Open Access. Powered by Scholars. Published by Universities.®

Theory and Algorithms Commons™

Open Access. Powered by Scholars. Published by Universities.®

University of Nevada, Las Vegas

Discipline
Keyword
Publication Year
Publication
Publication Type

Articles 1 - 30 of 53

Full-Text Articles in Theory and Algorithms

The Locals Casino As A Social Network – Can An Interconnected Community Of Players Detect Differences In Hold?, Jason D. Fiege, Anastasia (Stasi) D. Baran May 2023

The Locals Casino As A Social Network – Can An Interconnected Community Of Players Detect Differences In Hold?, Jason D. Fiege, Anastasia (Stasi) D. Baran

International Conference on Gambling & Risk Taking

Abstract

It is difficult for individual players to detect differences in theoretical hold between slot machines without playing an unrealistically large number of games. This difficulty occurs because the fractional loss incurred by a player converges only slowly to the theoretical hold in the presence of volatility designed into slot pay tables. Nevertheless, many operators believe that players can detect changes in hold or differences compared to competition, especially in a locals casino market, and therefore resist increasing holds. Instead of investigating whether individual players can detect differences in hold, we ask whether a population of casino regulars who share …


Novel Theorems And Algorithms Relating To The Collatz Conjecture, Michael R. Schwob, Peter Shiue, Rama Venkat Sep 2021

Novel Theorems And Algorithms Relating To The Collatz Conjecture, Michael R. Schwob, Peter Shiue, Rama Venkat

Mathematical Sciences Faculty Research

Proposed in 1937, the Collatz conjecture has remained in the spotlight for mathematicians and computer scientists alike due to its simple proposal, yet intractable proof. In this paper, we propose several novel theorems, corollaries, and algorithms that explore relationships and properties between the natural numbers, their peak values, and the conjecture. These contributions primarily analyze the number of Collatz iterations it takes for a given integer to reach 1 or a number less than itself, or the relationship between a starting number and its peak value.


Toward A Quantum Neural Network: Proposing The Qaoa Algorithm To Replace A Feed Forward Neural Network, Erick Serrano Apr 2021

Toward A Quantum Neural Network: Proposing The Qaoa Algorithm To Replace A Feed Forward Neural Network, Erick Serrano

Undergraduate Research Symposium Posters

With a surge in popularity of machine learning as a whole, many researchers have sought optimization methods to reduce the complexity of neural networks; however, only recent attempts have been made to optimize neural networks via quantum computing methods. In this paper, we describe the training process of a feed forward neural network (FFNN) and the time complexity of the training process. We highlight the inefficiencies of the FFNN training process, particularly when implemented with gradient descent, and introduce a call to action for optimization of a FFNN. Afterward, we discuss the strides made in quantum computing to improve the …


Machine Learning Corrected Quantum Dynamics Calculations, A. Jasinski, J. Montaner, R. C. Forrey, B. H. Yang, P. C. Stancil, Naduvalath Balakrishnan, J. Dai, A. Vargas-Hernandez, R. V. Krems Aug 2020

Machine Learning Corrected Quantum Dynamics Calculations, A. Jasinski, J. Montaner, R. C. Forrey, B. H. Yang, P. C. Stancil, Naduvalath Balakrishnan, J. Dai, A. Vargas-Hernandez, R. V. Krems

Chemistry and Biochemistry Faculty Research

Quantum scattering calculations for all but low-dimensional systems at low energies must rely on approximations. All approximations introduce errors. The impact of these errors is often difficult to assess because they depend on the Hamiltonian parameters and the particular observable under study. Here, we illustrate a general, system- and approximation-independent, approach to improve the accuracy of quantum dynamics approximations. The method is based on a Bayesian machine learning (BML) algorithm that is trained by a small number of exact results and a large number of approximate calculations, resulting in ML models that can generalize exact quantum results to different dynamical …


Self-Stabilizing Token Distribution On Trees With Constant Space, Yuichi Sudo, Ajoy K. Datta, Lawrence L. Larmore, Toshimitsu Masuzawa Aug 2020

Self-Stabilizing Token Distribution On Trees With Constant Space, Yuichi Sudo, Ajoy K. Datta, Lawrence L. Larmore, Toshimitsu Masuzawa

Computer Science Faculty Research

Self-stabilizing and silent distributed algorithms for token distribution in rooted tree networks are given. Initially, each process of a graph holds at most l tokens. Our goal is to distribute the tokens uniformly in the whole network so that every process holds exactly k tokens. In the initial configuration, the total number of tokens in the network may not be nk where n is the number of processes in the network. The root process is given the ability to create a new token or remove a token from the network. We aim to minimize the convergence time, the number of …


Optimizing The Mix Of Games And Their Locations On The Casino Floor, Jason D. Fiege, Anastasia D. Baran Jun 2016

Optimizing The Mix Of Games And Their Locations On The Casino Floor, Jason D. Fiege, Anastasia D. Baran

International Conference on Gambling & Risk Taking

We present a mathematical framework and computational approach that aims to optimize the mix and locations of slot machine types and denominations, plus other games to maximize the overall performance of the gaming floor. This problem belongs to a larger class of spatial resource optimization problems, concerned with optimizing the allocation and spatial distribution of finite resources, subject to various constraints. We introduce a powerful multi-objective evolutionary optimization and data-modelling platform, developed by the presenter since 2002, and show how this software can be used for casino floor optimization. We begin by extending a linear formulation of the casino floor …


Stationary And Time-Dependent Optimization Of The Casino Floor Slot Machine Mix, Anastasia D. Baran, Jason D. Fiege Jun 2016

Stationary And Time-Dependent Optimization Of The Casino Floor Slot Machine Mix, Anastasia D. Baran, Jason D. Fiege

International Conference on Gambling & Risk Taking

Modeling and optimizing the performance of a mix of slot machines on a gaming floor can be addressed at various levels of coarseness, and may or may not consider time-dependent trends. For example, a model might consider only time-averaged, aggregate data for all machines of a given type; time-dependent aggregate data; time-averaged data for individual machines; or fully time dependent data for individual machines. Fine-grained, time-dependent data for individual machines offers the most potential for detailed analysis and improvements to the casino floor performance, but also suffers the greatest amount of statistical noise. We present a theoretical analysis of single …


Efficient Estimation Of Cluster Population, Sanjeev K C May 2015

Efficient Estimation Of Cluster Population, Sanjeev K C

UNLV Theses, Dissertations, Professional Papers, and Capstones

Partitioning a given set of points into clusters is a well known problem in pattern recognition, data mining, and knowledge discovery. One of the well known methods for identifying clusters in Euclidean space is the K-mean algorithm. In using the K-mean clustering algorithm it is necessary to know the value of k (the number of clusters) in advance. We propose to develop algorithms for good estimation of k for points distributed in two dimensions. The techniques we pursue include a bucketing method, g-hop neighbors, and Voronoi diagrams. We also present experimental results for examining the performances of the bucketing method …


Concurrent Localized Wait-Free Operations On A Red Black Tree, Vitaliy Kubushyn Dec 2014

Concurrent Localized Wait-Free Operations On A Red Black Tree, Vitaliy Kubushyn

UNLV Theses, Dissertations, Professional Papers, and Capstones

A red-black tree is a type of self-balancing binary search tree. Some wait-free algorithms have been proposed for concurrently accessing and modifying a red-black tree from multiple threads in shared memory systems. Most algorithms presented utilize the concept of a "window", and are entirely top-down implementations. Top-down algorithms like these have to operate on large portions of the tree, and operations on nodes that would otherwise not overlap at all still have to compete with and help one another.

A wait-free framework is proposed for obtaining ownership of small portions of the tree at a time in a bottom-up manner. …


Spectral Decomposition Of The Scattered Light Due To Deposits On The Solar Panel Surface, And Cross Correlated To Power Loss, Suzanna Ho Dec 2014

Spectral Decomposition Of The Scattered Light Due To Deposits On The Solar Panel Surface, And Cross Correlated To Power Loss, Suzanna Ho

UNLV Theses, Dissertations, Professional Papers, and Capstones

The electric energy generated by solar panels declines due to dust particulates, bird deposits, water spots, and other contaminants that inhibit sunlight absorption and promote light scattering. As part of our research, we use cameras to capture images of solar panels, and analyze the images to detect the amount of scattered light. The more scattered light there is, the less light there is to penetrate the solar panel glass and reach the part of the panel that converts incident light to electric energy; therefore, less energy is generated. In this paper, we discuss the classification algorithm we developed to classify …


A Taxonomy Of Polynomially Solvable Shop Problems With Limited Number Of Machines Or Jobs, Megha Sairam Darapuneni Aug 2014

A Taxonomy Of Polynomially Solvable Shop Problems With Limited Number Of Machines Or Jobs, Megha Sairam Darapuneni

UNLV Theses, Dissertations, Professional Papers, and Capstones

Among shop scheduling problems, job shop and mixed shop are one of the most general models encompassing open shop and flow shop. Many job shop problems are NP hard, but there are numerous cases, which possess polynomial solutions when the number of jobs or the number of machines (or both) is limited.

This thesis gives an overview of methods and algorithms for solving - in polynomial time - such special shop problems, including open, flow, job shop and mixed shop. The tools used include Monge interchange, dynamic programming, greedy techniques and sweep line algorithms and the primary focus of this …


Approaches For Generating 2d Shapes, Pratik Shankar Hada Aug 2014

Approaches For Generating 2d Shapes, Pratik Shankar Hada

UNLV Theses, Dissertations, Professional Papers, and Capstones

Constructing a two dimensional shape from given a set of point sites is a well known problem in computation geometry. We present a critical review of the existing algorithms for constructing polygonal shapes. We present a new approach calledinward dentingfor constructing simple polygons. We then extend the proposed approach for modeling polygons with holes. This is the

first known algorithm for modeling holes in the interior of 2d shapes. We also present experimental investigations of the quality of the solutions generated by the proposed algorithms.

For this we implemented the proposed algorithms in Java programming language. The prototype program can …


A Characterization Of Open Shop Scheduling Problems Using The Hall Theorem And Network Flow, Arunasri Chitti Aug 2014

A Characterization Of Open Shop Scheduling Problems Using The Hall Theorem And Network Flow, Arunasri Chitti

UNLV Theses, Dissertations, Professional Papers, and Capstones

Open shop scheduling problems are combinatorial problems where jobs with certain processing requirements on a number of different machines must be arranged in such a way that objectives related to completion time are optimized. Such problems have applications over a wide spectrum including such as communications, routing and manufacturing.

Many open shop problems are NP-hard but there are a number of special cases which possess polynomial solutions in the case of few machines or few jobs or when preemption of jobs is permitted. Many such solutions are based in the theory of matching or Hall's theorem, or more generally network …


Object Detection Using Contrast Enhancement And Dynamic Noise Reduction, Justin Lee Baker Dec 2013

Object Detection Using Contrast Enhancement And Dynamic Noise Reduction, Justin Lee Baker

UNLV Theses, Dissertations, Professional Papers, and Capstones

Edge detection is one of the most important steps a computer must perform to gain understanding of an object in a digital image either from disk or from video feed. Edge detection allows for the computer to describe the shape of the objects in an image and create a pixel boundary defining what is considered part of an object, and what is not. Cannys edge detection algorithm is one of the most robust and accurate of these edge detection algorithms. However, as with many algorithms in image processing, there are many cases where the algorithm does not perform as well …


Application Of Ntru Cryptographic Algorithm For Securing Scada Communication, Amritha Puliadi Premnath Dec 2013

Application Of Ntru Cryptographic Algorithm For Securing Scada Communication, Amritha Puliadi Premnath

UNLV Theses, Dissertations, Professional Papers, and Capstones

Supervisory Control and Data Acquisition (SCADA) system is a control system which is widely used in Critical Infrastructure System to monitor and control industrial processes autonomously. Most of the SCADA communication protocols are vulnerable to various types of cyber-related attacks. The currently used security standards for SCADA communication specify the use of asymmetric cryptographic algorithms like RSA or ECC for securing SCADA communications. There are certain performance issues with cryptographic solutions of these specifications when applied to SCADA system with real-time constraints and hardware limitations. To overcome this issue, in this thesis we propose the use of a faster and …


Scheduling Jobs On Two Uniform Parallel Machines To Minimize The Makespan, Sandhya Kodimala May 2013

Scheduling Jobs On Two Uniform Parallel Machines To Minimize The Makespan, Sandhya Kodimala

UNLV Theses, Dissertations, Professional Papers, and Capstones

The problem of scheduling n independent jobs on m uniform parallel machines such that the total completion time is minimized is a NP-Hard problem. We propose several heuristic-based online algorithms for machines with different speeds called Q2||Cmax. To show the efficiency of the proposed online algorithms, we compute the optimal solution for Q2||Cmax using pseudo-polynomial algorithms based on dynamic programming method. The pseudo-polynomial algorithm has time complexity O (n T2) and can be run on reasonable time for small number of jobs and small processing times. This optimal offline algorithm is …


Real Time Digital Night Vision Using Nonlinear Contrast Enhancement, Nishikar Sapkota May 2013

Real Time Digital Night Vision Using Nonlinear Contrast Enhancement, Nishikar Sapkota

UNLV Theses, Dissertations, Professional Papers, and Capstones

This thesis describes a nonlinear contrast enhancement technique to implement night vision in digital video. It is based on the global histogram equalization algorithm. First, the effectiveness of global histogram equalization is examined for images taken in low illumination environments in terms of Peak signal to noise ratio (PSNR) and visual inspection of images. Our analysis establishes the existence of an optimum intensity for which histogram equalization yields the best results in terms of output image quality in the context of night vision. Based on this observation, an incremental approach to histogram equalization is developed which gives better results than …


Calibration Of Traffic Flow Models, Victor Molano Apr 2013

Calibration Of Traffic Flow Models, Victor Molano

College of Engineering: Graduate Celebration Programs

This study proposes a methodology to calibrate microscopic traffic flow simulation models. A Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm searches for the set of model parameters that minimizes the difference between actual and simulated values


Fast Sobel Edge Detection Using Parallel Pipeline-Based Architecture On Fpga, Mohammad Shokrolah Shirazi, Brendan Morris Apr 2013

Fast Sobel Edge Detection Using Parallel Pipeline-Based Architecture On Fpga, Mohammad Shokrolah Shirazi, Brendan Morris

College of Engineering: Graduate Celebration Programs

Implementing image processing algorithms on FPGA has recently become more popular since it provides high speed in comparison with software-based approaches. In this paper, we have presented fast pipeline-based architecture for one of the most popular edge detection algorithms called Sobel edge detection. The objective of our work is to present two fast pipeline-based architectures for Sobel edge detection on FPGA benefiting one and two way parallelism. We used Verilog language to implement our designs and we synthesized each one for Cyclone IV FPGA. Experimental results show that our pipeline-based architectures perform edge detection process more than 379 and 751 …


On High-Performance Parallel Decimal Fixed-Point Multiplier Designs, Ming Zhu Apr 2013

On High-Performance Parallel Decimal Fixed-Point Multiplier Designs, Ming Zhu

College of Engineering: Graduate Celebration Programs

Decimal computations are required in finance, and etc.

  • Precise representation for decimals (E.g. 0.2, 0.7… )
  • Performance Requirements (Software simulations are very slow)


Image Processing Algorithms For Improving Planetary Exploration And Understanding, Ali Pouryazdanpanah Apr 2013

Image Processing Algorithms For Improving Planetary Exploration And Understanding, Ali Pouryazdanpanah

College of Engineering: Graduate Celebration Programs

  • To design a fully automated tool-set that allows to detect and extract the sky region in planetary images.
  • To develop the new method for rock segmentation in planetary stereo images.
  • To develop the new method for shadow detection in planetary images


Mono-Sized Sphere Packing Algorithm Development Using Optimized Monte Carlo Technique, Karn Soontrapa, Yitung Chen Apr 2013

Mono-Sized Sphere Packing Algorithm Development Using Optimized Monte Carlo Technique, Karn Soontrapa, Yitung Chen

College of Engineering: Graduate Celebration Programs

In this research, fuel cell catalyst layer was developed using the optimized sphere packing algorithm. An optimization technique named adaptive random search technique (ARSET) was employed in this packing algorithm. The ARSET algorithm will generate the initial location of spheres and allow them to move in the random direction with the variable moving distance, randomly selected from the sampling range (a), based on the Lennard–Jones potential and Morse potential of the current and new configuration. The solid fraction values obtained from this developed algorithm are in the range of 0.610–0.624 while the actual processing time can significantly be reduced by …


Hardware-Software Co-Design, Acceleration And Prototyping Of Control Algorithms On Reconfigurable Platforms, Desta Kumsa Edosa Dec 2012

Hardware-Software Co-Design, Acceleration And Prototyping Of Control Algorithms On Reconfigurable Platforms, Desta Kumsa Edosa

UNLV Theses, Dissertations, Professional Papers, and Capstones

Differential equations play a significant role in many disciplines of science and engineering. Solving and implementing Ordinary Differential Equations (ODEs) and partial Differential Equations (PDEs) effectively are very essential as most complex dynamic systems are modeled based on these equations. High Performance Computing (HPC) methodologies are required to compute and implement complex and data intensive applications modeled by differential equations at higher speed. There are, however, some challenges and limitations in implementing dynamic system, modeled by non-linear ordinary differential equations, on digital hardware. Modeling an integrator involves data approximation which results in accuracy error if data values are not considered …


Degree Constrained Triangulation, Roshan Gyawali Aug 2012

Degree Constrained Triangulation, Roshan Gyawali

UNLV Theses, Dissertations, Professional Papers, and Capstones

Triangulation of simple polygons or sets of points in two dimensions is a widely investigated problem in computational geometry. Some researchers have considered variations of triangulation problems that include minimum weight triangulation, de-launay triangulation and triangulation refinement. In this thesis we consider a constrained version of the triangulation problem that asks for triangulating a given domain (polygon or point sites) so that the resulting triangulation has an increased number of even degree vertices. This problem is called Degree Constrained Triangulation (DCT). We propose four algorithms to solve DCT problems. We also present experimental results based on the implementation of the …


Message Passing Algorithm For Different Problems Sum, Mean, Guide And Sorting In A Rooted Tree Network., Sabaresh Nageswara Rao Maddula Aug 2012

Message Passing Algorithm For Different Problems Sum, Mean, Guide And Sorting In A Rooted Tree Network., Sabaresh Nageswara Rao Maddula

UNLV Theses, Dissertations, Professional Papers, and Capstones

In this thesis, we give message passing algorithms in distributed environment for five different problems of a rooted tree having n nodes. In the first algorithm, every node has a value; the root calculates the sum of those values, and sends it to all the nodes in the network. In the second algorithm, the root computes the value of mean of values of all the nodes, and sends it to all nodes of the network. The third algorithm calculates the guide pairs. Guide pair of a node x is an ordered pair (pre_index(x), post_index(x)), where pre_index(x) and post_index(x) are the …


Framework Developmant For Construction Safety Visialization, Kishor Shrestha Apr 2012

Framework Developmant For Construction Safety Visialization, Kishor Shrestha

College of Engineering: Graduate Celebration Programs

Throughout the history of the construction industry, many fatalities and injuries have occurred in construction sites. One of the major causes of accidents is unsafe site conditions: basically, this is due to inadequate supervision. To improve upon the traditional supervision approach, this study proposes a 'Framework Development for Construction Safety Visualization' approach. In addition to this, a computer vision Edge Detection Algorithm was developed and tested to convert construction site still images into edges of the objects in the images. The framework development of this study uses computer vision, robot vision, image compression, pattern recognition, internet transmission, network communication, and …


Adaptive Image Diffusion In Wavelet Domain, Kumar Mandava Apr 2012

Adaptive Image Diffusion In Wavelet Domain, Kumar Mandava

College of Engineering: Graduate Celebration Programs

  • Removing noise without sacrificing important structures
  • Nonlinear strategies: Wavelet shrinkage and Nonlinear diffusion filtering based on features
  • Clustering based wavelet diffusion


Identifying Effort Estimation Factors For Corrective Maintenance In Object-Oriented Systems, Michael J. Lee Dec 2011

Identifying Effort Estimation Factors For Corrective Maintenance In Object-Oriented Systems, Michael J. Lee

UNLV Theses, Dissertations, Professional Papers, and Capstones

This research identifies factors that impact software maintenance effort by exploring the decision-making process of expert estimators of corrective maintenance projects by using qualitative methods to identify the factors that they use in deriving estimates. We implement a technique called causal mapping, which allows us to identify the cognitive links between the information that estimators use, and the estimates that they produce based on that information. Results suggest that a total of 17 factors may be relevant for corrective maintenance effort estimation, covering constructs related to developers, code, defects, and environment. When these factors are rank-ordered, they demonstrate that some …


Quantification Of Stochastic Uncertainty Propagation For Monte Carlo Depletion Methods In Reactor Analysis, Quentin Thomas Newell Dec 2011

Quantification Of Stochastic Uncertainty Propagation For Monte Carlo Depletion Methods In Reactor Analysis, Quentin Thomas Newell

UNLV Theses, Dissertations, Professional Papers, and Capstones

The Monte Carlo method provides powerful geometric modeling capabilities for large problem domains in 3-D; therefore, the Monte Carlo method is becoming popular for 3-D fuel depletion analyses to compute quantities of interest in spent nuclear fuel including isotopic compositions. The Monte Carlo approach has not been fully embraced due to unresolved issues concerning the effect of Monte Carlo uncertainties on the predicted results.

Use of the Monte Carlo method to solve the neutron transport equation introduces stochastic uncertainty in the computed fluxes. These fluxes are used to collapse cross sections, estimate power distributions, and deplete the fuel within depletion …


Roaming Region For Delaunay Triangulation, Romas James Hada Aug 2011

Roaming Region For Delaunay Triangulation, Romas James Hada

UNLV Theses, Dissertations, Professional Papers, and Capstones

Delaunay graphs have been used in CAD/CAM, sensor network and geographic information systems. We investigate the reliability properties of nodes in Delaunay graphs. For measuring the reliability we formulate the concept of roaming-region for nodes. A node v with large roaming-region r(v) such that v is positioned near the center of r(v) is identified as a reliable node. We develop algorithms for constructing roaming-regions and present an implementation of the proposed algorithm in the Java programming language.