A sonar approach to obstacle detection for a vision-based autonomous wheelchair

An advanced prototype Computer Controlled Power Wheelchair Navigation System or CCPWNS has been developed to provide autonomy for highly disabled users, whose mix of disabilities makes it difficult or impossible to control their own power chairs in their homes. The working paradigm is “teach and repeat” a mode of control for typical industrial holonomic robots. Ultrasound sensors, which during subsequent autonomous tracking will be used to detect obstacles, also are active during teaching. Based upon post-processed data collected during this teaching event, elaborate trajectories–which may involve multiple direction changes, pivoting and so on, depending upon the requirements of the typically restricted spaces within which the chair must operate–will later be called upon by the disabled rider. An off-line postprocessor assigns an ultrasound profile to the sequence of poses of any taught trajectory. Use of this profile during tracking obviates most of the inherent problems of using ultrasound to avoid obstacles while retaining the ability to near solid objects, such as when passing through a narrow doorway, where required by the environment and trajectory objectives. The work in this article describes a procedure to obtain consistent maps of sonar boundaries during the teaching process, and a preliminary approach to use this information during the tracking phase. The approach is illustrated by results obtained by using the CCPWNS prototype.     

Vector Image Segmentation by Piecewise Continuous Approximation

In this article we present an approach to the segmentation problem by a piecewise approximation of the given image with continuous functions. Unlike the common approach of Mumford and Shah in our formulation of the problem the number of segments is a parameter, which can be estimated. The problem can be stated as: Compute the optimal segmentation with a fixed number of segments, then reduce the number of segments until the segmentation result fulfills a given suitability. This merging algorithm results in a multi-objective optimization, which is not only resolved by a linear combination of the contradicting error functions. To constrain the problem we use a finite dimensional vector space of functions in our approximation and we restrict the shape of the segments. Our approach results in a multi-objective optimization: On the one hand the number of segments is to be minimized, on the other hand the approximation error should also be kept minimal. The approach is sound theoretically and practically: We show that for L ²-images a Pareto-optimal solution exists and can be computed for the discretization of the image efficiently.     

Analytic complexities associated with group therapy in substance abuse treatment research: Problems, recommendations, and future directions.

In community-based alcoholism and drug abuse treatment programs, the vast majority of interventions are delivered in a group therapy context. In turn, treatment providers and funding agencies have called for more research on interventions delivered in groups in an effort to make the emerging empirical literature on the treatment of substance abuse more ecologically valid. Unfortunately, the complexity of data structures derived from therapy groups (because of member interdependence and changing membership over time) and the present lack of statistically valid and generally accepted approaches to analyzing these data have had a significant stifling effect on group therapy research. This article (a) describes the analytic challenges inherent in data generated from therapy groups, (b) outlines common (but flawed) analytic and design approaches investigators often use to address these issues (e.g., ignoring group-level nesting, treating data from therapy groups with changing membership as fully hierarchical), and (c) provides recommendations for handling data from therapy groups using presently available methods. In addition, promising data-analytic frameworks that may eventually serve as foundations for the development of more appropriate analytic methods for data from group therapy research (i.e., nonhierarchical data modeling, pattern-mixture approaches) are also briefly described. Although there are other substantial obstacles that impede rigorous research on therapy groups (e.g., evaluation and measurement of group process, limited control over treatment delivery ingredients), addressing data-analytic problems is critical for improving the accuracy of statistical inferences made from research on ecologically valid group-based substance abuse interventions. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The application of the multiple transient technique for the experimental determination of the relative abundances and decay constants of delayed neutrons of the IPEN/MB-01 reactor

An in-pile experiment for the determination of the relative abundances and decay constants of delayed neutrons has been successfully performed at the IPEN/MB-01 research reactor facility. The experimental data are of good quality and can be used to validate theoretical predictions of the delayed neutron group constants based on the current knowledge of the fission products yields and emission probabilities for known precursors. The theory/experiment comparison shows that the current release of ENDF/B-VI, namely release 8, shows severe discrepancies in both relative abundances and in its first decay constant. The version revised at LANL shows very good progress in both aspects. JENDL3.3 shows the best performance in the C/E comparison. One of the main achievements of the experiment was the consistency of the measured first decay constant to that of ⁸⁷Br. Finally, it is also shown preliminary experimental results for an eight-group model.     

Using Maude to write and execute ODP information viewpoint specifications

The aim of the open distributed processing (ODP) information viewpoint is to describe the semantics of the information and of the information processing in a system, from a global point of view, without having to worry about other considerations, such as how the information will be finally distributed or implemented or the technology used to achieve such implementation. Although several notations have been proposed to model this ODP viewpoint, they are not expressive enough to faithfully represent all the information concepts, or they tend to suffer from a lack of (formal) support, or both. In this paper, we explore the use of Maude as a formal notation for writing ODP information specifications. Maude is an executable rewriting logic language especially well suited for the specification of object-oriented open and distributed systems. We show how Maude offers a simple, natural, and accurate way of modeling the ODP information viewpoint concepts, allows the execution of the specifications produced, and offers good tool support for reasoning about them.     

Estimation of a fluorescent lamp spectral distribution for color image in machine vision

We present a technique to quickly estimate the Illumination Spectral Distribution (ISD) in an image illuminated by a fluorescent lamp. It is assumed that the object colors are a set of colors for which spectral reflectances are available (in our experiments we use spectral measurements of 12 colors checker chart), the sensitivities of the camera sensors are known and the camera response is linear. Thus, the ISD can be approximated by a finite linear combinations of a small number of basis functions.     

Morphological Pyramids in Multiresolution MIP Rendering of Large Volume Data: Survey and New Results

We survey and extend nonlinear signal decompositions based on morphological pyramids, and their application to multiresolution maximum intensity projection (MIP) volume rendering with progressive refinement and perfect reconstruction. The structure of the resulting multiresolution rendering algorithm is very similar to wavelet splatting. Several existing classes of pyramids are discussed, and their limitations indicated. To enhance the approximation quality of visualizations from reduced data (higher levels of the pyramid), two approaches are explored. First, a new class of morphological pyramids, involving connectivity enhancing operators, is considered. In the pyramidal analysis phase, a conditional dilation operator is used, with a given number n of iterations. The corresponding pyramids for n = 0 and n = 1 are known as the adjunction pyramid and Sun-Maragos pyramid, respectively. We show that the approximation quality when rendering from higher levels of the pyramid does increase as a function of the number of iterations n of the conditional dilation operator, but the improvement for n > 1 is limited. The second new approach, called streaming MIP-splatting, again starts from the adjunction pyramid. The new element is that detail coefficients of all levels are considered simultaneously and are resorted with respect to decreasing magnitude of a suitable error measure. All resorted coefficients are projected successively, until a desired accuracy of the resulting MIP image is obtained. We show that this method outperforms the previous methods based on morphological pyramids, both with respect to image quality with a fixed amount of detail data, and in terms of flexibility of controlling approximation error or computation time.Jos B.T.M. Roerdink received his M.Sc. (1979) in theoretical physics from the University of Nijmegen, the Netherlands. Following his Ph.D. (1983) from the University of Utrecht and a two-year position (1983–1985) as a Postdoctoral Fellow at the University of California, San Diego, both in the area of stochastic processes, he joined the Centre for Mathematics and Computer Science in Amsterdam. There he worked from 1986–1992 on image processing and tomographic reconstruction. He was appointed associate professor (1992) and full professor (2003), respectively, at the Institute for Mathematics and Computing Science of the University of Groningen, where he currently holds a chair in Scientific Visualization and Computer Graphics. His current research interests include morphological image processing, biomedical visualization, neuroimaging and bioinformatics.     

Construction Management of a Small-Scale Accelerated Pavement Testing Facility

Research in accelerated pavement testing (APT) facilities has traditionally focused on the pavement performance such as rutting and fatigue cracking, but documentation on construction management and information of the actual pavement construction quality is limited. There are typically four critical factors that need to be considered to achieve the best possible outcome in construction: cost, schedule, construction process, and quality control, and management. With the objective of developing guidelines for planning and executing construction of a small-scale APT facility, this paper presents a case study documenting and evaluating the construction process and construction management efforts of two sensor-instrumented hot mix asphalt pavement test sections built in a small-scale APT facility. The focus of the experiment was to study bottom-up fatigue cracking of the flexible pavement structure. The presented information and lessons learned serve as a template and guide for agencies pursuing this type of research and pavement construction.     

Exploiting Narrow Values for Soft Error Tolerance

Soft errors are an important challenge in contemporary microprocessors. Particle hits on the components of a processor are expected to create an increasing number of transient errors with each new microprocessor generation. In this paper we propose simple mechanisms that effectively reduce the vulnerability to soft errors In a processor. Our designs are generally motivated by the fact that many of the produced and consumed values in the processors are narrow and their upper order bits are meaningless. Soft errors canted by any particle strike to these higher order bits can be avoided by simply identifying these narrow values. Alternatively soft errors can be detected or corrected on the narrow values by replicating the vulnerable portion of the value inside the storage space provided for the upper order bits of these operands. We offer a variety of schemes that make use of narrow values and analyze their efficiency in reducing soft error vulnerability of level-1 data cache of the processor     

Coupled model for the nonlinear analysis of sections made of anisotropic materials, subjected to general 3D loading. Part 2: Implementation and validation

A numerical model for the coupled analysis of cross-sections made of anisotropic materials under general combined loading was formulated in an accompanying paper (1). In this paper, additional aspects concerning its implementation and the scheme for nonlinear analysis are discussed. The model is validated by analyzing several isotropic and anisotropic elastic problems; excellent accuracy was obtained compared to closed-form solutions. Further, the case of a RC section presenting crack-induced anisotropy is investigated. The capability of the model to capture interactions between tangent and normal forces is proved. The conclusion drawn is that the developed model is a suitable sectional constitutive equation for 3D beam elements for realistic structural analysis.