What does current generative theory have to say about the explicit-implicit debate?

Taking a generative perspective, we divide aspects of language into three broad categories: those that cannot be learned (are inherent in Universal Grammar), those that are derived from Universal Grammar, and those that must be learned from the input. Using this framework of language to clarify the “what” of learning, we take the acquisition of null (and overt) subjects in languages like Spanish as an example of how to apply the framework. We demonstrate what properties of a null-subject grammar cannot be learned explicitly, which properties can, but also argue that it is an open empirical question as to whether these latter properties are learned using explicit processes, showing how linguistic and psychological approaches may intersect to better understand acquisition.

Learning of shared attention in sociable robotics

Sociable robots are embodied agents that are part of a heterogeneous society of robots and humans. They Should be able to recognize human beings and each other, and to engage in social, interactions. The use of a robotic architecture may strongly reduce the time and effort required to construct a sociable robot. Such architecture must have structures and mechanisms to allow social interaction. behavior control and learning from environment. Learning processes described oil Science of Behavior Analysis may lead to the development of promising methods and Structures for constructing robots able to behave socially and learn through interactions from the environment by a process of contingency learning. In this paper, we present a robotic architecture inspired from Behavior Analysis. Methods and structures of the proposed architecture, including a hybrid knowledge representation. are presented and discussed. The architecture has been evaluated in the context of a nontrivial real problem: the learning of the shared attention, employing an interactive robotic head. The learning capabilities of this architecture have been analyzed by observing the robot interacting with the human and the environment. The obtained results show that the robotic architecture is able to produce appropriate behavior and to learn from social interaction. (C) 2009 Elsevier Inc. All rights reserved.

Opinion dynamics of learning agents: does seeking consensus lead to disagreement?

We study opinion dynamics in a population of interacting adaptive agents voting on a set of issues represented by vectors. We consider agents who can classify issues into one of two categories and can arrive at their opinions using an adaptive algorithm. Adaptation comes from learning and the information for the learning process comes from interacting with other neighboring agents and trying to change the internal state in order to concur with their opinions. The change in the internal state is driven by the information contained in the issue and in the opinion of the other agent. We present results in a simple yet rich context where each agent uses a Boolean perceptron to state their opinion. If the update occurs with information asynchronously exchanged among pairs of agents, then the typical case, if the number of issues is kept small, is the evolution into a society torn by the emergence of factions with extreme opposite beliefs. This occurs even when seeking consensus with agents with opposite opinions. If the number of issues is large, the dynamics becomes trapped, the society does not evolve into factions and a distribution of moderate opinions is observed. The synchronous case is technically simpler and is studied by formulating the problem in terms of differential equations that describe the evolution of order parameters that measure the consensus between pairs of agents. We show that for a large number of issues and unidirectional information flow, global consensus is a fixed point; however, the approach to this consensus is glassy for large societies.

Cross-situational learning of object-word mapping using Neural Modeling Fields

The issue of how children learn the meaning of words is fundamental to developmental psychology. The recent attempts to develop or evolve efficient communication protocols among interacting robots or Virtual agents have brought that issue to a central place in more applied research fields, such as computational linguistics and neural networks, as well. An attractive approach to learning an object-word mapping is the so-called cross-situational learning. This learning scenario is based on the intuitive notion that a learner can determine the meaning of a word by finding something in common across all observed uses of that word. Here we show how the deterministic Neural Modeling Fields (NMF) categorization mechanism can be used by the learner as an efficient algorithm to infer the correct object-word mapping. To achieve that we first reduce the original on-line learning problem to a batch learning problem where the inputs to the NMF mechanism are all possible object-word associations that Could be inferred from the cross-situational learning scenario. Since many of those associations are incorrect, they are considered as clutter or noise and discarded automatically by a clutter detector model included in our NMF implementation. With these two key ingredients - batch learning and clutter detection - the NMF mechanism was capable to infer perfectly the correct object-word mapping. (C) 2009 Elsevier Ltd. All rights reserved.

Study of the phenanthroline-Mn-imidazole bonding in Mn(I) triscarbonyl complex: A X-ray and DFT computational analysis

355 nm light irradiation of fac-[Mn(CO)(3)(phen)(imH)](+) (fac-1) produces the mer-1 isomer and a long lived radical which can be efficiently trapped by electron acceptor molecules. EPR experiments shows that when excited, the manganese(I) complex can be readily oxidized by one-electron process to produce Mn(II) and phen(.-). In the present study, DFT calculations have been used to investigated the photochemical isomerization of the parent Mn(I) complex and to characterize the electronic structures of the long lived radical. The theoretical calculations have been performed on both the fac-1 and mer-1 species as well as on their one electron oxidized species fac-1+ and mer-1+ for the lowest spin configurations (S = 1/2) and fac-6 and mer-6 (S = 5/2) for the highest one to characterize these complexes. In particular, we used a charge decomposition analysis (CDA) and a natural bonding orbital (NBO) to have a better understanding of the chemical bonding in terms of the nature of electronic interactions. The observed variations in geometry and bond energies with an increasing oxidation state in the central metal ion are interpreted in terms of changes in the nature of metal-ligand bonding interactions. The X-ray structure of fac-1 is also described. (C) 2011 Elsevier B.V. All rights reserved.

An Information Theory framework for two-stage binary image operator design

The design of translation invariant and locally defined binary image operators over large windows is made difficult by decreased statistical precision and increased training time. We present a complete framework for the application of stacked design, a recently proposed technique to create two-stage operators that circumvents that difficulty. We propose a novel algorithm, based on Information Theory, to find groups of pixels that should be used together to predict the Output Value. We employ this algorithm to automate the process of creating a set of first-level operators that are later combined in a global operator. We also propose a principled way to guide this combination, by using feature selection and model comparison. Experimental results Show that the proposed framework leads to better results than single stage design. (C) 2009 Elsevier B.V. All rights reserved.

FT-Raman, FTIR and density functional theory studies of a hydrogen-bonded formamide: pyridine complex

Raman and IR experiments have been carried out on formamide (FA) and pyridine (Py) mixtures at different compositions. The appearance of a new Raman band at 996 cm(-1) (nu(1) region of Py), whose intensity depends on the FA concentration, is assigned to an FA: Py adduct and this result is in excellent agreement with those of other authors who employed noisy light-based coherent Raman scattering spectroscopy (I((2)) CARS). Another band at 1587 cm(-1) (nu(8) region of Py) has been observed for the first time by using Raman and IR spectroscopies. Its intensity shows the same dependence on the FA concentration and this fact allows us to also attribute it to an FA: Py adduct. The good relationship between the Raman and IR data demonstrates the potential of the vibrational spectroscopy for this kind of study. Owing to higher absolute Raman scattering cross section, the nu(1) region of Py has been chosen for the quantitative analysis and a stoichiometry of 1 : 1 FA: Py is reported. The experimental data are very well supported by the density functional theory (OFT) calculation, which was employed for the first time to the present system. Furthermore, the actual investigation shows an excellent agreement with those reported from computational calculations for similar systems. A comparison with our previous studies confirms that: the solvent dielectric constant determines the stoichiometry of a given Lewis acid-base adduct in the infinite dilution limit. Copyright (C) 2009 John Wiley & Sons, Ltd.

Oxindole-Schiff base copper(II) complexes interactions with human serum albumin: Spectroscopic, oxidative damage, and computational studies

CD and EPR were used to characterize interactions of oxindole-Schiff base copper(II) complexes with human serum albumin (HSA). These imine ligands form very stable complexes with copper, and can efficiently compete for this metal ion towards the specific N-terminal binding site of the protein, consisting of the amino acid sequence Asp-Ala-His. Relative stability constants for the corresponding complexes were estimated from CD data, using the protein as competitive ligand, with values of log K(CuL) in the range 15.7-18.1, very close to that of [Cu(HSA)] itself, with log K(CuHSA) 16.2. Some of the complexes are also able to interfere in the a-helix structure of the protein, while others seem not to affect it. EPR spectra corroborate those results, indicating at least two different metal species in solution, depending on the imine ligand. Oxidative damage to the protein after incubation with these copper(II) complexes, particularly in the presence of hydrogen peroxide, was monitored by carbonyl groups formation, and was observed to be more severe when conformational features of the protein were modified. Complementary EPR spin-trapping data indicated significant formation of hydroxyl and carbon centered radicals, consistent with an oxidative mechanism. Theoretical calculations at density functional theory (DFT) level were employed to evaluate Cu(II)-L binding energies, L -> Cu(II) donation, and Cu(II) -> L back-donation, by considering the Schiff bases and the N-terminal site of HSA as ligands. These results complement previous studies on cytotoxicity, nuclease and pro-apoptotic properties of this kind of copper(II) complexes, providing additional information about their possibilities of transport and disposition in blood plasma. (C) 2009 Elsevier Inc. All rights reserved.

"She was a Bitch" : A Socio-Educational Perspective on Motivation for Learning English.

AbstractThis degree project focuses motivation for learning English among a group of Swedish uppersecondary school students. By employing a socio-educational perspective, some vital factorsbehind a strong motivation for learning English in school are investigated through individualinterviews. Components in the past, heralding either a high level of motivation for English or a low such, are primarily focused. Moreover, essential socio-educational factors behind managing to achieve grades in English despite a low level of motivation and various impediments, such as severe socio-psychological adversities, are looked into. While motivation for English is emphasized as a critical factor, in accordance with socio-educational motivation theory, the study also stresses the importance of a positive first encounter with the English language, a satisfying English teacher-student relationship, and a sense of success in the English classroom. But above all, the study stresses a need for early tests among young students for reading disabilities, which according to this study often go undetected and thus severely impede any kind of second language learning and motivation.

E-learning opens the door to the global community. Novice users experiences of e-learning in a Somali University

E-learning has become one of the primary ways of delivering education around the globe. In Somalia, which is a country torn within and from the global community by a prolonged civil war, University of Hargeisa has in collaboration with Dalarna University in Sweden adopted, for the first time, e-learning. This study explores barriers and facilitators to e-learning usage, experienced by students in Somalia’s higher education, using the University of Hargeisa as case study. Interviews were conducted with students to explore how University of Hargeisa’s novice users perceived elearning, and what factors positively and negatively affected their e-learning experiences. The Unified Theory of Acceptance and Use of Technology (UTAUT) model was used as a framework for interpreting the results. The findings show that, in general, the students have a very positive attitude towards e-learning, and they perceived that e-learning enhanced their educational experience. The communication aspect was found to be especially important for Somali students, as it facilitated a feeling of belonging to the global community of students and scholars and alleviated the war-torn country’s isolation. However, some socio-cultural aspects of students’ communities negatively affected their e-learning experience. This study ends with recommendations based on the empirical findings to promote the use and enhance the experience of e-learning in post conflict Somali educational institutions

School leaders as agents of change : a case study on how two head teachers are trying to implement the learning study method in their school

This paper seeks to describe and discuss the impact of inspections of schools in Sweden. It outlines the political context, based on New Public Management (NPM) theory, according to what role the Schools Inspectorate is supposed to play in order to govern and control. Attention is also devoted, referring an on-going case study, to how inspections influence head teachers and their leadership in their everyday work.   Reports from the Schools inspectorate are public. This forces both politicians and head teachers to take measures. In this case, the head teachers perceived that the inspection reports confirmed what they already knew, but it also gave them an alibi and a tool to push their teachers to take part in everyday school development work. During the first year after the inspection the head teachers mainly strived to adjust formal deficiencies in local steering documents. However, some of the deviations reported from the Schools inspectorate are regarding pedagogical problems that are complicated and difficult to handle. As interventions in many cases will show up much later the results are, for example as increased goal fulfilment, in this case, still an open question. Nevertheless, it seems obvious that the Schools Inspectorate must be seen as a result of the governing philosophy that denotes New Public Management NPM).

Machine translation and the disruption of foreign language learning activities

This study examines the question of how language teachers in a highly technology-friendly university environment view machine translation and the implications that this has for the personal learning environments of students. It brings an activity-theory perspective to the question, examining the ways that the introduction of new tools can disrupt the relationship between different elements in an activity system. This perspective opens up for an investigation of the ways that new tools have the potential to fundamentally alter traditional learning activities. In questionnaires and group discussions, respondents showed general agreement that although use of machine translation by students could be considered cheating, students are bound to use it anyway, and suggested that teachers focus on the kinds of skills students would need when using machine translation and design assignments and exams to practice and assess these skills. The results of the empirical study are used to reflect upon questions of what the roles of teachers and students are in a context where many of the skills that a person needs to be able to interact in a foreign language increasingly can be outsourced to laptops and smartphones.

Prediction Of Hydrological Models’ Uncertainty By A Committee Of Machine Learning-Models

This study presents an approach to combine uncertainties of the hydrological model outputs predicted from a number of machine learning models. The machine learning based uncertainty prediction approach is very useful for estimation of hydrological models' uncertainty in particular hydro-metrological situation in real-time application [1]. In this approach the hydrological model realizations from Monte Carlo simulations are used to build different machine learning uncertainty models to predict uncertainty (quantiles of pdf) of the a deterministic output from hydrological model . Uncertainty models are trained using antecedent precipitation and streamflows as inputs. The trained models are then employed to predict the model output uncertainty which is specific for the new input data. We used three machine learning models namely artificial neural networks, model tree, locally weighted regression to predict output uncertainties. These three models produce similar verification results, which can be improved by merging their outputs dynamically. We propose an approach to form a committee of the three models to combine their outputs. The approach is applied to estimate uncertainty of streamflows simulation from a conceptual hydrological model in the Brue catchment in UK and the Bagmati catchment in Nepal. The verification results show that merged output is better than an individual model output. [1] D. L. Shrestha, N. Kayastha, and D. P. Solomatine, and R. Price. Encapsulation of parameteric uncertainty statistics by various predictive machine learning models: MLUE method, Journal of Hydroinformatic, in press, 2013.