Abstract

Abstract
The growing trend of business collaboration exerts an extra pressure on global business communities. This collaboration can be evolved in the form of hierarchical and no-hierarchical. In this research, we have considered non-hierarchical collaboration, where manufacturing firms' especially small and medium enterprises (SMEs) enjoy equal power and freedom within their networks. In order to develop such business collaboration, SMEs need to adopt different procedural steps such as build, qualify, form, operate and dissolve. In such circumstances, in this article we have proposed an implementation framework or methodology to demonstrate the logical approaches of the formation and operation of a collaborative business network. The formation and operation of this collaboration is illustrated through a complex engineer-to-order (ETO) case product. The common goals and understanding of the successful non-hierarchical business collaborations and future research directions are concluded within the scope of this paper. ©2010 IEEE.

Abstract
In this work the concept of long period based optical fibre sensors with the broadband light illumination generated just after the sensing structure is presented. This new approach allows the interrogation in transmission of the sensing head while integrated in a reflective configuration, which means the LPG sensor is seen in transmission by the optical source but in reflection by the measurement system. Also, it is shown that with this illumination layout the optical power balance is more favorable when compared with the standard configurations, allowing better sensor performances particularly when the sensing head is located far away from the photodetection and processing unit. This is demonstrated for the case of the LPG structure applied to measure strain and using ratiometric interrogation based on the readout of the optical power reflected by two fibre Bragg gratings spectrally located in each side of the LPG resonance.

Abstract
This paper describes part of the research developed by the Power Systems Unit of INESC Porto in the scope of the MoreMicrogrids EU financed project (under the Contract No: PL019864). In this project, and apart from other issues, it was investigated how microgrid agents could participate in a more effective way in electricity markets. In this paper we present models to enable the participation of microgrid agents in the provision of ancillary services, namely reactive power/voltage control, active loss balancing and demand interruption. This participation is accomplished after running the day-ahead market and it corresponds to the activation of a specific market to allocate these services. The implementation of this kind of models can contribute to create a new stream of money to microgrid agents so that they can integrate themselves in a more natural way in power systems, eventually eliminating subsidized tariffs that represent in several countries an increasing amount of the final end user tariffs. Finally, the paper includes a Case Study to illustrate the use of the developed approaches. © 2010 IEEE.

Abstract
In a competitive framework, producers and consumers require short-term electricity prices prediction to derive their bidding strategies to the electricity market. Accurate forecasting tools are required for producers to maximize their profits and for consumers to maximize their utilities. In this paper, a wavelet-neuro-fuzzy approach is proposed for short-term electricity prices prediction. Results from a real-world case study based on the electricity market of mainland Spain are presented. Finally, conclusions are duly drawn.

Abstract
Support vector machines (SVMs) were initially proposed to solve problems with two classes. Despite the myriad of schemes for multiclassification with SVMs proposed since then, little work has been done for the case where the classes are ordered. Usually one constructs a nominal classifier and a posteriori defines the order. The definition of an ordinal classifier leads to a better generalisation. Moreover, most of the techniques presented so far in the literature can generate ambiguous regions. All-at-Once methods have been proposed to solve this issue. In this work we devise a new SVM methodology based on the unimodal paradigm with the All-at-Once scheme for the ordinal classification. © 2010 IEEE.