Computer Sciences Commons^™

Impact Of Primary User Activity On The Performance Of Energy-Based Spectrum Sensing In Cognitive Radio Systems, Sara L. Macdonald

Electrical & Computer Engineering Theses & Dissertations

Increasing numbers of wireless devices and mobile data requirements have led to a spectrum shortage. However spectrum utilization percentages are often low due to the current static spectrum allocation process where primary users (PUs) are given exclusive use to spectrum. Several mechanisms to increase spectrum utilization have been proposed including opportunistic spectrum access (OSA). Cognitive Radio (CR) is an emerging concept in wireless communication systems that aims to enable OSA in licensed frequencies by secondary users (SUs). CR systems are expected to sense the spectrum in order to determine if the PU is transmitting. Therefore OSA performance relies on the …

Modeling Social Information Learning Among Taxi Drivers, Siyuan Liu, Ramayya Krishnan, Emma Brunskill, Lionel Ni

Research Collection School Of Computing and Information Systems

When a taxi driver of an unoccupied taxi is seeking passengers on a road unknown to him or her in a large city, what should the driver do? Alternatives include cruising around the road or waiting for a time period at the roadside in the hopes of finding a passenger or just leaving for another road enroute to a destination he knows (e.g., hotel taxi rank)? This is an interesting problem that arises everyday in many cities worldwide. There could be different answers to the question poised above, but one fundamental problem is how the driver learns about the likelihood …

Artificial Immune Systems And Particle Swarm Optimization For Solutions To The General Adversarial Agents Problem, Jeremy Mange

Dissertations

The general adversarial agents problem is an abstract problem description touching on the fields of Artificial Intelligence, machine learning, decision theory, and game theory. The goal of the problem is, given one or more mobile agents, each identified as either “friendly" or “enemy", along with a specified environment state, to choose an action or series of actions from all possible valid choices for the next “timestep" or series thereof, in order to lead toward a specified outcome or set of outcomes. This dissertation explores approaches to this problem utilizing Artificial Immune Systems, Particle Swarm Optimization, and hybrid approaches, along with …

Confidence Weighted Mean Reversion Strategy For Online Portfolio Selection, Bin Li, Steven C. H. Hoi, Peilin Zhao, Vivekanand Gopalkrishnan

Research Collection School Of Computing and Information Systems

Online portfolio selection has been attracting increasing attention from the data mining and machine learning communities. All existing online portfolio selection strategies focus on the first order information of a portfolio vector, though the second order information may also be beneficial to a strategy. Moreover, empirical evidence shows that relative stock prices may follow the mean reversion property, which has not been fully exploited by existing strategies. This article proposes a novel online portfolio selection strategy named Confidence Weighted Mean Reversion (CWMR). Inspired by the mean reversion principle in finance and confidence weighted online learning technique in machine learning, CWMR …

Fault-Tolerant Coverage In Dense Wireless Sensor Networks, Akshaye Dhawan, Magdalena Parks

Mathematics, Computer Science & Statistics Faculty Publications

In this paper, we present methods to detect and recover from sensor failure in dense wireless sensor networks. In order to extend the lifetime of a sensor network while maintaining coverage, a minimal subset of the deployed sensors are kept active while the other sensors can enter a low power sleep state. Several distributed algorithms for coverage have been proposed in the literature. Faults are of particular concern in coverage algorithms since sensors go into a sleep state in order to conserve battery until woken up by active sensors. If these active sensors were to fail, this could lead to …

Interpreting Individual Classifications Of Hierarchical Networks, Will Landecker, Michael David Thomure, Luis M.A. Bettencourt, Melanie Mitchell, Garrett T. Kenyon, Steven P. Brumby

Computer Science Faculty Publications and Presentations

Hierarchical networks are known to achieve high classification accuracy on difficult machine-learning tasks. For many applications, a clear explanation of why the data was classified a certain way is just as important as the classification itself. However, the complexity of hierarchical networks makes them ill-suited for existing explanation methods. We propose a new method, contribution propagation, that gives per-instance explanations of a trained network's classifications. We give theoretical foundations for the proposed method, and evaluate its correctness empirically. Finally, we use the resulting explanations to reveal unexpected behavior of networks that achieve high accuracy on visual object-recognition tasks using well-known …

Using Mapreduce Streaming For Distributed Life Simulation On The Cloud, Atanas Radenski

Mathematics, Physics, and Computer Science Faculty Books and Book Chapters

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable …

Accelerated Data Delivery Architecture, Michael L. Grecol

College of Graduate Studies: Theses & Dissertations

This paper introduces the Accelerated Data Delivery Architecture (ADDA). ADDA establishes a framework to distribute transactional data and control consistency to achieve fast access to data, distributed scalability and non-blocking concurrency control by using a clean declarative interface. It is designed to be used with web-based business applications. This framework uses a combination of traditional Relational Database Management System (RDBMS) combined with a distributed Not Only SQL (NoSQL) database and a browser-based database. It uses a single physical and conceptual database schema designed for a standard RDBMS driven application. The design allows the architect to assign consistency levels to entities …

A Parallel Template For Implementing Filters For Biological Correlation Networks, Kathryn Dempsey Cooper, Vladimir Ufimtsev, Sanjukta Bhowmick, Hesham Ali

Interdisciplinary Informatics Faculty Publications

High throughput biological experiments are critical for their role in systems biology – the ability to survey the state of cellular mechanisms on the broad scale opens possibilities for the scientific researcher to understand how multiple components come together, and what goes wrong in disease states. However, the data returned from these experiments is massive and heterogeneous, and requires intuitive and clever computational algorithms for analysis. The correlation network model has been proposed as a tool for modeling and analysis of this high throughput data; structures within the model identified by graph theory have been found to represent key players …

Automatic Detection Of Abnormal Behavior In Computing Systems, James Frank Roberts

Theses and Dissertations--Computer Science

I present RAACD, a software suite that detects misbehaving computers in large computing systems and presents information about those machines to the system administrator. I build this system using preexisting anomaly detection techniques. I evaluate my methods using simple synthesized data, real data containing coerced abnormal behavior, and real data containing naturally occurring abnormal behavior. I find that the system adequately detects abnormal behavior and significantly reduces the amount of uninteresting computer health data presented to a system administrator.

Hyperspectral Image Classification Using A Spectral-Spatial Sparse Coding Model, Ender Oguslu, Guoqing Zhou, Jiang Li, Lorenzo Bruzzone (Ed.)

Electrical & Computer Engineering Faculty Publications

We present a sparse coding based spectral-spatial classification model for hyperspectral image (HSI) datasets. The proposed method consists of an efficient sparse coding method in which the l₁/l_q regularized multi-class logistic regression technique was utilized to achieve a compact representation of hyperspectral image pixels for land cover classification. We applied the proposed algorithm to a HSI dataset collected at the Kennedy Space Center and compared our algorithm to a recently proposed method, Gaussian process maximum likelihood (GP-ML) classifier. Experimental results show that the proposed method can achieve significantly better performances than the GP-ML classifier when training data …

Usefulness Of Infeasible Solutions In Evolutionary Search: An Empirical And Mathematical Study, Lyndon While, Philip Hingston

Research outputs 2013

When evolutionary algorithms are used to solve constrained optimization problems, the question arises how best to deal with infeasible solutions in the search space. A recent theoretical analysis of two simple test problems argued that allowing infeasible solutions to persist in the population can either help or hinder the search process, depending on the structure of the fitness landscape. We report new empirical and mathematical analyses that provide a different interpretation of the previous theoretical predictions: that the important effect is on the probability of finding the global optimum, rather than on the time complexity of the algorithm. We also …

Gpu-Optimized Code For Long-Term Simulations Of Beam-Beam Effects In Colliders, Y. Roblin, V. Morozov, B. Terzić, M. Aturban, D. Ranjan, M. Zubair

Computer Science Faculty Publications

We report on the development of the new code for long-term simulation of beam-beam effects in particle colliders. The underlying physical model relies on a matrix-based arbitrary-order symplectic particle tracking for beam transport and the Bassetti-Erskine approximation for beam-beam interaction. The computations are accelerated through a parallel implementation on a hybrid GPU/CPU platform. With the new code, a previously computationally prohibitive long-term simulations become tractable. We use the new code to model the proposed medium-energy electron-ion collider (MEIC) at Jefferson Lab.

Analyzing The Impact Of Cloud Services Brokers On Cloud Computing Markets, Richard D. Shang, Jianhui Huang, Yinping Yang, Robert J. Kauffman

Research Collection School Of Computing and Information Systems

This research offers a theoretical model of brokered services and provides an analysis of their impact on the cloud computing market with risk preference-based stratification of client segments. The model structures the decision problem that clients face when they choose among spot, reserved and brokered services. Although all the three types of services do not indemnify the cloud services client against other kinds of service outages, due to changes in market demand, service interruptions occur most frequently in the spot market, and are lower when brokered services are offered, and no risk of inter-ruption is involved in reserved services. Based …

Connotational Subtyping And Runtime Class Mutability In Ruby, Ian S. Dillon

Electronic Theses and Dissertations

Connotational subtyping is an approach to typing that allows an object's type to change dynamically, following changes to the object's internal state. This allows for a more precise representation of a problem domain with logical objects that have variable behavior. Two approaches to supporting connotational subtyping in the Ruby programming language were implemented: a language-level implementation using pure Ruby and a modification to the Ruby 1.8.7 interpreter. While neither implementation was wholly successful the language level implementation created complications with reflective language features like self and super and, while Ruby 1.8.7 has been obsoleted by Ruby 1.9 (YARV), the results …

Application Of Digital Forensic Science To Electronic Discovery In Civil Litigation, Brian Roux

LSU New Orleans Theses and Dissertations

Following changes to the Federal Rules of Civil Procedure in 2006 dealing with the role of Electronically Stored Information, digital forensics is becoming necessary to the discovery process in civil litigation. The development of case law interpreting the rule changes since their enactment defines how digital forensics can be applied to the discovery process, the scope of discovery, and the duties imposed on parties. Herein, pertinent cases are examined to determine what trends exist and how they effect the field. These observations buttress case studies involving discovery failures in large corporate contexts along with insights on the technical reasons those …

Contour Extraction Of Drosophila Embryos Using Active Contours In Scale Space, Soujanya Siddavaram Ananta

Masters Theses & Specialist Projects

Contour extraction of Drosophila embryos is an important step to build a computational system for pattern matching of embryonic images which aids in the discovery of genes. Automatic contour extraction of embryos is challenging due to several image variations such as size, shape, orientation and neigh- boring embryos such as touching and non-touching embryos. In this thesis, we introduce a framework for contour extraction based on the connected components in the gaussian scale space of an embryonic image. The active contour model is applied on the images to refine embryo contours. Data cleaning methods are applied to smooth the jaggy …

Hardware-Software Co-Design, Acceleration And Prototyping Of Control Algorithms On Reconfigurable Platforms, Desta Kumsa Edosa

UNLV Theses, Dissertations, Professional Papers, and Capstones

Differential equations play a significant role in many disciplines of science and engineering. Solving and implementing Ordinary Differential Equations (ODEs) and partial Differential Equations (PDEs) effectively are very essential as most complex dynamic systems are modeled based on these equations. High Performance Computing (HPC) methodologies are required to compute and implement complex and data intensive applications modeled by differential equations at higher speed. There are, however, some challenges and limitations in implementing dynamic system, modeled by non-linear ordinary differential equations, on digital hardware. Modeling an integrator involves data approximation which results in accuracy error if data values are not considered …

Microblog Search And Filtering With Time Sensitive Feedback And Thresholding Based On Bm25, Wei Gao, Zhongyu Wei, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

Microblogs such as Twitter are considered faster first-hand sources of information with many real-time fashions. We report our work in the real-time adhoc search and filtering tasks of TREC 2012 microblog track. Our system is built based on the traditional BM25 relevance model, in which specific techniques are tried out to respond to the ne.ed of frnding relevant tweets, ln thc real-time adhoc task, we applied a peak detection algorithm for the process of blind feedback, We also tried to automatically combine the search results of multiple retrieval techniques. In the real-time filtering pilot task, we examine the effectiveness of …

Snap-And-Ask: Answering Multimodal Question By Naming Visual Instance, Wei Zhang, Lei Pang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

In real-life, it is easier to provide a visual cue when asking a question about a possibly unfamiliar topic, for example, asking the question, “Where was this crop circle found?”. Providing an image of the instance is far more convenient than texting a verbose description of the visual properties, especially when the name of the query instance is not known. Nevertheless, having to identify the visual instance before processing the question and eventually returning the answer makes multimodal question-answering technically challenging. This paper addresses the problem of visual-totext naming through the paradigm of answering-by-search in a two-stage computational framework, which …

Retrieval Of Sub-Pixel-Based Fire Intensity And Its Application For Characterizing Smoke Injection Heights And Fire Weather In North America, David Peterson

Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research

For over two decades, satellite sensors have provided the locations of global fire activity with ever-increasing accuracy. However, the ability to measure fire intensity, know as fire radiative power (FRP), and its potential relationships to meteorology and smoke plume injection heights, are currently limited by the pixel resolution. This dissertation describes the development of a new, sub-pixel-based FRP calculation (FRP_f) for fire pixels detected by the MODerate Resolution Imaging Spectroradiometer (MODIS) fire detection algorithm (Collection 5), which is subsequently applied to several large wildfire events in North America. The methodology inherits an earlier bi-spectral algorithm for retrieving sub-pixel …

Verifying Total Correctness Of Graph Programs, Christopher M. Poskitt, Detlef Plump

Research Collection School Of Computing and Information Systems

GP 2 is an experimental nondeterministic programming language based on graph transformation rules, allowing for visual programming and the solving of graph problems at a high-level of abstraction. In previous work we demonstrated how to verify graph programs using a Hoare-style proof calculus, but only partial correctness was considered. In this paper, we add new proof rules and termination functions, which allow for proofs to additionally guarantee that program executions always terminate (weak total correctness), or that programs always terminate and do so without failure (total correctness). We show that the new proof rules are sound with respect to the …

Verification Of Graph Programs, Christopher M. Poskitt

Research Collection School Of Computing and Information Systems

GP (for Graph Programs) is an experimental nondeterministic programming language which allows for the manipulation of graphs at a high level of abstraction. The program states of GP are directed labelled graphs. These are manipulated directly via the application of (conditional) rule schemata, which generalise double-pushout rules with expressions over labels and relabelling. In contrast with graph grammars, the application of these rule schemata is directed by a number of simple control constructs including sequential composition, conditionals, and as-long-as-possible iteration. GP shields programmers at all times from low-level implementation issues (e.g. graph representation), and with its nondeterministic semantics, allows one …

Theoretical Approaches To The Characterization Of Water, Aqueous Interfaces, And Improved Sampling Of Protein Conformational Changes, Alexis J. Lee

LSU New Orleans Theses and Dissertations

Methods to advance the understanding of water and other aqueous systems are devel- oped. This work falls into three areas: The creation of better interaction potentials for water, improved methods for sampling configurational space, and the applications of these methods to understand systems of interest. Charge transfer has been shown by ab initio methods to be important in the water–water and water–ion interactions. A model for treating charge transfer in liquid water and aqueous systems is presented in this manuscript. The model is called Discrete Charge Transfer (DCT) and is based on the commonly-used TIP4P/2005 model, which represents the charge …

Measurement-Driven Performance Analysis Of Indoor Femtocellular Networks, Trung-Tuan Luong, Vigneshwaran Subbaraju, Archan Misra, Srinivasan Seshan

Research Collection School Of Computing and Information Systems

This paper describes initial empirical studies, performed on a 6-node 3G indoor femtocellular testbed, that investigate the impact of pedestrian mobility on network parameters, such as handoff behavior and data throughput. The studies establish that, owing to the small radii of cells, even modest changes in movement speed can have disproportionately large impact on handoff patterns and network throughput. By also revealing a strong temporal dependency effect, the studies motivate the need for algorithms to accurately predict RF signal strength distributions in dynamic indoor environments. We present such an RF prediction algorithm, based on crowd-sourced signal strength readings, and show …

Degree Constrained Triangulation, Roshan Gyawali

UNLV Theses, Dissertations, Professional Papers, and Capstones

Triangulation of simple polygons or sets of points in two dimensions is a widely investigated problem in computational geometry. Some researchers have considered variations of triangulation problems that include minimum weight triangulation, de-launay triangulation and triangulation refinement. In this thesis we consider a constrained version of the triangulation problem that asks for triangulating a given domain (polygon or point sites) so that the resulting triangulation has an increased number of even degree vertices. This problem is called Degree Constrained Triangulation (DCT). We propose four algorithms to solve DCT problems. We also present experimental results based on the implementation of the …

Message Passing Algorithm For Different Problems Sum, Mean, Guide And Sorting In A Rooted Tree Network., Sabaresh Nageswara Rao Maddula

UNLV Theses, Dissertations, Professional Papers, and Capstones

In this thesis, we give message passing algorithms in distributed environment for five different problems of a rooted tree having n nodes. In the first algorithm, every node has a value; the root calculates the sum of those values, and sends it to all the nodes in the network. In the second algorithm, the root computes the value of mean of values of all the nodes, and sends it to all nodes of the network. The third algorithm calculates the guide pairs. Guide pair of a node x is an ordered pair (pre_index(x), post_index(x)), where pre_index(x) and post_index(x) are the …

Transition States Of Dbt Molecule At The Mos2/Co9s8 Interface: First Principles, Svetlana Gelpi, Alvaro S. Laham, Gilles Berhault, Brenda Torres, Russel R. Chianelli, Manuel Ramos *

COURI Symposium Abstracts, Summer 2012

Sulfur removal in crude oil, is one of most important application when designing catalytic material to target hydrodesulphurization reactions. This particular study comprehends the quantum computational calculations for the transitional states during the HDS reaction in the molecular model of MoS₂/Co₉S₈, which is a theoretical molecular model to describe the synergic contact between both crystallographic structures. Results produced using the exchange correlation Perdew-Burke-Ernzerhof(PBE) functional indicate the existence of endothermic and exothermic transitions during the attachment of DBT molecules. In addition, it proves that promotion (addition of Co, Ni) provokes the electronic configuration of electron …

A Multi-Paradigm Modeling Framework For Modeling And Simulating Problem Situations, Christopher James Lynch

Computational Modeling & Simulation Engineering Theses & Dissertations

Problem situations are problems whose specifications are not universally agreed upon making them a challenge to be modeled and simulated. Models of problem situations depart from the premise of well-defined problems, problems where stakeholders disagree, but also modelers' interpretations play a role in their design and computer implementation.

This thesis proposes a multi-paradigm modeling framework for modeling and simulating problem situations in order to explore the problem space of the problem situations and answer specific modeling questions.

The proposed framework implements the Modeling and Simulation (M&S) System Development Framework (MS-SDF), which is a methodology for modeling a problem situation while …

Exact Soft Confidence-Weighted Learning, Jialei Wang, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

In this paper, we propose a new Soft Confidence-Weighted (SCW) online learning scheme, which enables the conventional confidence-weighted learning method to handle non-separable cases. Unlike the previous confidence-weighted learning algorithms, the proposed soft confidence-weighted learning method enjoys all the four salient properties: (i) large margin training, (ii) confidence weighting, (iii) capability to handle non-separable data, and (iv) adaptive margin. Our experimental results show that the proposed SCW algorithms significantly outperform the original CW algorithm. When comparing with a variety of state-of-the art algorithms (including AROW, NAROW and NHERD), we found that SCW generally achieves better or at least comparable predictive …