Abstract
Innovation and knowledge creation are tightly related concepts. Collaborative innovation networks (COINs) are very productive ecosystems for knowledge generation. Acknowledging their relevance for innovation, we propose a novel ontology for knowledge management (KM) in COINs, which builds on COINs related literature and is partially derived from topic-related and enterprise ontologies. The utility of the ontology is illustrated through an application case in a software house. The ontology can be applied in different cases involving KM in COINs, such as support the development of IT-based KM services for knowledge co-creation in COINs or, be used as an auditing tool in collaborative innovation processes. © 2016 Inderscience Enterprises Ltd.

Abstract
Previous studies of market power within a regional system have considered multiple competing generation operators and the role of transmission constraints. However, these studies typically assume simplified structures in which each operator is restricted to a unique node in a transmission constrained network. Real systems typically have operators making decisions for units in several zones at once. Past studies also implicitly treated market power as a static concept for a given set of market rules and network configuration. We demonstrate that market power is dynamic, and can vary significantly with fuel prices and even with large-scale weather patterns. We also demonstrate the impact on region-wide market power of operators that manage units in multiple zones. We use the Electric Reliability Council of Texas (ERCOT) as an illustrative case study, and apply a conjectured supply function equilibrium (CSFE) approach that accounts for transmission constraints. We show that the companies with greater influence on the market price will depend on the relative prices of coal and natural gas. We also show that a weather event, such as a period without any wind, can have a substantial impact on market power.

Abstract
This chapter provides an overview of the procedural modelling methodology that is addressed in this book. With the purpose of pointing out its need, the current issues in Procedural Modelling will be highlighted. In addition, the justification of some strategic decisions made during the development activities will be presented along with a brief enlightenment of the aforementioned methodology. © The Author(s) 2016.

Abstract
This paper describes the development of a novel microfluidic platform for multifactorial analysis integrating four label-free detection methods: electrical impedance, refractometry, optical absorption and fluorescence. We present the rationale for the design and the details of the microfabrication of this multifactorial hybrid microfluidic chip. The structure of the platform consists of a three-dimensionally patterned polydimethylsiloxane top part attached to a bottom SU-8 epoxy-based negative photoresist part, where microelectrodes and optical fibers are incorporated to enable impedance and optical analysis. As a proof of concept, the chip functions have been tested and explored, enabling a diversity of applications: (i) impedance-based identification of the size of micro beads, as well as counting and distinguishing of erythrocytes by their volume or membrane properties; (ii) simultaneous determination of the refractive index and optical absorption properties of solutions; and (iii) fluorescence-based bead counting.

Abstract
This paper addresses the problem of maximising the expected number of transplants in kidney exchange programmes. New schemes for matching rearrangement in case of failure are presented, along with a new tree search algorithm used for the computation of optimal expected values. Extensive computational experiments demonstrate the effectiveness of the algorithm and reveal a clear superiority of a newly proposed scheme, subset-recourse, as compared to previously known approaches.

Abstract
This paper presents an autonomous navigation and position estimation framework which enables an Unmanned Aerial Vehicle (UAV) to possess the ability to safely navigate in indoor environments. This system uses both the on-board Inertial Measurement Unit (IMU) and the front camera of a AR. Drone platform and a laptop computer were all the data is processed. The system is composed of the following modules: navigation, door detection and position estimation. For the navigation part, the system relies on the detection of the vanishing point using the Hough transform for wall detection and avoidance. The door detection part relies not only on the detection of the contours but also on the recesses of each door using the latter as the main detector and the former as an additional validation for a higher precision. For the position estimation part, the system relies on pre-coded information of the floor in which the drone is navigating, and the velocity of the drone provided by its IMU. Several flight experiments show that the drone is able to safely navigate in corridors while detecting evident doors and estimate its position. The developed navigation and door detection methods are reliable and enable an UAV to fly without the need of human intervention.