Theory and Algorithms Commons^™

Constructing Carmichael Numbers Through Improved Subset-Product Algorithms, W.R. Alford, Jon Grantham, Steven Hayman, Andrew Shallue

Scholarship

style="color: rgb(51, 51, 51); font-family: "Helvetica Neue", Helvetica, Arial, sans-serif; font-size: 14px;">We have constructed a Carmichael number with 10,333,229,505 prime factors, and have also constructed Carmichael numbers with style="color: rgb(51, 51, 51); font-family: "Helvetica Neue", Helvetica, Arial, sans-serif; font-size: 14px;"> prime factors for every style="color: rgb(51, 51, 51); font-family: "Helvetica Neue", Helvetica, Arial, sans-serif; font-size: 14px;"> between 3 and 19,565,220. These computations are the product of implementations of two new algorithms for the subset product problem that exploit the non-uniform distribution of primes style="color: rgb(51, 51, 51); font-family: "Helvetica Neue", Helvetica, Arial, sans-serif; font-size: 14px;">with the property that …

Hybrid Intelligent Model For Software Maintenance Prediction, Abdulrahman Ahmed Bobakr Baqais, Mohammad Alshayeb, Zubair A. Baig

Research outputs 2014 to 2021

Maintenance is an important activity in the software life cycle. No software product can do without undergoing the process of maintenance. Estimating a software’s maintainability effort and cost is not an easy task considering the various factors that influence the proposed measurement. Hence, Artificial Intelligence (AI) techniques have been used extensively to find optimized and more accurate maintenance estimations. In this paper, we propose an Evolutionary Neural Network (NN) model to predict software maintainability. The proposed model is based on a hybrid intelligent technique wherein a neural network is trained for prediction and a genetic algorithm (GA) implementation is used …

Towards A Computational Analysis Of Probabilistic Argumentation Frameworks, Pierpaolo Dondio

Articles

In this paper we analyze probabilistic argumentation frameworks (PAFs), defined as an extension of Dung abstract argumentation frameworks in which each argument n is asserted with a probability p(n). The debate around PAFs has so far centered on their theoretical definition and basic properties. This work contributes to their computational analysis by proposing a first recursive algorithm to compute the probability of acceptance of each argument under grounded and preferred semantics, and by studying the behavior of PAFs with respect to reinstatement, cycles and changes in argument structure. The computational tools proposed may provide strategic information for agents selecting the …

Neutrosophic Logic Approaches Applied To ”Rabot” Real Time Control, Alexandru Gal, Luige Vladareanu, Florentin Smarandache, Hongnian Yu, Mincong Deng

Branch Mathematics and Statistics Faculty and Staff Publications

In this paper we present a way of deciding which control law should operate at a time for a mobile walking robot. The proposed deciding method is based on the new research field, called Neutrosophic Logic. The results are presented as a simulated system for which the output is related to the inputs according to the Neutrosophic Logic.

An Investigation Of Complex Systems In 16 Dimensions, Jordon M. Huffman

Theses and Dissertations

Sir Isaac Newton studied the world around him. He observed unexplainable phenomena that the math of his time could not prove. With the help of Gottfried Leibniz, he created infinitesimal calculus to prove his theories. The new concepts he created revolutionized science, and opened new realms of science previously unthought of. In 2002, Dr. Stephen Wolfram published A New Kind of Science, He argues that the processes of understanding cellular automata can be applied to other aspects of science. Dr. Rodrigo Obando of Columbus State University took Dr. Wolfram's work and dissected it. By breaking down the rules, he started …

Information In Biological Systems And The Fluctuation Theorem, Yaşar Demirel

Department of Chemical and Biomolecular Engineering: Faculty Publications

Some critical trends in information theory, its role in living systems and utilization in fluctuation theory are discussed. The mutual information of thermodynamic coupling is incorporated into the generalized fluctuation theorem by using information theory and nonequilibrium thermodynamics. Thermodynamically coupled dissipative structures in living systems are capable of degrading more energy, and processing complex information through developmental and environmental constraints. The generalized fluctuation theorem can quantify the hysteresis observed in the amount of the irreversible work in nonequilibrium regimes in the presence of information and thermodynamic coupling.

Generic Instance-Specific Automated Parameter Tuning Framework, Linda Lindawati

Dissertations and Theses Collection (Open Access)

Meta-heuristic algorithms play an important role in solving combinatorial optimization problems (COP) in many practical applications. The caveat is that the performance of these meta-heuristic algorithms is highly dependent on their parameter configuration which controls the algorithm behaviour. Selecting the best parameter configuration is often a difficult, tedious and unsatisfying task. This thesis studies the problem of automating the selection of good parameter configurations. Existing approaches to address the challenges of parameter configuration can be classified into one-size-fits-all and instance-specific approaches. One-size-fits-all approaches focus on finding a single best parameter configuration for a set of problem instances, while instance-specific approaches …

Using Acl2 To Verify Loop Pipelining In Behavioral Synthesis, Disha Puri, Sandip Ray, Kecheng Hao, Fei Xie

Civil and Environmental Engineering Faculty Publications and Presentations

Behavioral synthesis involves compiling an Electronic System-Level (ESL) design into its RegisterTransfer Level (RTL) implementation. Loop pipelining is one of the most critical and complex transformations employed in behavioral synthesis. Certifying the loop pipelining algorithm is challenging because there is a huge semantic gap between the input sequential design and the output pipelined implementation making it infeasible to verify their equivalence with automated sequential equivalence checking techniques. We discuss our ongoing effort using ACL2 to certify loop pipelining transformation. The completion of the proof is work in progress. However, some of the insights developed so far may already be of …

Colormoo: An Algorithmic Approach To Generating Color Palettes, Joshua Rael

CMC Senior Theses

Selecting one color can be done with relative ease, but this task becomes more difficult with each subsequent color. Colormoo is an online tool aimed at solving this problem. We implement three algorithms for generating color palettes based off of a starting color. Data is collected for each palette that is generated. Our analysis reveals two of the algorithms are preferred, but under different circumstances. Furthermore, we find that users prefer palettes containing colors that are compatible, but not too similar. With refined heuristics, we believe these techniques can be extended and applied beyond the field of graphic design alone.

Classification With Hidden Markov Model, Badreddine Benyacoub, Souad Elbernoussi, Abdelhak Zoglat, Ismail El Moudden

Research and Infrastructure Service Enterprise (RISE) Faculty Publications

Classification and statistical learning by hidden markov model has achieved remarkable progress in the past decade. They have been applied in many areas like speech recognition and handwriting recognition. However, learning by Hidden Markov Model (HMM) is still restricted to supervised problems. In this paper, we propose a new learning method based on HMM techniques estimations, to built a model for classification. The approach consists of evaluation of the probability to belonging in one group, given the observations by a linear classifier. Our developed algorithm is based on discrete states and discrete observations cases of HMM. Experimental results show that …

A Hybrid Approach To Music Recommendation: Exploiting Collaborative Music Tags And Acoustic Features, Jaime C. Kaufman

UNF Graduate Theses and Dissertations

Recommendation systems make it easier for an individual to navigate through large datasets by recommending information relevant to the user. Companies such as Facebook, LinkedIn, Twitter, Netflix, Amazon, Pandora, and others utilize these types of systems in order to increase revenue by providing personalized recommendations. Recommendation systems generally use one of the two techniques: collaborative filtering (i.e., collective intelligence) and content-based filtering.

Systems using collaborative filtering recommend items based on a community of users, their preferences, and their browsing or shopping behavior. Examples include Netflix, Amazon shopping, and Last.fm. This approach has been proven effective due to increased popularity, and …

A Genetic Algorithm-Based Feature Selection, Oluleye H. Babatunde, Leisa Armstrong, Jinsong Leng, Dean Diepeveen

Research outputs 2014 to 2021

This article details the exploration and application of Genetic Algorithm (GA) for feature selection. Particularly a binary GA was used for dimensionality reduction to enhance the performance of the concerned classifiers. In this work, hundred (100) features were extracted from set of images found in the Flavia dataset (a publicly available dataset). The extracted features are Zernike Moments (ZM), Fourier Descriptors (FD), Lengendre Moments (LM), Hu 7 Moments (Hu7M), Texture Properties (TP) and Geometrical Properties (GP). The main contributions of this article are (1) detailed documentation of the GA Toolbox in MATLAB and (2) the development of a GA-based feature …

Genetic Algorithm With Logistic Regression For Prediction Of Progression To Alzheimer's Disease, Piers Johnson, Luke Vandewater, William Wilson, Paul Maruff, Greg Savage, Petra Graham, Lance S. Macaulay, Kathryn A. Ellis, Cassandra Szoeke, Ralph N. Martins, Christopher Rowe, Colin L. Masters, David Ames, Ping Zhang

Research outputs 2014 to 2021

Assessment of risk and early diagnosis of Alzheimer's disease (AD) is a key to its prevention or slowing the progression of the disease. Previous research on risk factors for AD typically utilizes statistical comparison tests or stepwise selection with regression models. Outcomes of these methods tend to emphasize single risk factors rather than a combination of risk factors. However, a combination of factors, rather than any one alone, is likely to affect disease development. Genetic algorithms (GA) can be useful and efficient for searching a combination of variables for the best achievement (eg. accuracy of diagnosis), especially when the search …

Zernike Moments And Genetic Algorithm : Tutorial And Application, Oluleye H. Babatunde, Leisa Armstrong, Jinsong Leng, Dean Diepeveen

Research outputs 2014 to 2021

Aims/ objectives: To demontrate effectiveness of Zernike Moments for Image Classification. Zernike moment(ZM) is an excellent region-based moment which has attracted the attentions of many image processing researchers since its first application to image analysis. Many papers have been published on several works done on ZM but no single paper ever give a detailed information of how the computation of ZM is done from the time the image is captured to the computation of ZM. This work showed how to effectively apply ZM on RGB images. We have demonstrated the effectiveness of Zernike moment in image classification system. A neuro-genetic …

Novel Image-Dependent Quality Assessment Measures, Asaad Hashim, Zahir Hussain

Research outputs 2014 to 2021

The image is a 2D signal whose pixels are highly correlated in a 2D manner. Hence, using pixel by pixel error what we called previously Mean-Square Error, (MSE) is not an efficient way to compare two similar images (e.g., an original image and a compressed version of it). Due to this correlation, image comparison needs a correlative quality measure. It is clear that correlation between two signals gives an idea about the relation between samples of the two signals. Generally speaking, correlation is a measure of similarity between the two signals. An important step in image similarity was introduced by …

A Comparison Of Evidence Fusion Rules For Situation Recognition In Sensor-Based Environments, Susan Mckeever, Juan Ye

Conference papers

Dempster-Shafer (DS) theory, and its associated Dempster rule of combination, has been widely used to determine belief based on uncertain evi-dence sources. Variations to the original Dempster rule of combination have appeared in the literature to support particular scenarios where unreliable results may result from the use of original DS theory. While theoretical explanations of the rule variations are explained, there is a lack of empirical comparisons of the DS theory and its variations against real data sets. In this work, we examine several variations to DS theory. Using two real-world sensor data sets, we com-pare the performance of DS …

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 …

An Analysis Of Peer-To-Peer Distributed Hash Algorithms In Improving Fault Tolerance In The Hadoop Running Environment, Benjamin R. Knaus

Honors Theses

Cloud computing is a “new frontier” in the world of computing. One of the cloud architectures widely used is the Hadoop running environment. Hadoop consists of many parts—including MapReduce, TaskTrackers, and JobTrackers. Right now, there is no fault-tolerance for JobTrackers in Hadoop. This paper analyzes four different distributed hash algorithms (Pastry, Tapestry, CAN, and Chord) that could be implemented inside Hadoop to improve JobTracker fault-tolerance. We recommend Chord as the best suited for integration and improvement of Hadoop.

In Perfect Xen, A Performance Study Of The Emerging Xen Scheduler, Ryan Hnarakis

Master's Theses

Fifty percent of Fortune 500 companies trust Xen, an open-source bare-metal hypervisor, to virtualize their websites and mission critical services in the cloud. Providing superior fault tolerance, scalability, and migration, virtualization allows these companies to run several isolated operating systems simultaneously on the same physical server. These isolated operating systems, called virtual machines, require a virtual traffic guard to cooperate with one another. This guard known as the Credit2 scheduler along with the newest Xen hypervisor was recently developed to supersede the older schedulers. Since wasted CPU cycles can be costly, the Credit2 prototype must undergo significant performance validation before …

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 …