271,225 research outputs found
Missouri River Watershed: the Object for Hydrological Study and Uncertainty of Models
The longest river (2540 mi) and the second drainage area (529 346 mi2) in the North America the Missouri River is one from the most interesting hydrological objects to study. The issue of uncertainty is the basis for any application of knowledge (“Uncertainty is an attribute of information.” From Zadeh, 2005) and has to be one of the main tasks in Earth’s systems study. Knowledge about natural systems (watershed in our case) may be only obtained by the analysis of the empirical (instrumental) data (observations). Principle of Uncertainty is the basic low in Physic. In Hydrology, the Uncertainty starts from the unveiling of the research task by the researcher. The main source of the uncertainty comes from the natural system “extraction” (unit’s boundaries) for modeling and from the limitations of data representing both time and space variability. The watershed has the formal determined boundary and this property places hydrology in the center of regional climate research. The uncertainty is considered in context of time and space with use of cybernetic model of the watershed and described on base of specification of the system in the coordinates on the Earth. The math model does not have criteria to verify itself (Gödel's incompleteness theorems) – multitasks & multiscales studies have to be completed. The data analysis for Upper Missouri River provide a base for regionalization, a multi-scaled description of the structure of river watersheds and their interaction with climate characteristics, and uncertainty of the obtained knowledge. The formulation of the uncertainty for watershed helps to explain the scope of practical applications to be developed, and the tasks to study, communicate and educate the public/communities about water resources and environmental issues, including extreme events like drought/flooding. Science is one of many components of life but the scientist is the only holder of the “truth” and a creator of formal knowledge of the nature. “… data analysis assists in the formulation of a model … A model is merely your reflection of reality and, like probability, it describes neither you nor the world, but only a relationship between you and that world” (From Lindley, “Principles of Statistics”, 2006)
Towards a Formal Framework for Mobile, Service-Oriented Sensor-Actuator Networks
Service-oriented sensor-actuator networks (SOSANETs) are deployed in
health-critical applications like patient monitoring and have to fulfill strong
safety requirements. However, a framework for the rigorous formal modeling and
analysis of SOSANETs does not exist. In particular, there is currently no
support for the verification of correct network behavior after node failure or
loss/addition of communication links. To overcome this problem, we propose a
formal framework for SOSANETs. The main idea is to base our framework on the
\pi-calculus, a formally defined, compositional and well-established formalism.
We choose KLAIM, an existing formal language based on the \pi-calculus as the
foundation for our framework. With that, we are able to formally model SOSANETs
with possible topology changes and network failures. This provides the basis
for our future work on prediction, analysis and verification of the network
behavior of these systems. Furthermore, we illustrate the real-life
applicability of this approach by modeling and extending a use case scenario
from the medical domain.Comment: In Proceedings FESCA 2013, arXiv:1302.478
Formal and Informal Methods for Multi-Core Design Space Exploration
We propose a tool-supported methodology for design-space exploration for
embedded systems. It provides means to define high-level models of applications
and multi-processor architectures and evaluate the performance of different
deployment (mapping, scheduling) strategies while taking uncertainty into
account. We argue that this extension of the scope of formal verification is
important for the viability of the domain.Comment: In Proceedings QAPL 2014, arXiv:1406.156
Verifying service continuity in a satellite reconfiguration procedure: application to a satellite
The paper discusses the use of the TURTLE UML profile to model and verify service continuity during dynamic reconfiguration of embedded software, and space-based telecommunication software in particular. TURTLE extends UML class diagrams with composition operators, and activity diagrams with temporal operators. Translating TURTLE to the formal description technique RT-LOTOS gives the profile a formal semantics and makes it possible to reuse verification techniques implemented by the RTL, the RT-LOTOS toolkit developed at LAAS-CNRS. The paper proposes a modeling and formal validation methodology based on TURTLE and RTL, and discusses its application to a payload software application in charge of an embedded packet switch. The paper demonstrates the benefits of using TURTLE to prove service continuity for dynamic reconfiguration of embedded software
Modeling adaptation with a tuple-based coordination language
In recent years, it has been argued that systems and applications, in order to deal with their increasing complexity, should be able to adapt their behavior according to new requirements or environment conditions. In this paper, we present a preliminary investigation aiming at studying how coordination languages and formal methods can contribute to a better understanding, implementation and usage of the mechanisms and techniques for adaptation currently proposed in the literature. Our study relies on the formal coordination language Klaim as a common framework for modeling some adaptation techniques, namely the MAPE-K loop, aspect- and context-oriented programming
Overview on agent-based social modelling and the use of formal languages
Transdisciplinary Models and Applications investigates a variety of programming languages used in validating and verifying models in order to assist in their eventual implementation. This book will explore different methods of evaluating and formalizing simulation models, enabling computer and industrial engineers, mathematicians, and students working with computer simulations to thoroughly understand the progression from simulation to product, improving the overall effectiveness of modeling systems.Postprint (author's final draft
Modeling Adaptation with Klaim
In recent years, it has been argued that systems and applications, in order to deal with their increasing complexity, should be able to adapt their behavior according to new requirements or environment conditions. In this paper, we present an investigation aiming at studying how coordination languages and formal methods can contribute to a better understanding, implementation and use of the mechanisms and techniques for adaptation currently proposed in the literature. Our study relies on the formal coordination language Klaim as a common framework for modeling some well-known adaptation techniques: the IBM MAPE-K loop, the Accord component-based framework for architectural adaptation, and the aspect- and context-oriented programming paradigms. We illustrate our approach through a simple example concerning a data repository equipped with an automated cache mechanism
Formalising the Continuous/Discrete Modeling Step
Formally capturing the transition from a continuous model to a discrete model
is investigated using model based refinement techniques. A very simple model
for stopping (eg. of a train) is developed in both the continuous and discrete
domains. The difference between the two is quantified using generic results
from ODE theory, and these estimates can be compared with the exact solutions.
Such results do not fit well into a conventional model based refinement
framework; however they can be accommodated into a model based retrenchment.
The retrenchment is described, and the way it can interface to refinement
development on both the continuous and discrete sides is outlined. The approach
is compared to what can be achieved using hybrid systems techniques.Comment: In Proceedings Refine 2011, arXiv:1106.348
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