Stable transport of assemblies by pushing

This paper presents a method to determine whether an assembly of planar parts will stay assembled as it is pushed over a support surface. For a given pushing motion, an assembly is classified into one of three categories: (P = possible): any force necessary to preserve the assembly can be generated by the pushing contacts; (I = impossible): pushing forces cannot preserve the assembly; and (U = undecided): pushing forces may or may not be able to preserve the assembly. This classification is made based on the solution of linear constraint satisfaction problems. If the part-part and part-pusher contacts are frictionless, motions labeled P are guaranteed to preserve the assembly. The results are based on bounds on the possible support friction acting on individual parts in the face of indeterminacy in the distribution of support forces. Experimental results supporting the analysis are given.     

Testing Self-Similar Networks

A hard problem in network testing is verifying the correctness of a class of networks, as well as the actual networks under test. In practice, at most a few networks (sometimes only one) are actually tested. Thus an important question is how to select one or more networks that are sufficiently representative to apply the results to a class of networks. We present a model-based technique for selecting a representative network. The central theorem establishes that the representative network displays any faults present in any network of the class. This paper introduces the concept of “self-similarity,” which is used to select the network, and presents the results of an experiment in testing one class of networks.     

Computer-assisted intervention improves patient-centered diabetes care by increasing autonomy support.

Objective: To determine if a patient-centered, computer-assisted diabetes care intervention increased perceived autonomy support, perceived competence (from self-determination theory), and if these constructs mediated the effect of the intervention on ADA/NCQA recommended diabetes care outcomes. Design: A randomized controlled trial of 866 adult type 2 diabetes patients in heterogeneous primary care settings in Colorado. Main Outcome Measures: Perceived autonomy support, perceived competence, patient satisfaction, glycemic control (HbA1c), ratio of total to HDL cholesterol, diabetes distress, and depressive symptoms. Results: The computer-assisted intervention increased patient perception of autonomy support relative to a computer-based control condition ( p = .05). Change in perceived competence partially mediated the effects of increased autonomy support on the change in lipids, diabetes distress, and depressive symptoms. The construct of autonomy support was found to be separate from that of patient satisfaction. Conclusions: A patient-centered, computer-assisted intervention was effective in improving diabetes self-management outcomes, in part, because it increased patients' perception that their autonomy was supported which changed perceived competence. These findings support the self-determination model for health behavior change and the chronic care model and support the further study of the use of these technologies to motivate patients to improve their health outcomes. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Mediators of telephone-based continuing care for alcohol and cocaine dependence.

A previous randomized trial with 224 alcohol and/or cocaine addicts who had completed an initial phase of treatment indicated that 12 weeks of telephone-based continuing care yielded higher abstinence rates over 24 months than did group counseling continuing care. The current study examined mediators of this treatment effect. Results suggested that self-help involvement during treatment and self-efficacy and commitment to abstinence 3 months after treatment mediated subsequent abstinence outcomes. These analyses controlled for substance use prior to the assessment of mediators. Conversely, there was no evidence that self-help beliefs or social support mediated the treatment effect. These results are consistent with a model in which treatment effects are first accounted for by changes in behavior, followed by changes in self-efficacy and in commitment to abstinence. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

The BG distributed simulation algorithm

We present a shared memory algorithm that allows a set of f+1 processes to wait-free “simulate” a larger system of n processes, that may also exhibit up to f stopping failures. Applying this simulation algorithm to the k-set-agreement problem enables conversion of an arbitrary k-fault-tolerant{\it n}-process solution for the k-set-agreement problem into a wait-free k+1-process solution for the same problem. Since the k+1-processk-set-agreement problem has been shown to have no wait-free solution [5,18,26], this transformation implies that there is no k-fault-tolerant solution to the n-process k-set-agreement problem, for any n. More generally, the algorithm satisfies the requirements of a fault-tolerant distributed simulation.\/ The distributed simulation implements a notion of fault-tolerant reducibility\/ between decision problems. This paper defines these notions and gives examples of their application to fundamental distributed computing problems. The algorithm is presented and verified in terms of I/O automata. The presentation has a great deal of interesting modularity, expressed by I/O automaton composition and both forward and backward simulation relations. Composition is used to include a safe agreement\/ module as a subroutine. Forward and backward simulation relations are used to view the algorithm as implementing a multi-try snapshot\/ strategy. The main algorithm works in snapshot shared memory systems; a simple modification of the algorithm that works in read/write shared memory systems is also presented. Received: February 2001 / Accepted: February 2001     

Nonlinear observers with approximately linear error dynamics: themultivariable case

Exact error linearization uses nonlinear input-output injection to design observers with linear error dynamics in certain coordinates. This approach can only be applied nongenerically. We propose an observer for a wider class of multivariable systems which uniformly minimizes the nonlinear part of the system that cannot be canceled by nonlinear input-output injection. Our approach is numerical, constructive, and provides locally exponentially stable error dynamics. An example compares our design with a high-gain method     

Breaking away from the conventional 'usability lab': the Customer-Centered Design Group at Tektronix, Inc.

The conventional usability lab is primarily responsible for testing prototypes and products to determine if customers will accept a new design. Often this testing comes too late in the development cycle to allow major design or product changes to occur. In the Customer-Centered Design Group at Tektronix Labs, the usability lab is a small part of our group's involvement in the entire design life cycle of a Tektronix product. We work with design groups to bring the benefits of a usability lab to all phases of design, beginning with understanding our customer's current system and work processes to assessing the competitor's strengths and weaknesses to simulating and evaluating design alternatives. Our 'lab' is often on the road; meeting with customers where they work, working with design teams to simulate and prototype designs, and evaluating designs with our customers. To keep in touch with customers and to keep product development focused, we feel a usability group must break down the barriers inherent in a conventional testing suite. By breaking these barriers we can better determine what customers need and how these needs are addressed throughout the entire product life cycle.