Theory and Algorithms Commons^™

The Pseudosquares Prime Sieve, Jonathan P. Sorenson

Jonathan P. Sorenson

We present the pseudosquares prime sieve, which finds all primes up to n.

Fast Bounds On The Distribution Of Smooth Numbers, Scott T. Parsell, Jonathan P. Sorenson

Jonathan P. Sorenson

In this paper we present improvements to Bernstein’s algorithm, which finds rigorous upper and lower bounds for (x, y).

Genetic Algorithms For The Extended Gcd Problem, Jonathan P. Sorenson

Jonathan P. Sorenson

We present several genetic algorithms for solving the extended greatest common divisor problem. After defining the problem and discussing previous work, we will state our results.

Design Of A Software Framework Prototype For Scientific Model Interoperability, Eric Fritzinger, Sohei Okamoto

2010 Annual Nevada NSF EPSCoR Climate Change Conference

19 PowerPoint slides Session 2: Infrastructure Convener: Sergiu Dascalu, UNR Abstract: -What are models? -Mathematical models used to describe a system -E.g. Atmospheric, Oceanic, Ecological, etc… -Algorithmic calculations which take input and produce estimated results -Weather forecasting, global warming predictions, sea level estimations, etc… -Models are invaluable

Segmentation Of Thermographic Images Of Hands Using A Genetic Algorithm, Payel Ghosh, Judith Gold, Melanie Mitchell

Computer Science Faculty Publications and Presentations

This paper presents a new technique for segmenting thermographic images using a genetic algorithm (GA). The individuals of the GA also known as chromosomes consist of a sequence of parameters of a level set function. Each chromosome represents a unique segmenting contour. An initial population of segmenting contours is generated based on the learned variation of the level set parameters from training images. Each segmenting contour (an individual) is evaluated for its fitness based on the texture of the region it encloses. The fittest individuals are allowed to propagate to future generations of the GA run using selection, crossover and …

A Randomized Sublinear Time Parallel Gcd Algorithm For The Erew Pram, Jonathan P. Sorenson

Jonathan P. Sorenson

We present a randomized parallel algorithm that computes the greatest common divisor of two integers of n bits in length with probability 1−o(1) that takes O(n log logn/ logn) time using O(n6 + ) processors for any > 0 on the EREW PRAM parallel model of computation. The algorithm either gives a correct answer or reports failure. We believe this to be the first randomized sublinear time algorithm on the EREW PRAM for this problem.

Sketch Of A Typology Of Abstract Memristic Machines, Rudolf Kaehr

Rudolf Kaehr

A typology of memristic machines is sketched. This sketch gives an overview and orientation to the paper “Towards Abstract Memristic Machines”. It also intents to propose a concise systematization of the newly introduced terms and strategies to memristics and morphogrammatics. This sketch is introducing four types of sign-use for four types of machines of fundamentally different paradigms: 1. semiotic, 2. monomorphic, 3. polymorphic and 4. bisimilar abstract machines. Further definitions of abstract machines have to be based on those graphematic notational systems. A realization of such constructions of abstract machines, in contrast to existing abstract machines of the theory of …

Towards Abstract Memristic Machines, Rudolf Kaehr

Rudolf Kaehr

No abstract provided.

From Universe To Polyverses, Rudolf Kaehr

Rudolf Kaehr

Some thoughts about the power of speculation behind important discoveries in mathematics, physics and computer science. The exercise shows that there is no need for a compulsory ultimate unifying universe. It is speculated that just this paradigm of a single ultimate universe is unmasking itself today as the main obstacle for further development in Western science and technology.

Morphogrammatics For Dummies: The Domino Approach, Rudolf Kaehr

Rudolf Kaehr

Dominoes, morphograms, cellular automata, memristics. Topics: possible continuation, coalitions, cooperations, substitution, morphic bisimilarity.

Local Fractional Fourier’S Transform Based On The Local Fractional Calculus, Yang Xiao-Jun

Xiao-Jun Yang

A new modeling for the local fractional Fourier’s transform containing the local fractional calculus is investigated in fractional space. The properties of the local fractional Fourier’s transform are obtained and two examples for the local fractional systems are investigated in detail.

Supporting Multiple Paths To Objects In Information Hierarchies: Faceted Classification, Faceted Search, And Symbolic Links, Saverio Perugini

Computer Science Faculty Publications

We present three fundamental, interrelated approaches to support multiple access paths to each terminal object in information hierarchies: faceted classification, faceted search, and web directories with embedded symbolic links. This survey aims to demonstrate how each approach supports users who seek information from multiple perspectives. We achieve this by exploring each approach, the relationships between these approaches, including tradeoffs, and how they can be used in concert, while focusing on a core set of hypermedia elements common to all. This approach provides a foundation from which to study, understand, and synthesize applications which employ these techniques. This survey does not …

Formalization Of The Ad Hominem Argumentation Scheme, Douglas Walton

CRRAR Publications

In this paper, several examples from the literature, and one central new one, are used as case studies of texts of discourse containing an argumentation scheme that has now been widely investigated in literature on argumentation. Argumentation schemes represent common patterns of reasoning used in everyday conversational discourse. The most typical ones represent defeasible arguments based on nonmonotonic reasoning. Each scheme has a matching set of critical questions used to evaluate a particular argument fitting that scheme. The project is to study how to build a formal computational model of this scheme for the circumstantial ad hominem argument using argumentation …

On The Applications Of Deterministic Chaos For Encrypting Data On The Cloud, Jonathan Blackledge, Nikolai Ptitsyn

Conference papers

Cloud computing is expected to grow considerably in the future because it has so many advantages with regard to sale and cost, change management, next generation architectures, choice and agility. However, one of the principal concerns for users of the Cloud is lack of control and above all, data security. This paper considers an approach to encrypting information before it is ‘place’ on the Cloud where each user has access to their own encryption algorithm, an algorithm that is based on a set of Iterative Function Systems that outputs a chaotic number stream, designed to produce a cryptographically secure cipher. …

Image Edge Detection Using Ant Colony Optimization, Carlos M. Oppus, Anna Veronica Baterina

Department of Information Systems & Computer Science Faculty Publications

Ant colony optimization (ACO) is a population-based metaheuristic that mimics the foraging behavior of ants to find approximate solutions to difficult optimization problems. It can be used to find good solutions to combinatorial optimization problems that can be transformed into the problem of finding good paths through a weighted construction graph. In this paper, an edge detection technique that is based on ACO is presented. The proposed method establishes a pheromone matrix that represents the edge information at each pixel based on the routes formed by the ants dispatched on the image. The movement of the ants is guided by …

Encryption Using Deterministic Chaos, Jonathan Blackledge, Nikolai Ptitsyn

Articles

The concepts of randomness, unpredictability, complexity and entropy form the basis of modern cryptography and a cryptosystem can be interpreted as the design of a key-dependent bijective transformation that is unpredictable to an observer for a given computational resource. For any cryptosystem, including a Pseudo-Random Number Generator (PRNG), encryption algorithm or a key exchange scheme, for example, a cryptanalyst has access to the time series of a dynamic system and knows the PRNG function (the algorithm that is assumed to be based on some iterative process) which is taken to be in the public domain by virtue of the Kerchhoff-Shannon …

Solving Continuous Linear Least-Squares Problems By Iterated Projection, Ralf Juengling

Computer Science Faculty Publications and Presentations

I present a new divide-and-conquer algorithm for solving continuous linear least-squares problems. The method is applicable when the column space of the linear system relating data to model parameters is “translation invariant”. The central operation is a matrix- vector product, which makes the method very easy to implement. Secondly, the structure of the computation suggests a straightforward parallel implementation.

A complexity analysis for sequential implementation shows that the method has the same asymptotic complexity as well-known algorithms for discrete linear least-squares. For illustration we work out the details for the problem of fitting quadratic bivariate polyno- mials to a piecewise …

A Boosting Framework For Visuality-Preserving Distance Metric Learning And Its Application To Medical Image Retrieval, Yang Liu, Rong Jin, Lily Mummert, Rahul Sukthankar, Adam Goode, Bin Zheng, Steven C. H. Hoi, Mahadev Satyanarayanan

Research Collection School Of Computing and Information Systems

Similarity measurement is a critical component in content-based image retrieval systems, and learning a good distance metric can significantly improve retrieval performance. However, despite extensive study, there are several major shortcomings with the existing approaches for distance metric learning that can significantly affect their application to medical image retrieval. In particular, "similarity" can mean very different things in image retrieval: resemblance in visual appearance (e.g., two images that look like one another) or similarity in semantic annotation (e.g., two images of tumors that look quite different yet are both malignant). Current approaches for distance metric learning typically address only one …

Motivated Learning As An Extension Of Reinforcement Learning, Janusz Starzyk, Pawel Raif, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

We have developed a unified framework to conduct computational experiments with both learning systems: Motivated learning based on Goal Creation System, and reinforcedment learning using RL Q-Learning Algorithm. Future work includes combining motivated learning to set abstract motivations and manage goals with reinforcement learning to learn proper actions. This will allow testing of motivated learning on typical reinforcement learning benchmarks with large dimensionality of the state/action spaces.

Nearest Neighbor Search With Strong Location Privacy, Stavros Papadopoulos, Spiridon Bakiras, Dimitris Papadias

Publications and Research

The tremendous growth of the Internet has significantly reduced the cost of obtaining and sharing information about individuals, raising many concerns about user privacy. Spatial queries pose an additional threat to privacy because the location of a query may be sufficient to reveal sensitive information about the querier. In this paper we focus on k nearest neighbor (kNN) queries and define the notion of strong location privacy, which renders a query indistinguishable from any location in the data space. We argue that previous work fails to support this property for arbitrary kNN search. Towards this end, we introduce methods that …