Classifying aerosol type using in situ surface spectral aerosol optical properties

Knowledge of aerosol size and composition is important for determining radiative forcing effects of aerosols, identifying aerosol sources and improving aerosol satellite retrieval algorithms. The ability to extrapolate aerosol size and composition, or type, from intensive aerosol optical properties can help expand the current knowledge of spatiotemporal variability in aerosol type globally, particularly where chemical composition measurements do not exist concurrently with optical property measurements. This study uses medians of the scattering Ångström exponent (SAE), absorption Ångström exponent (AAE) and single scattering albedo (SSA) from 24 stations within the NOAA/ESRL Federated Aerosol Monitoring Network to infer aerosol type using previously published aerosol classification schemes. Three methods are implemented to obtain a best estimate of dominant aerosol type at each station using aerosol optical properties. The first method plots station medians into an AAE vs. SAE plot space, so that a unique combination of intensive properties corresponds with an aerosol type. The second typing method expands on the first by introducing a multivariate cluster analysis, which aims to group stations with similar optical characteristics and thus similar dominant aerosol type. The third and final classification method pairs 3-day backward air mass trajectories with median aerosol optical properties to explore the relationship between trajectory origin (proxy for likely aerosol type) and aerosol intensive parameters, while allowing for multiple dominant aerosol types at each station. The three aerosol classification methods have some common, and thus robust, results. In general, estimating dominant aerosol type using optical properties is best suited for site locations with a stable and homogenous aerosol population, particularly continental polluted (carbonaceous aerosol), marine polluted (carbonaceous aerosol mixed with sea salt) and continental dust/biomass sites (dust and carbonaceous aerosol); however, current classification schemes perform poorly when predicting dominant aerosol type at remote marine and Arctic sites and at stations with more complex locations and topography where variable aerosol populations are not well represented by median optical properties. Although the aerosol classification methods presented here provide new ways to reduce ambiguity in typing schemes, there is more work needed to find aerosol typing methods that are useful for a larger range of geographic locations and aerosol populations

A Timed Multitasking Architecture for Distributed Embedded Systems

Abstract — The paper presents a software architecture for Distributed Timed Multitasking- a new model of computation that can be used to engineer open, and the same time, predictable embedded systems. Systems are composed from components (actors) that communicate transparently by exchanging labeled messages (signals) over a real-time network. Actors may be viewed as real-time tasks with event-triggered input/output signal drivers. The latter are executed atomically at precisely specified time instants, resulting in the elimination of transaction I/O jitter. Drivers are actually integrated into a middleware component- the Timed Communication Bus, which provides for complete separation of computation and communication, as well as transparent interaction between embedded actors, independent of their allocation on network nodes. The Communication Bus has been conceived as a subsystem of a distributed timed multitasking kernel whose architecture and operation are discussed as well. Index Terms — Distributed hard real-time systems, componentbased design, embedded actors, signal-based communication, timed multitasking, semi-static cyclic scheduling I

A Software Framework for Component-Based Embedded Applications

The widespread use of embedded systems mandates the development of industrial software design methods, i.e. computer-aided design and engineering of embedded applications using formal models (frameworks) and repositories of prefabricated components, much in the same way as in other mature areas of engineering such as mechanical engineering and electronics. These guidelines have been used to develop the COMDES framework and the associated software design method, which are presented in the paper. The framework has been used to systematically define a hierarchy of generic executable components, which can be used as standard building blocks for a broad variety of embedded applications. 1

A Jitter-Free Kernel for Hard Real-Time Systems

Abstract. The paper presents advanced task management techniques featuring Boolean vectors and bitwise vector operations on kernel data structures in the context of the HARTEX TM hard real-time kernel. These techniques have been consistently applied to all aspects of task management and interaction. Hence, the execution time of system functions no longer depends on the number of tasks involved, resulting in predictable, jitter-free kernel operation. This approach has been further extended to time management resulting in a new type of kernel component, which can be used to implement timed multitasking- a novel technique providing for jitter-free execution of hard real-time tasks.

COMDES-II: A Component-Based Framework for Generative Development of Distributed Real-Time Control Systems

The paper presents a generative development methodology and component models of COMDES-II, a component-based software framework for distributed embedded control systems with real-time constraints. The adopted methodology allows for rapid modeling and validation of control software at a higher level of abstraction, from which a system implementation in C can be automatically synthesized. To achieve this objective, COMDES-II defines formally various kinds of components to address the critical requirements of the targeted domain, taking into consideration both the architectural and behavioral aspects of the system. Accordingly, a system can be hierarchically composed from reusable components with heterogeneous models of computation, whereas behavioral aspects of interest are specified independently, following the principle of separation-of-concerns. The paper introduces the established generative methodology for COMDES-II from a general perspective, describes the component models in details and demonstrates their application through a DC-Motor control system case study. 1