Educational orientation regarding vocabulary and literacy access : Evaluating the impact of an intervention program designed to promote early learning at home

El estudio evalúa el impacto de un programa de promoción del desarrollo lingüístico y cognitivo para niños de 5 años implementado según dos modalidades: una que implicó acciones de alfabetización familiar en los hogares de los niños (modalidad intensiva) y otra que incluyó la participación de los niños en las salas de jardín de infantes (modalidad extensiva). La evaluación del impacto se realizó por medio de un diseño pre-test ? post-test. Se tomaron pruebas de vocabulario receptivo (VR), producción de categorías (PC) y escritura a una muestra de 214 niños participantes de la modalidad intensiva, 69 participantes de la modalidad extensiva y un grupo control de no participó del programa (49 niños). Los resultados mostraron que la participación en la modalidad intensiva implicó un mayor incremento en las habilidades infantiles de VR, PC que en la modalidad extensiva. A su vez ambas modalidades experimentales mostraron un mayor incremento en las variables examinadas respecto de las observadas en el grupo control. No se detectaron efectos de la escolaridad de la madre y la asistencia previa al jardín. Los resultados mostraron correlaciones significativas entre todas las variables analizadas y el valor predictivo de los puntajes en VR a principio de año respecto de los puntajes en VR y escritura a fin de año.

Skill sorting and production chains : evidence from India

This study proposes a new mechanism that explains skill-sorting patterns and skill wage differentials across industries based on the length of the industry's production chain. A simple simultaneous production model shows that when the quality of intermediate inputs deteriorates rapidly along the production chains, high-skilled individuals choose to work in industries with shorter production chains because of higher returns to skill. I empirically confirm this skill-sorting pattern and these inter-industry skill wage differentials in India, where the quality of intermediate inputs is likely to degrade rapidly because of the high number of unskilled laborers, poor infrastructure, and less-advantaged technology. The results remain robust even when considering selection bias, alternative reasons for inter-industry skill wage differentials, and a different period. The results of this study have important implications when considering countries' industrial development patterns.

Negative skill sorting across production chains

Previous literature generally predicts that individuals with higher skills work in industries with longer production chains. However, the opposite skill-sorting pattern, a "negative skill-sorting" phenomenon, is also observed in reality. This paper proposes a possible mechanism by which both cases can happen and shows that negative skill sorting is more likely to occur when the quality of intermediate inputs degrade rapidly (or improves slowly) along the production chain. We empirically confirm our theoretical prediction by using country-industry panel data. The results are robust regardless of estimation method, control variables, and industry coverage. This study has important implications for understanding countries' comparative advantages and development patterns.

Development and implementation of a virtual laboratory for training process improvement in the mechanics of continuous media

The project arises from the need to develop improved teaching methodologies in field of the mechanics of continuous media. The objective is to offer the student a learning process to acquire the necessary theoretical knowledge, cognitive skills and the responsibility and autonomy to professional development in this area. Traditionally the teaching of the concepts of these subjects was performed through lectures and laboratory practice. During these lessons the students attitude was usually passive, and therefore their effectiveness was poor. The proposed methodology has already been successfully employed in universities like University Bochum, Germany, University the South Australia and aims to improve the effectiveness of knowledge acquisition through use by the student of a virtual laboratory. This laboratory allows to adapt the curricula and learning techniques to the European Higher Education and improve current learning processes in the University School of Public Works Engineers -EUITOP- of the Technical University of Madrid -UPM-, due there are not laboratories in this specialization. The virtual space is created using a software platform built on OpenSim, manages 3D virtual worlds, and, language LSL -Linden Scripting Language-, which imprints specific powers to objects. The student or user can access this virtual world through their avatar -your character in the virtual world- and can perform practices within the space created for the purpose, at any time, just with computer with internet access and viewfinder. The virtual laboratory has three partitions. The virtual meeting rooms, where the avatar can interact with peers, solve problems and exchange existing documentation in the virtual library. The interactive game room, where the avatar is has to resolve a number of issues in time. And the video room where students can watch instructional videos and receive group lessons. Each audiovisual interactive element is accompanied by explanations framing it within the area of knowledge and enables students to begin to acquire a vocabulary and practice of the profession for which they are being formed. Plane elasticity concepts are introduced from the tension and compression testing of test pieces of steel and concrete. The behavior of reticulated and articulated structures is reinforced by some interactive games and concepts of tension, compression, local and global buckling will by tests to break articulated structures. Pure bending concepts, simple and composite torsion will be studied by observing a flexible specimen. Earthquake resistant design of buildings will be checked by a laboratory test video.

Intelligent Therapy Assistant (ITA) for cognitive rehabilitation in patients with Acquired Brain Injury

This paper presents the design, development and first evaluation of an algorithm, named Intelligent Therapy Assistant (ITA), which automatically selects, configures and schedules rehabilitation tasks for patients with cognitive impairments after an episode of Acquired Brain Injury. The ITA is integrated in "Guttmann, Neuro Personal Trainer" (GNPT), a cognitive tele-rehabilitation platform that provides neuropsychological services.

Three-dimensional mapping of real environments for cognitive robots navigation

Abstract The development of cognitive robots needs a strong “sensorial” support which should allow it to perceive the real world for interacting with it properly. Therefore the development of efficient visual-processing software to be equipped in effective artificial agents is a must. In this project we study and develop a visual-processing software that will work as the “eyes” of a cognitive robot. This software performs a three-dimensional mapping of the robot’s environment, providing it with the essential information required to make proper decisions during its navigation. Due to the complexity of this objective we have adopted the Scrum methodology in order to achieve an agile development process, which has allowed us to correct and improve in a fast way the successive versions of the product. The present project is structured in Sprints, which cover the different stages of the software development based on the requirements imposed by the robot and its real necessities. We have initially explored different commercial devices oriented to the acquisition of the required visual information, adopting the Kinect Sensor camera (Microsoft) as the most suitable option. Later on, we have studied the available software to manage the obtained visual information as well as its integration with the robot’s software, choosing the high-level platform Matlab as the common nexus to join the management of the camera, the management of the robot and the implementation of the behavioral algorithms. During the last stages the software has been developed to include the fundamental functionalities required to process the real environment, such as depth representation, segmentation, and clustering. Finally the software has been optimized to exhibit real-time processing and a suitable performance to fulfill the robot’s requirements during its operation in real situations.

Improving brain injury cognitive rehabilitation by personalized telerehabilitation services: Guttmann neuropersonal trainer

Cognitive rehabilitation aims to remediate or alleviate the cognitive deficits appearing after an episode of acquired brain injury (ABI). The purpose of this work is to describe the telerehabilitation platform called Guttmann Neuropersonal Trainer (GNPT) which provides new strategies for cognitive rehabilitation, improving efficiency and access to treatments, and to increase knowledge generation from the process. A cognitive rehabilitation process has been modeled to design and develop the system, which allows neuropsychologists to configure and schedule rehabilitation sessions, consisting of set of personalized computerized cognitive exercises grounded on neuroscience and plasticity principles. It provides remote continuous monitoring of patient's performance, by an asynchronous communication strategy. An automatic knowledge extraction method has been used to implement a decision support system, improving treatment customization. GNPT has been implemented in 27 rehabilitation centers and in 83 patients' homes, facilitating the access to the treatment. In total, 1660 patients have been treated. Usability and cost analysis methodologies have been applied to measure the efficiency in real clinical environments. The usability evaluation reveals a system usability score higher than 70 for all target users. The cost efficiency study results show a relation of 1-20 compared to face-to-face rehabilitation. GNPT enables brain-damaged patients to continue and further extend rehabilitation beyond the hospital, improving the efficiency of the rehabilitation process. It allows customized therapeutic plans, providing information to further development of clinical practice guidelines.

Cognitive wireless sensor network platform for cooperative communications

Nowadays, Wireless Ad Hoc Sensor Networks (WAHSNs), specially limited in energy and resources, are subject to development constraints and difficulties such as the increasing RF spectrum saturation at the unlicensed bands. Cognitive Wireless Sensor Networks (CWSNs), leaning on a cooperative communication model, develop new strategies to mitigate the inefficient use of the spectrum that WAHSNs face. However, few and poorly featured platforms allow their study due to their early research stage. This paper presents a versatile platform that brings together cognitive properties into WAHSNs. It combines hardware and software modules as an entire instrument to investigate CWSNs. The hardware fits WAHSN requirements in terms of size, cost, features, and energy. It allows communication over three different RF bands, becoming the only cognitive platform for WAHSNs with this capability. In addition, its modular and scalable design is widely adaptable to almost any WAHSN application. Significant features such as radio interface (RI) agility or energy consumption have been proven throughout different performance tests.

A game theory based strategy for reducing energy consumption in cognitive WSN

Wireless sensor networks (WSNs) are one of the most important users of wireless communication technologies in the coming years and some challenges in this area must be addressed for their complete development. Energy consumption and spectrum availability are two of the most severe constraints of WSNs due to their intrinsic nature. The introduction of cognitive capabilities into these networks has arisen to face the issue of spectrum scarcity but could be used to face energy challenges too due to their new range of communication possibilities. In this paper a new strategy based on game theory for cognitive WSNs is discussed. The presented strategy improves energy consumption by taking advantage of the new change-communication-channel capability. Based on game theory, the strategy decides when to change the transmission channel depending on the behavior of the rest of the network nodes. The strategy presented is lightweight but still has higher energy saving rates as compared to noncognitive networks and even to other strategies based on scheduled spectrum sensing. Simulations are presented for several scenarios that demonstrate energy saving rates of around 65% as compared to WSNs without cognitive techniques.

Cognitive strategies for reducing energy consumption in wireless sensor networks

El consumo energético de las Redes de Sensores Inalámbricas (WSNs por sus siglas en inglés) es un problema histórico que ha sido abordado desde diferentes niveles y visiones, ya que no solo afecta a la propia supervivencia de la red sino que el creciente uso de dispositivos inteligentes y el nuevo paradigma del Internet de las Cosas hace que las WSNs tengan cada vez una mayor influencia en la huella energética. Debido a la tendencia al alza en el uso de estas redes se añade un nuevo problema, la saturación espectral. Las WSNs operan habitualmente en bandas sin licencia como son las bandas Industrial, Científica y Médica (ISM por sus siglas en inglés). Estas bandas se comparten con otro tipo de redes como Wi-Fi o Bluetooth cuyo uso ha crecido exponencialmente en los últimos años. Para abordar este problema aparece el paradigma de la Radio Cognitiva (CR), una tecnología que permite el acceso oportunista al espectro. La introducción de capacidades cognitivas en las WSNs no solo permite optimizar su eficiencia espectral sino que también tiene un impacto positivo en parámetros como la calidad de servicio, la seguridad o el consumo energético. Sin embargo, por otra parte, este nuevo paradigma plantea algunos retos relacionados con el consumo energético. Concretamente, el sensado del espectro, la colaboración entre los nodos (que requiere comunicación adicional) y el cambio en los parámetros de transmisión aumentan el consumo respecto a las WSN clásicas. Teniendo en cuenta que la investigación en el campo del consumo energético ha sido ampliamente abordada puesto que se trata de una de sus principales limitaciones, asumimos que las nuevas estrategias deben surgir de las nuevas capacidades añadidas por las redes cognitivas. Por otro lado, a la hora de diseñar estrategias de optimización para CWSN hay que tener muy presentes las limitaciones de recursos de estas redes en cuanto a memoria, computación y consumo energético de los nodos. En esta tesis doctoral proponemos dos estrategias de reducción de consumo energético en CWSNs basadas en tres pilares fundamentales. El primero son las capacidades cognitivas añadidas a las WSNs que proporcionan la posibilidad de adaptar los parámetros de transmisión en función del espectro disponible. La segunda es la colaboración, como característica intrínseca de las CWSNs. Finalmente, el tercer pilar de este trabajo es teoría de juegos como algoritmo de soporte a la decisión, ampliamente utilizado en WSNs debido a su simplicidad. Como primer aporte de la tesis se presenta un análisis completo de las posibilidades introducidas por la radio cognitiva en materia de reducción de consumo para WSNs. Gracias a las conclusiones extraídas de este análisis, se han planteado las hipótesis de esta tesis relacionadas con la validez de usar capacidades cognitivas como herramienta para la reducción de consumo en CWSNs. Una vez presentada las hipótesis, pasamos a desarrollar las principales contribuciones de la tesis: las dos estrategias diseñadas para reducción de consumo basadas en teoría de juegos y CR. La primera de ellas hace uso de un juego no cooperativo que se juega mediante pares de jugadores. En la segunda estrategia, aunque el juego continúa siendo no cooperativo, se añade el concepto de colaboración. Para cada una de las estrategias se presenta el modelo del juego, el análisis formal de equilibrios y óptimos y la descripción de la estrategia completa donde se incluye la interacción entre nodos. Con el propósito de probar las estrategias mediante simulación e implementación en dispositivos reales hemos desarrollado un marco de pruebas compuesto por un simulador cognitivo y un banco de pruebas formado por nodos cognitivos capaces de comunicarse en tres bandas ISM desarrollados en el B105 Lab. Este marco de pruebas constituye otra de las aportaciones de la tesis que permitirá el avance en la investigación en el área de las CWSNs. Finalmente, se presentan y discuten los resultados derivados de la prueba de las estrategias desarrolladas. La primera estrategia proporciona ahorros de energía mayores al 65% comparados con una WSN sin capacidades cognitivas y alrededor del 25% si la comparamos con una estrategia cognitiva basada en el sensado periódico del espectro para el cambio de canal de acuerdo a un nivel de ruido fijado. Este algoritmo se comporta de forma similar independientemente del nivel de ruido siempre que éste sea espacialmente uniformemente. Esta estrategia, a pesar de su sencillez, nos asegura el comportamiento óptimo en cuanto a consumo energético debido a la utilización de teoría de juegos en la fase de diseño del comportamiento de los nodos. La estrategia colaborativa presenta mejoras respecto a la anterior en términos de protección frente al ruido en escenarios de ruido más complejos donde aporta una mejora del 50% comparada con la estrategia anterior. ABSTRACT Energy consumption in Wireless Sensor Networks (WSNs) is a known historical problem that has been addressed from different areas and on many levels. But this problem should not only be approached from the point of view of their own efficiency for survival. A major portion of communication traffic has migrated to mobile networks and systems. The increased use of smart devices and the introduction of the Internet of Things (IoT) give WSNs a great influence on the carbon footprint. Thus, optimizing the energy consumption of wireless networks could reduce their environmental impact considerably. In recent years, another problem has been added to the equation: spectrum saturation. Wireless Sensor Networks usually operate in unlicensed spectrum bands such as Industrial, Scientific, and Medical (ISM) bands shared with other networks (mainly Wi-Fi and Bluetooth). To address the efficient spectrum utilization problem, Cognitive Radio (CR) has emerged as the key technology that enables opportunistic access to the spectrum. Therefore, the introduction of cognitive capabilities to WSNs allows optimizing their spectral occupation. Cognitive Wireless Sensor Networks (CWSNs) do not only increase the reliability of communications, but they also have a positive impact on parameters such as the Quality of Service (QoS), network security, or energy consumption. These new opportunities introduced by CWSNs unveil a wide field in the energy consumption research area. However, this also implies some challenges. Specifically, the spectrum sensing stage, collaboration among devices (which requires extra communication), and changes in the transmission parameters increase the total energy consumption of the network. When designing CWSN optimization strategies, the fact that WSN nodes are very limited in terms of memory, computational power, or energy consumption has to be considered. Thus, light strategies that require a low computing capacity must be found. Since the field of energy conservation in WSNs has been widely explored, we assume that new strategies could emerge from the new opportunities presented by cognitive networks. In this PhD Thesis, we present two strategies for energy consumption reduction in CWSNs supported by three main pillars. The first pillar is that cognitive capabilities added to the WSN provide the ability to change the transmission parameters according to the spectrum. The second pillar is that the ability to collaborate is a basic characteristic of CWSNs. Finally, the third pillar for this work is the game theory as a decision-making algorithm, which has been widely used in WSNs due to its lightness and simplicity that make it valid to operate in CWSNs. For the development of these strategies, a complete analysis of the possibilities is first carried out by incorporating the cognitive abilities into the network. Once this analysis has been performed, we expose the hypotheses of this thesis related to the use of cognitive capabilities as a useful tool to reduce energy consumption in CWSNs. Once the analyses are exposed, we present the main contribution of this thesis: the two designed strategies for energy consumption reduction based on game theory and cognitive capabilities. The first one is based on a non-cooperative game played between two players in a simple and selfish way. In the second strategy, the concept of collaboration is introduced. Despite the fact that the game used is also a non-cooperative game, the decisions are taken through collaboration. For each strategy, we present the modeled game, the formal analysis of equilibrium and optimum, and the complete strategy describing the interaction between nodes. In order to test the strategies through simulation and implementation in real devices, we have developed a CWSN framework composed by a CWSN simulator based on Castalia and a testbed based on CWSN nodes able to communicate in three different ISM bands. We present and discuss the results derived by the energy optimization strategies. The first strategy brings energy improvement rates of over 65% compared to WSN without cognitive techniques. It also brings energy improvement rates of over 25% compared with sensing strategies for changing channels based on a decision threshold. We have also seen that the algorithm behaves similarly even with significant variations in the level of noise while working in a uniform noise scenario. The collaborative strategy presents improvements respecting the previous strategy in terms of noise protection when the noise scheme is more complex where this strategy shows improvement rates of over 50%.

Cognitive Surveillance Architecture for Scenario Understanding

Uno de los mayores retos para la comunidad científica es conseguir que las máquinas posean en un futuro la capacidad del sistema visual y cognitivo humanos, de forma que, por ejemplo, en entornos de video vigilancia, puedan llegar a proporcionar de manera automática una descripción fiable de lo que está ocurriendo en la escena. En la presente tesis, mediante la propuesta de un marco de trabajo de referencia, se discuten y plantean los pasos necesarios para el desarrollo de sistemas más inteligentes capaces de extraer y analizar, a diferentes niveles de abstracción y mediante distintos módulos de procesamiento independientes, la información necesaria para comprender qué está sucediendo en un conjunto amplio de escenarios de distinta naturaleza. Se parte de un análisis de requisitos y se identifican los retos para este tipo de sistemas en la actualidad, lo que constituye en sí mismo los objetivos de esta tesis, contribuyendo así a un modelo de datos basado en el conocimiento que permitirá analizar distintas situaciones en las que personas y vehículos son los actores principales, dejando no obstante la puerta abierta a la adaptación a otros dominios. Así mismo, se estudian los distintos procesos que se pueden lanzar a nivel interno así como la necesidad de integrar mecanismos de realimentación a distintos niveles que permitan al sistema adaptarse mejor a cambios en el entorno. Como resultado, se propone un marco de referencia jerárquico que integra las capacidades de percepción, interpretación y aprendizaje para superar los retos identificados en este ámbito; y así poder desarrollar sistemas de vigilancia más robustos, flexibles e inteligentes, capaces de operar en una variedad de entornos. Resultados experimentales ejecutados sobre distintas muestras de datos (secuencias de vídeo principalmente) demuestran la efectividad del marco de trabajo propuesto respecto a otros propuestos en el pasado. Un primer caso de estudio, permite demostrar la creación de un sistema de monitorización de entornos de parking en exteriores para la detección de vehículos y el análisis de plazas libres de aparcamiento. Un segundo caso de estudio, permite demostrar la flexibilidad del marco de referencia propuesto para adaptarse a los requisitos de un entorno de vigilancia completamente distinto, como es un hogar inteligente donde el análisis automático de actividades de la vida cotidiana centra la atención del estudio. ABSTRACT One of the most ambitious objectives for the Computer Vision and Pattern Recognition research community is that machines can achieve similar capacities to the human's visual and cognitive system, and thus provide a trustworthy description of what is happening in the scene under surveillance. Thus, a number of well-established scenario understanding architectural frameworks to develop applications working on a variety of environments can be found in the literature. In this Thesis, a highly descriptive methodology for the development of scene understanding applications is presented. It consists of a set of formal guidelines to let machines extract and analyse, at different levels of abstraction and by means of independent processing modules that interact with each other, the necessary information to understand a broad set of different real World surveillance scenarios. Taking into account the challenges that working at both low and high levels offer, we contribute with a highly descriptive knowledge-based data model for the analysis of different situations in which people and vehicles are the main actors, leaving the door open for the development of interesting applications in diverse smart domains. Recommendations to let systems achieve high-level behaviour understanding will be also provided. Furthermore, feedback mechanisms are proposed to be integrated in order to let any system to understand better the environment and the logical context around, reducing thus the uncertainty and noise, and increasing its robustness and precision in front of low-level or high-level errors. As a result, a hierarchical cognitive architecture of reference which integrates the necessary perception, interpretation, attention and learning capabilities to overcome main challenges identified in this area of research is proposed; thus allowing to develop more robust, flexible and smart surveillance systems to cope with the different requirements of a variety of environments. Once crucial issues that should be treated explicitly in the design of this kind of systems have been formulated and discussed, experimental results shows the effectiveness of the proposed framework compared with other proposed in the past. Two case studies were implemented to test the capabilities of the framework. The first case study presents how the proposed framework can be used to create intelligent parking monitoring systems. The second case study demonstrates the flexibility of the system to cope with the requirements of a completely different environment, a smart home where activities of daily living are performed. Finally, general conclusions and future work lines to further enhancing the capabilities of the proposed framework are presented.

Alternative neural circuitry that might be impaired in the development of Alzheimer disease

It is well established that some individuals with normal cognitive capacity have abundant senile plaques in their brains. It has been proposed that those individuals are resilient or have compensation factors to prevent cognitive decline. In this comment, we explore an alternative mechanism through which cognitive capacity is maintained. This mechanism could involve the impairment of alternative neural circuitry. Also, the proportion of molecules such as A? or tau protein present in different areas of the brain could be important.

Development of a sensorimotor algorithm able to deal with unforeseen pushes and its implementation based on VHDL

Development of a Sensorimotor Algorithm Able to Deal with Unforeseen Pushes and Its Implementation Based on VHDL is the title of my thesis which concludes my Bachelor Degree in the Escuela Técnica Superior de Ingeniería y Sistemas de Telecomunicación of the Universidad Politécnica de Madrid. It encloses the overall work I did in the Neurorobotics Research Laboratory from the Beuth Hochschule für Technik Berlin during my ERASMUS year in 2015. This thesis is focused on the field of robotics, specifically an electronic circuit called Cognitive Sensorimotor Loop (CSL) and its control algorithm based on VHDL hardware description language. The reason that makes the CSL special resides in its ability to operate a motor both as a sensor and an actuator. This way, it is possible to achieve a balanced position in any of the robot joints (e.g. the robot manages to stand) without needing any conventional sensor. In other words, the back electromotive force (EMF) induced by the motor coils is measured and the control algorithm responds depending on its magnitude. The CSL circuit contains mainly an analog-to-digital converter (ADC) and a driver. The ADC consists on a delta-sigma modulation which generates a series of bits with a certain percentage of 1's and 0's, proportional to the back EMF. The control algorithm, running in a FPGA, processes the bit frame and outputs a signal for the driver. This driver, which has an H bridge topology, gives the motor the ability to rotate in both directions while it's supplied with the power needed. The objective of this thesis is to document the experiments and overall work done on push ignoring contractive sensorimotor algorithms, meaning sensorimotor algorithms that ignore large magnitude forces (compared to gravity) applied in a short time interval on a pendulum system. This main objective is divided in two sub-objectives: (1) developing a system based on parameterized thresholds and (2) developing a system based on a push bypassing filter. System (1) contains a module that outputs a signal which blocks the main Sensorimotor algorithm when a push is detected. This module has several different parameters as inputs e.g. the back EMF increment to consider a force as a push or the time interval between samples. System (2) consists on a low-pass Infinite Impulse Response digital filter. It cuts any frequency considered faster than a certain push oscillation. This filter required an intensive study on how to implement some functions and data types (fixed or floating point data) not supported by standard VHDL packages. Once this was achieved, the next challenge was to simplify the solution as much as possible, without using non-official user made packages. Both systems behaved with a series of interesting advantages and disadvantages for the elaboration of the document. Stability, reaction time, simplicity or computational load are one of the many factors to be studied in the designed systems. RESUMEN. Development of a Sensorimotor Algorithm Able to Deal with Unforeseen Pushes and Its Implementation Based on VHDL es un Proyecto de Fin de Grado (PFG) que concluye mis estudios en la Escuela Técnica Superior de Ingeniería y Sistemas de Telecomunicación de la Universidad Politécnica de Madrid. En él se documenta el trabajo de investigación que realicé en el Neurorobotics Research Laboratory de la Beuth Hochschule für Technik Berlin durante el año 2015 mediante el programa de intercambio ERASMUS. Este PFG se centra en el campo de la robótica y en concreto en un circuito electrónico llamado Cognitive Sensorimotor Loop (CSL) y su algoritmo de control basado en lenguaje de modelado hardware VHDL. La particularidad del CSL reside en que se consigue que un motor haga las veces tanto de sensor como de actuador. De esta manera es posible que las articulaciones de un robot alcancen una posición de equilibrio (p.ej. el robot se coloca erguido) sin la necesidad de sensores en el sentido estricto de la palabra. Es decir, se mide la propia fuerza electromotriz (FEM) inducida sobre el motor y el algoritmo responde de acuerdo a su magnitud. El circuito CSL se compone de un convertidor analógico-digital (ADC) y un driver. El ADC consiste en un modulador sigma-delta, que genera una serie de bits con un porcentaje de 1's y 0's determinado, en proporción a la magnitud de la FEM inducida. El algoritmo de control, que se ejecuta en una FPGA, procesa esta cadena de bits y genera una señal para el driver. El driver, que posee una topología en puente H, provee al motor de la potencia necesaria y le otorga la capacidad de rotar en cualquiera de las dos direcciones. El objetivo de este PFG es documentar los experimentos y en general el trabajo realizado en algoritmos Sensorimotor que puedan ignorar fuerzas de gran magnitud (en comparación con la gravedad) y aplicadas en una corta ventana de tiempo. En otras palabras, ignorar empujones conservando el comportamiento original frente a la gravedad. Para ello se han desarrollado dos sistemas: uno basado en umbrales parametrizados (1) y otro basado en un filtro de corte ajustable (2). El sistema (1) contiene un módulo que, en el caso de detectar un empujón, genera una señal que bloquea el algoritmo Sensorimotor. Este módulo recibe diferentes parámetros como el incremento necesario de la FEM para que se considere un empujón o la ventana de tiempo para que se considere la existencia de un empujón. El sistema (2) consiste en un filtro digital paso-bajo de respuesta infinita que corta cualquier variación que considere un empujón. Para crear este filtro se requirió un estudio sobre como implementar ciertas funciones y tipos de datos (coma fija o flotante) no soportados por las librerías básicas de VHDL. Tras esto, el objetivo fue simplificar al máximo la solución del problema, sin utilizar paquetes de librerías añadidos. En ambos sistemas aparecen una serie de ventajas e inconvenientes de interés para el documento. La estabilidad, el tiempo de reacción, la simplicidad o la carga computacional son algunas de las muchos factores a estudiar en los sistemas diseñados. Para concluir, también han sido documentadas algunas incorporaciones a los sistemas: una interfaz visual en VGA, un módulo que compensa el offset del ADC o la implementación de una batería de faders MIDI entre otras.

L’abilità di perspective taking : un training per bambini in età prescolare in differenti contesti

Elemento centrale della presente tesi dottorale è il costrutto di perspective taking, definibile come l’abilità, emergente nei bambini intorno a 4-5 anni, di assumere la prospettiva altrui secondo tre differenti dimensioni: emotiva, cognitiva e percettiva (Bonino, Lo Coco, Tani, 1998; Moll e Meltzoff, 2011). Dalla letteratura emerge come il perspective taking, in quanto abilità di comprensione sociale, rivesta un ruolo adattivo e sia fondamentale per lo sviluppo, non solo intellettivo, ma anche per la formazione di adeguate capacità relazionali e sociali (Jenkins e Astington, 2000; Weil et al., 2011). Sulla base di tali considerazioni, alcuni ricercatori si sono interrogati sulla possibilità di insegnare questa abilità, elaborando specifiche e differenti procedure di intervento finalizzate ad incrementare l’abilità di perspective taking sia in bambini a sviluppo normativo (Cigala e Mori, 2015), sia in gruppi di bambini a sviluppo atipico (Fisher e Happé, 2005; Heagle e Rehfeldt, 2006; Paynter e Peterson, 2012). A partire da una prospettiva teorica socio-costruzionista, secondo cui l’acquisizione del perspective taking si configura come un’impresa di co-costruzione continua, all’interno di interazioni quotidiane con figure significative per il bambino, si è deciso di analizzare il perspective taking non solo in relazione a variabili individuali (genere, età del bambino, regolazione emotiva, abilità sociali) ma anche e soprattutto a variabili contestuali quali le caratteristiche del contesto familiare (caratteristiche disposizionali e stili genitoriali di socializzazione emotiva, presenza di fratelli). Sono stati in particolare indagati un contesto familiare normativo ed uno caratterizzato da maltrattamento psicologico, contrassegnato dalla reiterazione di comportamenti inadeguati (critiche svalutanti, denigrazione, umiliazione, minacce verbali, indifferenza) nei confronti del minore, che convogliano sul bambino l’idea di non essere amato e di avere poco valore. Con i termini “a sviluppo tipico” si intendono i bambini per i quali non sussista una diagnosi clinica e con quelli di “famiglie normative” ci si riferisce a nuclei per i quali non ci siano state segnalazioni da parte dei Servizi Educativi e Sociali di riferimento, indipendentemente dalle caratteristiche della composizione del nucleo familiare (nucleare, estesa, multipla, ricostituita o ricomposta). Tale studio rientra in un ampio progetto di ricerca e formazione che ha coinvolto più di 250 prescolari frequentanti 8 scuole dell’infanzia e 15 comunità terapeutiche e di accoglienza mamma-bambino, situate in differenti province del Nord Italia. Il gruppo dei partecipanti alla ricerca si è composto di 256 bambini in età prescolare, compresa quindi tra 3 e 5 anni (M=54,39; DS=5,705): 128 maschi (M=54,08; DS=5,551) e 128 femmine (M=54,70; DS=5,860). In particolare, 213 bambini appartenevano a famiglie normative e 43 a nuclei familiari caratterizzati dalla presenza di maltrattamento psicologico. Oltre ai bambini, la ricerca ha previsto il coinvolgimento di 155 coppie di genitori, 43 madri ospitate in comunità, 18 insegnanti e 30 operatori. Obiettivo centrale è stato l’indagine della possibilità di poter promuovere il perspective taking in bambini di età prescolare a sviluppo tipico appartenenti a due differenti tipologie di contesto familiare (normativo e psicologicamente maltrattante), attraverso l’applicazione di uno specifico percorso di training di natura “ecologica” all’interno della scuola dell’infanzia e della comunità, assimilabile a quelli di tipo evidence based. In particolare è stata prevista una procedura quasi sperimentale di tipo pre-test, training, post-test e follow-up. Dopo una preliminare valutazione dello sviluppo del perspective taking nelle sue tre componenti, in bambini appartenenti ad entrambi i contesti, si è voluto verificare l’esistenza di eventuali relazioni tra questa abilità ed alcune capacità socio-emotive dei bambini, con particolare riferimento alla disposizione prosociale, rilevate nel contesto scolastico attraverso differenti metodologie (osservazioni dirette non partecipanti, questionari self report compilati dalle insegnanti). Inoltre, data l’importanza del contesto familiare per lo sviluppo di tale abilità, la ricerca ha avuto lo scopo di verificare l’esistenza di eventuali relazioni tra le abilità di perspective taking mostrate dai bambini e gli stili di socializzazione emotiva delle figure familiari, caratteristiche di entrambi i contesti (maltrattante e non maltrattante). È stato inoltre previsto uno studio di confronto tra i due campioni rispetto alle dimensioni indagate. I risultati ottenuti sono stati particolarmente interessanti. Innanzitutto, le esperienze di training hanno determinato, in entrambi i contesti, miglioramenti nell’abilità dei prescolari di mettersi nei panni altrui. Tale training ha inoltre dimostrato effetti positivi sulla competenza sociale dei bambini, che, a seguito del percorso, hanno manifestato un incremento dei comportamenti prosociali ed una diminuzione di quelli aggressivi. Per lo studio in contesto normativo, è stato inoltre dimostrato un mantenimento delle abilità acquisite a seguito del training attraverso un follow-up a distanza di 4 mesi dal termine dell’intervento. Il positivo esito di tale percorso sembra quindi rappresentare un’importante risorsa per i prescolari, soprattutto in caso di situazioni in cui l’abilità di perspective taking risulti deficitaria. Il confronto dei due gruppi a seguito del training ha evidenziato come non siano emerse differenze significative, rispetto al perspective taking, ad eccezione della dimensione emotiva, in cui le prestazioni dei prescolari maltrattati sono risultate inferiori, come già evidenziato prima del training. Tali risultati non giungono però inaspettati, poiché, sebbene il percorso abbia agito significativamente sull’abilità di comprensione delle emozioni altrui di questi bambini, non si configura come sufficiente a ristrutturare così profondamente le problematiche presentate. Interessanti sono stati altresì i risultati ottenuti dall’analisi degli stili di socializzazione emotiva, dei genitori (madri e padri) dei prescolari non maltrattati e delle mamme dei bambini residenti in comunità. In particolare è emerso come, stili accettanti e di tipo coaching nei confronti delle emozioni negative dei bambini, siano positivamente correlati con il perspective taking dei figli, e come all’opposto, stili rifiutanti rispetto alle espressioni emotive negative dei propri bambini, mostrino correlazioni negative con le abilità di perspective taking dei figli. Oltre ad interessi di ordine teorico e metodologico, è possibile quindi affermare come, il presente lavoro di tesi, sia stato guidato da fini applicativi, affinché la ricerca scientifica possa tradursi in pratiche educative quotidiane da applicare ai contesti di vita significativi per i bambini.

A Young Child's Anxiety and Math Performance: Enhancing Cognitive Behavioral Intervention with Conjoint Behavioral Consultation

Partnering with families, school personnel, and community resources is an important step to supporting the child and family, especially when children might suffer from debilitating anxiety concerns. However, little research examines the impact of anxiety on math performance for young children participating in school-based interventions enhanced by family components. The following research questions were addressed in the study: 1a) Will a young child with elevated levels of anxiety show a decrease in anxiety symptoms with a Cognitive Behavioral framework intervention program for children? 1b) Will anxiety be reduced with the addition of a Conjoint Behavioral Consultation with the family and teacher? 2a) Will a young child show an increase in math performance after participation in a Cognitive Behavioral framework intervention program for children? 2b) Will math performance be increased with the addition of a Conjoint Behavioral Consultation with the family and teacher? A single-subject staggered baseline across situations intervention study addressed whether the Coping Cat, an evidenced-based child-focused intervention now widely used in schools and clinics to treat childhood anxiety, combined with family and school consultation will decrease elevated anxiety levels and improve math performance in an elementary-aged student. The objective was to support mental health development and math performance with an eight-year-old, female elementary student through a collaborative effort of stakeholders in the student's life. Baseline data was collected with repeated measures of anxiety and math performance, and was compared to two intervention phases: first, a child-focused intervention and second, a family and school consultation. The study tested the theory that the Cognitive Behavioral intervention and Conjoint Behavioral Consultation intervention will influence, positively, the anxiety levels and math performance for an elementary-aged student. Results indicate that the child participant with elevated levels of anxiety showed a reduction in symptoms with the introduction of a Cognitive Behavioral framework intervention when compared to her baseline data. The participant showed further reduction in symptoms across the school and home settings with the implementation of Conjoint Behavioral Consultation when compared to baseline and the first intervention phase. Math performance began to increase with the introduction of the Cognitive Behavioral intervention, and continued to improve with the implementation of the Conjoint Behavioral Consultation. Findings suggest that consultation should begin immediately when an intervention is implemented in order to enhance outcomes.