Theory and Algorithms Commons^™

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 …

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 …

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 …

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 …

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 …

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 …

On-Line Portfolio Selection With Moving Average Reversion, Bin Li, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

On-line portfolio selection has attracted increasing interests in machine learning and AI communities recently. Empirical evidences show that stock's high and low prices are temporary and stock price relatives are likely to follow the mean reversion phenomenon. While the existing mean reversion strategies are shown to achieve good empirical performance on many real datasets, they often make the single-period mean reversion assumption, which is not always satisfied in some real datasets, leading to poor performance when the assumption does not hold. To overcome the limitation, this article proposes a multiple-period mean reversion, or so-called Moving Average Reversion (MAR), and a …

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 …

Fast Bounded Online Gradient Descent Algorithms For Scalable Kernel-Based Online Learning, Peilin Zhao, Jialei Wang, Pengcheng Wu, Rong Jin, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Kernel-based online learning has often shown state-of-the-art performance for many online learning tasks. It, however, suffers from a major shortcoming, that is, the unbounded number of support vectors, making it non-scalable and unsuitable for applications with large-scale datasets. In this work, we study the problem of bounded kernel-based online learning that aims to constrain the number of support vectors by a predefined budget. Although several algorithms have been proposed in literature, they are neither computationally efficient due to their intensive budget maintenance strategy nor effective due to the use of simple Perceptron algorithm. To overcome these limitations, we propose a …

Online Kernel Selection: Algorithms And Evaluations, Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Yi, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Kernel methods have been successfully applied to many machine learning problems. Nevertheless, since the performance of kernel methods depends heavily on the type of kernels being used, identifying good kernels among a set of given kernels is important to the success of kernel methods. A straightforward approach to address this problem is cross-validation by training a separate classifier for each kernel and choosing the best kernel classifier out of them. Another approach is Multiple Kernel Learning (MKL), which aims to learn a single kernel classifier from an optimal combination of multiple kernels. However, both approaches suffer from a high computational …

Lagrangian Relaxation For Large-Scale Multi-Agent Planning, Geoffrey J. Gordon, Pradeep Varakantham, William Yeoh, Hoong Chuin Lau, Ajay Srinivasan Aravamudhan, Shih-Fen Cheng

LARC Research Publications

Multi-agent planning is a well-studied problem with applications in various areas. Due to computational constraints, existing research typically focuses either on unstructured domains with many agents, where we are content with heuristic solutions, or domains with small numbers of agents or special structure, where we can find provably near-optimal solutions. In contrast, here we focus on provably near-optimal solutions in domains with many agents, by exploiting influence limit. To that end, we make two key contributions: (a) an algorithm, based on Lagrangian relaxation and randomized rounding, for solving multi-agent planning problems represented as large mixed-integer programs; (b) a proof of …

The Intersection Between Science And Computer Science Is Almost Empty, Dick Hamlet

Systems Science Friday Noon Seminar Series

Traditionally, a science such as physics overlaps with mathematics and engineering in a way that has been astonishingly productive. The math provides precise expression for the science, which in turn supplies the engineering with the information it needs to exploit physical phenomena. Computer science naturally wishes to put itself in the center of the traditional picture as a science. Unfortunately, it won't wash. The `science' of programming is pure and simple mathematics, not science. The distinction is more than linguistic, since science and mathematics have quite distinct goals and methods. By making the wrong choice, computer science research has been …

An Evolutionary Search Paradigm That Learns With Past Experiences, Liang Feng, Yew-Soon Ong, Ivor Tsang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

A major drawback of evolutionary optimization approaches in the literature is the apparent lack of automated knowledge transfers and reuse across problems. Particularly, evolutionary optimization methods generally start a search from scratch or ground zero state, independent of how similar the given new problem of interest is to those optimized previously. In this paper, we present a study on the transfer of knowledge in the form of useful structured knowledge or latent patterns that are captured from previous experiences of problem-solving to enhance future evolutionary search. The essential contributions of our present study include the meme learning and meme selection …

Distributed Incomplete Pattern Matching Via A Novelweighted Bloom Filter, Siyuan Liu, Lei Kang, Lei Chen, Lionel Ni

Research Collection School Of Computing and Information Systems

In this paper, we first propose a very interesting and practical problem, pattern matching in a distributed mobile environment. Pattern matching is a well-known problem and extensive research has been conducted for performing effective and efficient search. However, previous proposed approaches assume that data are centrally stored, which is not the case in a mobile environment (e.g., mobile phone networks), where one person’s pattern could be separately stored in a number of different stations, and such a local pattern is incomplete compared with the global pattern. A simple solution to pattern matching over a mobile environment is to collect all …

Utilization Of Probabilistic Models In Short Read Assembly From Second-Generation Sequencing, Matthew W. Segar

Honors Theses

With the advent of cheaper and faster DNA sequencing technologies, assembly methods have greatly changed. Instead of outputting reads that are thousands of base pairs long, new sequencers parallelize the task by producing read lengths between 35 and 400 base pairs. Reconstructing an organism’s genome from these millions of reads is a computationally expensive task. Our algorithm solves this problem by organizing and indexing the reads using n-grams, which are short, fixed-length DNA sequences of length n. These n-grams are used to efficiently locate putative read joins, thereby eliminating the need to perform an exhaustive search over all possible read …

Wi-Fi Sensing Algorithms Utilizing Zigbee Rf Reciever For Use In Emergency Communications Mesh, Alexander Nelson

Computer Science and Computer Engineering Undergraduate Honors Theses

This thesis introduces the idea of a low-power Wi-Fi sensing wake-up controller for an emergency communications mesh network, progressively developing a prototype system which could be used in a live environment. Wireless network protocols are reviewed, as well as a limited view of cluster analysis, in order to introduce relevant concepts crucial to understanding this thesis. Algorithms for system implementation are developed, and pseudocode, designed to be configurable and platform independent, is given for each. Design goals for the system are identified with potential approaches are defined in order to optimize for each. An example hardware configuration is given, in …

Efficient Algorithm To Construct Phi Function In Vector Space Secret Sharing Scheme And Application Of Secret Sharing Scheme In Visual Cryptography, Sunny Potay

Masters Theses & Specialist Projects

Secret Sharing refers to a method through which a secret key K can be shared among a group of authorized participants, such that when they come together later, they can figure out the secret key K to decrypt the encrypted message. Any group which is not authorized cannot determine the secret key K. Some of the important secret schemes are Shamir Threshold Scheme, Monotone Circuit Scheme, and Brickell Vector Space Scheme. Brikell’s vector space secret sharing construction requires the existence of a function from a set of participant P in to vector space Zdp, where p is a …

Incorporating The Nsf/Tcpp Curriculum Recommendations In A Liberal Arts Setting, Akshaye Dhawan

Mathematics, Computer Science & Statistics Faculty Publications

This paper examines the integration of the NSF/TCPP Core Curriculum Recommendations in a liberal arts undergraduate setting. We examine how parallel and distributed computing concepts can be incorporated across the breadth of the undergraduate curriculum. As a model of such an integration, changes are proposed to Data Structures and Design and Analysis of Algorithms. These changes were implemented in Design and Analysis of Algorithms and the results were compared to previous iterations of that course taught by the same instructor. The student feedback received shows that the introduction of these topics made the course more engaging and conveyed an adequate …

Error Estimation Techniques To Refine Overlapping Aerial Image Mosaic Processes Via Detected Parameters, William Glenn Bond

Dissertations

In this paper, I propose to demonstrate a means of error estimation preprocessing in the assembly of overlapping aerial image mosaics. The mosaic program automatically assembles several hundred aerial images from a data set by aligning them, via image registration using a pattern search method, onto a GIS grid.

The method presented first locates the images from a data set that it predicts will not align well via the mosaic process, then it uses a correlation function, optimized by a modified Hooke and Jeeves algorithm, to provide a more optimal transformation function input to the mosaic program. Using this improved …

Framework Developmant For Construction Safety Visialization, Kishor Shrestha

College of Engineering: Graduate Celebration Programs

Throughout the history of the construction industry, many fatalities and injuries have occurred in construction sites. One of the major causes of accidents is unsafe site conditions: basically, this is due to inadequate supervision. To improve upon the traditional supervision approach, this study proposes a 'Framework Development for Construction Safety Visualization' approach. In addition to this, a computer vision Edge Detection Algorithm was developed and tested to convert construction site still images into edges of the objects in the images. The framework development of this study uses computer vision, robot vision, image compression, pattern recognition, internet transmission, network communication, and …

Adaptive Image Diffusion In Wavelet Domain, Kumar Mandava

College of Engineering: Graduate Celebration Programs

• Removing noise without sacrificing important structures
• Nonlinear strategies: Wavelet shrinkage and Nonlinear diffusion filtering based on features
• Clustering based wavelet diffusion