Abstract
Most reconfigurable computing architectures suffer from computationally demanding Placement and Routing (P&R) steps which might hamper their use in contexts requiring dynamic compilation (e.g., to guarantee application portability in embedded systems). Bearing in mind the simplification of P&R steps, this paper presents and analyzes a coarse-grained reconfigurable array extended with global Omega Networks. We show that integrating one or two Omega Networks in a coarse-grained array simplifies the P&R stage with both low hardware resource overhead and low performance degradation (18% for an 8 x 8 array). The experimental results included permit to compare the coarse-grained array with one or two Omega Networks with a coarse-grained array based on a grid of processing elements with neighbor connections. When comparing the execution time to perform the P&R stage needed for the two arrays, we show that the array using two Omega Networks needs a far simple P&R which for the benchmarks used completed on average in about 20x less time.

Abstract
The need to improve communication between humans and computers has been instrumental in defining new communication models, and accordingly, new ways of interacting with machines. The use of gestures as a means of communication has been a challenging task. The latest generation of smartphones boasts powerful processors and built-in video cameras, making them capable of executing complex and computationally demanding applications. Thus, the integration of gesture recognition systems in smartphone applications might be a close reality. In this paper, we present studies of a gesture recognition prototype system for smartphones. We use a number of tasks typically employed in gesture recognition systems which permit to assess the current feasibility of smartphones to implement this kind of systems. Based on both the execution time and classification performance, we conclude that the latest smartphone generation is capable of executing complex image processing applications, with the most penalizing factor being camera performance regarding capture rates with the current J2ME support. Copyright 2009 ACM.

Abstract
The ability to infer user context based on a mobile device together with a set of external sensors opens up the way to new context-aware services and applications. In this paper, we describe a mobile context provider that makes use of sensors available in a smartphone as well as sensors externally connected via bluetooth. We describe the system architecture from sensor data acquisition to feature extraction, context inference and the publication of context information to well-known social networking services such as Twitter and Hi5. In the current prototype, context inference is based on decision trees, but the middleware allows the integration of other inference engines. Experimental results suggest that the proposed solution is a promising approach to provide user context to both local and network-level services.

Abstract
The growing processing capabilities of mobile devices coupled with portable and wearable sensors have enabled the development of context-aware services tailored to the user environment and its daily activities. The problem of determining the user context at each particular point in time is one of the main challenges in this area. In this paper, we describe the approach pursued in the UPCASE project, which makes use of sensors available in the mobile device as well as sensors externally connected via Bluetooth. We describe the system architecture from raw data acquisition to feature extraction and context inference. As a proof of concept, the inference of contexts is based on a decision tree to learn and identify contexts automatically and dynamically at runtime. Preliminary results suggest that this is a promising approach for context inference in several application scenarios.

Abstract
Embedded systems are considered one of the most potential areas for future innovations. Two embedded fields that will most certainly take a primary role in future innovations are mobile robotics and mobile computing. Mobile robots and srnartphones are growing in number and functionalities. becoming a presence in our daily life. In this paper, we study the current feasibility of a smartphone to execute navigation algorithms. As a test case, we use a smartphone to control an autonomous mobile robot. We tested three navigation problems: Mapping, Localization and Path Planning. For each of these problems, an algorithm has been chosen, developed in J2ME, and tested on the field. Results show the current mobile Java capacity for executing computationally demanding algorithms and reveal the real possibility of using smartphones for autonomous navigation.

Abstract
Reconfigurable computing architectures are becoming increasingly important in many computing domains (e.g., embedded and high-performance systems). These architectures promise comparable characteristics to specific hardware solutions with the flexibility and programmability of microprocessor solutions. This chapter gives a comprehensible overview of reconfigurable computing concepts and programming paradigms for the current and future generation of reconfigurable computing architectures. Two paramount aspects are highlighted: understanding how the programming model can help the mapping of computations to these architectures, and understanding also the way new programming models can be used to develop applications to these architectures. We include a set of simple examples to show different aspects of the use of the reconfigurable computing synergies, driven by the initial programming model used. © 2010, IGI Global.