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Problem Solver (problem + solver)

Distribution by Scientific Domains
Information Science and Computing40%
Engineering40%

Selected Abstracts

IT project managers' construction of successful project management practice: a repertory grid investigation

INFORMATION SYSTEMS JOURNAL, Issue 3 2009
Nannette P. Napier
Abstract Although effective project management is critical to the success of information technology (IT) projects, little empirical research has investigated skill requirements for IT project managers (PMs). This study addressed this gap by asking 19 practicing IT PMs to describe the skills that successful IT PMs exhibit. A semi-structured interview method known as the repertory grid (RepGrid) technique was used to elicit these skills. Nine skill categories emerged: client management, communication, general management, leadership, personal integrity, planning and control, problem solving, systems development and team development. Our study complements existing research by providing a richer understanding of several skills that were narrowly defined (client management, planning and control, and problem solving) and by introducing two new skill categories that had not been previously discussed (personal integrity and team development). Analysis of the individual RepGrids revealed four distinct ways in which study participants combined skill categories to form archetypes of effective IT PMs. We describe these four IT PM archetypes , General Manager, Problem Solver, Client Representative and Balanced Manager , and discuss how this knowledge can be useful for practitioners, researchers and educators. The paper concludes with suggestions for future research. [source]

Full waveform seismic inversion using a distributed system of computers

CONCURRENCY AND COMPUTATION: PRACTICE & EXPERIENCE, Issue 11 2005
Indrajit G. Roy
Abstract The aim of seismic waveform inversion is to estimate the elastic properties of the Earth's subsurface layers from recordings of seismic waveform data. This is usually accomplished by using constrained optimization often based on very simplistic assumptions. Full waveform inversion uses a more accurate wave propagation model but is extremely difficult to use for routine analysis and interpretation. This is because computational difficulties arise due to: (1) strong nonlinearity of the inverse problem; (2) extreme ill-posedness; and (3) large dimensions of data and model spaces. We show that some of these difficulties can be overcome by using: (1) an improved forward problem solver and efficient technique to generate sensitivity matrix; (2) an iteration adaptive regularized truncated Gauss,Newton technique; (3) an efficient technique for matrix,matrix and matrix,vector multiplication; and (4) a parallel programming implementation with a distributed system of processors. We use a message-passing interface in the parallel programming environment. We present inversion results for synthetic and field data, and a performance analysis of our parallel implementation. Copyright © 2005 John Wiley & Sons, Ltd. [source]

Extension of a combined analytical/numerical initial value problem solver for unsteady periodic flow

INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS, Issue 9 2002
Lawrence J. De Chant
Abstract Here we describe analytical and numerical modifications that extend the Differential Reduced Ejector/ mixer Analysis (DREA), a combined analytical/numerical, multiple species ejector/mixing code developed for preliminary design applications, to apply to periodic unsteady flow. An unsteady periodic flow modelling capability opens a range of pertinent simulation problems including pulse detonation engines (PDE), internal combustion engine ICE applications, mixing enhancement and more fundamental fluid dynamic unsteadiness, e.g. fan instability/vortex shedding problems. Although mapping between steady and periodic forms for a scalar equation is a classical problem in applied mathematics, we will show that extension to systems of equations and, moreover, problems with complex initial conditions are more challenging. Additionally, the inherent large gradient initial condition singularities that are characteristic of mixing flows and that have greatly influenced the DREA code formulation, place considerable limitations on the use of numerical solution methods. Fortunately, using the combined analytical,numerical form of the DREA formulation, a successful formulation is developed and described. Comparison of this method with experimental measurements for jet flows with excitation shows reasonable agreement with the simulation. Other flow fields are presented to demonstrate the capabilities of the model. As such, we demonstrate that unsteady periodic effects can be included within the simple, efficient, coarse grid DREA implementation that has been the original intent of the DREA development effort, namely, to provide a viable tool where more complex and expensive models are inappropriate. Copyright © 2002 John Wiley & Sons, Ltd. [source]

dsoa: The implementation of a dynamic system optimization algorithm

OPTIMAL CONTROL APPLICATIONS AND METHODS, Issue 3 2010
Brian C. Fabien
Abstract This paper describes the ANSI C/C++ computer program dsoa, which implements an algorithm for the approximate solution of dynamics system optimization problems. The algorithm is a direct method that can be applied to the optimization of dynamic systems described by index-1 differential-algebraic equations (DAEs). The types of problems considered include optimal control problems and parameter identification problems. The numerical techniques are employed to transform the dynamic system optimization problem into a parameter optimization problem by: (i) parameterizing the control input as piecewise constant on a fixed mesh, and (ii) approximating the DAEs using a linearly implicit Runge-Kutta method. The resultant nonlinear programming (NLP) problem is solved via a sequential quadratic programming technique. The program dsoa is evaluated using 83 nontrivial optimal control problems that have appeared in the literature. Here we compare the performance of the algorithm using two different NLP problem solvers, and two techniques for computing the derivatives of the functions that define the problem. Copyright © 2009 John Wiley & Sons, Ltd. [source]

Learning Organizations in the Public Sector?

PUBLIC ADMINISTRATION REVIEW, Issue 1 2003
A Study of Police Agencies Employing Information, Technology to Advance Knowledge
In an attempt to reap the purported benefits that "knowledge workers" bring to organizations, many police departments have shifted to a community problem,oriented policing philosophy. Rather than focusing on enforcement and incarceration, this philosophy is based on the dissemination of information to promote a proactive, preventative approach to reduce crime and disorder. In keeping with much of the contemporary literature on the "learning organization" (sometimes called the "knowledge organization"), police departments hope to deter crime through the knowledge benefits that derive from information and its associated technologies. With goals to stimulate productivity, performance, and effectiveness, police departments across the country are employing information technology to turn police officers into problem solvers and to leverage their intellectual capital to preempt crime and neighborhood deterioration. Many public and private organizations are striving to change their operations toward this same concept of the knowledge worker. Information technology is often touted as a vehicle for capturing, tracking, sorting, and providing information to advance knowledge, thus leading to improvements in service,delivery efforts. Based on an extensive study of police departments that have attempted to implement a knowledge,worker paradigm (supported by information technology initiatives), this research explores the feasibility, effectiveness, and limitations of information and technology in promoting the learning organization in the public sector. [source]