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Quality Assessment Mechanisms Implementation
No full textThis deliverable describes the implementation of the quality assessment strategy in Learn PAd. In particular, it describes the implementation of the Model Verification component (MV), and Content Analysis component (CA). The former implements the strategy for formal verification, and understandability checking of BP models. The latter implements the strategy for quality assessment of the natural language content that describes the BP models
Business Process Flexibility - A Systematic Literature Review with a Software Systems Perspective.
No full textBusiness Process flexibility supports organizations in changing their everyday work activities to remain competitive. Since much research has been done on this topic a better awareness on the current state of knowledge is needed. This paper reports the results of a systematic literature review to develop a map on Business Process flexibility with a special focus on software systems related aspects. It covers a spectrum of the state of the art from academic point of view. It includes 164 research works from the main computer science digital libraries. After an introduction into the topic the applied methodology is described. The output of the paper is in the form of schemes and reflections. Starting from the needs for Business Process flexibility, its impact on Business Process life-cycle is introduced. Successively instruments used to express and to support Business Process flexibility are presented together with related validation scenarios. In this paper we also highlight possible future research lines needing further investigations. In particular we identified room for future works in the area of languages for modeling flexibility, on-the-fly verification solutions, adaptation of Business Process running instances, and techniques for evolution recognition
Dual-phase amyloid PET: hitting two birds with one stone
Get PDFOne of the major breakthroughs in Alzheimer\u27s disease (AD) clinical research over the past two decades has been the validation of diagnostic biomarkers able to demonstrate the presence of pathological mechanisms of AD and to predict further cognitive decline and dementia onset in mild cognitive impairment (MCI) patients by identifying the prodromal stage of AD [1, 2]. Among AD biomarkers, two main categories exist: (1) amyloidosis biomarkers, able to identify a molecular feature typical of AD: these include cerebrospinal fluid (CSF) amyloid-?42 reduction and PET imaging using radiotracers selectively binding to the fibrillar aggregates of amyloid-? plaques; (2) neurodegeneration biomarkers reflecting neuronal injury, such as the increase of tau and phosphorylated-tau levels in the CSF, regional atrophy as measured by MRI and demonstration of synaptic dysfunction/degeneration by means of 18F-fluorodeoxyglucose (FDG) PET. Neurodegeneration biomarkers are useful tools for further differential diagnosis among amyloid positive and amyloid negative forms of dementia, and also a prognostic tool in the MCI population
A Customizable Approach for the Automated Quality Assessment of Modelling Artefacts
No full textAbstract-In Model-Driven Engineering (MDE) giving a precise defini- tion of quality models, identifying which quality attributes are of interest for specific stakeholders, and how relating and aggregating together quality attributes are still open issues. The main limitations of currently available quality approaches are limited extensibility, artifact specificity, and manual assessment. This paper proposes an approach supporting the definition of custom quality models consisting of hierarchically organized quality attributes whose evaluation depends on metrics specifically conceived and applied on the modeling artifacts to be analysed. A domain specific language is proposed to specify how quality attributes and metrics have to be aggregated. An execution environment is also provided to apply the defined quality models on actual modeling artifacts so to enable their automated quality assessment. Real applications of the approach are presented by defining and applying explanatory quality models suitably conceived to assess the quality of metamodels and transformations retrieved from public repositories
Ecological restoration of Lake Orta (Northern Italy), one of the largest world\u27s acidified lakes
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Limnology at work: when scientific research leads to the successful recovery of the polluted Lake Orta
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Developing spatially and thematically detailed backdated maps for land cover studies
No full textGlobal or regional land cover change on a decadal time scale can be studied at a high level of detail using the availability of remote sensing data such as that provided by Landsat. However, there are three main technical challenges in this goal. First, the generation of land cover maps without reference data is problematic (backdating). Second, it is important to maintain high accuracies in land cover change map products, requiring a reasonably rich legend within each map. Third, a high level of automation is necessary to aid the management of large volumes of data. This paper describes a robust methodology for processing time series of satellite data over large spatial areas. The methodology includes a retrospective analysis used for the generation of training and test data for historical periods lacking reference information. This methodology was developed in the context of research on global change in the Iberian Peninsula. In this study we selected two scenes covering geographic regions that are representative of the Iberian Peninsula. For each scene, we present the results of two classifications (1985-1989 and 2000-2004 quinquennia), each with a legend of 13 categories. An overall accuracy of over 92% was obtained for all 4 maps
Long-Term monitoring of the flooding regime and hydroperiod of Do?ana Marshes with Landsat Time Series (1974-2014)
No full textThis paper presents a semi-automatic procedure to discriminate seasonally flooded areas in the shallow temporary marshes of Do?ana National Park (SW Spain) by using a radiommetrically normalized long time series of Landsat MSS, TM, and ETM+ images (1974-2014). Extensive field campaigns for ground truth data retrieval were carried out simultaneous to Landsat overpasses. Ground truth was used as training and testing areas to check the performance of the method. Simple thresholds on TM and ETM band 5 (1.55-1.75 m) worked significantly better than other empirical modeling techniques and supervised classification methods to delineate flooded areas at Do?ana marshes. A classification tree was applied to band 5 reflectance values to classify flooded versus non-flooded pixels for every scene. Inter-scene cross-validation identified the most accurate threshold on band 5 reflectance ( < 0.10 despite spectral and spatial resolution differences. Band slicing was retrospectively applied to the complete time series of MSS and TM images. About 391 flood masks were used to reconstruct historical spatial and temporal patterns of Do?ana marshes flooding, including hydroperiod. Hydroperiod historical trends were used as a baseline to understand Do?ana\u27s flooding regime, test hydrodynamic models, and give an assessment of relevant management and restoration decisions. The historical trends in the hydroperiod of Do?ana marshes show two opposite spatial patterns. While the north-western part of the marsh is increasing its hydroperiod, the southwestern part shows a steady decline. Anomalies in each flooding cycle allowed us to assess recent management decisions and monitor their hydrological effects
A threshold-based caching mechanism for distributed network monitoring tools
No full textA critical issue in monitoring and controlling geo-distributed dual-stack networks may be the following one: if a Remote Component has to send all the gathered traffic to the Central Component, the information is doubled with a consequent significant waist of bandwidth. This is particularly true if the gathered information is repeated and redundant. In this case, the information might be preprocessed on the Remote Component to obtain and propagate to the Central Component only the essential part of information useful for the network management. In a distributed statistical-based monitoring tool (i.e. that uses statistics to synthesize the whole information gathered, extracting only the essential pieces of information), the goal of minimizing the exchanged traffic, can be achieved by using a caching mechanism and by processing the gathered information on the Remote Components using simple and efficient algorithms to reduce the flow of information, before sending it to the Central Component.This report describes how to address the latter issue on a Remote Component, introducing a threshold-based caching mechanism for minimizing the transmission of the gathered information to the Central Component and proving its efficiency by showing results obtained by taking some measurements on a real network. This mechanism has been implemented and is used to minimize information exchange in the distributed components of 6MoN