Abstract
The participation of an EV aggregator in the electricity market for purchasing electrical energy requires an algorithm for managing the EV charging during the operational day. In this paper the coordination of EV for minimizing the deviation between bid and consumed electrical energy is studied and compared with an uncoordinated strategy. Two algorithms are proposed: a heuristic algorithm that dispatches the EV for each time interval separately, and another one, formulated as an optimization problem for dispatching the EV considering all the time intervals. Furthermore, the aggregator architecture is compared with an autonomous architecture where each EV operates and participates in the market individually. The results, for a realistic case-study, show that the aggregator with an optimized coordination strategy achieves the lowest deviation cost and magnitude.

Abstract
Very few developments have been done to provide electric power supply of instrumented hip prosthesis. Actually, vibration-powered generators are the most appropriate mechanisms for this kind of application's environment. This paper describes the first attempt to develop the concept of energy harvesting from multiple energy sources applied in the same hip implant. Exploiting the potential of the three angular movements over the femoral component, namely in the abduction-adduction, flexion-extension and inward-outward rotation axes, three in board vibration-based mechanisms were developed in order to ensure electric power supply from multiple energy sources. A total of 53.7 mu J/s was harvested by a translation movement-based electromagnetic energy generator when a sinusoidal function with an amplitude of 40 mm and a frequency of 4 Hz was applied. A rotation movement-based electromagnetic energy generator has harvested 0.77 mu J/s when a sinusoidal function with an amplitude of 60 degrees and a frequency of 2.5 Hz was used. The piezoelectric energy harvester has achieved 0.6 mu J/s with the application of a sinusoidal function with an amplitude of 200 N and a frequency of 4 Hz. Besides, its ability of being fully autonomous, operating without expiry and maintenance, while offering safety during its entire lifetime are relevant features. This paper should provide the basis for the development of smart hip prosthesis with the ability to fix the aseptic implant loosening problem.

Abstract
Many data stream clustering algorithms operate in two well-defined steps: (i) online statistical data collection stage; and (ii) offline macro-clustering stage. The well-known k-means algorithm is often employed for performing the offline macro-clustering step. The conventional k-means algorithm assumes that the number of clusters (k) is defined a priori by the user. Given the difficulty of defining the value of k a priori in real-world problems, we describe a new approach that allows estimating k dynamically from streams with variable number of clusters, which is a common scenario in data with a non-stationary distribution. In addition, we combine our dynamic approach with two different strategies for initializing the centroids during the offline clustering. Analysis of results suggest that, using the dynamic approach, the method k-means++ for centroids initialization present better results. © 2012 Authors.

Abstract
Theoretical and experimental results of three different high-birefringent fiber loop mirrors with output ports are analyzed. For theoretical model, the Jones matrix analysis is used. The theoretical studies present similar results for all experimental configurations. The last configuration is tested as an interrogation system where the spectral response arises from the combination of the reference signal modulated by the sensor signal. The configuration is characterized in strain with the phase changes recovered from two quadrature phase signals, providing a sensitivity of 16 mrad/mu epsilon with a resolution of 1.9 mu epsilon.

Abstract
Purpose: The purpose of this paper is to provide practical justification for performance measurement and management within a collaborative business network. The basic performance measurement indicators are elaborated within the scope of this research. Design/methodology/approach: Performance measurement techniques are highlighted through the application of an ICT-based solution approach, with special focus on business collaboration among small and medium sized enterprises (SMEs). Findings: From the basic need to measure the performance of individual partners within a business network, this research proposes a generic framework and process flow with the objective of evaluating the individual partners in terms of various performance indicators such as key success factors (KSF), key performance factors (KPF) and key performance indicators (KPI). The outcomes from this framework or process flow will help partners in the network to build valuable trust, cooperation and coordination. Originality/value: The focus of this paper is to demonstrate the methodological approach of measuring the performance through identifying and prioritizing the performance indicators (KSF, KPF, KPI) among collaborative partners and to highlight their importance for successful business operations. © Emerald Group Publishing Limited.

Abstract
Pervasive environments offer an increasing number of services to a large number of people moving within these environments, including timely information about where to go and when, and contextual information about the surrounding environment. This information may be conveyed to people through public displays or direct to a person's mobile phone. People using these services interact with the system but they are also meeting other people and performing other activities as relevant opportunities arise. The design of such systems and the analysis of collective dynamic behaviour of people within them is a challenging problem.We present results on a novel usage of a scalable analysis technique in this context.We show the validity of an approach based on stochastic process-algebraic models by focussing on a representative example, i.e. emergency egress.The chosen case study has the advantage that detailed data is available from studies employing alternative analysis methods, making cross-methodology comparison possible. We also illustrate how realistic, context-dependent human behaviour, often observed in emergency egress, can naturally be embedded in the models, and how the effect of such behaviour on evacuation can be analysed in an efficient and scalable way. The proposed approach encompasses both the agent modelling viewpoint, as system behaviour emerges from specific (discrete) agent interaction, and the population viewpoint,when classes of homogeneous individuals are considered for a (continuous) approximation of overall system behaviour. © 2011 BCS.