Advanced Topics On State Complexity Of Combined Operations,
2010
The University of Western Ontario
Advanced Topics On State Complexity Of Combined Operations, Yuan Gao
Electronic Thesis and Dissertation Repository
State complexity is a fundamental topic in formal languages and automata theory. The study of state complexity is also strongly motivated by applications of finite automata in software engineering, programming languages, natural language and speech processing and other practical areas. Since many of these applications use automata of large sizes, it is important to know the number of states of the automata. In this thesis, we firstly discuss the state complexities of individual operations on regular languages, including union, intersection, star, catenation, reversal and so on. The state complexity of an operation on unary languages is usually different from that …
Random Automata Networks: Why Playing Dice Is Not A Vice,
2010
Portland State University
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, …
Topical Summarization Of Web Videos By Visual-Text Time-Dependent Alignment,
2010
Singapore Management University
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 …
Optimized Algorithms For Predictive Range And Knn Queries On Moving Objects,
2010
Singapore Management University
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 …
Distributed Energy-Conserving Routing Protocols,
2010
Dartmouth College
Distributed Energy-Conserving Routing Protocols, Qun Li, Javed A. Aslam, Daniela Rus
Javed A. Aslam
This paper discusses several distributed power-aware routing protocols in wireless ad-hoc networks (especially sensor networks). We seek to optimize the lifetime of the network. We have developed three distributed power-aware algorithms and analyzed their efficiency in terms of the number of message broadcasts and the overall network lifetime modeled as the time to the first message that can not be sent. These are: (1) a distributed min Power algorithm (modeled on a distributed version of Dijkstra's algorithm), (2) a distributed max-min algorithm, and (3) the distributed version of our the centralized online max-min zPmin algorithm presented in [12]. The first …
Morphogrammatics Of Reflection,
2010
ThinkArt Lab Glasgow
Morphogrammatics Of Reflection, Rudolf Kaehr
Rudolf Kaehr
Turning back from the studies of morphogrammatics to some open questions of reflectional programming, the recountered problematics might be put into a different light and new methods of handling formal aspects of reflection and reflectionality shall be introduced. Albeit the use of light-metaphors, morphogrammatic reflection is not sketched along the paradigm of optical metaphors. Morphograms are presenting neither propositions nor perceptions able for mirroring (representation). Exercises in defining morphogrammatic retro-grade recursion and reflection schemata are continued from the paper “Sketches to Morphogrammatic Programming”.
Adaptive Algorithms For Coverage Control And Space Partitioning In Mobile Robotic Networks,
2010
University of Pennsylvania
Adaptive Algorithms For Coverage Control And Space Partitioning In Mobile Robotic Networks, Jerome Le Ny, George J. Pappas
Technical Reports (ESE)
We consider deployment problems where a mobile robotic network must optimize its configuration in a distributed way in order to minimize a steady-state cost function that depends on the spatial distribution of certain probabilistic events of interest. Three classes of problems are discussed in detail: coverage control problems, spatial partitioning problems, and dynamic vehicle routing problems. Moreover, we assume that the event distribution is a priori unknown, and can only be progressively inferred from the observation of the location of the actual event occurrences. For each problem we present distributed stochastic gradient algorithms that optimize the performance objective. The stochastic …
Program Transformations For Information Personalization,
2010
University of Dayton
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 …
A Hoare Calculus For Graph Programs,
2010
Singapore Management University
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.
Cloud Storage And Online Bin Packing,
2010
University of Nevada, Las Vegas
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 …
The Maximum Clique Problem: Algorithms, Applications, And Implementations,
2010
University of Tennessee, Knoxville
The Maximum Clique Problem: Algorithms, Applications, And Implementations, John David Eblen
Doctoral Dissertations
Computationally hard problems are routinely encountered during the course of solving practical problems. This is commonly dealt with by settling for less than optimal solutions, through the use of heuristics or approximation algorithms. This dissertation examines the alternate possibility of solving such problems exactly, through a detailed study of one particular problem, the maximum clique problem. It discusses algorithms, implementations, and the application of maximum clique results to real-world problems. First, the theoretical roots of the algorithmic method employed are discussed. Then a practical approach is described, which separates out important algorithmic decisions so that the algorithm can be easily …
On Decision Support For Deliberating With Constraints In Constrained Optimization Models,
2010
Singapore Management University
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.
Hoare Logic For Graph Programs,
2010
Singapore Management University
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.
Semi-Supervised Distance Metric Learning For Collaborative Image Retrieval And Clustering,
2010
Singapore Management University
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 …
A Review Of Procedures To Evolve Quantum Algorithms,
2010
Bond University
A Review Of Procedures To Evolve Quantum Algorithms, Adrian Gepp, Phil Stocks
Adrian Gepp
There exist quantum algorithms that are more efficient than their classical counterparts; such algorithms were invented by Shor in 1994 and then Grover in 1996. A lack of invention since Grover’s algorithm has been commonly attributed to the non-intuitive nature of quantum algorithms to the classically trained person. Thus, the idea of using computers to automatically generate quantum algorithms based on an evolutionary model emerged. A limitation of this approach is that quantum computers do not yet exist and quantum simulation on a classical machine has an exponential order overhead. Nevertheless, early research into evolving quantum algorithms has shown promise. …
Business Failure Prediction Using Survival Analysis,
2010
Bond University
Business Failure Prediction Using Survival Analysis, Kuldeep Kumar, Adrian Gepp
Adrian Gepp
Accurate business failure prediction models would be extremely valuable to many industry sectors, particularly in financial investment and lending. Recently, there has been a significant increase in interest in business failure prediction, from both industry and academia. Statistical business failure prediction models attempt to predict the failure or success of a business. Discriminant and logit analyses have been the most popular approaches, but there are also a large number of alternative techniques available. In this paper, a comparatively new technique known as survival analysis has been used for business failure prediction. Overall, the results suggest that survival analysis techniques provide …
A First Practical Algorithm For High Levels Of Relational Consistency,
2010
University of Nebraska-Lincoln
A First Practical Algorithm For High Levels Of Relational Consistency, Shant Karakashian, Robert J. Woodward, Christopher Reesons, Berthe Y. Choueiry, Christian Bessiere
CSE 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.
An Application Of Automated Theorem Provers To Computer System Security: The Schematic Protection Model,
2010
Air Force Institute of Technology
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,
2010
Technological University Dublin
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.,
2010
East Tennessee State University
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 …
