Showing papers by "Carleton University published in 2005"

A review and evaluation of intraurban air pollution exposure models

Abstract: The development of models to assess air pollution exposures within cities for assignment to subjects in health studies has been identified as a priority area for future research. This paper reviews models for assessing intraurban exposure under six classes, including: (i) proximity-based assessments, (ii) statistical interpolation, (iii) land use regression models, (iv) line dispersion models, (v) integrated emission-meteorological models, and (vi) hybrid models combining personal or household exposure monitoring with one of the preceding methods. We enrich this review of the modelling procedures and results with applied examples from Hamilton, Canada. In addition, we qualitatively evaluate the models based on key criteria important to health effects assessment research. Hybrid models appear well suited to overcoming the problem of achieving population representative samples while understanding the role of exposure variation at the individual level. Remote sensing and activity-space analysis will complement refinements in pre-existing methods, and with expected advances, the field of exposure assessment may help to reduce scientific uncertainties that now impede policy intervention aimed at protecting public health.

Is mutation an appropriate tool for testing experiments

Abstract: The empirical assessment of test techniques plays an important role in software testing research. One common practice is to instrument faults, either manually or by using mutation operators. The latter allows the systematic, repeatable seeding of large numbers of faults; however, we do not know whether empirical results obtained this way lead to valid, representative conclusions. This paper investigates this important question based on a number of programs with comprehensive pools of test cases and known faults. It is concluded that, based on the data available thus far, the use of mutation operators is yielding trustworthy results (generated mutants are similar to real faults). Mutants appear however to be different from hand-seeded faults that seem to be harder to detect than real faults.

Hypersensitivity of DJ-1-deficient mice to 1-methyl-4-phenyl-1,2,3,6-tetrahydropyrindine (MPTP) and oxidative stress

Abstract: Mutations of the DJ-1 (PARK7) gene are linked to familial Parkinson's disease. We used gene targeting to generate DJ-1-deficient mice that were viable, fertile, and showed no gross anatomical or neuronal abnormalities. Dopaminergic neuron numbers in the substantia nigra and fiber densities and dopamine levels in the striatum were normal. However, DJ-1-/- mice showed hypolocomotion when subjected to amphetamine challenge and increased striatal denervation and dopaminergic neuron loss induced by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyrindine. DJ-1-/-embryonic cortical neurons showed increased sensitivity to oxidative, but not nonoxidative, insults. Restoration of DJ-1 expression to DJ-1-/- mice or cells via adenoviral vector delivery mitigated all phenotypes. WT mice that received adenoviral delivery of DJ-1 resisted 1-methyl-4-phenyl-1,2,3,6-tetrahydropyrindine-induced striatal damage, and neurons overexpressing DJ-1 were protected from oxidative stress in vitro. Thus, DJ-1 protects against neuronal oxidative stress, and loss of DJ-1 may lead to Parkinson's disease by conferring hypersensitivity to dopaminergic insults.

A Gaussian mixture model based classification scheme for myoelectric control of powered upper limb prostheses

Abstract: This paper introduces and evaluates the use of Gaussian mixture models (GMMs) for multiple limb motion classification using continuous myoelectric signals. The focus of this work is to optimize the configuration of this classification scheme. To that end, a complete experimental evaluation of this system is conducted on a 12 subject database. The experiments examine the GMMs algorithmic issues including the model order selection and variance limiting, the segmentation of the data, and various feature sets including time-domain features and autoregressive features. The benefits of postprocessing the results using a majority vote rule are demonstrated. The performance of the GMM is compared to three commonly used classifiers: a linear discriminant analysis, a linear perceptron network, and a multilayer perceptron neural network. The GMM-based limb motion classification system demonstrates exceptional classification accuracy and results in a robust method of motion classification with low computational load.

Stochastic Finite-Fault Modeling Based on a Dynamic Corner Frequency

Abstract: In finite-fault modeling of earthquake ground motions, a large fault is divided into N subfaults, where each subfault is considered as a small point source The ground motions contributed by each subfault can be calculated by the stochastic point-source method and then summed at the observation point, with a proper time delay, to obtain the ground motion from the entire fault A new variation of this approach is introduced based on a "dynamic corner frequency" In this model, the corner frequency is a function of time, and the rupture history controls the frequency content of the simulated time series of each subfault The rupture begins with a high corner frequency and progresses to lower corner frequencies as the ruptured area grows Limiting the number of active subfaults in the calculation of dynamic corner frequency can control the amplitude of lower frequencies Our dynamic corner frequency approach has several advantages over previous formulations of the stochastic finite-fault method, including conservation of radiated energy at high frequencies regardless of subfault size, application to a broader mag- nitude range, and control of the relative amplitude of higher versus lower frequencies The model parameters of the new approach are calibrated by finding the best overall fit to a ground-motion database from 27 well-recorded earthquakes in California The lowest average residuals are obtained for a dynamic corner frequency model with a stress drop of 60 bars and with 25% of the fault actively slipping at any time in the rupture As an additional tool to allow the stochastic modeling to generate the impulsive long-period velocity pulses that can be caused by forward directivity of the source, the analytical approach proposed by Mavroeidis and Papageorgiou (2003) has been included in our program This novel mathematical model of near-fault ground mo- tions is based on a few additional input parameters that have an unambiguous physi- cal meaning; the method has been shown by Mavroeidis and Papageorgiou to sim- ulate the entire set of available near-fault displacement and velocity records, as well as the corresponding deformation, velocity, and acceleration response spectra The inclusion of this analytical model of long-period pulses substantially increases the power of the stochastic finite-fault simulation method to model broadband time his- tories over a wide range of distances, magnitudes, and frequencies

The Effectiveness of Restorative Justice Practices: A Meta-Analysis:

Abstract: This article provides an empirical synthesis of the existing literature on the effectiveness of restorative justice practices using meta-analytic techniques. The data were aggregated from studies that compared restorative justice programs to traditional nonrestorative approaches to criminal behavior. Victim and offender satisfaction, restitution compliance, and recidivism were selected as appropriate outcomes to adequately measure effectiveness. Although restorative programs were found to be significantly more effective, these positive findings are tempered by an important self-selection bias inherent in restorative justice research. A possible method of addressing this problem, as well as directions for future research, are provided.

Quivers with relations arising from clusters $(A_n$ case)

Abstract: Cluster algebras were introduced by S. Fomin and A. Zelevinsky in connection with dual canonical bases. Let U be a cluster algebra of type A_n. We associate to each cluster C of U an abelian category Cat_C such that the indecomposable objects of Cat_C are in natural correspondence with the cluster variables of U which are not in C. We give an algebraic realization and a geometric realization of Cat_C. Then, we generalize the ``denominator Theorem'' of Fomin and Zelevinsky to any cluster.

Framing the frameworks: a review of it governance research

Abstract: With the passage of the Sarbanes-Oxley Act in the United States in 2002, and an ever-increasing corporate focus on ensuring prudent returns on technology investments, the notion of IT governance became a major issue for both business practitioners and academics. Although the term “IT governance” is a relatively new addition to the syntax of academic research, significant previous work is reported on IT decisions rights and IT loci of control, notions that are synonymous with the current understanding of IT governance. This paper presents a literature review for existing research in IT governance. A framework, named the Conceptual Framework For IT Governance Research is proposed to provide a logical structure for existing research results. Using this framework, we classify the previous literature on governance into two separate streams that follow parallel paths of advancement. A popular contemporary notion of IT governance is then presented, together with the argument that this new notion, by implicitly extending both streams of research, represents an initial amalgamation of the two paths of literature. We conclude that even with the consideration of contemporary structures, academicians and practitioners alike continue to explore the concept of IT governance in an attempt to find appropriate mechanisms to govern corporate IT decisions.

Forgiveness and collective guilt assignment to historical perpetrator groups depend on level of social category inclusiveness.

Abstract: The authors examined how categorization influences victimized group members' responses to contemporary members of a historical perpetrator group. Specifically, the authors tested whether increasing category inclusiveness--from the intergroup level to the maximally inclusive human level--leads to greater forgiveness of a historical perpetrator group and decreased collective guilt assignment for its harmdoing. Among Jewish North Americans (Experiments 1, 2, and 4) and Native Canadians (Experiment 3) human-level categorization resulted in more positive responses toward Germans and White Canadians, respectively, by decreasing the uniqueness of their past harmful actions toward the in-group. Increasing the inclusiveness of categorization led to greater forgiveness and lessened expectations that former out-group members should experience collective guilt compared with when categorization was at the intergroup level. Discussion focuses on obstacles that are likely to be encountered on the road to reconciliation between groups that have a history of conflictual relations.

Continuous myoelectric control for powered prostheses using hidden Markov models

Abstract: This paper represents an ongoing investigation of dexterous and natural control of upper extremity prostheses using the myoelectric signal. The scheme described within uses a hidden Markov model (HMM) to process four channels of myoelectric signal, with the task of discriminating six classes of limb movement. The HMM-based approach is shown to be capable of higher classification accuracy than previous methods based upon multilayer perceptrons. The method does not require segmentation of the myoelectric signal data, allowing a continuous stream of class decisions to be delivered to a prosthetic device. Due to the fact that the classifier learns the muscle activation patterns for each desired class for each individual, a natural control actuation results. The continuous decision stream allows complex sequences of manipulation involving multiple joints to be performed without interruption. The computational complexity of the HMM in its operational mode is low, making it suitable for a real-time implementation. The low computational overhead associated with training the HMM also enables the possibility of adaptive classifier training while in use.

Can Local Ecological Knowledge Contribute to Wildlife Management? Case Studies of Migratory Birds

Abstract: Sound management of wildlife species, particularly those that are harvested, requires extensive information on their natural history and demography. For many global wildlife populations, however, insufficient scientific information exists, and alternative data sources may need to be considered in management decisions. In some circumstances, local ecological knowledge (LEK) can serve as a useful, complementary data source, and may be particularly valuable when managing wildlife populations that occur in remote locations inhabited by indigenous peoples. Although several published papers discuss the general benefits of LEK, few attempt to examine the reliability of information generated through this approach. We review four case studies of marine birds in which we gathered LEK for each species and then compared this information to empirical data derived from independent scientific studies of the same populations. We then discuss how we attempted to integrate LEK into our own conservation and management efforts of these bird species with variable success. Although LEK proved to be a useful source of information for three of four species, we conclude that management decisions based primarily on LEK, in the absence of scientific scrutiny, should be treated with caution.

Teleoperation of a robot manipulator using a vision-based human-robot interface

Abstract: Remote teleoperation of a robot manipulator by a human operator is often necessary in unstructured dynamic environments when human presence at the robot site is undesirable. Mechanical and other contacting interfaces used in teleoperation require unnatural human motions for object manipulation tasks or they may hinder human motion. Previous vision-based approaches have used only a few degrees of freedom for hand motion and have required hand motions that are unnatural for object manipulation tasks. This paper presents a noncontacting vision-based method of robot teleoperation that allows a human operator to communicate simultaneous six-degree-of-freedom motion tasks to a robot manipulator by having the operator perform the three-dimensional human hand-arm motion that would naturally be used to complete an object manipulation task. A vision-based human-robot interface is used for communication of human motion to the robot and for feedback of the robot motion and environment to the human operator. Teleoperation under operator position control was performed with high accuracy in object placement on a target. Semi-autonomous traded and shared control using robot-vision guidance aided in achieving a more accurate positioning and orientation of the end-effector for object gripping tasks.

Developing a Generic Framework for E-Government

Abstract: Electronic government (e-government) initiatives are pervasive and form a significant part of government investment portfolio in almost all countries around the world. However, understanding of what is meant by e-government is still nascent and becomes complicated because the construct means different things to different people. Consequently, the conceptualization and implementation of e-government programs are diverse and are often difficult to assess and compare across different contexts of application. This paper addresses the following key question: Given the wide variety of visions, strategic agendas, and contexts of application, how may we assess, categorize, classify, compare, and discuss the e-government efforts of various government administrations? In answering this question, we propose a generic e-government framework that will allow for the identification of e-government strategic agendas and key application initiatives that transcend country-specific requirements. In developing the framework, a number of requirements are first outlined. The framework is proposed and described; it is then illustrated using brief case studies from three countries. Finally, findings and limitations are discussed.

On implementation of min-sum algorithm and its modifications for decoding low-density Parity-check (LDPC) codes

Abstract: The effects of clipping and quantization on the performance of the min-sum algorithm for the decoding of low-density parity-check (LDPC) codes at short and intermediate block lengths are studied. It is shown that in many cases, only four quantization bits suffice to obtain close to ideal performance over a wide range of signal-to-noise ratios. Moreover, we propose modifications to the min-sum algorithm that improve the performance by a few tenths of a decibel with just a small increase in decoding complexity. A quantized version of these modified algorithms is also studied. It is shown that, when optimized, modified quantized min-sum algorithms perform very close to, and in some cases even slightly outperform, the ideal belief-propagation algorithm at observed error rates.

Physiological causes and consequences of social status in salmonid fish.

Abstract: Social interactions in small groups of juvenile rainbow trout (Oncorhynchus mykiss) lead to the formation of dominance hierarchies. Dominant fish hold better positions in the environment, gain a larger share of the available food and exhibit aggression towards fish lower in the hierarchy. By contrast, subordinate fish exhibit behavioural inhibition, including reduced activity and feeding. The behavioural characteristics associated with social status are likely the result of changes in brain monoamines resulting from social interactions. Whereas substantial physiological benefits, including higher growth rates and condition factor, are experienced by dominant trout, low social status appears to be a chronic stress, as indicated by sustained elevation of circulating cortisol concentrations in subordinate fish. High cortisol levels, in turn, may be responsible for many of the deleterious physiological consequences of low social status, including lower growth rates and condition factor, immunosuppression and increased mortality. Circulating cortisol levels may also be a factor in determining the outcome of social interactions in pairs of rainbow trout, and hence in determining social status. Rainbow trout treated with cortisol were significantly more likely to become subordinate in paired encounters with smaller untreated conspecifics.

Supersymmetry Parameter Analysis: SPA Convention and Project

Abstract: High-precision analyses of supersymmetry parameters aim at reconstructing the fundamental supersymmetric theory and its breaking mechanism. A well defined theoretical framework is needed when higher-order corrections are included. We propose such a scheme, Supersymmetry Parameter Analysis SPA, based on a consistent set of conventions and input parameters. A repository for computer programs is provided which connect parameters in different schemes and relate the Lagrangian parameters to physical observables at LHC and high energy e+e- linear collider experiments, i.e., masses, mixings, decay widths and production cross sections for supersymmetric particles. In addition, programs for calculating high-precision low energy observables, the density of cold dark matter (CDM) in the universe as well as the cross sections for CDM search experiments are included. The SPA scheme still requires extended efforts on both the theoretical and experimental side before data can be evaluated in the future at the level of the desired precision. We take here an initial step of testing the SPA scheme by applying the techniques involved to a specific supersymmetry reference point.

Comparison of Laminar Separation Bubble Measurements on a Low Reynolds Number Airfoil in Three Facilities

Abstract: This paper describes a series of experiments on the SD7003 airfoil, conducted in three different facilities: a low-turbulence wind tunnel, a water tunnel, and a tow tank. An attempt was made to achieve commonality of model geometry, Reynolds number and test conditions, in order to directly compare the experimental results. The SD7003 airfoil was chosen because of its robust, thin laminar separation bubble, which challenges the capability of current Particle Image Velocimetry (PIV) methods to accurately resolve the near-wall flowfield. Chordwise locations of separation, reattachment, and transition were compared. Since the time-averaged bubble geometry is a strong function of the flowfield ambient turbulence level, comparison of bubble geometry gives some assessment of facility flow quality, and hence of facility suitability for low Reynolds number testing in general.

Reliability and Validity Analyses of the Youth Level of Service/Case Management Inventory

Abstract: The Youth Level of Service/Case Management Inventory (YLS/CMI) is a structured assessment tool designed to facilitate the effective intervention and rehabilitation of juvenile offenders by assessing each youth’s risk level and criminogenic needs. The present study examined the YLS/CMI’s reliability and validity in a sample of 107 juvenile offenders who were court-referred for mental health assessments. Results demonstrated the YLS/CMI’s internal consistency and interrater reliability. Moreover, the instrument’s predictive validity was substantiated on a number of recidivism measures for both males and females. Limitations of the current findings are discussed.

Performance by unified model analysis (PUMA)

Abstract: Evaluation of non-functional properties of a design (such as performance, dependability, security, etc.) can be enabled by design annotations specific to the property to be evaluated. Performance properties, for instance, can be annotated on UML designs by using the "UML Profile for Schedulability, Performance and Time (SPT)". However the communication between the design description in UML and the tools used for non-functional properties evaluation requires support, particularly for performance where there are many alternative performance analysis tools that might be applied. This paper describes a tool architecture called PUMA, which provides a unified interface between different kinds of design information and different kinds of performance models, for example Markov models, stochastic Petri nets and process algebras, queues and layered queues.The paper concentrates on the creation of performance models. The unified interface of PUMA is centered on an intermediate model called Core Scenario Model (CSM), which is extracted from the annotated design model. Experience shows that CSM is also necessary for cleaning and auditing the design information, and providing default interpretations in case it is incomplete, before creating a performance model.

Matrix structure obscures the relationship between interpatch movement and patch size and isolation

Abstract: Metapopulation models assume that local population size (in a habitat patch) and therefore local extinction probability, is a function of patch size, and that interpatch movement rate and therefore recolonization of local extinctions is a function of both patch size and patch isolation. We hypothesized that the predictive power of models that relate patch immigration rate to patch size and isolation will be reduced when spatial structure in the landscape matrix (the nonhabitat portion of the landscape) affects organism movement through the landscape. We used a simulation model to evaluate this hypothesis for three different aspects of matrix spatial structure (contrast among matrix cover types, number of matrix cover types, and grain of matrix spatial pattern) and for two different types of movement behavior, representing a specialist and a generalist species. We tested the hy- pothesis for one aspect of matrix structure (number of matrix cover types) in a translocation field study of the eastern chipmunk ( Tamias striatus, a habitat specialist) and the white- footed mouse (Peromyscus leucopus, a habitat generalist). When the matrix was composed of a small number of cover types, patch size and isolation accounted for up to 75% of the variation in patch immigration rate in the simulation study, and for 61% of the variation in interpatch movement in the field study. However, when the matrix was composed of a large number of cover types, the amount of explained variation dropped to as little as 33% for the simulation study and to 17% in the field study. Our results suggest that patch characteristics, such as patch size and isolation, may be poor predictors of interpatch movement when the landscape matrix is heterogeneous and when the organism responds to boundaries between different matrix cover types. These results imply that habitat patch- based models, such as those based on current metapopulation theory, will perform poorly in these situations.