• Composites Research
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• v.32 no.6
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• pp.327-334
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• 2019

The delamination is a special mode of failure occurring in composite laminates. Several numerical studies with finite element analysis have been carried out on the delamination behavior of unidirectional composite laminates. On the other hand, the fracture for the multi-directional composite laminates may occur not only along the resin-fiber interface between plies known as interply or interlaminar fracture but also within a ply known as interyarn or intralaminar fracture accompanied by matrix cracking and fiber bridging. In addition, interlaminar and intralaminar cracks appear at irregular proportions and intralaminar cracks proceeded at arbitrary angle. The probabilistic analysis method for the prediction of crack growth behavior within a layer is more advantageous than the deterministic analysis method. In this paper, we analyze the crack path when the mode I load is applied to the cross-ply carbon/epoxy composite laminates and collect and analyze the probability data to be used as the basis of the probabilistic analysis in the future. Two criteria for the theoretical analysis of the crack growth direction were proposed by analyzing the stress field at the crack tip of orthotropic materials. Using the proposed method, the crack growth directions of the cross-ply carbon/epoxy laminates were analyzed qualitatively and quantitatively and compared with experimental results.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.15
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• pp.6267-6272
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• 2015

Background: Extra nodal lymphoma (ENL) constitutes about 33 % of all non-Hodgkin's lymphoma. 18-28% develops in the head and neck region. A multimodality treatment with multi-agent chemotherapy (CT) and radiotherapy (RT) is considered optimum. Materials and Methods: We retrieved the treatment charts of patients of HNENL treated in our institute from 2001-2012. The charts were reviewed and the demographic, treatment details and outcome of HNENL patients were retrieved using predesigned pro-forma. Results: We retrieved data of 75consecutive patients HNENL. Median age was 47years (Range: 8-76 years). Of the 75 patients 51 were male and 24 were female. 55patients were evaluable. The patient and tumor characteristics are summarized in Table 1. All patients were staged comprehensively with contrast enhanced computed tomography of head, neck, thorax, abdomen, pelvis and bone marrow aspiration and biopsy 66 patients received a combination multi-agent CT with CHOP being the commonest regimen. 42 patients received 4 or lesser number of cycles of chemotherapy whereas 24received more than 4 cycles chemotherapy. Post radiotherapy, 41 out of 42 patients had a complete response at 3 months. Only 21patients had a complete response after chemotherapy. All patients received radiation (mostly involved field radiation) as a part of the treatment. The median radiation dose was 45 Gray (Range: 36 Gray-50 Gray). The radiation was planned by 2D fluoro simulation based technique in 37cases and by 3 Dimensional conformal radiation therapy (3DCRT) in 36 cases. Two patients were planned by the intensity modulated radiation therapy (IMRT) technique. IMRT was planned for one thyroid and one nasal cavity primary. 5 patients experienced relapse after a median follow up of 19 months. The median survival was not reached. The estimated two and three year survival were 92.9% (95%CI- 68.6- 95.35) and 88% (95%CI- 60.82 - 92.66) respectively. Univariate analysis revealed higher stage and poorer baseline performance status to be significantly associated with worse progression free survival. 5 patients progressed (relapse or primary disease progression) after treatment. Of the 5 patients, two patients were primary orbital NHL, two patients had NHL nasal cavity and one was NHL thyroid. Conclusions: Combined modality treatment in HNENL confers excellent disease control with acceptable side effects.

• Journal of the Korean Society of Radiology
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• v.11 no.2
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• pp.123-130
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• 2017

Patients diagnosed with the serious disease of cancer may have anxiety and fear of closed spaces while receiving radiation therapy. This study investigated patients receiving treatment based on Linac and Tomotherapy to look into this anxiety and fear. Study method was survey. The survey was performed according to treatment duration (treatment within 5 minutes, 10 minutes, over 20 minutes, and over 30 minutes). The patients were also surveyed about any experience of changing treatment rooms or machines due to machine failure. A total of 200 survey questionnaires with full answers were researched in this study. As a result, it was found that the less the patients' experience on radiation therapy, the higher their anxiety was. The dominating reason for this result was because the patients expected possible pain during the treatment process. In terms of treatment machine, Linac showed the highest anxiety of all for the openness of its patient stand. The most stable status was found in the case of treatment between 20 minutes and 30 minutes using Tomotherapy. The reason was the coziness of Tomotherapy machine. In the case of receiving the treatment for over 30 minutes, patients felt anxious for the isolation from the outside. The study findings are expected to serve as the necessary data for quality medical service with enhanced patient satisfaction in the clinical field.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.5
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• pp.1025-1037
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• 2015

Flexible base isolation bearings that separate superstructure from ground have been widely used in the construction field because they make a significant contribution to increasing the fundamental period of the structure, thereby decreasing response acceleration transmitted into the superstructure. However, the established bearing devices installed to uphold the whole building give rise to some problems involved with failure and collapse due to lack of the capacity as modern structures are getting more massive and higher. Therefore, this study suggests new isolation bearings assembled with additional restrainers enabled to reinforcing and recentering, and then evaluates their performance to withstand the seismic load. The superelastic shape memory alloy (SMA) bars are installed into the conventional lead-rubber bearing (LRB) devices in order to provide recentering forces. These new systems are modeled as component spring models for the purpose of conducting nonlinear dynamic analyses with near fault ground motion data. The LRB devices with steel bars are also designed and analyzed to compare their responses with those of new systems. After numerical analyses, ultimate strength, maximum displacement, permanent deformation, and recentering ratio are compared to each model with an aim to investigate which base isolation models are superior. It can be shown that LRB models with superelastic SMA bars are superior to other models compared to each other in terms of seismic resistance and recentering effect.

• Magazine of the Korean Society of Agricultural Engineers
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• v.35 no.4
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• pp.55-66
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• 1993

Upon freezing a soil swells due to phase change and its compression stress increase a lot. As the soil undergo thawing, however, it becomes a soft soil layer because the 'soil changes from a solid state to a plastic state. These changes are largely dependent on freezing temperature and repeated freezing-thawing cycle as well as the density of the soil and applied loading condition. This study was initiated to describe the effect of the freezing temperature and repeated freezing-thawing cycle on the unconfined compressive strength. Soil samples were collected at about 20 sites where soil structures were installed in Kangwon provincial area and necessary laboratory tests were conducted. The results could be used to help manage effectively the field structures and can be used as a basic data for designing and constructing new projects in the future. The results were as follows ; 1. Unconfined compressive strength decreased as the number of freezing and thawing cycle went up. But the strength increased as compression speed, water content and temperature decreased. The largest effect on the strength was observed at the first freezing and thawing cycle. 2. Compression strain went up with the increase of deformation speed, and was largely influenced by the number of the freezing-thawing cycle. 3. Secant modulus was responded sensitivefy to the material of the loading plates, increased with decrease of temperature down to - -10$^{\circ}$C, but was nearly constant below the temperature. Thixotropic ratio characteristic became large as compression strain got smaller and was significantly larger in the controlled soil than in the soil treated with freezing and thawing processes 4. Vertical compression strength of ice crystal(development direction) was 3 to 4 times larger than that of perpendicular to the crystal. The vertical compression strength was agreed well with Clausius-Clapeyrons equation when temperature were between 0 to 5C$^{\circ}$, but the strength below - 5$^{\circ}$C were different from the equation and showed a strong dependency on temperature and deformation speed. When the skew was less then 20 degrees, the vertical compression strength was gradually decreased but when the skew was higher than that, the strength became nearly constant. Almost all samples showed ductile failure. As considered above, strength reduction of the soil due to cyclic freezing-thawing prosses must be considered when trenching and cutting the soil to construct soil structures if the soil is likely subject to the processes. Especially, if a soil no freezing-thawing history, cares for the strength reduction must be given before any design or construction works begin. It is suggested that special design and construction techniques for the strength reduction be developed.

• Journal of Korea Water Resources Association
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• v.44 no.5
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• pp.363-376
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• 2011

1-D hydrodynamic numerical models have been most widely used in the field of flood analysis. The model's input data are upstream/downstream boundaries, roughness coefficients, cross-sections, and so on, and computational distance step and time step are the most important factors in order to guarantee the computational accuracy, stability, and efficiency. In this study, a theoretical explanation is presented for the basis of the previous empirical selection criteria of cross-section's location; also, the estimation technique of computationally variable distance step is proposed to reflect the properties of flow at every computational time step. Combining this technique with 1-D unsteady numerical model, it was applied to two events of Teton dam failure flood and the Han River flood. The numerical experimental results demonstrate that the accuracy and stability is increased when used more interpolated cross-sections and show that the proposed technique of computationally variable distance step has the same order of accuracy with smaller numbers of cross-section than previous empirical selection criteria. The practical use of this technique will be possible to analyze the river floods with high efficiency as well as accuracy and stability.

• Restorative Dentistry and Endodontics
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• v.35 no.2
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• pp.106-115
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• 2010

The purpose of this study was to evaluate the microtensile bond strength (${\mu}TBS$), failure modes and bonding interfaces of self-etching and three self-adhesive resin cements to dentin and indirect composite resin. Cylindrical composite blocks (Tescera, Bisco Inc.) were luted with resin cements (PA: Panavia F 2.0, Kuraray Medical Inc., RE: RelyX Unicem Clicker, 3M ESPE., MA: Maxem, Kerr Co., BI: BisCem, Bisco Inc.) on the prepared occlusal dentin surfaces of 20 extracted molars. After storage in distilled water for 24 h, $1.0\;mm\;{\times}\;1.0\;mm$ composite-dentin beams were prepared. ${\mu}TBS$ was tested at a cross-head speed of 0.5 mm/min. Data were analyzed with one-way ANOVA and Tukey's HSD test. Dentin sides of all fractured specimens and interfaces of resin cements-dentin or resin cements-composite were examined at FESEM (Field Emission-Scanning Electron Microscope). In conclusion, PA and RE showed higher bond strength and closer adaptation than MA and BI when indirect composite blocks were luted to dentin using a self-etching and three self-adhesive resin cements.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.5
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• pp.15-23
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• 2021

In this paper, service life for RC(Reinforced Concrete) substructure subjective to carbonation was evaluated through deterministic and probabilistic method considering field investigation data and Design Code(KDS 14 20 40). Furthermore changes in service life with increasing COV(Coefficient of Variation) and equivalent safety index meeting the same service life were studied. From the investigation, the mean and its COV of cover depth were evaluated to 70.0 ~ 90.0 mm and 0.2, respectively. With intended failure probability of 10.0 % and 70 mm of cover depth, service life decreased to 137 years, 123 years, and 91 years with increasing COV of 0.05, 0.1, and 0.2, respectively. In the case of 80 mm of cover depth, it changes to 179 years, 161 years, and 120 years with increasing COV. The equivalent safety index meeting the same service life from deterministic method showed 1.66 ~ 3.43 for 70 mm of cover depth and 1.61 ~ 3.24 for 80 mm of cover depth, respectively. The various design parameters covering local environment and quality condition in deterministic method yields a considerable difference of service life, so that determination of design parameters are required for exposure conditions and parameter variation.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.1
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• pp.141-158
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• 2023

From the perspective of an entrepreneur, one of the most important factors for understanding the inherent limitations of a startup, reducing the risk of failure, and succeeding is the composition of the talent, that is, the founding team. Therefore, a common concern experienced by entrepreneurs in the pre-entrepreneurship stage or the early stage of startup is the choice between independent startups and co-founding start-up. Nonetheless, in Korea, the share of independent entrepreneurship is significantly higher than that of co-founding start-up. On the other hand, focusing on the fact that many successful global innovative companies are in the form of co-founding start-up, the success factors of co-founding start-up were examined. Most of the related preceding studies are studies that identify the capabilities and characteristics of individual entrepreneurs as factors influencing the survival and success of entrepreneurship, and there is a lack of research on partnerships, that is, co-founding start-up, which are common in the field of entrepreneurship ecosystems. Therefore, this study attempted a multi-case study through in-depth interviews, collection of relevant data, analysis of contextual information, and consideration of previous studies targeting co-founders of domestic startups that succeeded in opportunistic startups. Through this, a model for deriving the phased characteristics and key success factors of co-founding start-up was proposed. As a result of the study, the key element of the preliminary start-up stage was 'opportunity', and the success factors were 'opportunity recognition through entrepreneur's experience' and 'idea development'. The key element in the early stages of start-up is "start-up team," and the success factor is "trust and complement of start-up team," and synergy is shown when "diversity and homogeneity of start-up team" are harmonized. In addition, conflicts between co-founders may occur in the early stages of start-ups, which has a large impact on the survival of start-ups. The conflict between the start-up team could be overcome through constant "mutual understanding and respect through communication" and "clear division of work and role sharing." It was confirmed that the core element of the start-up growth stage was 'resources', and 'securing excellent talent' and 'raising external funds' were important factors for success. These results are expected to overcome the limitations of start-up companies, such as limited resources, lack of experience, and risk of failure, in entrepreneurship studies, and prospective entrepreneurs preparing for a start-up in a situation where the form of co-founding start-up is attracting attention as one of the alternatives to increase the success rate. It has implications for various stakeholders in the entrepreneurial ecosystem.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.27-65
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• 2020

Many companies on information and communication technology make public their own developed AI technology, for example, Google's TensorFlow, Facebook's PyTorch, Microsoft's CNTK. By releasing deep learning open source software to the public, the relationship with the developer community and the artificial intelligence (AI) ecosystem can be strengthened, and users can perform experiment, implementation and improvement of it. Accordingly, the field of machine learning is growing rapidly, and developers are using and reproducing various learning algorithms in each field. Although various analysis of open source software has been made, there is a lack of studies to help develop or use deep learning open source software in the industry. This study thus attempts to derive a strategy for adopting the framework through case studies of a deep learning open source framework. Based on the technology-organization-environment (TOE) framework and literature review related to the adoption of open source software, we employed the case study framework that includes technological factors as perceived relative advantage, perceived compatibility, perceived complexity, and perceived trialability, organizational factors as management support and knowledge & expertise, and environmental factors as availability of technology skills and services, and platform long term viability. We conducted a case study analysis of three companies' adoption cases (two cases of success and one case of failure) and revealed that seven out of eight TOE factors and several factors regarding company, team and resource are significant for the adoption of deep learning open source framework. By organizing the case study analysis results, we provided five important success factors for adopting deep learning framework: the knowledge and expertise of developers in the team, hardware (GPU) environment, data enterprise cooperation system, deep learning framework platform, deep learning framework work tool service. In order for an organization to successfully adopt a deep learning open source framework, at the stage of using the framework, first, the hardware (GPU) environment for AI R&D group must support the knowledge and expertise of the developers in the team. Second, it is necessary to support the use of deep learning frameworks by research developers through collecting and managing data inside and outside the company with a data enterprise cooperation system. Third, deep learning research expertise must be supplemented through cooperation with researchers from academic institutions such as universities and research institutes. Satisfying three procedures in the stage of using the deep learning framework, companies will increase the number of deep learning research developers, the ability to use the deep learning framework, and the support of GPU resource. In the proliferation stage of the deep learning framework, fourth, a company makes the deep learning framework platform that improves the research efficiency and effectiveness of the developers, for example, the optimization of the hardware (GPU) environment automatically. Fifth, the deep learning framework tool service team complements the developers' expertise through sharing the information of the external deep learning open source framework community to the in-house community and activating developer retraining and seminars. To implement the identified five success factors, a step-by-step enterprise procedure for adoption of the deep learning framework was proposed: defining the project problem, confirming whether the deep learning methodology is the right method, confirming whether the deep learning framework is the right tool, using the deep learning framework by the enterprise, spreading the framework of the enterprise. The first three steps (i.e. defining the project problem, confirming whether the deep learning methodology is the right method, and confirming whether the deep learning framework is the right tool) are pre-considerations to adopt a deep learning open source framework. After the three pre-considerations steps are clear, next two steps (i.e. using the deep learning framework by the enterprise and spreading the framework of the enterprise) can be processed. In the fourth step, the knowledge and expertise of developers in the team are important in addition to hardware (GPU) environment and data enterprise cooperation system. In final step, five important factors are realized for a successful adoption of the deep learning open source framework. This study provides strategic implications for companies adopting or using deep learning framework according to the needs of each industry and business.