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Inductive Inference Of Languages From Samplings, Sanjay Jain, Efim Kinber 2010 National University of Singapore

Inductive Inference Of Languages From Samplings, Sanjay Jain, Efim Kinber

School of Computer Science & Engineering Faculty Publications

We introduce, discuss, and study a model for inductive inference from samplings, formalizing an idea of learning different “projections” of languages. One set of our results addresses the problem of finding a uniform learner for all samplings of a language from a certain set when learners for particular samplings are available. Another set of results deals with extending learnability from a large natural set of samplings to larger sets. A number of open problems is formulated.


A Comparative Analysis Of Ascii And Xml Logging Systems, Eric C. Hanington 2010 Air Force Institute of Technology

A Comparative Analysis Of Ascii And Xml Logging Systems, Eric C. Hanington

Theses and Dissertations

This research compares XML and ASCII based event logging systems in terms of their storage and processing efficiency. XML has been an emerging technology, even for security. Therefore, it is researched as a logging system with the mitigation of its verbosity. Each system consists of source content, the network transmission, database storage, and querying which are all studied as individual parts. The ASCII logging system consists of the text file as source, FTP as transport, and a relational database system for storage and querying. The XML system has the XML files and XML files in binary form using Efficient XML …


Developing Model Checkers Using Pat, Yang LIU, Jun SUN, Jin Song DONG 2010 Singapore Management University

Developing Model Checkers Using Pat, Yang Liu, Jun Sun, Jin Song Dong

Research Collection School Of Computing and Information Systems

During the last two decades, model checking has emerged as an effective system analysis technique complementary to simulation and testing. Many model checking algorithms and state space reduction techniques have been proposed. Although it is desirable to have dedicated model checkers for every language (or application domain), implementing one with effective reduction techniques is rather challenging. In this work, we present a generic and extensible framework PAT, which facilitates users to build customized model checkers. PAT provides a library of state-of-art model checking algorithms as well as support for customizing language syntax, semantics, state space reduction techniques, graphic user interfaces, …


Enumeration Refactoring: A Tool For Automatically Converting Java Constants To Enumerated Types, Raffi Khatchadourian, Benjamin Muskalla 2010 CUNY Hunter College

Enumeration Refactoring: A Tool For Automatically Converting Java Constants To Enumerated Types, Raffi Khatchadourian, Benjamin Muskalla

Publications and Research

Java 5 introduces several new features that significantly improve older Java technology. We consider the new enum construct, which provides language support for enumerated types. Before Java 5, programmers needed to employ various patterns to compensate for the absence of enumerated types in Java. Unfortunately, these compensation patterns lack several highly desirable properties of the enum construct, notably type-safety. We demonstrate an automated refactoring tool called Convert Constants to Enum for transforming legacy Java code to use the new enumeration construct. An interprocedural type inferencing algorithm that tracks the flow of enumerated values drives the approach, and the tool is …


Visual Occam: High Level Visualization And Design Of Process Networks, Mikolaj M. Slomka 2010 University of Nevada, Las Vegas

Visual Occam: High Level Visualization And Design Of Process Networks, Mikolaj M. Slomka

UNLV Theses, Dissertations, Professional Papers, and Capstones

With networks, multiprocessors, and multi-threaded systems becoming more common in our world it is increasingly evident that concurrent programming is not something to be ignored or marginalized even though many takes on concurrency (mainly by means of monitors or shared resources) have proven to be difficult to deal with on large scales. Thankfully, a good deal of work has already been done to combat this, through CSP, occam, and other such derivatives, to produce a scalable process oriented paradigm. Still, it is cumbersome to attempt to deal with the intricacies of such communicating networks down to every minutia; if, instead, …


The Executable Command In Support Of Scheduled Subroutine Calls, Andrew Scott Lewis 2010 Old Dominion University

The Executable Command In Support Of Scheduled Subroutine Calls, Andrew Scott Lewis

Electrical & Computer Engineering Theses & Dissertations

A potential solution to improving the utilization of increased thread level parallelism available in modern general purpose CPU's is the inclusion of a hardware scheduler. The hardware scheduler is designed to schedule subroutine calls based on a numerical condition in a high performance memory located on the CPU die, due to which the size of available memory is extremely limited. The main stumbling block in the development of a feasible hardware scheduler is the lack of a method of invoking a scheduled call using a single pointer. The use of a single pointer allows the limited size of the memory …


Glmperm: A Permutation Of Regressor Residuals Test For Inference In Generalized Linear Models, Wiebke Werft, Axel Benner 2010 German Cancer Research Center

Glmperm: A Permutation Of Regressor Residuals Test For Inference In Generalized Linear Models, Wiebke Werft, Axel Benner

The R Journal

We introduce a new R package called glmperm for inference in generalized linear models especially for small and moderate-sized data sets. The inference is based on the per mutation of regressor residuals test introduced by Potter (2005). The implementation of glmperm outperforms currently available permutation test software as glmperm can be applied in situations where more than one covariate is involved.


Tmvtnorm: A Package For The Truncated Multivariate Normal Distribution, Stefan Wilhelm, B. G. Manjunath 2010 University of Basel

Tmvtnorm: A Package For The Truncated Multivariate Normal Distribution, Stefan Wilhelm, B. G. Manjunath

The R Journal

In this article we present tmvtnorm, an R package implementation for the truncated multivariate normal distribution. We consider random number generation with rejection and Gibbs sampling, computation of marginal densities as well as computation of the mean and co variance of the truncated variables. This contribution brings together latest research in this field and provides useful methods for both scholars and practitioners when working with truncated normal variables.


Two-Sided Exact Tests And Matching Confidence Intervals For Discrete Data, Michael P. Fay 2010 National Institute of Allergy and Infectious Diseases

Two-Sided Exact Tests And Matching Confidence Intervals For Discrete Data, Michael P. Fay

The R Journal

There is an inherent relationship between two-sided hypothesis tests and confidence intervals. A series of two-sided hypothesis tests may be inverted to obtain the matching 100(1-)% confidence interval defined as the smallest interval that contains all point null parameter values that would not be rejected at the α level. Unfortunately, for discrete data there are several different ways of defining two-sided exact tests and the most commonly used two sided exact tests are defined one way, while the most commonly used exact confidence intervals are inversions of tests defined another way. This can lead to inconsistencies where the exact test …


Neuralnet: Training Of Neural Networks, Franke Günther, Stefan Fritsch 2010 University of Bremen

Neuralnet: Training Of Neural Networks, Franke Günther, Stefan Fritsch

The R Journal

Artificial neural networks are applied in many situations. neuralnet is built to train multi-layer perceptrons in the context of regression analyses, i.e. to approximate functional relationships between covariates and response variables. Thus, neural networks are used as extensions of generalized linear models. neuralnet is a very flexible package. The back propagation algorithm and three versions of resilient back-propagation are implemented and it provides a custom-choice of activation and error function. An arbitrary number of covariates and response variables as well as of hidden layers can theoretically be included. The paper gives a brief introduction to multi-layer perceptrons and resilient back-propagation …


Mcmc For Generalized Linear Mixed Models With Glmmbugs, Patrick Brown, Lutong Zhou 2010 University of Toronto, and Cancer Care Ontario

Mcmc For Generalized Linear Mixed Models With Glmmbugs, Patrick Brown, Lutong Zhou

The R Journal

The glmmBUGS package is a bridging tool between Generalized Linear Mixed Models (GLMMs) in R and the BUGS language. It provides a simple way of performing Bayesian inference using Markov Chain Monte Carlo (MCMC) methods, taking a model formula and data frame in R and writing a BUGS model file, data file, and initial values files. Functions are provided to reformat and summarize the BUGS results. A key aim of the package is to provide files and objects that can be modified prior to calling BUGS, giving users a platform for customizing and extending the models to accommodate a wide …


Max Flow Spill Code Placement Algorithm Implemented In Gcc 4.4.3, Stephen Robert Beard 2010 CaliforniaPolytechnic State University - San Luis Obispo

Max Flow Spill Code Placement Algorithm Implemented In Gcc 4.4.3, Stephen Robert Beard

Computer Engineering

The placement of spill code plays an important role in the register allocator of an optimizing compiler. Many computer architectures possess a register linkage convention that dictates which registers are preserved across function calls and which are not. This project addresses the problem of optimizing spill code that is associated with register linkage conventions.

This algorithm was created by Dr. Chris Lupo and is described in the paper Beyond Register Allocation: a Novel Algorithm for Spill-Code Placement. The algorithm was implemented for GCC 2.5.7 for a PA-RISC architecture [4]. The work in this project will involve porting the existing code …


The R Journal (June 2010) 2(1): Complete Issue, The R Foundation 2010 University of Nebraska - Lincoln

The R Journal (June 2010) 2(1): Complete Issue, The R Foundation

The R Journal

Contributed Research Articles

IsoGene: An R Package for Analyzing Dose-response Studies in Microarray Experiments, Setia Pramana, Dan Lin, Philippe Haldermans, Ziv Shkedy, Tobias Verbeke, Hinrich Göhlmann, An De Bondt, Willem Talloen, and Luc Bijnens

MCMC for Generalized Linear Mixed Models with glmmBUGS, Patrick Brown and Lutong Zhou

Mapping and Measuring Country Shapes, Nils B. Weidmann and Kristian Skrede Gleditsch

tmvtnorm: A Package for the Truncated Multivariate Normal Distribution, Stefan Wilhelm and B. G. Manjunath

neuralnet: Training of Neural Networks, Frauke Günther and Stefan Fritsch

glmperm: A Permutation of Regressor Residuals Test for Inference in Generalized Linear Models, Wiebke Werft and …


Isogene: An R Package For Analyzing Dose-Response Studies In Microarray Experiments, Setia Pramana, Dan Lin, Philippe Haldermans, Ziv Shkedy, Tobias Verbeke, Hinrich Göhlmann, An De Bondt, Williem Talloen, Luc Bijnens 2010 Universiteit Hasselt

Isogene: An R Package For Analyzing Dose-Response Studies In Microarray Experiments, Setia Pramana, Dan Lin, Philippe Haldermans, Ziv Shkedy, Tobias Verbeke, Hinrich Göhlmann, An De Bondt, Williem Talloen, Luc Bijnens

The R Journal

IsoGene is an R package for the analysis of dose-response microarray experiments to identify gene or subsets of genes with a mono tone relationship between the gene expression and the doses. Several testing procedures (i.e., the likelihood ratio test, Williams, Marcus, the M, and Modified M), that take into account the order restriction of the means with respect to the increasing doses are implemented in the package. The inference is based on resampling methods, both permutations and the Significance Analysis of Microarrays (SAM).


Guppie: A Coordination Framework For Parallel Processing Using Shared Memory Featuring A Master-Worker Relationship, Sean Christopher McCarthy 2010 University of Southern Mississippi

Guppie: A Coordination Framework For Parallel Processing Using Shared Memory Featuring A Master-Worker Relationship, Sean Christopher Mccarthy

Dissertations

Most programs can be parallelized to some extent. The processing power available in computers today makes parallel computing more desirable and attainable than ever before. Many machines today have multiple processors or multiple processing cores making parallel computing more available locally, as well as over a network. In order for parallel applications to be written, they require a computing language, such as C++, and a coordination language (or library), such as Linda. This research involves the creation and implementation of a coordination framework, Guppie, which is easy to use, similar to Linda, but provides more efficiency when dealing with large …


Information Cost Tradeoffs For Augmented Index And Streaming Language Recognition, Amit Chakrabarti, Graham Cormode, Ranganath Kondapally, Andrew McGregor 2010 Dartmouth College

Information Cost Tradeoffs For Augmented Index And Streaming Language Recognition, Amit Chakrabarti, Graham Cormode, Ranganath Kondapally, Andrew Mcgregor

Dartmouth Scholarship

This paper makes three main contributions to the theory of communication complexity and stream computation. First, we present new bounds on the information complexity of AUGMENTED-INDEX. In contrast to analogous results for INDEX by Jain, Radhakrishnan and Sen [J. ACM, 2009], we have to overcome the significant technical challenge that protocols for AUGMENTED-INDEX may violate the “rectangle property” due to the inherent input sharing. Second, we use these bounds to resolve an open problem of Magniez, Mathieu and Nayak [STOC, 2010] that asked about the multi-pass complexity of recognizing Dyck languages. This results in a natural separation between the standard …


Detecting Malicious Javascript, Matthew F. Der 2010 University of Richmond

Detecting Malicious Javascript, Matthew F. Der

Honors Theses

The increased use of the World Wide Web and JavaScript as a scripting language for Web pages have made JavaScript a popular attack vector for infecting users' machines with malware. Additionally, attackers often obfuscate their code to avoid detection, which heightens the challenge and complexity of automated defense systems. We present two analyses of malicious scripts and suggest how they could be extended into intrusion detection systems. For our analyses we use a sample of deobfuscated malicious and benign scripts collected from actual Web sites. First, using our malicious sample, we perform a manual analysis of attack signatures, identifying four …


A Verification System For Interval-Based Specification Languages, Chunqing CHEN, Jin Song DONG, Jun SUN, Andrew P. MARTIN 2010 Singapore Management University

A Verification System For Interval-Based Specification Languages, Chunqing Chen, Jin Song Dong, Jun Sun, Andrew P. Martin

Research Collection School Of Computing and Information Systems

Interval-based specification languages have been used to formally model and rigorously reason about real-time computing systems. This usually involves logical reasoning and mathematical computation with respect to continuous or discrete time. When these systems are complex, analyzing their models by hand becomes error-prone and difficult. In this article, we develop a verification system to facilitate the formal analysis of interval-based specification languages with machine-assisted proof support. The verification system is developed using a generic theorem prover, Prototype Verification System (PVS). Our system elaborately encodes a highly expressive set-based notation, Timed Interval Calculus (TIC), and can rigorously carry out the verification …


Creating An Immersive Game World With Evolutionary Fuzzy Cognitive Maps, Yundong CAI, Ah-hwee TAN, Zhiqi SHEN, Boyang LI 2010 Singapore Management University

Creating An Immersive Game World With Evolutionary Fuzzy Cognitive Maps, Yundong Cai, Ah-Hwee Tan, Zhiqi Shen, Boyang Li

Research Collection School Of Computing and Information Systems

An increasing number of serious games have been developed to enhance the user experiences in education and training. In order to bridge the gap of game experiences in the virtual environment and in the real life, it is crucial to generate believable characters and contexts in real-time. However, the variables to be simulated for a large-scale serious game are numerous. These variables are involved in complex causal relationships and their values change over time. In view that world modeling has not been well addressed with conventional models, this paper uses a computational model Evolutionary Fuzzy Cognitive Map (EFCM) to model …


Design Of A Software Framework Prototype For Scientific Model Interoperability, Eric Fritzinger, Sohei Okamoto 2010 University of Nevada Reno

Design Of A Software Framework Prototype For Scientific Model Interoperability, Eric Fritzinger, Sohei Okamoto

2010 Annual Nevada NSF EPSCoR Climate Change Conference

19 PowerPoint slides Session 2: Infrastructure Convener: Sergiu Dascalu, UNR Abstract: -What are models? -Mathematical models used to describe a system -E.g. Atmospheric, Oceanic, Ecological, etc… -Algorithmic calculations which take input and produce estimated results -Weather forecasting, global warming predictions, sea level estimations, etc… -Models are invaluable


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