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University of Georgia
1.
Sebastian, Bram.
Computational prediction of chicken pre-microRNA.
Degree: MS, Poultry Science, 2007, University of Georgia
URL: http://purl.galileo.usg.edu/uga_etd/sebastian_bram_200712_ms 
► MicroRNAs (miRNAs) are a small single strand non-coding RNA with ~22 nucleotides (nts) which can regulate gene expression. MiRNAs are generated from a ~60-70 nts…
(more)
▼ MicroRNAs (miRNAs) are a small single strand non-coding RNA with ~22 nucleotides (nts) which can regulate gene expression. MiRNAs are generated from a ~60-70 nts long hairpin shapped pre-miRNA which is a product of the cleavage of primary miRNA. The slow pace of the identification of novel miRNA by laboratory experiment has raised the importance of computational method. Three major programs ProMir, ERPIN, and MiR-abela were tested for known chicken pre-miRNA. ProMir, ERPIN and MiR-abela detected 53%, 93% and 57% respectively where ERPIN only has 25% of the chicken miRNA classes available. Thus, novel computational approach miR-Explore is introduced which was demonstrated to have 89% sensitivity in identifying known chicken pre-miRNA.
Advisors/Committee Members: Samuel E. Aggrey.
Subjects/Keywords: computational prediction
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APA (6th Edition):
Sebastian, B. (2007). Computational prediction of chicken pre-microRNA. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/sebastian_bram_200712_ms
Chicago Manual of Style (16th Edition):
Sebastian, Bram. “Computational prediction of chicken pre-microRNA.” 2007. Masters Thesis, University of Georgia. Accessed February 23, 2020.
http://purl.galileo.usg.edu/uga_etd/sebastian_bram_200712_ms.
MLA Handbook (7th Edition):
Sebastian, Bram. “Computational prediction of chicken pre-microRNA.” 2007. Web. 23 Feb 2020.
Vancouver:
Sebastian B. Computational prediction of chicken pre-microRNA. [Internet] [Masters thesis]. University of Georgia; 2007. [cited 2020 Feb 23].
Available from: http://purl.galileo.usg.edu/uga_etd/sebastian_bram_200712_ms.
Council of Science Editors:
Sebastian B. Computational prediction of chicken pre-microRNA. [Masters Thesis]. University of Georgia; 2007. Available from: http://purl.galileo.usg.edu/uga_etd/sebastian_bram_200712_ms
University of Alberta
2.
Ghazimirsaied, Seyedahmad.
Extending HCCI Low Load Operation Using Chaos Prediction and
Feedback Control.
Degree: PhD, Department of Mechanical Engineering, 2012, University of Alberta
URL: https://era.library.ualberta.ca/files/4m90dv928
► Homogenous Charge Compression Ignition (HCCI) is a promising technology that offers high fuel economy and low oxides of nitrogen and particulate emission for automotive and…
(more)
▼ Homogenous Charge Compression Ignition (HCCI) is a
promising technology that offers high fuel economy and low oxides
of nitrogen and particulate emission for automotive and stationary
engines. A significant challenge with HCCI is the large number of
partial burn/misfire cycles within the lean operation and the
control of the combustion phasing. A detailed experimental and
modeling investigation into the patterns of HCCI ignition timing
and control based on deterministic structure of data points in HCCI
combustion to reduce the high cyclic variations for operating
conditions near misfire and to extend the HCCI operating range is
the focus of this thesis. Nonlinear dynamics and chaos theory
applied to a wide range of engine operating conditions show that
unstable operation of HCCI with higher cyclic variations with a
non-Gaussian distribution is observed near the partial burn and
misfire region of the engine. In order to predict and control the
ignition timing in the partial burn region of HCCI, the temporal
dynamics of cyclic variation in HCCI engine near misfire is
analyzed using chaotic theory methods. Closed loop ignition timing
control is used to reduce cyclic combustion variations for an
unstable operating range of the engine near misfire using fuel
octane as the control input.
Subjects/Keywords: prediction; hcci
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APA (6th Edition):
Ghazimirsaied, S. (2012). Extending HCCI Low Load Operation Using Chaos Prediction and
Feedback Control. (Doctoral Dissertation). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/4m90dv928
Chicago Manual of Style (16th Edition):
Ghazimirsaied, Seyedahmad. “Extending HCCI Low Load Operation Using Chaos Prediction and
Feedback Control.” 2012. Doctoral Dissertation, University of Alberta. Accessed February 23, 2020.
https://era.library.ualberta.ca/files/4m90dv928.
MLA Handbook (7th Edition):
Ghazimirsaied, Seyedahmad. “Extending HCCI Low Load Operation Using Chaos Prediction and
Feedback Control.” 2012. Web. 23 Feb 2020.
Vancouver:
Ghazimirsaied S. Extending HCCI Low Load Operation Using Chaos Prediction and
Feedback Control. [Internet] [Doctoral dissertation]. University of Alberta; 2012. [cited 2020 Feb 23].
Available from: https://era.library.ualberta.ca/files/4m90dv928.
Council of Science Editors:
Ghazimirsaied S. Extending HCCI Low Load Operation Using Chaos Prediction and
Feedback Control. [Doctoral Dissertation]. University of Alberta; 2012. Available from: https://era.library.ualberta.ca/files/4m90dv928
University of Johannesburg
3.
Erasmus, Adrian Dean.
A tracking theory of prediction.
Degree: 2015, University of Johannesburg
URL: http://hdl.handle.net/10210/14056
► M.A. (Philosophy)
The purpose of my project is to provide necessary and sufficient conditions for a prediction to be considered good. Alex Broadbent (2013) claims…
(more)
▼ M.A. (Philosophy)
The purpose of my project is to provide necessary and sufficient conditions for a prediction to be considered good. Alex Broadbent (2013) claims that a good prediction is a stable prediction, thereby providing an internalist account of judging predictions. In contrast, this project demonstrates that an externalist approach to identifying good predictions is not only possible but, on the proposed view, more reliable too. Robert Nozick’s notion of sensitivity provides a means of understanding what makes a good prediction. It is argued that a good prediction is a sensitive prediction; one where a prediction activity tracks the truth of the claims and assumptions used to produce prediction claims. To gauge whether a prediction activity tracks the truth it is suggested that we ask the following question of the prediction: if the claims and assumptions appealed to in the prediction activity were false, would the same prediction claims have been made if at all? If the prediction claims would have been made in spite of this, then the prediction is not sensitive. Otherwise, the prediction satisfies the following tracking condition for good prediction: in the closest possible world to our own where one or more of the claims and assumptions appealed to in the prediction activity are false the prediction claims would be different or not made at all.
Subjects/Keywords: Prediction (Logic)
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APA (6th Edition):
Erasmus, A. D. (2015). A tracking theory of prediction. (Thesis). University of Johannesburg. Retrieved from http://hdl.handle.net/10210/14056
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Erasmus, Adrian Dean. “A tracking theory of prediction.” 2015. Thesis, University of Johannesburg. Accessed February 23, 2020.
http://hdl.handle.net/10210/14056.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Erasmus, Adrian Dean. “A tracking theory of prediction.” 2015. Web. 23 Feb 2020.
Vancouver:
Erasmus AD. A tracking theory of prediction. [Internet] [Thesis]. University of Johannesburg; 2015. [cited 2020 Feb 23].
Available from: http://hdl.handle.net/10210/14056.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Erasmus AD. A tracking theory of prediction. [Thesis]. University of Johannesburg; 2015. Available from: http://hdl.handle.net/10210/14056
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
4.
park, ju-hwa.
The Psychological Reality of the Markov Property of Causal
Bayes Nets.
Degree: PhD, Cognitive Sciences, 2012, Brown University
URL: https://repository.library.brown.edu/studio/item/bdr:297597/
► Previous research has questioned the causal Bayes net formalism reporting the violation of the Markov principle which lies at the heart of the causal Bayes…
(more)
▼ Previous research has questioned the causal Bayes net
formalism reporting the violation of the Markov principle which
lies at the heart of the causal Bayes net formalism. Two sets of
studies attempted to test the current hypotheses about the
violation of the Markov principle. Of particular interest was
whether causal representation of causal learning is consistent with
that of causal
prediction. In contrast to the causal Bayes nets
view which assumes the consistency, I proposed an alternative
hypothesis called the different abstraction level hypothesis,
claiming that a mental representation of causal structure learning
is different from that of causal
prediction and the difference is
the source of the violation. To be specific, the mechanistic
knowledge is not a part of a mental causal model when we define an
event in question as a cause or an effect (structure learning) in
general, but it is a part of the mental model when we make causal
predictions. The first set (Experiments 1-4) examines the role of
mechanisms in causal predictions providing a pair of causal
statements which describe a common cause structure. The second set
of experiments (Experiments 5-7) gave participants causally
sufficient dependency information among three abstract sliders and
asked them to learn the causal relation, a common cause, a chain,
and a common effect structure. Overall, all seven experiments
showed that causal predictions were not just a matter of causal
structure. Rather, the results demonstrated that causal predictions
were mediated by mechanisms between a cause and effect. Critically,
when mechanisms were construed as the same, participants violated
the screening-off rule while they respected the screening off rule
when mechanisms were different. Despite the differences in
probability judgments, causal graphs that participants drew in both
conditions were not different (Experiment 5 and 7). Together, the
thesis effectively isolated under what condition adults violate or
respect the Markov principle enhancing the current understanding of
how mechanisms constraint causal predictions given a specific
causal structure.
Advisors/Committee Members: Sloman, Steven (Director), Sobel, David (Reader), Serre, Thomas (Reader).
Subjects/Keywords: causal prediction
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APA ·
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MLA ·
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Manager
APA (6th Edition):
park, j. (2012). The Psychological Reality of the Markov Property of Causal
Bayes Nets. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:297597/
Chicago Manual of Style (16th Edition):
park, ju-hwa. “The Psychological Reality of the Markov Property of Causal
Bayes Nets.” 2012. Doctoral Dissertation, Brown University. Accessed February 23, 2020.
https://repository.library.brown.edu/studio/item/bdr:297597/.
MLA Handbook (7th Edition):
park, ju-hwa. “The Psychological Reality of the Markov Property of Causal
Bayes Nets.” 2012. Web. 23 Feb 2020.
Vancouver:
park j. The Psychological Reality of the Markov Property of Causal
Bayes Nets. [Internet] [Doctoral dissertation]. Brown University; 2012. [cited 2020 Feb 23].
Available from: https://repository.library.brown.edu/studio/item/bdr:297597/.
Council of Science Editors:
park j. The Psychological Reality of the Markov Property of Causal
Bayes Nets. [Doctoral Dissertation]. Brown University; 2012. Available from: https://repository.library.brown.edu/studio/item/bdr:297597/
Vanderbilt University
5.
Boyles, Robert William.
Mechanical Design of an Instrumented Cane for Gait Prediction by Physical Therapists.
Degree: MS, Mechanical Engineering, 2015, Vanderbilt University
URL: http://etd.library.vanderbilt.edu/available/etd-11102015-164312/
;
► Many individuals at some point in their lives will utilize an assisted walking device to help them move around. Physical therapists use their experience to…
(more)
▼ Many individuals at some point in their lives will utilize an assisted walking device to help them move around. Physical therapists use their experience to assess a person's likelihood of experiencing a fall, as well as recommend types of these assisted devices that can help decrease this probability. This thesis presents the design of an instrumented offset-style walking cane to provide a quantitative measurement of an individual's walking ability to go along with other observation-based assessments. Through several sensors in the handle and base of the cane, force and inertial data can be captured to determine how an individual is gripping and bearing their weight on the device as they walk around. The goal of this work is to improve upon an earlier design by moving from a standard to an offset-style cane, as well as make the device more appealing for use in the lives of individuals outside of a clinical setting. This is accomplished by designing a subsystem that can help detect and alert users of potential obstacles in their current walking path, thus helping to decrease the likelihood of experiencing a fall.
Advisors/Committee Members: Nilanjan Sarkar (chair), Thomas Withrow (committee member), Pietro Valdastri (committee member), Michael de Riesthal (committee member).
Subjects/Keywords: gait prediction
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APA ·
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APA (6th Edition):
Boyles, R. W. (2015). Mechanical Design of an Instrumented Cane for Gait Prediction by Physical Therapists. (Masters Thesis). Vanderbilt University. Retrieved from http://etd.library.vanderbilt.edu/available/etd-11102015-164312/ ;
Chicago Manual of Style (16th Edition):
Boyles, Robert William. “Mechanical Design of an Instrumented Cane for Gait Prediction by Physical Therapists.” 2015. Masters Thesis, Vanderbilt University. Accessed February 23, 2020.
http://etd.library.vanderbilt.edu/available/etd-11102015-164312/ ;.
MLA Handbook (7th Edition):
Boyles, Robert William. “Mechanical Design of an Instrumented Cane for Gait Prediction by Physical Therapists.” 2015. Web. 23 Feb 2020.
Vancouver:
Boyles RW. Mechanical Design of an Instrumented Cane for Gait Prediction by Physical Therapists. [Internet] [Masters thesis]. Vanderbilt University; 2015. [cited 2020 Feb 23].
Available from: http://etd.library.vanderbilt.edu/available/etd-11102015-164312/ ;.
Council of Science Editors:
Boyles RW. Mechanical Design of an Instrumented Cane for Gait Prediction by Physical Therapists. [Masters Thesis]. Vanderbilt University; 2015. Available from: http://etd.library.vanderbilt.edu/available/etd-11102015-164312/ ;
Università della Svizzera italiana
6.
D'Ambros, Marco.
On the evolution of source code and software defects.
Degree: 2010, Università della Svizzera italiana
URL: http://doc.rero.ch/record/21151
► Software systems are subject to continuous changes to adapt to new and changing requirements.This phenomenon, known as software evolution, leads in the long term to…
(more)
▼ Software systems are
subject to continuous changes to
adapt to new and changing requirements.This phenomenon, known as
software evolution, leads in the long term to software aging: The
size and the complexity of systems increase, while their quality
decreases. In this context, it is no wonder that software
maintenance claims the most part of a software system's cost.The
analysis of software evolution helps practitioners deal with the
negative effects of software aging. With the advent of the Internet
and the consequent widespread adoption of distributed development
tools, such as software configuration management and issue tracking
systems, a vast amount of valuable information concerning software
evolution has become available. In the last two decades,
researchers have focused on mining and analyzing this data,
residing in various software repositories, to understand software
evolution and support maintenance activities. However, most
approaches target a specific maintenance task, and consider only
one of the several facets of software evolution. Such approaches,
and the infrastructures that implement them, cannot be extended to
address different maintenance problems. In this dissertation, we
propose an integrated view of software evolution that combines
different evolutionary aspects. Our thesis is that an integrated
and flexible approach supports an extensible set of software
maintenance activities. To this aim, we present a meta-model that
integrates two aspects of software evolution: source code and
software defects. We implemented our approach in a framework that,
by retrieving information from source code and defect repositories,
serves as a basis to create analysis techniques and tools. To show
the flexibility of our approach, we extended our meta-model and
framework with e-mail information extracted from development
mailing lists. To validate our thesis, we devised and evaluated, on
top of our approach, a number of novel analysis techniques that
achieve two goals: 1. Inferring the causes of problems in a
software system. We propose three retrospective analysis
techniques, based on interactive visualizations, to analyze the
evolution of source code, software defects, and their co-evolution.
These techniques support various maintenance tasks, such as system
restructuring, re- documentation, and identification of critical
software components. 2. Predicting the future of a software system.
We present four analysis techniques aimed at anticipating the
locations of future defects, and investigating the impact of
certain source code properties on the presence of defects. They
support two maintenance tasks: defect
prediction and software
quality analysis. By creating our framework and the mentioned
techniques on top of it, we provide evidence that an integrated
view of software evolution, combining source code and software
defects information, supports an extensible set of software
maintenance tasks.
Advisors/Committee Members: Michele (Dir.).
Subjects/Keywords: Defect prediction
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APA (6th Edition):
D'Ambros, M. (2010). On the evolution of source code and software defects. (Thesis). Università della Svizzera italiana. Retrieved from http://doc.rero.ch/record/21151
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
D'Ambros, Marco. “On the evolution of source code and software defects.” 2010. Thesis, Università della Svizzera italiana. Accessed February 23, 2020.
http://doc.rero.ch/record/21151.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
D'Ambros, Marco. “On the evolution of source code and software defects.” 2010. Web. 23 Feb 2020.
Vancouver:
D'Ambros M. On the evolution of source code and software defects. [Internet] [Thesis]. Università della Svizzera italiana; 2010. [cited 2020 Feb 23].
Available from: http://doc.rero.ch/record/21151.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
D'Ambros M. On the evolution of source code and software defects. [Thesis]. Università della Svizzera italiana; 2010. Available from: http://doc.rero.ch/record/21151
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Università della Svizzera italiana
7.
Verbosio, Fabio.
High performance selected inversion methods for sparse
matrices: direct and stochastic approaches to selected
inversion.
Degree: 2019, Università della Svizzera italiana
URL: http://doc.rero.ch/record/324252
► The explicit evaluation of selected entries of the inverse of a given sparse matrix is an important process in various application fields and is gaining…
(more)
▼ The explicit evaluation of selected entries of the
inverse of a given sparse matrix is an important process in various
application fields and is gaining visibility in recent years. While
a standard inversion process would require the computation of the
whole inverse who is, in general, a dense matrix, state-of-the-art
solvers perform a selected inversion process instead. Such approach
allows to extract specific entries of the inverse, e.g., the
diagonal, avoiding the standard inversion steps, reducing therefore
time and memory requirements. Despite the complexity reduction
already achieved, the natural direction for the development of the
selected inversion software is the parallelization and distribution
of the computation, exploiting multinode implementations of the
algorithms. In this work we introduce parallel, high performance
selected inversion algorithms suitable for both the computation and
estimation of the diagonal of the inverse of large, sparse
matrices. The first approach is built on top of a sparse
factorization method and a distributed computation of the
Schur-complement, and is specifically designed for the parallel
treatment of large, dense matrices including a sparse block. The
second is based on the stochastic estimation of the matrix diagonal
using a stencil-based, matrix-free Krylov subspace iteration. We
implement the two solvers and prove their excellent performance on
Cray supercomputers, focusing on both the multinode scalability and
the numerical accuracy. Finally, we include the solvers into two
distinct frameworks designed for the solution of selected inversion
problems in real-life applications. First, we present a parallel,
scalable framework for the log-likelihood maximization in genomic
prediction problems including marker by environment effects. Then,
we apply the matrix-free estimator to the treatment of large-scale
three-dimensional nanoelectronic device simulations with open
boundary conditions.
Advisors/Committee Members: Olaf (Dir.).
Subjects/Keywords: Genomic prediction
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APA ·
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Manager
APA (6th Edition):
Verbosio, F. (2019). High performance selected inversion methods for sparse
matrices: direct and stochastic approaches to selected
inversion. (Thesis). Università della Svizzera italiana. Retrieved from http://doc.rero.ch/record/324252
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Verbosio, Fabio. “High performance selected inversion methods for sparse
matrices: direct and stochastic approaches to selected
inversion.” 2019. Thesis, Università della Svizzera italiana. Accessed February 23, 2020.
http://doc.rero.ch/record/324252.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Verbosio, Fabio. “High performance selected inversion methods for sparse
matrices: direct and stochastic approaches to selected
inversion.” 2019. Web. 23 Feb 2020.
Vancouver:
Verbosio F. High performance selected inversion methods for sparse
matrices: direct and stochastic approaches to selected
inversion. [Internet] [Thesis]. Università della Svizzera italiana; 2019. [cited 2020 Feb 23].
Available from: http://doc.rero.ch/record/324252.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Verbosio F. High performance selected inversion methods for sparse
matrices: direct and stochastic approaches to selected
inversion. [Thesis]. Università della Svizzera italiana; 2019. Available from: http://doc.rero.ch/record/324252
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Texas Tech University
8.
Howard, Bradley A.
Digital human posture and motion prediction considering cognitive decision making.
Degree: PhD, Mechanical Engineering, 2018, Texas Tech University
URL: http://hdl.handle.net/2346/74379
► Every day, humans are presented with tasks that they complete with little effort of even consideration of the planning that goes into the movement. Movements…
(more)
▼ Every day, humans are presented with tasks that they complete with little effort of even consideration of the planning that goes into the movement. Movements such as reaching around an obstacle or manual manipulation tasks are completed with ease, even though the complexities and years of learned behavior are largely hidden from the person. Digital Human Modeling (DHM) and specifically optimization-based posture and motion
prediction methodologies have employed numerical methods in order to simulate/predict/analyze human movements. However, these movements are heavily constrained such that the panning of the motion/posture is explicitly provided in the formulation of the problem. This implies that for each posture or movement under analysis, a unique formulation that relies heavily on the experience of the researcher to provide these constraints is required. However, there has been much study within the realm of cognitive psychology focused on the reasoning or motivation behind the cognitive planning of movements. This presents an opportunity for DHM to adopt these methodologies in order to provide a more general or versatile posture and motion
prediction framework. This work presents the addition of cognitive principles into the optimization-based posture and motion
prediction formulations. It considers two specific scenarios. First, the simulation/
prediction of manual manipulation tasks are considered such that a single formulation can accomplish multiple tasks. It adopts a theory from cognitive psychology referred to as the end-state comfort effect in order to derive general constraints for the
prediction of the initial and final posture states that frame the movement related to the manual manipulation task. It considers multiple tasks from the literature that have been heavily studied through experimentation in order to evaluate the efficacy of the formulation. The results show strong correlation with observations reported in the literature. Second, the formulation of a collision avoidance algorithm considering perceived risk is offered. Humans tend to overestimate the risk associated with colliding with objects during movement, and therefore adopt suboptimal movements with respect to biomechanical cost. An experiment in order to evaluate human performance when avoiding obstacles in movement is designed. Using Bayesian inference, perceived risk, which is studied heavily in motor planning research, is modeled and minimized for use as a constraint in the larger human motion
prediction problem. The performance using the new formulation is compared to the observed performance from the experiment. The results show that the new formulation can account for the suboptimal behavior observed in real subjects while still optimizing biomechanical cost.
Advisors/Committee Members: Barhorst, Alan (committee member), Ekwaro-Osire, Stephen (committee member), Delucia, Patricia (committee member), Ren, Beibei (committee member), Yang, James (Committee Chair).
Subjects/Keywords: Digital Human Modeling; Posture Prediction; Motion Prediction
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Manager
APA (6th Edition):
Howard, B. A. (2018). Digital human posture and motion prediction considering cognitive decision making. (Doctoral Dissertation). Texas Tech University. Retrieved from http://hdl.handle.net/2346/74379
Chicago Manual of Style (16th Edition):
Howard, Bradley A. “Digital human posture and motion prediction considering cognitive decision making.” 2018. Doctoral Dissertation, Texas Tech University. Accessed February 23, 2020.
http://hdl.handle.net/2346/74379.
MLA Handbook (7th Edition):
Howard, Bradley A. “Digital human posture and motion prediction considering cognitive decision making.” 2018. Web. 23 Feb 2020.
Vancouver:
Howard BA. Digital human posture and motion prediction considering cognitive decision making. [Internet] [Doctoral dissertation]. Texas Tech University; 2018. [cited 2020 Feb 23].
Available from: http://hdl.handle.net/2346/74379.
Council of Science Editors:
Howard BA. Digital human posture and motion prediction considering cognitive decision making. [Doctoral Dissertation]. Texas Tech University; 2018. Available from: http://hdl.handle.net/2346/74379
NSYSU
9.
Tong, Ting-Chi.
Bandwidth Optimized Integrated Predictive Pixel Compensator of H.264 Decoder.
Degree: Master, Computer Science and Engineering, 2008, NSYSU
URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0807108-200335
► In this thesis, a high-efficient integrated pixel compensator architecture for the H.264/AVC standard has been proposed which can provide both inter and intra prediction functions…
(more)
▼ In this thesis, a high-efficient integrated pixel compensator architecture for the H.264/AVC standard has been proposed which can provide both inter and intra
prediction functions for luma and chroma components of pixels. By decomposing the algorithms used for both
prediction methods into small micro-operation steps, the fundamental arithmetic processing unit architecture capable for performing these operations can be first determined. Next, by considering the possible reference sample transfer issue, the overall compensator architecture will be built by using parallel processing units with some input and intermediate buffers which can be dynamically configured to perform proper computation schedules of different modes suitable for the nature input order of reference samples. The proposed design not only can avoid the additional data transposition buffer, but most importantly the data transfer time spent to fetch the reference samples can be overlapped with the data computation time. Since both arithmetic units and the intermediate data buffer for both inter and intra
prediction processes have been shared, our integrated design can achieve more than 30% reduction of gate count compared with the sum of the separate designs. Our design can also lead to more than 38% saving of gate count compared with the previous designs.
In addition to the data-path design, this thesis also addresses the memory bandwidth optimization issue which is especially important for the luma interpolation process. A new data-reuse buffer design based on a two-dimensional cache architecture to explore the possible data reuse among the inter and intra partitions will be proposed. The proposed design can be easily integrated with the H.264 interpolator to reduce the enormous demand of memory access. Our experimental results shows that our saving of memory bandwidth can be 20% more than what the best design can achieve by exploring the intra-partition data reuse only. Besides, our compensator can decode the videos up to HDTV resolution, and be applied for the dedicated H.264 hardware codec for various consumer devices.
Advisors/Committee Members: Chuen-Yau Chen (chair), Yun-Nan Chang (committee member), Shen-Fu Hsiao (chair).
Subjects/Keywords: Predictive Pixel Compensator; Inter Prediction; Intra Prediction
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APA (6th Edition):
Tong, T. (2008). Bandwidth Optimized Integrated Predictive Pixel Compensator of H.264 Decoder. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0807108-200335
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Tong, Ting-Chi. “Bandwidth Optimized Integrated Predictive Pixel Compensator of H.264 Decoder.” 2008. Thesis, NSYSU. Accessed February 23, 2020.
http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0807108-200335.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Tong, Ting-Chi. “Bandwidth Optimized Integrated Predictive Pixel Compensator of H.264 Decoder.” 2008. Web. 23 Feb 2020.
Vancouver:
Tong T. Bandwidth Optimized Integrated Predictive Pixel Compensator of H.264 Decoder. [Internet] [Thesis]. NSYSU; 2008. [cited 2020 Feb 23].
Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0807108-200335.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Tong T. Bandwidth Optimized Integrated Predictive Pixel Compensator of H.264 Decoder. [Thesis]. NSYSU; 2008. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0807108-200335
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
University of Georgia
10.
Ding, Liren.
GSP: glycosylation sites prediction.
Degree: MS, Computer Science, 2008, University of Georgia
URL: http://purl.galileo.usg.edu/uga_etd/ding_liren_200812_ms
► The attachment of the sugar N-acetylglucosamine (GlcNAc) to proteins occurs after the protein is folded into its 3D shape. The GlcNAc is transferred to the…
(more)
▼ The attachment of the sugar N-acetylglucosamine (GlcNAc) to proteins occurs after the protein is folded into its 3D shape. The GlcNAc is transferred to the surface of the protein by the enzyme O-GlcNAc transferase (OGTase). This process is called glycosylation. Glycosylation is a normal process in mammals, including humans. However, when it becomes hyperactivated, it leads to health problems, including type II diabetes. If we could identify the requirements for glycosylation, it is possible that a drug could be derived that could be used to mediate this interaction and so treat diseases such as diabetes. In this thesis, we propose a method which adapt RMSD algorithm to identify the structural features in the vicinity of serine or threonine residues, which are responsible for directing the enzyme to a particular position in the protein.
Advisors/Committee Members: Krzysztof J. Kochut.
Subjects/Keywords: Glycosylation site prediction
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APA (6th Edition):
Ding, L. (2008). GSP: glycosylation sites prediction. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/ding_liren_200812_ms
Chicago Manual of Style (16th Edition):
Ding, Liren. “GSP: glycosylation sites prediction.” 2008. Masters Thesis, University of Georgia. Accessed February 23, 2020.
http://purl.galileo.usg.edu/uga_etd/ding_liren_200812_ms.
MLA Handbook (7th Edition):
Ding, Liren. “GSP: glycosylation sites prediction.” 2008. Web. 23 Feb 2020.
Vancouver:
Ding L. GSP: glycosylation sites prediction. [Internet] [Masters thesis]. University of Georgia; 2008. [cited 2020 Feb 23].
Available from: http://purl.galileo.usg.edu/uga_etd/ding_liren_200812_ms.
Council of Science Editors:
Ding L. GSP: glycosylation sites prediction. [Masters Thesis]. University of Georgia; 2008. Available from: http://purl.galileo.usg.edu/uga_etd/ding_liren_200812_ms
University of Alberta
11.
Morrison, Kimberly H.
Factors that Influence Daily Human-Caused Forest Fires in
Alberta.
Degree: MS, Department of Renewable Resources, 2016, University of Alberta
URL: https://era.library.ualberta.ca/files/cxd07gs955
► Humans are the major cause of forest fires in the spring in Alberta, and have resulted in major property damage in both the Flat Top…
(more)
▼ Humans are the major cause of forest fires in the
spring in Alberta, and have resulted in major property damage in
both the Flat Top Complex fires in 2011 and the Fort McMurray fire
in 2016. Fire occurrence prediction (FOP) models can help predict
when and where fires can be expected in order to help fire managers
manage resources. In Alberta, these FOP models need to be improved,
especially in regards to spring fire starts and the timing of the
end of the spring fire season as most human-started forest fires in
Alberta occur in the spring. Candidate models were created to
explore which independent variables best predict human-caused fire
starts in Alberta. The independent variables are separated into
four groups: spatial distribution, Fire Weather Index System codes
and indices, human influences, and seasonality. Finally, several
model forms were explored to determine the best model, as
determined by best fit to the data and/or best predicted fire
occurrence. These were: Generalized Linear Model (GLM), Hurdle
Model and Zero-Inflated Model, each with a Poisson and negative
binomial link. A GLM with a negative binomial link and the
following variables predicted the number of human-caused fire
starts the best: FFMC, FWI, ECOREGION, FFMC X ECOREGON, and SEASON3
(a three level variable with a transition season between spring and
summer). This model had a RMSE of 0.697 when tested on a
bootstrapped set of test data. This model could be used as the
basis of future FOP model research in Alberta, and management of
wildfire fighting resources in conjunction with other fire activity
prediction methods.
Subjects/Keywords: prediction; wildfire; Alberta
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APA (6th Edition):
Morrison, K. H. (2016). Factors that Influence Daily Human-Caused Forest Fires in
Alberta. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/cxd07gs955
Chicago Manual of Style (16th Edition):
Morrison, Kimberly H. “Factors that Influence Daily Human-Caused Forest Fires in
Alberta.” 2016. Masters Thesis, University of Alberta. Accessed February 23, 2020.
https://era.library.ualberta.ca/files/cxd07gs955.
MLA Handbook (7th Edition):
Morrison, Kimberly H. “Factors that Influence Daily Human-Caused Forest Fires in
Alberta.” 2016. Web. 23 Feb 2020.
Vancouver:
Morrison KH. Factors that Influence Daily Human-Caused Forest Fires in
Alberta. [Internet] [Masters thesis]. University of Alberta; 2016. [cited 2020 Feb 23].
Available from: https://era.library.ualberta.ca/files/cxd07gs955.
Council of Science Editors:
Morrison KH. Factors that Influence Daily Human-Caused Forest Fires in
Alberta. [Masters Thesis]. University of Alberta; 2016. Available from: https://era.library.ualberta.ca/files/cxd07gs955
Texas A&M University
12.
Maruyama, Ashley Katsumi.
Prediction of automotive turbocharger nonlinear dynamic forced response with engine-induced housing excitations: comparisons to test data.
Degree: 2009, Texas A&M University
URL: http://hdl.handle.net/1969.1/ETD-TAMU-2546
► The trend in passenger vehicle internal combustion (IC) engines is to produce smaller, more fuel-efficient engines with power outputs comparable to those of large displacement…
(more)
▼ The trend in passenger vehicle internal combustion (IC) engines is to produce
smaller, more fuel-efficient engines with power outputs comparable to those of large
displacement engines. One way to accomplish this goal is through using turbochargers
(TCs) supported on semi-floating ring bearings (SFRBs). The thesis presents progress
on the nonlinear modeling of rotor-bearing systems (RBSs) by including engine-induced
TC housing excitations. Test data collected from an engine-mounted TC unit operating
to a top speed of 160 krpm (engine speed = 3,600 rpm) validates the nonlinear
predictions of shaft motion. Engine-induced housing excitations are input into the
nonlinear time transient rotor model as Fourier coefficients (and corresponding phase
angles) derived from measured TC center housing accelerations.
Analysis of recorded housing accelerations shows the IC engine induces TC
motions with a broad range of subsynchronous frequencies, rich in engine (e) superharmonics.
In particular, 2e and 4e vibration frequencies contribute greatly to housing
motion. Most importantly, the analysis reveals TC center and compressor housings do
not vibrate as a rigid body.
Eigenvalue analysis of the TC system evidences four damped natural frequencies
within the TC operating speed range. However, only the highest damped natural
frequency (first elastic mode, f = 2,025 Hz, ? = 0.14) is lightly-damped (critical speed =
150 krpm). Predicted linear and nonlinear imbalance response amplitudes increase with
TC shaft speed, with linear predictions agreeing with test data at high shaft speeds. The
differences between predictions and test data are attributed to an inaccurate knowledge
of the actual TC rotor imbalance distribution. For the nonlinear analysis, predicted shaft motions not accounting for housing
accelerations show the TC is stable (i.e. no subsynchronous whirl) at all but the lowest
shaft speeds (<70 krpm). However, predicted shaft motions accounting for housing
accelerations, as well as the test data, reveal TC motions rich in subsynchronous activity.
Clearly, engine-induced housing accelerations have a significant impact on TC shaft
motions. Predicted total shaft motions show good agreement with test data. Predicted
nonlinear subsynchronous amplitudes as well as peak shaft amplitudes also agree well
with test data. However, nonlinear predictions only show TC shaft vibrations attributed
to engine order frequencies below 6e, whereas test data evidences TC vibrations are due
to order frequencies greater than 6e. Overall, nonlinear predictions and test data
illustrate the importance of accounting for engine-induced housing vibrations in the
design and operation of TC systems. The good agreement between predictions and test
data serve to validate the rotor model. The tools developed will aid a TC manufacturer
in reducing development time and expenditures.
Advisors/Committee Members: San Andres, Luis A. (advisor), Childs, Dara W. (committee member), Holtzapple, Mark T. (committee member).
Subjects/Keywords: Turbocharger; Excitations; Prediction
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APA ·
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CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Maruyama, A. K. (2009). Prediction of automotive turbocharger nonlinear dynamic forced response with engine-induced housing excitations: comparisons to test data. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2546
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Maruyama, Ashley Katsumi. “Prediction of automotive turbocharger nonlinear dynamic forced response with engine-induced housing excitations: comparisons to test data.” 2009. Thesis, Texas A&M University. Accessed February 23, 2020.
http://hdl.handle.net/1969.1/ETD-TAMU-2546.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Maruyama, Ashley Katsumi. “Prediction of automotive turbocharger nonlinear dynamic forced response with engine-induced housing excitations: comparisons to test data.” 2009. Web. 23 Feb 2020.
Vancouver:
Maruyama AK. Prediction of automotive turbocharger nonlinear dynamic forced response with engine-induced housing excitations: comparisons to test data. [Internet] [Thesis]. Texas A&M University; 2009. [cited 2020 Feb 23].
Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2546.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Maruyama AK. Prediction of automotive turbocharger nonlinear dynamic forced response with engine-induced housing excitations: comparisons to test data. [Thesis]. Texas A&M University; 2009. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2546
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Texas A&M University
13.
Zhang, Jin.
Three essays on business failure: causality and prediction.
Degree: 2009, Texas A&M University
URL: http://hdl.handle.net/1969.1/ETD-TAMU-1032
► This dissertation investigates three issues on business failure causality and prediction. First, a nonlinear model for mathematical programming based discriminant analysis is studied. This study…
(more)
▼ This dissertation investigates three issues on business failure causality and
prediction. First, a nonlinear model for mathematical programming based discriminant analysis is studied. This study proposes a nonlinear model that builds on the existing linear and quadratic models and allows for a more flexible degree of nonlinearity through a set of power parameters. The proposed nonlinear model is solved using a genetic algorithm and is tested against linear and quadratic models using real financial data. The results show that each model is better in certain cases, but the nonlinear model turns out to be the best overall among the three. Better performance of this nonlinear model appears likely, but a more robust solver would be required. Second, the relationship between aggregate business failures and macroeconomic conditions is studied from a causality perspective. A structural Vector Autoregression (VAR) is used while incorporating the recently developed causal inference method Directed Acyclic Graph (DAG). Particularly, DAG is used to provide a contemporaneous causal structure and the VAR results are summarized using innovation accounting techniques. The results show that during the period from 1980 to 2004 in the U.S., aggregate business failures were influenced by interest rates, but overall these failures appear to be far more exogenous than was found previously. Third, the effect of incorporating macroeconomic variables into business failure
prediction models is investigated with a focus on the U.S. airline industry from 1995 to 2005. The attention is placed on
prediction accuracy, parameter stability, and the effect of particular macroeconomic variables. The results show that the stability of parameters in the
prediction model is improved when macro variables are added. In terms of
prediction accuracy, the model augmented with a macro variable performed better in a jackknife
prediction, but not in out-of-sample predictions. The macroeconomic variable found to be significant is the change of interest rate, which is probably related to the high level of leverage common in this particular industry. Also, the results demonstrate that a probability score can be used as a more informative evaluation measure than the current one based on cutoff probabilities.
Advisors/Committee Members: Leatham, David (advisor), Bessler, David (committee member), Tian, Guoqiang (committee member), Wu, Ximing (committee member).
Subjects/Keywords: Business failure; prediction
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APA ·
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Manager
APA (6th Edition):
Zhang, J. (2009). Three essays on business failure: causality and prediction. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-1032
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Zhang, Jin. “Three essays on business failure: causality and prediction.” 2009. Thesis, Texas A&M University. Accessed February 23, 2020.
http://hdl.handle.net/1969.1/ETD-TAMU-1032.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Zhang, Jin. “Three essays on business failure: causality and prediction.” 2009. Web. 23 Feb 2020.
Vancouver:
Zhang J. Three essays on business failure: causality and prediction. [Internet] [Thesis]. Texas A&M University; 2009. [cited 2020 Feb 23].
Available from: http://hdl.handle.net/1969.1/ETD-TAMU-1032.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Zhang J. Three essays on business failure: causality and prediction. [Thesis]. Texas A&M University; 2009. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-1032
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
University of Edinburgh
14.
Thompson, Douglas David.
Predicted risk of harm versus treatment benefit in large randomised controlled trials.
Degree: PhD, 2015, University of Edinburgh
URL: http://hdl.handle.net/1842/15843
► Most drugs come with unwanted, and perhaps harmful, side-effects. Depending on the size of the treatment benefit such harms may be tolerable. In acute stroke,…
(more)
▼ Most drugs come with unwanted, and perhaps harmful, side-effects. Depending on the size of the treatment benefit such harms may be tolerable. In acute stroke, treatment with aspirin and treatment with alteplase have both proven to be effective in reducing the odds of death or dependency in follow-up. However, in both cases, treated patients are subject to a greater risk of haemorrhage – a serious side-effect which could result in early death or greater dependency. Current treatment licenses are restricted so as to avoid treating those with certain traits or risk factors associated with bleeding. It is plausible however that a weighted combination of all these factors would achieve better discrimination than an informal assessment of each individual risk factor. This has the potential to help target treatment to those most likely to benefit and avoid treating those at greater risk from harm. This thesis will therefore: (i) explore how predictions of harm and benefit are currently made; (ii) seek to make improvements by adopting more rigorous methodological approaches in model development; and (iii) investigate how the predicted risk of harm and treatment benefit could be used to strike an optimal balance. Statistical prediction is not an exact science. Before clinical utility can be established it is essential that the performance of any prediction method be assessed at the point of application. A prediction method must attain certain desirable properties to be of any use, namely: good discrimination – which quantifies how well the prediction method can separate events from non-events; and good calibration – which measures how close the obtained predicted risks match the observed. A comparison of informal predictions made by clinicians and formal predictions made by clinical prediction models is presented using a prospective observational study of stroke patients seen at a single centre hospital in Edinburgh. These results suggest that both prediction methods achieve similar discrimination. A stratified framework based on predicted risks obtained from clinical prediction models is considered using data from large randomised trials. First, with three of the largest aspirin trials it is shown that there is no evidence to suggest that the benefit of aspirin on reducing six month death or dependency varies with the predicted risk of benefit or with the predicted risk of harm. Second, using data from the third International Stroke Trial (IST3) a similar question is posed of the effect of alteplase and the predicted risk of symptomatic intracranial haemorrhage. It was found that this relationship corresponded strongly with the relationship associated with stratifying patients according to their predicted risk of death or dependency in the absence of treatment: those at the highest predicted risk from either event stand to experience the largest absolute benefit from alteplase with no indication of harm amongst those at lower predicted risk. It is concluded that prediction models for harmful side-effects based on simple…
Subjects/Keywords: 616.8; prediction; stroke
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APA (6th Edition):
Thompson, D. D. (2015). Predicted risk of harm versus treatment benefit in large randomised controlled trials. (Doctoral Dissertation). University of Edinburgh. Retrieved from http://hdl.handle.net/1842/15843
Chicago Manual of Style (16th Edition):
Thompson, Douglas David. “Predicted risk of harm versus treatment benefit in large randomised controlled trials.” 2015. Doctoral Dissertation, University of Edinburgh. Accessed February 23, 2020.
http://hdl.handle.net/1842/15843.
MLA Handbook (7th Edition):
Thompson, Douglas David. “Predicted risk of harm versus treatment benefit in large randomised controlled trials.” 2015. Web. 23 Feb 2020.
Vancouver:
Thompson DD. Predicted risk of harm versus treatment benefit in large randomised controlled trials. [Internet] [Doctoral dissertation]. University of Edinburgh; 2015. [cited 2020 Feb 23].
Available from: http://hdl.handle.net/1842/15843.
Council of Science Editors:
Thompson DD. Predicted risk of harm versus treatment benefit in large randomised controlled trials. [Doctoral Dissertation]. University of Edinburgh; 2015. Available from: http://hdl.handle.net/1842/15843
15.
Erar Hood, Bahar.
Whole Genome Regression for Modeling Gene by Treatment
Interactions in Structured Populations.
Degree: Biostatistics, 2017, Brown University
URL: https://repository.library.brown.edu/studio/item/bdr:730659/
► A critical aspect of personalized medicine is the development of methods that evaluate genetic predisposition to respond to a treatment. Whole genome prediction (WGP) methods…
(more)
▼ A critical aspect of personalized medicine is the
development of methods that evaluate genetic predisposition to
respond to a treatment. Whole genome
prediction (WGP) methods have
been shown to improve predictive accuracy in genetically complex
traits. However, the methodology is not tailored for outcome
prediction in human randomized clinical trials (RCTs). In this
thesis, a novel statistical tool for predicting responsiveness to
treatment in RCTs is developed using whole genome regression
modeling of univariate continuous outcomes, categorical outcomes,
and multiple correlated outcomes. The proposed adaptive Bayesian
WGP method accounts for the underlying genetic heterogeneity
present in populations, which are often targeted in RCTs, using a
mixed model approach. Under this model, small effects regulated by
the treatment that would normally go undetected and disregarded are
captured by the unconstrained covariance structure of genetic
random effects. This flexible method improves existing methodology
by capturing the genetic correlation across treatment groups so
that the model can readily adapt to different levels and forms of
genetic structure present in the whole target population. This
method is extended to allow the modeling of categorical and
multivariate or longitudinal outcomes. Computational challenges
that arise in the implementation of this multi-group model are
addressed by employing an efficient estimation approach that allows
application to large datasets at a reasonable computational cost.
Predictive accuracy of adaptive BWGP is compared to other methods
using simulated phenotypes generated from real genotypes under
various scenarios. Results demonstrate that adaptive BWGP performs
better or at least as well as stratified methods, such as BayesC,
Bayesian Ridge Regression and Bayesian LASSO. The gain in
prediction accuracy is highest for moderately and highly heritable
traits under realistic effect regulation scenarios. Applications on
real RCT outcomes from the Look AHEAD trial are also used to
demonstrate how benefit from treatment can be predicted in practice
using adaptive BWGP.
Advisors/Committee Members: Papandonatos, George (Director), Istrail, Sorin (Reader), Wu, Zhijin (Reader), Bauer, Cici (Reader), McCaffery, Jeanne (Reader).
Subjects/Keywords: Whole genome prediction
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APA ·
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Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Erar Hood, B. (2017). Whole Genome Regression for Modeling Gene by Treatment
Interactions in Structured Populations. (Thesis). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:730659/
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Erar Hood, Bahar. “Whole Genome Regression for Modeling Gene by Treatment
Interactions in Structured Populations.” 2017. Thesis, Brown University. Accessed February 23, 2020.
https://repository.library.brown.edu/studio/item/bdr:730659/.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Erar Hood, Bahar. “Whole Genome Regression for Modeling Gene by Treatment
Interactions in Structured Populations.” 2017. Web. 23 Feb 2020.
Vancouver:
Erar Hood B. Whole Genome Regression for Modeling Gene by Treatment
Interactions in Structured Populations. [Internet] [Thesis]. Brown University; 2017. [cited 2020 Feb 23].
Available from: https://repository.library.brown.edu/studio/item/bdr:730659/.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Erar Hood B. Whole Genome Regression for Modeling Gene by Treatment
Interactions in Structured Populations. [Thesis]. Brown University; 2017. Available from: https://repository.library.brown.edu/studio/item/bdr:730659/
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
NSYSU
16.
Chang, Hsiao-Yen.
Refinement of All-atom Backbone Prediction of Proteins.
Degree: Master, Computer Science and Engineering, 2008, NSYSU
URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0820108-215243
► The all-atom protein backbone reconstruction problem (PBRP) is to rebuild the 3D coordinates of all atoms on the backbone which includes N, C, and O…
(more)
▼ The all-atom protein backbone reconstruction problem (PBRP) is to rebuild the 3D coordinates of all atoms on the backbone which includes N, C, and O atoms. In the previous work, we find that the
prediction accuracy of the 3D positions of the O atoms is not so good, compared with the other two atoms N and C. Thus, our goal is to refine the positions of the O atoms after the initial
prediction of N, C, and O atoms on the backbone has been done by the previous work. Based on the AMBER force field, we modify the energy function to a simplified one with the statistical data on the bond lengths and bond angles of the 21 distinct amino acids (including the nonstandard one). Then, we propose a two-phase refinement method (TPRM) to find the position of each O atom independently that optimizes the modified energy function. We perform our method on two test sets of proteins. The experimental results show that the reconstruction accuracy of our method is better than the previous ones. The solution of our method is also more stable than most of the previous work. Besides, our method runs much faster than the famous
prediction tool, SABBAC.
Advisors/Committee Members: Shih-Chung Chen (chair), Yow-Ling Shiue (chair), Chang-Biau Yang (committee member), Yue-Li Wang (chair), Chia-Ning Yang (chair).
Subjects/Keywords: backbone; prediction; protein
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APA (6th Edition):
Chang, H. (2008). Refinement of All-atom Backbone Prediction of Proteins. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0820108-215243
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Chang, Hsiao-Yen. “Refinement of All-atom Backbone Prediction of Proteins.” 2008. Thesis, NSYSU. Accessed February 23, 2020.
http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0820108-215243.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Chang, Hsiao-Yen. “Refinement of All-atom Backbone Prediction of Proteins.” 2008. Web. 23 Feb 2020.
Vancouver:
Chang H. Refinement of All-atom Backbone Prediction of Proteins. [Internet] [Thesis]. NSYSU; 2008. [cited 2020 Feb 23].
Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0820108-215243.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Chang H. Refinement of All-atom Backbone Prediction of Proteins. [Thesis]. NSYSU; 2008. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0820108-215243
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
University of Illinois – Chicago
17.
Ahmed, Madiha.
Tornado Path Prediction Using Data Driven Techniques.
Degree: 2018, University of Illinois – Chicago
URL: http://hdl.handle.net/10027/22977
► Each year around 800-1400 tornadoes occur in the United States. Although a very small number of these tornadoes result in injuries and fatalities, the destruction…
(more)
▼ Each year around 800-1400 tornadoes occur in the United States. Although a very small number of these tornadoes result in injuries and fatalities, the destruction caused by these events can be catastrophic. Despite having advance warning mechanisms and alert systems, the entire prevention of tornado casualties is still quite challenging (1). Studies have indicated that the rate of tornado-related fatalities and injuries are higher when effective warnings are not issued and people do not have access to suitable storm shelters (2). Tornado warnings are issued based upon the atmospheric disturbances being detected on Doppler radars. This system, however, provides the national average lead time of 13 minutes which is insufficient when families are expected to evacuate the areas under danger (3). The National Oceanic and Atmospheric Administration (NOAA) is currently working on developing a warn-on-forecast system to potentially improve the lead time for warnings before the formation of tornadoes (4). Upon studying numerous tornadoes, however, it became evident that the issues pertaining to tornado casualties could not simply be improved by extending warning times. The lack of communication between individuals and officials creates confusion about appropriate actions that individuals must take. Officials believe that by generating the warnings they have performed their job and the responsibility to take appropriate actions were then on the individuals. Individuals, on the other hand, seek to obtain more information regarding the arrival of a tornado, rather than simply relying on current warning mechanisms such as sirens and warnings broadcasted on television and radio. This communication dilemma results in preventable casualties (5).
For the present model, the tornado path was predicted for El-Reno, Oklahoma tornado that had occurred on May 31, 2013. For Model 1, the exact locations were determined by calculating the latitude and longitude points based upon the previously predicted locations. The data was divided into one and two-minute intervals. For Model 2, the same locations were predicted based on the previous original locations that would be provided by the radar in the actual scenario. Results showed that the distance between the predicted and the original locations were reduced significantly when the locations were predicted from the prior original locations in Model 2. Furthermore, the predicted path of the tornado was divided into different circles of diameter equal to the width of tornadoes which are usually around 0.17 miles to 0.28 miles (6). Results indicated that 90% of the locations were predicted successfully when the diameter/width of the tornado was around 0.3 miles.
To improve the communication gap between officials and individuals when providing warnings to people in a tornado’s path, the usage of UAVs (unmanned aerial vehicles) is proposed. UAVs equipped with cameras and Global Positioning Systems (GPS) can continuously map the land features of the area stricken by the disaster and provide updates…
Advisors/Committee Members: Houshang, Darabi (advisor), Williams, Quintin (committee member), Sharabiani, Ashkan (committee member), Houshang, Darabi (chair).
Subjects/Keywords: Tornado; Path Prediction
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APA (6th Edition):
Ahmed, M. (2018). Tornado Path Prediction Using Data Driven Techniques. (Thesis). University of Illinois – Chicago. Retrieved from http://hdl.handle.net/10027/22977
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Ahmed, Madiha. “Tornado Path Prediction Using Data Driven Techniques.” 2018. Thesis, University of Illinois – Chicago. Accessed February 23, 2020.
http://hdl.handle.net/10027/22977.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Ahmed, Madiha. “Tornado Path Prediction Using Data Driven Techniques.” 2018. Web. 23 Feb 2020.
Vancouver:
Ahmed M. Tornado Path Prediction Using Data Driven Techniques. [Internet] [Thesis]. University of Illinois – Chicago; 2018. [cited 2020 Feb 23].
Available from: http://hdl.handle.net/10027/22977.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Ahmed M. Tornado Path Prediction Using Data Driven Techniques. [Thesis]. University of Illinois – Chicago; 2018. Available from: http://hdl.handle.net/10027/22977
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Tulane University
18.
Hui Shao.
Updating Risk Engine for Diabetes Progression and Mortality in the United States: the Building, Relating, Acting, Validating for Outcomes (BRAVO) of Diabetes Risk Engine.
Degree: 2017, Tulane University
URL: https://digitallibrary.tulane.edu/islandora/object/tulane:75487
► Background The prediction of diabetes-related comorbidities and mortality over lifetime has significant clinical and policy implications. A prediction model can be used for economic evaluation…
(more)
▼ Background
The
prediction of diabetes-related comorbidities and mortality over lifetime has significant clinical and policy implications. A
prediction model can be used for economic evaluation on diabetes medications, comparative effectiveness review (CER) over different therapeutic plans, and estimation of the expected long-tern outcomes for different treatment goals (e.g., HbA1c). Most of the current diabetes
prediction models heavily relied on the UKPDS risk engine and Framingham equation, which used data from 1970s on European populations. These populations were significantly different from current US population in various ways including race, different health related concept, treatment algorithm, screening method of comorbidities and even definition of diabetes. In addition, UKPDS risk engine does not include impact of hypoglycemia, which emerged as an important issue in the management of diabetes due to its impact on quality of life, cardiovascular events and mortality. Furthermore, with the advancement of the medical technology and innovation in redefining treatment guideline during the last decades, the rates of cardiovascular events, all-cause mortality and event related mortality have fundamentally changed, especially the survival rates from CVD events has substantially increased. There is an urgent needs to develop a new risk engine that more adaptable to the current US population.
Objective
The objective of this study was to update risk engine using a cohort of patients with type 2 diabetes in the United States.
Methods
A total of 21 equations for forecasting diabetes-related microvascular and macrovascular events, hypoglycemia, mortality, and progression of diabetes risk factors were estimated using data on 10,251 patients from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial.
Left truncated proportional hazard model was applied to fit each event equation using diabetes duration as time index, and a variety of distributions including Weibull and Gompertz distribution were tested. 10-folds cross-validation or bootstrapped validation was applied to account for overfitting issue. Predicted cumulative incidence rates was plotted against the observed cumulative incidence to serve as internal validation to evaluate the
prediction accuracy of the BRAVO risk engine on ACCORD data. External validation was performed through applying the BRAVO risk engine onto population from other clinical trials.
Results
The BRAVO risk engine’s forecast felled within the 95% confidence interval for the occurrence of observed events at each time point through 40 years after diabetes onset. The model
prediction provides accurate
prediction according to the internal validation and external validation process, and good face validity on risk factors were established by endocrinologists. Severe hypoglycemia was found to be an important risk factor for congestive heart failure (CHF), myocardial infarction (MI), angina, blindness, and associated with increased mortality. Racial factor was included in more…
Advisors/Committee Members: Lizheng Shi (Thesis advisor), School of Public Health & Tropical Medicine Global Health Management and Policy (Degree granting institution).
Subjects/Keywords: Diabetes; Simulation; Prediction
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APA (6th Edition):
Shao, H. (2017). Updating Risk Engine for Diabetes Progression and Mortality in the United States: the Building, Relating, Acting, Validating for Outcomes (BRAVO) of Diabetes Risk Engine. (Thesis). Tulane University. Retrieved from https://digitallibrary.tulane.edu/islandora/object/tulane:75487
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Shao, Hui. “Updating Risk Engine for Diabetes Progression and Mortality in the United States: the Building, Relating, Acting, Validating for Outcomes (BRAVO) of Diabetes Risk Engine.” 2017. Thesis, Tulane University. Accessed February 23, 2020.
https://digitallibrary.tulane.edu/islandora/object/tulane:75487.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Shao, Hui. “Updating Risk Engine for Diabetes Progression and Mortality in the United States: the Building, Relating, Acting, Validating for Outcomes (BRAVO) of Diabetes Risk Engine.” 2017. Web. 23 Feb 2020.
Vancouver:
Shao H. Updating Risk Engine for Diabetes Progression and Mortality in the United States: the Building, Relating, Acting, Validating for Outcomes (BRAVO) of Diabetes Risk Engine. [Internet] [Thesis]. Tulane University; 2017. [cited 2020 Feb 23].
Available from: https://digitallibrary.tulane.edu/islandora/object/tulane:75487.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Shao H. Updating Risk Engine for Diabetes Progression and Mortality in the United States: the Building, Relating, Acting, Validating for Outcomes (BRAVO) of Diabetes Risk Engine. [Thesis]. Tulane University; 2017. Available from: https://digitallibrary.tulane.edu/islandora/object/tulane:75487
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Harvard University
19.
Davis, Joshua Seth.
Circulating microRNAs and Both Association With Methacholine PC20 and Prediction of Asthma Exacerbation in the Childhood Asthma Management Program (CAMP) Cohort.
Degree: Master of Medical Sciences, 2017, Harvard University
URL: http://nrs.harvard.edu/urn-3:HUL.InstRepos:41940985
► Background: Circulating microRNAs have shown promise both as a non-invasive biomarker and a predictor of disease activity. Prior asthma studies with clinical, biochemical, or genomic…
(more)
▼ Background: Circulating microRNAs have shown promise both as a non-invasive biomarker and a predictor of disease activity. Prior asthma studies with clinical, biochemical, or genomic tests have failed to demonstrate excellent
prediction of asthma exacerbation. This thesis hypothesizes that circulating miRNA would reveal: 1) candidate biomarkers related to airway hyperresponsiveness (AHR) and provide biologic insights into asthma epigenetic influences, 2) a panel of circulating miRNA in a pediatric asthma cohort or a combined microRNA-clinical asthma exacerbation score that may have superior predictive capability compared to the clinical asthma exacerbation score alone, and 3) the power of machine learning techniques such as backpropagation neural networks and XGBoost that may provide both improved
prediction of exacerbations or perhaps yield insight into complex non-linear behavior.
Methods: Serum samples were obtained at randomization for 160 children in the Childhood Asthma Management Program and were profiled using the TaqMan miRNA array set containing 754 miRNAs. For Aims 2 and 3, only 153 subjects had complete information on steroid bursts in the first year after randomization.
Aim 1: The association of the isolated miRNA with methacholine PC20 was assessed. Network and pathway analyses were performed. Functional validation of two significant miRNAs was performed in human airway smooth muscle cells (HASMs).
Aim 2: Dichotomized data for asthma exacerbation from the first year after randomization to the inhaled corticosteroid arm were used for binary logistic regression with microRNA cycle threshold and clinical exacerbation score. Ontology and pathway analyses were performed for significant miRNAs
Aim 3: Dichotomized data for asthma exacerbation as in Aim 2 was used for both backpropagation and resilient backpropagation neural networks and XGBoost with miRNA features selected by the Kruskal Test for binary and multiclass classification. Randomized hyperparameter optimization was used for all 3 algorithms. The neural network metric for classification was mean misclassification error. The XGBoost metric for classification was AUROC.
Results:
Aim 1: Of 155 well-detected circulating miRNAs, eight were significantly associated with PC20 with the strongest association with miR-296-5p. Pathway analysis revealed miR-16-5p as a network hub, and involvement of multiple miRNAs interacting with genes in the FoxO and Hippo signaling pathways by KEGG analysis. Functional validation of two miRNA in HASM showed effects on cell growth and diameter.
Aim 2: Of the 125 well-detected circulating miRNA, 12 had significant odd ratios for exacerbation with the most significant being miR-206. Each doubling of expression of the 12 miRNA resulted in between a 25-67% increase in risk of exacerbation. Stepwise logistic regression resulted in a three miRNA model that, when combined with the clinical score, demonstrated an AUROC of 0.81, which was superior to either the clinical model alone (AUROC 0.67) or miRNA model (AUROC 0.71). The…
Advisors/Committee Members: Tantisira, Kelan G. (committee member), Lu, Quan (committee member), Weiss, Scott T. (committee member).
Subjects/Keywords: asthma; microrna; prediction
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APA (6th Edition):
Davis, J. S. (2017). Circulating microRNAs and Both Association With Methacholine PC20 and Prediction of Asthma Exacerbation in the Childhood Asthma Management Program (CAMP) Cohort. (Masters Thesis). Harvard University. Retrieved from http://nrs.harvard.edu/urn-3:HUL.InstRepos:41940985
Chicago Manual of Style (16th Edition):
Davis, Joshua Seth. “Circulating microRNAs and Both Association With Methacholine PC20 and Prediction of Asthma Exacerbation in the Childhood Asthma Management Program (CAMP) Cohort.” 2017. Masters Thesis, Harvard University. Accessed February 23, 2020.
http://nrs.harvard.edu/urn-3:HUL.InstRepos:41940985.
MLA Handbook (7th Edition):
Davis, Joshua Seth. “Circulating microRNAs and Both Association With Methacholine PC20 and Prediction of Asthma Exacerbation in the Childhood Asthma Management Program (CAMP) Cohort.” 2017. Web. 23 Feb 2020.
Vancouver:
Davis JS. Circulating microRNAs and Both Association With Methacholine PC20 and Prediction of Asthma Exacerbation in the Childhood Asthma Management Program (CAMP) Cohort. [Internet] [Masters thesis]. Harvard University; 2017. [cited 2020 Feb 23].
Available from: http://nrs.harvard.edu/urn-3:HUL.InstRepos:41940985.
Council of Science Editors:
Davis JS. Circulating microRNAs and Both Association With Methacholine PC20 and Prediction of Asthma Exacerbation in the Childhood Asthma Management Program (CAMP) Cohort. [Masters Thesis]. Harvard University; 2017. Available from: http://nrs.harvard.edu/urn-3:HUL.InstRepos:41940985
20.
McElroy, Helen.
Risk factors for hip and groin injury in Gaelic football.
Degree: PhD, 2018, Ulster University
URL: https://ulster.pure.elsevier.com/en/studentTheses/3d8ddd4c-d303-4cfd-99d3-748566ce5ae0
;
https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.793691
► Introduction: Injury prevention and prediction in sports medicine is of huge importance to sports medicine professionals, coaches, and athletes as it improves performance and reduces…
(more)
▼ Introduction: Injury prevention and prediction in sports medicine is of huge importance to sports medicine professionals, coaches, and athletes as it improves performance and reduces time and money lost due to injury. Previously there has been no evidence- based prospective study in an elite population of gaelic footballers regarding the risk factors for hip and groin injury. Aims: To investigate the etiology of hip and groin injury in sport, through prospective examination of dynamic risk factor profile and injury incidence in GAA athletes. Methodology: The aims of this study were achieved through three strands of research: A systematic review, A nominal group and finally, a prospective study to determine how risk factor profile changes across a playing season, using a large cohort of GAA athletes and how this relates to injury incidence. Results: This thesis encompasses a systematic review highlighting the dearth of evidence regarding risk factor analysis in this population. This is followed by the establishment of a testing protocol using consensus methods and a large, prospective study examining these proposed risk factors at two time points across a playing season. The most notable findings of the prospective study are first, that previous injury continues to be a risk factor for subsequent injury. In addition to this, clinical measures offer little value in injury prediction, however pain provocation tests and patient reported outcome measures may be useful in the monitoring of 'at risk' athletes. Conclusion: This thesis suggests that continuous monitoring of a dynamic risk factor profile may be of more benefit than preseason or baseline testing. It is noted, however that it remains difficult to predict hip and groin injury at an individual level.
Subjects/Keywords: Hip; Groin; Prediction
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APA (6th Edition):
McElroy, H. (2018). Risk factors for hip and groin injury in Gaelic football. (Doctoral Dissertation). Ulster University. Retrieved from https://ulster.pure.elsevier.com/en/studentTheses/3d8ddd4c-d303-4cfd-99d3-748566ce5ae0 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.793691
Chicago Manual of Style (16th Edition):
McElroy, Helen. “Risk factors for hip and groin injury in Gaelic football.” 2018. Doctoral Dissertation, Ulster University. Accessed February 23, 2020.
https://ulster.pure.elsevier.com/en/studentTheses/3d8ddd4c-d303-4cfd-99d3-748566ce5ae0 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.793691.
MLA Handbook (7th Edition):
McElroy, Helen. “Risk factors for hip and groin injury in Gaelic football.” 2018. Web. 23 Feb 2020.
Vancouver:
McElroy H. Risk factors for hip and groin injury in Gaelic football. [Internet] [Doctoral dissertation]. Ulster University; 2018. [cited 2020 Feb 23].
Available from: https://ulster.pure.elsevier.com/en/studentTheses/3d8ddd4c-d303-4cfd-99d3-748566ce5ae0 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.793691.
Council of Science Editors:
McElroy H. Risk factors for hip and groin injury in Gaelic football. [Doctoral Dissertation]. Ulster University; 2018. Available from: https://ulster.pure.elsevier.com/en/studentTheses/3d8ddd4c-d303-4cfd-99d3-748566ce5ae0 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.793691
Rice University
21.
Cheng, Yushao.
Template-based Protein Structure Prediction and its Applications.
Degree: PhD, Engineering, 2013, Rice University
URL: http://hdl.handle.net/1911/76475
► Protein structure prediction, also called protein folding, is one of the most significant and challenging research areas in computational biophysics and structural bioinformatics. With the…
(more)
▼ Protein structure
prediction, also called protein folding, is one of the most significant and challenging research areas in computational biophysics and structural bioinformatics. With the rapid growth of PDB database, template-based modeling such as homology modeling and threading has become a popular method in protein structure
prediction. However, it is still hard to detect good templates when the sequence identity is below 30%. In chapter 1, a profile-profile alignment method is proposed. It uses evolutionary and structural profiles to detect homologs, and a z-score-based method to rank templates. The performance of this method in the critical assessment of protein structure
prediction experiments (CASP) was reported.
In chapter 2, p53 mutations are studied as an application of protein structure
prediction. The TP53 gene encodes a tumor suppressor protein called p53, and p53 mutations occur in about half of human cancers. Experimental studies showed that p53 cancer mutants can be reactivated by mutations on other sites. Machine learning technologies were used in this research. Multiple classifiers were built to predict whether a p53 mutant (single-point or multiple-point) would be transcriptionally active or not, based on features extracted from amino acid sequences and structures. The mutant structures were modeled using template-based protein structure
prediction. Theses features were selected and analyzed using different feature selection methods, and classifiers were built under different learning settings, such as supervised learning and semi-supervised learning. The performances of these classifiers were analyzed and compared.
Besides the study of single proteins, protein complexes in yeast are studied in chapter 3. Multiple classifiers were built to predict whether several given proteins can form a protein complex, based on features generated from amino acid sequences and protein-protein interaction network. Theses features were selected and analyzed using different feature selection methods. Also, these classifiers were built under different learning settings, such as supervised learning and active learning. The performances of these classifiers were analyzed and compared.
Advisors/Committee Members: Ma, Jianpeng (advisor), Diehl, Michael R. (committee member), Tao, Yizhi Jane (committee member).
Subjects/Keywords: Protein structure prediction
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APA (6th Edition):
Cheng, Y. (2013). Template-based Protein Structure Prediction and its Applications. (Doctoral Dissertation). Rice University. Retrieved from http://hdl.handle.net/1911/76475
Chicago Manual of Style (16th Edition):
Cheng, Yushao. “Template-based Protein Structure Prediction and its Applications.” 2013. Doctoral Dissertation, Rice University. Accessed February 23, 2020.
http://hdl.handle.net/1911/76475.
MLA Handbook (7th Edition):
Cheng, Yushao. “Template-based Protein Structure Prediction and its Applications.” 2013. Web. 23 Feb 2020.
Vancouver:
Cheng Y. Template-based Protein Structure Prediction and its Applications. [Internet] [Doctoral dissertation]. Rice University; 2013. [cited 2020 Feb 23].
Available from: http://hdl.handle.net/1911/76475.
Council of Science Editors:
Cheng Y. Template-based Protein Structure Prediction and its Applications. [Doctoral Dissertation]. Rice University; 2013. Available from: http://hdl.handle.net/1911/76475
University of Waterloo
22.
Chong, Michael.
Commit-Level vs. File-Level Vulnerability Prediction.
Degree: 2016, University of Waterloo
URL: http://hdl.handle.net/10012/10867
► Helping software development teams find and repair vulnerabilities before they are released and exploited can prevent costs due to loss of data, availability, and reputation.…
(more)
▼ Helping software development teams find and repair vulnerabilities before they are released and exploited can prevent costs due to loss of data, availability, and reputation. However, while general defect prediction models exist to help developers find bugs, vulnerability prediction models currently do not achieve high enough prediction performance to be used in industry [43]. Prediction of vulnerabilities in commits and files has been explored by previous work, and while commit-level prediction, at a finer granularity, may offer more useful results, there exists no clear comparison in predictive performance to justify this assumption.
To inform further research in vulnerability prediction, we compare commit and file-level prediction, across 7 projects, using 6 classifiers, for 8 different training dates. We evaluate the performance of each prediction model using ‘online prediction’ for ensuring an evaluation in line with practical usage of the prediction model. We evaluate each model using four different metrics, which we interpret as representing two different practical usage scenarios. We also perform an analysis of the data and techniques for evaluating prediction models. We find that despite achieving a low absolute prediction performance, file-level prediction generally tends to outperform commit-level prediction, but in a few outstanding cases, commit-level performs better.
Subjects/Keywords: Vulnerability Prediction; Commit-level Prediction; File-level Prediction
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APA (6th Edition):
Chong, M. (2016). Commit-Level vs. File-Level Vulnerability Prediction. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/10867
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Chong, Michael. “Commit-Level vs. File-Level Vulnerability Prediction.” 2016. Thesis, University of Waterloo. Accessed February 23, 2020.
http://hdl.handle.net/10012/10867.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Chong, Michael. “Commit-Level vs. File-Level Vulnerability Prediction.” 2016. Web. 23 Feb 2020.
Vancouver:
Chong M. Commit-Level vs. File-Level Vulnerability Prediction. [Internet] [Thesis]. University of Waterloo; 2016. [cited 2020 Feb 23].
Available from: http://hdl.handle.net/10012/10867.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Chong M. Commit-Level vs. File-Level Vulnerability Prediction. [Thesis]. University of Waterloo; 2016. Available from: http://hdl.handle.net/10012/10867
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
University of Texas – Austin
23.
Farooq, Muhammad Umar, active 2013.
Improving prediction accuracy of hard-to-predict branches using data value correlation.
Degree: PhD, Electrical and Computer Engineering, 2013, University of Texas – Austin
URL: http://hdl.handle.net/2152/23191
► Performance of modern pipelined processor depends on steady flow of useful instructions for processing. Branch instruction disrupts sequential flow of instructions by presenting multiple paths…
(more)
▼ Performance of modern pipelined processor depends on steady flow of useful instructions for processing. Branch instruction disrupts sequential flow of instructions by presenting multiple paths through which a program can proceed. By predicting branch
outcome early, branch predictors allow processor to continue fetching instructions from the predicted path. History-based dynamic branch predictors have shown to reach high
prediction accuracy, yet certain branch types continue to mispredict. These are multitarget indirect branches and data-dependent direct and indirect branches. These are hard-to-predict branches since their outcome do not always exhibit repeatable patterns.
This thesis describes branch
prediction schemes for improving
prediction accuracy of hard-to-predict branches using data value correlation. In these schemes, instead of relying on branch history information, compiler identifies program instructions whose output value strongly correlates with branch outcome. These correlated instructions are tracked at run-time, and their output is used for making branch predictions. Specifically, this thesis proposes following two branch
prediction schemes:
(i) Value-based BTB indexing (VBBI) is a low cost, compiler-guided scheme for
predicting multi-target indirect branches. For every indirect branch, compiler identifies an instruction whose output strongly correlates with targets taken by the indirect branch. At run-time, multiple branch targets are stored and subsequently accessed from BTB using index formed by hashing indirect branch PC with output of the correlated instruction.
(ii) Store-Load-Branch (SLB) predictor is a compiler-assisted branch
prediction scheme for data-dependent branches. Typically, data-dependent branches are associated with program data structures such as arrays, linked list etc., and follow store-load-branch
execution sequence. A set of memory locations is written at an earlier point in a program. Later, these locations are read, and used for evaluating branch condition. Branch outcome depends on values stored in data structure, which, normally do not have repeatable patterns. In SLB scheme, compiler identifies all program points where data structure associated with a data-dependent branch is modified. These
marked store instructions are tracked at run-time, and stored values are used for computing branch flags ahead of time. Later, when branch instruction is fetched, pre-computed flags are read, and used for making predictions.
This thesis introduces new branch
prediction schemes, describes hardware structures and compiler analysis for implementing these schemes, evaluates their performance
impact, and estimates their area, power and timing overhead.
Advisors/Committee Members: John, Lizy Kurian (advisor).
Subjects/Keywords: Branch prediction; Compiler guided; Indirect branch prediction; Value based branch prediction
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APA (6th Edition):
Farooq, Muhammad Umar, a. 2. (2013). Improving prediction accuracy of hard-to-predict branches using data value correlation. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/23191
Chicago Manual of Style (16th Edition):
Farooq, Muhammad Umar, active 2013. “Improving prediction accuracy of hard-to-predict branches using data value correlation.” 2013. Doctoral Dissertation, University of Texas – Austin. Accessed February 23, 2020.
http://hdl.handle.net/2152/23191.
MLA Handbook (7th Edition):
Farooq, Muhammad Umar, active 2013. “Improving prediction accuracy of hard-to-predict branches using data value correlation.” 2013. Web. 23 Feb 2020.
Vancouver:
Farooq, Muhammad Umar a2. Improving prediction accuracy of hard-to-predict branches using data value correlation. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2013. [cited 2020 Feb 23].
Available from: http://hdl.handle.net/2152/23191.
Council of Science Editors:
Farooq, Muhammad Umar a2. Improving prediction accuracy of hard-to-predict branches using data value correlation. [Doctoral Dissertation]. University of Texas – Austin; 2013. Available from: http://hdl.handle.net/2152/23191
Ohio University
24.
Khajotia, Burzin K.
CASE BASED REASONING – TAYLOR SERIES MODEL TO PREDICT
CORROSION RATE IN OIL AND GAS WELLS AND PIPELINES.
Degree: MS, Industrial and Manufacturing Systems Engineering
(Engineering), 2007, Ohio University
URL: http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1173828758
► Corrosion rate prediction involves developing a predictive model that provides a realistic estimate, utilizing common operational parameters, existing lab/field data, and theoretical models. The…
(more)
▼ Corrosion rate
prediction involves developing
a predictive model that provides a realistic estimate, utilizing
common operational parameters, existing lab/field data, and
theoretical models. The novel Case-based Reasoning – Taylor Series
(CBR-TS) model for corrosion
prediction developed in this thesis,
takes knowledge from existing field cases and uses CBR techniques
and Taylor series to predict corrosion rates for new fields having
similar parameters. The model predicts corrosion in three steps:
case search (selection of similar cases), case ranking (by using
Taylor series expansion), and case revision (by using correction
factor from mechanistic or semi-empirical model). The model is
implemented as a prototype and verified on a large hypothetical
case base and a small field database with real
data.
Advisors/Committee Members: Sormaz, Dusan (Advisor).
Subjects/Keywords: CBR; Case Based Prediction; Case Based Reasoning; Corrosion Prediction; Corrosion Rate Prediction
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APA (6th Edition):
Khajotia, B. K. (2007). CASE BASED REASONING – TAYLOR SERIES MODEL TO PREDICT
CORROSION RATE IN OIL AND GAS WELLS AND PIPELINES. (Masters Thesis). Ohio University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1173828758
Chicago Manual of Style (16th Edition):
Khajotia, Burzin K. “CASE BASED REASONING – TAYLOR SERIES MODEL TO PREDICT
CORROSION RATE IN OIL AND GAS WELLS AND PIPELINES.” 2007. Masters Thesis, Ohio University. Accessed February 23, 2020.
http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1173828758.
MLA Handbook (7th Edition):
Khajotia, Burzin K. “CASE BASED REASONING – TAYLOR SERIES MODEL TO PREDICT
CORROSION RATE IN OIL AND GAS WELLS AND PIPELINES.” 2007. Web. 23 Feb 2020.
Vancouver:
Khajotia BK. CASE BASED REASONING – TAYLOR SERIES MODEL TO PREDICT
CORROSION RATE IN OIL AND GAS WELLS AND PIPELINES. [Internet] [Masters thesis]. Ohio University; 2007. [cited 2020 Feb 23].
Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1173828758.
Council of Science Editors:
Khajotia BK. CASE BASED REASONING – TAYLOR SERIES MODEL TO PREDICT
CORROSION RATE IN OIL AND GAS WELLS AND PIPELINES. [Masters Thesis]. Ohio University; 2007. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1173828758
University of Southern California
25.
Dai, Yunyang.
Advanced intra prediction techniques for image and video
coding.
Degree: PhD, Electrical Engineering, 2010, University of Southern California
URL: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/352423/rec/543
► Intra prediction has been used in the H.264/AVC video coding standard to improve the coding efficiency of the intra frame. We present different intra prediction…
(more)
▼ Intra
prediction has been used in the H.264/AVC video
coding standard to improve the coding efficiency of the intra
frame. We present different intra
prediction techniques that
outperform the existing ones adopted by H.264/AVC and JPEG-LS in
this research: 1. joint block/line-based intra
prediction (JBLIP),
2. hierarchical (or multi-resolution) intra
prediction (HIP), and
3. context-based hierarchical intra
prediction (CHIP).; We consider
two image/video coding scenarios: lossy compression and lossless
compression. For lossy compression, we conduct a comprehensive
study and show that the existing line-based
prediction (LIP)
technique adopted by the H.264/AVC standard can only be effective
in smooth and simple edge regions. However, it is not as useful in
predicting complex regions that contain texture patterns. To
overcome this difficulty, we propose a JBLIP scheme with 2D
geometrical manipulation to improve coding efficiency. The
complexity of the JBLIP scheme is however quite hight due to the
need to search the best matched block for the
prediction purpose.
Thus, we propose a fast search algorithm to reduce the coding
complexity. The proposed JBLIP scheme outperforms the LIP scheme in
H.264/AVC by up to 1.68dB in the PSNR improvement at the same bit
rate.; Next, for lossless compression, we present an advanced intra
frame coding using a hierarchical (or multi-resolution) approach
called HIP. The objective is to support lossless image/video
compression with spatial scalability. We analyze the
characteristics of the underlying input signal characteristics and
previously proposed signal modeling algorithms and show that most
of the existing signal models cannot capture the dynamic signal
characteristics through one fixed model. Hence, we propose a
spatially scalable intra-
prediction scheme that decompose signals
according to their characteristics in the frequency domain. A
block-based linear combination with edge detection and training set
optimization is used to improve coding efficiency for complex
textured areas in the EL. It is shown by experimental results the
proposed lossless HIP scheme outperforms the lossless LIP scheme of
H.264/AVC and JPEG-LS by a bit rate saving of 10%.; Finally, we
analyze the inefficiency of the proposed lossless HIP scheme and
present an enhanced hierarchical intra
prediction coding called the
context-based hierarchical intra
prediction (CHIP). To save bits
for the coding of modes, we propose a mode estimation scheme. To
improve
prediction accuracy, we employ the principal components
analysis (PCA) to extract dominant features from the coarse
representation of the base layer. The extracted features are
clustered using a k-means clustering algorithm. Then, the
context-based interlayer
prediction (CIP) scheme is used to select
the best
prediction candidate without any side information. To
enhance coding efficiency furthermore, an adaptive precoding
process is performed by analyzing the characteristics of the
prediction residual signal and a more accurate approach is proposed
to estimate…
Advisors/Committee Members: Kuo, C.-C. Jay (Committee Chair), Ortega, Antonio (Committee Member), Chang, Tu-Nan (Committee Member).
Subjects/Keywords: block-based intra prediction; intra prediction; linear combination prediction; lossless image compression; signal decorrelation
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APA (6th Edition):
Dai, Y. (2010). Advanced intra prediction techniques for image and video
coding. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/352423/rec/543
Chicago Manual of Style (16th Edition):
Dai, Yunyang. “Advanced intra prediction techniques for image and video
coding.” 2010. Doctoral Dissertation, University of Southern California. Accessed February 23, 2020.
http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/352423/rec/543.
MLA Handbook (7th Edition):
Dai, Yunyang. “Advanced intra prediction techniques for image and video
coding.” 2010. Web. 23 Feb 2020.
Vancouver:
Dai Y. Advanced intra prediction techniques for image and video
coding. [Internet] [Doctoral dissertation]. University of Southern California; 2010. [cited 2020 Feb 23].
Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/352423/rec/543.
Council of Science Editors:
Dai Y. Advanced intra prediction techniques for image and video
coding. [Doctoral Dissertation]. University of Southern California; 2010. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/352423/rec/543
Vanderbilt University
26.
Fischer, Axel Walter.
In silico prediction of protein structures and ensembles.
Degree: PhD, Chemistry, 2018, Vanderbilt University
URL: http://etd.library.vanderbilt.edu//available/etd-01132018-113518/
;
► Determination of a proteinâs structural equilibrium constitution remains a challenge. Experimental techniques like X-ray crystallography or nuclear magnetic resonance spectroscopy either are only able to…
(more)
▼ Determination of a proteinâs structural equilibrium constitution remains a challenge. Experimental techniques like X-ray crystallography or nuclear magnetic resonance spectroscopy either are only able to determine single snapshots of the protein or are not applicable due to the protein's size or dynamics. Orthogonal techniques like electron paramagnetic resonance (EPR) spectroscopy are able to capture all significant populations of the
protein but the obtainable data are typically too sparse to unambiguously determine a structural ensemble. Computational methods on the other hand, suffer from necessary simplifications of the structure sampling and free energy evaluation. In order to solve these existing problems, I developed a computational
prediction pipeline for protein structures and ensembles that supports incorporation of limited experimental data from EPR spectroscopy and chemical cross-linking. The pipeline encompasses coarse-grained Monte Carlo Metropolis sampling using BCL::Fold, high-resolution refinement using Rosetta, and stability evaluations using molecular dynamics simulations. Novel methods were developed to incorporate the experimental data into the pipeline.
Both types of experimental data significantly improved the average accuracy of the sampled models as well as the discrimination between accurate and inaccurate models. In addition, a novel loop sampling algorithm consisting of conformation hashing and cyclic coordinate descent was developed. The algorithm is substantially faster than other available algorithms and samples the conformation of the proteinâs major population in 94 % of all cases. The developed methods were applied to determine the structure and dynamics of the Bcl-2-associated X protein (BAX), exotoxin U (ExoU), and the efflux-multidrug resistance protein (EmrE) in conjunction with structural data obtained through EPR spectroscopy.
Advisors/Committee Members: Jens Meiler (chair), Carlos F. Lopez (committee member), Terry P. Lybrand (committee member), Hassane S. Mchaourab (committee member), Michael P. Stone (committee member).
Subjects/Keywords: de novo prediction; emre; protein modeling; epr; loop modeling; protein ensemble prediction; protein structure prediction
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Manager
APA (6th Edition):
Fischer, A. W. (2018). In silico prediction of protein structures and ensembles. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://etd.library.vanderbilt.edu//available/etd-01132018-113518/ ;
Chicago Manual of Style (16th Edition):
Fischer, Axel Walter. “In silico prediction of protein structures and ensembles.” 2018. Doctoral Dissertation, Vanderbilt University. Accessed February 23, 2020.
http://etd.library.vanderbilt.edu//available/etd-01132018-113518/ ;.
MLA Handbook (7th Edition):
Fischer, Axel Walter. “In silico prediction of protein structures and ensembles.” 2018. Web. 23 Feb 2020.
Vancouver:
Fischer AW. In silico prediction of protein structures and ensembles. [Internet] [Doctoral dissertation]. Vanderbilt University; 2018. [cited 2020 Feb 23].
Available from: http://etd.library.vanderbilt.edu//available/etd-01132018-113518/ ;.
Council of Science Editors:
Fischer AW. In silico prediction of protein structures and ensembles. [Doctoral Dissertation]. Vanderbilt University; 2018. Available from: http://etd.library.vanderbilt.edu//available/etd-01132018-113518/ ;
Virginia Tech
27.
Burbey, Ingrid.
Predicting Future Locations and Arrival Times of Individuals.
Degree: PhD, Electrical and Computer Engineering, 2011, Virginia Tech
URL: http://hdl.handle.net/10919/27551
► This work has two objectives: a) to predict people's future locations, and b) to predict when they will be at given locations. Current location-based applications…
(more)
▼ This work has two objectives: a) to predict people's future locations, and b) to predict when they will be at given locations. Current location-based applications react to the user's current location. The progression from location-awareness to location-
prediction can enable the next generation of proactive, context-predicting applications.
Existing location-
prediction algorithms predict someone's next location. In contrast, this dissertation predicts someone's future locations. Existing algorithms use a sequence of locations and predict the next location in the sequence. This dissertation incorporates temporal information as timestamps in order to predict someone's location at any time in the future. Sequence predictors based on Markov models have been shown to be effective predictors of someone's next location. This dissertation applies a Markov model to two-dimensional, timestamped location information to predict future locations.
This dissertation also predicts when someone will be at a given location. These predictions can support presence or understanding co-workers’ routines. Predicting the times that someone is going to be at a given location is a very different and more difficult problem than predicting where someone will be at a given time. A location-
prediction application may predict one or two key locations for a given time, while there could be hundreds of correct predictions for times of the day that someone will be in a given location. The approach used in this dissertation, a heuristic model loosely based on Market Basket Analysis, is the first to predict when someone will arrive at any given location.
The models are applied to sparse, WiFi mobility data collected on PDAs given to 275 college freshmen. The location-
prediction model predicts future locations with 78-91% accuracy. The temporal-
prediction model achieves 33-39% accuracy. If a tolerance of plus/minus twenty minutes is allowed, the
prediction rates rise to 77%-91%.
This dissertation shows the characteristics of the timestamped, location data which lead to the highest number of correct predictions. The best data cover large portions of the day, with less than three locations for any given timestamp.
Advisors/Committee Members: Martin, Thomas L. (committeechair), Tront, Joseph G. (committee member), Pérez-Quiñones, Manuel A. (committee member), Jones, Mark T. (committee member), Midkiff, Scott F. (committee member).
Subjects/Keywords: Location Awareness; Context Prediction; Location Prediction; Time-of-Arrival Prediction; Context Awareness
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Manager
APA (6th Edition):
Burbey, I. (2011). Predicting Future Locations and Arrival Times of Individuals. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/27551
Chicago Manual of Style (16th Edition):
Burbey, Ingrid. “Predicting Future Locations and Arrival Times of Individuals.” 2011. Doctoral Dissertation, Virginia Tech. Accessed February 23, 2020.
http://hdl.handle.net/10919/27551.
MLA Handbook (7th Edition):
Burbey, Ingrid. “Predicting Future Locations and Arrival Times of Individuals.” 2011. Web. 23 Feb 2020.
Vancouver:
Burbey I. Predicting Future Locations and Arrival Times of Individuals. [Internet] [Doctoral dissertation]. Virginia Tech; 2011. [cited 2020 Feb 23].
Available from: http://hdl.handle.net/10919/27551.
Council of Science Editors:
Burbey I. Predicting Future Locations and Arrival Times of Individuals. [Doctoral Dissertation]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/27551
Royal Holloway, University of London
28.
Petej, Ivan.
Small and large scale probabilistic classifiers with guarantees of validity.
Degree: PhD, 2018, Royal Holloway, University of London
URL: https://pure.royalholloway.ac.uk/portal/en/publications/small-and-large-scale-probabilistic-classifiers-with-guarantees-of-validity(0b4f2ee3-8a2c-4ace-815f-440de3af6858).html
;
https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.792821
► This thesis addresses and expands research in probabilistic prediction with a particular emphasis on generating forecasts which are well calibrated. Chapter 1 describes standard techniques…
(more)
▼ This thesis addresses and expands research in probabilistic prediction with a particular emphasis on generating forecasts which are well calibrated. Chapter 1 describes standard techniques in machine learning and outlines two methods - conformal prediction and Venn prediction - both which serve as important building blocks for the remainder of the results in this thesis. Chapter 2 introduces the field of probabilistic machine learning and highlights some of the advantages and challenges of the methods developed to date. Chapter 3 proposes a new method of probabilistic prediction which is based on conformal prediction - a machine learning method for generating prediction sets that are guaranteed to have a specified coverage probability. The method is applied to the standard USPS data set with encouraging results. Chapter 4 focuses on the study of Venn prediction, concentrating on binary prediction problems. Venn predictors produce probability-type predictions for the labels of test objects which are guaranteed to be well calibrated under the standard assumption that the observations are generated independently from the same distribution. A new class of Venn predictors is introduced, called Venn-Abers predictors, which are based on the idea of isotonic regression. Promising empirical results are demonstrated both for Venn-Abers predictors and for their more computationally efficient simplified version. Chapter 5 studies theoretically and empirically a method of turning machine learning algorithms into probabilistic predictors that, as the Venn-Abers predictors described in the preceding chapter, automatically enjoy a property of validity (perfect calibration) but are computationally more efficient. The price to pay for perfect calibration is that these probabilistic predictors produce imprecise probabilities. When these imprecise probabilities are merged into precise probabilities, the resulting predictors, while losing the theoretical property of perfect calibration, are shown to be consistently more accurate than the existing methods in empirical studies.
Subjects/Keywords: Venn machine; reliable probabilistic prediction; additional information; transfer; Conformal Prediction; Probabilistic prediction; Class membership probability
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to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Petej, I. (2018). Small and large scale probabilistic classifiers with guarantees of validity. (Doctoral Dissertation). Royal Holloway, University of London. Retrieved from https://pure.royalholloway.ac.uk/portal/en/publications/small-and-large-scale-probabilistic-classifiers-with-guarantees-of-validity(0b4f2ee3-8a2c-4ace-815f-440de3af6858).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.792821
Chicago Manual of Style (16th Edition):
Petej, Ivan. “Small and large scale probabilistic classifiers with guarantees of validity.” 2018. Doctoral Dissertation, Royal Holloway, University of London. Accessed February 23, 2020.
https://pure.royalholloway.ac.uk/portal/en/publications/small-and-large-scale-probabilistic-classifiers-with-guarantees-of-validity(0b4f2ee3-8a2c-4ace-815f-440de3af6858).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.792821.
MLA Handbook (7th Edition):
Petej, Ivan. “Small and large scale probabilistic classifiers with guarantees of validity.” 2018. Web. 23 Feb 2020.
Vancouver:
Petej I. Small and large scale probabilistic classifiers with guarantees of validity. [Internet] [Doctoral dissertation]. Royal Holloway, University of London; 2018. [cited 2020 Feb 23].
Available from: https://pure.royalholloway.ac.uk/portal/en/publications/small-and-large-scale-probabilistic-classifiers-with-guarantees-of-validity(0b4f2ee3-8a2c-4ace-815f-440de3af6858).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.792821.
Council of Science Editors:
Petej I. Small and large scale probabilistic classifiers with guarantees of validity. [Doctoral Dissertation]. Royal Holloway, University of London; 2018. Available from: https://pure.royalholloway.ac.uk/portal/en/publications/small-and-large-scale-probabilistic-classifiers-with-guarantees-of-validity(0b4f2ee3-8a2c-4ace-815f-440de3af6858).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.792821
The Ohio State University
29.
Schenck, Edward Allen.
A study of the independent effect of cue redundancy upon the
human inference process in tasks of varying predictablility
.
Degree: PhD, Graduate School, 1968, The Ohio State University
URL: http://rave.ohiolink.edu/etdc/view?acc_num=osu1486647766580641
Subjects/Keywords: Psychology; Prediction
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APA ·
Chicago ·
MLA ·
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CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Schenck, E. A. (1968). A study of the independent effect of cue redundancy upon the
human inference process in tasks of varying predictablility
. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1486647766580641
Chicago Manual of Style (16th Edition):
Schenck, Edward Allen. “A study of the independent effect of cue redundancy upon the
human inference process in tasks of varying predictablility
.” 1968. Doctoral Dissertation, The Ohio State University. Accessed February 23, 2020.
http://rave.ohiolink.edu/etdc/view?acc_num=osu1486647766580641.
MLA Handbook (7th Edition):
Schenck, Edward Allen. “A study of the independent effect of cue redundancy upon the
human inference process in tasks of varying predictablility
.” 1968. Web. 23 Feb 2020.
Vancouver:
Schenck EA. A study of the independent effect of cue redundancy upon the
human inference process in tasks of varying predictablility
. [Internet] [Doctoral dissertation]. The Ohio State University; 1968. [cited 2020 Feb 23].
Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1486647766580641.
Council of Science Editors:
Schenck EA. A study of the independent effect of cue redundancy upon the
human inference process in tasks of varying predictablility
. [Doctoral Dissertation]. The Ohio State University; 1968. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1486647766580641
The Ohio State University
30.
Hutchins, Charles Willis.
A new approach to the construction of a prediction battery
.
Degree: PhD, Graduate School, 1970, The Ohio State University
URL: http://rave.ohiolink.edu/etdc/view?acc_num=osu1486655760439104
Subjects/Keywords: Psychology; Prediction
Record Details
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APA ·
Chicago ·
MLA ·
Vancouver ·
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Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Hutchins, C. W. (1970). A new approach to the construction of a prediction battery
. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1486655760439104
Chicago Manual of Style (16th Edition):
Hutchins, Charles Willis. “A new approach to the construction of a prediction battery
.” 1970. Doctoral Dissertation, The Ohio State University. Accessed February 23, 2020.
http://rave.ohiolink.edu/etdc/view?acc_num=osu1486655760439104.
MLA Handbook (7th Edition):
Hutchins, Charles Willis. “A new approach to the construction of a prediction battery
.” 1970. Web. 23 Feb 2020.
Vancouver:
Hutchins CW. A new approach to the construction of a prediction battery
. [Internet] [Doctoral dissertation]. The Ohio State University; 1970. [cited 2020 Feb 23].
Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1486655760439104.
Council of Science Editors:
Hutchins CW. A new approach to the construction of a prediction battery
. [Doctoral Dissertation]. The Ohio State University; 1970. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1486655760439104
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Open Access Theses and Dissertations