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You searched for subject:(Large Scientific Data). Showing records 1 – 6 of 6 total matches.

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Colorado State University

1. Shannigrahi, Susmit. Future of networking is the future of Big Data, The.

Degree: PhD, Computer Science, 2019, Colorado State University

Scientific domains such as Climate Science, High Energy Particle Physics (HEP), Genomics, Biology, and many others are increasingly moving towards data-oriented workflows where each of… (more)

Subjects/Keywords: Future Internet Architecture; Large Scientific Data; Networking for big data; Information Centric Networking; Big Science; Named Data Networking

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APA (6th Edition):

Shannigrahi, S. (2019). Future of networking is the future of Big Data, The. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/197325

Chicago Manual of Style (16th Edition):

Shannigrahi, Susmit. “Future of networking is the future of Big Data, The.” 2019. Doctoral Dissertation, Colorado State University. Accessed January 20, 2020. http://hdl.handle.net/10217/197325.

MLA Handbook (7th Edition):

Shannigrahi, Susmit. “Future of networking is the future of Big Data, The.” 2019. Web. 20 Jan 2020.

Vancouver:

Shannigrahi S. Future of networking is the future of Big Data, The. [Internet] [Doctoral dissertation]. Colorado State University; 2019. [cited 2020 Jan 20]. Available from: http://hdl.handle.net/10217/197325.

Council of Science Editors:

Shannigrahi S. Future of networking is the future of Big Data, The. [Doctoral Dissertation]. Colorado State University; 2019. Available from: http://hdl.handle.net/10217/197325


Penn State University

2. Li, Chuang. SAVE: A Scalable Archival and Visualization Environment for Large-Scale Scientific Computing Applications.

Degree: PhD, Computer Science and Engineering, 2004, Penn State University

Large-scale computer simulations are playing an increasingly important role in many areas of science and engineering. A central problem for these simulations is that when… (more)

Subjects/Keywords: scientific computing; large data set; visualization; computational steering.

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APA (6th Edition):

Li, C. (2004). SAVE: A Scalable Archival and Visualization Environment for Large-Scale Scientific Computing Applications. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/6405

Chicago Manual of Style (16th Edition):

Li, Chuang. “SAVE: A Scalable Archival and Visualization Environment for Large-Scale Scientific Computing Applications.” 2004. Doctoral Dissertation, Penn State University. Accessed January 20, 2020. https://etda.libraries.psu.edu/catalog/6405.

MLA Handbook (7th Edition):

Li, Chuang. “SAVE: A Scalable Archival and Visualization Environment for Large-Scale Scientific Computing Applications.” 2004. Web. 20 Jan 2020.

Vancouver:

Li C. SAVE: A Scalable Archival and Visualization Environment for Large-Scale Scientific Computing Applications. [Internet] [Doctoral dissertation]. Penn State University; 2004. [cited 2020 Jan 20]. Available from: https://etda.libraries.psu.edu/catalog/6405.

Council of Science Editors:

Li C. SAVE: A Scalable Archival and Visualization Environment for Large-Scale Scientific Computing Applications. [Doctoral Dissertation]. Penn State University; 2004. Available from: https://etda.libraries.psu.edu/catalog/6405

3. Canahuate, Guadalupe M. Enhanced Bitmap Indexes for Large Scale Data Management.

Degree: PhD, Computer Science and Engineering, 2009, The Ohio State University

 Advances in technology have enabled the production of massive volumes of data through observations and simulations in many application domains.These new data sets and the… (more)

Subjects/Keywords: bitmap index; scientific data management; large scale indexing

…on Very Large Data Bases (VLDB), Seoul, Korea, 2006/September, pp. 846-857. Hakan… …storage and retrieval of data and require novel indexing structures and algorithms. Most large… …lossy data compression technique, it is mainly used in domains where large amount of data are… …manage large scale data efficiently. We focus on generalizing bitmap indexes to address the… …CHAPTER 2 Background The data generated by scientific experiments is composed of attributes… 

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APA (6th Edition):

Canahuate, G. M. (2009). Enhanced Bitmap Indexes for Large Scale Data Management. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1244047153

Chicago Manual of Style (16th Edition):

Canahuate, Guadalupe M. “Enhanced Bitmap Indexes for Large Scale Data Management.” 2009. Doctoral Dissertation, The Ohio State University. Accessed January 20, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1244047153.

MLA Handbook (7th Edition):

Canahuate, Guadalupe M. “Enhanced Bitmap Indexes for Large Scale Data Management.” 2009. Web. 20 Jan 2020.

Vancouver:

Canahuate GM. Enhanced Bitmap Indexes for Large Scale Data Management. [Internet] [Doctoral dissertation]. The Ohio State University; 2009. [cited 2020 Jan 20]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1244047153.

Council of Science Editors:

Canahuate GM. Enhanced Bitmap Indexes for Large Scale Data Management. [Doctoral Dissertation]. The Ohio State University; 2009. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1244047153

4. Wang, Ko-Chih. Distribution-based Summarization for Large Scale Simulation Data Visualization and Analysis.

Degree: PhD, Computer Science and Engineering, 2019, The Ohio State University

 The advent of high-performance supercomputers enables scientists to perform extreme-scale simulations that generate millions of cells and thousands of time steps. Through exploring and analyzing… (more)

Subjects/Keywords: Computer Science; Computer Engineering; Scientific data visualization and analysis, Large-scale dataset, Statistical-based data summarization, In situ data processing

…Woodring, Han-Wei Shen “Statistical Super Resolution for Data Analysis and Visualization of Large… …Rendering for Large Data Sets”, In IEEE Pacific Visualization (PacificVis) Symposium… …Statistical visualization and analysis of large data using a value-based spatial distribution”, In… …Data Representation for Large Dataset In-situ Techniques . . . . . . . . . . Distribution… …7 . 9 . 10 . 11 . 12 Image and Distribution Based Volume Rendering for Large Data Sets… 

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APA (6th Edition):

Wang, K. (2019). Distribution-based Summarization for Large Scale Simulation Data Visualization and Analysis. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1555452764885977

Chicago Manual of Style (16th Edition):

Wang, Ko-Chih. “Distribution-based Summarization for Large Scale Simulation Data Visualization and Analysis.” 2019. Doctoral Dissertation, The Ohio State University. Accessed January 20, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1555452764885977.

MLA Handbook (7th Edition):

Wang, Ko-Chih. “Distribution-based Summarization for Large Scale Simulation Data Visualization and Analysis.” 2019. Web. 20 Jan 2020.

Vancouver:

Wang K. Distribution-based Summarization for Large Scale Simulation Data Visualization and Analysis. [Internet] [Doctoral dissertation]. The Ohio State University; 2019. [cited 2020 Jan 20]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1555452764885977.

Council of Science Editors:

Wang K. Distribution-based Summarization for Large Scale Simulation Data Visualization and Analysis. [Doctoral Dissertation]. The Ohio State University; 2019. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1555452764885977

5. Iqbal, Sumaiya. Machine Learning based Protein Sequence to (un)Structure Mapping and Interaction Prediction.

Degree: PhD, Computer Science, 2017, University of New Orleans

  Proteins are the fundamental macromolecules within a cell that carry out most of the biological functions. The computational study of protein structure and its… (more)

Subjects/Keywords: Machine Learning; Large-Scale Data Analysis; Bioinformatics; Intrinsically Disordered Protein; Predictor Framework; Protein-Protein Interaction; Artificial Intelligence and Robotics; Biochemistry, Biophysics, and Structural Biology; Bioinformatics; Computational Biology; Computer Sciences; Databases and Information Systems; Numerical Analysis and Scientific Computing

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APA (6th Edition):

Iqbal, S. (2017). Machine Learning based Protein Sequence to (un)Structure Mapping and Interaction Prediction. (Doctoral Dissertation). University of New Orleans. Retrieved from https://scholarworks.uno.edu/td/2379

Chicago Manual of Style (16th Edition):

Iqbal, Sumaiya. “Machine Learning based Protein Sequence to (un)Structure Mapping and Interaction Prediction.” 2017. Doctoral Dissertation, University of New Orleans. Accessed January 20, 2020. https://scholarworks.uno.edu/td/2379.

MLA Handbook (7th Edition):

Iqbal, Sumaiya. “Machine Learning based Protein Sequence to (un)Structure Mapping and Interaction Prediction.” 2017. Web. 20 Jan 2020.

Vancouver:

Iqbal S. Machine Learning based Protein Sequence to (un)Structure Mapping and Interaction Prediction. [Internet] [Doctoral dissertation]. University of New Orleans; 2017. [cited 2020 Jan 20]. Available from: https://scholarworks.uno.edu/td/2379.

Council of Science Editors:

Iqbal S. Machine Learning based Protein Sequence to (un)Structure Mapping and Interaction Prediction. [Doctoral Dissertation]. University of New Orleans; 2017. Available from: https://scholarworks.uno.edu/td/2379


Linköping University

6. Frishert, Willem Jan. Interactive Visualization Of Large Scale Time-Varying Datasets.

Degree: Science and Technology, 2008, Linköping University

  Visualization of large scale time-varying volumetric datasets is an active topic of research. Technical limitations in terms of bandwidth and memory usage become a… (more)

Subjects/Keywords: Large Scale Time-Varying Data; Direct Volume Rendering; Scientific Visualization; Real-Time Rendering; TECHNOLOGY; TEKNIKVETENSKAP

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Frishert, W. J. (2008). Interactive Visualization Of Large Scale Time-Varying Datasets. (Thesis). Linköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-12283

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Frishert, Willem Jan. “Interactive Visualization Of Large Scale Time-Varying Datasets.” 2008. Thesis, Linköping University. Accessed January 20, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-12283.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Frishert, Willem Jan. “Interactive Visualization Of Large Scale Time-Varying Datasets.” 2008. Web. 20 Jan 2020.

Vancouver:

Frishert WJ. Interactive Visualization Of Large Scale Time-Varying Datasets. [Internet] [Thesis]. Linköping University; 2008. [cited 2020 Jan 20]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-12283.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Frishert WJ. Interactive Visualization Of Large Scale Time-Varying Datasets. [Thesis]. Linköping University; 2008. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-12283

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

.