149,426 research outputs found
Function-Theoretic Explanation and the Search for Neural Mechanisms
A common kind of explanation in cognitive neuroscience might be called functiontheoretic:
with some target cognitive capacity in view, the theorist hypothesizes that
the system computes a well-defined function (in the mathematical sense) and explains
how computing this function constitutes (in the systemās normal environment) the
exercise of the cognitive capacity. Recently, proponents of the so-called ānew mechanistā
approach in philosophy of science have argued that a model of a cognitive capacity is
explanatory only to the extent that it reveals the causal structure of the mechanism
underlying the capacity. If they are right, then a cognitive model that resists a transparent
mapping to known neural mechanisms fails to be explanatory. I argue that a functiontheoretic
characterization of a cognitive capacity can be genuinely explanatory even
absent an account of how the capacity is realized in neural hardware
Reusing Test-Cases on Different Levels of Abstraction in a Model Based Development Tool
Seamless model based development aims to use models during all phases of the
development process of a system. During the development process in a
component-based approach, components of a system are described at qualitatively
differing abstraction levels: during requirements engineering component models
are rather abstract high-level and underspecified, while during implementation
the component models are rather concrete and fully specified in order to enable
code generation. An important issue that arises is assuring that the concrete
models correspond to abstract models. In this paper, we propose a method to
assure that concrete models for system components refine more abstract models
for the same components. In particular we advocate a framework for reusing
testcases at different abstraction levels. Our approach, even if it cannot
completely prove the refinement, can be used to ensure confidence in the
development process. In particular we are targeting the refinement of
requirements which are represented as very abstract models. Besides a formal
model of our approach, we discuss our experiences with the development of an
Adaptive Cruise Control (ACC) system in a model driven development process.
This uses extensions which we implemented for our model-based development tool
and which are briefly presented in this paper.Comment: In Proceedings MBT 2012, arXiv:1202.582
On the policy function in continuos time economic models
In this paper, I consider a general class of continuous-time economic models with unbounded horizon. I study the sets of conditions under which the policy function is continuous, Lipschitz continuous, and Cl differentiable. 1 also single out certain postulates which may prevent higher-order differentiability. The analysis provides, therefore, a fmn foundation to the use of dynamic programming methods in continuous time models with unbounded horizo
Mathematical and computer modeling of electro-optic systems using a generic modeling approach
The conventional approach to modelling electro-optic sensor systems is to develop separate models for individual systems or classes of system, depending on the detector technology employed in the sensor and the application. However, this ignores commonality in design and in components of these systems. A generic approach is presented for modelling a variety of sensor systems operating in the infrared waveband that also allows systems to be modelled with different levels of detail and at different stages of the product lifecycle. The provision of different model types (parametric and image-flow descriptions) within the generic framework can allow valuable insights to be gained
A Product Line Systems Engineering Process for Variability Identification and Reduction
Software Product Line Engineering has attracted attention in the last two
decades due to its promising capabilities to reduce costs and time to market
through reuse of requirements and components. In practice, developing system
level product lines in a large-scale company is not an easy task as there may
be thousands of variants and multiple disciplines involved. The manual reuse of
legacy system models at domain engineering to build reusable system libraries
and configurations of variants to derive target products can be infeasible. To
tackle this challenge, a Product Line Systems Engineering process is proposed.
Specifically, the process extends research in the System Orthogonal Variability
Model to support hierarchical variability modeling with formal definitions;
utilizes Systems Engineering concepts and legacy system models to build the
hierarchy for the variability model and to identify essential relations between
variants; and finally, analyzes the identified relations to reduce the number
of variation points. The process, which is automated by computational
algorithms, is demonstrated through an illustrative example on generalized
Rolls-Royce aircraft engine control systems. To evaluate the effectiveness of
the process in the reduction of variation points, it is further applied to case
studies in different engineering domains at different levels of complexity.
Subject to system model availability, reduction of 14% to 40% in the number of
variation points are demonstrated in the case studies.Comment: 12 pages, 6 figures, 2 tables; submitted to the IEEE Systems Journal
on 3rd June 201
Early aspects: aspect-oriented requirements engineering and architecture design
This paper reports on the third Early Aspects: Aspect-Oriented Requirements Engineering and Architecture Design Workshop, which has been held in Lancaster, UK, on March 21, 2004. The workshop included a presentation session and working sessions in which the particular topics on early aspects were discussed. The primary goal of the workshop was to focus on challenges to defining methodical software development processes for aspects from early on in the software life cycle and explore the potential of proposed methods and techniques to scale up to industrial applications
Digital Color Imaging
This paper surveys current technology and research in the area of digital
color imaging. In order to establish the background and lay down terminology,
fundamental concepts of color perception and measurement are first presented
us-ing vector-space notation and terminology. Present-day color recording and
reproduction systems are reviewed along with the common mathematical models
used for representing these devices. Algorithms for processing color images for
display and communication are surveyed, and a forecast of research trends is
attempted. An extensive bibliography is provided
Deriving safety cases for hierarchical structure in model-based development
Model-based development and automated code generation are increasingly used for actual production code, in particular in mathematical and engineering domains. However, since code generators are typically not qualified, there is no guarantee that their output satisfies the system requirements, or is even safe. Here we present an approach to systematically derive safety cases that argue along the hierarchical structure in model-based development. The safety cases are constructed mechanically using a formal analysis, based on automated theorem proving, of the automatically generated code. The analysis recovers the model structure and component hierarchy from the code, providing independent assurance of both code and model. It identifies how the given system safety requirements are broken down into component requirements, and where they are ultimately established, thus establishing a hierarchy of requirements that is aligned with the hierarchical model structure. The derived safety cases reflect the results of the analysis, and provide a high-level argument that traces the requirements on the model via the inferred model structure to the code. We illustrate our approach on flight code generated from hierarchical Simulink models by Real-Time Worksho
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