Active learning: When is more better? The case of resident physicians’ medical errors.

An active learning climate facilitates new knowledge acquisition by encouraging employees to ask questions, seek feedback, reflect on potential results, explore, and experiment. These activities, however, also increase a learner’s chances of erring. In high-reliability organizations, any error is unacceptable and may well be life threatening. The authors use the example of resident physicians to suggest that by adjusting the conditions of priority of safety and managerial safety practices, organizations can balance these potentially conflicting activities. Participants in the study were 123 residents from 25 medical wards. Results demonstrated that the positive linear relationship between priority of safety and safety performance, demonstrated in earlier studies, existed only when the active learning climate was low. When the active learning climate was high, results demonstrated a U-shaped curvilinear relationship between priority of safety and number of errors. In addition, high managerial safety practices mitigated the number of errors as a result of the active learning climate. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Fat-tree routing and node ordering providing contention free traffic for MPI global collectives

As the size of High Performance Computing clusters grows, so does the probability of interconnect hot spots that degrade the latency and effective bandwidth the network provides. This paper presents a solution to this scalability problem for real life constant bisectional-bandwidth fat-tree topologies. It is shown that maximal bandwidth and cut-through latency can be achieved for MPI global collective traffic. To form such a congestion-free configuration, MPI programs should utilize collective communication, MPI-node-order should be topology aware, and the packet routing should match the MPI communication patterns. First, we show that MPI collectives can be classified into unidirectional and bidirectional shifts. Using this property, we propose a scheme for congestion-free routing of the global collectives in fully and partially populated fat trees running a single job. The no-contention result is then obtained for multiple jobs running on the same fat-tree by applying some job size and placement restrictions. Simulation results of the proposed routing, MPI-node-order and communication patterns show no contention which provides a 40% throughput improvement over previously published results for all-to-all collectives.     

A Simple Discretization of the Vector Dirichlet Energy

We present a simple and concise discretization of the covariant derivative vector Dirichlet energy for triangle meshes in 3D using Crouzeix-Raviart finite elements. The discretization is based on linear discontinuous Galerkin elements, and is simple to implement, without compromising on quality: there are two degrees of freedom for each mesh edge, and the sparse Dirichlet energy matrix can be constructed in a single pass over all triangles using a short formula that only depends on the edge lengths, reminiscent of the scalar cotangent Laplacian. Our vector Dirichlet energy discretization can be used in a variety of applications, such as the calculation of Killing fields, parallel transport of vectors, and smooth vector field design. Experiments suggest convergence and suitability for applications similar to other discretizations of the vector Dirichlet energy.     

Capacity of Multiservice WCDMA Networks with Variable GoS

Traditional definitions of capacity of CDMA networks are either related to the number of calls they can handle (pole capacity) or to the arrival rate that guarantees that the rejection rate (or outage) is below a given fraction (Erlang capacity). We extend the latter definition to other quality of service (QoS). We consider best-effort (BE) traffic sharing the network resources with real-time (RT) applications. As is often the case in CDMA systems, we assume that the BE traffic access is done using a time-shared channel (such as the HDR or the HSDPA). BE applications can adapt their instantaneous transmission rate to the available one and thus need not be subject to admission control or outages. Their meaningful QoS is the average delay (i.e. the sojourn time). The delay aware capacity is then defined as the arrival rate of BE calls that the system can handle such that their expected delay is bounded by a given constant. We compute in this paper both the blocking probability of the RT traffic having an adaptive Grade of Service (GoS) as well as the expected delay of the BE traffic for an uplink multicell WCDMA system. This yields the Erlang capacity for former and the delay capacity for the latter. A shorter version of this work was presented at the IEEE WCNC 2003 in New Orleans, LA, USA. Nidhi Hegde received the B.Sc. degree with specialization in Biochemistry (1995) from the University of Alberta, Canada, and the M.Sc (1997) in Computer Science and the Ph.D (2000) degree in Telecommunications and Computer Networking, both at the University of Missouri-Kansas City, USA. She has been with France Telecom R&D since January 2005. Her research interests include performance evaluation of networks, with an emphasis on wireless networks. E. Altman received the B.Sc. degree in electrical engineering (1984), the B.A. degree in physics (1984) and the Ph.D. degree in electrical engineering (1990), all from the Technion-Israel Institute, Haifa. In (1990) he further received his B.Mus. degree in music composition in Tel-Aviv university. Since 1990, he has been with INRIA (National research institute in informatics and control) in Sophia-Antipolis, France. His current research interests include performance evaluation and control of telecommunication networks and in particular congestion control, wireless communications and networking games. He is in the editorial board of several scientific journals: Stochastic Models, JEDC, COMNET, SIAM SICON and WINET. He has been the (co)chairman of the program committee of several international conferences and workshops (on game theory, networking games and mobile networks). More informaion can be found at     

Analysis of AIMD protocols over paths with variable delay

The throughput of AIMD protocols in general and of TCP in particular, has been computed in many existing works by modeling the round-trip time as a constant and thus replacing it by its expectation. There are however many scenarios in which the delays of packets vary, causing a variation of the round-trip time. Many typical scenarios occur in wireless and mobile networks. We propose in this paper an analytical model that accounts for the variability of delay, while computing the throughput of an AIMD protocol. We derive a closed-form expression for the throughput, that illustrates the impact of delay variability. We show by analysis and simulation, that an increase in the variability of delay improves the performance of an AIMD protocol. Thus, an analytical model that only considers the average delay could underestimate the performance of an AIMD protocol in scenarios where delay is variable.     

Continuum equilibria and global optimization for routing in dense static ad hoc networks

We consider massively dense ad hoc networks and study their continuum limits as the node density increases and as the graph providing the available routes becomes a continuous area with location and congestion dependent costs. We study both the global optimal solution as well as the non-cooperative routing problem among a large population of users where each user seeks a path from its origin to its destination so as to minimize its individual cost. Finally, we seek for a (continuum version of the) Wardrop equilibrium. We first show how to derive meaningful cost models as a function of the scaling properties of the capacity of the network and of the density of nodes. We present various solution methodologies for the problem: (1) the viscosity solution of the Hamilton–Jacobi–Bellman equation, for the global optimization problem, (2) a method based on Green’s Theorem for the least cost problem of an individual, and (3) a solution of the Wardrop equilibrium problem using a transformation into an equivalent global optimization problem.     

Advances in Polyimide‐Based Materials for Space Applications

The space environment raises many challenges for new materials development and ground characterization. These environmental hazards in space include solar radiation, energetic particles, vacuum, micrometeoroids and debris, and space plasma. In low Earth orbits, there is also a significant concentration of highly reactive atomic oxygen (AO). This Progress Report focuses on the development of space‐durable polyimide (PI)‐based materials and nanocomposites and their testing under simulated space environment. Commercial PIs suffer from AO‐induced erosion and surface electric charging. Modified PIs and PI‐based nanocomposites are developed and tested to resist degradation in space. The durability of PIs in AO is successfully increased by addition of polyhedral oligomeric silsesquioxane. Conductive materials are prepared based on composites of PI and either carbon nanotube (CNT) sheets or 3D‐graphene structures. 3D PI structures, which can expand PI space applications, made by either additive manufacturing (AM) or thermoforming, are presented. The selection of AM‐processable engineering polymers in general, and PIs in particular, is relatively limited. Here, innovative preliminary results of a PI‐based material processed by the PolyJet technology are presented.     

Computing discrete shape operators on general meshes

Discrete curvature and shape operators, which capture complete information about directional curvatures at a point, are essential in a variety of applications: simulation of deformable two‐dimensional objects, variational modeling and geometric data processing. In many of these applications, objects are represented by meshes. Currently, a spectrum of approaches for formulating curvature operators for meshes exists, ranging from highly accurate but computationally expensive methods used in engineering applications to efficient but less accurate techniques popular in simulation for computer graphics. We propose a simple and efficient formulation for the shape operator for variational problems on general meshes, using degrees of freedom associated with normals. On the one hand, it is similar in its simplicity to some of the discrete curvature operators commonly used in graphics; on the other hand, it passes a number of important convergence tests and produces consistent results for different types of meshes and mesh refinement.     

Reducing error in neural network time series forecasting

Neural network time series forecasting error comprises autocorrelation error, due to an imperfect model, and random noise, inherent in the data. Both problems are addressed here, the first using a two stage training, growth-network neuron: the autocorrelation error (ACE) neuron. The second is considered as a post-processing noise filtering problem. These techniques are applied in forecasting the sunspot time series, with comparison of stochastic, BFGS and conjugate gradient solvers.