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You searched for +publisher:"Colorado State University" +contributor:("Anderson, Charles W."). Showing records 1 – 27 of 27 total matches.

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Colorado State University

1. Trinko, David A. Predictive energy management strategies for hybrid electric vehicles applied during acceleration events.

Degree: MS(M.S.), Mechanical Engineering, 2019, Colorado State University

 The emergence and widespread adoption of vehicles with hybrid powertrains and onboard computing capabilities have improved the feasibility of utilizing predictions of vehicle state to… (more)

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APA (6th Edition):

Trinko, D. A. (2019). Predictive energy management strategies for hybrid electric vehicles applied during acceleration events. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/195328

Chicago Manual of Style (16th Edition):

Trinko, David A. “Predictive energy management strategies for hybrid electric vehicles applied during acceleration events.” 2019. Masters Thesis, Colorado State University. Accessed January 23, 2021. http://hdl.handle.net/10217/195328.

MLA Handbook (7th Edition):

Trinko, David A. “Predictive energy management strategies for hybrid electric vehicles applied during acceleration events.” 2019. Web. 23 Jan 2021.

Vancouver:

Trinko DA. Predictive energy management strategies for hybrid electric vehicles applied during acceleration events. [Internet] [Masters thesis]. Colorado State University; 2019. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10217/195328.

Council of Science Editors:

Trinko DA. Predictive energy management strategies for hybrid electric vehicles applied during acceleration events. [Masters Thesis]. Colorado State University; 2019. Available from: http://hdl.handle.net/10217/195328


Colorado State University

2. Peterson, Erik J. Many hats: intra-trial and reward-level dependent bold activity in the striatum and premotor cortex.

Degree: MS(M.S.), Psychology, 2012, Colorado State University

 Lesion, drug, single-cell recording, as well as human fMRI studies, suggest dopaminergic projections from VTA/SNc (ventral tagmental area/substantia nigra pars compacta) and cortically driven striatal… (more)

Subjects/Keywords: basal ganglia; striatum; reward; response; dopamine

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APA (6th Edition):

Peterson, E. J. (2012). Many hats: intra-trial and reward-level dependent bold activity in the striatum and premotor cortex. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/65351

Chicago Manual of Style (16th Edition):

Peterson, Erik J. “Many hats: intra-trial and reward-level dependent bold activity in the striatum and premotor cortex.” 2012. Masters Thesis, Colorado State University. Accessed January 23, 2021. http://hdl.handle.net/10217/65351.

MLA Handbook (7th Edition):

Peterson, Erik J. “Many hats: intra-trial and reward-level dependent bold activity in the striatum and premotor cortex.” 2012. Web. 23 Jan 2021.

Vancouver:

Peterson EJ. Many hats: intra-trial and reward-level dependent bold activity in the striatum and premotor cortex. [Internet] [Masters thesis]. Colorado State University; 2012. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10217/65351.

Council of Science Editors:

Peterson EJ. Many hats: intra-trial and reward-level dependent bold activity in the striatum and premotor cortex. [Masters Thesis]. Colorado State University; 2012. Available from: http://hdl.handle.net/10217/65351


Colorado State University

3. McNeely-White, David G. Same data, same features: modern ImageNet-trained convolutional neural networks learn the same thing.

Degree: MS(M.S.), Computer Science, 2020, Colorado State University

 Deep convolutional neural networks (CNNs) are the dominant technology in computer vision today. Much of the recent computer vision literature can be thought of as… (more)

Subjects/Keywords: convolutional neural networks; feature space; machine learning; feature mapping; computer vision; ImageNet

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APA (6th Edition):

McNeely-White, D. G. (2020). Same data, same features: modern ImageNet-trained convolutional neural networks learn the same thing. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/208467

Chicago Manual of Style (16th Edition):

McNeely-White, David G. “Same data, same features: modern ImageNet-trained convolutional neural networks learn the same thing.” 2020. Masters Thesis, Colorado State University. Accessed January 23, 2021. http://hdl.handle.net/10217/208467.

MLA Handbook (7th Edition):

McNeely-White, David G. “Same data, same features: modern ImageNet-trained convolutional neural networks learn the same thing.” 2020. Web. 23 Jan 2021.

Vancouver:

McNeely-White DG. Same data, same features: modern ImageNet-trained convolutional neural networks learn the same thing. [Internet] [Masters thesis]. Colorado State University; 2020. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10217/208467.

Council of Science Editors:

McNeely-White DG. Same data, same features: modern ImageNet-trained convolutional neural networks learn the same thing. [Masters Thesis]. Colorado State University; 2020. Available from: http://hdl.handle.net/10217/208467


Colorado State University

4. Kumar, Shantanu. Finding a solution for the tradeoff between time, cost and sustainability/LEED credits for new construction.

Degree: MS(M.S.), Construction Management, 2018, Colorado State University

 Project complexity generated tradeoffs in construction, which evolved over decades. This research focuses on the tradeoff between time-cost and sustainability represented in the LEED credits… (more)

Subjects/Keywords: genetic algorithm; optimization; tradeoffs; LEED; construction; sustainability

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APA (6th Edition):

Kumar, S. (2018). Finding a solution for the tradeoff between time, cost and sustainability/LEED credits for new construction. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/191361

Chicago Manual of Style (16th Edition):

Kumar, Shantanu. “Finding a solution for the tradeoff between time, cost and sustainability/LEED credits for new construction.” 2018. Masters Thesis, Colorado State University. Accessed January 23, 2021. http://hdl.handle.net/10217/191361.

MLA Handbook (7th Edition):

Kumar, Shantanu. “Finding a solution for the tradeoff between time, cost and sustainability/LEED credits for new construction.” 2018. Web. 23 Jan 2021.

Vancouver:

Kumar S. Finding a solution for the tradeoff between time, cost and sustainability/LEED credits for new construction. [Internet] [Masters thesis]. Colorado State University; 2018. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10217/191361.

Council of Science Editors:

Kumar S. Finding a solution for the tradeoff between time, cost and sustainability/LEED credits for new construction. [Masters Thesis]. Colorado State University; 2018. Available from: http://hdl.handle.net/10217/191361


Colorado State University

5. Yeluri, Sri Sagar Abhishek. Classification using out of sample testing of neural networks and Siamese-like neural network for handwritten characters.

Degree: MS(M.S.), Computer Science, 2020, Colorado State University

 In a world where Machine Learning Algorithms in the field of Image Processing is being developed at a rapid pace, a developer needs to have… (more)

Subjects/Keywords: machine learning; Siamese-like neural networks; neural networks; deep learning

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APA (6th Edition):

Yeluri, S. S. A. (2020). Classification using out of sample testing of neural networks and Siamese-like neural network for handwritten characters. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/212032

Chicago Manual of Style (16th Edition):

Yeluri, Sri Sagar Abhishek. “Classification using out of sample testing of neural networks and Siamese-like neural network for handwritten characters.” 2020. Masters Thesis, Colorado State University. Accessed January 23, 2021. http://hdl.handle.net/10217/212032.

MLA Handbook (7th Edition):

Yeluri, Sri Sagar Abhishek. “Classification using out of sample testing of neural networks and Siamese-like neural network for handwritten characters.” 2020. Web. 23 Jan 2021.

Vancouver:

Yeluri SSA. Classification using out of sample testing of neural networks and Siamese-like neural network for handwritten characters. [Internet] [Masters thesis]. Colorado State University; 2020. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10217/212032.

Council of Science Editors:

Yeluri SSA. Classification using out of sample testing of neural networks and Siamese-like neural network for handwritten characters. [Masters Thesis]. Colorado State University; 2020. Available from: http://hdl.handle.net/10217/212032


Colorado State University

6. Mussa, Awad A. Younis. Quantifying the security risk of discovering and exploiting software vulnerabilities.

Degree: PhD, Computer Science, 2016, Colorado State University

 Most of the attacks on computer systems and networks are enabled by vulnerabilities in a software. Assessing the security risk associated with those vulnerabilities is… (more)

Subjects/Keywords: software security; vulnerabilities exploitation; vulnerability rewards program and time to vulnerability disclosure; software vulnerabilities; cvss and OWASP metrics; vulnerabilities risk and severity

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APA (6th Edition):

Mussa, A. A. Y. (2016). Quantifying the security risk of discovering and exploiting software vulnerabilities. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/176641

Chicago Manual of Style (16th Edition):

Mussa, Awad A Younis. “Quantifying the security risk of discovering and exploiting software vulnerabilities.” 2016. Doctoral Dissertation, Colorado State University. Accessed January 23, 2021. http://hdl.handle.net/10217/176641.

MLA Handbook (7th Edition):

Mussa, Awad A Younis. “Quantifying the security risk of discovering and exploiting software vulnerabilities.” 2016. Web. 23 Jan 2021.

Vancouver:

Mussa AAY. Quantifying the security risk of discovering and exploiting software vulnerabilities. [Internet] [Doctoral dissertation]. Colorado State University; 2016. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10217/176641.

Council of Science Editors:

Mussa AAY. Quantifying the security risk of discovering and exploiting software vulnerabilities. [Doctoral Dissertation]. Colorado State University; 2016. Available from: http://hdl.handle.net/10217/176641


Colorado State University

7. Rajasree, Revathy. Extending and validating the stencil processing unit.

Degree: MS(M.S.), Electrical and Computer Engineering, 2016, Colorado State University

 Stencils are an important class of programs that appear in the core of many scientific and general-purpose applications. These compute-intensive kernels can benefit heavily from… (more)

Subjects/Keywords: CUDA; GPGPU; stencil; energy-efficiency; accelerator; multi-pass

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APA (6th Edition):

Rajasree, R. (2016). Extending and validating the stencil processing unit. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/176694

Chicago Manual of Style (16th Edition):

Rajasree, Revathy. “Extending and validating the stencil processing unit.” 2016. Masters Thesis, Colorado State University. Accessed January 23, 2021. http://hdl.handle.net/10217/176694.

MLA Handbook (7th Edition):

Rajasree, Revathy. “Extending and validating the stencil processing unit.” 2016. Web. 23 Jan 2021.

Vancouver:

Rajasree R. Extending and validating the stencil processing unit. [Internet] [Masters thesis]. Colorado State University; 2016. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10217/176694.

Council of Science Editors:

Rajasree R. Extending and validating the stencil processing unit. [Masters Thesis]. Colorado State University; 2016. Available from: http://hdl.handle.net/10217/176694


Colorado State University

8. Alzahrani, Saleh Ibrahim. P300 wave detection using Emotiv EPOC+ headset: effects of matrix size, flash duration, and colors.

Degree: MS(M.S.), Bioengineering, 2016, Colorado State University

 Brain-computer interfaces (BCIs) allow interactions between human beings and comput- ers without using voluntary muscle. Enormous research effort has been employed in the last few… (more)

Subjects/Keywords: P300; Emotiv EPOC+; BCI; EEG

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APA (6th Edition):

Alzahrani, S. I. (2016). P300 wave detection using Emotiv EPOC+ headset: effects of matrix size, flash duration, and colors. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/178958

Chicago Manual of Style (16th Edition):

Alzahrani, Saleh Ibrahim. “P300 wave detection using Emotiv EPOC+ headset: effects of matrix size, flash duration, and colors.” 2016. Masters Thesis, Colorado State University. Accessed January 23, 2021. http://hdl.handle.net/10217/178958.

MLA Handbook (7th Edition):

Alzahrani, Saleh Ibrahim. “P300 wave detection using Emotiv EPOC+ headset: effects of matrix size, flash duration, and colors.” 2016. Web. 23 Jan 2021.

Vancouver:

Alzahrani SI. P300 wave detection using Emotiv EPOC+ headset: effects of matrix size, flash duration, and colors. [Internet] [Masters thesis]. Colorado State University; 2016. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10217/178958.

Council of Science Editors:

Alzahrani SI. P300 wave detection using Emotiv EPOC+ headset: effects of matrix size, flash duration, and colors. [Masters Thesis]. Colorado State University; 2016. Available from: http://hdl.handle.net/10217/178958


Colorado State University

9. Jaksic, Aleksandar. Design and evaluation of the FAMILIAR tool.

Degree: MS(M.S.), Computer Science, 2014, Colorado State University

 Software Product Line Engineering (SPLE) aims to efficiently produce multiple software products, on a large scale, that share a common set of core development features.… (more)

Subjects/Keywords: feature models; feature modeling; FAMILIAR; FAMILIAR tool; software product lines

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APA (6th Edition):

Jaksic, A. (2014). Design and evaluation of the FAMILIAR tool. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/82556

Chicago Manual of Style (16th Edition):

Jaksic, Aleksandar. “Design and evaluation of the FAMILIAR tool.” 2014. Masters Thesis, Colorado State University. Accessed January 23, 2021. http://hdl.handle.net/10217/82556.

MLA Handbook (7th Edition):

Jaksic, Aleksandar. “Design and evaluation of the FAMILIAR tool.” 2014. Web. 23 Jan 2021.

Vancouver:

Jaksic A. Design and evaluation of the FAMILIAR tool. [Internet] [Masters thesis]. Colorado State University; 2014. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10217/82556.

Council of Science Editors:

Jaksic A. Design and evaluation of the FAMILIAR tool. [Masters Thesis]. Colorado State University; 2014. Available from: http://hdl.handle.net/10217/82556


Colorado State University

10. Saripalli, Venkata Ratnam. Scalable and data efficient deep reinforcement learning methods for healthcare applications.

Degree: PhD, Systems Engineering, 2019, Colorado State University

 Artificial intelligence driven medical devices have created the potential for significant breakthroughs in healthcare technology. Healthcare applications using reinforcement learning are still very sparse as… (more)

Subjects/Keywords: artificial intelligence; AI assisted annotation; reinforcement learning

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APA (6th Edition):

Saripalli, V. R. (2019). Scalable and data efficient deep reinforcement learning methods for healthcare applications. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/199875

Chicago Manual of Style (16th Edition):

Saripalli, Venkata Ratnam. “Scalable and data efficient deep reinforcement learning methods for healthcare applications.” 2019. Doctoral Dissertation, Colorado State University. Accessed January 23, 2021. http://hdl.handle.net/10217/199875.

MLA Handbook (7th Edition):

Saripalli, Venkata Ratnam. “Scalable and data efficient deep reinforcement learning methods for healthcare applications.” 2019. Web. 23 Jan 2021.

Vancouver:

Saripalli VR. Scalable and data efficient deep reinforcement learning methods for healthcare applications. [Internet] [Doctoral dissertation]. Colorado State University; 2019. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10217/199875.

Council of Science Editors:

Saripalli VR. Scalable and data efficient deep reinforcement learning methods for healthcare applications. [Doctoral Dissertation]. Colorado State University; 2019. Available from: http://hdl.handle.net/10217/199875


Colorado State University

11. Rieker, Jeffrey Donald. Optimal reservoir operations for riverine water quality improvement: a reinforcement learning strategy.

Degree: PhD, Civil and Environmental Engineering, 2011, Colorado State University

 Complex water resources systems often involve a wide variety of competing objectives and purposes, including the improvement of water quality downstream of reservoirs. An increased… (more)

Subjects/Keywords: reinforcement learning; truckee; reservoir operations; artificial intelligence; optimization; water quality

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APA (6th Edition):

Rieker, J. D. (2011). Optimal reservoir operations for riverine water quality improvement: a reinforcement learning strategy. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/49858

Chicago Manual of Style (16th Edition):

Rieker, Jeffrey Donald. “Optimal reservoir operations for riverine water quality improvement: a reinforcement learning strategy.” 2011. Doctoral Dissertation, Colorado State University. Accessed January 23, 2021. http://hdl.handle.net/10217/49858.

MLA Handbook (7th Edition):

Rieker, Jeffrey Donald. “Optimal reservoir operations for riverine water quality improvement: a reinforcement learning strategy.” 2011. Web. 23 Jan 2021.

Vancouver:

Rieker JD. Optimal reservoir operations for riverine water quality improvement: a reinforcement learning strategy. [Internet] [Doctoral dissertation]. Colorado State University; 2011. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10217/49858.

Council of Science Editors:

Rieker JD. Optimal reservoir operations for riverine water quality improvement: a reinforcement learning strategy. [Doctoral Dissertation]. Colorado State University; 2011. Available from: http://hdl.handle.net/10217/49858


Colorado State University

12. Lee, Minwoo. Sparse Bayesian reinforcement learning.

Degree: PhD, Computer Science, 2017, Colorado State University

 This dissertation presents knowledge acquisition and retention methods for efficient and robust learning. We propose a framework for learning and memorizing, and we examine how… (more)

Subjects/Keywords: continuous action space; practice; sparse learning; knowledge retention; Bayesian learning; reinforcement learning

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APA (6th Edition):

Lee, M. (2017). Sparse Bayesian reinforcement learning. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/183935

Chicago Manual of Style (16th Edition):

Lee, Minwoo. “Sparse Bayesian reinforcement learning.” 2017. Doctoral Dissertation, Colorado State University. Accessed January 23, 2021. http://hdl.handle.net/10217/183935.

MLA Handbook (7th Edition):

Lee, Minwoo. “Sparse Bayesian reinforcement learning.” 2017. Web. 23 Jan 2021.

Vancouver:

Lee M. Sparse Bayesian reinforcement learning. [Internet] [Doctoral dissertation]. Colorado State University; 2017. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10217/183935.

Council of Science Editors:

Lee M. Sparse Bayesian reinforcement learning. [Doctoral Dissertation]. Colorado State University; 2017. Available from: http://hdl.handle.net/10217/183935


Colorado State University

13. Tan, Haiming. Machine learning-based fusion studies of rainfall estimation from spaceborne and ground-based radars.

Degree: MS(M.S.), Computer Science, 2019, Colorado State University

 Precipitation measurement by satellite radar plays a significant role in researching the water circle and forecasting extreme weather event. Tropical Rainfall Measuring Mission (TRMM) Precipitation… (more)

Subjects/Keywords: rainfall estimation; machine learning; spaceborne radar

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APA (6th Edition):

Tan, H. (2019). Machine learning-based fusion studies of rainfall estimation from spaceborne and ground-based radars. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/195325

Chicago Manual of Style (16th Edition):

Tan, Haiming. “Machine learning-based fusion studies of rainfall estimation from spaceborne and ground-based radars.” 2019. Masters Thesis, Colorado State University. Accessed January 23, 2021. http://hdl.handle.net/10217/195325.

MLA Handbook (7th Edition):

Tan, Haiming. “Machine learning-based fusion studies of rainfall estimation from spaceborne and ground-based radars.” 2019. Web. 23 Jan 2021.

Vancouver:

Tan H. Machine learning-based fusion studies of rainfall estimation from spaceborne and ground-based radars. [Internet] [Masters thesis]. Colorado State University; 2019. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10217/195325.

Council of Science Editors:

Tan H. Machine learning-based fusion studies of rainfall estimation from spaceborne and ground-based radars. [Masters Thesis]. Colorado State University; 2019. Available from: http://hdl.handle.net/10217/195325


Colorado State University

14. Rohmat, Faizal Immaddudin Wira. Machine learning methods to facilitate optimal water allocation and management in irrigated river basins to comply with water law.

Degree: PhD, Civil and Environmental Engineering, 2019, Colorado State University

 The sustainability issues facing irrigated river basins are intensified by legal and institutional regulations imposed on the hydrologic system. Although solutions that would boost water… (more)

Subjects/Keywords: machine learning; reservoir operation; stream-aquifer systems; particle swarm optimization; fuzzy logic; river basin management

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APA (6th Edition):

Rohmat, F. I. W. (2019). Machine learning methods to facilitate optimal water allocation and management in irrigated river basins to comply with water law. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/197364

Chicago Manual of Style (16th Edition):

Rohmat, Faizal Immaddudin Wira. “Machine learning methods to facilitate optimal water allocation and management in irrigated river basins to comply with water law.” 2019. Doctoral Dissertation, Colorado State University. Accessed January 23, 2021. http://hdl.handle.net/10217/197364.

MLA Handbook (7th Edition):

Rohmat, Faizal Immaddudin Wira. “Machine learning methods to facilitate optimal water allocation and management in irrigated river basins to comply with water law.” 2019. Web. 23 Jan 2021.

Vancouver:

Rohmat FIW. Machine learning methods to facilitate optimal water allocation and management in irrigated river basins to comply with water law. [Internet] [Doctoral dissertation]. Colorado State University; 2019. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10217/197364.

Council of Science Editors:

Rohmat FIW. Machine learning methods to facilitate optimal water allocation and management in irrigated river basins to comply with water law. [Doctoral Dissertation]. Colorado State University; 2019. Available from: http://hdl.handle.net/10217/197364

15. Oikonomou, Panagiotis D. Methodologies for transforming data to information and advancing the understanding of water resources systems towards integrated water resources management.

Degree: PhD, Civil and Environmental Engineering, 2017, Colorado State University

 The majority of river basins in the world, have undergone a great deal of transformations in terms of infrastructure and water management practices in order… (more)

Subjects/Keywords: drought vulnerability; groundwater level gap-filling methodology; Weld and Garfield counties; drought; unconventional oil and gas water demand; ensemble smoother; Colorado

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APA (6th Edition):

Oikonomou, P. D. (2017). Methodologies for transforming data to information and advancing the understanding of water resources systems towards integrated water resources management. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/183883

Chicago Manual of Style (16th Edition):

Oikonomou, Panagiotis D. “Methodologies for transforming data to information and advancing the understanding of water resources systems towards integrated water resources management.” 2017. Doctoral Dissertation, Colorado State University. Accessed January 23, 2021. http://hdl.handle.net/10217/183883.

MLA Handbook (7th Edition):

Oikonomou, Panagiotis D. “Methodologies for transforming data to information and advancing the understanding of water resources systems towards integrated water resources management.” 2017. Web. 23 Jan 2021.

Vancouver:

Oikonomou PD. Methodologies for transforming data to information and advancing the understanding of water resources systems towards integrated water resources management. [Internet] [Doctoral dissertation]. Colorado State University; 2017. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10217/183883.

Council of Science Editors:

Oikonomou PD. Methodologies for transforming data to information and advancing the understanding of water resources systems towards integrated water resources management. [Doctoral Dissertation]. Colorado State University; 2017. Available from: http://hdl.handle.net/10217/183883


Colorado State University

16. Narayana, Pradyumna. Improving gesture recognition through spatial focus of attention.

Degree: PhD, Computer Science, 2018, Colorado State University

 Gestures are a common form of human communication and important for human computer interfaces (HCI). Most recent approaches to gesture recognition use deep learning within… (more)

Subjects/Keywords: focus of attention; network fusion; gesture recognition; deep learning

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APA (6th Edition):

Narayana, P. (2018). Improving gesture recognition through spatial focus of attention. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/193149

Chicago Manual of Style (16th Edition):

Narayana, Pradyumna. “Improving gesture recognition through spatial focus of attention.” 2018. Doctoral Dissertation, Colorado State University. Accessed January 23, 2021. http://hdl.handle.net/10217/193149.

MLA Handbook (7th Edition):

Narayana, Pradyumna. “Improving gesture recognition through spatial focus of attention.” 2018. Web. 23 Jan 2021.

Vancouver:

Narayana P. Improving gesture recognition through spatial focus of attention. [Internet] [Doctoral dissertation]. Colorado State University; 2018. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10217/193149.

Council of Science Editors:

Narayana P. Improving gesture recognition through spatial focus of attention. [Doctoral Dissertation]. Colorado State University; 2018. Available from: http://hdl.handle.net/10217/193149


Colorado State University

17. Ashari, Rehab Bahaaddin. EEG subspace analysis and classification using principal angles for brain-computer interfaces.

Degree: PhD, Computer Science, 2015, Colorado State University

 Brain-Computer Interfaces (BCIs) help paralyzed people who have lost some or all of their ability to communicate and control the outside environment from loss of… (more)

Subjects/Keywords: principal angles; brain computer interfaces; subspace

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APA (6th Edition):

Ashari, R. B. (2015). EEG subspace analysis and classification using principal angles for brain-computer interfaces. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/167006

Chicago Manual of Style (16th Edition):

Ashari, Rehab Bahaaddin. “EEG subspace analysis and classification using principal angles for brain-computer interfaces.” 2015. Doctoral Dissertation, Colorado State University. Accessed January 23, 2021. http://hdl.handle.net/10217/167006.

MLA Handbook (7th Edition):

Ashari, Rehab Bahaaddin. “EEG subspace analysis and classification using principal angles for brain-computer interfaces.” 2015. Web. 23 Jan 2021.

Vancouver:

Ashari RB. EEG subspace analysis and classification using principal angles for brain-computer interfaces. [Internet] [Doctoral dissertation]. Colorado State University; 2015. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10217/167006.

Council of Science Editors:

Ashari RB. EEG subspace analysis and classification using principal angles for brain-computer interfaces. [Doctoral Dissertation]. Colorado State University; 2015. Available from: http://hdl.handle.net/10217/167006

18. Elliott, Daniel L. Wisdom of the crowd: reliable deep reinforcement learning through ensembles of Q-functions, The.

Degree: PhD, Computer Science, 2018, Colorado State University

 Reinforcement learning agents learn by exploring the environment and then exploiting what they have learned. This frees the human trainers from having to know the… (more)

Subjects/Keywords: machine learning; Q-learning; ensemble; reinforcement learning; neural networks

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APA (6th Edition):

Elliott, D. L. (2018). Wisdom of the crowd: reliable deep reinforcement learning through ensembles of Q-functions, The. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/191477

Chicago Manual of Style (16th Edition):

Elliott, Daniel L. “Wisdom of the crowd: reliable deep reinforcement learning through ensembles of Q-functions, The.” 2018. Doctoral Dissertation, Colorado State University. Accessed January 23, 2021. http://hdl.handle.net/10217/191477.

MLA Handbook (7th Edition):

Elliott, Daniel L. “Wisdom of the crowd: reliable deep reinforcement learning through ensembles of Q-functions, The.” 2018. Web. 23 Jan 2021.

Vancouver:

Elliott DL. Wisdom of the crowd: reliable deep reinforcement learning through ensembles of Q-functions, The. [Internet] [Doctoral dissertation]. Colorado State University; 2018. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10217/191477.

Council of Science Editors:

Elliott DL. Wisdom of the crowd: reliable deep reinforcement learning through ensembles of Q-functions, The. [Doctoral Dissertation]. Colorado State University; 2018. Available from: http://hdl.handle.net/10217/191477

19. Sadeghi, Marjan. Information-augmented building information models (BIM) to inform facilities management (FM) guidelines.

Degree: PhD, Civil and Environmental Engineering, 2019, Colorado State University

 The asset portfolios of Higher Education Institutions (HEI) typically incorporate a highly diverse collection of buildings with various and often shared campus uses. These facilities… (more)

Subjects/Keywords: building information modeling; industry foundation classes; level of semantics; facilities management; BIM execution plan; level of development

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APA (6th Edition):

Sadeghi, M. (2019). Information-augmented building information models (BIM) to inform facilities management (FM) guidelines. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/197250

Chicago Manual of Style (16th Edition):

Sadeghi, Marjan. “Information-augmented building information models (BIM) to inform facilities management (FM) guidelines.” 2019. Doctoral Dissertation, Colorado State University. Accessed January 23, 2021. http://hdl.handle.net/10217/197250.

MLA Handbook (7th Edition):

Sadeghi, Marjan. “Information-augmented building information models (BIM) to inform facilities management (FM) guidelines.” 2019. Web. 23 Jan 2021.

Vancouver:

Sadeghi M. Information-augmented building information models (BIM) to inform facilities management (FM) guidelines. [Internet] [Doctoral dissertation]. Colorado State University; 2019. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10217/197250.

Council of Science Editors:

Sadeghi M. Information-augmented building information models (BIM) to inform facilities management (FM) guidelines. [Doctoral Dissertation]. Colorado State University; 2019. Available from: http://hdl.handle.net/10217/197250

20. Alotaibi, Saud Saleh. Sentiment analysis in the Arabic language using machine learning.

Degree: PhD, Computer Science, 2015, Colorado State University

 Sentiment analysis has recently become one of the growing areas of research related to natural language processing and machine learning. Much opinion and sentiment about… (more)

Subjects/Keywords: machine learning; sentiment analysis; Arabic sentiment; subjectivity classification; polarity classification

…Translation tOsst jAmς wlAy kwlwrAdw AlHkwmy sn 1870 kkly kwlwrAdw llzrAς Colorado State University… 

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APA (6th Edition):

Alotaibi, S. S. (2015). Sentiment analysis in the Arabic language using machine learning. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/167091

Chicago Manual of Style (16th Edition):

Alotaibi, Saud Saleh. “Sentiment analysis in the Arabic language using machine learning.” 2015. Doctoral Dissertation, Colorado State University. Accessed January 23, 2021. http://hdl.handle.net/10217/167091.

MLA Handbook (7th Edition):

Alotaibi, Saud Saleh. “Sentiment analysis in the Arabic language using machine learning.” 2015. Web. 23 Jan 2021.

Vancouver:

Alotaibi SS. Sentiment analysis in the Arabic language using machine learning. [Internet] [Doctoral dissertation]. Colorado State University; 2015. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10217/167091.

Council of Science Editors:

Alotaibi SS. Sentiment analysis in the Arabic language using machine learning. [Doctoral Dissertation]. Colorado State University; 2015. Available from: http://hdl.handle.net/10217/167091

21. Alzahrani, Saleh Ibrahim. Comparison of tri-polar concentric ring electrodes to disc electrodes for decoding real and imaginary finger movements, A.

Degree: PhD, Bioengineering, 2019, Colorado State University

 The electroencephalogram (EEG) is broadly used for diagnosis of brain diseases and research of brain activities. Although the EEG provides a good temporal resolution, it… (more)

Subjects/Keywords: brain-computer interface; TCRE; EEG

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APA (6th Edition):

Alzahrani, S. I. (2019). Comparison of tri-polar concentric ring electrodes to disc electrodes for decoding real and imaginary finger movements, A. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/195380

Chicago Manual of Style (16th Edition):

Alzahrani, Saleh Ibrahim. “Comparison of tri-polar concentric ring electrodes to disc electrodes for decoding real and imaginary finger movements, A.” 2019. Doctoral Dissertation, Colorado State University. Accessed January 23, 2021. http://hdl.handle.net/10217/195380.

MLA Handbook (7th Edition):

Alzahrani, Saleh Ibrahim. “Comparison of tri-polar concentric ring electrodes to disc electrodes for decoding real and imaginary finger movements, A.” 2019. Web. 23 Jan 2021.

Vancouver:

Alzahrani SI. Comparison of tri-polar concentric ring electrodes to disc electrodes for decoding real and imaginary finger movements, A. [Internet] [Doctoral dissertation]. Colorado State University; 2019. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10217/195380.

Council of Science Editors:

Alzahrani SI. Comparison of tri-polar concentric ring electrodes to disc electrodes for decoding real and imaginary finger movements, A. [Doctoral Dissertation]. Colorado State University; 2019. Available from: http://hdl.handle.net/10217/195380


Colorado State University

22. Teli, Mohammad Nayeem. Dimensionality reduction and classification of time embedded EEG signals.

Degree: MS(M.S.), Computer Science, 2007, Colorado State University

 Electroencephalogram (EEG) is the measurement of the electrical activity of the brain measured by placing electrodes on the scalp. These EEG signals give the micro-voltage… (more)

Subjects/Keywords: SVM; electroencephalogram; QDA; support vector machines; bottleneck neural network; linear discriminant analysis; LDA; quadratic discriminant analysis; Brain-computer interfaces; Electroencephalography; EEG

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APA (6th Edition):

Teli, M. N. (2007). Dimensionality reduction and classification of time embedded EEG signals. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/28637

Chicago Manual of Style (16th Edition):

Teli, Mohammad Nayeem. “Dimensionality reduction and classification of time embedded EEG signals.” 2007. Masters Thesis, Colorado State University. Accessed January 23, 2021. http://hdl.handle.net/10217/28637.

MLA Handbook (7th Edition):

Teli, Mohammad Nayeem. “Dimensionality reduction and classification of time embedded EEG signals.” 2007. Web. 23 Jan 2021.

Vancouver:

Teli MN. Dimensionality reduction and classification of time embedded EEG signals. [Internet] [Masters thesis]. Colorado State University; 2007. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10217/28637.

Council of Science Editors:

Teli MN. Dimensionality reduction and classification of time embedded EEG signals. [Masters Thesis]. Colorado State University; 2007. Available from: http://hdl.handle.net/10217/28637


Colorado State University

23. Buehner, Michael R. Perfect tracking for non-minimum phase systems with applications to biofuels from microalgae.

Degree: PhD, Electrical and Computer Engineering, 2010, Colorado State University

 In a causal setting, a closed-loop control system receives reference inputs (with no a priori knowledge) that it must track. For this setting, controllers are… (more)

Subjects/Keywords: robust; microalgae; feedforward; control systems; biofuels; adaptive; Adaptive control systems; Feedforward control systems; Biomass energy; Microalgae  – Biotechnology

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APA (6th Edition):

Buehner, M. R. (2010). Perfect tracking for non-minimum phase systems with applications to biofuels from microalgae. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/39322

Chicago Manual of Style (16th Edition):

Buehner, Michael R. “Perfect tracking for non-minimum phase systems with applications to biofuels from microalgae.” 2010. Doctoral Dissertation, Colorado State University. Accessed January 23, 2021. http://hdl.handle.net/10217/39322.

MLA Handbook (7th Edition):

Buehner, Michael R. “Perfect tracking for non-minimum phase systems with applications to biofuels from microalgae.” 2010. Web. 23 Jan 2021.

Vancouver:

Buehner MR. Perfect tracking for non-minimum phase systems with applications to biofuels from microalgae. [Internet] [Doctoral dissertation]. Colorado State University; 2010. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10217/39322.

Council of Science Editors:

Buehner MR. Perfect tracking for non-minimum phase systems with applications to biofuels from microalgae. [Doctoral Dissertation]. Colorado State University; 2010. Available from: http://hdl.handle.net/10217/39322


Colorado State University

24. Yadon, Carly Ann. Three types of sensory gating: exploring interrelationships, individual differences, and implications.

Degree: PhD, Psychology, 2010, Colorado State University

 The primary purpose of this dissertation was to determine how information is selectively processed in the brain through sensory gating mechanisms. Filtering, habituation, and orienting… (more)

Subjects/Keywords: Sensory receptors; Cognitive neuroscience; Neuropsychological tests; Attention  – Psychological aspects

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APA (6th Edition):

Yadon, C. A. (2010). Three types of sensory gating: exploring interrelationships, individual differences, and implications. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/39329

Chicago Manual of Style (16th Edition):

Yadon, Carly Ann. “Three types of sensory gating: exploring interrelationships, individual differences, and implications.” 2010. Doctoral Dissertation, Colorado State University. Accessed January 23, 2021. http://hdl.handle.net/10217/39329.

MLA Handbook (7th Edition):

Yadon, Carly Ann. “Three types of sensory gating: exploring interrelationships, individual differences, and implications.” 2010. Web. 23 Jan 2021.

Vancouver:

Yadon CA. Three types of sensory gating: exploring interrelationships, individual differences, and implications. [Internet] [Doctoral dissertation]. Colorado State University; 2010. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10217/39329.

Council of Science Editors:

Yadon CA. Three types of sensory gating: exploring interrelationships, individual differences, and implications. [Doctoral Dissertation]. Colorado State University; 2010. Available from: http://hdl.handle.net/10217/39329


Colorado State University

25. Kazeka, Alexander. Visual location awareness for mobile robots using feature-based vision.

Degree: MS(M.S.), Computer Science, 2010, Colorado State University

 This thesis presents an evaluation of feature-based visual recognition paradigm for the task of mobile robot localization. Although many works describe feature-based visual robot localization,… (more)

Subjects/Keywords: Mobile robots; Robot vision; Computer vision

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APA (6th Edition):

Kazeka, A. (2010). Visual location awareness for mobile robots using feature-based vision. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/38186

Chicago Manual of Style (16th Edition):

Kazeka, Alexander. “Visual location awareness for mobile robots using feature-based vision.” 2010. Masters Thesis, Colorado State University. Accessed January 23, 2021. http://hdl.handle.net/10217/38186.

MLA Handbook (7th Edition):

Kazeka, Alexander. “Visual location awareness for mobile robots using feature-based vision.” 2010. Web. 23 Jan 2021.

Vancouver:

Kazeka A. Visual location awareness for mobile robots using feature-based vision. [Internet] [Masters thesis]. Colorado State University; 2010. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10217/38186.

Council of Science Editors:

Kazeka A. Visual location awareness for mobile robots using feature-based vision. [Masters Thesis]. Colorado State University; 2010. Available from: http://hdl.handle.net/10217/38186


Colorado State University

26. Crawford-Hines, Stewart. Machine learned boundary definitions for an expert's tracing assistant in image processing.

Degree: PhD, Computer Science, 2003, Colorado State University

 Most image processing work addressing boundary definition tasks embeds the assumption that an edge in an image corresponds to the boundary of interest in the… (more)

Subjects/Keywords: visible human imagery; boundary definitions; expert's tracing assistant; ETA; intelligent scissors; IS; active contour models; ACM; boundary-learning system; Image processing; Pattern recognition systems

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APA (6th Edition):

Crawford-Hines, S. (2003). Machine learned boundary definitions for an expert's tracing assistant in image processing. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/28552

Chicago Manual of Style (16th Edition):

Crawford-Hines, Stewart. “Machine learned boundary definitions for an expert's tracing assistant in image processing.” 2003. Doctoral Dissertation, Colorado State University. Accessed January 23, 2021. http://hdl.handle.net/10217/28552.

MLA Handbook (7th Edition):

Crawford-Hines, Stewart. “Machine learned boundary definitions for an expert's tracing assistant in image processing.” 2003. Web. 23 Jan 2021.

Vancouver:

Crawford-Hines S. Machine learned boundary definitions for an expert's tracing assistant in image processing. [Internet] [Doctoral dissertation]. Colorado State University; 2003. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10217/28552.

Council of Science Editors:

Crawford-Hines S. Machine learned boundary definitions for an expert's tracing assistant in image processing. [Doctoral Dissertation]. Colorado State University; 2003. Available from: http://hdl.handle.net/10217/28552


Colorado State University

27. Bush, Keith A. Echo state model of non-Markovian reinforcement learning, An.

Degree: PhD, Computer Science, 2008, Colorado State University

 There exists a growing need for intelligent, autonomous control strategies that operate in real-world domains. Theoretically the state-action space must exhibit the Markov property in… (more)

Subjects/Keywords: reinforcement learning (machine learning); mountain car problem; reinforcement learning; Markovian; echo state network; ESN; fixed point analysis; Hybrid systems

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APA (6th Edition):

Bush, K. A. (2008). Echo state model of non-Markovian reinforcement learning, An. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/28682

Chicago Manual of Style (16th Edition):

Bush, Keith A. “Echo state model of non-Markovian reinforcement learning, An.” 2008. Doctoral Dissertation, Colorado State University. Accessed January 23, 2021. http://hdl.handle.net/10217/28682.

MLA Handbook (7th Edition):

Bush, Keith A. “Echo state model of non-Markovian reinforcement learning, An.” 2008. Web. 23 Jan 2021.

Vancouver:

Bush KA. Echo state model of non-Markovian reinforcement learning, An. [Internet] [Doctoral dissertation]. Colorado State University; 2008. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10217/28682.

Council of Science Editors:

Bush KA. Echo state model of non-Markovian reinforcement learning, An. [Doctoral Dissertation]. Colorado State University; 2008. Available from: http://hdl.handle.net/10217/28682

.