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Full-Text Articles in Physical Sciences and Mathematics

Addressing The Challenged Of Dcop Based Decision-Making Algorithms In Modern Power Systems, Luis Daniel Ramirez Burgueno May 2023

Addressing The Challenged Of Dcop Based Decision-Making Algorithms In Modern Power Systems, Luis Daniel Ramirez Burgueno

Open Access Theses & Dissertations

Natural disasters have been determined as the leading cause of power outages, causing not only huge economic losses, but also the interruption of crucial welfare activities and the arise of security concerns. Because of the later, decision-making considering grid modernization, power system economics, and system resiliency has been a crucial theme in power systemsâ?? research. The need to better withstand catastrophic events and reducing the dependency of bulky generating units has propelled the development and better management of behind-the-meter generation or distributed energy resources (DERs). DERs can assist in the grid in different manners, not only by meeting energy demand …


Optimization Of Quantum Circuits Using Spin Bus Multiqubit Gates For Quantum Dots, Miguel Gonzalo Rodriguez Aug 2022

Optimization Of Quantum Circuits Using Spin Bus Multiqubit Gates For Quantum Dots, Miguel Gonzalo Rodriguez

Open Access Theses & Dissertations

The current conventional method for designing quantum circuits is to employ a number of single- and two-qubit gates, which often necessitate a lengthy sequence, imposing severe constraints on quantum coherence and quantum circuit complexity. Coupling multiple spin qubits to a common spin chain can result in a generically multiqubit gate. It is demonstrated that the multiqubit gate can substantially reduce the depth of quantum circuits and establish multiqubit entanglement considerably more quickly.


Renewable Energy Systems Optimization Using Monte Carlo Simulation And Evolutionary Algorithms, Nicolas Lopez Jan 2017

Renewable Energy Systems Optimization Using Monte Carlo Simulation And Evolutionary Algorithms, Nicolas Lopez

Open Access Theses & Dissertations

This Dissertation explores the Renewable Energy Integration Problem, and proposes a Genetic Algorithm embedded with a Monte Carlo simulation to solve large instances of the problem that are impractical to solve via full enumeration. The Renewable Energy Integration Problem is defined as finding the optimum set of components to supply the electric demand to a hybrid

microgrid. The components considered are solar panels, wind turbines, diesel generators, electric batteries, connections to the power grid and converters, which can be inverters and/or rectifiers. The methodology developed is explained as well as the combinatorial formulation. In addition, 2 case studies of a …


The New Issues In Classification Problems, Md Mahmudul Hasan Jan 2016

The New Issues In Classification Problems, Md Mahmudul Hasan

Open Access Theses & Dissertations

The data involved with science and engineering getting bigger everyday. To study and organize a big amount of data is difficult without classification. In machine learning, classification is the problem of identifying a given data from a set of categories. There are several classification technique people using to classify a given data. In our work we present a sparse representation technique to perform classification. The popularity of this technique motivates us to use on our collected samples. To find a sparse representation, we used an $l_1$-minimization algorithm which is a convex relaxation algorithm proven very efficient by researchers. The purpose …


Contributions To The Solution Of Large Nonlinear Systems Via Model-Order Reduction And Interval Constraint Solving Techniques, Leobardo Valera Jan 2015

Contributions To The Solution Of Large Nonlinear Systems Via Model-Order Reduction And Interval Constraint Solving Techniques, Leobardo Valera

Open Access Theses & Dissertations

Many engineering problems boil down to solving partial differential equations (PDEs) that describe real-life phenomena. Nevertheless, efficiently and reliably solving such problems constitutes a major challenge in computational sciences and in engineering in general.

PDE-based systems can reach sizes so large after they are discretized. The large size in these problems generate several issues, among them we can mention: large space of storing, computing time, and the most important, lost of accuracy. A popular approach to solving such problems is assume that the PDE's solution is in a subspace, and the solution is sought there. This assumption and later searching …


Optimization Schemes For The Inversion Of Bouguer Gravity Anomalies, Azucena Zamora Jan 2015

Optimization Schemes For The Inversion Of Bouguer Gravity Anomalies, Azucena Zamora

Open Access Theses & Dissertations

Data sets obtained from measurable physical properties of the Earth structure have helped advance the understanding of its tectonic and structural processes and constitute key elements for resource prospecting. 2-Dimensional (2-D) and 3-D models obtained from the inversion of geophysical data sets are widely used to represent the structural composition of the Earth based on physical properties such as density, seismic wave velocities, magnetic susceptibility, conductivity, and resistivity. The inversion of each one of these data sets provides structural models whose consistency depends on the data collection process, methodology, and overall assumptions made in their individual mathematical processes. Although sampling …


Contributions To Global Optimization Using Interval Methods And Speculation, Angel Fernando Garcia Contreras Jan 2014

Contributions To Global Optimization Using Interval Methods And Speculation, Angel Fernando Garcia Contreras

Open Access Theses & Dissertations

Most electronic devices we are familiar with, such as cell phones and computers, are small and require similarly small electronic components arranged and connected in small areas. Finding the right size and arrangement of the components inside a device can be a challenge. The manufacturing process of the components limits their possible size, some components have specific needs to operate at a certain speed, and the total area of the device is also limited. In portable devices, these designs have one important objective: that the entire device consumes the minimum amount of electricity possible, so the device can keep functioning …


Biofuel Feedstock Optimization Considering Different Land Cover Scenarios And Watershed Impacts, Rodney Wayne Vance Jan 2014

Biofuel Feedstock Optimization Considering Different Land Cover Scenarios And Watershed Impacts, Rodney Wayne Vance

Open Access Theses & Dissertations

With an increased demand for renewable energy production, especially the conversion of biomass to biofuels, perennial grasses are gaining interest as a renewable source of biofuel feedstocks. Identifying the trade-offs between bioenergy crop cultivation and nutrient runoff, erosion, and water requirements will be important as the demand for these crops continues to grow. The primary objective of this study is develop an integrated optimal control model that estimates the potential effects on water quality and demand and soil erosion from cultivating switchgrass and other perennial grasses instead of conventional crops at the watershed scale. The Soil and Water Assessment Tool …


A Multimodal Freight Collaborative Hub Location And Network Design Problem, Jiri Tylich Jan 2012

A Multimodal Freight Collaborative Hub Location And Network Design Problem, Jiri Tylich

Open Access Theses & Dissertations

The study presents an analytical framework to explore the rail-road collaborative paradigm.

New collaborative technologies have been developed in recent years and they offer a potential solutions and opportunities for collaboration among all modes of transportation. The most progressive technologies that could fulfill the gap in rail-road collaborative paradigm are identified and presented in this research.

The research deals with current state and possible development of collaboration of rail and highway modes of transportation, referred to as rail-road collaboration. Multimodal transportation is the shipment of goods in a single transportation unit. The longest part of the route takes place by …


Algorithms For Training Large-Scale Linear Programming Support Vector Regression And Classification, Pablo Rivas Perea Jan 2011

Algorithms For Training Large-Scale Linear Programming Support Vector Regression And Classification, Pablo Rivas Perea

Open Access Theses & Dissertations

The main contribution of this dissertation is the development of a method to train a Support Vector Regression (SVR) model for the large-scale case where the number of training samples supersedes the computational resources. The proposed scheme consists of posing the SVR problem entirely as a Linear Programming (LP) problem and on the development of a sequential optimization method based on variables decomposition, constraints decomposition, and the use of primal-dual interior point methods. Experimental results demonstrate that the proposed approach has comparable performance with other SV-based classifiers. Particularly, experiments demonstrate that as the problem size increases, the sparser the solution …


On Constrained Optimization Schemes For Joint Inversion Of Geophysical Datasets, Uram Anibal Sosa Aguirre Jan 2011

On Constrained Optimization Schemes For Joint Inversion Of Geophysical Datasets, Uram Anibal Sosa Aguirre

Open Access Theses & Dissertations

In the area of geological sciences, there exist several experimental techniques used to advance in the understanding of the Earth. We implement a joint inversion least-squares (LSQ) algorithm to characterize one dimensional Earth's structure by using seismic shear wave velocities as a model parameter. We use two geophysical datasets sensitive to shear velocities, namely Receiver Function and Surface Wave dispersion velocity observations, with a choice of an optimization method: Truncated Singular Value Decomposition (TSVD) or Primal-Dual Interior-Point (PDIP). The TSVD and the PDIP methods solve a regularized unconstrained and a constrained minimization problem, respectively. Both techniques include bounds into the …


Stochastic Optimization For Learning-Based Super-Resolution: Algorithms And Applications, Jun Zheng Jan 2010

Stochastic Optimization For Learning-Based Super-Resolution: Algorithms And Applications, Jun Zheng

Open Access Theses & Dissertations

Human beings get much of their information visually and depend on perception of images for many critical tasks, such as object identification, medical image analysis, photography, etc. In many visual-based applications, higher resolution images are required for perceiving and receiving critical information. A high resolution image can contribute to a better identification of a suspect's face, or a more accurate localization of a tumor in a mammogram, or a more pleasing view in high definition television, and so on. However, it is hard to obtain the high resolution images needed for some applications, for example, the cost of sensors increases …


An Optimization Approach For The Cascade Vulnerability Problem, Christian Servin Jan 2009

An Optimization Approach For The Cascade Vulnerability Problem, Christian Servin

Open Access Theses & Dissertations

In inter-connected systems, where several computers share information with each other, problems may arise when inappropriate information starts to flow through. For example, let us consider a simple scenario of a university composed of three departments: payroll, financial aid, and academic services. We know that the payroll department deals with sensitive information, such as social security numbers, dates of birth, amounts of wages, etc. The financial aid department may use information that payroll owns. Similarly, the academic department communicates with the financial aid department. An intruder can take advantage of this network connectivity and create an inappropriate flow of information …