196 research outputs found

    Analysis of data processing systems

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    Mathematical simulation models and software monitoring of multiprogramming computer syste

    AES-EPO study program, volume II Final study report

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    Packaging, machine organization, error detection, and fabrication and test in determining solution to long-term and time-critical reliability of Apollo command module guidance-control compute

    Virtual image out-the-window display system study. Volume 2 - Appendix

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    Virtual image out-the-window display system imaging techniques and simulation devices - appendices containing background materia

    Montana Kaimin, March 9, 1978

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    Student newspaper of the University of Montana, Missoula.https://scholarworks.umt.edu/studentnewspaper/7760/thumbnail.jp

    ๋ฐ”์ด์˜ค์ธํฌ๋งคํ‹ฑ์Šค ํ”„๋กœ๊ทธ๋žจ์„ ์ด์šฉํ•œ ์œ ์ „์ž ๋งˆ์ปค ์„ ๋ณ„ ๋ฐ ๊ณ„ํ†ต์ˆ˜ ์˜ค๋ฅ˜ ํ‰๊ฐ€ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์ž์—ฐ๊ณผํ•™๋Œ€ํ•™ ํ˜‘๋™๊ณผ์ • ์ƒ๋ฌผ์ •๋ณดํ•™์ „๊ณต, 2021.8. ์†ํ˜„์„.์ง€์†์ ์œผ๋กœ ์‚ฐ์ถœ๋˜๋Š” ์—„์ฒญ๋‚œ ์–‘์˜ ์ƒ๋ฌผํ•™์  ์„œ์—ด ๋ฐ์ดํ„ฐ๋Š” ์œ ๊ธฐ์ฒด ์‚ฌ์ด์˜ ์ง„ํ™”์  ์—ญ์‚ฌ์™€ ๊ณ„ํ†ตํ•™์  ๊ด€๊ณ„(phylogenetic relationship)๋ฅผ ์œ ์ถ”ํ•  ์ˆ˜ ์žˆ๋Š” ๊ธฐํšŒ๋ฅผ ์ œ๊ณตํ•œ๋‹ค. ์ด์ œ ๊ณ„ํ†ต์ˆ˜ ๊ตฌ์ถ•์€ ๊ฑฐ์˜ ๋ชจ๋“  ์ƒ๋ฌผํ•™ ์—ฐ๊ตฌ์—์„œ ์ˆ˜ํ–‰๋˜๋Š” ๊ณผ์ •์˜ ํ•˜๋‚˜๊ฐ€ ๋˜์—ˆ๋‹ค. ์—ฌ๊ธฐ์„œ ๊ณ„ํ†ต์ •๋ณดํ•™(phyloinformatics)์€ ๊ณ„ํ†ต์ˆ˜ ์ƒ์„ฑ ์•Œ๊ณ ๋ฆฌ์ฆ˜๊ณผ ์ง„ํ™”์  ๋ชจ๋ธ ๊ฐœ๋ฐœ๊ณผ ๊ฐ™์€ ๊ธฐ์ˆ ์  ๋˜๋Š” ๋ฐฉ๋ฒ•๋ก ์  ์—ฐ๊ตฌ๋ฅผ ์ค‘์‹ฌ์œผ๋กœ ๋ฐœ์ „๋˜์–ด ์™”๋‹ค. ํ˜„์žฌ์˜ ๊ณ„ํ†ต์ˆ˜ ๋ถ„์„์€ ์„œ์—ด ๋ฐ์ดํ„ฐ, ์ฆ‰ ์œ ์ „์  ๋งˆ์ปค๋ฅผ ์ด์šฉํ•˜์—ฌ ๊ณ„ํ†ต์ˆ˜๋ฅผ ์ƒ์„ฑํ•จ์œผ๋กœ์จ ์‹ค์ œ์— ๊ฐ€๊นŒ์šด ๊ณ„ํ†ต์ˆ˜๋ฅผ ์ถ”๋ก ํ•˜๋Š” ๊ฒƒ์„ ๋ชฉํ‘œ๋กœ ํ•œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์œ ์ „์  ๋งˆ์ปค๋ฅผ ๋น„๋กฏํ•œ ๋ฐ์ดํ„ฐ์˜ ํฌ๊ธฐ๊ฐ€ ๊ธฐํ•˜๊ธ‰์ˆ˜์ ์œผ๋กœ ์ฆ๊ฐ€ํ•˜๊ณ  ๋”ฐ๋ผ์˜ค๋Š” ๊ณ„ํ†ต์ˆ˜ ๋ถ„์„์˜ ์ •ํ™•์„ฑ์— ๋Œ€ํ•œ ์˜๋ฌธ์ด ์ ์ฐจ ์ค‘์š”ํ•˜๊ฒŒ ๋‹ค๋ฃจ์–ด ์ง€๊ธฐ ์‹œ์ž‘ํ•˜๋ฉด์„œ ๊ณ„ํ†ต์ˆ˜์˜ ์ •ํ™•์„ฑ ๋ฐ ์‹ ๋ขฐ์„ฑ์„ ํ‰๊ฐ€ํ•˜๊ธฐ ์œ„ํ•œ ์—ฐ๊ตฌ๊ฐ€ ๋‹ค์ˆ˜ ์ด๋ฃจ์–ด์ง€๊ณ  ์žˆ๋Š” ์ƒํ™ฉ์ด๋‹ค. ๋ถ„์ž ์‹œ์Šคํ…œํ•™ ๊ด€์ ์—์„œ ๊ณ„ํ†ต์ˆ˜์— ๋Œ€ํ•œ ์ •ํ™•์„ฑ ํ‰๊ฐ€๋Š” ๋‘ ๊ฐ€์ง€ ๊ฐˆ๋ž˜๋กœ ๋‚˜๋ˆ„์–ด ์ ‘๊ทผํ•  ์ˆ˜ ์žˆ๋Š”๋ฐ, ํ•˜๋‚˜๋Š” ์ง„ํ™” ์กฐ๊ฑด, ๋ถ„์ž๋ฐ์ดํ„ฐ์˜ ์–‘๊ณผ ๊ฐ™์€ ํŠน์ • ํ™˜๊ฒฝ ์•„๋ž˜์—์„œ ๊ณ„ํ†ต ๋ถ„์„ ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด ์–ผ๋งˆ๋‚˜ ์ž˜ ์ž‘๋™ํ•˜๋Š”์ง€๋ฅผ ๋‹ค๋ฃจ๋Š” ๊ฒƒ์ด๊ณ , ๋˜ ๋‹ค๋ฅธ ํ•˜๋‚˜๋Š” ํŠน์ • ๊ณ„ํ†ต์ˆ˜๋ฅผ ์–ผ๋งˆ๋‚˜ ์‹ ๋ขฐํ•  ์ˆ˜ ์žˆ๋Š”์ง€์— ์ง‘์ค‘ํ•˜๋Š” ๊ฒƒ์ด๋‹ค. ๊ทธ๋ฆฌ๊ณ  ๋ฐ์ดํ„ฐ์…‹์˜ ํ€„๋ฆฌํ‹ฐ ๊ด€์ ์—์„œ ์‹ ๋ขฐํ•  ๋งŒํ•œ ๊ณ„ํ†ต์ˆ˜๋ฅผ ํš๋“ํ•˜๊ธฐ ์œ„ํ•ด ๊ณ„ํ†ต์ˆ˜ ๋ถ„์„์„ ์ˆ˜ํ–‰ํ•œ ํ›„, ์‚ฌ์šฉํ•œ ๋ฐ์ดํ„ฐ์…‹๊ณผ์˜ ์ ์ ˆ์„ฑ์„ ํ‰๊ฐ€ํ•˜๋Š” ๊ฒƒ๋„ ์ค‘์š”ํ•˜๋‹ค. ๋Œ€๊ทœ๋ชจ ๋ฐ์ดํ„ฐ๋ฅผ ๊ธฐ๋ณธ์œผ๋กœ ์ทจ๊ธ‰ํ•˜๋Š” ์ตœ๊ทผ ๊ณ„ํ†ต์ˆ˜ ๋ถ„์„์—์„œ ํ™•๋ฅ ๋ก ์  ์˜ค๋ฅ˜์˜ ๊ฐ€๋Šฅ์„ฑ์€ ๋‚ฎ์•„์กŒ์ง€๋งŒ, ์‹œ์Šคํ…œ ์˜ค๋ฅ˜์˜ ๊ฐ€๋Šฅ์„ฑ์€ ์˜คํžˆ๋ ค ๋†’์•„์กŒ์œผ๋ฏ€๋กœ, ๊ณ„ํ†ต์ˆ˜ ์ •ํ™•์„ฑ์„ ํ‰๊ฐ€ ๋ฐ ๊ฐœ์„ ํ•˜๊ธฐ ์œ„ํ•ด ๊ณ„ํ†ต ๋ถ„์„ ๊ฒฐ๊ณผ ํ›„์— ๋ฐ์ดํ„ฐ์…‹์ด ๊ฐ€์ง€๋Š” ์‹œ์Šคํ…œ ์˜ค๋ฅ˜์˜ ๊ทผ์›์„ ํ‰๊ฐ€ํ•˜๋Š” ๊ฒƒ์ด ๋งค์šฐ ์ค‘์š”ํ•œ ๊ณผ์ •์ด ๋˜์—ˆ๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ์ด์— ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋ฐ์ดํ„ฐ ํ€„๋ฆฌํ‹ฐ ๊ด€์ ์—์„œ ๊ณ„ํ†ต์ˆ˜์˜ ์‹ ๋ขฐ๋„ ํ–ฅ์ƒ์„ ๊ฐ€์ ธ์˜ค๊ธฐ ์œ„ํ•ด APSE (Assessment Program for Systematic Error, tentative)๋ผ๋Š” ํ”„๋กœ๊ทธ๋žจ์„ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. APSE๋ฅผ ํ™œ์šฉํ•˜๋ฉด ๋ถ„๋ฅ˜๊ตฐ ํŠน์ด์  ์ƒ๋Œ€์  ๊ตฌ์„ฑ ๋นˆ๋„ ๋ณ€์ด(RCFV)์™€ ๋Œ€์นญ์  ์™œ๊ณก๊ฐ’(skew)์„ ์‚ฐ์ถœํ•˜์—ฌ ์—ผ๊ธฐ์„œ์—ด์˜ ๊ตฌ์„ฑ์  ํŽธํ–ฅ์„ฑ์— ๋Œ€ํ•œ ์ •๋ณด๋ฅผ ์–ป๊ณ , ์ด๋ฅผ ํ†ตํ•ด ์—ฐ๊ตฌํ•˜๊ณ ์ž ํ•˜๋Š” ๋ฐ์ดํ„ฐ์˜ ์œ ์ „์  ์ด์งˆ์„ฑ(heterogeneity) ๋ฐ ์œ ์ „์  ๋ณ€์ด ํŽธํ–ฅ์„ฑ(mutational bias)์„ ์ถ”์ •ํ•  ์ˆ˜ ์žˆ๋‹ค. ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ๋‹ค์–‘ํ•œ ์—ผ๊ธฐ ๊ทธ๋ฃน์˜ ๋นˆ๋„, ๋ณ€์ด์— ์˜ํ•œ ๋‹ค์ˆ˜ ์น˜ํ™˜์„ ์˜๋ฏธํ•˜๋Š” ํฌํ™”(saturation)์™€ ๊ณต์œ  ๊ฒฐ์ธก ๋ฐ์ดํ„ฐ(shared missing data) ๋ณ€์ˆ˜๋ฅผ ํ†ตํ•ด ์‹œ์Šคํ…œ ์˜ค๋ฅ˜๋ฅผ ์œ ๋ฐœํ•  ์ˆ˜ ์žˆ๋Š” ํŽธํ–ฅ์„ฑ ์ •๋ณด๋“ค์„ ๊ณ„์‚ฐํ•˜๋Š” ๊ฒƒ์ด ๊ฐ€๋Šฅํ•˜๋‹ค. ๋˜ํ•œ, ์‹œ์Šคํ…œ ์„ฑ๋Šฅ์„ ํ‰๊ฐ€ํ•˜๊ธฐ ์œ„ํ•ด ๋‹ค์–‘ํ•œ ์œ ์ „์ž ๋งˆ์ปค ์‚ฌ์ด์˜ ๋ชจ์ˆœ๋˜๋Š” ๊ณ„ํ†ต์ˆ˜๋ฅผ ์ถœ๋ ฅํ•˜๊ณ  ์žˆ๋Š”, ํŠน์ด์  ์˜ˆ์‹œ(Terebelliformia, Daphniid, Glires)๋ฅผ APSE์— ์ ์šฉํ•˜์—ฌ ๋งˆ์ปค ๋ฐ์ดํ„ฐ์…‹์˜ ์‹œ์Šคํ…œ ์˜ค๋ฅ˜ ํ‰๊ฐ€์™€ ๊ทธ์— ๋”ฐ๋ผ ์„ ๋ณ„๋œ ๋งˆ์ปค ๊ณ„ํ†ต์ˆ˜์˜ ์ •ํ™•์„ฑ ์ถ”๋ก ์— ๋Œ€ํ•œ ๋ถ„์„์ด ์ œ๋Œ€๋กœ ์ˆ˜ํ–‰๋  ์ˆ˜ ์žˆ์Œ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋”ฐ๋ผ์„œ ํ–ฅํ›„ APSE๋Š” ์‹œ์Šคํ…œํ•™์  ๊ด€์ ์—์„œ ๋ฐ์ดํ„ฐ ํ€„๋ฆฌํ‹ฐ์— ์ง‘์ค‘ํ•˜์—ฌ ์ƒ์„ฑ๋œ ๊ณ„ํ†ต์ˆ˜๊ฐ€ ๋ณด๋‹ค ์ •ํ™•ํ•œ ๊ฒฐ๊ณผ๋ฅผ ์ด๋Œ์–ด๋‚ผ ์ˆ˜ ์žˆ๋„๋ก ์‚ฌ์šฉ์ž์˜ ๋ฐ์ดํ„ฐ์™€ ๊ณ„ํ†ต์ˆ˜ ์‚ฌ์ด์˜ ์ •ํ™•์„ฑ์„ ํ‰๊ฐ€ํ•˜๋Š” ์—ญํ• ์„ ํ•  ๊ฒƒ์ด๊ณ , ์œ ์ „์  ๋งˆ์ปค์— ๋”ฐ๋ผ ์˜คํ•ด์˜ ์†Œ์ง€๊ฐ€ ์žˆ๋Š” ๊ณ„ํ†ต์ˆ˜๊ฐ€ ์ถœ๋ ฅ๋˜์—ˆ์„ ๋•Œ, ์‹œ์Šคํ…œ ์˜ค๋ฅ˜์˜ ๊ทผ์›์— ๋Œ€ํ•œ ์ฒ ์ €ํ•œ ๋ถ„์„๊ณผ ํ•ด๋‹น ์˜ค๋ฅ˜์˜ ์˜ํ–ฅ์„ ๋ฐ›์€ ๋ฐ์ดํ„ฐ๊ฐ€ ๊ณ„ํ†ต์ˆ˜์— ์ฃผ๋Š” ํšจ๊ณผ๋ฅผ ํŒŒ์•…ํ•˜๋Š” ์ผ์„ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋ผ ๊ธฐ๋Œ€ํ•œ๋‹ค.The steadily increasing volume of biological data with decisive phylogenetic relationship provides unparalleled opportunities in bioinformatics. Phylogenetics based on a large amount of datasets handling an evolutionary history and assigning the placement of taxa in a phylogeny establishes the tree of life. Constructing a phylogeny involving a phylogenetic analysis is implemented in most branches of biology and emphasizing the evolutionary history elucidates the phylogenetical background as a prerequisite interpreting a specific biological system, which is a biologically indispensable process. Due to the advent of computing and sequencing techniques as the phylogenetic approach, phyloinformatics has rapidly advanced at the technical and methodological levels along with phylogenetic reconstruction algorithm and evolutionary models. Unlike the classic approach using morphological data, modern phylogenetic analysis reconstructs a phylogeny using genetic information following the inference of phylogenetic tree from molecular data. Therefore, phylogeneticists have naturally dealt with questions concerning the accuracy of phylogenetic estimation and carried out studies on the reliability of phylogenies. In terms of molecular systematics, the concerns regarding the assessment of phylogenetic accuracy considering specific evolutionary conditions and the amount of molecular data implemented can now be divided into two types: how phylogenetic method works and how reliable it is under certain circumstances. Moreover, in terms of data quality, assessment for suitability of nuclear marker is required before the phylogenetic inference is performed for confident phylogeny. Recently, the probability of stochastic errors in phylogenetic estimation dealing with a large-scale datasets has decreased, while the probability of systematic errors has increased. Thus, before the implementation of phylogenetic reconstruction, the assessment of sources of systematic errors is indispensable for the improvement and estimation of phylogenetic accuracy. Assessment Program for Systematic Error (APSE) developed by this study will plays a key role in assessment between user datasets and phylogenies for improving the results of phylogenetic reconstruction in systematics and will be able to implement an analysis of the effect on data bearing systematic errors in a phylogeny after the misleading phylogenetic results are produced. This study with APSE will serve as the inference of phylogenetic accuracy and the assessment of systematic errors using an unresolved example showing the contradicting topologies between different gene markers in the same diversity group. Furthermore, by selectively grouping the properties of the existing systematic biases provided by the APSE, it proceeds in the direction of proposing a new protocol that can provide the best gene marker among candidate markers for a specific taxon.I. INTRODUCTION 1 1.1 Background of research 1 1.2 Necessity of research 20 1.3 Research objectives 22 II. MATERIALS AND METHODS 30 2.1 Datasets definition and data collection 30 2.2 Data processing and bioinformatics software used 33 2.3 Phylogenetic reconstruction and accuracy assessment 36 2.4 Software development environment and allowable data 37 2.5 Assessment of the systematic errors 38 III. RESULTS 45 3.1 Phylogenetic analysis results for incongruence between gene markers 45 3.2 Data-quality analysis using systematic errors 49 IV. DISCUSSION 79 4.1 Significance and implications of study 79 4.2 Application to bioinformatics research 80 4.3 Improvement and achievement 81 V. CONCLUSION AND SUMMARY 83 5.1 Conclusion 83 5.2 Summary 84 BIBLIOGRAPHY 87 ABSTRACT (KOREAN) 96์„

    NASA Thesaurus. Volume 2: Access vocabulary

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    The NASA Thesaurus -- Volume 2, Access Vocabulary -- contains an alphabetical listing of all Thesaurus terms (postable and nonpostable) and permutations of all multiword and pseudo-multiword terms. Also included are Other Words (non-Thesaurus terms) consisting of abbreviations, chemical symbols, etc. The permutations and Other Words provide 'access' to the appropriate postable entries in the Thesaurus

    Major Trends in Operating Systems Development

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    Operating systems have changed in nature in response to demands of users, and in response to advances in hardware and software technology. The purpose of this paper is to trace the development of major themes in operating system design from their beginnings through the present. This is not an exhaustive history of operating systems, but instead is intended to give the reader the flavor of the dif ferent periods in operating systems\u27 development. To this end, the paper will be organized by topic in approximate order of development. Each chapter will start with an introduction to the factors behind the rise of the period. This will be fol lowed by a survey of the state-of-the-art systems, and the conditions influencing them. The chapters close with a summation of the significant hardware and software contributions from the period

    Special Libraries, October 1961

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    Volume 52, Issue 8https://scholarworks.sjsu.edu/sla_sl_1961/1007/thumbnail.jp

    Special Libraries, October 1961

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    Volume 52, Issue 8https://scholarworks.sjsu.edu/sla_sl_1961/1007/thumbnail.jp
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