subject:(Hidden Markov Model)

Texas A&M University

1. Wang, Xiduo. A State Dependent Lane-Changing Model for Urban Arterials with Hidden Markov Model Method.

Degree: MS, Civil Engineering, 2015, Texas A&M University

URL: http://hdl.handle.net/1969.1/156266

► The inherent intention and decision process of lane changes are complex and unobservable. Though the external environment and traffic conditions are changing along the traveling… (more)

Subjects/Keywords: Lane Changing; Hidden Markov Model

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

APA (6^th Edition):

Wang, X. (2015). A State Dependent Lane-Changing Model for Urban Arterials with Hidden Markov Model Method. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/156266

Chicago Manual of Style (16^th Edition):

Wang, Xiduo. “A State Dependent Lane-Changing Model for Urban Arterials with Hidden Markov Model Method.” 2015. Masters Thesis, Texas A&M University. Accessed March 01, 2021. http://hdl.handle.net/1969.1/156266.

MLA Handbook (7^th Edition):

Wang, Xiduo. “A State Dependent Lane-Changing Model for Urban Arterials with Hidden Markov Model Method.” 2015. Web. 01 Mar 2021.

Vancouver:

Wang X. A State Dependent Lane-Changing Model for Urban Arterials with Hidden Markov Model Method. [Internet] [Masters thesis]. Texas A&M University; 2015. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/1969.1/156266.

Council of Science Editors:

Wang X. A State Dependent Lane-Changing Model for Urban Arterials with Hidden Markov Model Method. [Masters Thesis]. Texas A&M University; 2015. Available from: http://hdl.handle.net/1969.1/156266

Rice University

2. Ackermann, Etienne Rudolph. Latent variable models for hippocampal sequence analysis.

Degree: PhD, Engineering, 2019, Rice University

URL: http://hdl.handle.net/1911/106148

► Place cell activity of hippocampal pyramidal cells has been described as the cognitive substrate of spatial memory. Indeed, the activity of ensembles of neurons within… (more)

▼ Place cell activity of hippocampal pyramidal cells has been described as the cognitive substrate of spatial memory. Indeed, the activity of ensembles of neurons within the hippocampus is thought to enable memory formation, storage, recall, and even decision making. Replay is observed during hippocampal sharp-wave-ripple-associated population burst events (PBEs) and is critical for consolidation and recall-guided behaviors. Notably, these PBEs occur during times of inactivity, so that their representations cannot easily be matched with observable animal behavior. In my thesis, I present an approach to uncover temporal structure within hippocampal output patterns during PBEs. More specifically, I use hidden Markov models (HMMs) to study PBEs observed in rats during exploration of both linear tracks and open fields, and I demonstrate that estimated models are consistent with a spatial map of the environment. Moreover, I demonstrate how the model can be used to identify hippocampal replay without recourse to the place code. These results suggest that downstream regions may rely on PBEs to provide a substrate for memory. Moreover, by forming models independent of animal behavior, I lay the groundwork for studies of non-spatial memory. Next, I present a new model, the "clusterless" switching Poisson hidden Markov model, which extends my work on HMMs of PBEs to the case where we only have multiunit (unsorted) spikes. Indeed, spike sorting is challenging, time-consuming, often subjective (not reproducible), and throws away potentially valuable information from unsorted spikes, as well as our certainty about the cluster assignments. It has previously been shown that we can often do just as well, or in some cases even better, if we forego the spike sorting process altogether, and work directly with the unsorted data. Consequently, my clusterless HMM will enable us to combine the benefits of unsupervised learning for internally generated neural activity, with the benefits of clusterless approaches (more data leading to higher fidelity, especially at fine temporal scales, and additional probabilistic / soft information to exploit). I demonstrate the model's ability to recover model parameters for simulated data, and show that it is able to learn a spatially-consistent representation of the environment from real experimental data. Advisors/Committee Members: Kemere, Caleb (advisor).

Subjects/Keywords: hippocampal replay; hidden Markov model

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

APA (6^th Edition):

Ackermann, E. R. (2019). Latent variable models for hippocampal sequence analysis. (Doctoral Dissertation). Rice University. Retrieved from http://hdl.handle.net/1911/106148

Chicago Manual of Style (16^th Edition):

Ackermann, Etienne Rudolph. “Latent variable models for hippocampal sequence analysis.” 2019. Doctoral Dissertation, Rice University. Accessed March 01, 2021. http://hdl.handle.net/1911/106148.

MLA Handbook (7^th Edition):

Ackermann, Etienne Rudolph. “Latent variable models for hippocampal sequence analysis.” 2019. Web. 01 Mar 2021.

Vancouver:

Ackermann ER. Latent variable models for hippocampal sequence analysis. [Internet] [Doctoral dissertation]. Rice University; 2019. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/1911/106148.

Council of Science Editors:

Ackermann ER. Latent variable models for hippocampal sequence analysis. [Doctoral Dissertation]. Rice University; 2019. Available from: http://hdl.handle.net/1911/106148

Rice University

3. Ackermann, Etienne Rudolph. Latent variable models for hippocampal sequence analysis.

Degree: PhD, Neuroengineering, 2019, Rice University

URL: http://hdl.handle.net/1911/106149

► Place cell activity of hippocampal pyramidal cells has been described as the cognitive substrate of spatial memory. Indeed, the activity of ensembles of neurons within… (more)

▼ Place cell activity of hippocampal pyramidal cells has been described as the cognitive substrate of spatial memory. Indeed, the activity of ensembles of neurons within the hippocampus is thought to enable memory formation, storage, recall, and even decision making. Replay is observed during hippocampal sharp-wave-ripple-associated population burst events (PBEs) and is critical for consolidation and recall-guided behaviors. Notably, these PBEs occur during times of inactivity, so that their representations cannot easily be matched with observable animal behavior. In my thesis, I present an approach to uncover temporal structure within hippocampal output patterns during PBEs. More specifically, I use hidden Markov models (HMMs) to study PBEs observed in rats during exploration of both linear tracks and open fields, and I demonstrate that estimated models are consistent with a spatial map of the environment. Moreover, I demonstrate how the model can be used to identify hippocampal replay without recourse to the place code. These results suggest that downstream regions may rely on PBEs to provide a substrate for memory. Moreover, by forming models independent of animal behavior, I lay the groundwork for studies of non-spatial memory. Next, I present a new model, the "clusterless" switching Poisson hidden Markov model, which extends my work on HMMs of PBEs to the case where we only have multiunit (unsorted) spikes. Indeed, spike sorting is challenging, time-consuming, often subjective (not reproducible), and throws away potentially valuable information from unsorted spikes, as well as our certainty about the cluster assignments. It has previously been shown that we can often do just as well, or in some cases even better, if we forego the spike sorting process altogether, and work directly with the unsorted data. Consequently, my clusterless HMM will enable us to combine the benefits of unsupervised learning for internally generated neural activity, with the benefits of clusterless approaches (more data leading to higher fidelity, especially at fine temporal scales, and additional probabilistic / soft information to exploit). I demonstrate the model's ability to recover model parameters for simulated data, and show that it is able to learn a spatially-consistent representation of the environment from real experimental data. Advisors/Committee Members: Kemere, Caleb (advisor).

Subjects/Keywords: hippocampal replay; hidden Markov model

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

APA (6^th Edition):

Ackermann, E. R. (2019). Latent variable models for hippocampal sequence analysis. (Doctoral Dissertation). Rice University. Retrieved from http://hdl.handle.net/1911/106149

Chicago Manual of Style (16^th Edition):

Ackermann, Etienne Rudolph. “Latent variable models for hippocampal sequence analysis.” 2019. Doctoral Dissertation, Rice University. Accessed March 01, 2021. http://hdl.handle.net/1911/106149.

MLA Handbook (7^th Edition):

Ackermann, Etienne Rudolph. “Latent variable models for hippocampal sequence analysis.” 2019. Web. 01 Mar 2021.

Vancouver:

Ackermann ER. Latent variable models for hippocampal sequence analysis. [Internet] [Doctoral dissertation]. Rice University; 2019. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/1911/106149.

Council of Science Editors:

Ackermann ER. Latent variable models for hippocampal sequence analysis. [Doctoral Dissertation]. Rice University; 2019. Available from: http://hdl.handle.net/1911/106149

NSYSU

4. Huang, Yu-Zhi. Detecting Attack Sequence in Cloud Based on Hidden Markov Model.

Degree: Master, Computer Science and Engineering, 2012, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0726112-150041

► Cloud computing provides business new working paradigm with the benefit of cost reduce and resource sharing. Tasks from different users may be performed on the… (more)

Subjects/Keywords: Cloud Computing; Hidden Markov Model; Attack Plan

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

APA (6^th Edition):

Huang, Y. (2012). Detecting Attack Sequence in Cloud Based on Hidden Markov Model. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0726112-150041

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

Chicago Manual of Style (16^th Edition):

Huang, Yu-Zhi. “Detecting Attack Sequence in Cloud Based on Hidden Markov Model.” 2012. Thesis, NSYSU. Accessed March 01, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0726112-150041.

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

MLA Handbook (7^th Edition):

Huang, Yu-Zhi. “Detecting Attack Sequence in Cloud Based on Hidden Markov Model.” 2012. Web. 01 Mar 2021.

Vancouver:

Huang Y. Detecting Attack Sequence in Cloud Based on Hidden Markov Model. [Internet] [Thesis]. NSYSU; 2012. [cited 2021 Mar 01]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0726112-150041.

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

Council of Science Editors:

Huang Y. Detecting Attack Sequence in Cloud Based on Hidden Markov Model. [Thesis]. NSYSU; 2012. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0726112-150041

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

5. Nut Sornchumni. Research on Parameter Estimation of Hidden Markov Model with Differential Privacy : 隠れマルコフモデルに対するパラメータ推定アルゴリズムの差分プライバシー化に関する研究; カクレマルコフモデルニタイスルパラメータスイテイアルゴリズムノサブンプライバシーカニカンスルケンキュウ.

Degree: Nara Institute of Science and Technology / 奈良先端科学技術大学院大学

URL: http://hdl.handle.net/10061/9846

Subjects/Keywords: Hidden Markov model

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APA (6^th Edition):

Sornchumni, N. (n.d.). Research on Parameter Estimation of Hidden Markov Model with Differential Privacy : 隠れマルコフモデルに対するパラメータ推定アルゴリズムの差分プライバシー化に関する研究; カクレマルコフモデルニタイスルパラメータスイテイアルゴリズムノサブンプライバシーカニカンスルケンキュウ. (Thesis). Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Retrieved from http://hdl.handle.net/10061/9846

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Sornchumni, Nut. “Research on Parameter Estimation of Hidden Markov Model with Differential Privacy : 隠れマルコフモデルに対するパラメータ推定アルゴリズムの差分プライバシー化に関する研究; カクレマルコフモデルニタイスルパラメータスイテイアルゴリズムノサブンプライバシーカニカンスルケンキュウ.” Thesis, Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Accessed March 01, 2021. http://hdl.handle.net/10061/9846.

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Sornchumni, Nut. “Research on Parameter Estimation of Hidden Markov Model with Differential Privacy : 隠れマルコフモデルに対するパラメータ推定アルゴリズムの差分プライバシー化に関する研究; カクレマルコフモデルニタイスルパラメータスイテイアルゴリズムノサブンプライバシーカニカンスルケンキュウ.” Web. 01 Mar 2021.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Vancouver:

Sornchumni N. Research on Parameter Estimation of Hidden Markov Model with Differential Privacy : 隠れマルコフモデルに対するパラメータ推定アルゴリズムの差分プライバシー化に関する研究; カクレマルコフモデルニタイスルパラメータスイテイアルゴリズムノサブンプライバシーカニカンスルケンキュウ. [Internet] [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; [cited 2021 Mar 01]. Available from: http://hdl.handle.net/10061/9846.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

Council of Science Editors:

Sornchumni N. Research on Parameter Estimation of Hidden Markov Model with Differential Privacy : 隠れマルコフモデルに対するパラメータ推定アルゴリズムの差分プライバシー化に関する研究; カクレマルコフモデルニタイスルパラメータスイテイアルゴリズムノサブンプライバシーカニカンスルケンキュウ. [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; Available from: http://hdl.handle.net/10061/9846

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

Penn State University

6. Osotsi, Ame J. Event Detection in Twitter Data: A Hidden Markov Model-Based Change Point Algorithm.

Degree: 2016, Penn State University

URL: https://submit-etda.libraries.psu.edu/catalog/vm40xr56k

► Twitter is a popular microblogging platform that displays real-time status updates from over 140 million users a day. The users post about anything, from daily… (more)

Subjects/Keywords: Change Point; Hidden Markov Model; Twitter

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APA (6^th Edition):

Osotsi, A. J. (2016). Event Detection in Twitter Data: A Hidden Markov Model-Based Change Point Algorithm. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/vm40xr56k

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

Chicago Manual of Style (16^th Edition):

Osotsi, Ame J. “Event Detection in Twitter Data: A Hidden Markov Model-Based Change Point Algorithm.” 2016. Thesis, Penn State University. Accessed March 01, 2021. https://submit-etda.libraries.psu.edu/catalog/vm40xr56k.

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

MLA Handbook (7^th Edition):

Osotsi, Ame J. “Event Detection in Twitter Data: A Hidden Markov Model-Based Change Point Algorithm.” 2016. Web. 01 Mar 2021.

Vancouver:

Osotsi AJ. Event Detection in Twitter Data: A Hidden Markov Model-Based Change Point Algorithm. [Internet] [Thesis]. Penn State University; 2016. [cited 2021 Mar 01]. Available from: https://submit-etda.libraries.psu.edu/catalog/vm40xr56k.

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

Council of Science Editors:

Osotsi AJ. Event Detection in Twitter Data: A Hidden Markov Model-Based Change Point Algorithm. [Thesis]. Penn State University; 2016. Available from: https://submit-etda.libraries.psu.edu/catalog/vm40xr56k

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

NSYSU

7. Liu, Lun-Kang. The Analysis and Forecasting of the Bitcoin Return.

Degree: Master, Institute Of Applied Mathematics, 2018, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0603118-164022

► The feasibility of cryptocurrency as an investment tool has been a topic of considerable concern in recent years. Bitcoin is a cryptocurrency that is universally… (more)

Subjects/Keywords: Text mining; Hidden Markov model; Cryptocurrency

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APA (6^th Edition):

Liu, L. (2018). The Analysis and Forecasting of the Bitcoin Return. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0603118-164022

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

Chicago Manual of Style (16^th Edition):

Liu, Lun-Kang. “The Analysis and Forecasting of the Bitcoin Return.” 2018. Thesis, NSYSU. Accessed March 01, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0603118-164022.

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

MLA Handbook (7^th Edition):

Liu, Lun-Kang. “The Analysis and Forecasting of the Bitcoin Return.” 2018. Web. 01 Mar 2021.

Vancouver:

Liu L. The Analysis and Forecasting of the Bitcoin Return. [Internet] [Thesis]. NSYSU; 2018. [cited 2021 Mar 01]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0603118-164022.

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

Council of Science Editors:

Liu L. The Analysis and Forecasting of the Bitcoin Return. [Thesis]. NSYSU; 2018. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0603118-164022

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

University of North Texas

8. Saudagar, Abdullah Naseer Ahmed. Automatic Extraction of Highlights from a Baseball Video Using HMM and MPEG-7 Descriptors.

Degree: 2011, University of North Texas

URL: https://digital.library.unt.edu/ark:/67531/metadc103388/

► In today’s fast paced world, as the number of stations of television programming offered is increasing rapidly, time accessible to watch them remains same or… (more)

Subjects/Keywords: highlights; descriptors; MPEG-7; hidden Markov model

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APA (6^th Edition):

Saudagar, A. N. A. (2011). Automatic Extraction of Highlights from a Baseball Video Using HMM and MPEG-7 Descriptors. (Thesis). University of North Texas. Retrieved from https://digital.library.unt.edu/ark:/67531/metadc103388/

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

Chicago Manual of Style (16^th Edition):

Saudagar, Abdullah Naseer Ahmed. “Automatic Extraction of Highlights from a Baseball Video Using HMM and MPEG-7 Descriptors.” 2011. Thesis, University of North Texas. Accessed March 01, 2021. https://digital.library.unt.edu/ark:/67531/metadc103388/.

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

MLA Handbook (7^th Edition):

Saudagar, Abdullah Naseer Ahmed. “Automatic Extraction of Highlights from a Baseball Video Using HMM and MPEG-7 Descriptors.” 2011. Web. 01 Mar 2021.

Vancouver:

Saudagar ANA. Automatic Extraction of Highlights from a Baseball Video Using HMM and MPEG-7 Descriptors. [Internet] [Thesis]. University of North Texas; 2011. [cited 2021 Mar 01]. Available from: https://digital.library.unt.edu/ark:/67531/metadc103388/.

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

Council of Science Editors:

Saudagar ANA. Automatic Extraction of Highlights from a Baseball Video Using HMM and MPEG-7 Descriptors. [Thesis]. University of North Texas; 2011. Available from: https://digital.library.unt.edu/ark:/67531/metadc103388/

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

University of Texas – Austin

9. Li, Na. Hidden Markov model and financial application.

Degree: MSin Statistics, Statistics, 2016, University of Texas – Austin

URL: http://hdl.handle.net/2152/47043

► A Hidden Markov model (HMM) is a statistical model in which the system being modeled is assumed to be a Markov process with numerous unobserved… (more)

Subjects/Keywords: Hidden Markov model; Financial time series

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

APA (6^th Edition):

Li, N. (2016). Hidden Markov model and financial application. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/47043

Chicago Manual of Style (16^th Edition):

Li, Na. “Hidden Markov model and financial application.” 2016. Masters Thesis, University of Texas – Austin. Accessed March 01, 2021. http://hdl.handle.net/2152/47043.

MLA Handbook (7^th Edition):

Li, Na. “Hidden Markov model and financial application.” 2016. Web. 01 Mar 2021.

Vancouver:

Li N. Hidden Markov model and financial application. [Internet] [Masters thesis]. University of Texas – Austin; 2016. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/2152/47043.

Council of Science Editors:

Li N. Hidden Markov model and financial application. [Masters Thesis]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/47043

University of Texas – Austin

10. -6024-5216. Uncertainty quantification and its properties for hidden Markov models with application to condition based maintenance.

Degree: PhD, Operations Research and Industrial Engineering, 2018, University of Texas – Austin

URL: http://hdl.handle.net/2152/63715

► Condition-based maintenance (CBM) can be viewed as a transformation of data gathered from a piece of equipment into information about its condition, and further into… (more)

▼ Condition-based maintenance (CBM) can be viewed as a transformation of data gathered from a piece of equipment into information about its condition, and further into decisions on what to do with the equipment. Hidden Markov model (HMM) is a useful framework to probabilistically model the condition of complex engineering systems with partial observability of the underlying states. Condition monitoring and prediction of such type of system requires accurate knowledge of HMM that describes the degradation of such a system with data collected from the sensors mounted on it, as well as understanding of the uncertainty of the HMMs identified from the available data. To that end, this thesis proposes a novel HMM estimation scheme based on the principles of Bayes theorem. The newly proposed Bayesian estimation approach for estimating HMM parameters naturally yields information about model parametric uncertainties via posterior distributions of HMM parameters emanating from the estimation process. In addition, a novel condition monitoring scheme based on uncertain HMMs of the degradation process is proposed and demonstrated on a large dataset obtained from a semiconductor manufacturing facility. Portion of the data was used to build operating mode specific HMMs of machine degradation via the newly proposed Bayesian estimation process, while the remainder of the data was used for monitoring of machine condition using the uncertain degradation HMMs yielded by Bayesian estimation. Comparison with a traditional signature-based statistical monitoring method showed that the newly proposed approach effectively utilizes the fact that its parameters are uncertain themselves, leading to orders of magnitude fewer false alarms. This methodology is further extended to address the practical issue that maintenance interventions are usually imperfect. We propose both a novel non-ergodic and non-homogeneous HMM that assumes imperfect maintenances and a novel process monitoring method capable of monitoring the hidden states considering model uncertainty. Significant improvement in both the log-likelihood of estimated HMM parameters and monitoring performance were observed, compared to those obtained using degradation HMMs that always assumed perfect maintenance. Finally, behavior of the posterior distribution of parameters of unidirectional non- ergodic HMMs modeling in this thesis for degradation was theoretically analyzed in terms of their evolution as more data become available in the estimation process. The convergence problem is formulated as a Bernstein-von Mises theorem (BvMT), and under certain regularity conditions, the sequence of posterior distributions is proven to converge to a Gaussian distribution with variance matrix being the inverse of the Fisher information matrix. An example of a unidirectional HMM is presented for which the regularity conditions are verified, and illustrations of expected theoretical results are given using simulation. The understanding of such convergence of posterior distributions enables one to… Advisors/Committee Members: Djurdjanovic, Dragan (advisor), Hasenbein, John (committee member), Bickel, James Eric (committee member), Walker, Stephen G (committee member), Hanasusanto, Grani (committee member).

Subjects/Keywords: Hidden Markov model; Condition-based maintenance

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APA (6^th Edition):

-6024-5216. (2018). Uncertainty quantification and its properties for hidden Markov models with application to condition based maintenance. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/63715

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16^th Edition):

-6024-5216. “Uncertainty quantification and its properties for hidden Markov models with application to condition based maintenance.” 2018. Doctoral Dissertation, University of Texas – Austin. Accessed March 01, 2021. http://hdl.handle.net/2152/63715.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7^th Edition):

-6024-5216. “Uncertainty quantification and its properties for hidden Markov models with application to condition based maintenance.” 2018. Web. 01 Mar 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-6024-5216. Uncertainty quantification and its properties for hidden Markov models with application to condition based maintenance. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2018. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/2152/63715.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-6024-5216. Uncertainty quantification and its properties for hidden Markov models with application to condition based maintenance. [Doctoral Dissertation]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/63715

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Virginia Tech

11. Liu, Mingming. Predicting the Functional Effects of Human Short Variations Using Hidden Markov Models.

Degree: PhD, Computer Science and Applications, 2015, Virginia Tech

URL: http://hdl.handle.net/10919/73703

► With the development of sequencing technologies, more and more sequence variants are available for investigation. Different types of variants in the human genome have been… (more)

Subjects/Keywords: Genetic variation; Indel; SNP; Hidden Markov Model

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

APA (6^th Edition):

Liu, M. (2015). Predicting the Functional Effects of Human Short Variations Using Hidden Markov Models. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/73703

Chicago Manual of Style (16^th Edition):

Liu, Mingming. “Predicting the Functional Effects of Human Short Variations Using Hidden Markov Models.” 2015. Doctoral Dissertation, Virginia Tech. Accessed March 01, 2021. http://hdl.handle.net/10919/73703.

MLA Handbook (7^th Edition):

Liu, Mingming. “Predicting the Functional Effects of Human Short Variations Using Hidden Markov Models.” 2015. Web. 01 Mar 2021.

Vancouver:

Liu M. Predicting the Functional Effects of Human Short Variations Using Hidden Markov Models. [Internet] [Doctoral dissertation]. Virginia Tech; 2015. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/10919/73703.

Council of Science Editors:

Liu M. Predicting the Functional Effects of Human Short Variations Using Hidden Markov Models. [Doctoral Dissertation]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/73703

Anna University

12. Jagadeesh Kannan R. Handwritten character recognition using hybrid techniques.

Degree: Information and Communication, 2013, Anna University

URL: http://shodhganga.inflibnet.ac.in/handle/10603/9849

►

The primary objective of this research work is to develop a character recognition system, which can further be developed to recognize all printed and handwritten… (more)

▼

The primary objective of this research work is to develop a character recognition system, which can further be developed to recognize all printed and handwritten Tamil characters. Such a system will be extremely useful to digitize innumerable ancient documents available both on paper and palm leaves and are dated few hundred years back. The problem considered is to develop a recognition system for Printed and Handwritten Tamil and Numeral Characters. An overview of the research work is presented below. The first component of this research work focuses on technique to recognize handwritten Tamil characters using a Hidden Markov Model (HMM) approach, for a subset of the Tamil alphabet. The second component of this research work also focuses on technique to recognize handwritten Tamil characters using an Octal Graph approach. The third component introduces a methodology to recognize handwritten characters using Structural Hidden Markov Models (SHMM). The proposed approach is motivated by the need to model complex structures which are encountered in many areas such as speech/handwriting recognition, content-based information retrieval etc. The observations considered are strings that produce the structures. These observations are related in the sense they all contribute to produce a particular structure. The recognition efficiency of the system is 96.5%. The results reported in this component shows that the Structural Hidden Markov Model (SHMM) produces better recognition than the Hidden Markov Model. A character recognition system was successfully developed for subset of Tamil characters and numerals and found to perform reasonably well with sufficient accuracy. With this preliminary study of character recognition systems it is planned to continue the work in future. A more complete OCR will evolve in public domain with this work as the starting point, so that the primary source of motivation will benefit from the efforts.

None

Advisors/Committee Members: Suresh R M.

Subjects/Keywords: Structural Hidden Markov Model; Hidden Markov Model; Character recognition system; Tamil character

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

APA (6^th Edition):

R, J. K. (2013). Handwritten character recognition using hybrid techniques. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/9849

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

Chicago Manual of Style (16^th Edition):

R, Jagadeesh Kannan. “Handwritten character recognition using hybrid techniques.” 2013. Thesis, Anna University. Accessed March 01, 2021. http://shodhganga.inflibnet.ac.in/handle/10603/9849.

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

MLA Handbook (7^th Edition):

R, Jagadeesh Kannan. “Handwritten character recognition using hybrid techniques.” 2013. Web. 01 Mar 2021.

Vancouver:

R JK. Handwritten character recognition using hybrid techniques. [Internet] [Thesis]. Anna University; 2013. [cited 2021 Mar 01]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/9849.

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

Council of Science Editors:

R JK. Handwritten character recognition using hybrid techniques. [Thesis]. Anna University; 2013. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/9849

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

Virginia Tech

13. Ali Akbar Soltan, Reza. Enhancements in Markovian Dynamics.

Degree: PhD, Mechanical Engineering, 2012, Virginia Tech

URL: http://hdl.handle.net/10919/77345

► Many common statistical techniques for modeling multidimensional dynamic data sets can be seen as variants of one (or multiple) underlying linear/nonlinear model(s). These statistical techniques… (more)

▼ Many common statistical techniques for modeling multidimensional dynamic data sets can be seen as variants of one (or multiple) underlying linear/nonlinear model(s). These statistical techniques fall into two broad categories of supervised and unsupervised learning. The emphasis of this dissertation is on unsupervised learning under multiple generative models. For linear models, this has been achieved by collective observations and derivations made by previous authors during the last few decades. Factor analysis, polynomial chaos expansion, principal component analysis, gaussian mixture clustering, vector quantization, and Kalman filter models can all be unified as some variations of unsupervised learning under a single basic linear generative model. Hidden Markov modeling (HMM), however, is categorized as an unsupervised learning under multiple linear/nonlinear generative models. This dissertation is primarily focused on hidden Markov models (HMMs). On the first half of this dissertation we study enhancements on the theory of hidden Markov modeling. These include three branches: 1) a robust as well as a closed-form parameter estimation solution to the expectation maximization (EM) process of HMMs for the case of elliptically symmetrical densities; 2) a two-step HMM, with a combined state sequence via an extended Viterbi algorithm for smoother state estimation; and 3) a duration-dependent HMM, for estimating the expected residency frequency on each state. Then, the second half of the dissertation studies three novel applications of these methods: 1) the applications of Markov switching models on the Bifurcation Theory in nonlinear dynamics; 2) a Game Theory application of HMM, based on fundamental theory of card counting and an example on the game of Baccarat; and 3) Trust modeling and the estimation of trustworthiness metrics in cyber security systems via Markov switching models. As a result of the duration dependent HMM, we achieved a better estimation for the expected duration of stay on each regime. Then by robust and closed form solution to the EM algorithm we achieved robustness against outliers in the training data set as well as higher computational efficiency in the maximization step of the EM algorithm. By means of the two-step HMM we achieved smoother probability estimation with higher likelihood than the standard HMM. Advisors/Committee Members: Ahmadian, Mehdi (committeechair), Hall, T. Simin (committee member), Southward, Steve C. (committee member), Asl, Farshid M. (committee member), Ball, Joseph A. (committee member), Taheri, Saied (committee member).

Subjects/Keywords: Duration Dependent Hidden Markov; Expectation Maximization; Nonlinear Stochastic Model; Hidden Markov Model; Maximum Likelihood Estimation

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

APA (6^th Edition):

Ali Akbar Soltan, R. (2012). Enhancements in Markovian Dynamics. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/77345

Chicago Manual of Style (16^th Edition):

Ali Akbar Soltan, Reza. “Enhancements in Markovian Dynamics.” 2012. Doctoral Dissertation, Virginia Tech. Accessed March 01, 2021. http://hdl.handle.net/10919/77345.

MLA Handbook (7^th Edition):

Ali Akbar Soltan, Reza. “Enhancements in Markovian Dynamics.” 2012. Web. 01 Mar 2021.

Vancouver:

Ali Akbar Soltan R. Enhancements in Markovian Dynamics. [Internet] [Doctoral dissertation]. Virginia Tech; 2012. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/10919/77345.

Council of Science Editors:

Ali Akbar Soltan R. Enhancements in Markovian Dynamics. [Doctoral Dissertation]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/77345

University of Waterloo

14. Shi, Yidan. Statistical Methods for Event History Data under Response Dependent Sampling and Incomplete Observation.

Degree: 2020, University of Waterloo

URL: http://hdl.handle.net/10012/16062

► This thesis discusses statistical problems in event history data analysis including survival analysis and multistate models. Research questions in this thesis are motivated by the… (more)

▼ This thesis discusses statistical problems in event history data analysis including survival analysis and multistate models. Research questions in this thesis are motivated by the Nun Study, which contains longevity data and longitudinal follow-up of cognition functions in 678 religious sisters. Our research interests lie in modeling the survival pattern and the disease process for dementia. These data are subject to a process-dependent sampling scheme, and the homogeneous Markov assumption is violated when using a multistate model to fit the panel data for cognition. In this thesis, we formulated three statistical questions according to the aforementioned issues and propose approaches to deal with these problems. Survival analysis is often subject to left-truncation when the data are collected within certain study windows. Naive methods ignoring the sampling conditions yield invalid estimates. Much work has been done to deal with the bias caused by left-truncation. However, discussion on the loss-in-efficiency is limited. In Chapter 2, we proposed a method in which auxiliary information is borrowed to improve the efficiency in estimation. The auxiliary information includes summary-level statistics from a previous study on the same cohort and census data for a comparable population. The likelihood and score functions are developed. A Monte Carlo approximation is proposed to deal with the difficulty in obtaining tractable forms of the score and information functions. The method is illustrated by both simulation and real data application to the Nun Study. Continuous-time Markov models are widely used for analyzing longitudinal data on the disease progression over time due to the great convenience for computing the probability transition matrices and the likelihood functions. However, in practice, the Markov assumption does not always hold. Most of the existing methods relax the Markov assumption while losing the advantage of that assumption in the calculation of transition probabilities. In Chapter 3, we consider the case where the violation of the Markov property is due to multiple underlying types of disease. We propose a mixture hidden Markov model where the underlying process is characterized by a mixture of multiple time-homogeneous Markov chains, one for each disease type, while the observation process contains states corresponding to the common symptomatic stages of these diseases. The method can be applied to modeling the disease process of Alzheimer's disease and other types of dementia. In the Nun Study, autopsies were conducted on some of the deceased participants so that one can know whether these individuals have Alzheimer's pathology in their brains. Our method can incorporate these partially observed pathology data as disease type indicators to improve the efficiency in estimation. The predictions for the overall prevalence and type-specific prevalence for dementia are calculated based on the proposed method. The performance of the proposed methods is also evaluated via simulation studies. …

Subjects/Keywords: survival analysis; multistate model; left truncation; hidden Markov model; auxiliary information

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

APA (6^th Edition):

Shi, Y. (2020). Statistical Methods for Event History Data under Response Dependent Sampling and Incomplete Observation. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/16062

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

Chicago Manual of Style (16^th Edition):

Shi, Yidan. “Statistical Methods for Event History Data under Response Dependent Sampling and Incomplete Observation.” 2020. Thesis, University of Waterloo. Accessed March 01, 2021. http://hdl.handle.net/10012/16062.

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

MLA Handbook (7^th Edition):

Shi, Yidan. “Statistical Methods for Event History Data under Response Dependent Sampling and Incomplete Observation.” 2020. Web. 01 Mar 2021.

Vancouver:

Shi Y. Statistical Methods for Event History Data under Response Dependent Sampling and Incomplete Observation. [Internet] [Thesis]. University of Waterloo; 2020. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/10012/16062.

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

Council of Science Editors:

Shi Y. Statistical Methods for Event History Data under Response Dependent Sampling and Incomplete Observation. [Thesis]. University of Waterloo; 2020. Available from: http://hdl.handle.net/10012/16062

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

University of St. Andrews

15. Worthington, Hannah. The statistical development of integrated multi-state stopover models .

Degree: 2016, University of St. Andrews

URL: http://hdl.handle.net/10023/18206

► This thesis focusses on the analysis of ecological capture-recapture data and the estimation of population parameters of interest. Many of the common models applied to… (more)

▼ This thesis focusses on the analysis of ecological capture-recapture data and the estimation of population parameters of interest. Many of the common models applied to such data, for example the Cormack-Jolly-Seber model, condition on the first capture of an individual or on the number of individuals encountered. A consequence of this conditioning is that it is not possible to estimate the total abundance directly. Stopover models remove the conditioning on first capture and instead explicitly model the arrival of individuals into the population. This permits the estimation of abundance through the likelihood along with other parameters such as capture and retention probabilities. We develop an integrated stopover model capable of analysing multiple years of data within a single likelihood and allowing parameters to be shared across years. We consider special cases of this model, writing the likelihood using sufficient statistics as well as utilising the hidden Markov model framework to allow for efficient evaluation of the likelihood. We further extend this model to an integrated multistate-stopover model which incorporates any available discrete state information. The new stopover models are applied to real ecological data sets. A cohort-dependent single-year stopover model is applied to data on grey seals, Halichoerus grypus, where the cohorts are determined by birth year. The integrated stopover model and integrated multi-state stopover model are used to analyse a data set on great crested newts, Triturus cristatus. A subset of this data is used to explore closed population models that permit capture probabilities to depend on discrete state information. The final section of this thesis considers a capture-recapture-recovery data set relating to Soay sheep, a breed of domestic sheep Ovis aries. These data contain individual time-varying continuous covariates and raise the issue of dealing with missing data. Advisors/Committee Members: King, Ruth (advisor).

Subjects/Keywords: Integrated stopover model; Capture-recapture; Hidden Markov model; Multi-state

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APA (6^th Edition):

Worthington, H. (2016). The statistical development of integrated multi-state stopover models . (Thesis). University of St. Andrews. Retrieved from http://hdl.handle.net/10023/18206

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

Chicago Manual of Style (16^th Edition):

Worthington, Hannah. “The statistical development of integrated multi-state stopover models .” 2016. Thesis, University of St. Andrews. Accessed March 01, 2021. http://hdl.handle.net/10023/18206.

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

MLA Handbook (7^th Edition):

Worthington, Hannah. “The statistical development of integrated multi-state stopover models .” 2016. Web. 01 Mar 2021.

Vancouver:

Worthington H. The statistical development of integrated multi-state stopover models . [Internet] [Thesis]. University of St. Andrews; 2016. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/10023/18206.

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

Council of Science Editors:

Worthington H. The statistical development of integrated multi-state stopover models . [Thesis]. University of St. Andrews; 2016. Available from: http://hdl.handle.net/10023/18206

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

University of Melbourne

16. Li, Yan. A probabilistic approach for Wi-Fi based indoor localization.

Degree: 2019, University of Melbourne

URL: http://hdl.handle.net/11343/234278

► The Global Navigation Satellite System (GNSS) has been widely used to provide location information in outdoor environments, but it fails to provide reliable positioning indoors.… (more)

▼ The Global Navigation Satellite System (GNSS) has been widely used to provide location information in outdoor environments, but it fails to provide reliable positioning indoors. WiFi based localization systems have attracted considerable attention because of the extensive deployment of Wireless Local Area Network (WLAN) infrastructure and the ubiquity of WiFi enabled mobile devices, offering a potentially low-cost way to track a mobile user in an indoor environment. The mainstream WiFi fingerprint based systems deployed in a practical large-scale wireless environment still encounter critical challenges in terms of intensive survey cost and large variations in a dynamic environment. Crowdsourcing, by its nature, uses heterogeneous devices in the process of surveying the site. While this reduces the time needed during the surveying phase, account needs to be taken of the variation in sensor performance. This variation results in a diversity in received signal strength (RSS) values and varying sensitivities to different access points (APs). In a complex and noisy indoor environment, for example a university building, a large number of APs can be sensed during both the survey and positioning phase, leading to a high-dimensional classification problem. In addition, because of multipath (fading channel) variation, signals from APs may not be sensed in every scan, thus resulting in a missing data problem. This PhD dissertation aims to mitigate these challenges and develop a practical room-level localization system at low deployment cost in a public wireless environment focusing on system architecture and methods. First, room-level localization is defined in terms of cell-based localization. By segmenting the floor plan into cells, training data collection is carried out by fusing RSS measurements taken within each cell by all contributed devices. A multivariate linear regression model is applied to calibrate the RSS measurements collected from different devices involved in the crowdsourced training phase. The conventional method of dealing with missing data is to set a low RSS value which will distort the RSS distribution and cause biased estimation. The Expectation-Maximization (EM) imputation method is used instead to estimate missing RSS values in the incomplete RSS measurements. Different features of the RSS spatial correlation for both fixed single location and across-cell measurements are studied. It is demonstrated that the RSS independence assumption is not valid in this context. We follow by using a high-dimensional probabilistic fingerprint for each cell, based on a multivariate Gaussian mixture model (MVGMM) to take account of spatial correlation of the signal strengths from multiple APs. The benefits of using information provided by invisible APs in differentiating between cells has been investigated, by incorporating a geometric distribution to provide a probability of existence of an AP that has not been seen in training. Finally, we design two frameworks based on hidden Markov model (HMM) and route…

Subjects/Keywords: WiFi localization; Hidden Markov Model; Probabilistic fingerprinting; Gaussian mixture model

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

APA (6^th Edition):

Li, Y. (2019). A probabilistic approach for Wi-Fi based indoor localization. (Doctoral Dissertation). University of Melbourne. Retrieved from http://hdl.handle.net/11343/234278

Chicago Manual of Style (16^th Edition):

Li, Yan. “A probabilistic approach for Wi-Fi based indoor localization.” 2019. Doctoral Dissertation, University of Melbourne. Accessed March 01, 2021. http://hdl.handle.net/11343/234278.

MLA Handbook (7^th Edition):

Li, Yan. “A probabilistic approach for Wi-Fi based indoor localization.” 2019. Web. 01 Mar 2021.

Vancouver:

Li Y. A probabilistic approach for Wi-Fi based indoor localization. [Internet] [Doctoral dissertation]. University of Melbourne; 2019. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/11343/234278.

Council of Science Editors:

Li Y. A probabilistic approach for Wi-Fi based indoor localization. [Doctoral Dissertation]. University of Melbourne; 2019. Available from: http://hdl.handle.net/11343/234278

University of Georgia

17. Wu, Yong. Modeling and searching for ncRNA secondary structure.

Degree: 2014, University of Georgia

URL: http://hdl.handle.net/10724/25717

► The discovery of functional non-coding RNAs (ncRNAs) has led to an increasing interest in efficient algorithms related to ncRNA secondary structure prediction and search for… (more)

Subjects/Keywords: ncRNA; sencodary structure; hidden Markov model; covariance model

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

APA (6^th Edition):

Wu, Y. (2014). Modeling and searching for ncRNA secondary structure. (Thesis). University of Georgia. Retrieved from http://hdl.handle.net/10724/25717

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

Chicago Manual of Style (16^th Edition):

Wu, Yong. “Modeling and searching for ncRNA secondary structure.” 2014. Thesis, University of Georgia. Accessed March 01, 2021. http://hdl.handle.net/10724/25717.

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

MLA Handbook (7^th Edition):

Wu, Yong. “Modeling and searching for ncRNA secondary structure.” 2014. Web. 01 Mar 2021.

Vancouver:

Wu Y. Modeling and searching for ncRNA secondary structure. [Internet] [Thesis]. University of Georgia; 2014. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/10724/25717.

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

Council of Science Editors:

Wu Y. Modeling and searching for ncRNA secondary structure. [Thesis]. University of Georgia; 2014. Available from: http://hdl.handle.net/10724/25717

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

University of Illinois – Chicago

18. Huang, Ziqian. Segmentation of Financial and Marketing Data: Mixture Logit model and Hidden Markov Model.

Degree: 2012, University of Illinois – Chicago

URL: http://hdl.handle.net/10027/9611

► Segmentation refers to the assignment of each consumer to a set of similar consumers. The formation of the sets and the assignments are done simultaneously… (more)

Subjects/Keywords: Segmentation; Finite Mixture Model; Mixture Logit Model; Hidden Markov Model; Quantitative Marketing Model

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APA (6^th Edition):

Huang, Z. (2012). Segmentation of Financial and Marketing Data: Mixture Logit model and Hidden Markov Model. (Thesis). University of Illinois – Chicago. Retrieved from http://hdl.handle.net/10027/9611

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

Chicago Manual of Style (16^th Edition):

Huang, Ziqian. “Segmentation of Financial and Marketing Data: Mixture Logit model and Hidden Markov Model.” 2012. Thesis, University of Illinois – Chicago. Accessed March 01, 2021. http://hdl.handle.net/10027/9611.

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

MLA Handbook (7^th Edition):

Huang, Ziqian. “Segmentation of Financial and Marketing Data: Mixture Logit model and Hidden Markov Model.” 2012. Web. 01 Mar 2021.

Vancouver:

Huang Z. Segmentation of Financial and Marketing Data: Mixture Logit model and Hidden Markov Model. [Internet] [Thesis]. University of Illinois – Chicago; 2012. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/10027/9611.

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

Council of Science Editors:

Huang Z. Segmentation of Financial and Marketing Data: Mixture Logit model and Hidden Markov Model. [Thesis]. University of Illinois – Chicago; 2012. Available from: http://hdl.handle.net/10027/9611

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

University of Illinois – Urbana-Champaign

19. Khosrowpour, Ardalan. Vision-based workface assessment using depth images for activity analysis of interior construction operations.

Degree: MS, 0106, 2014, University of Illinois – Urbana-Champaign

URL: http://hdl.handle.net/2142/46892

► Workface assessment –the process of determining the overall activity rates of onsite construction workers throughout a day– typically involves manual visual observations which are time-consuming… (more)

▼ Workface assessment –the process of determining the overall activity rates of onsite construction workers throughout a day– typically involves manual visual observations which are time-consuming and labor-intensive. To minimize subjectivity and the time required for conducting detailed assessments, and allowing managers to spend their time on the more important task of assessing and implementing improvements, we propose a new inexpensive vision-based method using RGB-D sensors that is applicable to interior construction operations. This is particularly a challenging task as construction activities have a large range of intra-class variability including varying sequences of body posture and time-spent on each individual activity. On the other hand, the state-of-the-art skeleton extraction algorithms from RGB-D sequences are not robust enough especially when workers interact with tools or self-occlude the camera’s field-of-view. Existing vision-based methods are also rather limited as they can primarily classify “atomic” activities from RGB-D sequences involving one worker conducting a single activity. To address these limitations, our proposed original method involves three main components: 1) an algorithm for detecting, tracking, and extracting body skeleton features from depth images; 2) A discriminative bag-of-poses activity classifier trained using multiple Support Vector Machines for classifying single visual activities from a given body skeleton sequence; and 3) a Hidden Markov model with a Kernel Density Estimation function to represent emission probabilities in form of a statistical distribution of single activity classifiers. For training and testing purposes, we also introduce a new dataset of eleven RGB-D sequences for interior drywall construction operations involving three actual construction workers conducting eight different activities in various interior locations. Our experimental results with an average accuracy of 76% on the testing dataset show the promise of vision-based methods using RGB-D sequences for facilitating the activity analysis workface assessment. Advisors/Committee Members: Golparvar-Fard, Mani (advisor).

Subjects/Keywords: Activity Analysis; Workface Assessment; RGB-D (RedGreenBlue-Depth) cameras; Hidden Markov ModelActivity analysis; Hidden Markov Model

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APA (6^th Edition):

Khosrowpour, A. (2014). Vision-based workface assessment using depth images for activity analysis of interior construction operations. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/46892

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

Chicago Manual of Style (16^th Edition):

Khosrowpour, Ardalan. “Vision-based workface assessment using depth images for activity analysis of interior construction operations.” 2014. Thesis, University of Illinois – Urbana-Champaign. Accessed March 01, 2021. http://hdl.handle.net/2142/46892.

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

MLA Handbook (7^th Edition):

Khosrowpour, Ardalan. “Vision-based workface assessment using depth images for activity analysis of interior construction operations.” 2014. Web. 01 Mar 2021.

Vancouver:

Khosrowpour A. Vision-based workface assessment using depth images for activity analysis of interior construction operations. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2014. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/2142/46892.

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

Council of Science Editors:

Khosrowpour A. Vision-based workface assessment using depth images for activity analysis of interior construction operations. [Thesis]. University of Illinois – Urbana-Champaign; 2014. Available from: http://hdl.handle.net/2142/46892

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

George Mason University

20. Nguyen, Thao Tran Nhu. Hidden Markov model based spectrum sensing for cognitive radio .

Degree: 2013, George Mason University

URL: http://hdl.handle.net/1920/8288

► Cognitive radio is an emerging technology for sensing and opportunistic spectrum access in wireless communication networks. It allows a secondary user to detect under-utilized spectrum… (more)

Subjects/Keywords: Engineering; Baum algorithm; Bivariate Markov chain; Cognitive radio; Hidden Markov model; Spectrum Sensing

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APA (6^th Edition):

Nguyen, T. T. N. (2013). Hidden Markov model based spectrum sensing for cognitive radio . (Thesis). George Mason University. Retrieved from http://hdl.handle.net/1920/8288

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

Chicago Manual of Style (16^th Edition):

Nguyen, Thao Tran Nhu. “Hidden Markov model based spectrum sensing for cognitive radio .” 2013. Thesis, George Mason University. Accessed March 01, 2021. http://hdl.handle.net/1920/8288.

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

MLA Handbook (7^th Edition):

Nguyen, Thao Tran Nhu. “Hidden Markov model based spectrum sensing for cognitive radio .” 2013. Web. 01 Mar 2021.

Vancouver:

Nguyen TTN. Hidden Markov model based spectrum sensing for cognitive radio . [Internet] [Thesis]. George Mason University; 2013. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/1920/8288.

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

Council of Science Editors:

Nguyen TTN. Hidden Markov model based spectrum sensing for cognitive radio . [Thesis]. George Mason University; 2013. Available from: http://hdl.handle.net/1920/8288

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

21. Le Corff, Sylvain. Estimations pour les modèles de Markov cachés et approximations particulaires : Application à la cartographie et à la localisation simultanées. : Inference in hidden Markov models and particle approximations - application to the simultaneous localization and mapping problem.

Degree: Docteur es, Signal et Images, 2012, Paris, ENST

URL: http://www.theses.fr/2012ENST0052

►

Dans cette thèse, nous nous intéressons à l'estimation de paramètres dans les chaînes de Markov cachées. Nous considérons tout d'abord le problème de l'estimation en… (more)

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Dans cette thèse, nous nous intéressons à l'estimation de paramètres dans les chaînes de Markov cachées. Nous considérons tout d'abord le problème de l'estimation en ligne (sans sauvegarde des observations) au sens du maximum de vraisemblance. Nous proposons une nouvelle méthode basée sur l'algorithme Expectation Maximization appelée Block Online Expectation Maximization (BOEM). Cet algorithme est défini pour des chaînes de Markov cachées à espace d'état et espace d'observations généraux. Dans le cas d'espaces d'états généraux, l'algorithme BOEM requiert l'introduction de méthodes de Monte Carlo séquentielles pour approcher des espérances sous des lois de lissage. La convergence de l'algorithme nécessite alors un contrôle de la norme Lp de l'erreur d'approximation Monte Carlo explicite en le nombre d'observations et de particules. Une seconde partie de cette thèse se consacre à l'obtention de tels contrôles pour plusieurs méthodes de Monte Carlo séquentielles. Nous étudions enfin des applications de l'algorithme BOEM à des problèmes de cartographie et de localisation simultanées. La dernière partie de cette thèse est relative à l'estimation non paramétrique dans les chaînes de Markov cachées. Le problème considéré est abordé dans un cadre précis. Nous supposons que (Xk) est une marche aléatoire dont la loi des incréments est connue à un facteur d'échelle a près. Nous supposons que, pour tout k, Yk est une observation de f(Xk) dans un bruit additif gaussien, où f est une fonction que nous cherchons à estimer. Nous établissons l'identifiabilité du modèle statistique et nous proposons une estimation de f et de a à partir de la vraisemblance par paires des observations.

This document is dedicated to inference problems in hidden Markov models. The first part is devoted to an online maximum likelihood estimation procedure which does not store the observations. We propose a new Expectation Maximization based method called the Block Online Expectation Maximization (BOEM) algorithm. This algorithm solves the online estimation problem for general hidden Markov models. In complex situations, it requires the introduction of Sequential Monte Carlo methods to approximate several expectations under the fixed interval smoothing distributions. The convergence of the algorithm is shown under the assumption that the Lp mean error due to the Monte Carlo approximation can be controlled explicitly in the number of observations and in the number of particles. Therefore, a second part of the document establishes such controls for several Sequential Monte Carlo algorithms. This BOEM algorithm is then used to solve the simultaneous localization and mapping problem in different frameworks. Finally, the last part of this thesis is dedicated to nonparametric estimation in hidden Markov models. It is assumed that the Markov chain (Xk) is a random walk lying in a compact set with increment distribution known up to a scaling factor a. At each time step k, Yk is a noisy observations of f(Xk) where f is an unknown function. We establish the…

Advisors/Committee Members: Moulines, Éric (thesis director), Fort, Gersende (thesis director).

Subjects/Keywords: Modèle de Markov caché; Estimation non-paramétrique; Hidden Markov model; Non-parametric estimation

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

APA (6^th Edition):

Le Corff, S. (2012). Estimations pour les modèles de Markov cachés et approximations particulaires : Application à la cartographie et à la localisation simultanées. : Inference in hidden Markov models and particle approximations - application to the simultaneous localization and mapping problem. (Doctoral Dissertation). Paris, ENST. Retrieved from http://www.theses.fr/2012ENST0052

Chicago Manual of Style (16^th Edition):

Le Corff, Sylvain. “Estimations pour les modèles de Markov cachés et approximations particulaires : Application à la cartographie et à la localisation simultanées. : Inference in hidden Markov models and particle approximations - application to the simultaneous localization and mapping problem.” 2012. Doctoral Dissertation, Paris, ENST. Accessed March 01, 2021. http://www.theses.fr/2012ENST0052.

MLA Handbook (7^th Edition):

Le Corff, Sylvain. “Estimations pour les modèles de Markov cachés et approximations particulaires : Application à la cartographie et à la localisation simultanées. : Inference in hidden Markov models and particle approximations - application to the simultaneous localization and mapping problem.” 2012. Web. 01 Mar 2021.

Vancouver:

Le Corff S. Estimations pour les modèles de Markov cachés et approximations particulaires : Application à la cartographie et à la localisation simultanées. : Inference in hidden Markov models and particle approximations - application to the simultaneous localization and mapping problem. [Internet] [Doctoral dissertation]. Paris, ENST; 2012. [cited 2021 Mar 01]. Available from: http://www.theses.fr/2012ENST0052.

Council of Science Editors:

Le Corff S. Estimations pour les modèles de Markov cachés et approximations particulaires : Application à la cartographie et à la localisation simultanées. : Inference in hidden Markov models and particle approximations - application to the simultaneous localization and mapping problem. [Doctoral Dissertation]. Paris, ENST; 2012. Available from: http://www.theses.fr/2012ENST0052

22. Khemiri, Houssemeddine. Approche générique appliquée à l'indexation audio par modélisation non supervisée : Unified data-driven approach for audio indexing, retrieval and recognition.

Degree: Docteur es, Signal et images, 2013, Paris, ENST

URL: http://www.theses.fr/2013ENST0055

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La quantité de données audio disponibles, telles que les enregistrements radio, la musique, les podcasts et les publicités est en augmentation constance. Par contre, il… (more)

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La quantité de données audio disponibles, telles que les enregistrements radio, la musique, les podcasts et les publicités est en augmentation constance. Par contre, il n'y a pas beaucoup d'outils de classification et d'indexation, qui permettent aux utilisateurs de naviguer et retrouver des documents audio. Dans ces systèmes, les données audio sont traitées différemment en fonction des applications. La diversité de ces techniques d'indexation rend inadéquat le traitement simultané de flux audio où différents types de contenu audio coexistent. Dans cette thèse, nous présentons nos travaux sur l'extension de l'approche ALISP, développé initialement pour la parole, comme une méthode générique pour l'indexation et l'identification audio. La particularité des outils ALISP est qu'aucune transcription textuelle ou annotation manuelle est nécessaire lors de l'étape d'apprentissage. Le principe de cet outil est de transformer les données audio en une séquence de symboles. Ces symboles peuvent être utilisés à des fins d'indexation. La principale contribution de cette thèse est l'exploitation de l'approche ALISP comme une méthode générique pour l'indexation audio. Ce système est composé de trois modules: acquisition et modélisation des unités ALISP d'une manière non supervisée, transcription ALISP des données audio et comparaison des symboles ALISP avec la technique BLAST et la distance de Levenshtein. Les évaluations du système proposé pour les différentes applications sont effectuées avec la base de données YACAST et avec d'autres corpus disponibles publiquement pour différentes tâche de l'indexation audio.

The amount of available audio data, such as broadcast news archives, radio recordings, music and songs collections, podcasts or various internet media is constantly increasing. Therefore many audio indexing techniques are proposed in order to help users to browse audio documents. Nevertheless, these methods are developed for a specific audio content which makes them unsuitable to simultaneously treat audio streams where different types of audio document coexist. In this thesis we report our recent efforts in extending the ALISP approach developed for speech as a generic method for audio indexing, retrieval and recognition. The particularity of ALISP tools is that no textual transcriptions are needed during the learning step. Any input speech data is transformed into a sequence of arbitrary symbols. These symbols can be used for indexing purposes. The main contribution of this thesis is the exploitation of the ALISP approach as a generic method for audio indexing. The proposed system consists of three steps; an unsupervised training to model and acquire the ALISP HMM models, ALISP segmentation of audio data using the ALISP HMM models and a comparison of ALISP symbols using the BLAST algorithm and Levenshtein distance. The evaluations of the proposed systems are done on the YACAST and other publicly available corpora for several tasks of audio indexing.

Advisors/Committee Members: Chollet, Gérard (thesis director), Petrovska-Delacrétaz, Dijana (thesis director).

Subjects/Keywords: Signal audio; Modèle de Markov caché; ALISP segmentation; Audio signal; Hidden Markov model; Segmentation ALISP

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

APA (6^th Edition):

Khemiri, H. (2013). Approche générique appliquée à l'indexation audio par modélisation non supervisée : Unified data-driven approach for audio indexing, retrieval and recognition. (Doctoral Dissertation). Paris, ENST. Retrieved from http://www.theses.fr/2013ENST0055

Chicago Manual of Style (16^th Edition):

Khemiri, Houssemeddine. “Approche générique appliquée à l'indexation audio par modélisation non supervisée : Unified data-driven approach for audio indexing, retrieval and recognition.” 2013. Doctoral Dissertation, Paris, ENST. Accessed March 01, 2021. http://www.theses.fr/2013ENST0055.

MLA Handbook (7^th Edition):

Khemiri, Houssemeddine. “Approche générique appliquée à l'indexation audio par modélisation non supervisée : Unified data-driven approach for audio indexing, retrieval and recognition.” 2013. Web. 01 Mar 2021.

Vancouver:

Khemiri H. Approche générique appliquée à l'indexation audio par modélisation non supervisée : Unified data-driven approach for audio indexing, retrieval and recognition. [Internet] [Doctoral dissertation]. Paris, ENST; 2013. [cited 2021 Mar 01]. Available from: http://www.theses.fr/2013ENST0055.

Council of Science Editors:

Khemiri H. Approche générique appliquée à l'indexation audio par modélisation non supervisée : Unified data-driven approach for audio indexing, retrieval and recognition. [Doctoral Dissertation]. Paris, ENST; 2013. Available from: http://www.theses.fr/2013ENST0055

University of Illinois – Urbana-Champaign

23. Baharian Khoshkhou, Golshid. Stochastic sequential assignment problem.

Degree: PhD, 0127, 2014, University of Illinois – Urbana-Champaign

URL: http://hdl.handle.net/2142/50503

► The stochastic sequential assignment problem (SSAP) studies the allocation of available distinct workers with deterministic values to sequentially-arriving tasks with stochastic parameters so as to… (more)

▼ The stochastic sequential assignment problem (SSAP) studies the allocation of available distinct workers with deterministic values to sequentially-arriving tasks with stochastic parameters so as to maximize the expected total reward obtained from the assignments. The difficulty and challenge in making the assignment decisions is that the assignments are performed in real-time; specifically, pairing a worker with a task is done without knowledge of future task values. This thesis focuses on studying practical variations and extensions of the SSAP, with the goal of eliminating restricting assumptions so that the problem setting converges to that of real-world problems. The existing SSAP literature considers a risk-neutral objective function, seeking an assignment policy to maximize the expected total reward; however, a risk-neutral objective function is not always desirable for the decision-maker since the probability distribution function (pdf) of the total reward might carry a high probability of low values. To take this issue into account, the first part of this dissertation studies the SSAP under a risk-sensitive objective function. Specifically, the assignments are performed so as to minimize the threshold probability, which is the probability of the total reward failing to achieve a specified target (threshold). A target-dependent Markov decision process (MDP) is solved, and sufficient conditions for the existence of a deterministic Markov optimal policy are provided. An approximate algorithm is presented, and convergence of the approximate value function to the optimal value function is established under mild conditions. The second part of this thesis analyzes the limiting behavior of the SSAP as the number of assignments approaches infinity. The optimal assignment policy for the basic SSAP has a threshold structure and involves computing a new set of breakpoints upon the arrival of each task, which is cumbersome for large-scale problems. To address this issue, the second part of this dissertation focuses on obtaining stationary (time-independent) optimal assignment policies that maximize the long-run expected reward per task and are much easier to perform in real-world problems. An exponential convergence rate is established for the convergence of the expected total reward per task to the optimal value as the number of tasks approaches infinity. The limiting behavior of the SSAP is studied in two different settings. The first setting assumes an independent and identically distributed (IID) sequence of arriving tasks with observable distribution functions, while the second problem considers the case where task distributions are unobservable and belong to a pool of feasible distributions. The next part of this dissertation basically brings the first two parts together, studying the limiting behavior of the target-dependent SSAP, where the goal is finding an assignment policy that minimizes the probability of the long-run reward per task failing to achieve a given target value. It is proven that the… Advisors/Committee Members: Jacobson, Sheldon H. (advisor), Chen, Xin (Committee Chair), Jacobson, Sheldon H. (committee member), Kiyavash, Negar (committee member), Shanbhag, Vinayak V. (committee member).

Subjects/Keywords: sequential assignment; Markov decision process; stationary policy; hidden Markov model; threshold criteria; risk measure

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

APA (6^th Edition):

Baharian Khoshkhou, G. (2014). Stochastic sequential assignment problem. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/50503

Chicago Manual of Style (16^th Edition):

Baharian Khoshkhou, Golshid. “Stochastic sequential assignment problem.” 2014. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed March 01, 2021. http://hdl.handle.net/2142/50503.

MLA Handbook (7^th Edition):

Baharian Khoshkhou, Golshid. “Stochastic sequential assignment problem.” 2014. Web. 01 Mar 2021.

Vancouver:

Baharian Khoshkhou G. Stochastic sequential assignment problem. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2014. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/2142/50503.

Council of Science Editors:

Baharian Khoshkhou G. Stochastic sequential assignment problem. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2014. Available from: http://hdl.handle.net/2142/50503

University of Waterloo

24. Raffa, Jesse Daniel. Multivariate Longitudinal Data Analysis with Mixed Effects Hidden Markov Models.

Degree: 2013, University of Waterloo

URL: http://hdl.handle.net/10012/7255

► Longitudinal studies, where data on study subjects are collected over time, is increasingly involving multivariate longitudinal responses. Frequently, the heterogeneity observed in a multivariate longitudinal… (more)

Subjects/Keywords: multivariate longitudinal data; hidden markov model; random effects; Markov chain monte carlo

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

APA (6^th Edition):

Raffa, J. D. (2013). Multivariate Longitudinal Data Analysis with Mixed Effects Hidden Markov Models. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/7255

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

Chicago Manual of Style (16^th Edition):

Raffa, Jesse Daniel. “Multivariate Longitudinal Data Analysis with Mixed Effects Hidden Markov Models.” 2013. Thesis, University of Waterloo. Accessed March 01, 2021. http://hdl.handle.net/10012/7255.

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

MLA Handbook (7^th Edition):

Raffa, Jesse Daniel. “Multivariate Longitudinal Data Analysis with Mixed Effects Hidden Markov Models.” 2013. Web. 01 Mar 2021.

Vancouver:

Raffa JD. Multivariate Longitudinal Data Analysis with Mixed Effects Hidden Markov Models. [Internet] [Thesis]. University of Waterloo; 2013. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/10012/7255.

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

Council of Science Editors:

Raffa JD. Multivariate Longitudinal Data Analysis with Mixed Effects Hidden Markov Models. [Thesis]. University of Waterloo; 2013. Available from: http://hdl.handle.net/10012/7255

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

San Jose State University

25. Chou, Peter. Dueling-HMM Analysis on Masquerade Detection.

Degree: MS, Computer Science, 2016, San Jose State University

URL: https://doi.org/10.31979/etd.497c-u3tp ; https://scholarworks.sjsu.edu/etd_projects/464

► Masquerade detection is the ability to detect attackers known as masqueraders that intrude on another user’s system and pose as legitimate users. Once a… (more)

Subjects/Keywords: masquarade intrusion detection Hidden Markov Model; Information Security

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APA (6^th Edition):

Chou, P. (2016). Dueling-HMM Analysis on Masquerade Detection. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.497c-u3tp ; https://scholarworks.sjsu.edu/etd_projects/464

Chicago Manual of Style (16^th Edition):

Chou, Peter. “Dueling-HMM Analysis on Masquerade Detection.” 2016. Masters Thesis, San Jose State University. Accessed March 01, 2021. https://doi.org/10.31979/etd.497c-u3tp ; https://scholarworks.sjsu.edu/etd_projects/464.

MLA Handbook (7^th Edition):

Chou, Peter. “Dueling-HMM Analysis on Masquerade Detection.” 2016. Web. 01 Mar 2021.

Vancouver:

Chou P. Dueling-HMM Analysis on Masquerade Detection. [Internet] [Masters thesis]. San Jose State University; 2016. [cited 2021 Mar 01]. Available from: https://doi.org/10.31979/etd.497c-u3tp ; https://scholarworks.sjsu.edu/etd_projects/464.

Council of Science Editors:

Chou P. Dueling-HMM Analysis on Masquerade Detection. [Masters Thesis]. San Jose State University; 2016. Available from: https://doi.org/10.31979/etd.497c-u3tp ; https://scholarworks.sjsu.edu/etd_projects/464

San Jose State University

26. Kicinski, Maciej. AB INITIO PROTEIN STRUCTURE PREDICTION ALGORITHMS.

Degree: MS, Computer Science, 2011, San Jose State University

URL: https://doi.org/10.31979/etd.dycd-k9fd ; https://scholarworks.sjsu.edu/etd_projects/165

► Genes that encode novel proteins are constantly being discovered and added to databases, but the speed with which their structures are being determined is… (more)

Subjects/Keywords: protein structure prediction hidden markov model; Bioinformatics; Other Computer Sciences

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APA (6^th Edition):

Kicinski, M. (2011). AB INITIO PROTEIN STRUCTURE PREDICTION ALGORITHMS. (Masters Thesis). San Jose State University. Retrieved from https://doi.org/10.31979/etd.dycd-k9fd ; https://scholarworks.sjsu.edu/etd_projects/165

Chicago Manual of Style (16^th Edition):

Kicinski, Maciej. “AB INITIO PROTEIN STRUCTURE PREDICTION ALGORITHMS.” 2011. Masters Thesis, San Jose State University. Accessed March 01, 2021. https://doi.org/10.31979/etd.dycd-k9fd ; https://scholarworks.sjsu.edu/etd_projects/165.

MLA Handbook (7^th Edition):

Kicinski, Maciej. “AB INITIO PROTEIN STRUCTURE PREDICTION ALGORITHMS.” 2011. Web. 01 Mar 2021.

Vancouver:

Kicinski M. AB INITIO PROTEIN STRUCTURE PREDICTION ALGORITHMS. [Internet] [Masters thesis]. San Jose State University; 2011. [cited 2021 Mar 01]. Available from: https://doi.org/10.31979/etd.dycd-k9fd ; https://scholarworks.sjsu.edu/etd_projects/165.

Council of Science Editors:

Kicinski M. AB INITIO PROTEIN STRUCTURE PREDICTION ALGORITHMS. [Masters Thesis]. San Jose State University; 2011. Available from: https://doi.org/10.31979/etd.dycd-k9fd ; https://scholarworks.sjsu.edu/etd_projects/165

University of Alberta

27. Hladky, Stephen Michael. Predicting opponent locations in first-person shooter video games.

Degree: MS, Department of Computing Science, 2009, University of Alberta

URL: https://era.library.ualberta.ca/files/5x21tg037

► Commercial video game developers constantly strive to create intelligent humanoid characters that are controlled by computers. To ensure computer opponents are challenging to human players,… (more)

Subjects/Keywords: opponent modelling; particle filter; hidden semi-Markov model; believability; video games

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

APA (6^th Edition):

Hladky, S. M. (2009). Predicting opponent locations in first-person shooter video games. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/5x21tg037

Chicago Manual of Style (16^th Edition):

Hladky, Stephen Michael. “Predicting opponent locations in first-person shooter video games.” 2009. Masters Thesis, University of Alberta. Accessed March 01, 2021. https://era.library.ualberta.ca/files/5x21tg037.

MLA Handbook (7^th Edition):

Hladky, Stephen Michael. “Predicting opponent locations in first-person shooter video games.” 2009. Web. 01 Mar 2021.

Vancouver:

Hladky SM. Predicting opponent locations in first-person shooter video games. [Internet] [Masters thesis]. University of Alberta; 2009. [cited 2021 Mar 01]. Available from: https://era.library.ualberta.ca/files/5x21tg037.

Council of Science Editors:

Hladky SM. Predicting opponent locations in first-person shooter video games. [Masters Thesis]. University of Alberta; 2009. Available from: https://era.library.ualberta.ca/files/5x21tg037

University of Illinois – Urbana-Champaign

28. Zhang, Susu. A multilevel logistic hidden Markov model for learning under cognitive diagnosis.

Degree: MS, Psychology, 2018, University of Illinois – Urbana-Champaign

URL: http://hdl.handle.net/2142/101112

► Students who wish to learn a specific skill have increasing access to a growing number of online courses and open-source educational repositories of instructional tools,… (more)

Subjects/Keywords: Hidden Markov Model; Cognitive Diagnostic Modeling; Learning; Multilevel Modeling

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

APA (6^th Edition):

Zhang, S. (2018). A multilevel logistic hidden Markov model for learning under cognitive diagnosis. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/101112

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

Chicago Manual of Style (16^th Edition):

Zhang, Susu. “A multilevel logistic hidden Markov model for learning under cognitive diagnosis.” 2018. Thesis, University of Illinois – Urbana-Champaign. Accessed March 01, 2021. http://hdl.handle.net/2142/101112.

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

MLA Handbook (7^th Edition):

Zhang, Susu. “A multilevel logistic hidden Markov model for learning under cognitive diagnosis.” 2018. Web. 01 Mar 2021.

Vancouver:

Zhang S. A multilevel logistic hidden Markov model for learning under cognitive diagnosis. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2018. [cited 2021 Mar 01]. Available from: http://hdl.handle.net/2142/101112.

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

Council of Science Editors:

Zhang S. A multilevel logistic hidden Markov model for learning under cognitive diagnosis. [Thesis]. University of Illinois – Urbana-Champaign; 2018. Available from: http://hdl.handle.net/2142/101112

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

Penn State University

29. Bardakci, Ibrahim Ekrem. Approximate Realization of Hidden Markov Models.

Degree: 2014, Penn State University

URL: https://submit-etda.libraries.psu.edu/catalog/23697

► The realization problem for hidden Markov models (HMMs) has been studied over years. However, it does not always have solution and requires the exact string… (more)

Subjects/Keywords: Hidden Markov Model; Approximate Realization; Hankel Matrix; Nuclear Norm

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APA (6^th Edition):

Bardakci, I. E. (2014). Approximate Realization of Hidden Markov Models. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/23697

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

Chicago Manual of Style (16^th Edition):

Bardakci, Ibrahim Ekrem. “Approximate Realization of Hidden Markov Models.” 2014. Thesis, Penn State University. Accessed March 01, 2021. https://submit-etda.libraries.psu.edu/catalog/23697.

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

MLA Handbook (7^th Edition):

Bardakci, Ibrahim Ekrem. “Approximate Realization of Hidden Markov Models.” 2014. Web. 01 Mar 2021.

Vancouver:

Bardakci IE. Approximate Realization of Hidden Markov Models. [Internet] [Thesis]. Penn State University; 2014. [cited 2021 Mar 01]. Available from: https://submit-etda.libraries.psu.edu/catalog/23697.

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

Council of Science Editors:

Bardakci IE. Approximate Realization of Hidden Markov Models. [Thesis]. Penn State University; 2014. Available from: https://submit-etda.libraries.psu.edu/catalog/23697

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

Penn State University

30. Bray, Brandon A. Dyadic Interaction Patterns During Infancy and Early Childhood.

Degree: 2017, Penn State University

URL: https://submit-etda.libraries.psu.edu/catalog/14805bab456

► Dyadic interaction patterns, the dynamic social interplay between caregiver and infant characterized by each partner’s response to the behavior of the other, are considered one… (more)

▼ Dyadic interaction patterns, the dynamic social interplay between caregiver and infant characterized by each partner’s response to the behavior of the other, are considered one of the foundational factors of infants’ emergent self-regulation (Beebe et al., 1992; Kopp, 1982; Schore, 1996). Theoretically, then, dyadic interaction patterns should change over time as infants develop regulatory autonomy and capabilities for mobility, social engagement, and independence (Kopp, 1982), and vary depending on caregivers’ interactive styles (Feldman, 2007). Although research has examined links between early dyadic interaction patterns, measured as dyadic synchrony between parents’ and infants’ behaviors, and later child outcomes, relatively little is known about the specific types of parents’ and infants’ behaviors that typically co-occur at different ages. To address this gap, the current study provided detailed descriptive data about dyadic interaction patterns across infancy and early toddlerhood for mother-child dyads. Following advances in time-series data analytic methods for modeling dyadic data (e.g., Stifter & Rovine, 2015), the current study used Hidden Markov Modeling (HMM; Visser & Speekenbrink, 2010) to identify patterns of moment-to-moment behaviors co-occurring between mothers and their children (latent dyadic states) and to compute probabilities of transitions among those states at three ages: 9-, 18-, and 27-months. The current study used microcoded observations of adoptive mothers’ and infants’ behaviors collected as part of the Early Growth and Development Study (Leve et al., 2013) during an observational Teaching Task at child ages 9-, 18-, and 27-months (N = 551). The Teaching Task elicits maternal support for infant autonomy and exploration, therefore relevant behaviors that were coded included, for example, maternal scaffolding, praise, and social bids, and child attention to task, compliance, and toy exploration. Separately at each age, HMM was used to compute the probabilities of all possible latent dyadic states (i.e., all possible co-occurring mother-child behaviors) and to determine the number of dyadic states that resulted in best model fit. In other words, HMM quantified specific patterns of dyadic interaction that were most likely to occur at 9-, 18-, and 27-months. Then, separately at each age, HMM was used to compute a set of transition probabilities (i.e., the probability of dyads’ moving from one latent state to any other latent state). Thus, HMM provided a rich description of the content of dyadic interactions (i.e., the most likely types of co-occurring behaviors) and the process of dyadic interactions (most likely patterns of movement among dyadic states) at each age. The dyadic interaction patterns at each age were discussed in terms of similarities and differences at the different ages. HMM can be used in future research to examine individual differences in dyadic interaction patterns, explore genetic and environmental contributions to the development of dyadic interaction patterns, and… Advisors/Committee Members: Ginger A Moore, Thesis Advisor/Co-Advisor, Pamela Marie Cole, Committee Member, Jenae Marie Neiderhiser, Committee Member.

Subjects/Keywords: dyadic interaction; parenting; dyadic regulation; Hidden Markov Model

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APA (6^th Edition):

Bray, B. A. (2017). Dyadic Interaction Patterns During Infancy and Early Childhood. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/14805bab456

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

Chicago Manual of Style (16^th Edition):

Bray, Brandon A. “Dyadic Interaction Patterns During Infancy and Early Childhood.” 2017. Thesis, Penn State University. Accessed March 01, 2021. https://submit-etda.libraries.psu.edu/catalog/14805bab456.

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

MLA Handbook (7^th Edition):

Bray, Brandon A. “Dyadic Interaction Patterns During Infancy and Early Childhood.” 2017. Web. 01 Mar 2021.

Vancouver:

Bray BA. Dyadic Interaction Patterns During Infancy and Early Childhood. [Internet] [Thesis]. Penn State University; 2017. [cited 2021 Mar 01]. Available from: https://submit-etda.libraries.psu.edu/catalog/14805bab456.

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

Council of Science Editors:

Bray BA. Dyadic Interaction Patterns During Infancy and Early Childhood. [Thesis]. Penn State University; 2017. Available from: https://submit-etda.libraries.psu.edu/catalog/14805bab456

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

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Open Access Theses and Dissertations