Theory and Algorithms Commons^™

L-Opacity: Linkage-Aware Graph Anonymization, Sadegh Nobari, Panagiotis Karras, Hwee Hwa Pang, Stephane Bressan

Research Collection School Of Computing and Information Systems

The wealth of information contained in online social networks has created a demand for the publication of such data as graphs. Yet, publication, even after identities have been removed, poses a privacy threat. Past research has suggested ways to publish graph data in a way that prevents the re-identification of nodes. However, even when identities are effectively hidden, an adversary may still be able to infer linkage between individuals with sufficiently high confidence. In this paper, we focus on the privacy threat arising from such link disclosure. We suggest L-opacity, a sufficiently strong privacy model that aims to control an …

Unstructured P2p Link Lifetimes Redux, Zhongmei Yao, Daren B. H. Cline

Computer Science Faculty Publications

We revisit link lifetimes in random P2P graphs under dynamic node failure and create a unifying stochastic model that generalizes the majority of previous efforts in this direction. We not only allow nonexponential user lifetimes and age-dependent neighbor selection, but also cover both active and passive neighbor-management strategies, model the lifetimes of incoming and outgoing links, derive churn-related message volume of the system, and obtain the distribution of transient in/out degree at each user. We then discuss the impact of design parameters on overhead and resilience of the network.

Digital Certificate Management: Optimal Pricing And Crl Releasing Strategies, Jie Zhang, Nan Hu, M. K. Raka

Research Collection School Of Computing and Information Systems

The fast growth of e-commerce and online activities places increasing needs for authentication and secure communication to enable information exchange and online transactions. The public key infrastructure (PKI) provides a promising foundation for meeting such demand, in which certificate authorities (CAs) provide digital certificates. In practice, it is critical to understand consumer purchasing and revocation behaviors so that CAs can better manage the digital certificates and its CRL releasing process. To address this problem, we analytically model a CA's pricing and revocation releasing strategies taking into consideration the users' rational decisions. The model provides solutions two main research questions: (1) …

A Fast Algorithm For The Inversion Of Quasiseparable Vandermonde-Like Matrices, Sirani M. Perera, Grigory Bonik, Vadim Olshevsky

Publications

The results on Vandermonde-like matrices were introduced as a generalization of polynomial Vandermonde matrices, and the displacement structure of these matrices was used to derive an inversion formula. In this paper we first present a fast Gaussian elimination algorithm for the polynomial Vandermonde-like matrices. Later we use the said algorithm to derive fast inversion algorithms for quasiseparable, semiseparable and well-free Vandermonde-like matrices having O(n2) complexity. To do so we identify structures of displacement operators in terms of generators and the recurrence relations(2-term and 3-term) between the columns of the basis transformation matrices for quasiseparable, semiseparable and well-free polynomials. Finally we …

Fast Algorithms For Analyzing Partially Ranked Data, Matthew Mcdermott

HMC Senior Theses

Imagine your local creamery administers a survey asking their patrons to choose their five favorite ice cream flavors. Any data collected by this survey would be an example of partially ranked data, as the set of all possible flavors is only ranked into subsets of the chosen flavors and the non-chosen flavors. If the creamery asks you to help analyze this data, what approaches could you take? One approach is to use the natural symmetries of the underlying data space to decompose any data set into smaller parts that can be more easily understood. In this work, I describe …

A Distributed Greedy Algorithm For Constructing Connected Dominating Sets In Wireless Sensor Networks, Akshaye Dhawan, Nicholas A. Scoville, Michelle Tanco

Mathematics, Computer Science & Statistics Faculty Publications

A Connected Dominating Set (CDS) of the graph representing a Wireless Sensor Network can be used as a virtual backbone for routing in the network. Since sensor nodes are constrained by limited on-board batteries, it is desirable to have a small CDS for the network. However, constructing a minimum size CDS has been shown to be a NP-hard problem. In this paper we present a distributed greedy algorithm for constructing a CDS that we call Greedy Connect. Our algorithm operates in two phases, first constructing a dominating set and then connecting the nodes in this set. We evaluate our algorithm …

Data Mining Based Hybridization Of Meta-Raps, Fatemah Al-Duoli, Ghaith Rabadi

Engineering Management & Systems Engineering Faculty Publications

Though metaheuristics have been frequently employed to improve the performance of data mining algorithms, the opposite is not true. This paper discusses the process of employing a data mining algorithm to improve the performance of a metaheuristic algorithm. The targeted algorithms to be hybridized are the Meta-heuristic for Randomized Priority Search (Meta-RaPS) and an algorithm used to create an Inductive Decision Tree. This hybridization focuses on using a decision tree to perform on-line tuning of the parameters in Meta-RaPS. The process makes use of the information collected during the iterative construction and improvement phases Meta-RaPS performs. The data mining algorithm …

Detection Of Seagrass Scars Using Sparse Coding And Morphological Filter, Ender Oguslu, Sertan Erkanli, Victoria J. Hill, W. Paul Bissett, Richard C. Zimmerman, Jiang Li, Charles R. Bostater Jr. (Ed.), Stelios P. Mertikas (Ed.), Xavier Neyt (Ed.)

OES Faculty Publications

We present a two-step algorithm for the detection of seafloor propeller seagrass scars in shallow water using panchromatic images. The first step is to classify image pixels into scar and non-scar categories based on a sparse coding algorithm. The first step produces an initial scar map in which false positive scar pixels may be present. In the second step, local orientation of each detected scar pixel is computed using the morphological directional profile, which is defined as outputs of a directional filter with a varying orientation parameter. The profile is then utilized to eliminate false positives and generate the final …

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 …

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.

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 …

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 …

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 …

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 …

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 …

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 …

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.

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 …

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 …

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.