Abstract
The development of applications for high-performance embedded systems is typically a long and error-prone process. In addition to the required functions, developers must consider various and often conflicting non-functional application requirements such as performance and energy efficiency. The complexity of this process is exacerbated by the multitude of target architectures and the associated retargetable mapping tools. This paper introduces an Aspect-Oriented Programming (AOP) approach that conveys domain knowledge and non-functional requirements to optimizers and mapping tools. We describe a novel AOP language, LARA, which allows the specification of compilation strategies to enable efficient generation of software code and hardware cores for alternative target architectures. We illustrate the use of LARA for code instrumentation and analysis, and for guiding the application of compiler and hardware synthesis optimizations. An important LARA feature is its capability to deal with different join points, action models, and attributes, and to generate an aspect intermediate representation. We present examples of our aspect-oriented hardware/software design flow for mapping real-life application codes to embedded platforms based on Field Programmable Gate Array (FPGA) technology. © 2012 ACM.

Abstract
By combining features from distinct theoretical approaches, namely the evolutionary and the job search, matching and bargaining literatures, we propose a model that captures the main dynamics of a world where heterogeneous firms and workers interact and co-evolve. Within a micro-meso framework, the model focuses on the influence of firms' labour choices ("institutional settings") on industry dynamics, taking into account the existence of employment adjustment costs. The consideration of endogenous matching and bargaining processes in the labour market results in significant frictions, such as the simultaneous coexistence of unfilled job vacancies and unemployment. In a setting where technological progress is not biased a stylized fact of industrialized world economies in the last few decades emerges, the increasing wage inequality. Additionally, turbulence in the industry increases after a negative demand shock. As expected, the negative demand shock causes a decrease in the number of vacancies and, consequently, unemployment rates increase considerably. Interestingly, and mimicking the recent experiences of countries such as US, Spain, Greece and Portugal, the rise in unemployment is matched by a rise in contractual wages. This outcome is explained by the lower ability of the firms to fill their posted vacancies, which results from friction in the interactions among agents.

Abstract
With the rapidly increasing over 60 and over 80 age groups in society, greater emphasis will be put on technology to detect emergency situations, such as falls, in order to promote independent living. This paper describes the development and deployment of fall-detection, activity classification and energy expenditure algorithms, deployed in a tele-monitoring system. These algorithms were successfully tested in an end-user trial involving 9 elderly volunteers using the system for 28 days.

Abstract
With the growing popularity of research in Temporal Information Retrieval (T-IR), a large amount of temporal data is ready to be exploited. The ability to exploit this information can be potentially useful for several tasks. For example, when querying "Football World Cup Germany", it would be interesting to have two separate clusters {1974,2006} corresponding to each of the two temporal instances. However, clustering of search results by time is a non-trivial task that involves determining the most relevant dates associated to a query. In this paper, we propose a first approach to flat temporal clustering of search results. We rely on a second order co-occurrence similarity measure approach which first identifies top relevant dates. Documents are grouped at the year level, forming the temporal instances of the query. Experimental tests were performed using real-world text queries. We used several measures for evaluating the performance of the system and compared our approach with Carrot Web-snippet clustering engine. Both experiments were complemented with a user survey.

Abstract
It is well established that S-shaped curves describe the diffusion processes of many innovations quite well, but little insight on the mechanics of diffusion is achieved by simple curve fitting. We propose an evolutionary model of the diffusion process, focusing on the characteristics of economic agents and on the interactions among them, and relate those determinants with the observed shape of the diffusion curve. Using simulation techniques, we show that the proposed model is able to explain why an innovation may not diffuse globally across an economy/region, even when it faces no rival innovations. Moreover, we show how network size, informational spillovers, and the behavior of innovation prices shape the diffusion process. The results regarding network size and informational spillovers rationalize the importance of informational lock-outs, proving they can influence both the aggregate adoption rate and the speed of the diffusion process. With respect to innovation prices, simulation results show that faster price decline leads to higher aggregate adoption rates, and that the diffusion process is more sensitive to the pricing dynamics than to the network size or the behavior of spillovers.

Abstract
Multi-agent systems paradigm is a suitable approach to implement distributed manufacturing systems addressing the emergent requirements of flexibility, robustness and responsiveness. In such systems, an ontology is a crucial piece to provide a common understanding on the vocabulary used by the intelligent, distributed agents during the exchange of shared knowledge. This paper describes the design of an ontology to define the structure of the knowledge that is used within a multi-agent system integrating process and quality control in production lines for home appliances, which is being developed within the EU FP7 GRACE (inteGration of pRocess and quAlity Control using multi-agEnt technology) project. The ontology schema is validated by instantiating for a case study derived from a washing machines production line.