Abstract
Airborne pollen emission model was used to determine pollen metrics and to examine their relationship with vineyard phenology in two wine regions of Northern Portugal: Vinhos Verdes (1993-2007) and Douro (1992-2011). A number of airborne pollen metrics were obtained through the rate of changes of logistic model adjusted to the time series of airborne pollen. In both regions, the mean absolute differences between observed phenology and model-predicted values for start, peak and final of flowering phenophases were always lower than 5 days and the slope of the regression through the origin is close to one. These metrics can be used to accurately and precisely predict the dynamic of Vitis flowering observed at field level. The model's simplicity and flexibility are of great advantage for its practical use in aerobiology.

Abstract
Owing to the current trends for higher performance and the ever growing availability of multiprocessors in the embedded computing (EC) domain, there is nowadays a strong push towards the parallelization of modern embedded applications. Several real-time task models have recently been proposed to capture different forms of parallelism. However, they do not deal explicitly with control flow information as they assume that all the threads of a parallel task must execute every time the task is activated. In contrast, in this paper, we present a multi-DAG model where each task is characterized by a set of execution flows, each of which represents a different execution path throughout the task code and is modeled as a DAG of sub-tasks. We propose a two-step solution that computes a single synchronous DAG of servers for a task modeled by a multi-DAG and show that these servers are able to supply every execution flow of that task with the required cpu-budget so that the task can execute entirely, irrespective of the execution flow taken at run-time, while satisfying its precedence constraints. As a result, each task can be modeled by its single DAG of servers, which facilitates in leveraging the existing single-DAG schedulability analyses techniques for analyzing the schedulability of parallel tasks with multiple execution flows.

Abstract
This paper presents a holistic timing analysis for fixed-priority fork-join Parallel/Distributed tasks (P/D tasks) over a Flexible Time Triggered - Switched Ethernet (FTT-SE) network. The holistic approach considers both time-triggered and eventtriggered tasks/messages.

Abstract
This paper presents the iMPAcT tool that tests recurring behaviour, i.e., UI Patterns, on mobile applications. This tool is implemented in Java and makes use of Android's APIs UI Automator and UiAutomation. The tool automatically explores a mobile application in order to automatically identify and test UI Patterns. Each UI Pattern has a test strategy, Test Patterns, associated, which is applied when an UI Pattern is found. The approach works on top of a catalogue of UI Patterns, which determines which UI Patterns are to be tested, and what should their correct behaviour be, and may be used for any application.

Abstract
The intermittent nature of wind generation will lead to greater demands for operational flexibility. Traditionally, reserves came from conventional power plants provide the majority of additional required flexibility leading to higher efficiency losses due to technical restrictions of such units. Recently, demand response programs and emerging utility-scale energy storages gained much attention as other flexible options. Under this perspective, this paper proposes a robust optimization scheduling framework to derive an optimal unit commitment decision in systems with high penetration of wind power incorporating demand response programs as well as bulk energy storages in co-optimized energy and reserve markets. In this regard, an improved demand response model is presented using the economic model of responsive loads based on customer's behavior concept that gives choice right opportunity to customers in order to participate in their desired demand response strategy. Moreover, bulk energy storages are considered to be as active market participants. Computational results demonstrate how coordinated operation of different type of demand response programs and bulk energy storages can help accommodate wind power uncertainty from the economic and technical points of view.

Abstract
The organizations' demand to integrate several heterogeneous data sources and an ever-increasing volume of data is revealing the presence of quality problems in data. Currently, most of the data cleaning approaches (for detection and correction of data quality problems) are tailored for data sources with the same schema and sharing the same data model (e.g., relational model). On the other hand, these approaches are highly dependent on a domain expert to specify the data cleaning operations. This paper extends a previously proposed data cleaning methodology that reuses cleaning knowledge specified for other data sources. The methodology is further detailed/refined by specifying the requirements that a data cleaning operations vocabulary must satisfy. Ontologies in RDF/OWL are proposed as the data model for an abstract representation of the data schemas, no matter which data model is used (e.g., relational; graph). Existing approaches, methods and techniques that support the implementation of the proposed methodology, in general, and specifically of the data cleaning operations vocabulary are also presented and discussed in this paper. Copyright