Physical Sciences and Mathematics Commons^™

Multi-Channel Peer-To-Peer Streaming Systems As Resource Allocation Problems, Miao Wang

School of Computing: Dissertations, Theses, and Student Research

In the past few years, the Internet has witnessed the success of Peer-to-Peer (P2P) streaming technology, which has attracted millions of users. More recently, commercial P2P streaming systems have begun to support multiple channels and a user in such systems is allowed to watch more than one channel at a time. We refer to such systems as multi-channel P2P streaming systems. In this dissertation, we focus on designing multi-channel P2P streaming systems with the goal of providing optimal streaming quality for all channels, termed as system-wide optimal streaming quality. Specifically, we design the systems from the perspective of how to …

Characterization Of A Boron Carbide Heterojunction Neutron Detector, James E. Bevins

Theses and Dissertations

New methods for neutron detection have become an important area of research in support of national security objectives. In support of this effort, p-type B₅C on n-type Si heterojunction diodes have been built and tested. This research sought to optimize the boron carbide (BC) diode by coupling the nuclear physics modeling capability of GEANT4 and TRIM with the semiconductor device simulation tools. Through an iterative modeling process of controllable parameters, optimal device construction was determined such detection efficiency and charge collection were optimized. This allows an estimation of expected charge collection and efficiency given a set of operating …

A Two-View Learning Approach For Image Tag Ranking, Jinfeng Zhuang, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Tags of social images play a central role for text-based social image retrieval and browsing tasks. However, the original tags annotated by web users could be noisy, irrelevant, and often incomplete for describing the image contents, which may severely deteriorate the performance of text-based image retrieval models. In this paper, we aim to overcome the challenge of social tag ranking for a corpus of social images with rich user-generated tags by proposing a novel two-view learning approach. It can effectively exploit both textual and visual contents of social images to discover the complicated relationship between tags and images. Unlike the …

Optimization Of A Pressure-Treating Process, Josean Velez

Undergraduate Journal of Mathematical Modeling: One + Two

A company that pressure-treats wood wants to minimize its annual cost without using more than 250 days of operation per year. In addition, they want to find the corresponding value of time, batches and cost for each category. We develop an expression in terms of boards per batch to model the total cost of the treatment process. We then take the derivative and use Newton's Method to find the number of boards per batch that minimizes total cost.

Change Detection Without Difference Image Computation Based On Multiobjective Cost Function Optimization, Turgay Çeli̇k, Zeki̇ Yetgi̇n

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we propose a novel method for unsupervised change detection in multi-temporal satellite images by using multiobjective cost function optimization via genetic algorithm (GA). The spatial image grid of the input multi-temporal satellite images is divided into two distinct regions, representing ``changed'' and ``unchanged'' regions between input images, via the intermediate change detection mask produced by the GA. The dissimilarity of pixels of ``changed'' regions and similarity of pixels of ``unchanged'' regions between input multi-temporal images are measured using image quality metrics which consider correlation, spectral distortion, radiometric distortion, and contrast distortion. The contextual information of each pixel …

Optimal Summer Camp Layout, Anthony Bonifonte

Honors Papers

Convex optimization is an important branch of operations research. It generalizes linear programming and offers powerful tools for modelling problems and discovering optimal solutions to real world problems. Mathematically it is an interesting topic because it ties together many branches: linear algebra, multivariable calculus, and numerical analysis, to name a few. Modelling a problem as a convex optimization problem can be challenging but offers many benefits. Algorithm design is critically important to ensure precision of solutions that solve with minimal computation power. From an engineering perspective it is also incredibly useful, since many more situations can be modeled than with …

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

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 …

Modeling Direct Runoff Hydrographs With The Surge Function, Denis Voytenko

USF Tampa Graduate Theses and Dissertations

A surge function is a mathematical function of the form f(x)=ax^pe^-bx. We simplify the surge function by holding p constant at 1 and investigate the simplified form as a potential model to represent the full peak of a stream discharge hydrograph. The previously studied Weibull and gamma distributions are included for comparison. We develop an analysis algorithm which produces the best-fit parameters for every peak for each model function, and we process the data with a MATLAB script that uses spectral analysis to filter year-long, 15-minute, stream-discharge data sets. The filtering is necessary to locate the …

Packing Virtual Machines Onto Servers, David Luke Wilcox

Theses and Dissertations

Data centers consume a significant amount of energy. This problem is aggravated by the fact that most servers and desktops are underutilized when powered on, and still consume a majority of the energy of a fully utilized computer even when idle This problem would be much worse were it not for the growing use of virtual machines. Virtual machines allow system administrators to more fully utilize hardware capabilities by putting more than one virtual system on the same physical server. Many times, virtual machines are placed onto physical servers inefficiently. To address this inefficiency, I developed a new family of …

A Case Study Of Network Design For Middle East Water Distribution, Rachel Bullene

Theses and Dissertations

The Middle Eastern region encompassing Israel, Jordan, and the Palestinian Territories (West Bank and Gaza) is an arid region with fast growing populations. Adequate and equitable access to water for all the people of the region is crucial to the future of Middle East peace. However, the current water distribution system not only fails to provide an adequate and equitable allocation of water, but also results adverse impacts on the environment. This project involves building a mathematical model to aid decision-makers in designing an optimal water distribution network. A new method for incorporating uncertainty in optimization that is based on …

Optimization Of A Chemical Reaction Train, Bahar Sansar

Undergraduate Journal of Mathematical Modeling: One + Two

This project consists of the optimization of a chemical reactor train. The reactor considered here is the continuous stirred tank reactor (CSTR), one of the reactor models used in engineering. Given the design equation for the CSTR and the cost function for a reactor, the following values are determined; the optimum number of reactors in the reaction train, the volume of each reactor and the total cost.

A Species-Conserving Genetic Algorithm For Multimodal Optimization, Michael Scott Brown

CCAC Theses and Dissertations

The problem of multimodal functional optimization has been addressed by much research producing many different search techniques. Niche Genetic Algorithms is one area that has attempted to solve this problem. Many Niche Genetic Algorithms use some type of radius. When multiple optima occur within the radius, these algorithms have a difficult time locating them. Problems that have arbitrarily close optima create a greater problem. This paper presents a new Niche Genetic Algorithm framework called Dynamic-radius Species-conserving Genetic Algorithm. This new framework extends existing Genetic Algorithm research.

This new framework enhances an existing Niche Genetic Algorithm in two ways. As the …

The Impact Of Overfitting And Overgeneralization On The Classification Accuracy In Data Mining, Huy Nguyen Anh Pham

LSU Doctoral Dissertations

Current classification approaches usually do not try to achieve a balance between fitting and generalization when they infer models from training data. Such approaches ignore the possibility of different penalty costs for the false-positive, false-negative, and unclassifiable types. Thus, their performances may not be optimal or may even be coincidental. This dissertation analyzes the above issues in depth. It also proposes two new approaches called the Homogeneity-Based Algorithm (HBA) and the Convexity-Based Algorithm (CBA) to address these issues. These new approaches aim at optimally balancing the data fitting and generalization behaviors of models when some traditional classification approaches are used. …

An Approach Based On Particle Swarm Computation To Study The Nanoscale Dg Mosfet-Based Circuits, Fayacl Djeffal, Toufik Bendib, Redha Benzid, Abdelhamid Benhaya

Turkish Journal of Electrical Engineering and Computer Sciences

The analytical modeling of nanoscale Double-Gate MOSFETs (DG) requires generally several necessary simplifying assumptions to lead to compact expressions of current-voltage characteristics for nanoscale CMOS circuits design. Further, progress in the development, design and optimization of nanoscale devices necessarily require new theory and modeling tools in order to improve the accuracy and the computational time of circuits' simulators. In this paper, we propose a new particle swarm strategy to study the nanoscale CMOS circuits. The latter is based on the 2-D numerical Non-Equilibrium Green's Function (NEGF) simulation and a new extended long channel DG MOSFET compact model. Good agreement between …

Redtnet: A Network Model For Strategy Games, Philip Hingston, Mike Preuss, Daniel Spierling

Research outputs pre 2011

In this work, we develop a simple, graph-based framework, RedTNet, for computational modeling of strategy games and simulations. The framework applies the concept of red teaming as a means by which to explore alternative strategies. We show how the model supports computer-based red teaming in several applications: realtime strategy games and critical infrastructure protection, using an evolutionary algorithm to automatically detect good and often surprising strategies.

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 …

Joint Routing And Link Rate Allocation Under Bandwidth And Energy Constraints In Sensor Networks, Maggie Cheng, Xuan Gong, Lin Cai

Computer Science Faculty Research & Creative Works

In sensor networks, both energy and bandwidth are scarce resources. in the past, many energies efficient routing algorithms have been devised in order to maximize network lifetime, in which wireless link bandwidth has been optimistically assumed to be sufficient. This article shows that ignoring the bandwidth constraint can lead to infeasible routing solutions. as energy constraint affects how data should be routed, link bandwidth also affects not only the routing topology but also the allowed data rate on each link. in this paper, we discuss the sufficient condition on link bandwidth that makes a routing solution feasible, then provide mathematical …

Radiotherapy Optimal Design: An Academic Radiotherapy Treatment Design System, Ryan Acosta, William Brick, A Hanna, Allen G. Holder, D Lara, G Mcquilen, D Nevin, P Uhlig, B Salter

Mathematics Faculty Research

Optimally designing radiotherapy and radiosurgery treatments to increase the likelihood of a successful recovery from cancer is an important application of operations research. Researchers have been hindered by the lack of academic software that supports head-to-head comparisons of different techniques, and this article addresses the inherent difficulties of designing and implementing an academic treatment planning system. In particular, this article details the algorithms and the software design of Radiotherapy optimAl Design (RAD).

Parameter Identification Of A Separately Excited Dc Motor Via Inverse Problem Methodology, Mounir Hadef, Mohamed Rachid Mekideche

Turkish Journal of Electrical Engineering and Computer Sciences

Identification is considered to be among the main applications of inverse theory and its objective for a given physical system is to use data which is easily observable, to infer some of the geometric parameters which are not directly observable. In this paper, a parameter identification method using inverse problem methodology is proposed. The minimisation of the objective function with respect to the desired vector of design parameters is the most important procedure in solving the inverse problem. The conjugate gradient method is used to determine the unknown parameters, and Tikhonov's regularization method is then used to replace the original …

Softcomputing Identification Techniques Of Asynchronous Machine Parameters: Evolutionary Strategy And Chemotaxis Algorithm, Nouri Benaïdja

Turkish Journal of Electrical Engineering and Computer Sciences

Softcomputing techniques are receiving attention as optimisation techniques for many industrial applications. Although these techniques eliminate the need for derivatives computation, they require much work to adjust their parameters at the stage of research and development. Issues such as speed, stability, and parameters convergence remain much to be investigated. This paper discusses the application of the method of reference model to determine parameters of asynchronous machines using two optimisation techniques. Softcomputing techniques used in this paper are evolutionary strategy and the chemotaxis algorithm. Identification results using the two techniques are presented and compared with respect to the conventional simplex technique …

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 …

Diversity Graphs, P Blain, C Davis, Allen G. Holder, J Silva, C Vinzant

Mathematics Faculty Research

Bipartite graphs have long been used to study and model matching problems, and in this paper we introduce the bipartite graphs that explain a recent matching problem in computational biology. The problem is to match haplotypes to genotypes in a way that minimizes the number of haplotypes, a problem called the Pure Parsimony problem. The goal of this work is not to address the computational or biological issues but rather to explore the mathematical structure through a study of the underlying graph theory.

Experimental Design, Synthesis And Application Of Molecular Micelle Modified Polymeric Nanoparticles For Drug Delivery Systems And Free Radical Detection, Gabriela M. Ganea Visser

LSU Doctoral Dissertations

Biodegradable and biocompatible polymeric nanoparticles such as poly (lactide-co-glycolide) (PLGA) nanoparticles have been extensively studied as drug delivery systems for a variety of pharmaceutical agents. Nanoparticle surface properties are primarily determined by the emulsifiers used in the synthesis process, which have a significant impact on nanoparticle physico-chemical and biological properties. Anionic amino acid – based molecular micelles were used in the emulsification process to prepare monodisperse, small (below 100 nm) PLGA nanoparticles with a well defined spherical shape. Such molecular micelle – modified nanoparticles were used as drug carriers for delivery of antioxidants. Thymoquinone is a natural antioxidant, and an …

Optimal Irrigation Management For Sloping, Blocked-End Borders, Jorge Jose Escurra

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

A robust mathematical model of one-dimensional flow for sloping, blocked-end border irrigation was developed using the four-point implicit method to solve the Saint-Venant equations, the volume-balance solution method, and the implementation of new algorithms to avoid numerical instability and solution divergence. The model has the capability of successfully simulating all surface irrigation phases in blocked-end borders for a range of inflow rates (0.01 - 0.05 m³/s per m), longitudinal slopes (up to 1.00%), and border lengths (100 - 500 m).

To achieve numerical stability over the specified parameter ranges, the model was divided into three parts: (1) advance-phase …

Optimization In The Undergraduate Curriculum, Allen Holder

Mathematical Sciences Technical Reports (MSTR)

A discussion of how an optimization course fits into the undergraduate mathematics curriculum

Optimizing Product Line Designs: Efficient Methods And Comparisons, Alexandre Belloni, Robert Freund, Matthew Selove, Duncan Simester

Business Faculty Articles and Research

We take advantage of recent advances in optimization methods and computer hardware to identify globally optimal solutions of product line design problems that are too large for complete enumeration. We then use this guarantee of global optimality to benchmark the performance of more practical heuristic methods. We use two sources of data: (1) a conjoint study previously conducted for a real product line design problem, and (2) simulated problems of various sizes. For both data sources, several of the heuristic methods consistently find optimal or near-optimal solutions, including simulated annealing, divide-and-conquer, product-swapping, and genetic algorithms.

Radiotherapy Optimal Design: An Academic Radiotherapy Treatment Design System, R Acosta, W Brick, A Hanna, Allen Holder, D Lara, G Mcquillen, D Nevin, P Uhlig, B Salter

Mathematical Sciences Technical Reports (MSTR)

Optimally designing radiotherapy and radiosurgery treatments to increase the likelihood of a successful recovery from cancer is an important application of operations research. Researchers have been hindered by the lack of academic software that supports head-to-head comparisons of different techniques, and this article addresses the inherent difficulties of designing and implementing an academic treatment planning system. In particular, this article details the algorithms and the software design of Radiotherapy optimAl Design (RAD).

Optimal Treatments For Photodynamic Therapy, Allen G. Holder, D Llagostera

Mathematics Faculty Research

Photodynamic therapy is a complex treatment for neoplastic diseases that uses the light-harvesting properties of a photosensitizer. The treatment depends on the amount of photosensitizer in the tissue and on the amount of light that is focused on the targeted area. We use a pharmacokinetic model to represent a photosensitizer's movement through the anatomy and design treatments with a linear program. This technique allows us to investigate how a treatment's success varies over time.

Utility-Based Adaptation In Mission-Oriented Wireless Sensor Networks, Sharanya Eswaran, Archan Misra, Thomas La Porta

Research Collection School Of Computing and Information Systems

This paper extends the distributed network utility maximization (NUM) framework to consider the case of resource sharing by multiple competing missions in a military-centric wireless sensor network (WSN) environment. Prior work on NUM-based optimization has considered unicast flows with sender-based utilities in either wireline or wireless networks. We extend the NUM framework to consider three key new features observed in mission-centric WSN environments: i) the definition of an individual mission's utility as a joint function of data from multiple sensor sources ii) the consumption of each senders (sensor) data by multiple receivers (missions) and iii) the multicast-tree based dissemination of …