5,487 research outputs found

    Testing in the incremental design and development of complex products

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    Testing is an important aspect of design and development which consumes significant time and resource in many companies. However, it has received less research attention than many other activities in product development, and especially, very few publications report empirical studies of engineering testing. Such studies are needed to establish the importance of testing and inform the development of pragmatic support methods. This paper combines insights from literature study with findings from three empirical studies of testing. The case studies concern incrementally developed complex products in the automotive domain. A description of testing practice as observed in these studies is provided, confirming that testing activities are used for multiple purposes depending on the context, and are intertwined with design from start to finish of the development process, not done after it as many models depict. Descriptive process models are developed to indicate some of the key insights, and opportunities for further research are suggested

    Hybrid optimizer for expeditious modeling of virtual urban environments

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    Tese de mestrado. Engenharia Informรกtica. Faculdade de Engenharia. Universidade do Porto. 200

    Harnessing the Power of Digital Platforms to Accelerate Adoption Rates of Emerging Technologies and Innovations

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    Excerpt from the Proceedings of the Nineteenth Annual Acquisition Research SymposiumThe recent Overmatch championed Artificial Intelligence and Networks (AINet) Advanced Naval Technology Exercise (ANTX) demonstrated an alternative all-digital ANTX format enabled by integrated Rapid Innovation Labs (iRILs). This resulted in shortened ANTX planning and execution timelines, increased focus on technologies of interest, earlier integration into naval architectures, sharing of relevant operational data with participants, and meaningful feedback to developers throughout integration phases, informing research and development (R&D) and program acquisitions. An iRIL is a digital environment and an acquisition tool used to address priority Fleet needs, evaluate technologies and prototypes, and inform and influence external partner R&D investments. An all-digital iRIL can facilitate faster, smaller cycles of iterative experimentation of component technologies of interest within representative Fleet architectures and simulated operational environments. Future applications of iRILs could fundamentally change the way we acquire systems. The use of open competitive events such as an ANTX Prize Challenge could yield component level, containerized technologies of interest that are matured throughout the event process and can be assessed as well-behaved. Such well-behaved software containers or component technologies may enter the Overmatch Software Armory (OSA) or Live, Virtual, and Constructive (LVC) pipelines, achieving rapid authorities to operate (ATO), cycling to a ship within days.Approved for public release; distribution is unlimited

    ํ™˜์ž๋งž์ถคํ˜• ์น˜๋ฃŒ๋ฅผ ์œ„ํ•œ ์ฒด์™ธ ํ•ญ์•”์ œ ์Šคํฌ๋ฆฌ๋‹์šฉ ๋ฐ”์ด์˜ค์นฉ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์ „๊ธฐยท์ •๋ณด๊ณตํ•™๋ถ€, 2020. 8. ๊ถŒ์„ฑํ›ˆ.์ •๋ฐ€์˜ํ•™(Precision Medicine) ํ˜น์€ ๊ฐœ์ธ๋งž์ถค์˜ํ•™(Personalized Medicine)์€ ๊ฐœ๊ฐœ์ธ์˜ ์ตœ์ ํ™”๋œ ์น˜๋ฃŒ๋ฐฉ๋ฒ•์„ ๊ฒฐ์ •ํ•˜๋Š” ๊ฒƒ์„ ๋ชฉํ‘œ๋กœ ํ•˜๋Š” ์˜ํ•™์˜ ํŒจ๋Ÿฌ๋‹ค์ž„์ด๋‹ค. ํŠนํžˆ, ์ž„์ƒ์ข…์–‘ํ•™์—์„œ๋Š” ์ฐจ์„ธ๋Œ€์—ผ๊ธฐ์„œ์—ด๋ถ„์„(NGS), ์ „์‚ฌ์ฒด์„œ์—ด๋ถ„์„, ๊ทธ๋ฆฌ๊ณ  ์งˆ๋Ÿ‰๋ถ„์„๋ฒ•๋“ค์„ ํ†ตํ•œ ํ™˜์ž์˜ ๋ถ„์ž ํ”„๋กœํŒŒ์ผ(molecular profile) ๋ฐฉ๋ฒ•์ด ๋ฐœ์ „ํ•ด์˜ค๊ณ  ์žˆ์œผ๋ฉฐ, ์ด๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ํ™˜์ž๋ฅผ ์„ธ๋ถ„ํ™”ํ•˜์—ฌ ๋งž์ถคํ˜• ์น˜๋ฃŒ๋ฅผ ๊ตฌํ˜„ํ•˜๋ ค๊ณ  ๋…ธ๋ ฅํ•ด์˜ค๊ณ  ์žˆ๋‹ค. ํ•˜์ง€๋งŒ, ์—ฌ์ „ํžˆ ํ˜„ ์ˆ˜์ค€์—์„œ ์ดํ•ด๋˜์ง€ ๋ชปํ•˜๋Š” ์ˆ˜์ค€์˜ ์ข…์–‘ ์ด์งˆ์„ฑ(tumor heterogeneity)๊ณผ ์˜ค๋žœ ์ฒ˜๋ฐฉ๊ธฐ๋ก์„ ๊ฐ€์ง„ ํ™˜์ž๊ตฐ๋“ค์˜ ํ•ญ์•”์ œ ํš๋“๋‚ด์„ฑ(acquired resistance) ๋“ฑ์˜ ์›์ธ์œผ๋กœ ๋งž์ถคํ˜• ํ™˜์ž ์ฒ˜๋ฐฉ์€ ์‰ฝ์ง€ ์•Š์€ ๊ฒฝ์šฐ๊ฐ€ ๋งŽ๋‹ค. ์ด๋Ÿฌํ•œ ๊ฒฝ์šฐ ํ™˜์ž๋กœ๋ถ€ํ„ฐ ์–ป์–ด์ง„ ์•”์„ธํฌ, ์กฐ์ง์œผ๋กœ๋ถ€ํ„ฐ ์–ป์–ด์ง„ ์ผ์ฐจ์„ธํฌ ํ˜น์€ ์ฒด์™ธ ๋ฐฐ์–‘๋œ ์„ธํฌ, ์ŠคํŽ˜๋กœ์ด๋“œ, ์žฅ๊ธฐ์œ ์‚ฌ์ฒด ๋“ฑ์„ ์ด์šฉํ•˜์—ฌ ๊ณ ์†๋‹ค์ค‘์•ฝ๋ฌผ์Šคํฌ๋ฆฌ๋‹๊ธฐ์ˆ ์„ ํ†ตํ•œ ๋งž์ถคํ˜• ํ•ญ์•”์ œ๋ฅผ ์„ ๋ณ„ํ•ด๋‚ด๋Š” ์ฒด์™ธ ์•ฝ๋ฌผ์ง„๋‹จ ๊ธฐ์ˆ ์„ ์ƒ๊ฐํ•ด๋‚ผ ์ˆ˜ ์žˆ๋Š”๋ฐ, ์ด๋Š” ๊ธฐ์กด์˜ ์œ ์ „์ฒด ๊ธฐ๋ฐ˜์˜ ์‹œ๋„์™€ ๋ณ‘ํ–‰๋˜์–ด ๊ฐœ๊ฐœ์˜ ํ™˜์ž๋“ค์—๊ฒŒ ๋”์šฑ ์ ํ•ฉํ•œ ์น˜๋ฃŒ๋ฐฉ๋ฒ•์„ ์ฐพ๋Š” ๊ฒƒ์ด ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•œ๋‹ค. ํ•˜์ง€๋งŒ ์ด๋Ÿฌํ•œ ๋ชฉ์ ์˜ ๊ณ ์†๋‹ค์ค‘์•ฝ๋ฌผ์Šคํฌ๋ฆฌ๋‹๊ธฐ์ˆ ์€ ๋†’์€ ํ™œ์šฉ๊ฐ€๋Šฅ์„ฑ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ , ๊ด‘๋ฒ”์œ„ํ•œ ๋ณด๊ธ‰๊ณผ ํ™œ์šฉ์ด ๋˜๊ธฐ์—๋Š” ์ œ์•ฝ์ ์ด ๋งŽ์•˜๋‹ค. ๊ธฐ์กด์˜ ๊ณ ์†๋‹ค์ค‘์•ฝ๋ฌผ์Šคํฌ๋ฆฌ๋‹๊ธฐ์ˆ ์€ ๋งŽ์€ ์–‘์˜ ์ƒ˜ํ”Œ์ด ์†Œ๋ชจ๋˜๊ณ , ๊ฐ’๋น„์‹ผ ์‹œ์•ฝ์˜ ์†Œ๋ชจ๋Ÿ‰๋„ ์ ์ง€ ์•Š์•˜๋‹ค. ๊ฒŒ๋‹ค๊ฐ€, ์ˆ˜์ฒœ ๊ฐ€์ง€ ์ด์ƒ์˜ ์„œ๋กœ ๋‹ค๋ฅธ ๋ฌผ์งˆ๋“ค์„ ํƒ์ƒ‰ํ•˜๊ธฐ ์œ„ํ•ด ๋ฐ˜๋“œ์‹œ ํ•„์š”ํ•œ ๊ณ ๊ฐ€์˜ ์ž๋™ํ™”๋œ ์•ก์ฒด ์šด๋ฐ˜๊ธฐ(liquid handler) ๋“ฑ์ด ํ•„์š”ํ•˜์˜€๋Š”๋ฐ, ์ด๋Ÿฌํ•œ ๋ฌธ์ œ๋กœ ๋Œ€ํ˜• ์ œ์•ฝ์‚ฌ, ์—ฐ๊ตฌ์†Œ ๋“ฑ์„ ์ œ์™ธํ•˜๊ณ ๋Š” ๋„์ž…์ด ์‰ฝ์ง€๊ฐ€ ์•Š์•„ ๊ธฐ์ˆ ์ ‘๊ทผ์„ฑ์ด ์ œํ•œ๋˜์–ด ์žˆ์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋ฐ˜๋„์ฒด๊ณต์ •์—์„œ์˜ ๋…ธ๊ด‘๊ธฐ์ˆ ์„ ์ด์šฉํ•˜์—ฌ ๊ฐœ๊ฐœ์˜ ์‹๋ณ„ํ•  ์ˆ˜ ์žˆ๋Š” ์ฝ”๋“œ๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ๋Š” ์ฝ”๋“œํ™”๋œ ํ•˜์ด๋“œ๋กœ์ ค ๊ธฐ๋ฐ˜์˜ ๊ด‘๊ฒฝํ™”์„ฑํด๋ฆฌ๋จธ ๋ฏธ์„ธ์ž…์ž๋ฅผ ๋งŒ๋“ค์–ด, ์ด๋ฅผ ์›ํ•˜๋Š” ์•”์„ธํฌ์— ์•ฝ๋ฌผ ์Šคํฌ๋ฆฌ๋‹์„ ํ•ด๋ณด๊ณ ์ž ํ•˜๋Š” ๋‹ค์–‘ํ•œ ์•ฝ๋ฌผ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ๋ฅผ ์ด์šฉ ๊ฐ๊ฐ์˜ ์ฝ”๋“œํ™”๋œ ๋ฏธ์„ธ์ž…์ž์— ํก์ˆ˜์‹œ์ผœ ์•ฝ๋ฌผ-๋ฏธ์„ธ์ž…์ž ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ๋ฅผ ์ œ์ž‘ํ•œ๋‹ค. ๊ทธํ›„, ๊ฐ’๋น„์‹ผ ์–ด๋ ˆ์ด ์ œ์ž‘์šฉ ์Šคํฌํ„ฐ ํ˜น์€ ๋””์ŠคํŽœ์„œ ์žฅ๋น„์—†์ด ๊ฐ„๋‹จํ•œ ์ž๊ธฐ์กฐ๋ฆฝ์„ ํ†ตํ•ด ๋Œ€๊ทœ๋ชจ์˜ ๋‹ค์–‘ํ•œ ์•ฝ๋ฌผ-ํ•˜์ด๋“œ๋กœ์ ค ์–ด๋ ˆ์ด๋ฅผ ์ œ์ž‘ํ•  ์ˆ˜ ์žˆ๋Š” ๊ธฐ์ˆ ์„ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ๋˜ํ•œ, ์†Œ๋Ÿ‰์˜ ์„ธํฌ๋“ค ๋งŒ์œผ๋กœ๋„ ๋ฏธ์„ธ์šฐ๋ฌผ(microwell) ๊ธฐ๋ฐ˜์˜ ์„ธํฌ์นฉ์— ๋„ํฌํ•˜๋Š” ๋ฐฉ์‹์„ ๊ฐœ๋ฐœํ•˜์˜€์œผ๋ฉฐ, ์ด๋ฅผํ†ตํ•ด ์•ฝ๋ฌผ-ํ•˜์ด๋“œ๋กœ์ ค ์–ด๋ ˆ์ด์™€ ๋ฏธ์„ธ์šฐ๋ฌผ๊ธฐ๋ฐ˜์˜ ์„ธํฌ์นฉ์˜ ๊ฒฐํ•ฉ์œผ๋กœ ์ˆ˜๋ฐฑ-์ˆ˜์ฒœ์˜ ๋‹ค์–‘ํ•œ ์–ด์„ธ์ด๋ฅผ ์ ์€ ์ˆ˜์˜ ์ƒ˜ํ”Œ๋งŒ์œผ๋กœ๋„ ํ•œ๋ฒˆ์— ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ๋Š” ๊ณ ์†๋‹ค์ค‘์•ฝ๋ฌผ์Šคํฌ๋ฆฌ๋‹ ๊ธฐ์ˆ ์„ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ๊ฒŒ ๋งŒ๋“ค์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ ์ œ์‹œํ•œ ์†Œํ˜•ํ™”๋œ ์ฒด์™ธ ํ•ญ์•”์ œ ์Šคํฌ๋ฆฌ๋‹์šฉ ์•ฝ๋ฌผํ”Œ๋žซํผ์€ ๋‹ค์Œ๊ณผ ๊ฐ™์€ ์˜์˜๋ฅผ ๊ฐ€์ง„๋‹ค. ์ ์€ ์ˆ˜์˜ ํ™˜์ž์„ธํฌ ํ˜น์€ ์ƒ˜ํ”Œ์˜ ์–‘์— ์ ์šฉํ•  ์ˆ˜ ์žˆ๋Š”, ์‚ฌ์šฉํ•˜๊ธฐ ์†์‰ฌ์šด ๊ธฐ์ˆ ๋กœ์„œ, ๊ธฐ์กด์˜ ๊ฐ’๋น„์‹ผ ์žฅ๋น„, ์‹œ์•ฝ์˜ ์‚ฌ์šฉ๋Ÿ‰์„ ํš๊ธฐ์ ์œผ๋กœ ์ค„์ผ ์ˆ˜ ์žˆ๋Š” ๊ธฐ์ˆ ์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ ์ œ์•ˆ๋œ ๊ธฐ์ˆ ์„ ํ†ตํ•ด ๊ธฐ์กด์˜ ์žฅ๋น„๋ฅผ ์‚ฌ์šฉํ•  ๋•Œ ์‹œ์•ฝ์˜ ๊ฐ’์ด ๋น„์‹ธ๊ฑฐ๋‚˜, ์žฅ๋น„์˜ ๊ฐ€๊ฒฉ์ด ๋น„์‹ธ์„œ, ํ˜น์€ ๋‹ค๋ฃจ๊ณ ์ž ํ•˜๋Š” ์ƒ˜ํ”Œ์˜ ์–‘์ด ์ œํ•œ์ ์ด์–ด์„œ ๊ธฐ์กด์— ์ ‘๊ทผํ•˜๊ธฐ ํž˜๋“ค์—ˆ๋˜ ๋‹ค์–‘ํ•œ ํ•™์ˆ ์—ฐ๊ตฌ์— ์ ์šฉํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ, ๋ณ‘์›์—์„œ์˜ ์ž„์ƒ์—ฐ๊ตฌ ๋ฐ ์‹ค์ œ ํ™˜์ž๋งž์ถคํ˜• ์น˜๋ฃŒ์— ์‚ฌ์šฉ ๋  ์ˆ˜ ์žˆ๋Š” ์ ‘๊ทผ์„ฑ์„ ํš๊ธฐ์ ์œผ๋กœ ๋†’์ผ ์ˆ˜ ์žˆ๋‹ค. ํŠนํžˆ, ๋น„๊ต์  ์ค‘,์†Œ ๊ทœ๋ชจ์˜ ์—ฐ๊ตฌํ™˜๊ฒฝ์—์„œ๋„ ๋‹ค์–‘ํ•œ ํฌ๊ท€ํ•œ ํ™˜์ž์œ ๋ž˜์„ธํฌ ํ˜น์€ ํ™˜์ž์œ ๋ž˜์˜ค๊ฐ€๋…ธ์ด๋“œ ๋“ฑ๊ณผ ์ ‘๋ชฉํ•˜์—ฌ ์‚ฌ์šฉ๋œ๋‹ค๋ฉด ๋ณธ ํ”Œ๋žซํผ์˜ ๊ฐ€๋Šฅ์„ฑ์„ ๋”์šฑ ๊ทน๋Œ€ํ™” ํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€ํ•œ๋‹ค.Precision or Personalized Medicine is a medical paradigm aimed to determine optimal therapy for individual patient. In particular, clinical oncology has been using methods of molecular profiling for each patient through next-generation sequencing (NGS), mRNA-sequencing, and mass spectrometry, and has been trying to implement personalized treatment. However, personalized treatment based on molecular profiling to each patient is not always possible due to the high level of heterogeneity of tumor that is still not fully understood at the current level and acquired resistance of anti-cancer drug due to cumulative targeted therapy. In such cases, in vitro drug testing platform using primary cells obtained from patients, or patient-derived cells, spheroids, and organoids can make it possible to find a more appropriate treatment for each individual patient. However, though high-throughput drug screening technology for this purpose is of the utmost importance in saving lives, there were many limitations to its wide use in many hospitals. The existing high-throughput drug combination screening technology consumes a large number of samples and consumes a considerable amount of expensive reagents. In addition, expensive automated liquid handlers, which were essential for exploring thousands of different pipetting, were not easy to introduce except for large-sized pharmaceutical companies and research institutes, which limited access to technology. In this study, I construct a heterogeneous drug-loaded microparticle library by fabricating encoded photocurable polymer particle that has individually identifiable codes to track loaded drug. and I load various drug molecules, which I want to test to target cells, into each coded microparticle. Then, I developed to produce heterogeneous drug-laden microparticle arrays through simple self-assembly without the need for a microarray spotter or dispensing machine for generating microarray. I also have developed cell seeding method of seeding small-volume samples into the microwell-based cell chip. By utilizing the drug-laden microparticle hydrogel array and microwell-based cell chip technology, hundreds to thousands of different assays can be done at once with just a small number of samples and low cost. Through the implemented platform, the anti-cancer drug sequential combination screening was conducted on the triple-negative breast cooler (TNBC) cells, which are generally known to be difficult to treat due to lack of known drug target, and the results of screening were analyzed by establishing a library of drugs in the EGFR inhibitory type and drugs in the genotoxin type. In addition, another study was conducted to find optimal drug combinations using patient-derived cells derived from tumors in patients with non-small cell lung cancer that have obtained acquired resistance. Finally, as the growing need for three-dimensional culture, such as spheroid and organoid for having a similar response to in vivo drug testing, it was also developed that microwell-based cell chip that is capable of 3D culture with low-cost and small-volume of cells. The miniaturized in vitro anticancer drug screening platform presented in this study has the following significance. An easy-to-use technique that can be applied to a small number of patient cells or samples, which can dramatically reduce the use of conventional expensive equipment, reagents. The proposed technology in this study can be applied to a variety of academic studies previously inaccessible to high-throughput screening due to the high cost of reagents, the high price of equipment, or the limited amount of samples in conventional drug screening. and this platform can also dramatically increase access to clinical research in hospitals for personalized treatments. In particular, it is expected that the possibility of this platform will be further maximized if it is used in a relatively small and medium-sized research environment by the combined use of various rare samples such as patient-derived cells or patient-derived organoids.Chapter 1 Introduction ๏ผ‘ 1.1 Motivation of this research ๏ผ’ 1.2 Competing technologies and Previous works ๏ผ˜ 1.3 Main Concept: In vitro drug testing using miniaturized encoded drug-laden hydrogel array technology ๏ผ‘๏ผ• Chapter 2 Platform Development of Drug Releasing Hydrogel Microarray ๏ผ’๏ผ 2.1 Encoded Drug-Laden Hydrogel & Library construction ๏ผ’๏ผ‘ 2.2 Array generation of heterogenous drug-laden microparticles. ๏ผ“๏ผ” 2.3 Cell Culturing on Cell Chip and bioassay ๏ผ“๏ผ– Chapter 3 Sequential Drug Combination Screening Assy on TNBC ๏ผ”๏ผ 3.1 Background : Sequential Drug Combination as promising therapeutic option ๏ผ”๏ผ‘ 3.2 Experimental design with sequential drug treatment assay ๏ผ”๏ผ“ 3.3 Technical Issue & its engineering solution ๏ผ”๏ผ” 3.4 Assay Result ๏ผ”๏ผ™ Chapter 4 Drug Combination Assay on Patient-Derived Cells ๏ผ•๏ผ˜ 4.1 Background : Simultaneous Combination Treatment using Patient-Derived Cells ๏ผ•๏ผ™ 4.2 Improvement of Platform for facilitating translational study ๏ผ–๏ผ’ 4.3 Study Design for small-volume drug combinatorial screening with NSCLC patient derived cell ๏ผ–๏ผ• 4.4 Assay Result ๏ผ–๏ผ™ Chapter 5 Development of platform for 3D culture model ๏ผ—๏ผ’ 5.1 3D culturable platform ๏ผ—๏ผ“ 5.2 Development of 3D culture platform based Matrigel scaffold. ๏ผ—๏ผ˜ 5.3 Advantage over conventional 3D culture-based drug testing platform. ๏ผ˜๏ผ• Chapter 6 Conclusion ๏ผ˜๏ผ— Bibliography ๏ผ™๏ผ Abstract in Korean ๏ผ™๏ผ—Docto

    Prospects and challenges for autonomous catalyst discovery viewed from an experimental perspective

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    The urgency with which fundamental questions of energy conversion and the sustainable use of raw materials must be solved today requires new approaches in catalysis research. One way is to couple high-throughput experiments with machine learning methods in autonomous catalyst development. The fact that the active form of a catalyst is only created under working conditions and that the catalytic function is always in a very complex relationship with a number of physical and chemical properties of the material makes it essential to integrate operando experiments into systems of autonomous catalyst development. The analysis of the current state of the art and knowledge revealed a lack of integration of the numerous, technically very different unit operations in catalyst discovery and a great need for new developments in online and in situ analytics, especially in catalyst synthesis. To pave the way for autonomous processing of work packages by robots, it is proposed to advance the automation of single unit operations currently performed by human researchers by introducing standard operating procedures described in handbooks. The work according to rigorous protocols produces, on the one hand, reliable data that can be evaluated using artificial intelligence and facilitates on the other hand the automation. Special attention should be paid to the acquisition and real-time evaluation of analytical data in in situ and operando experiments as well as the automatic storage of data and metadata in databases
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