44 research outputs found

    ์ฒœ์—ฐ๊ฐ€์Šค ๊ณต๊ธ‰๋ง ๋‚ด ์ดˆ๊ตฌ์กฐ ์ตœ์ ํ™” ๋ฐ ๋‹ค์ค‘๋ชจ๋“ˆ๋ฐฉ์‹์„ ์ด์šฉํ•œ ๊ณต์ •์„ค๊ณ„ ๋ฐ ์šด์ „

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ํ™”ํ•™์ƒ๋ฌผ๊ณตํ•™๋ถ€, 2019. 2. ์ด์›๋ณด.๋ณธ ๋…ผ๋ฌธ์€ ๊ณต์ •์‹œ์Šคํ…œ ๋ถ„์•ผ์˜ ์ตœ์‹ ๊ธฐ์ˆ  ์ˆ˜์š”์— ์ƒ์‘ํ•˜๋Š” ์ตœ์  ๊ณต์ •์„ค๊ณ„ ๋ฐ ์šด์ „๊ธฐ์ˆ  ๊ฐœ๋ฐœ์„ ์ฃผ๋ชฉ์ ์œผ๋กœ ํ•œ๋‹ค. ์ตœ๊ทผ ์…ฐ์ผ๊ฐ€์Šค ๋“ฑ ๋ณ€ํ™”ํ•˜๋Š” ์ฒœ์—ฐ๊ฐ€์Šค ์ž์›์œผ๋กœ๋ถ€ํ„ฐ ์ง€์†์ ์ธ ๋ถ€๊ฐ€๊ฐ€์น˜ ์ฐฝ์ถœ๊ณผ ํ”Œ๋žœํŠธ์˜ ๋‚ด์žฌ์  ์•ˆ์ „์„ฑ์„ ์ œ๊ณ ํ•  ์ˆ˜ ์žˆ๋Š” ์„ค๊ณ„ ๋ฐ ์šด์ „์„ ๋„๋ชจํ•˜์˜€๋‹ค๋Š” ์ ์—์„œ ์‹ค์ œ ์‚ฐ์—…์—์˜ ์‘์šฉ๊ฐ€์น˜๊ฐ€ ๋งค์šฐ ๋†’๋‹ค. ์ฒซ ๋ฒˆ์งธ๋กœ ์ฒœ์—ฐ๊ฐ€์Šค ๊ฐ€์†”๋ฆฐํšŒ์ˆ˜ ๋ฐ ์•กํ™” ํ†ตํ•ฉ๊ณต์ •์— ์งˆ์†ŒํšŒ์ˆ˜๊ณต์ •์„ ์ถ”๊ฐ€ํ•˜์—ฌ, ์ €ํ’ˆ์งˆ ์ฒœ์—ฐ๊ฐ€์Šค๋กœ๋ถ€ํ„ฐ ์ง€์†์ ์ธ ์•กํ™”์ฒœ์—ฐ๊ฐ€์Šค ์ƒ์‚ฐ์ด ๊ฐ€๋Šฅํ•œ ๊ณต์ •์„ ์„ค๊ณ„ํ•˜์˜€๋‹ค. ์—ด๊ตํ™˜๋ง ๋ฐ ๋ถ„๋ฆฌ๊ณต์ • ์ตœ์ ํ™”๋ฅผ ์œ„ํ•ด ๊ณต์ •์š”์†Œ๋“ค์˜ ์—‘์„œ์ง€๋ฅผ ์ตœ์†Œํ™”ํ•  ์ˆ˜ ์žˆ๋Š” ์ดˆ๊ตฌ์กฐ๋ฅผ ์„ค๊ณ„ํ•จ์œผ๋กœ์จ ๊ธฐ์กด์˜ ์—ฐ๊ตฌ๊ฐ€ ์ฐพ์ง€ ๋ชปํ•˜์˜€๋˜ ์ƒˆ๋กœ์šด ์ตœ์  ๊ตฌ์กฐ ๋ฐ ์šด์ „์กฐ๊ฑด์„ ๊ฒฐ์ •ํ•˜์˜€๋‹ค. ๋‚˜์•„๊ฐ€ ์„œ๋กœ ๋‹ค๋ฅธ ์ฒœ์—ฐ๊ฐ€์Šค ์กฐ์„ฑ์— ๋”ฐ๋ผ ๊ฐ๊ธฐ ์ ์šฉ์ด ๊ฐ€๋Šฅํ•œ ๋Œ€์•ˆ๊ณต์ •์„ ์ถ”๊ฐ€ ์„ค๊ณ„ยท์ตœ์ ํ™”ํ•จ์œผ๋กœ์จ ๋ณ€ํ™”๋˜๋Š” ์ฒœ์—ฐ๊ฐ€์Šค ์ž์›์— ์ง€์†์ ์ธ ๊ฐ€์น˜์ฐฝ์ถœ์„ ์œ„ํ•œ ํ•ด๋‹ต์„ ์ œ์‹œํ•˜๊ณ  ์žˆ๋‹ค. ๋‘ ๋ฒˆ์งธ๋กœ ๊ณต์ •์˜ ์˜ˆ๋น„์„ค๊ณ„๋‹จ๊ณ„์—์„œ ๋‚ด์žฌ์  ์•ˆ์ „์„ฑ์˜ ๊ฐœ๋…์„ ๋„์ž…ํ•˜์—ฌ, ๊ฒฝ์ œ์„ฑ๊ณผ ์•ˆ์ „์„ฑ์˜ ๊ท ํ˜•์„ ์œ ์ง€ํ•˜๊ธฐ ์œ„ํ•œ ์ƒˆ๋กœ์šด ๋‹ค๋ชฉ์ ์ตœ์ ํ™” ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ์ž ์žฌ์  ์œ„ํ—˜๋„๊ฐ€ ๋†’์€ ์ฒœ์—ฐ๊ฐ€์Šค ์•กํ™”๊ณต์ •์„ ๋Œ€์ƒ์œผ๋กœ ์•กํ™”์‚ฌ์ดํด์— ๋”ฐ๋ฅธ ์ดˆ๊ตฌ์กฐ๋ฅผ ๋ชจ์‚ฌํ•˜์—ฌ ๋‘ ๊ฐ€์ง€ ๋ชฉ์ ํ•จ์ˆ˜์˜ ๊ฐ€์ค‘์น˜์— ๋”ฐ๋ฅธ ์ตœ์ ํ•ด๋ฅผ ๊ฒฐ์ •ํ•จ์œผ๋กœ์จ ๊ธฐ์กด ์ตœ์ ํ™”์˜ ํ•œ๊ณ„๋ฅผ ๋ณด์™„ํ•˜์˜€๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ํ”Œ๋žœํŠธ ์•ˆ์ „์šด์ „์„ ์œ„ํ•ด ๊ณต์ •์ด์ƒ์—์„œ๋ถ€ํ„ฐ ์‚ฌ๊ณ ์˜ ๋ฐœ์ƒ ๋ฐ ์ „ํŒŒ๊ณผ์ •์„ ์‹ค์‹œ๊ฐ„์œผ๋กœ ๊ตฌํ˜„ํ•  ์ˆ˜ ์žˆ๋Š” ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๋ชจ๋“ˆ์„ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ๋™์ ๊ณต์ •์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๋ฐ ์‚ฌ๊ณ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์˜ ๋‘ ๊ฐ€์ง€ ๋…๋ฆฝ๋œ ๋ชจ๋“ˆ์„ ๊ฐ์ฒด์—ฐ๊ฒฐ๋งค์ž… ๊ธฐ๋ฒ•์„ ์ด์šฉํ•˜์—ฌ ์—ฐ๋™ํ•จ์œผ๋กœ์จ ์‚ฌ๊ณ ์ƒํ™ฉ์—์„œ ์šด์ „์›์˜ ์ž„์˜์กฐ์น˜๊ฐ€ ๋ชจ๋“ˆ์— ์‹ค์‹œ๊ฐ„ ๋ฐ˜์˜๋˜๋„๋ก ํ•˜์˜€๋‹ค. ํ•ด๋‹น ๋ชจ๋“ˆ์€ ์ž„์˜์˜ ์‚ฌ๊ณ ์ƒํ™ฉ์—์„œ ์ œ์–ด์‹ค ๋ฐ ํ˜„์žฅ ์šด์ „์›์˜ ์ ์ ˆํ•œ ๋Œ€์‘์„ ํšจ๊ณผ์ ์œผ๋กœ ์œ ๋„ํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ ๋‚˜์•„๊ฐ€ ํ”Œ๋žœํŠธ ์•ˆ์ „์‹œ์Šคํ…œ์„ค๊ณ„์— ๊ฐ๊ด€ํ™”๋œ ์ง€ํ‘œ๋ฅผ ์ œ์‹œํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ ์œ„์™€ ๊ฐ™์ด ์‹ค์ œ ์‚ฐ์—…์˜ ๊ธฐ์ˆ ์  ์ˆ˜์š”๋ฅผ ์ถฉ์กฑ์‹œํ‚ค๊ณ  ์ด๋ฅผ ๋ฐœ์ „์‹œํ‚ด์œผ๋กœ์จ ๊ณต์ •์‹œ์Šคํ…œ ํ•™์ˆ ๋ถ„์•ผ์— ๊ธฐ์—ฌํ•˜์˜€๋‹ค.Recently in the field of process systems engineering in natural gas processing, various researches trying to make changes in the existing framework of process design and operation have been studied with the emerging need of sustainability and safety in the chemical processes. These two considerations of sustainability and safety either result in a totally new solution for a certain decision making or require far different methods or technologies for it. Especially for a natural gas supply chain broadly from drilling of the gas/oil reservoirs to distributing the product gas to end-users like households or offices, new frameworks of process design and operation critically influence the way of producing desired products and supplying them to the users in the associated industries. Then it determines the structure, operating conditions, and operation procedures of chemical processes which are economically powerful and good in operability. Recently, as the natural gas sources becomes unconventional varying from mid-to-small size reservoirs or shale gases, this change makes the offshore natural gas plants emerge as an alternative and vital site of producing LNG (liquefied natural gas) with strict requirements of safety. It also makes additional processing units like a cryogenic nitrogen recovery be necessary for sustainable production of LNG with leaner feed natural gases. Among various processes in the overall natural gas supply chain, this thesis dealt with largely three parts including gas pre-treatment, liquefaction, and distribution to the end-users, attempting to design new processes or develop new methods of decision making in the context of the new framework considering sustainability and safety in process systems engineering. In this thesis, I will discuss the process synthesis, intensification, and optimization for sequential units, multi-objective optimization for economic feasibility and inherent safety, and multi-modular approach for interactive simulation of dynamic process and 3D-CFD (computational fluid dynamics) accident models. First of all, for designing a sustainable process of producing LNG from feed natural gases with high amounts of nitrogen, two cryogenic nitrogen recovery processes integrated with LNG production and NGL (natural gas liquid) recovery were designed and optimized based on the structural analysis of components separation: one for integrated nitrogen recovery unit and the other for standalone one. The difference of each process is the way the nitrogen is removed from the natural gas. The former recovers nitrogen in the integrated heat and mass transfer structure with natural gas liquefaction while the latter separates the nitrogen recovery unit into an independent structure apart from the liquefaction section. These sophisticated nitrogen recovery solutions follow the recent demand of highly efficient electric motors as alternative compressor drivers which require less or no fuel gas, the major sink of nitrogen in the feed gas. These two processes were compared with each other in terms of specific power (kWH/kg_LNG), which is equivalent to the overall process efficiency, with respect to the nitrogen content in the feed gas from 0mol% to 20mol%. Consequently, as the nitrogen content in the feed gas increases, the specific power of each process also increases while the standalone solution has a priority over the other until around 17mol% of nitrogen and after that point the integrated solution becomes relatively more efficient. It should be noted that all of the optimization results of each configuration were improved with the reduced specific power by up 38.6% compared to those from previous studies which have similar configurations. The way this study aimed could be reasonable guidelines for other chemical process designs as well as nitrogen recovery in natural gas processing. Secondly, for designing a safer process of natural gas processing, two different systematic approaches were newly proposed in this study: one for risk reduction method based on rigorous QRA (quantitative risk assessment) results through process design modification of an existing plant which already finished up to the detailed design stage, and the other for deciding an optimal process design through multi-objective optimization for minimizing both the TAC (total annual cost) and the risk (fatality frequency) at the preliminary design stage. This latter approach could largely lower the cost required for finalizing the design as it doesnt need to follow the general QRA procedure where the recursive loop is recycled until the risk is reduced to an acceptable level. But before this approach starts to be applied, the suitability of its method should be verified as it has to make some assumptions in assessing the safety level of the process with limited information. Also the computation load would be higher as it needs to simultaneously consider the economic feasibility and inherent safety in designing a process. Despite the differences these two approaches have each other, however, they are essentially in the same context in that they share the same purpose of deciding a process design which is safer and/or even cheaper than the existing processes. Consequently, for the former approach of which the target process is the GTU (gas treatment unit) of an existing GOSP (gas oil separation plant) for processing associated natural gas, the modified design with different operation conditions reduced the total risk integrals by 27% at the expense of only the additional 50,000forcapitalcost.Inaddition,sensitivityanalysisoftotalriskwithrespecttoprobabilityofsuccessforsafetybarrierswascarriedoutinordertoshowthepreferencesofprocessdesignmodification,thisstudyproposed,overtheimprovementofsafetysystems.Meanwhile,thelatterapproachofsuperstructureformulationandmultiโˆ’objectiveoptimizationfordesigninganoptimalheattransferstructureandoperatingconditionswasappliedtothenaturalgasliquefactionprocesses,decidingthattheSMR(singleโˆ’stagemixedrefrigerantprocess)structurewiththeTACof626.6MM50,000 for capital cost. In addition, sensitivity analysis of total risk with respect to probability of success for safety barriers was carried out in order to show the preferences of process design modification, this study proposed, over the improvement of safety systems. Meanwhile, the latter approach of superstructure formulation and multi-objective optimization for designing an optimal heat transfer structure and operating conditions was applied to the natural gas liquefaction processes, deciding that the SMR (single-stage mixed refrigerant process) structure with the TAC of 626.6MM/yr and fatality frequency of 1.28E-03/yr has the highest priority over all possible solutions. Finally, with the aim of safely operating a chemical plant, a new operator training module which mainly targets the interactive cooperation of control room operators and field operators was developed through using multi-modular approach with advanced simulations and data processing technologies. This interactive simulation modeling delivers the online simulation results of process operation to the operators and induces them to take proper actions in case of a random accidental situation among pre-identified scenarios in a chemical plant. Developed model integrates the real-time process dynamic simulations with the off-line database of 3D-CFD accident simulation results in a designed interface using OLE (Object Linking and Embedding) technology so that it could convey the online information of the accident to trainees which is not available in existing operator training systems. The model encompasses the whole process of data transfer till the end of the training at which trainees complete an emergency shutdown system in a programmed model. The developed module was applied to a natural gas pressure regulating station where the high pressure gas is depressurized and distributed to the end-users like households or offices. An overall scenario is simulated in the interactive simulation model, which starts from an abnormal increase of the discharge (2nd) pressure of the main valve due to its malfunction, spreads to an accidental gas release through the crack of a pressure recorder, and ends with gas dispersion and explosion. Then the magnitude of the accident outcomes with respect to the lead time of each trainees emergency response is analyzed. Consequently, the module could improve the effectiveness of operator training system through interactively linking the trainee actions with the model interface so that the associated accident situations would vary with respect to each trainees competence facing an accident.Abstract i Table of Contents vii List of Figures x List of Tables xiv CHAPTER 1. Introduction 1 1.1. Research motivation 1 1.2. Research objectives 4 1.3. Outline of the thesis 6 1.4. Associated publications 11 CHAPTER 2. Process Intensification 12 2.1. Introduction 13 2.2. Conceptual Design of the Nitrogen Recovery 17 2.3. Design Improvement and Optimization 26 2.3.1. Integrated Nitrogen Recovery Unit 26 2.3.2. Optimization of the Base Case 32 2.3.3. Design Improvement 40 2.4. Alternative Process Design and Optimization 65 2.4.1. Standalone Nitrogen Recovery Unit 65 2.4.2. Optimization of Standalone Nitrogen Recovery Unit 74 2.4.3. Comparison between End-flash and Stripping Options 78 2.5. Varying Feed Composition and Optimization 95 2.6. Concluding Remarks 105 CHAPTER 3. Safer Process Design 107 3.1. Introduction 109 3.2. Risk Reduction through Process Design Modification 112 3.2.1. Risk Assessment for the Target Process 113 3.2.2. Risk Reduction to ALARP 141 3.3. Multi-objective Optimization Including Inherent Safety 154 3.3.1. New Decision Making Schemes for Inherent Safety 159 3.3.2. Superstructure for Natural Gas Liquefaction Processes 168 3.3.3. Multi-objective Optimization 187 3.3.4. Decision Making for Final Optimal Solution 203 3.3.5. Future Works 208 3.4. Concluding Remarks 210 CHAPTER 4. Safe Operation with Multi-modular Approach 212 4.1. Introduction 213 4.2. Interactive Simulation Modeling 218 4.2.1. Model Structure 218 4.2.2. Dynamic Process and Accident Simulation Engine 221 4.2.3. Real-time 3D-CFD Data Processing Method 225 4.3. Case Study โ€“ Pressure Regulating Station 231 4.3.1. Developing a Program Prototype 231 4.3.2. Prototype Test and Training Evaluation 252 4.4. Concluding Remarks 256 CHAPTER 5. Conclusion 257 Nomenclature 261 Reference 263 Abstract in Korean (๊ตญ๋ฌธ์ดˆ๋ก) 270Docto

    ์˜ํ•™ ์—ฐ๊ตฌ์—์„œ์˜ ๊ณผํ•™์  ์ฆ๊ฑฐ์˜ ํ™œ์šฉ์„ ์œ„ํ•œ ์‹œ๊ฐ์  ๋ถ„์„ ์‹œ์Šคํ…œ ๋””์ž์ธ

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2022. 8. ์„œ์ง„์šฑ.Evidence-based medicine, "the conscientious, explicit, and judicious use of current best evidence in healthcare and medical research" [98], is one of the most widely accepted medical paradigms of modern times. Searching, reviewing, and synthesizing reliable and high-quality scientific evidence is the key step for the paradigm. However, despite the widespread use of the EBM paradigm, challenges remain in applying Evidence-based medicine protocols to medical research. One of the barriers to applying the best scientific evidence to medical research is the severe literature and clinical data overload that causes the evidence-based tasks to be tremendous time-consuming tasks that require vast human effort. In this dissertation, we aim to employ visual analytics approaches to address the challenges of searching and reviewing massive scientific evidence in medical research. To overcome the burden and facilitate handling scientific evidence in medical research, we conducted three design studies and implemented novel visual analytics systems for laborious evidence-based tasks. First, we designed PLOEM, a novel visual analytics system to aid evidence synthesis, an essential step in Evidence-Based medicine, and generate an Evidence Map in a standardized method. We conducted a case study with an oncologist with years of evidence-based medicine experience. In the second study, we conducted a preliminary survey with 76 medical doctors to derive the design requirements for a biomedical literature search. Based on the results, We designed EEEVis, an interactive visual analytic system for biomedical literature search tasks. The system enhances the PubMed search result with several bibliographic visualizations and PubTator annotations. We performed a user study to evaluate the designs with 24 medical doctors and presented the design guidelines and challenges for a biomedical literature search system design. The third study presents GeneVis, a visual analytics system to identify and analyze gene expression signatures across major cancer types. A task that cancer researchers utilize to discover biomarkers in precision medicine. We conducted four case studies with domain experts in oncology and genomics. The study results show that the system can facilitate the task and provide new insights from the data. Based on the three studies of this dissertation, we conclude that carefully designed visual analytics approaches can provide an enhanced understanding and support medical researchers for laborious evidence-based tasks in medical research.๊ทผ๊ฑฐ์ค‘์‹ฌ์˜ํ•™(Evidence-Based Medicine)์ด๋ž€ "์ž„์ƒ ์น˜๋ฃŒ ๋ฐ ์˜ํ•™ ์—ฐ๊ตฌ์—์„œ ํ˜„์žฌ ์กด์žฌํ•˜๋Š” ์ตœ๊ณ ์˜ ์ฆ๊ฑฐ๋ฅผ ์–‘์‹ฌ์ ์ด๊ณ , ๋ช…๋ฐฑํ•˜๋ฉฐ, ๋ถ„๋ณ„ ์žˆ๊ฒŒ ์ด์šฉํ•˜๋Š” ๋ฐฉ๋ฒ•๋ก "์ด๋ฉฐ [98], ํ˜„๋Œ€ ์˜ํ•™์—์„œ ๊ฐ€์žฅ ๋„๋ฆฌ ๋ฐ›์•„๋“ค์—ฌ์ง€๋Š” ์˜ํ•™ ํŒจ๋Ÿฌ๋‹ค์ž„์ด๋‹ค. ์‹ ๋ขฐํ•  ์ˆ˜ ์žˆ๋Š” ๊ณ ์ˆ˜์ค€์˜ ๊ณผํ•™์  ๊ทผ๊ฑฐ๋ฅผ ๊ฒ€์ƒ‰, ๊ฒ€ํ† , ํ•ฉ์„ฑํ•˜๋Š” ๊ฒƒ์ด์•ผ ๋ง๋กœ ๊ทผ๊ฑฐ์ค‘์‹ฌ์˜ํ•™์˜ ํ•ต์‹ฌ์ด๋‹ค. ํ•˜์ง€๋งŒ, ๊ทผ๊ฑฐ์ค‘์‹ฌ์˜ํ•™์ด ์ด๋ฏธ ๊ด‘๋ฒ”์œ„ํ•˜๊ฒŒ ์‚ฌ์šฉ๋˜๊ณ  ์žˆ์Œ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ , ์˜ํ•™ ์—ฐ๊ตฌ์— ๊ทผ๊ฑฐ์ค‘์‹ฌ์˜ํ•™์˜ ํ”„๋กœํ† ์ฝœ์„ ์‹ค์ฒœํ•˜๋Š” ๋ฐ์—๋Š” ์—ฌ์ „ํžˆ ๋งŽ์€ ์–ด๋ ค์›€์ด ๋”ฐ๋ฅธ๋‹ค. ์˜๋ฃŒ ๋ฌธํ—Œ ์ •๋ณด, ์ž„์ƒ ์ •๋ณด ๋ฐ ์œ ์ „์ฒดํ•™ ์ •๋ณด๊นŒ์ง€ ์—ฐ๊ตฌ์ž๊ฐ€ ๊ฒ€ํ† ํ•ด์•ผ ํ•  ๊ทผ๊ฑฐ์˜ ์–‘์€ ๋ฐฉ๋Œ€ํ•˜๋ฉฐ ๊ด‘๋ฒ”์œ„ํ•˜๋‹ค. ๋˜ํ•œ ์˜ํ•™๊ณผ ๊ธฐ์ˆ ์˜ ๋ฐœ์ „์œผ๋กœ ์ธํ•ด ์ ์ฐจ ๋” ๋น ๋ฅธ ์†๋„๋กœ ๋Š˜์–ด๋‚˜๊ณ  ์žˆ๊ธฐ์—, ์ด๋ฅผ ๋ชจ๋‘ ์—„๋ฐ€ํžˆ ๊ฒ€ํ† ํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ๋ง‰๋Œ€ํ•œ ์–‘์˜ ์‹œ๊ฐ„๊ณผ ์ธ๋ ฅ์ด ์žˆ์–ด์•ผ ํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ ์‹œ๊ฐ์  ๋ถ„์„ ๋ฐฉ๋ฒ•๋ก ์„ ์ ‘๋ชฉํ•˜์—ฌ ์˜ํ•™ ์—ฐ๊ตฌ์—์„œ ๋ฐฉ๋Œ€ํ•œ ๊ณผํ•™์  ์ฆ๊ฑฐ๋ฅผ ๊ฒ€์ƒ‰ํ•˜๊ณ  ๊ฒ€ํ† ํ•  ์‹œ ๋ฐœ์ƒํ•˜๋Š” ๋ง‰๋Œ€ํ•œ ์ธ์  ์ž์›์˜ ๊ณผ๋ถ€ํ•˜ ๋ฌธ์ œ๋ฅผ ์™„ํ™”ํ•˜๊ณ ์ž ํ•œ๋‹ค. ์ด๋ฅผ ์œ„ํ•˜์—ฌ ๊ทผ๊ฑฐ์ค‘์‹ฌ์˜ํ•™์˜ ์ ˆ์ฐจ ์ค‘ ํŠนํžˆ ์ธ๋ ฅ ์†Œ๋ชจ๊ฐ€ ๋ง‰์‹ฌํ•œ ์ ˆ์ฐจ๋“ค์„ ์„ ์ •ํ•˜๊ณ , ์ด๋Ÿฌํ•œ ๋‚œ๊ด€์„ ๊ทน๋ณตํ•˜๊ณ  ๋ณด๋‹ค ํšจ์œจ์ ์ด๊ณ  ํšจ๊ณผ์ ์œผ๋กœ ๋ฐ์ดํ„ฐ์—์„œ ์œ ์˜๋ฏธํ•œ ์ •๋ณด๋ฅผ ๋„์ถœํ•  ์ˆ˜ ์žˆ๊ฒŒ๋” ๋ณด์กฐํ•˜๋Š” ์„ธ ๊ฐ€์ง€ ์‹œ๊ฐ์  ๋ถ„์„ ์‹œ์Šคํ…œ๋“ค์„ ๊ตฌํ˜„ํ•˜์˜€์œผ๋ฉฐ, ๊ฐ๊ฐ์˜ ์‹œ์Šคํ…œ์— ๊ด€ํ•œ ๋””์ž์ธ ์—ฐ๊ตฌ๋ฅผ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ์šฐ์„  ์ฒซ ๋””์ž์ธ ์—ฐ๊ตฌ์—์„œ๋Š” ๊ทผ๊ฑฐ์ค‘์‹ฌ์˜ํ•™ ์—ฐ๊ตฌ์— ์žˆ์–ด ํ•„์ˆ˜์  ๋‹จ๊ณ„์ธ ๊ทผ๊ฑฐ ํ•ฉ์„ฑ ๋ฐฉ๋ฒ•๋ก ์˜ ํ•˜๋‚˜์ธ ๊ทผ๊ฑฐ ๋งคํ•‘(Evidence Mapping) ๊ณผ์ •์„ ์ง€์›ํ•˜๊ธฐ ์œ„ํ•œ ์‹œ๊ฐ์  ๋ถ„์„ ์‹œ์Šคํ…œ PLOEM์„ ์„ค๊ณ„ํ–ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ด๋ฅผ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•ด ๋‹ค๋…„๊ฐ„์˜ ๊ทผ๊ฑฐ ๊ธฐ๋ฐ˜ ์˜๋ฃŒ ๊ฒฝํ—˜์ด ์žˆ๋Š” ์ข…์–‘ํ•™์ž์™€ ํ•จ๊ป˜ ์‚ฌ๋ก€ ์—ฐ๊ตฌ๋ฅผ ์ˆ˜ํ–‰ํ–ˆ๋‹ค. ๋‘ ๋ฒˆ์งธ ๋””์ž์ธ ์—ฐ๊ตฌ์—์„œ๋Š” ์˜ํ•™ ๋ฌธํ—Œ ๊ฒ€์ƒ‰ ์‹œ์Šคํ…œ์˜ ์š”๊ตฌ์‚ฌํ•ญ ๋ถ„์„์„ ์œ„ํ•ด ์ด 76๋ช…์˜ ์˜์‚ฌ๋ฅผ ์ƒ๋Œ€๋กœ ์„ค๋ฌธ์กฐ์‚ฌ๋ฅผ ์ง„ํ–‰ํ•˜์˜€๊ณ , ์ด๋Ÿฌํ•œ ๋ถ„์„์„ ๋ฐ”ํƒ•์œผ๋กœ ๋Œ€ํ™”ํ˜• ์‹œ๊ฐ์  ๋ถ„์„ ์‹œ์Šคํ…œ์ธ EEEVis๋ฅผ ์„ค๊ณ„ํ–ˆ๋‹ค. ์ด ์‹œ์Šคํ…œ์€ ์—ฌ๋Ÿฌ ์ข…์˜ ์„œ์ง€ ์ •๋ณด ์‹œ๊ฐํ™” ์ธํ„ฐํŽ˜์ด์Šค์™€ PubTator์˜ ์ฃผ์„ ์ •๋ณด๋ฅผ ํ™œ์šฉํ•˜์—ฌ PubMed ๊ฒ€์ƒ‰ ์—”์ง„์˜ ๊ฒ€์ƒ‰ ๊ฒฐ๊ณผ๋ฅผ ์ฆ๊ฐ•ํ•˜๋Š” ์‹œ์Šคํ…œ์ด๋ฉฐ, ์ด๋ฅผ ํ‰๊ฐ€ํ•˜๊ธฐ ์œ„ํ•ด ์ด 24๋ช…์˜ ์˜์‚ฌ์™€ ํ•จ๊ป˜ ์‚ฌ์šฉ์ž ์—ฐ๊ตฌ๋ฅผ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ์ด ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์˜ํ•™ ๋ฌธํ—Œ ๊ฒ€์ƒ‰ ์‹œ์Šคํ…œ์— ๋Œ€ํ•œ ์„ค๊ณ„ ์ง€์นจ๊ณผ ๊ณผ์ œ๋ฅผ ์ œ์‹œํ•œ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ์„ธ ๋ฒˆ์งธ ๋””์ž์ธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ž„์˜์˜ ์œ ์ „์ž๊ตฐ์˜ ์œ ์ „์ž ๋ฐœํ˜„ ํŒจํ„ด์„ ์ฃผ์š” ์•” ์œ ํ˜•์— ๋”ฐ๋ผ ์‹œ๊ฐํ™”ํ•˜๊ณ  ๋ถ„์„ํ•  ์ˆ˜ ์žˆ๋Š” ์‹œ์Šคํ…œ์ธ GeneVis๋ฅผ ์„ค๊ณ„ํ•˜์˜€๋‹ค. ์•” ์œ ํ˜•์— ๋”ฐ๋ฅธ ์œ ์ „์ž ๋ฐœํ˜„ ํŒจํ„ด์˜ ๋ถ„์„๊ณผ ๋น„๊ต๋Š” ์•” ์—ฐ๊ตฌ์ž๋“ค์ด ์ •๋ฐ€ ์˜ํ•™์—์„œ ์ƒ์ฒด ์ง€ํ‘œ(Biomarker)๋ฅผ ๋ฐœ๊ฒฌํ•˜๊ธฐ ์œ„ํ•ด ๋นˆ๋ฒˆํžˆ ์ˆ˜ํ–‰ํ•˜๋Š” ์ž‘์—…์ด๋‹ค. ์šฐ๋ฆฌ๋Š” ์ข…์–‘ํ•™ ์ „๋ฌธ๊ฐ€ ๋ฐ ์œ ์ „์ฒดํ•™ ์ „๋ฌธ๊ฐ€ ์ด 4์ธ์„ ๋Œ€์ƒ์œผ๋กœ ์‚ฌ๋ก€ ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•˜์˜€๊ณ , ๊ทธ ๊ฒฐ๊ณผ GeneVis๊ฐ€ ํ•ด๋‹น ์ž‘์—…์„ ๋” ์ˆ˜์›”ํ•˜๊ฒŒ ์ˆ˜ํ–‰ํ•˜๋Š” ๊ฒƒ๊ณผ ๊ธฐ์กด์˜ ๋ฐ์ดํ„ฐ์—์„œ ์ƒˆ๋กœ์šด ์ •๋ณด๋ฅผ ๋„์ถœํ•˜๋Š” ๊ฒƒ์— ๋„์›€์ด ๋˜์—ˆ์Œ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์œ„์˜ ์„ธ ๋””์ž์ธ ์—ฐ๊ตฌ์˜ ๊ฒฐ๊ณผ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ, ๋ณธ ๋…ผ๋ฌธ์€ ์‚ฌ์šฉ์ž ๋ถ„์„๊ณผ ์ž‘์—… ๋ถ„์„์„ ๋™๋ฐ˜ํ•œ ์‹œ๊ฐ์  ๋ถ„์„ ๋ฐฉ๋ฒ•๋ก ์ด ์˜ํ•™ ์—ฐ๊ตฌ์˜ ๊ทผ๊ฑฐ ๊ด€๋ จ ์ž‘์—…์˜ ์–ด๋ ค์›€์„ ํ•ด์†Œํ•˜๊ณ , ๋ถ„์„ ๋ฐ์ดํ„ฐ์— ๋Œ€ํ•œ ๋ณด๋‹ค ๋‚˜์€ ์ดํ•ด๋ฅผ ์ œ๊ณตํ•˜๋Š” ๊ฒƒ์ด ๊ฐ€๋Šฅํ•˜๋‹ค๊ณ  ๊ฒฐ๋ก  ๋‚ด๋ฆฐ๋‹ค.CHAPTER1 Introduction 1 1.1 Background and Motivation 1 1.2 Dissertation Outline 5 CHAPTER2 Related Work 7 2.1 Evidence Mapping: Graphical Representation for a Scientific Evidence Landscape 7 2.2 Scientific Literature Visualizations and Bibliography Visualizations 9 2.3 Visual Anlytics Systems for Genomics Data sets and Research Tasks 10 CHAPTER3 PLOEM: An Interactive Visualization Tool for Effective Evidence Mapping with Biomedical literature 12 3.1 Introduction 12 3.2 Visual Representations and Interactions of PLOEM 14 3.2.1 Overview of the PICO Criteria 14 3.2.2 Trend Visualization with the Timeline view 17 3.2.3 Representing the PICO Co-occurrence with the Relation view 20 3.2.4 Study detail view 22 3.3 Usage Scenarios: Visualizing Various Study Sizes with PLOEM 23 3.4 Conclusion 24 CHAPTER4 EEEvis: Efficacy improvement in searching MEDLINE database using a novel PubMed visual analytic system 26 4.1 Introduction 26 4.1.1 Motivation 26 4.1.2 Preliminary Survey: A Questionnaire on conventional literature search methods 28 4.1.3 Design Requirements for Biomedical Literature Search Systems 36 4.2 System and Interface Implementation of EEEVis 37 4.2.1 System Overview 37 4.2.2 Bibliography Filters 40 4.2.3 Timeline View 41 4.2.4 Co-authorship Network View 43 4.2.5 Article List and Detail View 44 4.3 User Study 46 4.3.1 Participants 46 4.3.2 Procedures 48 4.3.3 Results and Observations 50 4.4 Discussion 54 4.4.1 Design Implications 56 4.4.2 Limitations and Future Work 57 4.5 Conclusions 59 CHAPTER5 GeneVis: A Visual Analytics Systemfor Gene Signature Analysis in Cancers 68 5.1 Motivation 68 5.2 System and Interface Implementation 69 5.2.1 System Overview 69 5.2.2 Gene Expression Detail View 71 5.2.3 Gene Vector Projection View 72 5.2.4 Gene x Cancer Type Heatmap view 74 5.2.5 User Interaction in Multiple Coordinated Views 76 5.3 Case Studies 76 5.3.1 Participants 76 5.3.2 Task and Procedures 76 5.3.3 Case1: Identifying SimilarGeneSignatures with TGFB1in Hallmark Gene Sets 80 5.3.4 Case2: Identifying Cluster Patterns in the HRD data set 81 5.3.5 Results 82 5.4 Summary 85 CHAPTER6 Conclusion and future work 86 6.1 Conclusion 86 6.2 Future Work 87 Abstract (Korean) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102๋ฐ•

    TEM-CL ๊ธฐ์ˆ ์„ ํ†ตํ•œ ์‚ฌํŒŒ์ด์–ด ๊ธฐํŒ ์œ„ ์„ฑ์žฅํ•œ ฮฒ-Ga2O3์˜ ๊ตฌ์กฐ์ , ๊ด‘ํ•™์  ์„ฑ์งˆ์— ๊ด€ํ•œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์žฌ๋ฃŒ๊ณตํ•™๋ถ€, 2020. 8. ๊น€์˜์šด.๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ฮฒ-Ga2O3์˜ ๊ตฌ์กฐ์ , ๊ด‘ํ•™์  ์„ฑ์งˆ์„ TEM๊ณผ TEM-CL ์‹œ์Šคํ…œ์„ ํ†ตํ•ด ๋ถ„์„ํ•˜์˜€๋‹ค. ์ฒซ ๋ฒˆ์งธ ํŒŒํŠธ์—์„œ๋Š” ฮฒ-Ga2O3๋ฅผ ์‚ฌํŒŒ์ด์–ด ๊ธฐํŒ ์œ„์— ์ฆ์ฐฉ์‹œํ‚จ XTEM ์ƒ˜ํ”Œ์„ ๋ช…์‹œ์•ผ์ƒ ์ด๋ฏธ์ง€, ์•”์‹œ์•ผ์ƒ ์ด๋ฏธ์ง€, ํšŒ์ ˆ ํŒจํ„ด, ๊ณ ๋ถ„ํ•ด๋Šฅ ์ด๋ฏธ์ง€๋ฅผ ์ด์šฉํ•˜์—ฌ ๋ถ„์„์„ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ์ผ๋ฐ˜์ ์œผ๋กœ ์‚ฌํŒŒ์ด์–ด ๊ธฐํŒ ์œ„์— ์„ฑ์žฅํ•œ ฮฒ-Ga2O3์˜ ์ •์ถ• ๋ฐฉํ–ฅ์€ ํฌ๊ฒŒ ๋‘ ๊ฐ€์ง€๋กœ ๋‚˜๋‰˜์—ˆ๊ณ , ๊ทธ ์ค‘ [102] ์ •์ถ•์— ํ•ด๋‹นํ•˜๋Š” ํšŒ์ ˆ ํŒจํ„ด์„ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋ถ„์„ ๊ฒฐ๊ณผ ์ค‘ ์ด์ „๊นŒ์ง€๋Š” ์ž์„ธํžˆ ์—ฐ๊ตฌ๋˜์ง€ ์•Š์•˜๋˜ ์ƒˆ๋กœ์šด ํšŒ์ ˆ spot์„ ๋ฐœ๊ฒฌํ•˜์˜€์œผ๋ฉฐ, ์ด spot์€ JCPDS์™€ JEMS software๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ [1-92] ์ •์ถ•์˜ (512)๋ผ๋Š” ๊ฒƒ์ž„์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋˜ํ•œ ์ด๋ก ์ ์œผ๋กœ๋„ ํƒ€๋‹นํ•œ์ง€์— ๋Œ€ํ•˜์—ฌ ์ง์ ‘ ์›์ž๋ฅผ ์Œ“์•„ ์˜ฌ๋ ค ์‚ฌํŒŒ์ด์–ด ๊ธฐํŒ๊ณผ์˜ ๊ฒฉ์ž ์ƒ์ˆ˜, ์„ฑ์žฅ ๋ฐฉํ–ฅ ๋“ฑ์— ๋Œ€ํ•œ ๊ฒ€ํ† ๋ฅผ ๋งˆ์ณค๋‹ค. ๋‘ ๋ฒˆ์งธ ํŒŒํŠธ์—์„œ๋Š” ฮฒ-Ga2O3์˜ TEM-CL ์Œ๊ทนํ˜•๊ด‘ ์‹ ํ˜ธ ์‹œ์Šคํ…œ์„ ์ด์šฉํ•˜์—ฌ peak ๋ถ„์„์„ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ํฌ๊ฒŒ 3๊ฐ€์ง€์˜ peak์œผ๋กœ ๋‚˜๋‰˜๋Š”๋ฐ, ์ฒซ ๋ฒˆ์งธ๋Š” ์ค‘์‹ฌ ํŒŒ์žฅ 350nm๋ฅผ ๊ฐ€์ง€๋Š” UV ๋Œ€์—ญ์ด๋‹ค. ์ด ๋Œ€์—ญ์€ ์‚ฌํŒŒ์ด์–ด ๊ธฐํŒ ๋ฐ”๋กœ ์œ„์— ์–‡์€ ํญ์—์„œ ๊ฐ€์žฅ ๊ฐ•ํ•œ ์‹ ํ˜ธ๋ฅผ ๋‚˜ํƒ€๋‚ธ๋‹ค. ์ด ๋ถ€๋ถ„์˜ ์‹ ํ˜ธ๊ฐ€ ๊ฐ€์žฅ ๊ฐ•ํ•˜๊ฒŒ ๋‚˜ํƒ€๋‚˜๋Š” ์ด์œ ์— ๋Œ€ํ•ด์„œ๋Š” ์•„์ง ๋ฐํžˆ์ง€ ๋ชปํ•˜์˜€๊ณ , ์ถ”ํ›„ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ์ง„ํ–‰ํ•  ์‚ฌํ•ญ์ด๋‹ค. ๋‘ ๋ฒˆ์งธ peak์˜ ์ค‘์‹ฌ ํŒŒ์žฅ์€ 373nm๋ฅผ ๊ฐ€์ง€๋Š” UV ๋Œ€์—ญ์ด๋‹ค. ์ด ํŒŒ์žฅ ๋Œ€์—์„œ๋Š” ์ฒซ ๋ฒˆ์งธ UV ๋Œ€์—ญ์˜ ์–‡์€ ํญ ์œ„๋กœ columnarํ•˜๊ฒŒ ์„ฑ์žฅํ•˜๋Š” ฮฒ-Ga2O3์˜ ๊ตฌ์กฐ๋ฅผ ํ™•์ธํ•  ์ˆ˜ ์žˆ๋‹ค. ์„ธ ๋ฒˆ์งธ peak์˜ ์ค‘์‹ฌ ํŒŒ์žฅ์€ 424nm๋กœ BL ๋Œ€์—ญ์„ ๊ฐ€์ง„๋‹ค. UV์—์„œ ๋ณด์—ฌ์ค€ ๊ฒƒ๊ณผ ๋‹ค๋ฅด๊ฒŒ ์ด ํŒŒ์žฅ ๋Œ€์—์„œ๋Š” ์‚ฌํŒŒ์ด์–ด ๊ธฐํŒ ๋ฐ”๋กœ ์œ„๋ถ€ํ„ฐ columnarํ•˜๊ฒŒ ์„ฑ์žฅํ•˜๋Š” ฮฒ-Ga2O3์˜ ๊ตฌ์กฐ๋ฅผ ํ™•์ธํ•  ์ˆ˜ ์žˆ๋‹ค. ฮฒ-Ga2O3์—์„œ ์ค‘์‹ฌ ํŒŒ์žฅ 350nm๋ฅผ ๊ฐ€์ง€๋Š” ๋‹จ์ƒ‰ ํŒŒ์žฅ ์ด๋ฏธ์ง€์—์„œ ๋ณด์ด๋Š” ์‚ฌํŒŒ์ด์–ด ๊ธฐํŒ ๋ฐ”๋กœ ์œ„, ์–‡์€ ํญ์˜ ฮฒ-Ga2O3 ์˜์—ญ์ด ๋‹ค๋ฅธ ์˜์—ญ๊ณผ ์–ด๋– ํ•œ ์ฐจ์ด๋ฅผ ํ†ตํ•˜์—ฌ ๋ฐœ๊ด‘๋˜๋Š”์ง€์— ๋Œ€ํ•ด์„œ๋Š” ์ •ํ™•ํžˆ ๋ฐํžˆ๊ฒŒ ๋œ๋‹ค๋ฉด ฮฒ-Ga2O3์˜ ๊ด‘ํ•™์  ์„ฑ์งˆ์„ ์ดํ•ดํ•˜๋Š”๋ฐ ํฌ๊ฒŒ ๊ธฐ์—ฌํ•  ๊ฒƒ์œผ๋กœ ํŒ๋‹จํ•œ๋‹ค.Cathodoluminescence is a phenomenon when light emitted by accelerated electron beams impacting on a material join together and thereby causing photon emission. This light is emitted in a large range, from ultraviolet to infrared, which is a great advantage in that it allows one to directly measure the band gap of the material. Until now, methods for measuring cathodoluminescence with electron microscope include scanning electron microscope (SEM) and transmission electron microscope (TEM). This disadvantage of using the SEM is that it has low resolution and could provide information from the surface of the material. However, if cathodoluminescence is measured using a TEM, higher resolution allows one to make a more accurate peak analysis on the peak and even on the internal structure of the material thank to the basic characteristics of the TEM that transmits the electron beam. Among the methods of measuring cathodoluminescence using TEM, this study implements the method using a TEM holder produced directly in our laboratory. The TEM holder has a dewer that can hold liquid nitrogen, which can drop the temperature of the sample to extremely low temperature. This minimizes the energy caused by the phonon vibrations, thus confirming a more accurate structure within the band gap. In addition, the implemented method also includes using the software QTCL produced in our laboratory. ฮฒ-Ga2O3 is a substance with various phases such as ฮฑ-, ฮฒ-, ฮณ-, ฮด-, ฮต- and so on. Among them, ฮฒ-Ga2O3 has a monoclinic structure and a C2/m spatial family, known to be the most stable. ฮฒ-Ga2O3 is a material with a wide band gap of 4.6-4.9eV and is widely used in the application of several electronic devices using these properties. In this study, the structural and optical properties are measured using materials in which ฮฒ-Ga2O3 grown on sapphire substrates and the analysis is concerned. It is crucial to first discuss the study on the structural properties of ฮฒ-Ga2O3. Since sapphire has a Hexagonal structure, when observing an XTEM sample, sapphire substrates has two main zone-axis directions [2-1-10] and [10-10]. ฮฒ-Ga2O3 deposition on sapphire substrates also has two directions [102], [010], of which [102] Diffraction Patterns are not reported much. The experiment was conducted on sapphire substrates with 100 nm depth of deposition of ฮฒ-Ga2O3 and IGZO (Indium-Gallium-Zinc-Oxygen) respectively. An unconfirmed crystal surface was found during the observation on the XTEM specimen, which was analyzed by its Diffraction Patterns, Dark Field, and High Resolution images. The results for the analysis were found to be ฮฒ-Ga2O3 (512) on the zone-axis [1-92]. The second part is about the study on the optical properties of ฮฒ-Ga2O3. ฮฒ-Ga2O3 has three emission areas: UV, Blue and Green, From near-infrared to visible light. UV lights and Blue lights are wavelength regions that also appear in ฮฒ-Ga2O3 that are undoped. Based on this point, the cathodoluminescence analysis of ฮฒ-Ga2O3 was conducted with the TEM-CL system. The experiment was conducted with an XTEM specimen in which ฮฒ-Ga2O3 200nm was deposited on sapphire substrates. The results showed that the light in the UV region was divided into two parts. UV(I) was strongly derived from the area having a thin width just above the sapphire substrates. UV(โ…ก) and Blue also confirmed that the cause of luminescence of ฮฒ-Ga2O3 that we have been working on is due to the transfer between the Self-Trapped-Hole (STH) and the Conduction Band transition and the Donor and the Acceptor transition respectively. Future experiments will greatly contribute to the determination of the optical properties of ฮฒ-Ga2O3 by analyzing the area where UV(I) occurs most and comparing it to the other areas of ฮฒ-Ga2O3.1. INTRODUCTION 1 1.1 TEM-Cathodolumienscence(CL) 1 1.2 Basic Properties of ฮฒ-Ga2O3 4 1.3 Experimental Detail 6 2. STRUCTURAL PROPERTIES OF ฮ’-GA2O3 8 2.1 XTEM Image and DP analysis 8 2.2 Analysis of HR Image 10 2.3 PTEM Image and DP analysis 14 2.4 Atomic modeling 15 3. OPTICAL PROPERTIES OF ฮ’-GA2O3 18 3.1 TEM-CL spectrum analysis 18 3.2 Monochromatic Image analysis 22 3.3 Analyze the cause of thin width in UV(โ… ) 25 4. CONCLUSION 27 5. REFERENCES 29Maste

    ๋ฒ ํŠธ๋‚จ ๋ƒ์งฑ ์ง€์—ญ์˜ ๋Ž…๊ธฐ ์—ญํ•™์กฐ์‚ฌ: ๋Ž…๊ธฐ์˜ ์ž„์ƒ์ง„๋‹จ๊ณผ ์‹คํ—˜์‹ค์ง„๋‹จ์˜ ์—ฐ๊ด€์„ฑ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๋ณด๊ฑด๋Œ€ํ•™์› ๋ณด๊ฑดํ•™๊ณผ, 2018. 2. ์กฐ์„ฑ์ผ.Dengue is a leading cause of morbidity in Vietnam with gradual increase from 32.5 per 100,000 population in 2000 to 120.0 per 100,000 population in 2009. In Vietnam, almost all cases of dengue virus (DENV) infection are diagnosed clinically based on the WHO guideline (2009), but it is commonly under-reported and many cases are misclassified due to its broad spectrum of symptoms shared with other febrile diseases. On behalf of the Dengue Vaccine Initiative (DVI), the International Vaccine Institute (IVI) assessed the strength of association between clinical and laboratory-confirmed diagnoses of dengue infection from a passive hospital-based surveillance study in Nha Trang City, in Khanh Hoa province, Vietnam from July 2014 to December 2015. The study was designed to determine the true burden of dengue, symptomatic infection of all fever cases among children and adults between 1 and 55 years of age in a defined population. Clinical signs and symptoms of 553 dengue patients and 1,152 non-dengue patients (laboratory-confirmed by IgM and IgG capture ELISA or real-time PCR) were analyzed. Leucopenia (OR = 6.03), thrombocytopenia (OR = 1.97), rash (OR = 1.90), headache (OR = 1.75), arthralgia (OR = 1.75), petechiae (OR = 1.71), and nausea/vomiting (OR = 1.42) were highly associated with laboratory-positive dengue cases in the absence of respiratory signs and symptoms such as rhinorrhea (OR = 0.41) and expectoration (OR = 0.39). A comparison between adults and children of laboratory-confirmed dengue cases revealed that the frequency of clinical signs and symptoms was different between two age groups. DENV infected adults were more likely to present flushed face (OR = 2.13), headache (OR = 2.10), rash (OR = 1.96), thrombocytopenia (OR = 1.91), and arthralgia (OR = 1.83) which were not apparent to DENV infected children. Overall sensitivity and specificity of clinical diagnoses were 57.7% and 92.0% with diagnostic accuracy of 80.9%. Once validated, those key clinical features for children and adult patients with dengue infection may improve the future clinical outcomes, especially in the resource-poor dengue endemic countries, as they would allow more closely monitoring of selected patients and it may affect the sensitivity of clinical diagnosis.I. Introduction 9 1. Dengue virus infection and its clinical manifestations 9 2. Global burden of dengue 11 3. Dengue in Vietnam 12 4. Objective of the study 15 II. Methods 16 1. Study area and population 16 2. Study Design 18 3. Sample collection 19 4. Laboratory testing 19 5. Case definitions of clinical diagnosis 20 6. Data management 21 7. Statistical analysis 22 8. Ethics 22 III. Results 24 1. Study enrollment and lab results 24 2. Demographic information of dengue patients 27 3. Medical information of dengue patients 31 4. Dengue serotypes 31 5. Seasonal and regional distribution of dengue cases 32 6. Clinical features of dengue patients 36 7. Comparison of clinical features between adults and children 41 8. Evaluation of clinical diagnostic accuracy 44 IV. Discussion 47 V. Reference 54 VI. ๊ตญ๋ฌธ์ดˆ๋ก 61Maste

    The Effect of duration of ischemia and body temperature on the expression of BaxBcl-2 in the hippocampus of gerbil in transient global ischemia

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์˜ํ•™๊ณผ ์‹ ๊ฒฝ๊ณผํ•™์ „๊ณต,2000.Docto

    ์•ก์ฒดํ‘œ์  ๊ฐ€์†๊ธฐ ๋น”์ฐฝ์˜ ์—ด์ ,๊ตฌ์กฐ์  ๊ฑด์ „์„ฑ ํ‰๊ฐ€ ๋ฐ ์„ค๊ณ„

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    Thesis (master`s)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์›์žํ•ต๊ณตํ•™๊ณผ,2001.Maste

    Gerbil์˜ ์ผ๊ณผ์„ฑ ์ „๋‡Œํ—ˆํ˜ˆ๋ชจ๋ธ์—์„œ Lamotrigine์— ์˜ํ•œ ํ•ด๋งˆ์˜ ์ง€์—ฐ์„ฑ ์‹ ๊ฒฝ์„ธํฌ์†์ƒ ๊ฐ์†Œํšจ๊ณผ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์˜ํ•™๊ณผ ์‹ ๊ฒฝ๊ณผํ•™์ „๊ณต,1998.Maste

    ๋„๋•์  ํ•ด์ด ์ƒํ™ฉ์—์„œ ๊ธฐ์—…์˜ ์ž๋ณธ์ฆ์ž๋ฐฉ๋ฒ•์— ๊ด€ํ•œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ฒฝ์ œํ•™๋ถ€, 2017. 2. ๊น€์„ ๊ตฌ.๋ณธ ๋…ผ๋ฌธ์€ ๊ธˆ์œต์‹œ์žฅ์— ๋„๋•์  ํ•ด์ด๊ฐ€ ์กด์žฌํ•˜๊ณ  ํˆฌ์ž๋น„์šฉ์ด ๊ณ ์ •๋˜์–ด ์žˆ์„ ๋•Œ ๊ธฐ์—…์ด ๋ณด์œ ํ•œ ์ž๋ณธ๋Ÿ‰์— ๋”ฐ๋ผ ์ฑ„๊ถŒ๋ฐœํ–‰, ์€ํ–‰ ๋Œ€์ถœ, ์ฃผ์‹ ๋ฐœํ–‰๊ณผ ๊ฐ™์€ ์ž๋ณธ์ฆ์ž๋ฐฉ๋ฒ• ๊ฐ€์šด๋ฐ ์–ด๋–ค ๊ฒƒ์„ ์„ ํƒํ•˜๋Š”์ง€ ๋ฐํžŒ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ฃผ์‹๋ฐœํ–‰์„ ๊ธฐ์—…์˜ ์ž๋ณธ์ฆ์ž๋ฐฉ๋ฒ•์œผ๋กœ ๊ณ ๋ คํ•˜์ง€ ์•Š์•˜๋˜ ๊ธฐ์กด ๋ชจํ˜•์— ์ฃผ์‹๋ฐœํ–‰์„ ํ†ตํ•œ ์ž๋ณธ์ฆ์ž๋ฐฉ์‹์„ ์ถ”๊ฐ€ํ•˜์—ฌ๋„ ๊ท ํ˜•์ด ๋ณ€ํ•˜์ง€ ์•Š์Œ์„ ๋ณด์ธ๋‹ค. ๋˜ํ•œ ๊ธฐ์กด ๋ชจํ˜•์— ํˆฌ์ž๊ณ„ํš์•ˆ ์„ ํƒ ๋ณ€์ˆ˜๋ฅผ ์ถ”๊ฐ€ํ•  ๊ฒฝ์šฐ ๊ธฐ์—…์ด ์ฃผ์‹๋ฐœํ–‰์„ ํฌํ•จํ•œ ๋‹ค์–‘ํ•œ ํ˜•ํƒœ๋กœ ์™ธ๋ถ€์ž๋ณธ์„ ์ฐจ์ž…ํ•˜๋Š” ๊ฒƒ์„ ๋ฐํžŒ๋‹ค. ๋ณธ ๋ชจํ˜•์˜ ๊ฒฐ๊ณผ๋Š” ์ผ๋ณธ ์ž๋ณธ์‹œ์žฅ์— ๋‚˜ํƒ€๋‚œ ๋ณ€ํ™”์™€ ๋Œ€๋žต์ ์œผ๋กœ ์ผ์น˜ํ•จ์„ ๋ฐํžŒ๋‹ค.This paper studies how a firm determines its financial structure by raising funds through equity issues, bond financing, and bank debt under the moral hazard when the investment cost is fixed. It shows that the equilibrium discussed earlier in the literature which did not consider an option of equity issue does not change even if the option is taken into consideration. It also shows that a firm decides to raise funds in different ways including equity issues in case the firm has a project choice. The predictions of the model presented in this paper are broadly consistent with the changes in corporate financing in Japan during the 1980s and 1990s since the liberalization of its financial market.1. ์„œ๋ก  1 2. ๊ธฐ๋ณธ ๋ชจํ˜• 3 3. ํšŒ์‚ฌ์˜ ์ž๋ณธ์ฆ์ž๋ฐฉ๋ฒ• 5 3.1 ์ง์ ‘๊ธˆ์œต 5 3.2 ๊ฐ„์ ‘๊ธˆ์œต 10 4. ํ™•์žฅ ๋ชจํ˜• 16 5. ๋งบ์Œ๋ง 22 ์ฐธ๊ณ ๋ฌธํ—Œ 24 Abstract 25Maste

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    Thesis(doctoral)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :ํ˜‘๋™๊ณผ์ • ์œ ์ „๊ณตํ•™์ „๊ณต,2006.Docto
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