Bringing Scheme programming to the iPhone—Experience

The iPhone SDK provides a powerful platform for the development of applications that make use of iPhone capabilities, such as sensors, GPS, Wi‐Fi, or Bluetooth connectivity. We observe that so far the development of iPhone applications has mostly been restricted to using Objective‐C. However, developing applications in plain Objective‐C on the iPhone OS suffers from limitations, such as the need for explicit memory management and lack of syntactic extension mechanism. Moreover, when developing distributed applications in Objective‐C, programmers have to manually deal with distribution concerns, such as service discovery, remote communication, and failure handling. In this paper, we discuss our experience in porting the Scheme programming language to the iPhone OS and how it can be used together with Objective‐C to develop iPhone applications. To support the interaction between Scheme programs and the underlying iPhone APIs, we have implemented a language symbiosis layer that enables programmers to access the iPhone SDK libraries from Scheme. In addition, we have designed high‐level distribution constructs to ease the development of distributed iPhone applications in an event‐driven style. We validate and discuss these constructs with a series of examples, including an iPod controller, a maps application, and a distributed multiplayer Scrabble‐like game. We discuss the lessons learned from this experience for other programming language ports to mobile platforms. Copyright © 2011 John Wiley & Sons, Ltd.     

Predicting change for individual psychotherapy clients on the basis of their nearest neighbors.

This study extended client-focused research by using the nearest neighbor (NN) approach, a client-specific sampling and prediction strategy derived from research on alpine avalanches. Psychotherapy clients (N = 203) seen in routine practice settings in the United Kingdom completed a battery of intake measures and then completed symptom intensity ratings before each session. Forecasts of each client's rate of change and session-by-session variability were computed on the basis of that client's NNs (n = 10-50 in different comparisons). Alternative forecasts used linear or log-linear slopes and were compared with an alternative prediction strategy. Results showed that the NN approach was superior to the alternative model in predicting rate of change, though the advantage was less clear for predicting variability. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

SUSANS With Polarized Neutrons

Super Ultra-Small Angle Neutron Scattering (SUSANS) studies over wave vector transfers of 10^–4 nm^–1 to 10^–3 nm^–1 afford information on micrometer-size agglomerates in samples. Using a right-angled magnetic air prism, we have achieved a separation of ≈10 arcsec between ≈2 arcsec wide up- and down-spin peaks of 0.54 nm neutrons. The SUSANS instrument has thus been equipped with the polarized neutron option. The samples are placed in a uniform vertical field of 8.8 × 10⁴ A/m (1.1 kOe). Several magnetic alloy ribbon samples broaden the up-spin neutron peak significantly over the ±1.3 × 10^–3 nm^–1 range, while leaving the down-spin peak essentially unaltered. Fourier transforms of these SUSANS spectra corrected for the instrument resolution, yield micrometer-range pair distribution functions for up- and down-spin neutrons as well as the nuclear and magnetic scattering length density distributions in the samples.     

Model Driven Performance Analysis of Enterprise Information Systems

This paper describes the particular motivation for performance analysis in the domain of Enterprise Information Systems (EISs) and argues that the Model Driven Architecture (MDA) is a suitable framework for integrating formal analysis techniques with engineering methods appropriate to the domain. The MDA permits natural and economical modelling of design and analysis domains and the relationships between them, supporting both manual and automatic analysis. It incorporates the Unified Modelling Language (UML), which is extensively used to capture system designs. We present our general modelling approach and outline its use in relating models of Enterprise Java Bean (EJB) applications, annotated using standard profiles, to analysable formal models.     

Large-scale mapping of boreal forest in SIBERIA using ERS tandem coherence and JERS backscatter data

Siberia's boreal forests represent an economically and ecologically precious resource, a significant part of which is not monitored on a regular basis. Synthetic aperture radars (SARs), with their sensitivity to forest biomass, offer mapping capabilities that could provide valuable up-to-date information, for example about fire damage or logging activity. The European Commission SIBERIA project had the aim of mapping an area of approximately 1 million km² in Siberia using SAR data from two satellite sources: the tandem mission of the European Remote Sensing Satellites ERS-1/2 and the Japanese Earth Resource Satellite JERS-1. Mosaics of ERS tandem interferometric coherence and JERS backscattering coefficient show the wealth of information contained in these data but they also show large differences in radar response between neighbouring images. To create one homogeneous forest map, adaptive methods which are able to account for brightness changes due to environmental effects were required. In this paper an adaptive empirical model to determine growing stock volume classes using the ERS tandem coherence and the JERS backscatter data is described. For growing stock volume classes up to 80 m³/ha, accuracies of over 80% are achieved for over a hundred ERS frames at a spatial resolution of 50 m.     

Analysis of numerical methods for the simulation of deformable models

Simulating deformable objects based on physical laws has become the most popular technique for modeling textiles, skin, or volumetric soft objects like human tissue. The physical model leads to an ordinary differential equation. Recently, several approaches to fast algorithms have been proposed.In this work, more profound numerical background about numerical stiffness is provided. Stiff equations impose stability restrictions on a numerical integrator. Some one-step and multistep methods with adequate stability properties are presented. For an efficient implementation, the inexact Newton method is discussed. Applications to 2D and 3D elasticity problems show that the discussed methods are faster and give higher-quality solutions than the commonly used linearized Euler method.     

Coordination in networks: An economic equilibrium analysis

Networks utilizing modern communication technologies can offer competitive advantages to those using them wisely. But due to the existence of network effects, planning and operating cooperation networks is difficult. In this paper, the strategic situation of individual agents deciding on network participation is analysed. A systematic equilibrium analysis using computer-based simulations reveals principal solution scenarios for network agents and shows that network cooperation problems might frequently be not as difficult to resolve as often feared. In particular, strategic situations are identified showing that a majority of individuals might be better off getting the optimal solution from a central principal and that in many cases simple information intermediation can solve the start-up problem notorious in network economics.     

The Attentional Dynamics of Masked Detection.

A dichoptic masking procedure was used to test whether the mask-dependent cuing effects found in luminance detection by P. L. Smith (2000a) were due to integration masking or interruption masking. Attentional cuing enhanced detection sensitivity (d') when stimuli were backwardly masked with either dichoptic or monoptic masks, whereas no cuing effect was found with unmasked stimuli, implying the mask dependencies were due to interruption of stimulus processing in visual cortex by the mask. The effect is predicted by a gated diffusion process model in which masks interrupt stimulus processing and attention controls the flow of information to a sequential-sampling decision mechanism. The model correctly predicts different patterns of performance for detection and discrimination and cuing effects in simple reaction time. (PsycINFO Database Record (c) 2010 APA, all rights reserved)