Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 15 of 15 for “"Feature models"”.
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Automating the analysis of stateful feature models
El modelado de la variabilidad es una de las principales tareas en el desarrollo de l´ıneas de productos software (LPS). Los FMs son el modelo mas utilizado para ello. Los FMs representan el conjunto de decisiones que pueden tomar los usuarios para configurar su producto como una jerarqu´ıa de …
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Latent feature models and non-invasive clonal reconstruction
… constraints or posit a perfect phylogeny. Models of the first type are typically latent feature models that can describe the observed data flexibly, but whose results may not be reconcilable with a phylogeny. The second type, instead, generally comprises non-parametric mixture models, with …
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Multi-object and multi-feature models of thumb anatomy for population based morphological assessment
… data from OA-affected and control subjects. Features related to shape, pose, and intensity in the CT images of the TMC joints from the subjects were correlated to a range of biomechanical risk factors. Multi-object and multi feature-class statistical models of control and OA-affected datasets …
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Evolutionary Search Techniques with Strong Heuristics for Multi-Objective Feature Selection in Software Product Lines
… configures software product lines (expressed as feature models) using various search-based software engineering methods. Our main result is that as we increase the number of optimization objectives, the methods in widespread use (e.g. NSGA-II, SPEA2) perform much worse than IBEA (Indicator-Based …
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Modeling Software Product Lines Using Feature Diagrams
… which software products in a domain are built. Feature modeling is a process that enables engineers to identify these core assets, in particular the com(e.g., shared) and variable features of products. The focus of this thesis is to give an overview of the feature modeling process by introducing …
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Nonparametric Bayesian Modelling in Machine Learning
… on an infinite dimensional space for latent feature models. Our contribution in this thesis is to collect many diverse groups of nonparametric Bayesian tools and explore algorithms to sample from them. We also explore machinery behind the theory to apply and expose some distinguished features …
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Representation and learning schemes for argument stance mining.
… use of a lexicon with modifiers as a temporal feature model for more complex classification algorithms. We find that the addition of contextual information enhances unsupervised stance classification, within reason, and that multi-strategy algorithms that combine multiple heuristics by ordering …
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Automated Prediction of Hepatic Arterial Stenosis
… invasive diagnostic procedure. Machine learning models have shown promise in determining stenosis in the carotid artery; however, they have yet to be tested on the less ideal data hepatic arteries generate. Software has been created to extract liver artery Doppler ultrasound information in an …
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Flow Kinematics and Dynamics of the Gulf Stream From Composite Imagery
… fractal and spectral analyses, two kinematic models, and a potential vorticity model, detailed comparisons are made between these data sets.</p> <p>Fractal and spectral analyses show that the data set is not fractal, there is no geographic variability, and there is not a strong fractal scaling …
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Automatic Derivation of Performance Models in the Context of Model-Driven SOA
… purpose is to automatically generate performance models from the UML software design models of SOA systems with performance annotations. The main goal of PUMA4SOA is to enable the analysis of performance properties of software systems in the early software development phases, which helps …
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Concepts and Schemas: Representational Format for Structured Knowledge
… We start by discussing classical geometric models of knowledge representation, which view concepts as regions in abstract, multidimensional spaces organised by metric principles. These models have been supported by recent neuroimaging studies that suggest shared neural representations for …
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Feature-based Approach to Bridge the Information Technology and Business Gap
… software products can be described by a set of features, a promising solution would be to link both the problem and solution domains based on these features. Thus, the proposed approach aims to bridge the gap between the problem and the solution domains by using a feature-based technique in …
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Forensic research on detecting seam carving in digital images
… proposed as the first work in this dissertation. Features measured global energy of images, remaining optimal seams, and noise level are extracted from four local derivative pattern (LDP) domains instead of from the original pixel domain to heighten the energy change caused by seam carving. A …
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HybridMDSD: Multi-Domain Engineering with Model-Driven Software Development using Ontological Foundations
… based on modeling languages. Corresponding models are used to generate actual programming code without the need for creating manually written, error-prone assets. Modeling languages that are tailored towards a particular domain are called domain-specific languages (DSLs). Domain-specific …
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FACTORS INFLUENCING THE SPATIAL AND TEMPORAL STRUCTURE OF A CARNIVORE GUILD IN THE CENTRAL HARDWOOD REGION
… methods to develop and evaluate models for detection, species-specific habitat occupancy, multi-species co-occupancy, and multi-season (colonization and extinction) occupancy dynamics. I developed hypotheses for each species regarding the occupancy of areas based on anthropogenic …