Generation of human computational models with machine learning

Services in smart environments pursue to increase the quality of people?s lives. The most important issues when developing this kind of environments is testing and validating such services. These tasks usually imply high costs and annoying or unfeasible real-world testing. In such cases, artificial societies may be used to simulate the smart environment (i.e. physical environment, equipment and humans). With this aim, the CHROMUBE methodology guides test engineers when modeling human beings. Such models reproduce behaviors which are highly similar to the real ones. Originally, these models are based on automata whose transitions are governed by random variables. Automaton?s structure and the probability distribution functions of each random variable are determined by a manual test and error process. In this paper, it is presented an alternative extension of this methodology which avoids the said manual process. It is based on learning human behavior patterns automatically from sensor data by using machine learning techniques. The presented approach has been tested on a real scenario, where this extension has given highly accurate human behavior models,

Fast 2D to 3D conversion using a clustering-based hierarchical search in a machine learning framework

Automatic 2D-to-3D conversion is an important application for filling the gap between the increasing number of 3D displays and the still scant 3D content. However, existing approaches have an excessive computational cost that complicates its practical application. In this paper, a fast automatic 2D-to-3D conversion technique is proposed, which uses a machine learning framework to infer the 3D structure of a query color image from a training database with color and depth images. Assuming that photometrically similar images have analogous 3D structures, a depth map is estimated by searching the most similar color images in the database, and fusing the corresponding depth maps. Large databases are desirable to achieve better results, but the computational cost also increases. A clustering-based hierarchical search using compact SURF descriptors to characterize images is proposed to drastically reduce search times. A significant computational time improvement has been obtained regarding other state-of-the-art approaches, maintaining the quality results.

A Semantic Approach to Problem-Based Learning with Conceptual Models

El aprendizaje basado en problemas se lleva aplicando con éxito durante las últimas tres décadas en un amplio rango de entornos de aprendizaje. Este enfoque educacional consiste en proponer problemas a los estudiantes de forma que puedan aprender sobre un dominio particular mediante el desarrollo de soluciones a dichos problemas. Si esto se aplica al modelado de conocimiento, y en particular al basado en Razonamiento Cualitativo, las soluciones a los problemas pasan a ser modelos que representan el compotamiento del sistema dinámico propuesto. Por lo tanto, la tarea del estudiante en este caso es acercar su modelo inicial (su primer intento de representar el sistema) a los modelos objetivo que proporcionan soluciones al problema, a la vez que adquieren conocimiento sobre el dominio durante el proceso. En esta tesis proponemos KaiSem, un método que usa tecnologías y recursos semánticos para guiar a los estudiantes durante el proceso de modelado, ayudándoles a adquirir tanto conocimiento como sea posible sin la directa supervisión de un profesor. Dado que tanto estudiantes como profesores crean sus modelos de forma independiente, estos tendrán diferentes terminologías y estructuras, dando lugar a un conjunto de modelos altamente heterogéneo. Para lidiar con tal heterogeneidad, proporcionamos una técnica de anclaje semántico para determinar, de forma automática, enlaces entre la terminología libre usada por los estudiantes y algunos vocabularios disponibles en la Web de Datos, facilitando con ello la interoperabilidad y posterior alineación de modelos. Por último, proporcionamos una técnica de feedback semántico para comparar los modelos ya alineados y generar feedback basado en las posibles discrepancias entre ellos. Este feedback es comunicado en forma de sugerencias individualizadas que el estudiante puede utilizar para acercar su modelo a los modelos objetivos en cuanto a su terminología y estructura se refiere. ABSTRACT Problem-based learning has been successfully applied over the last three decades to a diverse range of learning environments. This educational approach consists of posing problems to learners, so they can learn about a particular domain by developing solutions to them. When applied to conceptual modeling, and particularly to Qualitative Reasoning, the solutions to problems are models that represent the behavior of a dynamic system. Therefore, the learner's task is to move from their initial model, as their first attempt to represent the system, to the target models that provide solutions to that problem while acquiring domain knowledge in the process. In this thesis we propose KaiSem, a method for using semantic technologies and resources to scaffold the modeling process, helping the learners to acquire as much domain knowledge as possible without direct supervision from the teacher. Since learners and experts create their models independently, these will have different terminologies and structure, giving rise to a pool of models highly heterogeneous. To deal with such heterogeneity, we provide a semantic grounding technique to automatically determine links between the unrestricted terminology used by learners and some online vocabularies of the Web of Data, thus facilitating the interoperability and later alignment of the models. Lastly, we provide a semantic-based feedback technique to compare the aligned models and generate feedback based on the possible discrepancies. This feedback is communicated in the form of individualized suggestions, which can be used by the learner to bring their model closer in terminology and structure to the target models.

Response-reinforcement learning is dependent on N-methyl-d-aspartate receptor activation in the nucleus accumbens core

The nucleus accumbens, a site within the ventral striatum, is best known for its prominent role in mediating the reinforcing effects of drugs of abuse such as cocaine, alcohol, and nicotine. Indeed, it is generally believed that this structure subserves motivated behaviors, such as feeding, drinking, sexual behavior, and exploratory locomotion, which are elicited by natural rewards or incentive stimuli. A basic rule of positive reinforcement is that motor responses will increase in magnitude and vigor if followed by a rewarding event. It is likely, therefore, that the nucleus accumbens may serve as a substrate for reinforcement learning. However, there is surprisingly little information concerning the neural mechanisms by which appetitive responses are learned. In the present study, we report that treatment of the nucleus accumbens core with the selective competitive N-methyl-d-aspartate (NMDA) antagonist 2-amino-5-phosphonopentanoic acid (AP-5; 5 nmol/0.5 μl bilaterally) impairs response-reinforcement learning in the acquisition of a simple lever-press task to obtain food. Once the rats learned the task, AP-5 had no effect, demonstrating the requirement of NMDA receptor-dependent plasticity in the early stages of learning. Infusion of AP-5 into the accumbens shell produced a much smaller impairment of learning. Additional experiments showed that AP-5 core-treated rats had normal feeding and locomotor responses and were capable of acquiring stimulus-reward associations. We hypothesize that stimulation of NMDA receptors within the accumbens core is a key process through which motor responses become established in response to reinforcing stimuli. Further, this mechanism, may also play a critical role in the motivational and addictive properties of drugs of abuse.

Running enhances neurogenesis, learning, and long-term potentiation in mice

Running increases neurogenesis in the dentate gyrus of the hippocampus, a brain structure that is important for memory function. Consequently, spatial learning and long-term potentiation (LTP) were tested in groups of mice housed either with a running wheel (runners) or under standard conditions (controls). Mice were injected with bromodeoxyuridine to label dividing cells and trained in the Morris water maze. LTP was studied in the dentate gyrus and area CA1 in hippocampal slices from these mice. Running improved water maze performance, increased bromodeoxyuridine-positive cell numbers, and selectively enhanced dentate gyrus LTP. Our results indicate that physical activity can regulate hippocampal neurogenesis, synaptic plasticity, and learning.

Chronic stress alters synaptic terminal structure in hippocampus

Repeated psychosocial or restraint stress causes atrophy of apical dendrites in CA3 pyramidal neurons of the hippocampus, accompanied by specific cognitive deficits in spatial learning and memory. Excitatory amino acids mediate this atrophy together with adrenal steroids and the neurotransmitter serotonin. Because the mossy fibers from dentate granule neurons provide a major excitatory input to the CA3 proximal apical dendrites, we measured ultrastructural parameters associated with the mossy fiber–CA3 synapses in control and 21-day restraint-stressed rats in an effort to find additional morphological consequences of stress that could help elucidate the underlying anatomical as well as cellular and molecular mechanisms. Although mossy fiber terminals of control rats were packed with small, clear synaptic vesicles, terminals from stressed animals showed a marked rearrangement of vesicles, with more densely packed clusters localized in the vicinity of active zones. Moreover, compared with controls, restraint stress increased the area of the mossy fiber terminal occupied by mitochondrial profiles and consequently, a larger, localized energy-generating capacity. A single stress session did not produce these changes either immediately after or the next day following the restraint session. These findings provide a morphological marker of the effects of chronic stress on the hippocampus that points to possible underlying neuroanatomical as well as cellular and molecular mechanisms for the ability of repeated stress to cause structural changes within the hippocampus.

Lack of tissue glucocorticoid reactivation in 11β-hydroxysteroid dehydrogenase type 1 knockout mice ameliorates age-related learning impairments

11β-hydroxysteroid dehydrogenase type 1 (11β-HSD-1) intracellularly regenerates active corticosterone from circulating inert 11-dehydrocorticosterone (11-DHC) in specific tissues. The hippocampus is a brain structure particularly vulnerable to glucocorticoid neurotoxicity with aging. In intact hippocampal cells in culture, 11β-HSD-1 acts as a functional 11β-reductase reactivating inert 11-DHC to corticosterone, thereby potentiating kainate neurotoxicity. We examined the functional significance of 11β-HSD-1 in the central nervous system by using knockout mice. Aged wild-type mice developed elevated plasma corticosterone levels that correlated with learning deficits in the watermaze. In contrast, despite elevated plasma corticosterone levels throughout life, this glucocorticoid-associated learning deficit was ameliorated in aged 11β-HSD-1 knockout mice, implicating lower intraneuronal corticosterone levels through lack of 11-DHC reactivation. Indeed, aged knockout mice showed significantly lower hippocampal tissue corticosterone levels than wild-type controls. These findings demonstrate that tissue corticosterone levels do not merely reflect plasma levels and appear to play a more important role in hippocampal functions than circulating blood levels. The data emphasize the crucial importance of local enzymes in determining intracellular glucocorticoid activity. Selective 11β-HSD-1 inhibitors may protect against hippocampal function decline with age.

Structure and function of declarative and nondeclarative memory systems

This article reviews recent studies of memory systems in humans and nonhuman primates. Three major conclusions from recent work are that (i) the capacity for nondeclarative (nonconscious) learning can now be studied in a broad array of tasks that assess classification learning, perceptuomotor skill learning, artificial grammar learning, and prototype abstraction; (ii) cortical areas adjacent to the hippocampal formation, including entorhinal, perirhinal, and parahippocampal cortices, are an essential part of the medial temporal lobe memory system that supports declarative (conscious) memory; and (iii) in humans, bilateral damage limited to the hippocampal formation is nevertheless sufficient to produce severe anterograde amnesia and temporally graded retrograde amnesia covering as much as 25 years.

Image recognition: Visual grouping, recognition, and learning

Vision extracts useful information from images. Reconstructing the three-dimensional structure of our environment and recognizing the objects that populate it are among the most important functions of our visual system. Computer vision researchers study the computational principles of vision and aim at designing algorithms that reproduce these functions. Vision is difficult: the same scene may give rise to very different images depending on illumination and viewpoint. Typically, an astronomical number of hypotheses exist that in principle have to be analyzed to infer a correct scene description. Moreover, image information might be extracted at different levels of spatial and logical resolution dependent on the image processing task. Knowledge of the world allows the visual system to limit the amount of ambiguity and to greatly simplify visual computations. We discuss how simple properties of the world are captured by the Gestalt rules of grouping, how the visual system may learn and organize models of objects for recognition, and how one may control the complexity of the description that the visual system computes.

Receptive field structure in the visual cortex: does selective stimulation induce plasticity?

Sensory areas of adult cerebral cortex can reorganize in response to long-term alterations in patterns of afferent signals. This long-term plasticity is thought to play a crucial role in recovery from injury and in some forms of learning. However, the degree to which sensory representations in primary cortical areas depend on short-term (i.e., minute to minute) stimulus variations remains unclear. A traditional view is that each neuron in the mature cortex has a fixed receptive field structure. An alternative view, with fundamentally different implications for understanding cortical function, is that each cell's receptive field is highly malleable, changing according to the recent history of the sensory environment. Consistent with the latter view, it has been reported that selective stimulation of regions surrounding the receptive field induces a dramatic short-term increase in receptive field size for neurons in the visual cortex [Pettet, M. W. & Gilbert, C. D. (1992) Proc. Natl. Acad. Sci. USA 89, 8366-8370]. In contrast, we report here that there is no change in either the size or the internal structure of the receptive field following several minutes of surround stimulation. However, for some cells, overall responsiveness increases. These results suggest that dynamic alterations of receptive field structure do not underlie short-term plasticity in the mature primary visual cortex. However, some degree of short-term adaptability could be mediated by changes in responsiveness.

EmotiBlog: a finer-grained and more precise learning of subjectivity expression models

The exponential growth of the subjective information in the framework of the Web 2.0 has led to the need to create Natural Language Processing tools able to analyse and process such data for multiple practical applications. They require training on specifically annotated corpora, whose level of detail must be fine enough to capture the phenomena involved. This paper presents EmotiBlog – a fine-grained annotation scheme for subjectivity. We show the manner in which it is built and demonstrate the benefits it brings to the systems using it for training, through the experiments we carried out on opinion mining and emotion detection. We employ corpora of different textual genres –a set of annotated reported speech extracted from news articles, the set of news titles annotated with polarity and emotion from the SemEval 2007 (Task 14) and ISEAR, a corpus of real-life self-expressed emotion. We also show how the model built from the EmotiBlog annotations can be enhanced with external resources. The results demonstrate that EmotiBlog, through its structure and annotation paradigm, offers high quality training data for systems dealing both with opinion mining, as well as emotion detection.

Development and psychometric testing of the clinical learning environment, supervision and nurse teacher evaluation scale (CLES+T): The Spanish version

Background: The Clinical Learning Environment, Supervision and Nurse Teacher scale is a reliable and valid instrument to evaluate the quality of the clinical learning process in international nursing education contexts. Objectives: This paper reports the development and psychometric testing of the Spanish version of the Clinical Learning Environment, Supervision and Nurse Teacher scale. Design: Cross-sectional validation study of the scale. Setting: 10 public and private hospitals in the Alicante area, and the Faculty of Health Sciences (University of Alicante, Spain). Participants: 370 student nurses on clinical placement (January 2011–March 2012). Methods: The Clinical Learning Environment, Supervision and Nurse Teacher scale was translated using the modified direct translation method. Statistical analyses were performed using PASW Statistics 18 and AMOS 18.0.0 software. A multivariate analysis was conducted in order to assess construct validity. Cronbach’s alpha coefficient was used to evaluate instrument reliability. Results: An exploratory factorial analysis identified the five dimensions from the original version, and explained 66.4% of the variance. Confirmatory factor analysis supported the factor structure of the Spanish version of the instrument. Cronbach’s alpha coefficient for the scale was .95, ranging from .80 to .97 for the subscales. Conclusion: This version of the Clinical Learning Environment, Supervision and Nurse Teacher scale instrument showed acceptable psychometric properties for use as an assessment scale in Spanish-speaking countries.

Validation of a Spanish version of the Distance Education Learning Environments Survey (DELES) in Spain

The aim of this study was to examine the validity of the Spanish version of the Distance Education Learning Environments Survey (Sp-DELES). This instrument assesses students’ perceptions of virtual learning environments using six scales: Instructor Support, Student Interaction and Collaboration, Personal Relevance, Authentic Learning, Active Learning, and Autonomy. Further, the Sp-DELES includes an additional scale that assesses students’ Satisfaction with their classes. The original DELES has been used in at least 27 independent studies with strong reliability and validity. For this study, we sampled 265 students from the University of Alicante enrolled in various hybrid and distance education courses taught by the Department of Health Psychology. We analysed the Sp-DELES for validity using principal component factor analysis with varimax rotation, and for reliability using Cronbach’s alpha. The Sp-DELES exhibited good reliability (Cronbach’s alpha for the scales ranging from 0.86 to 0.97) and the original six-factor structure was replicated and accounted for 72.9 % of the total variance. Overall the results are consistent with those of the original English-language version of the instrument. The Sp-DELES has proven to be a reliable and valid instrument for assessing psychosocial learning environments in tertiary-level hybrid and distance-education settings.

Teaching-learning process of historical heritage: a Journey as a beginning, path and end

The implantation of new university degrees within the European Higher Education Area implies the need of innovative methodologies in teaching and learning to improve the skills and competencies of students and to answer the growing needs that society continuously demands to heritage management experts. The present work shows an application of the teaching methodology proposed during the international workshop entitled “I International Planning Preservation Workshop. Learning from Al Andalus”, which included the participation of the University of Alicante and Granada, Università Politecnico di Milano and Hunter College City University of New York; where we tried to dissolve traditional boundaries derived of interuniversity cooperation programs. The main objective of the workshop was to discuss and debate the role of urban Historical Centers within the Global Heritage by the integrated work through multidisciplinary teams and the creation of a permanent international working group between these universities to both teach and research. The methodology of this workshop was very participatory and considered the idea of a new learning process generated by "a journey experience." A trip from global to local (from the big city to the small village) but also a trip from the local (historical) part of a big city to the global dimension of contemporary historical villages identified by the students through a system of exhibition panels in affinity groups, specific projects proposed by lecturers and teachers or the generation of publications in various areas (texts, photographs, videos, etc.). So, the participation of the students in this multidisciplinary meeting has enhanced their capacity for self-criticism in several disciplines and has promoted their ability to perform learning and research strategies in an autonomous way. As a result, it has been established a permanent international work structure for the development of projects of the Historical City. This relationship has generated the publication of several books whose contents have reflected the conclusions developed in the workshop and several teaching proposals shared between those institutions. All these aspects have generated a new way of understanding the teaching process through a journey, in order to study the representative role of university in the historical heritage and to make students (from planning, heritage management, architecture, geography, sociology, history or engineering areas) be compromised on searching strategies for sustainable development in the Contemporary City.

Principles of Navy budget : self-instructional learning unit.

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