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Full-Text Articles in Physical Sciences and Mathematics
Polymorphic Data Modeling, Steven R. Benson
Polymorphic Data Modeling, Steven R. Benson
Electronic Theses and Dissertations
There are currently no data modeling standards for modeling NoSQL document store databases. This work proposes a standard to fill the void. The proposed standard is based on our new data modeling pattern named The Polymorphic Table Pattern. The pattern embraces the “schemaless” nature of document store NoSQL while allowing the data modeler to use his or her existing skillsets. The concepts of our proposed modeling have been demonstrated against MongoDB.
Epistasis In Predator-Prey Relationships, Iuliia Inozemtseva
Epistasis In Predator-Prey Relationships, Iuliia Inozemtseva
Electronic Theses and Dissertations
Epistasis is the interaction between two or more genes to control a single phenotype. We model epistasis of the prey in a two-locus two-allele problem in a basic predator- prey relationship. The resulting model allows us to examine both population sizes as well as genotypic and phenotypic frequencies. In the context of several numerical examples, we show that if epistasis results in an undesirable or desirable phenotype in the prey by making the particular genotype more or less susceptible to the predator or dangerous to the predator, elimination of undesirable phenotypes and then genotypes occurs.
Selection Of Step Size For Total Variation Minimization In Ct, Anna N. Yeboah
Selection Of Step Size For Total Variation Minimization In Ct, Anna N. Yeboah
Electronic Theses and Dissertations
Medical image reconstruction by total variation minimization is a newly developed area in computed tomography (CT). In compressed sensing literature, it hasbeen shown that signals with sparse representations in an orthonormal basis may be reconstructed via l1-minimization. Furthermore, if an image can be approximately modeled to be piecewise constant, then its gradient is sparse. The application of l1-minimization to a sparse gradient, known as total variation minimization, may then be used to recover the image. In this paper, the steepest descent method is employed to update the approximation of the image. We propose a way to estimate an optimal step …
Using Neural Networks To Provide Local Weather Forecasts, Andrew Culclasure
Using Neural Networks To Provide Local Weather Forecasts, Andrew Culclasure
Electronic Theses and Dissertations
Artificial neural networks (ANNs) have been applied extensively to both regress and classify weather phenomena. While one of the core strengths of neural networks is rendering accurate predictions with noisy datasets, there is currently not a significant amount of research focusing on whether ANNs are capable of producing accurate forecasts of relevant weather variables from small-scale, imperfect datasets. Also, there is not a significant amount of research focusing on the forecasting performance of neural networks applied to weather datasets that have been temporally rolled-up from a base dataset. In this paper, a survey of existing research on applying ANNs to …
Accelerated Data Delivery Architecture, Michael L. Grecol
Accelerated Data Delivery Architecture, Michael L. Grecol
Electronic Theses and Dissertations
This paper introduces the Accelerated Data Delivery Architecture (ADDA). ADDA establishes a framework to distribute transactional data and control consistency to achieve fast access to data, distributed scalability and non-blocking concurrency control by using a clean declarative interface. It is designed to be used with web-based business applications. This framework uses a combination of traditional Relational Database Management System (RDBMS) combined with a distributed Not Only SQL (NoSQL) database and a browser-based database. It uses a single physical and conceptual database schema designed for a standard RDBMS driven application. The design allows the architect to assign consistency levels to entities …