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Articles 1 - 30 of 44
Full-Text Articles in Theory and Algorithms
Random Automata Networks: Why Playing Dice Is Not A Vice, Christof Teuscher
Random Automata Networks: Why Playing Dice Is Not A Vice, Christof Teuscher
Systems Science Friday Noon Seminar Series
Random automata networks consist of a set of simple compute nodes interacting with each other. In this generic model, one or multiple model parameters, such as the the node interactions and/or the compute functions, are chosen at random. Random Boolean Networks (RBNs) are a particular case of discrete dynamical automata networks where both time and states are discrete. While traditional RBNs are generally credited to Stuart Kauffman (1969), who introduced them as simplified models of gene regulation, Alan Turing proposed unorganized machines as early as 1948. In this talk I will start with Alan Turing's early work on unorganized machines, …
Optimized Algorithms For Predictive Range And Knn Queries On Moving Objects, Rui Zhang, H.V. Jagadish, Bing Tian Dai, Kotagiri Ramamohanarao
Optimized Algorithms For Predictive Range And Knn Queries On Moving Objects, Rui Zhang, H.V. Jagadish, Bing Tian Dai, Kotagiri Ramamohanarao
Research Collection School Of Computing and Information Systems
There have been many studies on management of moving objects recently. Most of them try to optimize the performance of predictive window queries. However, not much attention is paid to two other important query types: the predictive range query and the predictive k nearest neighbor query. In this article, we focus on these two types of queries. The novelty of our work mainly lies in the introduction of the Transformed Minkowski Sum, which can be used to determine whether a moving bounding rectangle intersects a moving circular query region. This enables us to use the traditional tree traversal algorithms to …
Topical Summarization Of Web Videos By Visual-Text Time-Dependent Alignment, Song Tan, Hung-Khoon Tan, Chong-Wah Ngo
Topical Summarization Of Web Videos By Visual-Text Time-Dependent Alignment, Song Tan, Hung-Khoon Tan, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Search engines are used to return a long list of hundreds or even thousands of videos in response to a query topic. Efficient navigation of videos becomes difficult and users often need to painstakingly explore the search list for a gist of the search result. This paper addresses the challenge of topical summarization by providing a timeline-based visualization of videos through matching of heterogeneous sources. To overcome the so called sparse-text problem of web videos, auxiliary information from Google context is exploited. Google Trends is used to predict the milestone events of a topic. Meanwhile, the typical scenes of web …
Program Transformations For Information Personalization, Saverio Perugini, Naren Ramakrishnan
Program Transformations For Information Personalization, Saverio Perugini, Naren Ramakrishnan
Computer Science Faculty Publications
Personalization constitutes the mechanisms necessary to automatically customize information content, structure, and presentation to the end user to reduce information overload. Unlike traditional approaches to personalization, the central theme of our approach is to model a website as a program and conduct website transformation for personalization by program transformation (e.g., partial evaluation, program slicing). The goal of this paper is study personalization through a program transformation lens and develop a formal model, based on program transformations, for personalized interaction with hierarchical hypermedia. The specific research issues addressed involve identifying and developing program representations and transformations suitable for classes of hierarchical …
Economic Optimization Of Offshore Wind Farms Using The Geometric Algorithm, Mahidhar Nandigam
Economic Optimization Of Offshore Wind Farms Using The Geometric Algorithm, Mahidhar Nandigam
Electrical & Computer Engineering Theses & Dissertations
The research project related to this thesis focuses on the optimization of electrical systems for offshore wind farms for a given capacity. The optimal design and planning is a critical issue for developing cost effectively Offshore Wind Farms in energy systems. The Geometric Optimization Algorithms approach has been adopted to develop an optimization program, where the main components of the electrical system of an offshore wind farm and key technical specifications are used as parameters to be optimized for a minimum cost with necessary constraints. The effectiveness of the optimization program can be evaluated with real-time comparison between offshore wind …
Electroencephalogram Artifact Removal Using A Wavelet Neural Network, Hoang-Anh T. Nguyen
Electroencephalogram Artifact Removal Using A Wavelet Neural Network, Hoang-Anh T. Nguyen
Electrical & Computer Engineering Theses & Dissertations
A wavelet neural network (WNN) technique rs developed for electroencephalogram (EEG) artifact removal without electrooculographic (EOG) recordings. The algorithm combines the universal approximation characteristics of neural networks and the time/frequency property of wavelet, where the neural network was trained on a simulated dataset with known ground truths. The contribution of this thesis is two-fold. First, many EEG artifact removal algorithms, including regression based methods, require reference EOG signals, which are not always available. To remove EEG ai1ifacts, a WNN tries to learn the characteristics of the artifacts first and does not need reference EOG signals once trained. Second, WNNs are …
A Hoare Calculus For Graph Programs, Christopher M. Poskitt, Detlef Plump
A Hoare Calculus For Graph Programs, Christopher M. Poskitt, Detlef Plump
Research Collection School Of Computing and Information Systems
We present Hoare-style axiom schemata and inference rules for verifying the partial correctness of programs in the graph programming language GP. The pre- and postconditions of this calculus are the nested conditions of Habel, Pennemann and Rensink, extended with expressions for labels in order to deal with GP’s conditional rule schemata and infinite label alphabet. We show that the proof rules are sound with respect to GP’s operational semantics.
Hoare Logic For Graph Programs, Christopher M. Poskitt, Detlef Plump
Hoare Logic For Graph Programs, Christopher M. Poskitt, Detlef Plump
Research Collection School Of Computing and Information Systems
We present a new approach for verifying programs written in GP (for Graph Programs), an experimental programming language for performing computations on graphs at a high level of abstraction. Taking a labelled graph as input, a graph program nondeterministically applies to it a number of graph transformation rules, directed by simple control constructs such as sequential composition and as-long-as-possible iteration. We adapt classical Hoare logic to the domain of graphs, and describe a system of sound proof rules for showing the partial correctness of graph programs.
Merging Schemas In A Collaborative Faceted Classification System, Jianxiang Li
Merging Schemas In A Collaborative Faceted Classification System, Jianxiang Li
Computer Science Theses & Dissertations
We have developed a system that improves access to a large, growing image collection by allowing users to collaboratively build a global faceted (multi-perspective) classification schema. We are extending our system to support both global and local schemas, where global schema provides a complete and uniform view of the collection whereas local schema provides a personal, possibly incomplete and idiosyncratic view of the collection. We argue that although users usually focus on their personal schemas, it is still desirable to have a global schema for the entire collection even if such local schemas are available. In order to keep the …
Cloud Storage And Online Bin Packing, Swathi Venigella
Cloud Storage And Online Bin Packing, Swathi Venigella
UNLV Theses, Dissertations, Professional Papers, and Capstones
Cloud storage is the service provided by some corporations (such as Mozy and Carbonite) to store and backup computer files. We study the problem of allocating memory of servers in a data center based on online requests for storage. Over-the-net data backup has become increasingly easy and cheap due to cloud storage. Given an online sequence of storage requests and a cost associated with serving the request by allocating space on a certain server one seeks to select the minimum number of servers as to minimize total cost. We use two different algorithms and propose a third algorithm; we show …
Detours Admitting Short Paths, Reshma Koganti
Detours Admitting Short Paths, Reshma Koganti
UNLV Theses, Dissertations, Professional Papers, and Capstones
Finding shortest paths between two vertices in a weighted graph is a well explored problem and several efficient algorithms for solving it have been reported. We propose a new variation of this problem which we call the Detour Admitting Shortest Path Problem (DASPP).We present an efficient algorithm for solving DASPP. This is the first algorithm that constructs a shortest path such that each edge of the shortest path admits a detour with no more than k−hops. This algorithm has important applications in transportation networks. We also present implementation issues for the detour admitting shortest path algorithm.
Semi-Supervised Distance Metric Learning For Collaborative Image Retrieval And Clustering, Steven C. H. Hoi, Wei Liu, Shih-Fu Chang
Semi-Supervised Distance Metric Learning For Collaborative Image Retrieval And Clustering, Steven C. H. Hoi, Wei Liu, Shih-Fu Chang
Research Collection School Of Computing and Information Systems
Learning a good distance metric plays a vital role in many multimedia retrieval and data mining tasks. For example, a typical content-based image retrieval (CBIR) system often relies on an effective distance metric to measure similarity between any two images. Conventional CBIR systems simply adopting Euclidean distance metric often fail to return satisfactory results mainly due to the well-known semantic gap challenge. In this article, we present a novel framework of Semi-Supervised Distance Metric Learning for learning effective distance metrics by exploring the historical relevance feedback log data of a CBIR system and utilizing unlabeled data when log data are …
On Decision Support For Deliberating With Constraints In Constrained Optimization Models, Steven O. Kimbrough, Ann Kuo, Hoong Chuin Lau, David H. Wood
On Decision Support For Deliberating With Constraints In Constrained Optimization Models, Steven O. Kimbrough, Ann Kuo, Hoong Chuin Lau, David H. Wood
Research Collection School Of Computing and Information Systems
This paper introduces the Deliberation Decision Support System (DDSS). The DDSS obtains heuristically (using a genetic algorithm) solutions of interest for constrained optimization models. This is illustrated, without loss of generality, by generalized assignment problems. The DDSS also provides users with graphical tools that support post-solution deliberation for constrained optimization models. The DDSS and this paper, as befits practical concerns, are focused on deliberation with respect to the constraints of the models being used.
A First Practical Algorithm For High Levels Of Relational Consistency, Shant Karakashian, Robert J. Woodward, Christopher Reesons, Berthe Y. Choueiry, Christian Bessiere
A First Practical Algorithm For High Levels Of Relational Consistency, Shant Karakashian, Robert J. Woodward, Christopher Reesons, Berthe Y. Choueiry, Christian Bessiere
School of Computing: Conference and Workshop Papers
Consistency properties and algorithms for achieving them are at the heart of the success of Constraint Programming. In this paper, we study the relational consistency property R(∗,m)C, which is equivalent to m-wise consistency proposed in relational databases. We also define wR(∗,m)C, a weaker variant of this property. We propose an algorithm for enforcing these properties on a Constraint Satisfaction Problem by tightening the existing relations and without introducing new ones. We empirically show that wR(∗,m)C solves in a backtrack-free manner all the instances of some CSP benchmark classes, thus hinting at the tractability of those classes.
Action Recognition Based On Multi-Level Representation Of 3d Shape, Binu M. Nair
Action Recognition Based On Multi-Level Representation Of 3d Shape, Binu M. Nair
Electrical & Computer Engineering Theses & Dissertations
A novel algorithm is proposed in this thesis for recognizing human actions using a combination of two shape descriptors, one of which is a 3D Euclidean distance transform and the other based on the Radon transform. This combination captures the necessary variations from the space time shape for recognizing actions. The space time shapes are created by the concatenation of human body silhouettes across time. The comparisons are done against some common shape descriptors such as the zernike moments and Radon transform. This is also compared with an algorithm which uses the same concept of a space time shape and …
A Differential Absorption Model For Remote Sensing Of Atmospheric Pressure, Shivam J. Shah
A Differential Absorption Model For Remote Sensing Of Atmospheric Pressure, Shivam J. Shah
Electrical & Computer Engineering Theses & Dissertations
The goal of the project is to develop and test a "model based" radar processing strategy that is compatible with the concept of a "cognitive radar". The basic approach will be to develop a cognitive radar algorithm (genetic algorithm) based on the capabilities of an existing commercially available Software Radio. While the focus of this effort is the development of a candidate approach for genetic algorithm, the longer term goal would be to implement the approach using this software radio technology to provide a low cost radar processor. The proposed technology would use differential absorption radar working at the 50-56 …
An Application Of Automated Theorem Provers To Computer System Security: The Schematic Protection Model, Mitchell D.I. Hirschfeld
An Application Of Automated Theorem Provers To Computer System Security: The Schematic Protection Model, Mitchell D.I. Hirschfeld
Theses and Dissertations
The Schematic Protection Model is specified in SAL and theorems about Take-Grant and New Technology File System schemes are proven. Arbitrary systems can be specified in SPM and analyzed. This is the first known automated analysis of SPM specifications in a theorem prover. The SPM specification was created in such a way that new specifications share the underlying framework and are configurable within the specifications file alone. This allows new specifications to be created with ease as demonstrated by the four unique models included within this document. This also allows future users to more easily specify models without recreating the …
Information Hiding Using Stochastic Diffusion For The Covert Transmission Of Encrypted Images, Jonathan Blackledge
Information Hiding Using Stochastic Diffusion For The Covert Transmission Of Encrypted Images, Jonathan Blackledge
Conference papers
A principal weakness of all encryption systems is that the output data can be `seen' to be encrypted. In other words, encrypted data provides a 'flag' on the potential value of the information that has been encrypted. In this paper, we provide a novel approach to `hiding' encrypted data in a digital image. We consider an approach in which a plaintext image is encrypted with a cipher using the processes of `stochastic diffusion' and the output quantized into a 1-bit array generating a binary image cipher-text. This output is then `embedded' in a host image which is undertaken either in …
Generating Compact Wasp Nest Structures Via Minimal Complexity Algorithms., Fadel Ewusi Kofi Adoe
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
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
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
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 …
Expression Invariant Face Recognition Using Shifted Phase-Encoded Joint Transform Correlation Technique, Trisha Ahmed
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 …
Finding Influentials Based On The Temporal Order Of Information Adoption In Twitter, Changhyun Lee, Haewoon Kwak, Hosung Park, Sue Moon
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.
Evolutionary Artificial Neural Network Weight Tuning To Optimize Decision Making For An Abstract Game, Corey M. Miller
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 …
Handshaking Protocols And Jamming Mechanisms For Blind Rendezvous In A Dynamic Spectrum Access Environment, Aaron A. Gross
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
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 …
Frequency Diverse Array Radar: Signal Characterization And Measurement Accuracy, Steven H. Brady
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
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
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 …