Abstract
This manuscript presents the performance evaluation of our algorithm that precisely finds human eyes in still gray-scale images and describes the state of the founded eye. This algorithm has been evaluated considering two descriptors - Pyramid transform domain (PLBP) and Multi-Block Histogram LBP (BHLBP), which are extended versions of the Local Binary Pattern descriptor (LBP). For the classification stage, two types of supervised learning techniques have also been evaluated, Support Vector Machine (SVM) and Multilayer Perceptron (MLP). The proposed method is assessed on the Face Recognition Grand Challenge (BioID) and (CAS-PEAL-R1) databases, and experimental results demonstrate improved performance than some state-of-the-art eye detection approaches.

Abstract
In this paper we discuss collaborative learning strategies based on the use of digital stories in corporate training and lifelong learning. The text starts with a concise review on theoretical and technical foundations about the use of digital technologies in collaborative strategies in lifelong learning. We will also discuss if the corporate training may be improved by the use of individual audio-visual experience in learning process. Careful planning, scripting and production of audio-visual digital stories can help in the construction of collaborative learning spaces in which adults are in the context of vocational training throughout life. Our analysis concludes emphasizing on the need to experience the routing performance of digital stories in the context of corporate training, following the reference levels mentioned here, so we can have in a future more theoretical and empirical elements for the validation and conceptualization in the use of digital stories in the context of corporate training. Ultimately we believe that lifelong learning can be improved with the use of strategies that promote the production of personal audio-visual for those involved in teaching and learning process in organizational context.

Abstract
The UK's 2008 Climate Change Act sets a legally binding target for reducing territorial greenhouse gas emissions by 80% by 2050, relative to 1990 levels. Four pathways to achieve this target have been developed by the Department of Energy and Climate Change, with all pathways requiring increased us of bioenergy. A significant amount of this could be indigenously sourced from crops, but will increased domestic production of energy crops conflict with other agricultural priorities?To address this question, a coupled analysis of the UK energy system and land use has been developed. The two systems are connected by the production of bioenergy, and are projected forwards in time under the energy pathways, accounting for various constraints on land use for agriculture and ecosystem services. The results show different combinations of crop yield and compositions for the pathways lead to the appropriation of between 7% and 61% of UK's agricultural land for bioenergy production. This could result in competition for land for food production and other land uses, as well as indirect land use change in other countries due to an increase in bioenergy imports. Consequently, the potential role of bioenergy in achieving UK emissions reduction targets may face significant deployment challenges.

Abstract

Abstract
This paper presents the design and implementation of a GaN-HEMT, class-J power amplifier suitable for cognitive radio transceivers, i.e., which presents high-efficiency and wideband characteristics, being these maintained for large load variations. Simulation results are presented which show large-signal measurement results of 30 dB gain with 60%-76% power-added efficiency (PAE) over a band of 1.3-2.3 GHz. Adaptivity to load changes is being developed to ensure PAE above 70% for large load variations.

Abstract
The term Dynamic Manufacturing Network (DMN) refers to a new collaborative business model that relies on real-time information sharing, synchronized planning and common business processes. DMNs are operational networks formed among autonomous and globally dispersed partners, and can be seen as the manufacturing industry application of the Virtual Enterprise (VE) concept. Despite their numerous practical benefits such as optimized processes and access to new and global markets, they are particularly vulnerable to disruptions. Any disruption in manufacturing or transportation of products may obviously result in failed orders, thus impacting the whole DMN reliability. Instead of developing stochastic models to deal with uncertainty, as it is usually done, we have rather integrated the concept of flexibility into the tactical and operational planning of such networks. We therefore propose in this work, a multi-objective optimization model that simultaneously maximizes reactive flexibility measures while minimizing total operating costs.