streamflow impact was estimated by applying GIS data for each decade (1980s: 1976~1985, 1990s: 1986~1995, 2000s: 1996~2005, 2010s: 2006~2015). The results showed that the 2010s averaged-wet streamflow (Q95) showed decrease of 4.1~6.3%, the 2010s averaged-normal streamflow (Q185) showed decreased of 6.7~9.1% and the 2010s averaged-drought streamflow (Q355) showed decrease of 8.4~10.4% compared to 1980s streamflows respectively on the whole. During 1975~2015, the increase of groundwater use covered 40.5% contribution and the next was forest growth with 29.0% contribution among the 5 influencing factors.

• Korean Journal of Occupational Health Nursing
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• v.11 no.1
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• pp.13-30
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• 2002

Industrial shift workers feels suffer mental stresses which are caused by unfamiliar day sleep, noisy environment, sleeping disorder by bright light, unusual contacts with family, difficulty in meeting with friends or having formal social meetings and other social limitations such as the use of transportation. Such stresses influence health of the workers negatively. Thus the health promotion policy for shift workers should be made considering the workers' ways of living and shift work specially. This study attempted to provide basic information for development of the health promotion program for industrial shift workers by examining predictive factors influencing health promotion behaviors of those workers. In designing the study, three power generation plants located in Pusan and south Kyungsang province were randomly selected and therefrom 280 workers at central control, boiler and turbine rooms and environmental chemistry parts whose processes require shift works were sampled as subjects of the study. Data were collected two times from September 17 to October 8, 1999 using questionnaires with helps of safety and health managers of the plants. The questionnaires were distributed through mails or direct visits. Means for the study included the measurement tool of health promotion behavior provided by Park(1995), the tool of self-efficacy measurement by Suh(1995), the tool of internal locus of control measurement by Oh(1987), the measurement tool of perceived health state by Park(1995) and the tool of social support measurement by Paek(1995). The collected data were analyzed using SPSS program. Controlling factors of the subjects were evaluated in terms of frequency and percentage ratio Perceived factors and health promotion behaviors of the subjects were done so in terms of mean and standard deviation, and average mark and standard deviation, respectively. Relations between controlling and perceived factors were analyzed using t-test and ANOVA and those between perceived factors and the performance of health promotion behaviors, using Pearson's Correlation Coefficient. The performance of health promotion behaviors was tested using t-test, ANOVA and post multi-comparison (Scheffe test). Predictive factors of health promotion behavior were examined through the Stepwise Multiple Regression Analysis. Results of the study are summarized as follows. 1. The performance of health promotion behaviors by the subjects was evaluated as having the value of mean, $161.27{\pm}26.73$ points(min.:60, max.:240) and average mark, $2.68{\pm}0.44$ points(min.:1, max.:4). When the performance was analyzed according to related aspects, it showed the highest level in harmonious relation with average mark, $3.15{\pm}.56$ points, followed by hygienic life($3.03{\pm}.55$), self-realization ($2.84{\pm}.55$), emotional support($2.73{\pm}.61$), regular meals($2.71{\pm}.76$), self-control($2.62{\pm}.63$), health diet($2.62{\pm}.56$), rest and sleep($2.60{\pm}.59$), exercise and activity($2.53{\pm}.57$), diet control($2.52{\pm}.56$) and special health management($2.06{\pm}.65$). 2. In relations between perceived factors of the subjects(self-efficacy, internal locus of control, perceived health state) and the performance of health promotion behaviors, the performance was found having significantly pure relations with self-efficacy (r=.524, P=.000), internal locus of control (r=.225, P=.000) and perceived health state(r=.244, P=.000). The higher each evaluated point of the three factors was, the higher the performance was in level. 3. When relations between the controlling factors(demography-based social, health-related, job-related and human relations characteristics) and the performance of health promotion behaviors were analyzed, the performance showed significant differences according to marital status (t=2.09, P= .03), religion(F=3.93, P= .00) and participation in religious activities (F=8.10, P= .00) out of demography-based characteristics, medical examination results (F=7.20, P= .00) and methods of the collection of health knowledge and information(F=3.41, P= .01) and methods of desired health education(F=3.41, P= .01) out of health-related characteristics, detrimental factors perception(F=4.49, P= .01) and job satisfaction(F=8.41, P= .00) out of job-related characteristics and social support(F=14.69, P= .00) out of human relations characteristics. 4. The factor which is a variable predicting best the performance of health promotion behaviors by the subjects was the self-efficacy accounting for 27.4% of the prediction, followed by participation in religious activities, social support, job satisfaction, received health state and internal locus of control in order all of which totally account for 41.0%. In conclusion, the predictive factor which most influence the performance of health promotion behaviors by shift workers was self-efficacy. To promote the sense, therefore, it is necessary to develop the nursing intervention program considering predictive factors as variables identified in this study. Further industrial nurses should play their roles actively to help shift workers increase their capability of self-management of health.

• The Journal of Engineering Geology
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• v.22 no.3
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• pp.343-351
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• 2012

This study proposes a modified equation to calculate the factor of safety for an infinite slope considering the saturation depth ratio as a new variable calculated from rainfall infiltration into unsaturated soil. For the proposed equation, this study introduces the concepts of the saturation depth ratio and subsurface flow depth. Analysis of the factor of safety for an infinite slope is conducted by the sequential calculation of the effective upslope contributing area, subsurface flow depth, and the saturation depth ratio based on quasi-dynamic wetness index theory. The calculation process makes it possible to understand changes in the factor of safety and the infiltration behavior of individual rainfall events. This study analyzes stability changes in an infinite slope, considering the saturation depth ratio of soil, based on the proposed equation and the results of soil column tests performed by Park et al. (2011 a). The analysis results show that changes in the factor of safety are dependent on the saturation depth ratio, which reflects the rainfall infiltration into unsaturated weathered gneiss soil. Under continuous rainfall with intensities of 20 and 50 mm/h, the time taken for the factor of safety to decrease to less than 1.3 was 2.86-5.38 hours and 1.34-2.92 hours, respectively; in the case of repeated rainfall events, the time taken was between 3.27 and 5.61 hours. The results demonstrate that it is possible to understand changes in the factor of safety for an infinite slope dependent on the saturation depth ratio.

• 대한공업교육학회지
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• v.38 no.2
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• pp.267-286
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• 2013

Recently, the advanced company has been sparing no efforts in improving necessary core knowledge and technology to achieve outstanding work performance. In this rapidly changing knowledge-based society, the company has confronted the task of creating a high value-added knowledge. The role of R&D workforce that corresponds to the characteristic and role of knowledge worker is getting more significant. As the life cycle of technical knowledge and skill shortens, in every industry, the technical knowledge and skill have become essential elements for successful business. It is difficult to improve competitiveness of the company without enhancing the competency of individual and organization. As the competency development which is a part of human resource management in the company is being spread now, it is required to focus on the research of determining necessary competency and to analyze the competency of a core organization in the research institute. 'H' is the semiconductor manufacturing company which has a affiliated research institute with its own R&D engineers. Based on focus group interview and job analysis data, vision and necessary competency were confirmed. And to confirm whether the required competency by job is different or not, analysis was performed by dividing members into workers who are in charge of circuit design and design before process development and who are in the process actualization and process development. Also, this research included members' importance awareness of the determined competency. The interview and job analysis were integrated and analyzed after arranging by groups and contents and the analyzed results were resorted after comparative analysis with a competency dictionary of Spencer & Spencer and competency models which are developed from the advanced research. Derived main competencies are: challenge, responsibility, and prediction/responsiveness, planning a new business, achievement -oriented, training, cooperation, self-development, analytic thinking, scheduling, motivation, communication, commercialization of technology, information gathering, professionalism on the job, and professionalism outside of work. The highly required competency for both jobs was 'Professionalism'. 'Attitude', 'Performance Management', 'Teamwork' for workers in charge of circuit design and 'Challenge', 'Training', 'Professionalism on the job' and 'Communication' were recognized to be required competency for those who are in charge of process actualization and process development. With above results, this research has determined the necessary competency that the 'H' company's affiliated research institute needs and found the difference of required competency by job. Also, it has suggested more enthusiastic education methods or various kinds of education by confirming the importance awareness of competency and individual's level of awareness about the competency.

• Horticultural Science & Technology
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• v.28 no.5
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• pp.768-776
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• 2010

This study was conducted to predict number and fresh weight of leaves, and total leaf area of a single-stemmed rose 'Vital' based on the accumulated thermal units, and to develop a model of shoot development for the prediction of the time when the flowering shoot reaches a phenological stage in a plant factory system. The base temperature ($T_b$), optimum temperature ($T_{opt}$), and maximum temperature ($T_{max}$) were estimated by regressing the rate of shoot development against the temperature gradient. The rate of shoot development ($R$, $d^{-1}$) for the phase from cutting to bud break (CT-BB) was best described by a linear model $R_b$ ($d^{-1}$) = -0.0089 + $0.0016{\cdot}temp$. The rate of shoot development for the phase from bud break to harvest (BB-HV) was fitted to the parabolic model $R_h$ ($d^{-1}$) = $-0.0001{\cdot}temp^2$ + $0.0054{\cdot}temp$ - 0.0484. The $T_b$, $T_{opt}$, and $T_{max}$ values were 5.56, 27.0, and $42.7^{\circ}C$, respectively. The $T_b$ value was used in the thermal unit computations for the shoot development. Number of leaves, leaf area (LA), and leaf fresh weight showed sigmoidal curves regardless of the cut time. The shoot development and leaf area model was described as a sigmoidal function using thermal units. Leaf area was described as LA = 578.7 $[1+(thermal units/956.1)^{-8.54}]^{-1}$. Estimated and observed shoot length and leaf fresh weight showed a reasonably good fit with 1.060 ($R^2=0.976^{***}$) and 1.043 ($R^2=0.955^{***}$), respectively. The average thermal units required from cutting to transplant and from transplant to harvest stages were $426{\pm}42^{\circ}C{\cdot}d$ and $783{\pm}24^{\circ}C{\cdot}d$, respectively.