• Korea journal of population studies
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• v.29 no.3
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• pp.139-157
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• 2006

This study presents limitations of the old family supported system for the elderly being surfaced in the face of the changing life style of the people in today's industrialized, urban Korean society. The qualitative data used for this study are collected from the focus group discussions(FGD). The FGD data numbered a total of 43 participants who were divided into 8 different groups, each consisting of 5-6 respondents sorted out by sex and age as well as by their current cohabitation with their parents or having such experience in the past. The study paid special attention focusing on the values and the expectations regarding the elderly support and the family relationship. A critical reexamination of the old family support system for the elderly at this particular juncture is also a step forward necessary for the eventual formulation of policy measures by the state and the society to produce a new viable support system for the elderly in the future.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.4
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• pp.55-65
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• 2015

An increase in patients' medical expenses for their injury. accident and intoxication is a major challenge to improve the sustain-ability of a national health security system, and increasing medical expenses need be suppressed through improving relevant systems and/or efficiently operating and managing the health insurance. At this juncture, in Korea which has a high rate of injury incidence and mortality, it is necessary to estimate social and/or economic costs for injuries with a focus on their social effects. This research has examined the results of a Korea medical panel investigation conducted in 2008, which largely surveyed of the actual conditions of outpatients' medical use for their injury, accident and/or intoxication and investigated relevant medical expenses, with a view to estimating the directly incurred costs when the patients use medical services and the production loss costs caused by an production decline and others, so that social and/or economic costs for injuries may be ultimately aggregated.

• Korean Journal of Plant Tissue Culture
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• v.27 no.3
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• pp.175-180
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• 2000

Cotyledonary somatic embryos after being cultured in a liquid MS medium for 1 week were subcultured on a solid MS medium and then the embryos germinated at a rate of 92%, but the rate was lowered by extending the culture period of the embryos on a liquid medium: 26% germination on a liquid medium culture for 4 weeks. Somatic embryos subcultured on the liquid medium showed the normal elongation of hypocotyl and radicle but in part showed secondary embryogenesis on hypocotyl and callus formation on and around the root-hypocotyl juncture. Through observation of scanning electron microscope, apical meristem in plumule showed the loose arrangement of cells, and abnormal leaf primordium formation and growth arrest of the primordium or no leaf primordium formation. Therefore, it is suggested that the germination arrest of carrot somatic embryos on liquid medium culture is due to the structural abnormality of the apical meristem in plumule.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.311-320
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• 2021

At present, the secondary school teacher employment examination(SSTEE) is the only gateway to become a national and public secondary teacher in Korea, and after the revision from the 2014 academic year, all the questions of the exam have been converted to supply-type test items, requiring more definitive, accurate, and solid answers. Compared to the selection-type test items that measure recognition memory, the supply-type questions, testing recall memory, require constant memorization and retrieval practices to furnish answers; however, there is not enough learning tools available to support the practices. At this juncture, this study invented a mobile app, called ONE PASS, for the SSTEE. By unpacking the functional mechanisms of the brain, the basis of cognitive processing, this ONE PASS app offers a set of tools that feature brain-based learning principles, such as a personalized study planner, motivation measurement scales, mind mapping, brainstorming, and sample questions from previous tests. This study is expected to contribute to the research on the development of learning contents for applications, and at the same time, it hopes to be of some help for candidates in their exam preparation process.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.15-31
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• 2023

In this study, we propose a novel approach to analyze big data related to patents in the field of smart factories, utilizing the Latent Dirichlet Allocation (LDA) topic modeling method and the generative artificial intelligence technology, ChatGPT. Our method includes extracting valuable insights from a large data-set of associated patents using LDA to identify latent topics and their corresponding patent documents. Additionally, we validate the suitability of the topics generated using generative AI technology and review the results with domain experts. We also employ the powerful big data analysis tool, KNIME, to preprocess and visualize the patent data, facilitating a better understanding of the global patent landscape and enabling a comparative analysis with the domestic patent environment. In order to explore quantitative and qualitative comparative advantages at this juncture, we have selected six indicators for conducting a quantitative analysis. Consequently, our approach allows us to explore the distinctive characteristics and investment directions of individual countries in the context of research and development and commercialization, based on a global-scale patent analysis in the field of smart factories. We anticipate that our findings, based on the analysis of global patent data in the field of smart factories, will serve as vital guidance for determining individual countries' directions in research and development investment. Furthermore, we propose a novel utilization of GhatGPT as a tool for validating the suitability of selected topics for policy makers who must choose topics across various scientific and technological domains.

• Journal of the Korea Institute of Building Construction
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• v.23 no.5
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• pp.547-558
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• 2023

This research delves into the fabrication of an ultra-high-strength concrete, enriched with oxidized graphene nanoplatelet(GO) and hollow glass powder(HGP), notably eschewing the conventional inclusion of silica fume(SF). The primary objective was to scrutinize the autogenous shrinkage characteristics of this innovative formulation. It was discerned that the NewMix specimen, which incorporated the cGO(sourced from Company C) and HGP, and intentionally bypassed SF, showcased a commendable 13% reduction in autogenous shrinkage relative to the benchmark(Ref) specimenthat incorporated SF. Moreover, the proclivity for crack formation owing to autogenous shrinkage in the NewMix was observed to manifested by NewMix at the juncture of cracking emerged as the apex value. Attributed to the expansive specific surface area and exemplary dispersibility of cGO, it was postulated that the concrete's pore structure benefitted from enhanced infill, leading to a reduction in autogenous shrinkage. Additionally, the cGO integration fortified the concrete's resistance to crack initiation. Consequently, such an enhancement is posied to be pivotal in mitigating crack propagation resulting from autogenous shrinkage in ultra-high-strength concrete.

• Geomechanics and Engineering
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• v.37 no.3
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• pp.223-241
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• 2024

Evaluating the performance of Tunnel Boring Machines (TBMs) stands as a pivotal juncture in the domain of hard rock mechanized tunneling, essential for achieving both a dependable construction timeline and utilization rate. In this investigation, three advanced artificial neural networks namely, gated recurrent unit (GRU), back propagation neural network (BPNN), and simple recurrent neural network (SRNN) were crafted to prognosticate TBM-rate of penetration (ROP). Drawing from a dataset comprising 1125 data points amassed during the construction of the Alborze Service Tunnel, the study commenced. Initially, five geomechanical parameters were scrutinized for their impact on TBM-ROP efficiency. Subsequent statistical analyses narrowed down the effective parameters to three, including uniaxial compressive strength (UCS), peak slope index (PSI), and Brazilian tensile strength (BTS). Among the methodologies employed, GRU emerged as the most robust model, demonstrating exceptional predictive prowess for TBM-ROP with staggering accuracy metrics on the testing subset (R² = 0.87, NRMSE = 6.76E-04, MAD = 2.85E-05). The proposed models present viable solutions for analogous ground and TBM tunneling scenarios, particularly beneficial in routes predominantly composed of volcanic and sedimentary rock formations. Leveraging forecasted parameters holds the promise of enhancing both machine efficiency and construction safety within TBM tunneling endeavors.