Towards Consistency Management for a Business-Driven Development of SOA

The usage of the Service Oriented Architecture (SOA) along with the Business Process Management has emerged as a valuable solution for the complex (business process driven) system engineering. With a Model Driven Engineering where the business process models drive the supporting service component architectures, less effort is gone into the Business/IT alignment during the initial development activities, and the IT developers can rapidly proceed with the SOA implementation. However, the difference between the design principles of the emerging domainspecific languages imposes serious challenges in the following re-design phases. Moreover, enabling evolutions on the business process models while keeping them synchronized with the underlying software architecture models is of high relevance to the key elements of any Business Driven Development (BDD). Given a business process update, this paper introduces an incremental model transformation approach that propagates this update to the related service component configurations. It, therefore, supports the change propagation among heterogenous domainspecific languages, e.g., the BPMN and the SCA. As a major contribution, our approach makes model transformation more tractable to reconfigure system architecture without disrupting its structural consistency. We propose a synchronizer that provides the BPMN-to-SCA model synchronization with the help of the conditional graph rewriting

Semantic model-driven development of service-centric software architectures

Service-oriented architecture (SOA) is a recent architectural paradigm that has received much attention. The prevalent focus on platforms such as Web services, however, needs to be complemented by appropriate software engineering methods. We propose the model-driven development of service-centric software systems. We present in particular an investigation into the role of enriched semantic modelling for a modeldriven development framework for service-centric software systems. Ontologies as the foundations of semantic modelling and its enhancement through architectural pattern modelling are at the core of the proposed approach. We introduce foundations and discuss the benefits and also the challenges in this context

A Model-Driven Architecture Approach to the Efficient Identification of Services on Service-oriented Enterprise Architecture

Service-Oriented Enterprise Architecture requires the efficient development of loosely-coupled and interoperable sets of services. Existing design approaches do not always take full advantage of the value and importance of the engineering invested in existing legacy systems. This paper proposes an approach to define the key services from such legacy systems effectively. The approach focuses on identifying these services based on a Model-Driven Architecture approach supported by guidelines over a wide range of possible service types

Thermally Evolved & Separated Composition of Atmospheric Aerosols: Development and Application of Advanced Data Analysis Techniques for a Thermal Desorption Aerosol Gas Chromatograph (TAG)

Atmospheric organic aerosols are composed of thousands of individual compounds, interacting with climate through changes in aerosol optical properties and cloud interactions, and can be detrimental to human health. Aerosol mass spectrometry (MS) and gas chromatography (GC)-separated MS measurements have been utilized to better characterize the chemical composition of this material that comes from a variety of sources and experiences continuous oxidation while in the atmosphere. This dissertation describes the development of a novel rapid data analysis method for grouping of major components within chromatography-separated measurements and first application using thermal desorption aerosol gas chromatograph (TAG) – MS data. Chromatograms are binned and inserted directly into a positive matrix factorization (PMF) analysis to determine major contributing components, eliminating the need for manual compound integrations of hundreds of resolved molecules, and incorporating the entirety of the eluting MS signal, including Unresolved Complex Mixtures (UCM) and decomposition products that are often ignored in traditional GC-MS analysis. Binned GC-MS data has three dimensions: (1) mass spectra index m/z, (2) bin number, and (3) sample number. PMF output is composed of two dimensions; factor profiles and factor time series. The specific arrangement of the input data (three dimensions of variation structured as a two dimensional matrix) in a two dimensional PMF analysis affects the structure of the PMF profiles and time series output. If mass spectra index is in the profile dimension, and bin number and sample number are in the time series dimension, PMF groups components into factors with similar mass spectra, such as major contributing individual compounds, UCM with similar functional composition, and homologous compound series. This type of PMF analysis is described as the binning method for chromatogram deconvolution, and is presented in Chapter 2. If the sample number is in the time series dimension, and the bin number and mass spectra index, arranged as mass spectra resolved retention time/chromatogram (bin number), are in the profile dimension, PMF groups components with similar time series trends. This type of PMF analysis is described as binning method for source apportionment, and is described in Chapter 3. The binning methods are compared to traditional compound integration methods using previously-collected hourly ambient samples from Riverside, CA during the 2005 Study of Organic Aerosols at Riverside (SOAR) field campaign, as discussed in Chapters 2-3. Further application of the binning method for source apportionment is performed on newly acquired hourly TAG data from East St. Louis, IL, operated as part of the 2013 St. Louis Air Quality Regional Study (SLAQRS). Major sources of biogenic secondary organic aerosol (SOA), anthropogenic primary organic aerosol (POA) were identified, as described in detail in Chapter 4. Finally, our PMF separation method was tested for reliability using primary and secondary sources in a controlled laboratory system. As shown in Chapter 5, we find that for application of PMF on receptor measurements, high signal intensity and unique measurement profiles, like those found in TAG chromatograms, are keys to successful source apportionment. The binning method with component separation by PMF may be a valuable analysis technique for other complex data sets that incorporate measurements (e.g., mass spectrometry, spectroscopy, etc.) with additional separations (e.g., volatility, hygroscopicity, electrical mobility, etc.)

Sources and characteristics of summertime organic aerosol in the Colorado Front Range: perspective from measurements and WRF-Chem modeling

Abstract. The evolution of organic aerosols (OAs) and their precursors in the boundary layer (BL) of the Colorado Front Range during the Front Range Air Pollution and Photochemistry Éxperiment (FRAPPÉ, July–August 2014) was analyzed by in situ measurements and chemical transport modeling. Measurements indicated significant production of secondary OA (SOA), with enhancement ratio of OA with respect to carbon monoxide (CO) reaching 0.085±0.003 µg m−3 ppbv−1. At background mixing ratios of CO, up to  ∼  1.8 µg m−3 background OA was observed, suggesting significant non-combustion contribution to OA in the Front Range. The mean concentration of OA in plumes with a high influence of oil and natural gas (O&G) emissions was  ∼  40 % higher than in urban-influenced plumes. Positive matrix factorization (PMF) confirmed a dominant contribution of secondary, oxygenated OA (OOA) in the boundary layer instead of fresh, hydrocarbon-like OA (HOA). Combinations of primary OA (POA) volatility assumptions, aging of semi-volatile species, and different emission estimates from the O&G sector were used in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) simulation scenarios. The assumption of semi-volatile POA resulted in greater than a factor of 10 lower POA concentrations compared to PMF-resolved HOA. Including top-down modified O&G emissions resulted in substantially better agreements in modeled ethane, toluene, hydroxyl radical, and ozone compared to measurements in the high-O&G-influenced plumes. By including emissions from the O&G sector using the top-down approach, it was estimated that the O&G sector contributed to  <  5 % of total OA, but up to 38 % of anthropogenic SOA (aSOA) in the region. The best agreement between the measured and simulated median OA was achieved by limiting the extent of biogenic hydrocarbon aging and consequently biogenic SOA (bSOA) production. Despite a lower production of bSOA in this scenario, contribution of bSOA to total SOA remained high at 40–54 %. Future studies aiming at a better emissions characterization of POA and intermediate-volatility organic compounds (IVOCs) from the O&G sector are valuable

Introduction to Microservice API Patterns (MAP)

The Microservice API Patterns (MAP) language and supporting website premiered under this name at Microservices 2019. MAP distills proven, platform- and technology-independent solutions to recurring (micro-)service design and interface specification problems such as finding well-fitting service granularities, rightsizing message representations, and managing the evolution of APIs and their implementations. In this paper, we motivate the need for such a pattern language, outline the language organization and present two exemplary patterns describing alternative options for representing nested data. We also identify future research and development directions

Organic aerosol and global climate modelling: a review

The present paper reviews existing knowledge with regard to Organic Aerosol (OA) of importance for global climate modelling and defines critical gaps needed to reduce the involved uncertainties. All pieces required for the representation of OA in a global climate model are sketched out with special attention to Secondary Organic Aerosol (SOA): The emission estimates of primary carbonaceous particles and SOA precursor gases are summarized. The up-to-date understanding of the chemical formation and transformation of condensable organic material is outlined. Knowledge on the hygroscopicity of OA and measurements of optical properties of the organic aerosol constituents are summarized. The mechanisms of interactions of OA with clouds and dry and wet removal processes parameterisations in global models are outlined. This information is synthesized to provide a continuous analysis of the flow from the emitted material to the atmosphere up to the point of the climate impact of the produced organic aerosol. The sources of uncertainties at each step of this process are highlighted as areas that require further studies

The formation, properties and impact of secondary organic aerosol: current and emerging issues

Secondary organic aerosol (SOA) accounts for a significant fraction of ambient tropospheric aerosol and a detailed knowledge of the formation, properties and transformation of SOA is therefore required to evaluate its impact on atmospheric processes, climate and human health. The chemical and physical processes associated with SOA formation are complex and varied, and, despite considerable progress in recent years, a quantitative and predictive understanding of SOA formation does not exist and therefore represents a major research challenge in atmospheric science. This review begins with an update on the current state of knowledge on the global SOA budget and is followed by an overview of the atmospheric degradation mechanisms for SOA precursors, gas-particle partitioning theory and the analytical techniques used to determine the chemical composition of SOA. A survey of recent laboratory, field and modeling studies is also presented. The following topical and emerging issues are highlighted and discussed in detail: molecular characterization of biogenic SOA constituents, condensed phase reactions and oligomerization, the interaction of atmospheric organic components with sulfuric acid, the chemical and photochemical processing of organics in the atmospheric aqueous phase, aerosol formation from real plant emissions, interaction of atmospheric organic components with water, thermodynamics and mixtures in atmospheric models. Finally, the major challenges ahead in laboratory, field and modeling studies of SOA are discussed and recommendations for future research directions are proposed