A priority in achieving sustainability and well-being for all This Policy Brief argues that the foremost priority for educational development should now be on enhancing quality, transcending past objectives focused primarily on access and attainment (i.e., Education For All (EFA) and the Millennium Development Goals). Enhancing Quality Education should become a cornerstone of both the Sustainable Development Goals (SDGs) and the post-2014 Global Action Programme on ESD for quality education is essential for further progress across all dimensions of sustainable development. Enhancing Quality Education can be achieved through integration of a holistic perspective on education for sustainable development (ESD) and use of measurable learning targets/outcomes. This Policy Brief presents an ESD Learning Performance Framework (LPF), addressing both learning processes and educational contents, that provides a roadmap for how stron-ger ESD can promote greater educational quality overall. The effectiveness of Quality Education for Sustainable Development could be significantly enhanced through applying the LPF to: Support curriculum developers in designing holistic and relevant school curricula that

A non-linear classification technique based on Fisher's discriminant is proposed. The main ingredient is the kernel trick which allows the efficient computation of Fisher discriminant in feature space. The linear classification in feature space corresponds to a (powerful) non-linear decision

An analogy with the way ant colonies function has suggested the definition of a new computational paradigm, which we call Ant System. We propose it as a viable new approach to stochastic combinatorial optimization. The main characteristics of this model are positive feedback, distributed

the use of infrared light which is harmful for the human eye. Motor vehicle accidents cause injury and death, and this system will help to decrease the amount of crashes due to fatigued drivers. The proposed algorithm will work in three main stages. In first stage the face of the driver is detected

of image patches. We propose and compare two alternative implementations using different classifiers: Naïve Bayes and SVM. The main advantages of the method are that it is simple, computationally efficient and intrinsically invariant. We present results for simultaneously classifying seven semantic visual

This paper proposes COPE, a new architecture for wireless mesh networks. In addition to forwarding packets, routers mix (i.e., code) packets from different sources to increase the information content of each transmission. We show that intelligently mixing packets increases network throughput. Our

This paper describes a self-organizing, multihop, mobile radio network, which relies on a code division access scheme for multimedia support. In the proposed network architecture, nodes are organized into nonoverlapping clusters. The clusters are independently controlled and are dynamically

The search for efficient image denoising methods is still a valid challenge at the crossing of functional analysis and statistics. In spite of the sophistication of the recently proposed methods, most algorithms have not yet attained a desirable level of applicability. All show an outstanding

Learning general functional dependencies between arbitrary input and output spaces is one of the key challenges in computational intelligence. While recent progress in machine learning has mainly focused on designing flexible and powerful input representations, this paper addresses

explanatory variables in a model provides a guide to the amount of selection on the unobservables. We also propose an informal way to assess selectivity bias based on measuring the ratio of selection on unobservables to selection on observables that would be required if one is to attribute the entire effect