An additional antecedent of empathic concern: Valuing the welfare of the person in need.

Two experiments examined the role of valuing the welfare of a person in need as an antecedent of empathic concern. Specifically, these experiments explored the relation of such valuing to a well-known antecedent--perspective taking. In Experiment 1, both perspective taking and valuing were manipulated, and each independently increased empathic concern, which, in turn, increased helping behavior. In Experiment 2, only valuing was manipulated. Manipulated valuing increased measured perspective taking and, in part as a result, increased empathic concern, which, in turn, increased helping. Valuing appears to be an important, largely overlooked, situational antecedent of feeling empathy for a person in need. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Improving convergence of Iterative Feedback Tuning

Iterative Feedback Tuning constitutes an attractive control loop tuning method for processes in the absence of an accurate process model. It is a purely data driven approach aiming at optimizing the closed loop performance. The standard formulation ensures an unbiased estimate of the loop performance cost function gradient with respect to the control parameters. This gradient is important in a search algorithm. The extension presented in this paper further ensures informative data to improve the convergence properties of the method and hence reduce the total number of required plant experiments especially when tuning for disturbance rejection. Informative data is achieved through application of an external probing signal in the tuning algorithm. The probing signal is designed based on a constrained optimization which utilizes an approximate black box model of the process. This model estimate is further used to guarantee nominal stability and to improve the parameter update using a line search algorithm for determining the iteration step size. The proposed algorithm is compared to the classical formulation in a simulation study of a disturbance rejection problem. This type of problem is notoriously difficult for Iterative Feedback Tuning due to the lack of excitation from the reference.     

Compositional specification of commercial contracts

We present a declarative language for compositional specification of contracts governing the exchange of resources. It extends Eber and Peyton Jones’s declarative language for specifying financial contracts (Jones et al. in The Fun of Programming. 2003) to the exchange of money, goods and services amongst multiple parties and complements McCarthy’s Resources, Events and Agents (REA) accounting model (McCarthy in Account Rev. LVII(3), 554–578, 1982) with a view- independent formal contract model that supports definition of user-defined contracts, automatic monitoring under execution and user-definable analysis of their state before, during and after execution. We provide several realistic examples of commercial contracts and their analyses. A variety of (real) contracts can be expressed in such a fashion as to support their integration, management and analysis in an operational environment that registers events. The language design is driven by both domain considerations and semantic language design methods: a contract denotes a set of traces of events, each of which is an alternative way of concluding the contract successfully, which gives rise to a CSP-style (Brooker et al. in J.ACM 31(3), 560–599, 1984; Hoare in Communicating Sequential Processes, 1985) denotational semantics. The denotational semantics drives the development of a sound and complete small-step operational semantics, where a partially executed contract is represented as a (full) contract that represents the remaining contractual commitments. This operational semantics is then systematically refined in two stages to an instrumented operational semantics that reflects the bookkeeping practice of identifying the specific contractual commitment a particular event matches at the time the event occurs, as opposed to delaying this matching until the contract is concluded.     

Context-Based Workplace Awareness

Maintaining an awareness of the working context of fellow co-workers is crucial to successful cooperation in a workplace. For mobile, non co-located workers, however, such workplace awareness is hard to maintain. This paper investigates how context-aware computing can be used to facilitate workplace awareness. In particular, we present the concept of Context-Based Workplace Awareness, which is derived from years of in-depth studies of hospital work and the design of computer supported cooperative work technologies to support the distributed collaboration and coordination of clinical work within large hospitals. This empirical background has revealed that an awareness especially of the social, spatial, temporal, and activity context plays a crucial role in the coordination of work in hospitals. The paper then presents and discusses technologies designed to support context-based workplace awareness, namely the AWARE architecture, and the AwarePhone and AwareMedia applications. Based on almost 2 year’ deployment of the technologies in a large hospital, the paper discuss how the four dimension of context-based workplace awareness play out in the coordination of clinical work.     

Parallel Globally Consistent Normal Orientation of Raw Unorganized Point Clouds

A mandatory component for many point set algorithms is the availability of consistently oriented vertex‐normals (e.g. for surface reconstruction, feature detection, visualization). Previous orientation methods on meshes or raw point clouds do not consider a global context, are often based on unrealistic assumptions, or have extremely long computation times, making them unusable on real‐world data. We present a novel massively parallelized method to compute globally consistent oriented point normals for raw and unsorted point clouds. Built on the idea of graph‐based energy optimization, we create a complete kNN‐graph over the entire point cloud. A new weighted similarity criterion encodes the graph‐energy. To orient normals in a globally consistent way we perform a highly parallel greedy edge collapse, which merges similar parts of the graph and orients them consistently. We compare our method to current state‐of‐the‐art approaches and achieve speedups of up to two orders of magnitude. The achieved quality of normal orientation is on par or better than existing solutions, especially for real‐world noisy 3D scanned data.