• Korean Journal of Social Welfare
• /
• v.68 no.2
• /
• pp.107-130
• /
• 2016

This study is aimed at the exploratory research on the influence of the obligation of extension of the retirement age on the baby boom generation. The basic question of this study is about which of the baby boom generation can get how much benefit according as the extension of the retirement age becomes compulsory. The extension of the retirement age is the system that can be applied to regular full-time workers. Accordingly, this study is intending to analyze the characteristics of the workers having a high likelihood for benefits from extension of the retirement age by tracing the economic activity state and labor history of the baby boomers. For this purpose, this study looked into the change of the economic activity state by age cohort of the male baby boomers based on the data for the Korea Labor Panel's 4th(2001) & 17th(2014)year. Using Survival analysis, this study also analyzed who will continue to remain as a regular full-time wage earner. As the result of the analysis, it was found that the more the cohort ages of baby boomers increased, the smaller the probability of remaining as a regular full-time wage earner, and the group who can get benefits from extension of the retirement age was predicted to account for only 11.4% level among the baby boomers. In addition, the result showed that there was a high likelihood of getting more benefits from extension of the retirement age when the baby boomers worked for the government-invested institution, corporate bodies, and government organizations rather than working for private enterprises. Thus, it can be safely said that there might appear a generational conflict due to extension of the retirement age in that such jobs coincide with the ones favored by the rising generation.

• Journal of dental hygiene science
• /
• v.17 no.6
• /
• pp.463-471
• /
• 2017

The purpose of this study was to examine the causes of career interruptions among dental hygienists, institutional measures required for their long service and ways of creating a stable employment culture for them in determine how to resolve labor shortage, create stable jobs, and step up the reemployment of idle manpower. In addition, the following suggestions are made for the establishment of a stable employment culture for dental hygienists by analyzing related literature, research materials, and information such as forums for establishing appropriate jobs for female dental workers. First, a system should be set up to prevent career interruption among dental hygienists. The work environment should be improved to prevent career breaks, and the wages, working hours, and working style should be efficiently structured to maintain the tenure of employees. Second, a plan should be devised to make use of idle manpower, and a variety of necessary programs should be developed. With respect to regular working hours, the time conversion system should be used, which reduces the amount of time one would want to work while receiving a national subsidy. Third, dental hygienists working in different occupations for marriage, childbirth, childcare, school and personal hygiene should make a way to return to the dental system immediately when they want. Fourth, the government should take institutional measures and offer down-to-earth support and benefits for women consideration their social characteristics to guarantee a balance between work and childcare.

• Journal of the Korean Geotechnical Society
• /
• v.38 no.7
• /
• pp.5-24
• /
• 2022

The current performance evaluation of slope anchors qualitatively determines the physical bonding between the anchor head and ground as well as cracks or breakage of the anchor head. However, such performance evaluation does not measure these primary factors quantitatively. Therefore, the time-dependent management of the anchors is almost impossible. This study is an evaluation of the 3D numerical model by SfM which combines UAS images with terrestrial LiDAR to collect numerical data on the damage factors. It also utilizes the data for the quantitative maintenance of the anchor system once it is installed on slopes. The UAS 3D model, which often shows relatively low precision in the z-coordinate for vertical objects such as slopes, is combined with terrestrial LiDAR scan data to improve the accuracy of the z-coordinate measurement. After validating the system, a field test is conducted with ten anchors installed on a slope with arbitrarily damaged heads. The damages (such as cracks, breakages, and rotational displacements) are detected and numerically evaluated through the orthogonal projection of the measurement system. The results show that the introduced system at the resolution of 8K can detect cracks less than 0.3 mm in any aperture with an error range of 0.05 mm. Also, the system can successfully detect the volume of the damaged part, showing that the maximum damage area of the anchor head was within 3% of the original design guideline. Originally, the ground adhesion to the anchor head, where the z-coordinate is highly relevant, was almost impossible to measure with the UAS 3D numerical model alone because of its blind spots. However, by applying the combined system, elevation differences between the anchor bottom and the irregular ground surface was identified so that the average value at 20 various locations was calculated for the ground adhesion. Additionally, rotation angle and displacement of the anchor head less than 1" were detected. From the observations, the validity of the 3D numerical model can obtain quantitative data on anchor damage. Such data collection can potentially create a database that could be used as a fundamental resource for quantitative anchor damage evaluation in the future.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.27 no.6
• /
• pp.152-161
• /
• 2023

In general, large-capacity hydrogen storage vessels, typically in the form of vertical cylindrical vessels, are constructed using steel materials. These vessels are anchored to foundation slabs that are specially designed to suit the environmental conditions. This anchoring method involves pre-installed anchors on top of the concrete foundation slab. However, it's important to note that such a design can result in concentrated stresses at the anchoring points when external forces, such as seismic events, are at play. This may lead to potential structural damage due to anchor and concrete damage. For this reason, in this study, it selected an vertical hydrogen storage vessel based on site observations and created a 3D finite element model. Artificial seismic motions made following the procedures specified in ICC-ES AC 156, as well as domestic recorded earthquakes with a magnitude greater than 5.0, were applied to analyze the structural behavior and performance of the target structures. Conducting experiments on a structure built to actual scale would be ideal, but due to practical constraints, it proved challenging to execute. Therefore, it opted for an analytical approach to assess the safety of the target structure. Regarding the structural response characteristics, the acceleration induced by seismic motion was observed to amplify by approximately ten times compared to the input seismic motions. Additionally, there was a tendency for a decrease in amplification as the response acceleration was transmitted to the point where the centre of gravity is located. For the vulnerable components, specifically the sub-system (support columns and anchorages), the stress levels were found to satisfy the allowable stress criteria. However, the concrete's tensile strength exhibited only about a 5% margin of safety compared to the allowable stress. This indicates the need for mitigation strategies in addressing these concerns. Based on the research findings presented in this paper, it is anticipated that predictable load information for the design of storage vessels required for future shaking table tests will be provided.

• Journal of Venture Innovation
• /
• v.6 no.4
• /
• pp.23-40
• /
• 2023

This study examines the customer value factors affecting the intention to continue using the mobile app of department stores, which are traditional offline retailers, in the retail industry that is rapidly digitalizing and becoming mobile. This study clarifies multidimensional customer value in three dimensions; functional, convenience, and social. Functional value refers to the integrated channel, and consistent customer experience provided between channels in the omnichannel retail environment, while convenience value is the convenience of saving time and effort save while customers use a mobile app. Social value refers to the improvement of social approval or social self-concept occurring due to the use of products or services related to green marketing within the mobile app of the department store. The influence of each on the dependent variable, the mobile app's continuous use intention, was analyzed by using the three dimensions of customer value as independent variables. Data was collected from customers who have a history of using the mobile app of Shinsegae Department Store in Korea, and a confirmatory analysis was conducted using Smart PLS 4.0. The analysis results showed that all three dimensions of customer value; functional value, convenience value, and social value, had a positive (+) influence on customers' intention to continue using the mobile app, and the influence of functional value had the greatest impact. As functional value appears to be the most important influencing factor due to the omnichannel retail trend by advancement of technology, it suggests that it is important for department stores, and offline retailers, to provide integrated channels. This provides insights into the direction of customer-centered strategy formulation for activating department store mobile apps and suggests basic analytical data for customized services and marketing activities that department stores can effectively meet the changing expectations and demands of customers through new mobile channels rather than existing offline channels.

• Journal of Intelligence and Information Systems
• /
• v.26 no.1
• /
• pp.47-73
• /
• 2020

KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.