View-dependent information theory quality measures for pixel sampling and scene discretization in flatland

In this paper, we present view-dependent information theory quality measures for pixel sampling and scene discretization in flatland. The measures are based on a definition for the mutual information of a line, and have a purely geometrical basis. Several algorithms exploiting them are presented and compare well with an existing one based on depth differences

Exploring chromium (VI) dioxodihalides chemistry: is density functional theory the most suitable tool?

A comparative systematic study of the CrO2F2 compound has been performed using different conventional ab initio methodologies and density functional procedures. Two points have been analyzed: first, the accuracy of results yielded by each method under study, and second, the computational cost required to reach such results. Weighing up both aspects, density functional theory has been found to be more appropriate than the Hartree-Fock (HF) and the analyzed post-HF methods. Hence, the structural characterization and spectroscopic elucidation of the full CrO2X2 series (X=F,Cl,Br,I) has been done at this level of theory. Emphasis has been given to the unknown CrO2I2 species, and specially to the UV/visible spectra of all four compounds. Furthermore, a topological analysis in terms of charge density distributions has revealed why the valence shell electron pair repulsion model fails in predicting the molecular shape of such CrO2X2 complexes

Socio-Cultural Transformation and the Promotion of Learning

The main premise of Vygotsky’s cultural-historical theory is that to promote learning, and thus development, educators must intervene in, and change, the students’ socio-cultural context. Vygotsky’s theory, however, has been misinterpreted and the opposite approach has been accepted: the teaching is adapted, according to the context. The result is widespread failure in schools. This article reclaims the true transformative meaning of Vygotskian theory and shows how successful schools in several countries implement various actions to transform their social and cultural environment. Data is presented from six case studies of successful schools conducted in five European countries. The analysis shows that these actions improve instrumental learning and, consequently, cognitive development. All these efforts focus on teaching methods that aim to increase the amount that students learn

Gradient-based reinforcement learning techniques for underwater robotics behavior learning

Darrerament, l'interès pel desenvolupament d'aplicacions amb robots submarins autònoms (AUV) ha crescut de forma considerable. Els AUVs són atractius gràcies al seu tamany i el fet que no necessiten un operador humà per pilotar-los. Tot i això, és impossible comparar, en termes d'eficiència i flexibilitat, l'habilitat d'un pilot humà amb les escasses capacitats operatives que ofereixen els AUVs actuals. L'utilització de AUVs per cobrir grans àrees implica resoldre problemes complexos, especialment si es desitja que el nostre robot reaccioni en temps real a canvis sobtats en les condicions de treball. Per aquestes raons, el desenvolupament de sistemes de control autònom amb l'objectiu de millorar aquestes capacitats ha esdevingut una prioritat. Aquesta tesi tracta sobre el problema de la presa de decisions utilizant AUVs. El treball presentat es centra en l'estudi, disseny i aplicació de comportaments per a AUVs utilitzant tècniques d'aprenentatge per reforç (RL). La contribució principal d'aquesta tesi consisteix en l'aplicació de diverses tècniques de RL per tal de millorar l'autonomia dels robots submarins, amb l'objectiu final de demostrar la viabilitat d'aquests algoritmes per aprendre tasques submarines autònomes en temps real. En RL, el robot intenta maximitzar un reforç escalar obtingut com a conseqüència de la seva interacció amb l'entorn. L'objectiu és trobar una política òptima que relaciona tots els estats possibles amb les accions a executar per a cada estat que maximitzen la suma de reforços totals. Així, aquesta tesi investiga principalment dues tipologies d'algoritmes basats en RL: mètodes basats en funcions de valor (VF) i mètodes basats en el gradient (PG). Els resultats experimentals finals mostren el robot submarí Ictineu en una tasca autònoma real de seguiment de cables submarins. Per portar-la a terme, s'ha dissenyat un algoritme anomenat mètode d'Actor i Crític (AC), fruit de la fusió de mètodes VF amb tècniques de PG.

Electronic structure of point defects in controlled self-doping of the TiO2 (110) surface: Combined photoemission spectroscopy and density functional theory study

Point defects in metal oxides such as TiO2 are key to their applications in numerous technologies. The investigation of thermally induced nonstoichiometry in TiO2 is complicated by the difficulties in preparing and determining a desired degree of nonstoichiometry. We study controlled self-doping of TiO2 by adsorption of 1/8 and 1/16 monolayer Ti at the (110) surface using a combination of experimental and computational approaches to unravel the details of the adsorption process and the oxidation state of Ti. Upon adsorption of Ti, x-ray and ultraviolet photoemission spectroscopy (XPS and UPS) show formation of reduced Ti. Comparison of pure density functional theory (DFT) with experiment shows that pure DFT provides an inconsistent description of the electronic structure. To surmount this difficulty, we apply DFT corrected for on-site Coulomb interaction (DFT+U) to describe reduced Ti ions. The optimal value of U is 3 eV, determined from comparison of the computed Ti 3d electronic density of states with the UPS data. DFT+U and UPS show the appearance of a Ti 3d adsorbate-induced state at 1.3 eV above the valence band and 1.0 eV below the conduction band. The computations show that the adsorbed Ti atom is oxidized to Ti2+ and a fivefold coordinated surface Ti atom is reduced to Ti3+, while the remaining electron is distributed among other surface Ti atoms. The UPS data are best fitted with reduced Ti2+ and Ti3+ ions. These results demonstrate that the complexity of doped metal oxides is best understood with a combination of experiment and appropriate computations.

Innovative use of vodcast (Video-Podcast) to enrich learning experience in structures laboratory

Students may have difficulty in understanding some of the complex concepts which they have been taught in the general areas of science and engineering. Whilst practical work such as a laboratory based examination of the performance of structures has an important role in knowledge construction this does have some limitations. Blended learning supports different learning styles, hence further benefits knowledge building. This research involves an empirical study of how vodcasts (video-podcasts) can be used to enrich learning experience in the structural properties of materials laboratory of an undergraduate course. Students were given the opportunity of downloading and viewing the vodcasts on the theory before and after the experimental work. It is the choice of the students when (before or after, before and after) and how many times they would like to view the vodcasts. In blended learning, the combination of face-to-face teaching, vodcasts, printed materials, practical experiments, writing reports and instructors’ feedbacks benefits different learning styles of the learners. For the preparation of the practical, the students were informed about the availability of the vodcasts prior to the practical session. After the practical work, students submitted an individual laboratory report for the assessment of the structures laboratory. The data collection consisted of a questionnaire completed by the students, follow-up semi-structured interviews and the practical reports submitted by them for assessment. The results from the questionnaire were analysed quantitatively, whilst the data from the assessment reports were analysed qualitatively. The analysis shows that most of the students who have not fully grasped the theory after the practical, managed to gain the required knowledge by viewing the vodcasts. According to their feedbacks, the students felt that they have control over how to use the material and to view it as many times as they wish. Some students who have understood the theory may choose to view it once or not at all. Their understanding was demonstrated by their explanations in their reports, and was illustrated by the approach they took to explicate the results of their experimental work. The research findings are valuable to instructors who design, develop and deliver different types of blended learning, and are beneficial to learners who try different blended approaches. Recommendations were made on the role of the innovative application of vodcasts in the knowledge construction for structures laboratory and to guide future work in this area of research.

Blended learning approach to include the innovative use of vodcasts (video-podcasts) to enrich students learning experience in structures laboratory

Students may have difficulty in understanding some of the complex concepts which they have been taught in the general areas of science and engineering. Whilst practical work such as a laboratory based examination of the performance of structures has an important role in knowledge construction this does have some limitations. Blended learning supports different learning styles, hence further benefits knowledge building. This research involves the empirical studies of how an innovative use of vodcasts (video-podcasts) can enrich learning experience in the structural properties of materials laboratory of an undergraduate course. Students were given the opportunity of downloading and viewing the vodcasts on the theory before and after the experimental work. It is the choice of the students when (before or after, before and after) and how many times they would like to view the vodcasts. In blended learning, the combination of face-to-face teaching, vodcasts, printed materials, practical experiments, writing reports and instructors’ feedbacks benefits different learning styles of the learners. For the preparation of the practical laboratory work, the students were informed about the availability of the vodcasts prior to the practical session. After the practical work, students submit an individual laboratory report for the assessment of the structures laboratory. The data collection consists of a questionnaire completed by the students, and the practical reports submitted by them for assessment. The results from the questionnaire were analysed quantitatively, whilst the data from the assessment reports were analysed qualitatively. The analysis shows that students who have not fully grasped the theory after the practical were successful in gaining the required knowledge by viewing the vodcasts. Some students who have understood the theory may choose to view it once or not at all. Their understanding was demonstrated by the quality of their explanations in their reports. This is illustrated by the approach they took to explicate the results of their experimental work, for example, they can explain how to calculate the Young’s Modulus properly and provided the correct value for it. The research findings are valuable to instructors who design, develop and deliver different types of blended learning, and beneficial to learners who try different blended approaches. Recommendations were made on the role of the innovative application of vodcasts in the knowledge construction for structures laboratory and to guide future work in this area of research.

A perspective on chaos theory: Potential applications to intelligent buildings

Mathematical models have been vitally important in the development of technologies in building engineering. A literature review identifies that linear models are the most widely used building simulation models. The advent of intelligent buildings has added new challenges in the application of the existing models as an intelligent building requires learning and self-adjusting capabilities based on environmental and occupants' factors. It is therefore argued that the linearity is an impropriate basis for any model of either complex building systems or occupant behaviours for control or whatever purpose. Chaos and complexity theory reflects nonlinear dynamic properties of the intelligent systems excised by occupants and environment and has been used widely in modelling various engineering, natural and social systems. It is proposed that chaos and complexity theory be applied to study intelligent buildings. This paper gives a brief description of chaos and complexity theory and presents its current positioning, recent developments in building engineering research and future potential applications to intelligent building studies, which provides a bridge between chaos and complexity theory and intelligent building research.

Designing Year 12 strategy training in listening and writing: from theory to practice

This article outlines some of the key issues involved in developing a programme of strategy training for learners of French, in listening and in writing. It highlights the theoretical perspectives and research findings on listening and writing that informed the selection of strategies to teach learners and thence the development of appropriate materials. Examples of these materials are given as well as advice regarding their use. The article concludes with suggestions for how strategy training might be incorporated into teachers' own work with learners.

An instructional design model for constructivist learning

The emergent requirements for effective e-learning calls for a paradigm shift for instructional design. Constructivist theory and semiotics offer a sound underpinning to enable such revolutionary change by employing the concepts of Learning Objects. E-learning guidelines adopted by the industry have led successfully to the development of training materials. Inadequacy and deficiency of those methods for Higher Education have been identified in this paper. Based on the best practice in industry and our empirical research, we present an instructional design model with practical templates for constructivist learning.

Dynamic automata for mobile robot learning

Researchers at the University of Reading have developed over many years some simple mobile robots that explore an environment they perceive through simple ultrasonic sensors. Information from these sensors has allowed the robots to learn the simple task of moving around while avoiding dynamic obstacles using a static set of fuzzy automata, the choice of which has been criticised, due to its arbitrary nature. This paper considers how a dynamic set of automata can overcome this criticism. In addition, a new reinforcement learning function is outlined which is both scalable to different numbers and types of sensors. The innovations compare successfully with earlier work.

Sparse model identification using orthogonal forward regression with basis pursuit and D-optimality

An efficient model identification algorithm for a large class of linear-in-the-parameters models is introduced that simultaneously optimises the model approximation ability, sparsity and robustness. The derived model parameters in each forward regression step are initially estimated via the orthogonal least squares (OLS), followed by being tuned with a new gradient-descent learning algorithm based on the basis pursuit that minimises the l(1) norm of the parameter estimate vector. The model subset selection cost function includes a D-optimality design criterion that maximises the determinant of the design matrix of the subset to ensure model robustness and to enable the model selection procedure to automatically terminate at a sparse model. The proposed approach is based on the forward OLS algorithm using the modified Gram-Schmidt procedure. Both the parameter tuning procedure, based on basis pursuit, and the model selection criterion, based on the D-optimality that is effective in ensuring model robustness, are integrated with the forward regression. As a consequence the inherent computational efficiency associated with the conventional forward OLS approach is maintained in the proposed algorithm. Examples demonstrate the effectiveness of the new approach.

Adapting to new challenges: extension theory and practice for the 21st century

Twenty first century challenges facing agriculture include climate change, threats to food security for a growing population and downward economic pressures on rural livelihoods. Addressing these challenges will require innovation in extension theory, policy and education, at a time when the dominance of the state in the provision of knowledge and information services to farmers and rural entrepreneurs continues to decline. This paper suggests that extension theory is catching up with and helping us to understand innovative extension practice, and therefore provides a platform for improving rural development policies and strategies. Innovation is now less likely to be spoken of as something to be passed on to farmers, than as a continuing process of creativity and adaptation that can be nurtured and sustained. Innovation systems and innovation platforms are concepts that recognise the multiple factors that lead to farmers’ developing, adapting and applying new ideas and the importance of linking all actors in the value chain to ensure producers can access appropriate information and advice for decision making at all stages in the production process. Concepts of social learning, group development and solidarity, social capital, collective action and empowerment all help to explain and therefore to apply more effectively group extension approaches in building confidence and sustaining innovation. A challenge facing educators is to ensure the curricula for aspiring extension professionals in our higher education institutions are regularly reviewed and keep up with current and future developments in theory, policy and practice.

Action observation and robotic agents: learning and anthropomorphism

The ‘action observation network’ (AON), which is thought to translate observed actions into motor codes required for their execution, is biologically tuned: it responds more to observation of human, than non-human, movement. This biological specificity has been taken to support the hypothesis that the AON underlies various social functions, such as theory of mind and action understanding, and that, when it is active during observation of non-human agents like humanoid robots, it is a sign of ascription of human mental states to these agents. This review will outline evidence for biological tuning in the AON, examining the features which generate it, and concluding that there is evidence for tuning to both the form and kinematic profile of observed movements, and little evidence for tuning to belief about stimulus identity. It will propose that a likely reason for biological tuning is that human actions, relative to non-biological movements, have been observed more frequently while executing corresponding actions. If the associative hypothesis of the AON is correct, and the network indeed supports social functioning, sensorimotor experience with non-human agents may help us to predict, and therefore interpret, their movements.