207225124
A Linear Programming Approach to Discriminant Analysis with a Reserved-Judgment Region
A linear-programming model is proposed for deriving discriminant rules that allow allocation of entities to a reserved-judgment region. The size of the reserved-judgment region, which can be controlled by varying parameters within the model, dictates the level of aggressiveness (cautiousness) of allocating (misallocating) entities to groups. Results of simulation experiments for various configurations of normal and contaminated normal three-group populations are reported for a variety of parameter selections. Results of cross-validation experiments using real data sets are also reported. Both the simulation and cross-validation experiments include comparison with other discriminant analysis techniques. The results demonstrate that the proposed model is useful for deriving discriminant rules that reduce the chances of misclassification, while maintaining a reasonable level of correct classification.
17704367
A Parallel, Linear Programming-based Heuristic for Large-Scale Set Partitioning Problems
We describe a parallel, linear programming and implication-based heuristic for solving set partitioning problems on distributed memory computer architectures. Our implementation is carefully designed to exploit parallelism to greatest advantage in advanced techniques like preprocessing and probing, primal heuristics, and cut generation. A primaldual subproblem simplex method is used for solving the linear programming relaxation, which breaks the linear programming solution process into natural phases from which we can exploit information to find good solutions on the various processors. Implications from the probing operation are shared among the processors. Combining these techniques allows us to obtain solutions to large and difficult problems in a reasonable amount of computing time.
19038002
Computational Experience of an Interior-Point Algorithm in a Parallel Branch-and-Cut Framework
An interior-point algorithm within a branch-and-bound framework for solving nonlinear mixed integer programs is described. In contrast to solving the relaxation to optimality at each tree node, the relaxation is only solved to near-optimality. Analogous to using advanced bases for warmstart solutions in the case of linear MIP, a \dynamic" collection of warmstart vectors is kept. Computational results on various classes of nonlinear mixed integer programs are presented.
18614557
On Mass-Conserving Least-Squares Methods
Least-squares variational methods have several practical and theoretical advantages for solving elliptic partial differential equations, including symmetric positive definite discrete operators and a sharp error measure. One of the potential drawbacks, especially in three dimensions, is that mass conservation is achieved only in a least-squares sense, and underresolved solutions are especially vulnerable to poor conservation. For the stationary Navier-Stokes equations, which are typically rewritten as a larger system of first-order equations, the loss of mass in the approximate solution is strongly dependent upon the boundary conditions used. A new first-order system reformulation of the Navier-Stokes equations is presented that admits a wider range of mass-conserving boundary conditions. This new formulation is shown to provide both excellent mass conservation and excellent algebraic multigrid performance for three different problems, a square channel, backward-facing step, and branching tubes with two generations of bifurcations.
26848095
Effects of "gender" of the computer on informational social influence: the moderating role of task type
The present experiment examined if and how "gender" of the computer, manifested in character representation, would affect its informational influence on individuals' decisions on masculine (sports) or feminine (fashion) topics. In a 2 (participant's gender) × 2 (character gender) × 2 (nature of topic: masculine vs. feminine) between-subjects experiment, participants played a trivia quiz game with the computer. During the game, they were given a chance to change their initial answer after seeing the computer's answer, which they knew was not necessarily correct. Results suported the match-up hypothesis such that while the male computer elicited greater conformity on the masculine topic than on the feminine topic, the opposite was true for the female counterpart. In addition, men were less likely to yield to the computer's suggestion than women on the masculine topic whereas women, were less likely to succumb to the computer's influence on the feminine topic. These findings are discussed in terms of the robustness of gender-stereotyping in human-computer interaction and the implications for Computers Are Social Actors paradigm.
858750
Operational Semantics of Hybrid Systems
Hybrid systems are heterogeneous systems that include continuous-time (CT) subsystems interacting with discrete-event (DE) subsystems. They are effective models for physical systems interacting with software or experiencing discrete mode changes. 
This dissertation discusses an interpretation of hybrid systems as executable programs written in a programming language with a hybrid system semantics. The semantic properties of such a programming language affect our ability to understand, execute, and analyze a hybrid system model. This dissertation focuses on a few semantic issues that come in defining such a programming language, such as the interpretation of discontinuities in CT signals and simultaneous discrete events in DE signals, liveness property, and the consequences of numerical ODE solver techniques. 
The interactions between CT and DE subsystems and between DE subsystems themselves are captured by discontinuities in continuous-time signals and simultaneous discrete events in discrete-event signals. In order to precisely represent them in compute execution results, a two-dimension domain, called "super-dense time," is used as the domain for defining signals. This domain allows a signal to have multiple values at the same time point while keeping the values ordered. 
CT and DE subsystems are modeled as actors, which are functions that map a set of signals to another set of signals. In this way, a hybrid system model is just a network of actors interacting via signals. We can always transform a network of actors into a composite actor with feedback, where the function of the composition actor is the composition of functions of the component actors. The least fixed point solution to the function of the composite actor, which is a set of signals, gives the denotational semantics of the hybrid system model. 
The operational semantics takes the denotational semantics as a mathematical foundation and defines a set of rules for evaluating actors such that the least fixed point solution can be constructed. Rather than constructing the whole signals, the operational semantics only computes a discrete subset of the signals called a discrete representation of the signals. The constructive procedure is formalized with the Abstract State Machine semantics, where a hybrid system is treated as a state transition system and the rules specify how state transformations are performed. 
This operational semantics supports heterogeneous and hierarchical composition of different models of computation, such as CT, DE, finite state machines, and synchronous languages, and modular execution of the composition as a whole. This ability makes it easy to jointly model and design software controlled systems. 
The operational semantics proposed in this dissertation has been implemented in HyVisual, which is a software tool for modeling and simulating hybrid systems. HyVisual is part of the Ptolemy II software framework, which is available in open-source form at http://ptolemy.org.
36039309
Consistency in Dataflow Graphs
Analytical properties of programming languages with dataflow graph semantics are discussed. It is shown that one of the most serious problems with these languages is that subtle inconsistencies between parts of the dataflow graph can be inadvertently created. These inconsistencies can lead to deadlock, or in the case of nonterminating programs, to unbounded memory requirements. Consistency is defined to mean that the same number of tokens is consumed as produced on any arc, in the long run. A token-flow model is developed for testing for inconsistency. The method is a generalization of consistency checks for synchronous dataflow (SDF) graphs. The token-flow model is compared to similar tests applied to hybrid dynamical systems. It is argued that dataflow semantics make steady-state analysis possible, leading to a simpler method in most cases. >
12760368
A Flexible Architecture for Virtual Humans in Networked Collaborative Virtual Environments
Complex virtual human representation provides more natural interaction and communication among participants in networked virtual environments, hence it is expected to increase the sense of being together within the same virtual world. We present a flexible framework for the integration of virtual humans in networked collaborative virtual environments. A modular architecture allows flexible representation and control of the virtual humans, whether they are controlled by a physical user using all sorts of tracking and other devices, or by an intelligent control program turning them into autonomous actors. The modularity of the system allows for fairly easy extensions and integration with new techniques making it interesting also as a testbed for various domains from “classic” VR to psychological experiments. We present results in terms of functionalities, example applications and measurements of performance and network traffic with an increasing number of participants in the simulation