Orchestrating Tuple-based Languages

The World Wide Web can be thought of as a global computing architecture supporting the deployment of distributed networked applications. Currently, such applications can be programmed by resorting mainly to two distinct paradigms: one devised for orchestrating distributed services, and the other designed for coordinating distributed (possibly mobile) agents. In this paper, the issue of designing a pro- gramming language aiming at reconciling orchestration and coordination is investigated. Taking as starting point the orchestration calculus Orc and the tuple-based coordination language Klaim, a new formalism is introduced combining concepts and primitives of the original calculi. To demonstrate feasibility and effectiveness of the proposed approach, a prototype implementation of the new formalism is described and it is then used to tackle a case study dealing with a simplified but realistic electronic marketplace, where a number of on-line stores allow client applications to access information about their goods and to place orders

A Java Middleware for Guaranteeing Privacy of Distributed Tuple Spaces

The tuple space communication model, such as the one used in Linda, provides great flexibility for modeling concurrent, distributed and mobile processes. In a distributed setting with mobile agents, particular attention is needed for protecting sites and information. We have designed and developed a Java middleware, Klava, for implementing distributed tuple spaces and operations to support agent interaction and mobility. In this paper, we extend the Klava middleware with cryptographic primitives that enable encryption and decryption of tuple fields. We describe the actual implementation of the new primitives and provide a few examples. The proposed extension is general enough to be applied to similar Java frameworks using multiple distributed tuples spaces possibly dealing with mobility

Monitoring Networks through Multiparty Session Types

In large-scale distributed infrastructures, applications are realised through communications among distributed components. The need for methods for assuring safe interactions in such environments is recognized, however the existing frameworks, relying on centralised verification or restricted specification methods, have limited applicability. This paper proposes a new theory of monitored π-calculus with dynamic usage of multiparty session types (MPST), offering a rigorous foundation for safety assurance of distributed components which asynchronously communicate through multiparty sessions. Our theory establishes a framework for semantically precise decentralised run-time enforcement and provides reasoning principles over monitored distributed applications, which complement existing static analysis techniques. We introduce asynchrony through the means of explicit routers and global queues, and propose novel equivalences between networks, that capture the notion of interface equivalence, i.e. equating networks offering the same services to a user. We illustrate our static-dynamic analysis system with an ATM protocol as a running example and justify our theory with results: satisfaction equivalence, local/global safety and transparency, and session fidelity

Rates for the reactions antiproton-proton --> pi phi and gamma phi

We study antiproton-proton annihilation at rest into $\pi\phi$ and $\gamma\phi$. Rescattering by $\overline{K^*}K+K^*\overline{K}$ and $\rho^{+}\rho^{-}$ for $\overline{p}p\rightarrow\pi\phi$ states is sizable, of order $(0.90\, {\rm to}\,2.6)\times 10^{-4}$ in the branching ratio, but smaller than experiment. For $\overline{p}p\rightarrow\gamma\phi$ the rescattering contributions are negligible, but the $\gamma\phi$ channel is well explained by a $\rho\phi$ intermediate state combined with vector meson dominance.Comment: 12 pages, plain latex, 2 postscript figures available upon request, PSI-PR-93-2

Inertial Sensor Based Modelling of Human Activity Classes: Feature Extraction and Multi-sensor Data Fusion Using Machine Learning Algorithms

Wearable inertial sensors are currently receiving pronounced interest due to applications in unconstrained daily life settings, ambulatory monitoring and pervasive computing systems. This research focuses on human activity recognition problem, in which inputs are multichannel time series signals acquired from a set of body-worn inertial sensors and outputs are automatically classified human activities. A general-purpose framework has been presented for designing and evaluating activity recognition system with six different activities using machine learning algorithms such as support vector machine (SVM) and artificial neural networks (ANN). Several feature selection methods were explored to make the recognition process faster by experimenting on the features extracted from the accelerometer and gyroscope time series data collected from a number of volunteers. In addition, a detailed discussion is presented to explore how different design parameters, for example, the number of features and data fusion from multiple sensor locations - impact on overall recognition performance

Deposição de gotas por pulverizações terrestre e aérea na cultura do algodoeiro.

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