Abstract
Currently, the teaching-learning process in domains, such as computer programming, is characterized by an extensive curricula and a high enrolment of students. This poses a great workload for faculty and teaching assistants responsible for the creation, delivery, and assessment of student exercises. The main goal of this chapter is to foster practice-based learning in complex domains. This objective is attained with an e-learning framework-called Ensemble-as a conceptual tool to organize and facilitate technical interoperability among services. The Ensemble framework is used on a specific domain: computer programming. Content issues are tacked with a standard format to describe programming exercises as learning objects. Communication is achieved with the extension of existing specifications for the interoperation with several systems typically found in an e-learning environment. In order to evaluate the acceptability of the proposed solution, an Ensemble instance was validated on a classroom experiment with encouraging results. © 2015, IGI Global.

Abstract
This paper explores the key factors that foster technology transfer within the triad university-industry-government in an international context, i.e., the Enterprise Europe Network (EEN). Based on 71 technological Partnership Agreements (PAs), estimation results indicate that PAs associated to partners that provide their collaborators with the appropriate training in technology transfer-related issues, present substantial past experience in international or technological projects, and participate in extensive networks, are those that achieve better performances in terms of international technology transfer. High levels of formal schooling per se are not a key determinant of international technology transfer; the critical factor is highly educated human resources who receive complementary training in technology transfer issues. © Universidad Alberto Hurtado, Facultad de Economía y Negocios.

Abstract

Abstract
Search and rescue (SAR) teams often face several complex and dangerous tasks, which could be aided by unmanned robotic vehicles (UV). UV agents can potentially be used to decrease the risk in the loss of lives both of the rescuers and victims and aid in the search and transportation of survivors and in the removal of debris in a catastrophe scenario. Depending on the nature of a catastrophe and its geographical location, there are potentially three types of UVs that can be deployed: aerial, surface and ground. Due to the control and manipulation particularities each type of UV contemplates, their operators need prior training and certification. To train and certify the operators a tool (serious game) is under development. In this paper we will make an overview about our approach in its development. This game uses a typical client-server architecture where all client agents (virtual UVs and operator client interfaces) share the same immersive virtual environment which is generated through the merging of GIS data and a semantic model extracted from 3D laser data. There will be several types of scenarios suitable to several types of catastrophe situations. Each of these scenarios has its own mission plan for the trainees to follow. The game will also provide an interface for mission planning so that each mission plan will be carefully designed to accurately correspond to a matrix of skills. This matrix lists a set of common skills in various different UV operational case studies which will allow the certification of operators.

Abstract
An interferometric tip sensor based on the post-process of a special design double-cladding optical fiber is proposed. Due to the sensing head design, it is sensitive to environmental variations. In order to analyze this effect, the sensing head is subjected to temperature variations both in liquid and gas (at 1 atm). Comparing the two signals, it is possible to discriminate the contribution of the liquid refractive index variation with temperature. Not only the amplitude of the signal varies with the surrounding medium, but also the phase of the interferometric pattern alters. This is due to the presence of a thin diaphragm at the end face of the fiber structure turning the sensing head in a three wave interferometric device. An indirect measurement of the water refractive index is performed, by subjecting the sensing head to temperature variations in air and water. Even though the sensitivities obtained are lower than the ones reported in the literature, it should be highlighted that there is no core exposition of the fiber to the external medium. The sensor is easy to fabricate, robust, and reproducible.

Abstract
This paper describes a new type of ensembles that aims at improving the predictive performance of these approaches in time series forecasting. Ensembles are recognised as one of the most successful approaches to prediction tasks. Previous theoretical studies of ensembles have shown that one of the key reasons for this performance is diversity among ensemble members. Several methods exist to generate diversity. The key idea of the work we are presenting here is to propose a new form of diversity generation that explores some specific properties of time series prediction tasks. Our hypothesis is that the resulting ensemble members will be better at addressing different dynamic regimes of time series data. Our large set of experiments confirms that the methods we have explored for generating diversity are able to improve the performance of the equivalent ensembles with standard diversity generation procedures. © 2014 M. Oliveira & L. Torgo.