Computer Sciences Commons^™

Generating Compact Wasp Nest Structures Via Minimal Complexity Algorithms., Fadel Ewusi Kofi Adoe

Electronic Theses and Dissertations

Many models have been developed to explain the process of self organization-the emergence of seemingly purposeful behaviors from groups of entities with limited individual intelligence. However, the underlying behavior that facilitates the emergence of this global pattern is not generally well understood. Our study focuses on different low complexity building algorithms and characterizes how nests are built using these algorithms. Three rules postulated to be functions of wasps' building behavior were developed. First is the random rule, in which there is no constraint per the choice of site to be initiated. The second is the 2-cell rule where only sites …

Personalization By Website Transformation: Theory And Practice, Saverio Perugini

Computer Science Faculty Publications

We present an analysis of a progressive series of out-of-turn transformations on a hierarchical website to personalize a user’s interaction with the site. We formalize the transformation in graph-theoretic terms and describe a toolkit we built that enumerates all of the traversals enabled by every possible complete series of these transformations in any site and computes a variety of metrics while simulating each traversal therein to qualify the relationship between a site’s structure and the cumulative effect of support for the transformation in a site. We employed this toolkit in two websites. The results indicate that the transformation enables users …

Open Innovation In Platform Competition, Mei Lin

Research Collection School Of Computing and Information Systems

We examine the competition between a proprietary platform and an open platform,where each platform holds a two-sided market consisted of app developers and users.The open platform cultivates an innovative environment by inviting public efforts todevelop the platform itself and permitting distribution of apps outside of its own appmarket; the proprietary platform restricts apps sales solely within its app market. Weuse a game theoretic model to capture this competitive phenomenon and analyze theimpact of growth of the open source community on the platform competition. We foundthat growth of the open community mitigates the platform rivalry, and balances the developernetwork sizes on …

A Genetic Algorithm Approach For Optimized Routing, Pavithra Gudur

Electrical & Computer Engineering Theses & Dissertations

Genetic Algorithms find several applications in a variety of fields, such as engineering, management, finance, chemistry, scheduling, data mining and so on, where optimization plays a key role. This technique represents a numerical optimization technique that is modeled after the natural process of selection based on the Darwinian principle of evolution. The Genetic Algorithm (GA) is one among several optimization techniques and attempts to obtain the desired solution by generating a set of possible candidate solutions or populations. These populations are then compared and the best solutions from the set are retained. Subsequently, new candidate solutions are produced, and the …

Finding Influentials Based On The Temporal Order Of Information Adoption In Twitter, Changhyun Lee, Haewoon Kwak, Hosung Park, Sue Moon

Research Collection School Of Computing and Information Systems

Twitter offers an explicit mechanism to facilitate information diffusion and has emerged as a new medium for communication. Many approaches to find influentials have been proposed, but they do not consider the temporal order of information adoption. In this work, we propose a novel method to find influentials by considering both the link structure and the temporal order of information adoption in Twitter. Our method finds distinct influentials who are not discovered by other methods.

Expression Invariant Face Recognition Using Shifted Phase-Encoded Joint Transform Correlation Technique, Trisha Ahmed

Electrical & Computer Engineering Theses & Dissertations

A new face recognition algorithm using a synthetic discriminant function based shifted phase-encoded fringe-adjusted joint transform correlation (SDF-SPFJTC) technique is proposed. The dark region in an input image is enhanced by using a nonlinear technique named ratio enhancement in gaussian neighborhood (REIGN). Histogram equalization and Gaussian smoothing are then performed to the enhanced face images and the synthetic discriminant function (SDF) image before they are subjected to the joint transform correlation process. The two distinct correlation peaks produced on extreme ends of the SPFJTC plane signifies the recognition of a potential target. A post processing step utilizes the peak-to-clutter ratio …

Handshaking Protocols And Jamming Mechanisms For Blind Rendezvous In A Dynamic Spectrum Access Environment, Aaron A. Gross

Theses and Dissertations

Blind frequency rendezvous is an important process for bootstrapping communications between radios without the use of pre-existing infrastructure or common control channel in a Dynamic Spectrum Access (DSA) environment. In this process, radios attempt to arrive in the same frequency channel and recognize each other’s presence in changing, under-utilized spectrum. This paper refines existing blind rendezvous techniques by introducing a handshaking algorithm for setting up communications once two radios have arrived in the same frequency channel. It then investigates the effect of different jamming techniques on blind rendezvous algorithms that utilize this handshake. The handshake performance is measured by determining …

Effects Of Channel Mismatches On Beamforming And Signal Detection, Christopher I. Allen

Theses and Dissertations

Tuner gain measurements of a multichannel receiver are reported. A linear regression model is used to characterize the gain, as a function of channel number, tuner set-on frequency, and intermediate frequency. Residual errors of this model are characterized by a t distribution. Very strong autocorrelation of tuner gain at various frequencies is noted. Tuner performance from one channel to the next is diverse; several defects at specific frequencies are noted. The Wilcoxon signed rank test is used to test normality of tuner gain among devices; normality is rejected. Antenna directivity and phase pattern measurements are also reported. An antenna element …

Evolutionary Artificial Neural Network Weight Tuning To Optimize Decision Making For An Abstract Game, Corey M. Miller

Theses and Dissertations

Abstract strategy games present a deterministic perfect information environment with which to test the strategic capabilities of artificial intelligence systems. With no unknowns or random elements, only the competitors’ performances impact the results. This thesis takes one such game, Lines of Action, and attempts to develop a competitive heuristic. Due to the complexity of Lines of Action, artificial neural networks are utilized to model the relative values of board states. An application, pLoGANN (Parallel Lines of Action with Genetic Algorithm and Neural Networks), is developed to train the weights of this neural network by implementing a genetic algorithm over a …

Frequency Diverse Array Radar: Signal Characterization And Measurement Accuracy, Steven H. Brady

Theses and Dissertations

Radar systems provide an important remote sensing capability, and are crucial to the layered sensing vision; a concept of operation that aims to apply the right number of the right types of sensors, in the right places, at the right times for superior battle space situational awareness. The layered sensing vision poses a range of technical challenges, including radar, that are yet to be addressed. To address the radar-specific design challenges, the research community responded with waveform diversity; a relatively new field of study which aims reduce the cost of remote sensing while improving performance. Early work suggests that the …

Information-Quality Aware Routing In Event-Driven Sensor Networks, Hwee Xian Tan, Mun-Choon Chan, Wendong Xiao, Peng-Yong Kong, Chen-Khong Tham

Research Collection School Of Computing and Information Systems

Upon the occurrence of a phenomenon of interest in a wireless sensor network, multiple sensors may be activated, leading to data implosion and redundancy. Data aggregation and/or fusion techniques exploit spatio-temporal correlation among sensory data to reduce traffic load and mitigate congestion. However, this is often at the expense of loss in Information Quality (IQ) of data that is collected at the fusion center. In this work, we address the problem of finding the least-cost routing tree that satisfies a given IQ constraint. We note that the optimal least-cost routing solution is a variation of the classical NP-hard Steiner tree …

K-Anonymity In The Presence Of External Databases, Dimitris Sacharidis, Kyriakos Mouratidis, Dimitris Papadias

Research Collection School Of Computing and Information Systems

The concept of k-anonymity has received considerable attention due to the need of several organizations to release microdata without revealing the identity of individuals. Although all previous k-anonymity techniques assume the existence of a public database (PD) that can be used to breach privacy, none utilizes PD during the anonymization process. Specifically, existing generalization algorithms create anonymous tables using only the microdata table (MT) to be published, independently of the external knowledge available. This omission leads to high information loss. Motivated by this observation we first introduce the concept of k-join-anonymity (KJA), which permits more effective generalization to reduce the …

On The Complexity Of Scheduling University Courses, April L. Lovelace

Master's Theses

It has often been said that the problem of creating timetables for scheduling university courses is hard, even as hard as solving an NP-Complete problem. There are many papers in the literature that make this assertion but rarely are precise problem definitions provided and no papers were found which offered proofs that the university course scheduling problem being discussed is NP-Complete.

This thesis defines a scheduling problem that has realistic constraints. It schedules professors to sections of courses they are willing to teach at times when they are available without overloading them. Both decision and optimization versions are precisely defined. …

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 …

Basic Online Scheduling System Optimizer: A Study In Genetic Alogrithms [Sic], Norman Lee Langhorne

Theses Digitization Project

The purpose of this project is to provide the School of Computer Science and Engineering at California State University, San Bernardino with an optimizing schedule module to enhance the latest version of the Basic Online Scheduling System.

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. …

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

Scholarship and Professional Work - LAS

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.

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.

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 …

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 …

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 …

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 …

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 …

Cbtv: Visualising Case Bases For Similarity Measure Design And Selection, Brian Mac Namee, Sarah Jane Delany

Conference papers

In CBR the design and selection of similarity measures is paramount. Selection can benefit from the use of exploratory visualisation- based techniques in parallel with techniques such as cross-validation ac- curacy comparison. In this paper we present the Case Base Topology Viewer (CBTV) which allows the application of different similarity mea- sures to a case base to be visualised so that system designers can explore the case base and the associated decision boundary space. We show, using a range of datasets and similarity measure types, how the idiosyncrasies of particular similarity measures can be illustrated and compared in CBTV allowing …

Dragon Age: Origins - Maps & Benchmark Problems, Nathan R. Sturtevant, Bioware Corp

Moving AI Lab: 2D Maps and Benchmark Problems

Maps extracted from Dragon Age: Origins with help and explicit permission from BioWare Corp. for use and distribution as benchmark problems.

Contains 156 maps and benchmark problem sets.

Image Registration Using Conformal Log Polar Mapping, Bala Krishna Vadapally

Electrical & Computer Engineering Theses & Dissertations

Image Registration is the process of aligning, or overlaying two images of the same scene that were taken at different times and/or from different viewing angles and/or by sensors with different modalities or resolutions. The variations in the imaging environment induce the difference between the images of the same scene. In our situation, we have two images of the same scene taken with two sensors, one in the visible and the other in the infrared (IR) domain. The cameras are placed adjacent to each other on a stable platform, and the images are captured almost simultaneously. This means that the …

Fault-Tolerance And Recovery In Wireless Sensor Networks, Kevin M. Somervill

Electrical & Computer Engineering Theses & Dissertations

The topic of Wireless Sensor Networks (WSNs) has gained considerable attention in the research community due to the variety of applications and interesting challenges in developing and deploying such networks. The typical WSN is significantly energy constrained and often deployed in harsh or even hostile environments, resulting in sensor nodes that are prone to failure. Failing nodes alter the topology of the network resulting in segmented routing paths and lost messages, ultimately reducing network efficiency. These issues spur the desire to develop energy-efficient, Fault-Tolerant (FT) algorithms that enable the network to persist in spite of the failed nodes. This work …

Networks - Ii: Optimal Fractional Frequency Reuse (Ffr) And Resource Allocation In Multiuser Ofdma System, Naveed Ul Hassan, Mohamad Assaad

International Conference on Information and Communication Technologies

In this paper we determine the optimal fractional frequency reuse (FFR) and resource allocation in OFDMA system. Since the users at the cell edge are more exposed to inter-cell interference therefore each cell is partitioned into two regions; inner region and outer region. We determine the optimal FFR factor for the outer region, bandwidth assigned to each region and subcarrier and power allocation to all the users in the cell. The problem is formulated as sum-power minimization problem subject to minimum rate constraints in both the regions. This is a mixed linear integer programming problem which is relaxed into a …