913 resultados para Embedded System, Domain Specific Language (DSL), Agenti BDI, Arduino, Agentino


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Pour être performant au plus haut niveau, les athlètes doivent posséder une capacité perceptivo-cognitive supérieure à la moyenne. Cette faculté, reflétée sur le terrain par la vision et l’intelligence de jeu des sportifs, permet d’extraire l’information clé de la scène visuelle. La science du sport a depuis longtemps observé l’expertise perceptivo-cognitive au sein de l’environnement sportif propre aux athlètes. Récemment, des études ont rapporté que l’expertise pouvait également se refléter hors de ce contexte, lors d’activités du quotidien par exemple. De plus, les récentes théories entourant la capacité plastique du cerveau ont amené les chercheurs à développer des outils pour entraîner les capacités perceptivo-cognitives des athlètes afin de les rendre plus performants sur le terrain. Ces méthodes sont la plupart du temps contextuelles à la discipline visée. Cependant, un nouvel outil d’entraînement perceptivo-cognitif, nommé 3-Dimensional Multiple Object Tracking (3D-MOT) et dénué de contexte sportif, a récemment vu le jour et a fait l’objet de nos recherches. Un de nos objectifs visait à mettre en évidence l’expertise perceptivo-cognitive spécifique et non-spécifique chez des athlètes lors d’une même étude. Nous avons évalué la perception du mouvement biologique chez des joueurs de soccer et des non-athlètes dans une salle de réalité virtuelle. Les sportifs étaient systématiquement plus performants en termes d’efficacité et de temps de réaction que les novices pour discriminer la direction du mouvement biologique lors d’un exercice spécifique de soccer (tir) mais également lors d’une action issue du quotidien (marche). Ces résultats signifient que les athlètes possèdent une meilleure capacité à percevoir les mouvements biologiques humains effectués par les autres. La pratique du soccer semble donc conférer un avantage fondamental qui va au-delà des fonctions spécifiques à la pratique d’un sport. Ces découvertes sont à mettre en parallèle avec la performance exceptionnelle des athlètes dans le traitement de scènes visuelles dynamiques et également dénuées de contexte sportif. Des joueurs de soccer ont surpassé des novices dans le test de 3D-MOT qui consiste à suivre des cibles en mouvement et stimule les capacités perceptivo-cognitives. Leur vitesse de suivi visuel ainsi que leur faculté d’apprentissage étaient supérieures. Ces résultats confirmaient des données obtenues précédemment chez des sportifs. Le 3D-MOT est un test de poursuite attentionnelle qui stimule le traitement actif de l’information visuelle dynamique. En particulier, l’attention sélective, dynamique et soutenue ainsi que la mémoire de travail. Cet outil peut être utilisé pour entraîner les fonctions perceptivo-cognitives des athlètes. Des joueurs de soccer entraînés au 3D-MOT durant 30 sessions ont montré une amélioration de la prise de décision dans les passes de 15% sur le terrain comparés à des joueurs de groupes contrôles. Ces données démontrent pour la première fois un transfert perceptivo-cognitif du laboratoire au terrain suivant un entraînement perceptivo-cognitif non-contextuel au sport de l’athlète ciblé. Nos recherches aident à comprendre l’expertise des athlètes par l’approche spécifique et non-spécifique et présentent également les outils d’entraînements perceptivo-cognitifs, en particulier le 3D-MOT, pour améliorer la performance dans le sport de haut-niveau.

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By the means of a questionnaire the present work examines the attitudes among pupils between the 5th and 9th grade towards choosing French, Spanish or German as their third language. The main question to be answered is "What needs to be improved to raise the interest in choosing specifically German as their preferred third language?". The other questions posed are for example "Do they want to study a language at all?", "Which language do they want to study and why?" or "What motivates them to keep studying generally?". The results show a high motivation and that the most pupils have already decided for a specific language at the middle of the 5th grade. Family and friends play a crucial role in choosing their language in combination with other factors such as the experiences of visiting countries or settings where the target language is used. To raise the popularity of German as the chosen language is not a short time project. More variation in teaching and real contact with German people, for instance language trips, needs to be done or improved. Nearly all of the pupils want to use modern techniques like chat or video conversations instead of just reading a text book.

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Ausgehend von einer allgemeinen Definition beschreibt der Beitrag zentrale Merkmale und Anforderungen Kompetenzorientierten Unterrichts sowie dessen bildungspolitische und lerntheoretische Hintergründe. Diese allgemeindidaktische Perspektive wird mit den Bedingungen und Zielsetzungen im Lernbereich Globale Entwicklung verknüpft. Die Möglichkeiten und Herausforderungen, die sich bei der Umsetzung Kompetenzorientierten Unterrichts zeigen, werden anhand eines Unterrichtsbeispiels aus dem Lernbereich Globale Entwicklung ausgeführt. Hierbei liegt der Fokus auf komplexen Problemen als Ausgangspunkt, auf der Ermöglichung von Selbststeuerung durch die Schüler/-innen sowie auf der Erarbeitung reichhaltiger Ergebnisse, die eine sinnhafte Kommunikation und Vernetzung von Wissen erfordern. (DIPF/Orig.)

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Within the public sector great change efforts are currently made to meet future challenges. In the area of health care, change initiatives are implemented to enhance quality and efficiency. To this end, a lean change programme is being widely introduced in Sweden as well as internationally. The overriding aim of this study is to increase knowledge of what happens when change programmes, CP, such as lean are implemented in a healthcare organisation, HCO. Previous research has shown that the main obstacle to implementing CP in HCO:s is their complexity. However, the complexity has often been reduced, as different factors such as management, professions, organisation and control have been studied separately. To fully capture the complexity of the HCO the Actor Network Theory, ANT, was used in this study. In line with ANT, introducing lean can be described in terms of a translation process in which human and non-human actors are woven into a network. This approach allows for the incorporation of various factors in the study of a change process in a complex organisation. Drawing on ANT, this thesis explores how network constructions enable or impede change programmes. The approach is based on ethnographic monitoring of the implementation of lean in the Värmland county council public healthcare organisation. As a result of the holistic perspective, the study provides detailed descriptions of how complexity impacts on the implementation. It displays the relations enabling or impeding the implementation of CP and the methods actors use to establish and defend the relations. The contribution of the study is threefold. Empirically, the study monitors a HCO aiming to implement full-scale lean as philosophy, principle and tool. Methodologically, the study evaluates ANT as a methodological theory to study CP in a HCO. Finally, the domain-specific contribution of the study is its identification of the relations and methods that impact on lean deployment. 

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Introduction. Research design should take into account both (a) the specific nature of the object under scrutiny, and (b) approaches to its study in the past. This is to ensure that informed decisions are made regarding research design in future empirical studies. Here these factors are taken into account with reference to methodological choice for a doctoral study on tacit knowledge sharing, and the extent to tacit knowledge sharing may be facilitated by online tools. The larger study responds to calls for the two domains of knowledge management and human information behaviour to be considered together in terms of their research approaches and theory development. Method. Relevant literature – both domain-specific (knowledge management) and general (research methods in social science) - was identified and analysed to identify the most appropriate approaches for an empirical study of tacit knowledge sharing. Analysis. The analysis shows that there are a number of challenges associated with studying an intangible entity such as tacit knowledge. Quantitative, qualitative and mixed methods have been adopted in prior work on this theme, each with their own strengths and weaknesses. Results. The analysis has informed a decision to adopt a research approach that deploys mixed methods for an inductive case study to extend knowledge of the influence of online tools on tacit knowledge sharing. Conclusion. This work intends to open the debate on methodological choice and routes to implementation for studies that are subject to practical constraints imposed by the context in which they are situated.

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Pour être performant au plus haut niveau, les athlètes doivent posséder une capacité perceptivo-cognitive supérieure à la moyenne. Cette faculté, reflétée sur le terrain par la vision et l’intelligence de jeu des sportifs, permet d’extraire l’information clé de la scène visuelle. La science du sport a depuis longtemps observé l’expertise perceptivo-cognitive au sein de l’environnement sportif propre aux athlètes. Récemment, des études ont rapporté que l’expertise pouvait également se refléter hors de ce contexte, lors d’activités du quotidien par exemple. De plus, les récentes théories entourant la capacité plastique du cerveau ont amené les chercheurs à développer des outils pour entraîner les capacités perceptivo-cognitives des athlètes afin de les rendre plus performants sur le terrain. Ces méthodes sont la plupart du temps contextuelles à la discipline visée. Cependant, un nouvel outil d’entraînement perceptivo-cognitif, nommé 3-Dimensional Multiple Object Tracking (3D-MOT) et dénué de contexte sportif, a récemment vu le jour et a fait l’objet de nos recherches. Un de nos objectifs visait à mettre en évidence l’expertise perceptivo-cognitive spécifique et non-spécifique chez des athlètes lors d’une même étude. Nous avons évalué la perception du mouvement biologique chez des joueurs de soccer et des non-athlètes dans une salle de réalité virtuelle. Les sportifs étaient systématiquement plus performants en termes d’efficacité et de temps de réaction que les novices pour discriminer la direction du mouvement biologique lors d’un exercice spécifique de soccer (tir) mais également lors d’une action issue du quotidien (marche). Ces résultats signifient que les athlètes possèdent une meilleure capacité à percevoir les mouvements biologiques humains effectués par les autres. La pratique du soccer semble donc conférer un avantage fondamental qui va au-delà des fonctions spécifiques à la pratique d’un sport. Ces découvertes sont à mettre en parallèle avec la performance exceptionnelle des athlètes dans le traitement de scènes visuelles dynamiques et également dénuées de contexte sportif. Des joueurs de soccer ont surpassé des novices dans le test de 3D-MOT qui consiste à suivre des cibles en mouvement et stimule les capacités perceptivo-cognitives. Leur vitesse de suivi visuel ainsi que leur faculté d’apprentissage étaient supérieures. Ces résultats confirmaient des données obtenues précédemment chez des sportifs. Le 3D-MOT est un test de poursuite attentionnelle qui stimule le traitement actif de l’information visuelle dynamique. En particulier, l’attention sélective, dynamique et soutenue ainsi que la mémoire de travail. Cet outil peut être utilisé pour entraîner les fonctions perceptivo-cognitives des athlètes. Des joueurs de soccer entraînés au 3D-MOT durant 30 sessions ont montré une amélioration de la prise de décision dans les passes de 15% sur le terrain comparés à des joueurs de groupes contrôles. Ces données démontrent pour la première fois un transfert perceptivo-cognitif du laboratoire au terrain suivant un entraînement perceptivo-cognitif non-contextuel au sport de l’athlète ciblé. Nos recherches aident à comprendre l’expertise des athlètes par l’approche spécifique et non-spécifique et présentent également les outils d’entraînements perceptivo-cognitifs, en particulier le 3D-MOT, pour améliorer la performance dans le sport de haut-niveau.

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In this work a system of autonomous agents engaged in cyclic pursuit (under constant bearing (CB) strategy) is considered, for which one informed agent (the leader) also senses and responds to a stationary beacon. Building on the framework proposed in a previous work on beacon-referenced cyclic pursuit, necessary and suffi- cient conditions for the existence of circling equilibria in a system with one informed agent are derived, with discussion of stability and performance. In a physical testbed, the leader (robot) is equipped with a sound sensing apparatus composed of a real time embedded system, estimating direction of arrival of sound by an Interaural Level and Phase Difference Algorithm, using empirically determined phase and level signatures, and breaking front-back ambiguity with appropriate sensor placement. Furthermore a simple framework for implementing and evaluating the performance of control laws with the Robot Operating System (ROS) is proposed, demonstrated, and discussed.

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This study tested whether the gender intensification hypothesis applies to relations between multiple domain-specific self-concept facets and self-esteem. This hypothesis predicts gender-stereotypic differences in these relations and assumes they intensify with age. Furthermore, knowledge about gender-related or age-related differences in self-concept-self-esteem relations might provide valuable knowledge for designing effective self-esteem enhancement interventions. We investigated grade and gender differences in the relations between domain-specific self-concept facets and self-esteem within a sample of 1958 German students in Grades 3 to 6. Results indicated no difference in the self-concept - self-esteem relations between the subsamples of third and fourth graders and fifth and sixth graders or between boys and girls. These relations also did not differ between boys and girls in the subsamples of third and fourth graders and fifth and sixth graders. These results suggest self-concept-self-esteem relations to be invariant across grade levels and gender and thus did not support the gender intensification hypothesis.

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Critical thinking in learners is a goal of educators and professional organizations in nursing as well as other professions. However, few studies in nursing have examined the role of the important individual difference factors topic knowledge, individual interest, and general relational reasoning strategies in predicting critical thinking. In addition, most previous studies have used domain-general, standardized measures, with inconsistent results. Moreover, few studies have investigated critical thinking across multiple levels of experience. The major purpose of this study was to examine the degree to which topic knowledge, individual interest, and relational reasoning predict critical thinking in maternity nurses. For this study, 182 maternity nurses were recruited from national nursing listservs explicitly chosen to capture multiple levels of experience from prelicensure to very experienced nurses. The three independent measures included a domain-specific Topic Knowledge Assessment (TKA), consisting of 24 short-answer questions, a Professed and Engaged Interest Measure (PEIM), with 20 questions indicating level of interest and engagement in maternity nursing topics and activities, and the Test of Relational Reasoning (TORR), a graphical selected response measure with 32 items organized in scales corresponding to four forms of relational reasoning: analogy, anomaly, antithesis, and antinomy. The dependent measure was the Critical Thinking Task in Maternity Nursing (CT2MN), composed of a clinical case study providing cues with follow-up questions relating to nursing care. These questions align with the cognitive processes identified in a commonly-used definition of critical thinking in nursing. Reliable coding schemes for the measures were developed for this study. Key findings included a significant correlation between topic knowledge and individual interest. Further, the three individual difference factors explained a significant proportion of the variance in critical thinking with a large effect size. While topic knowledge was the strongest predictor of critical thinking performance, individual interest had a moderate significant effect, and relational reasoning had a small but significant effect. The findings suggest that these individual difference factors should be included in future studies of critical thinking in nursing. Implications for nursing education, research, and practice are discussed.

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Reconfigurable platforms are a promising technology that offers an interesting trade-off between flexibility and performance, which many recent embedded system applications demand, especially in fields such as multimedia processing. These applications typically involve multiple ad-hoc tasks for hardware acceleration, which are usually represented using formalisms such as Data Flow Diagrams (DFDs), Data Flow Graphs (DFGs), Control and Data Flow Graphs (CDFGs) or Petri Nets. However, none of these models is able to capture at the same time the pipeline behavior between tasks (that therefore can coexist in order to minimize the application execution time), their communication patterns, and their data dependencies. This paper proves that the knowledge of all this information can be effectively exploited to reduce the resource requirements and the timing performance of modern reconfigurable systems, where a set of hardware accelerators is used to support the computation. For this purpose, this paper proposes a novel task representation model, named Temporal Constrained Data Flow Diagram (TCDFD), which includes all this information. This paper also presents a mapping-scheduling algorithm that is able to take advantage of the new TCDFD model. It aims at minimizing the dynamic reconfiguration overhead while meeting the communication requirements among the tasks. Experimental results show that the presented approach achieves up to 75% of resources saving and up to 89% of reconfiguration overhead reduction with respect to other state-of-the-art techniques for reconfigurable platforms.

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In this report, we develop an intelligent adaptive neuro-fuzzy controller by using adaptive neuro fuzzy inference system (ANFIS) techniques. We begin by starting with a standard proportional-derivative (PD) controller and use the PD controller data to train the ANFIS system to develop a fuzzy controller. We then propose and validate a method to implement this control strategy on commercial off-the-shelf (COTS) hardware. An analysis is made into the choice of filters for attitude estimation. These choices are limited by the complexity of the filter and the computing ability and memory constraints of the micro-controller. Simplified Kalman filters are found to be good at estimation of attitude given the above constraints. Using model based design techniques, the models are implemented on an embedded system. This enables the deployment of fuzzy controllers on enthusiast-grade controllers. We evaluate the feasibility of the proposed control strategy in a model-in-the-loop simulation. We then propose a rapid prototyping strategy, allowing us to deploy these control algorithms on a system consisting of a combination of an ARM-based microcontroller and two Arduino-based controllers. We then use a combination of the code generation capabilities within MATLAB/Simulink in combination with multiple open-source projects in order to deploy code to an ARM CortexM4 based controller board. We also evaluate this strategy on an ARM-A8 based board, and a much less powerful Arduino based flight controller. We conclude by proving the feasibility of fuzzy controllers on Commercial-off the shelf (COTS) hardware, we also point out the limitations in the current hardware and make suggestions for hardware that we think would be better suited for memory heavy controllers.

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Traditional decision making research has often focused on one's ability to choose from a set of prefixed options, ignoring the process by which decision makers generate courses of action (i.e., options) in-situ (Klein, 1993). In complex and dynamic domains, this option generation process is particularly critical to understanding how successful decisions are made (Zsambok & Klein, 1997). When generating response options for oneself to pursue (i.e., during the intervention-phase of decision making) previous research has supported quick and intuitive heuristics, such as the Take-The-First heuristic (TTF; Johnson & Raab, 2003). When generating predictive options for others in the environment (i.e., during the assessment-phase of decision making), previous research has supported the situational-model-building process described by Long Term Working Memory theory (LTWM; see Ward, Ericsson, & Williams, 2013). In the first three experiments, the claims of TTF and LTWM are tested during assessment- and intervention-phase tasks in soccer. To test what other environmental constraints may dictate the use of these cognitive mechanisms, the claims of these models are also tested in the presence and absence of time pressure. In addition to understanding the option generation process, it is important that researchers in complex and dynamic domains also develop tools that can be used by `real-world' professionals. For this reason, three more experiments were conducted to evaluate the effectiveness of a new online assessment of perceptual-cognitive skill in soccer. This test differentiated between skill groups and predicted performance on a previously established test and predicted option generation behavior. The test also outperformed domain-general cognitive tests, but not a domain-specific knowledge test when predicting skill group membership. Implications for theory and training, and future directions for the development of applied tools are discussed.

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Esta investigación analiza el impacto del Programa de Alimentación Escolar en el trabajo infantil en Colombia a través de varias técnicas de evaluación de impacto que incluyen emparejamiento simple, emparejamiento genético y emparejamiento con reducción de sesgo. En particular, se encuentra que este programa disminuye la probabilidad de que los escolares trabajen alrededor de un 4%. Además, se explora que el trabajo infantil se reduce gracias a que el programa aumenta la seguridad alimentaria, lo que consecuentemente cambia las decisiones de los hogares y anula la carga laboral en los infantes. Son numerosos los avances en primera infancia llevados a cabo por el Estado, sin embargo, estos resultados sirven de base para construir un marco conceptual en el que se deben rescatar y promover las políticas públicas alimentarias en toda la edad escolar.

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Embedding intelligence in extreme edge devices allows distilling raw data acquired from sensors into actionable information, directly on IoT end-nodes. This computing paradigm, in which end-nodes no longer depend entirely on the Cloud, offers undeniable benefits, driving a large research area (TinyML) to deploy leading Machine Learning (ML) algorithms on micro-controller class of devices. To fit the limited memory storage capability of these tiny platforms, full-precision Deep Neural Networks (DNNs) are compressed by representing their data down to byte and sub-byte formats, in the integer domain. However, the current generation of micro-controller systems can barely cope with the computing requirements of QNNs. This thesis tackles the challenge from many perspectives, presenting solutions both at software and hardware levels, exploiting parallelism, heterogeneity and software programmability to guarantee high flexibility and high energy-performance proportionality. The first contribution, PULP-NN, is an optimized software computing library for QNN inference on parallel ultra-low-power (PULP) clusters of RISC-V processors, showing one order of magnitude improvements in performance and energy efficiency, compared to current State-of-the-Art (SoA) STM32 micro-controller systems (MCUs) based on ARM Cortex-M cores. The second contribution is XpulpNN, a set of RISC-V domain specific instruction set architecture (ISA) extensions to deal with sub-byte integer arithmetic computation. The solution, including the ISA extensions and the micro-architecture to support them, achieves energy efficiency comparable with dedicated DNN accelerators and surpasses the efficiency of SoA ARM Cortex-M based MCUs, such as the low-end STM32M4 and the high-end STM32H7 devices, by up to three orders of magnitude. To overcome the Von Neumann bottleneck while guaranteeing the highest flexibility, the final contribution integrates an Analog In-Memory Computing accelerator into the PULP cluster, creating a fully programmable heterogeneous fabric that demonstrates end-to-end inference capabilities of SoA MobileNetV2 models, showing two orders of magnitude performance improvements over current SoA analog/digital solutions.

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Spectral sensors are a wide class of devices that are extremely useful for detecting essential information of the environment and materials with high degree of selectivity. Recently, they have achieved high degrees of integration and low implementation cost to be suited for fast, small, and non-invasive monitoring systems. However, the useful information is hidden in spectra and it is difficult to decode. So, mathematical algorithms are needed to infer the value of the variables of interest from the acquired data. Between the different families of predictive modeling, Principal Component Analysis and the techniques stemmed from it can provide very good performances, as well as small computational and memory requirements. For these reasons, they allow the implementation of the prediction even in embedded and autonomous devices. In this thesis, I will present 4 practical applications of these algorithms to the prediction of different variables: moisture of soil, moisture of concrete, freshness of anchovies/sardines, and concentration of gasses. In all of these cases, the workflow will be the same. Initially, an acquisition campaign was performed to acquire both spectra and the variables of interest from samples. Then these data are used as input for the creation of the prediction models, to solve both classification and regression problems. From these models, an array of calibration coefficients is derived and used for the implementation of the prediction in an embedded system. The presented results will show that this workflow was successfully applied to very different scientific fields, obtaining autonomous and non-invasive devices able to predict the value of physical parameters of choice from new spectral acquisitions.