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Articles 31 - 47 of 47
Full-Text Articles in Theory and Algorithms
Prostate Segmentation On Pelvic Ct Images Using A Genetic Algorithm, Payel Ghosh, Melanie Mitchell
Prostate Segmentation On Pelvic Ct Images Using A Genetic Algorithm, Payel Ghosh, Melanie Mitchell
Computer Science Faculty Publications and Presentations
A genetic algorithm (GA) for automating the segmentation of the prostate on pelvic computed tomography (CT) images is presented here. The images consist of slices from three-dimensional CT scans. Segmentation is typically performed manually on these images for treatment planning by an expert physician, who uses the “learned” knowledge of organ shapes, textures and locations to draw a contour around the prostate. Using a GA brings the flexibility to incorporate new “learned” information into the segmentation process without modifying the fitness function that is used to train the GA. Currently the GA uses prior knowledge in the form of texture …
Traffic Analysis Of Udp-Based Flows In Ourmon, Jim Binkley, Divya Parekh
Traffic Analysis Of Udp-Based Flows In Ourmon, Jim Binkley, Divya Parekh
Computer Science Faculty Publications and Presentations
We present a custom UDP flow tuple with an IP address key and a set of simple related statistical attributes. Attributes are used to calculate a per host metric called the UDP work weight which roughly measures the amount of network noise caused by a host. The work weight is used to produce a near real-time sorted top N report for UDP host tuples. We also present a derived attribute based on an algorithm called the UDP guesstimator. The UDP guesstimator roughly classifies port report hosts into various traffic categories including security threats (DOS/scanning) or P2P hosts based on high …
Rcu Semantics: A First Attempt, Paul E. Mckenney, Jonathan Walpole
Rcu Semantics: A First Attempt, Paul E. Mckenney, Jonathan Walpole
Computer Science Faculty Publications and Presentations
There is not yet a formal statement of RCU (read-copy update) semantics. While this lack has thus far not been an impediment to adoption and use of RCU, it is quite possible that formal semantics would point the way towards tools that automatically validate uses of RCU or that permit RCU algorithms to be automatically generated by a parallel compiler. This paper is a first attempt to supply a formal definition of RCU. Or at least a semi-formal definition: although RCU does not yet wear a tux (though it does run in Linux), at least it might yet wear some …
Toward A Sound Integration Of Isabelle With A Combined Decision Procedure, Tom Harke
Toward A Sound Integration Of Isabelle With A Combined Decision Procedure, Tom Harke
Computer Science Faculty Publications and Presentations
I present work on a project to integrate Isabelle, an extremely versatile interactive proof assistant, with a combined decision procedure, the Cooperating Validity Checker (CVC). Isabelle is sound and flexible, however it is often tedious to use. CVC is fully automatic, but only handles decision problems expressible over a relatively weak set of theories including linear arithmetic, uninterpreted functions, data types, and firstorder quantifier-free logic. My goal is to increase the amount of automation in Isabelle, by making it use CVC as an oracle for such problems, but without compromising Isabelle’s soundness.
In this paper I report on the progress …
Reconstructability Analysis With Fourier Transforms, Martin Zwick
Reconstructability Analysis With Fourier Transforms, Martin Zwick
Complex Systems Faculty Publications and Presentations
Fourier methods used in two‐ and three‐dimensional image reconstruction can be used also in reconstructability analysis (RA). These methods maximize a variance‐type measure instead of information‐theoretic uncertainty, but the two measures are roughly collinear and the Fourier approach yields results close to that of standard RA. The Fourier method, however, does not require iterative calculations for models with loops. Moreover, the error in Fourier RA models can be assessed without actually generating the full probability distributions of the models; calculations scale with the size of the data rather than the state space. State‐based modeling using the Fourier approach is also …
Directed Extended Dependency Analysis For Data Mining, Thaddeus T. Shannon, Martin Zwick
Directed Extended Dependency Analysis For Data Mining, Thaddeus T. Shannon, Martin Zwick
Complex Systems Faculty Publications and Presentations
Extended dependency analysis (EDA) is a heuristic search technique for finding significant relationships between nominal variables in large data sets. The directed version of EDA searches for maximally predictive sets of independent variables with respect to a target dependent variable. The original implementation of EDA was an extension of reconstructability analysis. Our new implementation adds a variety of statistical significance tests at each decision point that allow the user to tailor the algorithm to a particular objective. It also utilizes data structures appropriate for the sparse data sets customary in contemporary data mining problems. Two examples that illustrate different approaches …
An Overview Of Reconstructability Analysis, Martin Zwick
An Overview Of Reconstructability Analysis, Martin Zwick
Complex Systems Faculty Publications and Presentations
This paper is an overview of reconstructability analysis (RA), a discrete multivariate modeling methodology developed in the systems literature; an earlier version of this tutorial is Zwick (2001). RA was derived from Ashby (1964), and was developed by Broekstra, Cavallo, Cellier Conant, Jones, Klir, Krippendorff, and others (Klir, 1986, 1996). RA resembles and partially overlaps log‐line (LL) statistical methods used in the social sciences (Bishop et al., 1978; Knoke and Burke, 1980). RA also resembles and overlaps methods used in logic design and machine learning (LDL) in electrical and computer engineering (e.g. Perkowski et al., 1997). Applications of RA, like …
Reconstructability Analysis Detection Of Optimal Gene Order In Genetic Algorithms, Martin Zwick, Stephen Shervais
Reconstructability Analysis Detection Of Optimal Gene Order In Genetic Algorithms, Martin Zwick, Stephen Shervais
Complex Systems Faculty Publications and Presentations
The building block hypothesis implies that genetic algorithm efficiency will be improved if sets of genes that improve fitness through epistatic interaction are near to one another on the chromosome. We demonstrate this effect with a simple problem, and show that information-theoretic reconstructability analysis can be used to decide on optimal gene ordering.
Ordering Genetic Algorithm Genomes With Reconstructability Analysis, Stephen Shervais, Martin Zwick
Ordering Genetic Algorithm Genomes With Reconstructability Analysis, Stephen Shervais, Martin Zwick
Complex Systems Faculty Publications and Presentations
The building block hypothesis implies that genetic algorithm effectiveness is influenced by the relative location of epistatic genes on the chromosome. We find that this influence exists, but depends on the generation in which it is measured. Early in the search process it may be more effective to have epistatic genes widely separated. Late in the search process, effectiveness is improved when they are close together. The early search effect is weak but still statistically significant; the late search effect is much stronger and plainly visible. We demonstrate both effects with a set of simple problems, and show that infonnation-theoretic …
Investigation Of Image Feature Extraction By A Genetic Algorithm, Steven P. Brumby, James P. Theiler, Simon J. Perkins, Neal R. Harvey, John J. Szymanski, Jeffrey J. Bloch, Melanie Mitchell
Investigation Of Image Feature Extraction By A Genetic Algorithm, Steven P. Brumby, James P. Theiler, Simon J. Perkins, Neal R. Harvey, John J. Szymanski, Jeffrey J. Bloch, Melanie Mitchell
Computer Science Faculty Publications and Presentations
We describe the implementation and performance of a genetic algorithm which generates image feature extraction algorithms for remote sensing applications. We describe our basis set of primitive image operators and present our chromosomal representation of a complete algorithm. Our initial application has been geospatial feature extraction using publicly available multi-spectral aerial-photography data sets. We present the preliminary results of our analysis of the efficiency of the classic genetic operations of crossover and mutation for our application, and discuss our choice of evolutionary control parameters. We exhibit some of our evolved algorithms, and discuss possible avenues for future progress.
Statistical Dynamics Of The Royal Road Genetic Algorithm, Erik Van Nimwegen, James P. Crutchfield, Melanie Mitchell
Statistical Dynamics Of The Royal Road Genetic Algorithm, Erik Van Nimwegen, James P. Crutchfield, Melanie Mitchell
Computer Science Faculty Publications and Presentations
Metastability is a common phenomenon. Many evolutionary processes, both natural and artificial, alternate between periods of stasis and brief periods of rapid change in their behavior. In this paper an analytical model for the dynamics of a mutation-only genetic algorithm (GA) is introduced that identifies a new and general mechanism causing metastability in evolutionary dynamics. The GA’s population dynamics is described in terms of flows in the space of fitness distributions. The trajectories through fitness distribution space are derived in closed form in the limit of infinite populations. We then show how finite populations induce metastability, even in regions where …
Materialized View Algorithms, Yubo Fan
Materialized View Algorithms, Yubo Fan
Dissertations and Theses
A data warehouse is a stand-alone repository of integrated information available for decision support OLAP querying and analysis. Aggregate views can be materialized (stored in disk) to improve query performance in a data warehouse.
Several static and dynamic algorithms for selecting materialized aggregate views (MA V) in a data warehouse are proposed in this thesis. The algorithms are then compared by running a simulation system, which can be configured to compare several algorithms on different type of data warehouses. Simulation results for static algorithms are presented to show that several proposed algorithms perform close to an existing good algorithm (HRU …
Dynamic Load Distribution In Mist, K. Al-Saqabi, R. M. Prouty, Dylan Mcnamee, Steve Otto, Jonathan Walpole
Dynamic Load Distribution In Mist, K. Al-Saqabi, R. M. Prouty, Dylan Mcnamee, Steve Otto, Jonathan Walpole
Computer Science Faculty Publications and Presentations
This paper presents an algorithm for scheduling parallel applications in large-scale, multiuser, heterogeneous distributed systems. The approach is primarily targeted at systems that harvest idle cycles in general-purpose workstation networks, but is also applicable to clustered computer systems and massively parallel processors. The algorithm handles unequal processor capacities, multiple architecture types and dynamic variations in the number of processes and available processors. Scheduling decisions are driven by the desire to minimize turnaround time while maintaining fairness among competing applications. For efficiency, the virtual processors (VPs) of each application are gang scheduled on some subset of the available physical processors.
Resolution Of Local Inconsistency In Identification, Douglas Ray Anderson, Martin Zwick
Resolution Of Local Inconsistency In Identification, Douglas Ray Anderson, Martin Zwick
Complex Systems Faculty Publications and Presentations
This paper reports an algorithm for the resolution of local inconsistency in information-theoretic identification. This problem was first pointed out by Klir as an important research area in reconstructability analysis. Local inconsistency commonly arises when an attempt is made to integrate multiple data sources, i.e., contingency tables, which have differing common margins. For example, if one ha)s an AB table and a BC table, the B margins obtained from the two tables may disagree. If the disagreement can be assigned to sampling error, then one can arrive at a compromise B margin, adjust the original AB and BC tables to …
Genetic Algorithms And Artificial Life, Melanie Mitchell, Stephanie Forrest
Genetic Algorithms And Artificial Life, Melanie Mitchell, Stephanie Forrest
Computer Science Faculty Publications and Presentations
Genetic algorithms are computational models of evolution that play a central role in many artificial-life models. We review the history and current scope of research on genetic algorithms in artificial life, giving illustrative examples in which the genetic algorithm is used to study how learning and evolution interact, and to model ecosystems, immune system, cognitive systems, and social systems. We also outline a number of open questions and future directions for genetic algorithms in artificial-life research
Adaptive Execution Of Data Parallel Computations On Networks Of Heterogeneous Workstations, Robert Prouty, Steve Otto, Jonathan Walpole
Adaptive Execution Of Data Parallel Computations On Networks Of Heterogeneous Workstations, Robert Prouty, Steve Otto, Jonathan Walpole
Computer Science Faculty Publications and Presentations
Parallel environments consisting of a network of heterogeneous workstations introduce an inherently dynamic environment that differs from multicomputers. Workstations are usually considered “shared” resources while multicomputers provide dedicated processing power. The number of workstations available for use is continually changing; the parallel machine presented by the network is in effect continually reconfiguring itself. Application programs must effectively adapt to the changing number of processing nodes while maintaining computational efficiency. This paper examines methods for adapting to this dynamic environment within the framework of explicit message passing under the data parallel programming model. We present four requirements which we feel a …
Matching Points To Lines: Sonar-Based Localization For The Psubot, Kevin Blythe Stanton
Matching Points To Lines: Sonar-Based Localization For The Psubot, Kevin Blythe Stanton
Dissertations and Theses
The PSUBOT (pronounced pea-es-you-bought) is an autonomous wheelchair robot for persons with certain disabilities. Its use of voice recognition and autonomous navigation enable it to carry out high level commands with little or no user assistance. We first describe the goals, constraints, and capabilities of the overall system including path planning and obstacle avoidance. We then focus on localization-the ability of the robot to locate itself in space. Odometry, a compass, and an algorithm which matches points to lines are each employed to accomplish this task. The matching algorithm (which matches "points" to "lines") is the main contribution to this …