Theory and Algorithms Commons^™

The Module Isomorphism Problem Reconsidered, Peter A. Brooksbank

Faculty Journal Articles

Algorithms to decide isomorphism of modules have been honed continually over the last 30 years, and their range of applicability has been extended to include modules over a wide range of rings. Highly efficient computer implementations of these algorithms form the bedrock of systems such as GAP and MAGMA, at least in regard to computations with groups and algebras. By contrast, the fundamental problem of testing for isomorphism between other types of algebraic structures -- such as groups, and almost any type of algebra -- seems today as intractable as ever. What explains the vastly different complexity status of the …

Learning Emotions: A Software Engine For Simulating Realistic Emotion In Artificial Agents, Douglas Code

Senior Independent Study Theses

This paper outlines a software framework for the simulation of dynamic emotions in simulated agents. This framework acts as a domain-independent, black-box solution for giving actors in games or simulations realistic emotional reactions to events. The emotion management engine provided by the framework uses a modified Fuzzy Logic Adaptive Model of Emotions (FLAME) model, which lets it manage both appraisal of events in relation to an individual’s emotional state, and learning mechanisms through which an individual’s emotional responses to a particular event or object can change over time. In addition to the FLAME model, the engine draws on the design …

Adaptive Graph Construction For Isomap Manifold Learning, Loc Tran, Zezhong Zheng, Guoquing Zhou, Jiang Li, Karen O. Egiazarian (Ed.), Sos S. Agaian (Ed.), Atanas P. Gotchev (Ed.)

Electrical & Computer Engineering Faculty Publications

Isomap is a classical manifold learning approach that preserves geodesic distance of nonlinear data sets. One of the main drawbacks of this method is that it is susceptible to leaking, where a shortcut appears between normally separated portions of a manifold. We propose an adaptive graph construction approach that is based upon the sparsity property of the ℓ₁ norm. The ℓ₁ enhanced graph construction method replaces k-nearest neighbors in the classical approach. The proposed algorithm is first tested on the data sets from the UCI data base repository which showed that the proposed approach performs better than …

Designing A Portfolio Of Parameter Configurations For Online Algorithm Selection, Aldy Gunawan, Hoong Chuin Lau, Mustafa Misir

Research Collection School Of Computing and Information Systems

Algorithm portfolios seek to determine an effective set of algorithms that can be used within an algorithm selection framework to solve problems. A limited number of these portfolio studies focus on generating different versions of a target algorithm using different parameter configurations. In this paper, we employ a Design of Experiments (DOE) approach to determine a promising range of values for each parameter of an algorithm. These ranges are further processed to determine a portfolio of parameter configurations, which would be used within two online Algorithm Selection approaches for solving different instances of a given combinatorial optimization problem effectively. We …

Algorithm Selection Via Ranking, Jayadi Oentaryo Richard, Handoko Stephanus Daniel, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

The abundance of algorithms developed to solve different problems has given rise to an important research question: How do we choose the best algorithm for a given problem? Known as algorithm selection, this issue has been prevailing in many domains, as no single algorithm can perform best on all problem instances. Traditional algorithm selection and portfolio construction methods typically treat the problem as a classification or regression task. In this paper, we present a new approach that provides a more natural treatment of algorithm selection and portfolio construction as a ranking task. Accordingly, we develop a Ranking-Based Algorithm Selection (RAS) …

Intersection Of Art And Science, Petronio Bendito, Tim Korb

Lawson Building Exhibitions on the Intersection of Art and Science

The Intersection of Art and Science exhibition is an interdisciplinary educational project that examines a wide range of expressive approaches explored by international artists working at the intersection of art, mathematics, computer science, and technology. It is a joint collaboration between the Department of Computer Science and the Patti and Rusty Rueff School of Visual and Performing Arts at Purdue University. Featured artists: Sergio Albiac, Anne Burns, Conan Chadbourne, Hans Dehlinger, Brian Evans, Richard Hassell, Patrick Bingham-Hall, John Arden Hiigli, So Yoon Lym, Gabriel Meyer, and Robert M. Spann. The exhibition was curated by Dr. Petronio Bendito and Dr. Tim …

Parameters Estimation Of Material Constitutive Models Using Optimization Algorithms, Kiswendsida Jules Kere

Williams Honors College, Honors Research Projects

Optimization Algorithms are very useful for solving engineering problems. Indeed, optimization algorithms can be used to optimize engineering designs in terms of safety and economy. Understanding the proprieties of materials in engineering designs is very important in order to make designs safe. Materials are not really perfectly homogeneous and there are heterogeneous distributions in most materials. In this paper, Self-OPTIM which is an inverse constitutive parameter identification framework will be used to identify parameters of a linear elastic material constitutive model. Data for Self-OPTIM will be obtained using ABAQUS simulation of a dog-bone uniaxial test. Optimization Algorithms will be used …

De Novo Protein Structure Modeling And Energy Function Design, Lin Chen

Computer Science Theses & Dissertations

The two major challenges in protein structure prediction problems are (1) the lack of an accurate energy function and (2) the lack of an efficient search algorithm. A protein energy function accurately describing the interaction between residues is able to supervise the optimization of a protein conformation, as well as select native or native-like structures from numerous possible conformations. An efficient search algorithm must be able to reduce a conformational space to a reasonable size without missing the native conformation. My PhD research studies focused on these two directions.

A protein energy function—the distance and orientation dependent energy function of …

A Dynamic Programming Algorithm For Finding The Optimal Placement Of A Secondary Structure Topology In Cryo-Em Data, Abhishek Biswas, Desh Ranjan, Mohammad Zubair, Jing He

Computer Science Faculty Publications

The determination of secondary structure topology is a critical step in deriving the atomic structures from the protein density maps obtained from electron cryomicroscopy technique. This step often relies on matching the secondary structure traces detected from the protein density map to the secondary structure sequence segments predicted from the amino acid sequence. Due to inaccuracies in both sources of information, a pool of possible secondary structure positions needs to be sampled. One way to approach the problem is to first derive a small number of possible topologies using existing matching algorithms, and then find the optimal placement for each …

What Is Answer Set Programming To Propositional Satisfiability, Yuliya Lierler

Computer Science Faculty Publications

Propositional satisfiability (or satisfiability) and answer set programming are two closely related subareas of Artificial Intelligence that are used to model and solve difficult combinatorial search problems. Satisfiability solvers and answer set solvers are the software systems that find satisfying interpretations and answer sets for given propositional formulas and logic programs, respectively. These systems are closely related in their common design patterns. In satisfiability, a propositional formula is used to encode problem specifications in a way that its satisfying interpretations correspond to the solutions of the problem. To find solutions to a problem it is then sufficient to use a …

Hash-Map-Eradicator: Filtering Non-Target Sequences From Next Generation Sequencing Reads, Jonathon Brenner, Catherine Putonti

Bioinformatics Faculty Publications

Contemporary DNA sequencing technologies are continuously increasing throughput at ever decreasing costs. Moreover, due to recent advances in sequencing technology new platforms are emerging. As such computational challenges persist. The average read length possible has taken a giant leap forward with the PacBio and Nanopore solutions. Regardless of the platform used, impurities within the DNA preparation of the sample - be it from unintentional contaminants or pervasive symbiots - remains an issue. We have developed a new tool, HAsh-MaP-ERadicator (HAMPER), for the detection and removal of non-target, contaminating DNA sequences. Integrating hash-based and mapping-based strategies, HAMPER is both memory and …

Sorting By Block Moves, Jici Huang

UNF Graduate Theses and Dissertations

The research in this thesis is focused on the problem of Block Sorting, which has applications in Computational Biology and in Optical Character Recognition (OCR). A block in a permutation is a maximal sequence of consecutive elements that are also consecutive in the identity permutation. BLOCK SORTING is the process of transforming an arbitrary permutation to the identity permutation through a sequence of block moves. Given an arbitrary permutation π and an integer m, the Block Sorting Problem, or the problem of deciding whether the transformation can be accomplished in at most m block moves has been shown to be …

A Comparison Of Cloud Computing Database Security Algorithms, Joseph A. Hoeppner

UNF Graduate Theses and Dissertations

The cloud database is a relatively new type of distributed database that allows companies and individuals to purchase computing time and memory from a vendor. This allows a user to only pay for the resources they use, which saves them both time and money. While the cloud in general can solve problems that have previously been too costly or time-intensive, it also opens the door to new security problems because of its distributed nature. Several approaches have been proposed to increase the security of cloud databases, though each seems to fall short in one area or another.

This thesis presents …

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 …

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. …

Feasibility Of Scalable Quantum Computers, Benjamin N. Goodberry

Selected Honors Theses

No abstract provided.

Band Selection For Hyperspectral Images Using Probabilistic Memetic Algorithm, Liang Feng, Ah-Hwee Tan, Meng-Hiot Lim, Si Wei Jiang

Research Collection School Of Computing and Information Systems

Band selection plays an important role in identifying the most useful and valuable information contained in the hyperspectral images for further data analysis such as classification, clustering, etc. Memetic algorithm (MA), among other metaheuristic search methods, has been shown to achieve competitive performances in solving the NP-hard band selection problem. In this paper, we propose a formal probabilistic memetic algorithm for band selection, which is able to adaptively control the degree of global exploration against local exploitation as the search progresses. To verify the effectiveness of the proposed probabilistic mechanism, empirical studies conducted on five well-known hyperspectral images against two …

Networked Employment Discrimination, Tamara Kneese

Media Studies

Employers often struggle to assess qualified applicants, particularly in contexts where they receive hundreds of applications for job openings. In an effort to increase efficiency and improve the process, many have begun employing new tools to sift through these applications, looking for signals that a candidate is “the best fit.” Some companies use tools that offer algorithmic assessments of workforce data to identify the variables that lead to stronger employee performance, or to high employee attrition rates, while others turn to third party ranking services to identify the top applicants in a labor pool. Still others eschew automated systems, but …

Comparison Of Optimization Techniques In Large Scale Transportation Problems, Tapojit Kumar

Journal of Undergraduate Research at Minnesota State University, Mankato

The Transportation Problem is a classic Operations Research problem where the objective is to determine the schedule for transporting goods from source to destination in a way that minimizes the shipping cost while satisfying supply and demand constraints. Although it can be solved as a Linear Programming problem, other methods exist. Linear Programming makes use of the Simplex Method, an algorithm invented to solve a linear program by progressing from one extreme point of the feasible polyhedron to an adjacent one. The algorithm contains tactics like pricing and pivoting. For a Transportation Problem, a simplified version of the regular Simplex …

Comparison Of Sequence Alignment Algorithms, Tejas Gandhi

Journal of Undergraduate Research at Minnesota State University, Mankato

The fact that biological sequences can be represented as strings belonging to a finite alphabet (A, C, G, and T for DNA) plays an important role in connecting biology to computer science. String representation allows researchers to apply various string comparison techniques available in computer science. As a result, various applications have been developed that facilitate the task of sequence alignment. The problem of finding sequence alignments consists of finding the best match between two biological sequences. A best match can infer an evolutionary relationship and functional similarity. However, there is a lack of research on how reliable and efficient …