• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.17 no.2
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• pp.213-226
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• 2019

Regulatory agency and licensee are preparing for the site restoration of Kori unit 1, the first commercial NPP in Korea, scheduled for 2031. Developing regulatory guidelines and strategies is essential for effective restoration work. Unfortunately, Korea does not have experience of site restoration of commercial NPPs. Therefore, it is important to review cases from experienced countries to establish a strategy and regulatory standards. The U.S. has had numerous soil remediation experiences using RESRAD and MARSSIM. However, formalized evaluation methodologies for subsurface soil have not yet been established in MARSSIM. This survey focused on subsurface soil remediation by reviewing the five decommissioned NPPs under regulation of the US NRC. Overall process of remediating a contaminated subsurface soil and groundwater was reviewed to identify considerations and lessons that could be applicable in Korea. In addition, an applied methodology for evaluation of contaminated subsurface soil and related major issues between regulatory agency and licensees were reviewed in detail to support establishment of remediation strategy for Kori unit 1.

• Journal of the Korean Society of Radiology
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• v.81 no.5
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• pp.1164-1174
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• 2020

Purpose To evaluate a deep learning model to predict recurrence of thyroid tumor using preoperative ultrasonography (US). Materials and Methods We included representative images from 229 US-based patients (male:female = 42:187; mean age, 49.6 years) who had been diagnosed with thyroid cancer on preoperative US and subsequently underwent thyroid surgery. After selecting each representative transverse or longitudinal US image, we created a data set from the resulting database of 898 images after augmentation. The Python 2.7.6 and Keras 2.1.5 framework for neural networks were used for deep learning with a convolutional neural network. We compared the clinical and histological features between patients with and without recurrence. The predictive performance of the deep learning model between groups was evaluated using receiver operating characteristic (ROC) analysis, and the area under the ROC curve served as a summary of the prognostic performance of the deep learning model to predict recurrent thyroid cancer. Results Tumor recurrence was noted in 49 (21.4%) among the 229 patients. Tumor size and multifocality varied significantly between the groups with and without recurrence (p < 0.05). The overall mean area under the curve (AUC) value of the deep learning model for prediction of recurrent thyroid cancer was 0.9 ± 0.06. The mean AUC value was 0.87 ± 0.03 in macrocarcinoma and 0.79 ± 0.16 in microcarcinoma. Conclusion A deep learning model for analysis of US images of thyroid cancer showed the possibility of predicting recurrence of thyroid cancer.

• Tunnel and Underground Space
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• v.34 no.2
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• pp.169-184
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• 2024

This study investigates acoustic emission (AE) and micro-deformation characteristics of circular openings through biaxial compression experiments. The experimental results showed a significant increase in the frequency, count, energy, and amplitude of AE signals immediately before damage occurred in the circular opening. The differences in frequency and count between before and after damage initiation were significantly pronounced, indicating suitable factors for identifying damage occurrence in circular openings. The results for digital image correlation (DIC) technique revealed that micro-deformation was concentrated around the openings, as evidenced by the spatial distribution of strain. In addition, spalling was observed at the end of the experiments. The AE and micro-deformation characteristics presented in this study are expected to serve as fundamental data for evaluating the stability of underground openings and boreholes for deep subsurface projects.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.1
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• pp.500-506
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• 2011

The deep mixing method, which is generally considered as a method for improving soft ground, is assessed in terms of its applicability for urban construction. Using small equipment tailored to perform deep mixing in congested urban areas, deep mixing was performed to reinforce the foundation ground of a retaining wall in a redevelopment site in Seoul. Strengths characteristics, construction vibrations and displacements induced to an adjacent old masonry wall were evaluated by laboratory tests and field monitoring. The results indicate that the strength of ground was improved appropriately whilst the vibrations and displacements induced by deep mixing were slight enough to satisfy the general requirements for construction works in urban environments. Therefore, it is concluded that deep mixing method can be a practical option for foundation methods in urban construction works where minimizing noise and vibrations is an important concern.

• The Journal of the Korea Contents Association
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• v.12 no.7
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• pp.415-424
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• 2012

This paper tried to identify the impacts of emotional labor on burnout and job satisfaction in the casino industry. Prepared questionnaires were distributed to 300 sample employees working in domestic casino, then used for data analysis 300. The results of this study are as follows: Firstly, surface acting have a positive effect on emotional exhaustion, lack of accomplishment and depersonalization. But deep acting have a negative effect on emotional exhaustion. And deep acting, emotion control have a negative effect on lack of accomplishment and depersonalization. Secondly, surface acting have a positive effect on job environment. Also deep acting, emotion control have a positive effect on rewards and value sharing. And emotion control have a positive effect on work environment. Thirdly, deep acting have a negative effect on job environment. Also, surface acting have a negative effect on rewards and value sharing.

• Restorative Dentistry and Endodontics
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• v.30 no.4
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• pp.319-326
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• 2005

This study compared the microtensile bond strength $({\mu}TBS)$ of single step adhesives to different dentin depths. Superficial or deep dentin was exposed in 30 molar teeth by sectioning immediately under the DEJ or 1.5mm area from central pit, respectively. After polishing with 600-grit SiC paper, the dentin surfaces were assigned to three groups: AQ group-AQ Bond, L-Pop group-Adper Prompt L-Pop, Xeno group-Xeno III. The bonded specimens were sectioned into sticks and subjected to ${\mu}TBS$ testing with a crosshead speed of 1mm/minute. The results of this study were as follows; The ${\mu}TBS$ to superficial dentin was higher than that to deep dentin in all group. The ${\mu}TBS$ of Xeno group was significantly higher than that of L-Pop group and AQ group in both superficial and deep dentin (p<0.05).

• Journal of Internet of Things and Convergence
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• v.8 no.4
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• pp.1-7
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• 2022

As the number of IoT devices increases, power management of the cluster head, which acts as a gateway between the cluster and sink nodes in the IoT network, becomes crucial. Particularly when the cluster head is a mobile wireless terminal, the power consumption of the IoT network must be minimized over its lifetime. In addition, the delay of information transmission in the IoT network is one of the primary metrics for rapid information collecting in the IoT network. In this paper, we propose a low-power buffer management algorithm that takes into account the information transmission delay in an IoT network. By forwarding or skipping received packets utilizing deep Q learning employed in deep reinforcement learning methods, the suggested method is able to reduce power consumption while decreasing transmission delay level. The proposed approach is demonstrated to reduce power consumption and to improve delay relative to the existing buffer management technique used as a comparison in slotted ALOHA protocol.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.11 no.2
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• pp.157-178
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• 2013

This study gives a conceptual and basic direction to develop a URL (underground research laboratory) program for establishing the performance and safety of a deep geological disposal system in Korea. The concept of deep geological disposal is one of the preferred methodologies for the final disposal of spent nuclear fuel (SNF). Advanced countries with radioactive waste disposal have developed their own disposal concepts reasonable to their social and environmental conditions and applied to their commercial projects. Deep geological disposal system is a multi-barrier system generally consisting of an engineered barrier and natural barrier. A disposal facility and its host environment can be relied on a necessary containment and isolation over timescales envisaged as several to tens of thousands of years. A disposal system is not allowed in the commercial stage of the disposal program without a validation and demonstration of the performance and safety of the system. All issues confirming performance and safety of a disposal system include investigation, analysis, assessment, design, construction, operation and closure from planning to closure of the deep geological repository. Advanced countries perform RD&D (research, development & demonstration) programs to validate the performance and safety of a disposal system using a URL facility located at the preferred rock area within their own territories. The results and processes from the URL program contribute to construct technical criteria and guidelines for site selection as well as suitability and safety assessment of the final disposal site. Furthermore, the URL program also plays a decisive role in promoting scientific understanding of the deep geological disposal system for stakeholders, such as the public, regulator, and experts.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.85-100
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• 2023

Corporate ESG performance (environmental, social, and corporate governance) reflecting a company's strategic sustainability has emerged as one of the main factors in today's investment decisions. The traditional ESG performance rating process is largely performed in a qualitative and subjective manner based on the institution-specific criteria, entailing limitations in reliability, predictability, and timeliness when making investment decisions. This study attempted to predict the corporate ESG rating through automated machine learning based on quantitative and disclosed corporate financial information. Using 12 types (21,360 cases) of market-disclosed financial information and 1,780 ESG measures available through the Korea Institute of Corporate Governance and Sustainability during 2019 to 2021, we suggested a deep neural network prediction model. Our model yielded about 86% of accurate classification performance in predicting ESG rating, showing better performance than other comparative models. This study contributed the literature in a way that the model achieved relatively accurate ESG rating predictions through an automated process using quantitative and publicly available corporate financial information. In terms of practical implications, the general investors can benefit from the prediction accuracy and time efficiency of our proposed model with nominal cost. In addition, this study can be expanded by accumulating more Korean and international data and by developing a more robust and complex model in the future.

• Korean Public Administration Review
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• v.47 no.1
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• pp.201-237
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• 2013

본 연구는 효율적 인적자원관리의 실행과 유지에 있어서 '일과 삶 균형(WLB: Work-Life Balance)' 정책의 중요성을 이론적·실증적 접근방식으로 규명하고자 하였다. 특히 본 연구에서는 WLB 정책을 유연근무제, 친가족정책, 개인신상지원 프로그램 등 3가지 차원으로 구분하여 제시하였으며, 분석대상을 공공조직과 민간조직으로 구분하여 기존 연구와의 차별화를 도모하였다. 연구모형 개발과 가설검증을 위해 제3차 여성가족패널(KLoWF) 자료를 바탕으로 WLB 정책과 정책 부합성, 직무만족도, 이직의도 간의 관계를 분석하였으며, 설문조사를 통한 양적 분석의 한계를 보완하기 위하여 공공조직 및 민간조직 여성 근로자와의 심층 인터뷰를 통한 질적 분석을 병행하였다. 분석결과, WLB 정책과 조직 효과성 간의 관계에 있어 공공조직과 민간조직 간의 유의미한 차이가 있음을 확인할 수 있었으며 심층 인터뷰를 통해 이러한 결과가 공공조직과 민간조직의 상호 이질적인 조직 문화, 제도, 구조적 특성에 기인하고 각 영역 구성원들의 서로 다른 욕구 및 동기 유발 체계에 의한 것임을 발견할 수 있었다. 이러한 분석결과를 바탕으로 본 연구에서는 각각의 조직 특성에 맞는 수요자 친화형 WLB 정책 구축의 필요성을 제안하고, WLB 정책 시행 측면의 문제점 및 개선방안 등을 제시하였다.