• Journal of Labour Economics
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• v.42 no.3
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• pp.75-98
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• 2019

This paper examines the impact of on-the-job training (OJT) programs on turnover rates and employment status in the labor market. Exploiting the administrative data (the Employment Insurance Database), we apply the propensity score matching method to investigate 1) whether OJT participation increases the probability of remaining in the labor market after the job training, and 2) whether trainees are more likely to transition to a new employer. Our findings reveal positive effects of OJT on the continuous employment (2.4~5.3%p). We also observe that trainees show lower rates of turnover for some part of the study period, from 2008 to 2015.

• The Journal of Fisheries Business Administration
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• v.53 no.3
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• pp.85-101
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• 2022

This study analyzed the performance of the national fishing port development project, which lacked ex-post impact evaluation despite a lot of investment in terms of fishery income opportunities. Using micro data from the Census of Agriculture, Forestry, and Fisheries, the sales amount of fishery products and the proportion of fishery-related businesses were used as performance indicators. The fishery households in the fishing port area (treatment group) and those not in the area (control group) were classified through data pre-processing, and factors unrelated to the fishing ports were controlled using the propensity score matching difference-in-difference method. The analysis target is six fishing ports with large investment in from 2010 to 2014. As a result of the analysis, it was confirmed that the sales of fishery products increased significantly in four of the six fishing ports, and the proportion of fishery-related businesses increased in two fishing ports. The analysis method of this study can be fully utilized in the evaluation of the Fishing Community New Deal 300 Project, which is in need of performance analysis.

• Economic Analysis
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• v.27 no.2
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• pp.41-70
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• 2021

Using the 2017 and 2019 Survey on Immigrants' Living Conditions and Labour Force, we examine how the job training programs in Korea affect immigrants' labor market outcomes by applying the propensity score matching method. The results show that job training programs increase the probability of being employed by 6.4 percentage points and positively affect monthly wages. There is significant heterogeneity in the effects of job training effects across visa categories. For immigrants with work visas, the effect on the employment rate is relatively small, while the wage effect is considerably large. On the other hand, we do not find a positive wage effect for marriage migrants. Both the employment rate and the monthly wage increased through job training for permanent residents.

• Educational Technology International
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• v.25 no.1
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• pp.67-92
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• 2024

This study aims to verify the practical effectiveness of learning management system (LMS) by introducing a LMS enhancing digital assessment utilizing automatic item generation in order to strengthen college student's mathematics performance. Teaching assisted with digital assessment in the LMS was applied to college mathematics classes, and the research question is whether or not students in the classes utilizing the LMS perform better than the regular classes. In particular, a calculus course, which is the foundation of important artificial intelligence technology in the future, was utilized in this study. The participants of this study were 248 freshmen in science and engineering who were taking calculus courses at a small to mid-size university. A total of 156 freshmen were selected after applying a propensity score matching method (PSMM), 78 from classes utilizing the LMS and 78 from regular classes without the LMS assisted with the digital assessment. As a result, it was found that there was a statistically significant difference in the math academic growth of students who used the LMS and those who did not. In other words, when LMS was used in calculus, students' academic growth was greater. The results of this study are meaningful in that they observed students' academic growth and confirmed that LMS enables a positive role in students' academic growth. In addition, if digital assessment is strengthened and LMS that enables individualized learning analysis is introduced and implemented in educational institutions, it is expected to play a major role in strengthening students' academic performance.

• The Korean Journal of Applied Statistics
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• v.36 no.5
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• pp.415-445
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• 2023

Oftentimes, the time dependent treatment covariate and the time dependent confounders exist in observation studies. It is an important problem to correctly adjust for the time dependent confounders in the propensity score analysis. Recently, In the survival data, Hade et al. (2020) used a propensity score matching method to correctly estimate the treatment delay effect when the time dependent confounder affects time to the treatment time, where the treatment delay effects is defined to the delay in treatment reception. In this paper, we proposed the Cox model based marginal structural model (Cox-MSM) framework to estimate the treatment delay effect and conducted extensive simulation studies to compare our proposed Cox-MSM with the propensity score matching method proposed by Hade et al. (2020). Our simulation results showed that the Cox-MSM leads to more exact estimate for the treatment delay effect compared with two sequential matching schemes based on propensity scores. Example from study in treatment discontinuation in conjunction with simulated data illustrates the practical advantages of the proposed Cox-MSM.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1766-1784
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• 2014

Finger vein images contain rich oriented features. Local line binary pattern (LLBP) is a good oriented feature representation method extended from local binary pattern (LBP), but it is limited in that it can only extract horizontal and vertical line patterns, so effective information in an image may not be exploited and fully utilized. In this paper, an orientation-selectable LLBP method, called generalized local line binary pattern (GLLBP), is proposed for finger vein recognition. GLLBP extends LLBP for line pattern extraction into any orientation. To effectually improve the matching accuracy, the soft power metric is employed to calculate the matching score. Furthermore, to fully utilize the oriented features in an image, the matching scores from the line patterns with the best discriminative ability are fused using the Hamacher rule to achieve the final matching score for the last recognition. Experimental results on our database, MMCBNU_6000, show that the proposed method performs much better than state-of-the-art algorithms that use the oriented features and local features, such as LBP, LLBP, Gabor filter, steerable filter and local direction code (LDC).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.5
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• pp.1829-1837
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• 2010

During the last year, public expenditures which provided the central and local governments for boosting research and development (R&D) activities of the private sector has been constantly increasing. 17 percent of public total R&D expenditure supported to private sector and 9 percent of R&D expenditure in service sector were public R&D funding. However, studies evaluating the impact of public R&D subsidies are quite few. The aim of this study empirically investigate the average effects of public R&D subsidies on the innovation activities in private sector, specifically those engaged in Korean service firms by using Propensity Score Matching(PSM) method. The effect of R&D subsidies is derived from either qualitative and quantitative outcomes of innovation activities, which is defined as the difference between innovation outcome of the treatment group (receiving R&D subsidies) and that of the control group (non receiving R&D subsidies) after the matching method. As a result of empirical analysis, government R&D grants stimulate only firm-first innovation outcomes in service firms. It is represent that public R&D subsidies cannot be contributed to level of national innovation and the total amount of national innovation activities but can enhance firm competitiveness from increasing firm-first innovation activities.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.2
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• pp.69-76
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• 2018

Referring expressions are natural language constructions used to identify particular objects within a scene. In this paper, we propose a new deep neural network model for referring expression comprehension. The proposed model finds out the region of the referred object in the given image by making use of the rich information about the referred object itself, the context object, and the relationship with the context object mentioned in the referring expression. In the proposed model, the object matching score and the relationship matching score are combined to compute the fitness score of each candidate region according to the structure of the referring expression sentence. Therefore, the proposed model consists of four different sub-networks: Language Representation Network(LRN), Object Matching Network (OMN), Relationship Matching Network(RMN), and Weighted Composition Network(WCN). We demonstrate that our model achieves state-of-the-art results for comprehension on three referring expression datasets.

• Research in Community and Public Health Nursing
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• v.31 no.spc
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• pp.534-548
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• 2020

Purpose: This study was conducted to evaluate the prevalence and lifestyle habits of cardiovascular disease (CVD) according to the type of disability in Korean adults compared to adults without disability. Methods: This study was secondary data analysis using the National Health check-up database from 2010 to 2013. Among the total 395,627 adults aged 30~80, the physically disabled (n=21,614) and the mentally disabled (n=1,448) who met the diagnosis criteria were extracted and compared with non-disabled (n=372,565) through 1:2 propensity score matching for nine characteristics. Results: Prior to matching, the prevalence of CVD was 34.4% in individuals without disabilities, accounting for 53.8% in those with physical disabilities and 22.4% in those with mental disabilities, showing significant differences between groups (p<.001). After matching, compared to the individuals without disability, those with physically disabled had significantly higher prevalence of CVD and the average number of CVD (p<.001). The prevalence of hypertension, diabetes, and vascular disease was significantly higher in the physically disabled (p<.05). Drinking was significantly higher in the non-disabled than in the physically and mentally disabled, and smoking was more in the non-disabled than in the mentally disabled. Physical activity was found to be significantly less in both the physically and mentally disabled than in the non-disabled (p<.01). Conclusion: It is necessary to confirm the differences in the prevalence of CVD risk factors and lifestyle according to the type of disability, suggesting the development and verification of health promotion programs including physical activity for CVD prevention in the disabled with CVD risk factors.

• KDI Journal of Economic Policy
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• v.34 no.3
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• pp.133-186
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• 2012

This paper analyzes the effectiveness of social networks in finding jobs and estimates the value of job search network using the Korean Laber and Income Panel Study (KLIPS) dataset and utilizing the Difference-in-Difference Propensity Score Matching (PSM) methodology (Heckman et al., 1997). While the wide use of social networks in the Korean labor market is often perceived as 'nepotism,' this study confirms that social networks, by serving as an effective information transmitter between job search and recruitment, make a significant contribution to improving the adequacy of job matching in the domestic labor market. In order to verify the effectiveness of using social networks for getting jobs, this study looks into the cases of labor turnover using social networks and also not using it. In the aspect of individual satisfaction improvement relating to workplace and job duties, both cases of turnover turn out to experience an increased satisfaction by 2~3 points (on a 100-score scale). Meanwhile, as for the educational and technical adequacy improvement, no positive effects are found in the case of turnover without social networks, whereas the educational and technical adequacy improvement turns out to increase by 2.13 and 2.52 points, respectively, in the case of turnover using social networks. The effect of income increase through turnover using social networks registered 40,074 Korean won per month (as of 2010), which can be considered as the result from the improved educational and technical adequacy. Of all things being considered, the value of job search network per wage worker in the Korean society is estimated to be 18.72 million won in terms of life-cycle wage improvement, and 758.2 scores in terms of the improvement of working life satisfaction. Provided that the cash value of satisfaction score 1 is equivalent to 'n' times 10,000 won, the aggregate value of job search network is estimated to be 18.72+7.582n million won, which means the total amount of costs that a wage worker in the Korean society willingly pays to maintain and manage job networks for lifetime.