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Contributions to Ensembles of Models for Predictive Toxicology Applications. On the Representation, Comparison and Combination of Models in Ensembles.Makhtar, Mokhairi January 2012 (has links)
The increasing variety of data mining tools offers a large palette
of types and representation formats for predictive models. Managing
the models then becomes a big challenge, as well as reusing the
models and keeping the consistency of model and data repositories.
Sustainable access and quality assessment of these models become
limited to researchers. The approach for the Data and Model Governance
(DMG) makes easier to process and support complex solutions.
In this thesis, contributions are proposed towards ensembles
of models with a focus on model representation, comparison and
usage.
Predictive Toxicology was chosen as an application field to demonstrate
the proposed approach to represent predictive models linked
to data for DMG. Further analysing methods such as predictive models
comparison and predictive models combination for reusing the
models from a collection of models were studied. Thus in this thesis,
an original structure of the pool of models was proposed to
represent predictive toxicology models called Predictive Toxicology
Markup Language (PTML). PTML offers a representation scheme for
predictive toxicology data and models generated by data mining tools.
In this research, the proposed representation offers possibilities
to compare models and select the relevant models based on different
performance measures using proposed similarity measuring techniques.
The relevant models were selected using a proposed cost
function which is a composite of performance measures such as
Accuracy (Acc), False Negative Rate (FNR) and False Positive Rate
(FPR). The cost function will ensure that only quality models be
selected as the candidate models for an ensemble.
The proposed algorithm for optimisation and combination of Acc,
FNR and FPR of ensemble models using double fault measure as
the diversity measure improves Acc between 0.01 to 0.30 for all toxicology
data sets compared to other ensemble methods such as Bagging,
Stacking, Bayes and Boosting. The highest improvements for
Acc were for data sets Bee (0.30), Oral Quail (0.13) and Daphnia
(0.10). A small improvement (of about 0.01) in Acc was achieved
for Dietary Quail and Trout. Important results by combining all
the three performance measures are also related to reducing the
distance between FNR and FPR for Bee, Daphnia, Oral Quail and
Trout data sets for about 0.17 to 0.28. For Dietary Quail data set
the improvement was about 0.01 though, but this data set is well
known as a difficult learning exercise. For five UCI data sets tested,
similar results were achieved with Acc improvement between 0.10 to
0.11, closing more the gaps between FNR and FPR.
As a conclusion, the results show that by combining performance
measures (Acc, FNR and FPR), as proposed within this thesis, the
Acc increased and the distance between FNR and FPR decreased.
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MODEL-BASED DEFORMABLE REGISTRATION OF MRI BREAST IMAGES WITH ENHANCED FEATURE SELECTIONEmami Abarghouei, Shadi 11 1900 (has links)
This thesis is concerned with model-based non-rigid registration of single-modality magnetic resonance images of compressed and uncompressed breast tissue in breast cancer diagnostic/interventional imaging.
First, a volumetric registration algorithm is developed which solves the registration as a state estimation problem. Using a static deformation model. To reduce computations, the similarity measure is calculated at some specific points called control points. These control points can be from a low resolution image grid or any irregular image grid.
Our numerical analysis has shown that control points placed in the area without much information; i.e with small or no changes in image intensity, yield negligible deformation. Therefore, the selection of the control points can significantly impact the accuracy and computation complexity of the registration algorithms. An extension of the speeded up robust features (SURF) to 3D is proposed for enhanced selection of the control points in deformable image registration. The impact of this new control point selection method on the performance of the registration algorithm is analyzed by comparing it to the case where regular grid control points are used. The results show that the number of control points could be reduced by a factor of ten with new selection methodology without sacrificing performance.
Second image registration method is proposed in which, based on a segmented pre-operative image, a deformation model of the breast tissue is developed and discretized in the spatial domain using the method of finite elements. The compression of the preoperative image is modeled by applying smooth forces on the surface of the breast where compression plates are placed. Image registration is accomplished by formulating and solving an optimization problem. The cost function is a similarity measure between the deformed preoperative image and intra-operative image computed at some control point and the decision variables are the tissue interaction forces. / Thesis / Master of Applied Science (MASc)
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A Response Selection Model for Choice Reaction TimeTindall, Albert Douglas 10 1900 (has links)
<p> The binary choice Fast Guess Model of Ollman and Yellott was generalized to a multiple choice model and six subjects were run in a choice reaction time task to test the model.
Stimulus set sizes of two, four and six were used and response accuracy and speed motivation was manipulated through specific instructions which were changed from trial to trial. Three
different motivational instructions were used. In all cases, subjects were to respond with maximum accuracy but were also told on each trial to either disregard the duration of their
response, respond within 440 milliseconds or respond within 300 milliseconds.</p> <p> The generalized Fast Guess Model was rejected because response time parameters of the SCR state were found to change across response accuracy-speed motivation instructions and across
stimulus set sizes. Implications of these results for other classes of models were also discussed.</p> / Thesis / Doctor of Philosophy (PhD)
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A Hybrid Cost Model for Evaluating Query Execution PlansWang, Ning 22 January 2024 (has links)
Query optimization aims to select a query execution plan among all query paths for a given query. The query optimization of traditional relational database management systems (RDBMSs) relies on estimating the cost of the alternative query plans in the query plan search space provided by a cost model. The classic cost model (CCM) may lead the optimizer to choose query plans with poor execution time due to inaccurate cardinality estimations and simplifying assumptions. A learned cost model (LCM) based on machine learning does not rely on such estimations and learns the cost from runtime. While learned cost models are shown to improve the average performance, they may not guarantee that optimal performance will be consistently achieved. In addition, the query plans generated using the LCM may not necessarily outperform the query plans generated with the CCM. This thesis proposes a hybrid approach to solve this problem by striking a balance between the LCM and the CCM. The hybrid model uses the LCM when it is expected to be reliable in selecting a good plan and falls back to the CCM otherwise. The evaluation results of the hybrid model demonstrate promising performance, indicating potential for successful use in future applications.
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Study of the Lightning Protection Zone of the Franklin RodSong, Yang 07 August 2004 (has links)
The protection zone of the Franklin Rod is widely used in practice due to its effectiveness and the wide usage. The theories are based on the mathematical approaches, regardless of physical inherence of lightning strokes. The study of this thesis is based on computer analysis of the field distribution in pre-breakdown stage, laboratory experiments of various test configurations and mathematical modeling. The impact of the Franklin Rod¡¯s height and the polarity of impulse are considered. New equations are developed to calculate the striking distance to Franklin Rod both under negative and positive polarity lightning strokes. The lightning protection zone of the Franklin Rod can be predicted by a proposed elliptical model. The experimental data coincides to the calculated protection zone by proposed equations. Finally, the dual-rod lightning protection system is studied. The protection zone of the dual-rod protection system can be evaluated by a combination of Rolling Sphere Circular Model and elliptical model.
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A Bayesian Subgroup Analysis Using An Additive ModelXiao, Yang January 2013 (has links)
No description available.
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Structural Dynamics Model Calibration and Validation of a Rectangular Steel Plate StructureKohli, Karan 24 October 2014 (has links)
No description available.
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An Adaptive Design Optimization Approach to Model-based Discrimination of Cognitive Control MechanismsLee, Sang Ho 01 June 2018 (has links)
No description available.
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Development of Robust Control Techniques towards Damage IdentificationMadden, Ryan J. 03 May 2016 (has links)
No description available.
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Aircraft control with nonlinear indicial response modelCetek, Cem January 1999 (has links)
No description available.
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