Model based code generation for distributed embedded systems

Embedded systems are becoming increasingly complex and more distributed. Cost and quality requirements necessitate reuse of the functional software components for multiple deployment architectures. An important step is the allocation of software components to hardware. During this process the differences between the hardware and application software architectures must be reconciled. In this paper we discuss an architecture driven approach involving model-based techniques to resolve these differences and integrate hardware and software components. The system architecture serves as the underpinning based on which distributed real-time components can be generated. Generation of various embedded system architectures using the same functional architecture is discussed. The approach leverages the following technologies – IME (Integrated Modeling Environment), the SAE AADL (Architecture Analysis and Design Language), and Ocarina. The approach is illustrated using the electronic throttle control system as a case study

Preliminary Functional-Structural Modeling on Poplar (Salicaceae)

Poplar is one of the best fast-growing trees in the world, widely used for windbreak and wood product. Although architecture of poplar has direct impact on its applications, it has not been descried in previous poplar models, probably because of the difficulties raised by measurement, data processing and parameterization. In this paper, the functional-structural model GreenLab is calibrated by using poplar data of 3, 4, 5, 6 years old. The data was acquired by simplifying measurement. The architecture was also simplified by classifying the branches into several types (physiological age) using clustering analysis, which decrease the number of parameters. By multi-fitting the sampled data of each tree, the model parameters were identified and the plant architectures at different tree ages were simulated

3D modelling of branching in plants

Shoot branching is a key determinant of overall aboveground plant form. During plant development, the number of branches formed strongly influences the amount of light absorbed by the plant, and thus the plant’s competitive strength in terms of light capture in relation to neighbouring plants. Branching is regulated by multiple internal factors which are modulated by different environmental signals. A key environmental signal in the context of a plant population is a low red / far-red intensity ratio (R:FR) of the light reflected by neighbouring plants. For instance, low R:FR results in suppression of branching in favour of elongation growth, which is a key aspect of shade avoidance. Shade avoidance enables plants to anticipate future competition by preventing being shaded, rather than to react to prevailing shade conditions. Internally, branching is regulated by a finely tuned plant hormone network. The interactions within this network are modified by environmental cues such as R:FR which is perceived by specific photoreceptors. Combined, internal and external signals enable regulation of branch formation under the influence of environmental conditions. The different aspects of branching control act at different levels of biological organization (organ, whole plant, plant community). These aspects can be integrated in one modelling approach, called functional-structural plant modelling (FSPM), explicitly considering spatial 3D plant development. An FSP model typically contains detailed information at any moment in development of the plant on the number, size, location and orientation of all organs that make up the plant. In FSP models, physiological and physical processes occur within the plant (e.g. photosynthesis and transport of assimilates), and interaction with the environment occurs at the interface of organ and environment (e.g. light absorption by a leaf). Explicit simulation of absorption and scattering of light at the level of the plant organ is an important aspect of FSPM. In combination with dedicated experiments, this modelling tool can be used to analyse the response of plants to (imminent) competition, simulate the competitive advantage of shade avoidance for plants of different architecture, and predict plant form in various light environments. To assess the effect of plant population density through R:FR signalling on tillering (branching) in spring wheat (Triticum aestivum L.), an FSPM study was conducted (Figure 1). A simple descriptive relationship was used to link R:FR as perceived by the plant to extension growth of tiller buds and probability of a bud to form a tiller. A further study included a complete sub-model of branching regulation, aiming at simulating branching as an emergent property in Arabidopsis (Arabidopsis thaliana) under the influence of R:FR. These and other studies show that FSPM is a promising tool to simulate aspects of plant development, such as branching, under the influence of environmental factors. In close combination with dedicated experiments, FSPM can shape our ideas of the mechanisms controlling plant development, can integrate existing knowledge on plant development, and can predict plant development in untested conditions

A rule-based functional-structural model of rice considering source and sink functions

As a first step towards a generic genotype-phenotype model of rice, we present here a model of the growth and morphology of rice in combination with ecophysiological processes using the technique of functional-structural plant modelling (FSPM) and the interactive modelling platform GroIMP along with the graph-based Relational Growth Grammar formalism. The model constitutes a simple yet functionally coherent phenotype model of rice, consisting of a set of morphogenetic RGG rules describing an “average” developmental course and final morphology, partially linking yield traits to processes (tiller and grain number, stem length, grain filling rate, grain weight)

Consciosusness in Cognitive Architectures. A Principled Analysis of RCS, Soar and ACT-R

This report analyses the aplicability of the principles of consciousness developed in the ASys project to three of the most relevant cognitive architectures. This is done in relation to their aplicability to build integrated control systems and studying their support for general mechanisms of real-time consciousness.\ud To analyse these architectures the ASys Framework is employed. This is a conceptual framework based on an extension for cognitive autonomous systems of the General Systems Theory (GST).\ud A general qualitative evaluation criteria for cognitive architectures is established based upon: a) requirements for a cognitive architecture, b) the theoretical framework based on the GST and c) core design principles for integrated cognitive conscious control systems

Time for a plant structural economics spectrum

We argue that tree and crown structural diversity can and should be integrated in the whole-plant economics spectrum. Ecologists have found that certain functional trait combinations have been more viable than others during evolution, generating a trait trade-off continuum which can be summarized along a few axes of variation, such as the "worldwide leaf economics spectrum" and the "wood economics spectrum." However, for woody plants the crown structural diversity should be included as well in the recently introduced "global spectrum of plant form and function," which now merely focusses on plant height as structural factor. The recent revolution in terrestrial laser scanning (TLS) unlocks the possibility to describe the three dimensional structure of trees quantitatively with unprecedented detail. We demonstrate that based on TLS data, a multidimensional structural trait space can be constructed, which can be decomposed into a few descriptive axes or spectra. We conclude that the time has come to develop a "structural economics spectrum" for woody plants based on structural trait data across the globe. We make suggestions as to what structural features might lie on this spectrum and how these might help improve our understanding of tree form-function relationships

Using numerical plant models and phenotypic correlation space to design achievable ideotypes

Numerical plant models can predict the outcome of plant traits modifications resulting from genetic variations, on plant performance, by simulating physiological processes and their interaction with the environment. Optimization methods complement those models to design ideotypes, i.e. ideal values of a set of plant traits resulting in optimal adaptation for given combinations of environment and management, mainly through the maximization of a performance criteria (e.g. yield, light interception). As use of simulation models gains momentum in plant breeding, numerical experiments must be carefully engineered to provide accurate and attainable results, rooting them in biological reality. Here, we propose a multi-objective optimization formulation that includes a metric of performance, returned by the numerical model, and a metric of feasibility, accounting for correlations between traits based on field observations. We applied this approach to two contrasting models: a process-based crop model of sunflower and a functional-structural plant model of apple trees. In both cases, the method successfully characterized key plant traits and identified a continuum of optimal solutions, ranging from the most feasible to the most efficient. The present study thus provides successful proof of concept for this enhanced modeling approach, which identified paths for desirable trait modification, including direction and intensity.Comment: 25 pages, 5 figures, 2017, Plant, Cell and Environmen