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.     

Service Composition Issues in Pervasive Computing

Providing new services by combining existing ones—or service composition—is an idea pervading pervasive computing. Pervasive computing technologies seek to concurrently exhibit context awareness, manage contingencies, leverage device heterogeneity, and empower users. These four goals prompt service-composition-mechanism design requirements that are unique to pervasive computing. This article catalogs service composition mechanisms and describes their variation points, which indicate how well the resulting compositions meet the four goals.     

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.     

Land cover classification with coarse spatial resolution data to derive continuous and discrete maps for complex regions

Regularly updated land cover information at continental or national scales is a requirement for various land management applications as well as biogeochemical and climate modeling exercises. However, monitoring or updating of map products with sufficient spatial detail is currently not widely practiced due to inadequate time-series coverage for most regions of the Earth. Classifications of coarser spatial resolution data can be automatically generated on an annual or finer time scale. However, discrete land cover classifications of such data cannot sufficiently quantify land surface heterogeneity or change. This study presents a methodology for continuous and discrete land cover mapping using moderate spatial resolution time series data sets. The method automatically selects sample data from higher spatial resolution maps and generates multiple decision trees. The leaves of decision trees are interpreted considering the sample distribution of all classes yielding class membership maps, which can be used as estimates for the diversity of classes in a coarse resolution cell. Results are demonstrated for the heterogeneous, small-patch landscape of Germany and the bio-climatically varying landscape of South Africa. Results have overall classification accuracies of 80%. A sensitivity analysis of individual modules of the classification process indicates the importance of appropriately chosen features, sample data balanced among classes, and an appropriate method to combine individual classifications. The comparison of classification results over several years not only indicates the method's consistency, but also its potential to detect land cover changes.     

Putting it all in the trunk: incremental software development in the FreeBSD open source project

Abstract. Software development in the FreeBSD project is incremental in the sense that a stream of contributions, including bugfixes and minor and major new features, go into a single branch in the repository, the development branch (or 'trunk'), and are required to preserve the software in a working state. This creates a succession of development releases, akin to the practice of frequent releasing argued by Eric S. Raymond in his essay 'The Cathedral and the Bazaar' to be the key to the success of Linux and other open source projects. The positive and negative impact of this approach is discussed based on a survey involving 72 project participants. On the positive side, the data indicate that it creates a highly motivating 'see bug, fix bug, see bug fixed in new release' life cycle, and helps integrate bugfixing with new development. On the negative side, the data indicates that the highly incremental model does not support the development of complex new features.     

Oxidation of proteins: Basic principles and perspectives for blood proteomics

Protein oxidation mechanisms result in a wide array of modifications, from backbone cleavage or protein crosslinking to more subtle modifications such as side chain oxidations. Protein oxidation occurs as part of normal regulatory processes, as a defence mechanism against oxidative stress, or as a deleterious processes when antioxidant defences are overcome. Because blood is continually exposed to reactive oxygen and nitrogen species, blood proteomics should inherently adopt redox proteomic strategies. In this review, we recall the biochemical basis of protein oxidation, review the proteomic methodologies applied to analyse redox modifications, and highlight some physiological and in vitro responses to oxidative stress of various blood components.     

Mass and position determination of attached particles on cantilever based mass sensors

An analytical expression relating mass and position of a particle attached on a cantilever to the resulting change in cantilever resonant frequency is derived. Theoretically, the position and mass of the attached particle can be deduced by combining measured resonant frequencies of several bending modes. This finding is verified experimentally using a microscale cantilever with and without an attached gold bead. The resonant frequencies of several bending modes are measured as a function of the bead position. The bead mass and position calculated from the measured resonant frequencies are in good agreement with the expected mass and the position measured.