Adaptive control of straight worms without derivative measurement

In this paper we consider an adaptive control problem of finite DoF worm-like locomotion systems (WLLS) which contact the ground with Coulomb dry friction. Using a rough mathematical friction law the system is shown to belong to a system class that allows adaptive control. Gaits from the kinematic theory can be tracked by means of adaptive controllers. For this we introduce two different adaptive controllers for λ-tracking and focus on that one which is not based on the derivative of the output. We pay attention to the analysis of such systems and present some theoretical control investigations including proofs. Numerical simulations of tracking different reference signals under arbitrary choice of the system parameters demonstrate and illustrate that the introduced simple adaptive controllers work successfully and effectively. Current experiments are aimed at the justification of theoretical results.     

Smooth velocity approximation for constrained systems in real-time simulation

The rapidly increasing complexity of multi-body system models in applications like vehicle dynamics, robotics and bio-mechanics requires qualitative new solution methods to slash computing times for the dynamical simulation.     

Iterant recombination with one-norm minimization for multilevel Markov chain algorithms via the ellipsoid method

Recently, it was shown how the convergence of a class of multigrid methods for computing the stationary distribution of sparse, irreducible Markov chains can be accelerated by the addition of an outer iteration based on iterant recombination. The acceleration was performed by selecting a linear combination of previous fine-level iterates with probability constraints to minimize the two-norm of the residual using a quadratic programming method. In this paper we investigate the alternative of minimizing the one-norm of the residual. This gives rise to a nonlinear convex program which must be solved at each acceleration step. To solve this minimization problem we propose to use a deep-cuts ellipsoid method for nonlinear convex programs. The main purpose of this paper is to investigate whether an iterant recombination approach can be obtained in this way that is competitive in terms of execution time and robustness. We derive formulas for subgradients of the one-norm objective function and the constraint functions, and show how an initial ellipsoid can be constructed that is guaranteed to contain the exact solution and give conditions for its existence. We also investigate using the ellipsoid method to minimize the two-norm. Numerical tests show that the one-norm and two-norm acceleration procedures yield a similar reduction in the number of multigrid cycles. The tests also indicate that one-norm ellipsoid acceleration is competitive with two-norm quadratic programming acceleration in terms of running time with improved robustness.     

Research on the group decision-making about emergency event based on network technology

In order to improve decision-making efficiency about emergency event, this paper proposes a novel concept, i.e., Agile-Delphi Method, which is an integration of agile decision and Delphi Method implicating that the decision-makers instantly deliver, respond, treat, and utilize information via Delphi process while conducting group decision-making about emergency event. The paper details the mechanism of group decision-making about emergency event based on network technology and Agile-Delphi Method. Finally, the paper conducts an empiric analysis taking the “111 event”, i.e., the liquid ammonia spill event happened on November 1, 2006 in a phosphorus chemical company in China, as an example.     

Influences on standards adoption in de facto standardization

In the IT industry, de facto standards emerge from standards competition as firms offer incompatible technologies, and user choices determine the outcome of the competition. The standards literature suggests that strong network effects create a bias toward a standard with a large installed base, leading to a winner-take-all outcome. More recently, several researchers have revealed that the dynamics of standardization are much more complex than the explanation offered by the economic theory of networks. Markets do not always exhibit tipping behavior so there is not always a single winner in de facto standardization; and the size of an overall installed base does not always exert a strong influence on adoption decisions. In contrast, network effects drawn from local social influence may be more salient to user adoption decisions. We ask: (1) Do we always observe a winner-take-all outcome in de facto standards competition? (2) What are the different technology adoption patterns observed in de facto standards competition? (3) What are the implications of network effects, switching costs, pricing, and functionality enhancement strategies on the outcome of de facto standards competition in different user network structures? Drawing on the economic theory of networks, the complex network theory, and previous work in the standards literature, we examine the influence of network effects, switching costs, price, and technology functionality on user adoption decisions using agent-based simulation. We incorporate underlying user network structures frequently observed in the real world as an important determining factor of user adoption decisions. Our results suggest that de facto standardization process does not always follow a three-phased S-shaped pattern. Winner-take-all is not a necessary outcome of standards competition. User network structures have a significant impact on the dynamics and outcomes of standards competition.     

Cognitive performance-altering effects of electronic medical records: an application of the human factors paradigm for patient safety

According to the human factors paradigm for patient safety, health care work systems and innovations such as electronic medical records do not have direct effects on patient safety. Instead, their effects are contingent on how the clinical work system, whether computerized or not, shapes health care providers’ performance of cognitive work processes. An application of the human factors paradigm to interview data from two hospitals in the Midwest United States yielded numerous examples of the performance-altering effects of electronic medical records, electronic clinical documentation, and computerized provider order entry. Findings describe both improvements and decrements in the ease and quality of cognitive performance, both for interviewed clinicians and for their colleagues and patients. Changes in cognitive performance appear to have desirable and undesirable implications for patient safety as well as for quality of care and other important outcomes. Cognitive performance can also be traced to interactions between work system elements, including new technology, allowing for the discovery of problems with “fit” to be addressed through design interventions.     

Tests and Proofs

This special issue collects current advances in the ongoing attempt to obtain synergies from the combination of Tests and Proofs.     

Direct raycasting of unstructured cell-centered data by discontinuity Roe-average computation

In the field of computational fluid dynamics (CFD), the upwind finite volume method (FVM) is widely applied to solve 3D flows with discontinuity phenomena (e.g., shock waves). It produces unstructured data at the center of each cell (cell-centered data) with the flow discontinuity constraint on the inner-face between face-neighboring cells. For visualization, existing approaches with interpolation usually pre-extrapolate cell-centered data into cell-vertexed data (data values given at cell vertices) and only handle cell-vertexed data during actual rendering, which unconsciously depress the rendering accuracy and violate the discontinuity constraint. In this paper, we propose a novel method to visualize cell-centered data directly avoiding extrapolation and keep the discontinuity in the rendering data on the framework of multi-pass raycasting. During resampling, the field is reconstructed using the original cell-centered data value and the cell-gradient estimated by Green–Gauss theorem. To keep the discontinuity, we reconstruct the field at an inner-face resampled point using both the face-adjacencies and get two discontinuous field values. Then the field is obtained by computing Roe-average of the two. The analysis and experiments demonstrate that our approach gains a high-accuracy reconstruction and leads to a high-quality image.