918 resultados para Dynamic Learning Capabilities
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Certain environments can inhibit learning and stifle enthusiasm, while others enhance learning or stimulate curiosity. Furthermore, in a world where technological change is accelerating we could ask how might architecture connect resource abundant and resource scarce innovation environments? Innovation environments developed out of necessity within urban villages and those developed with high intention and expectation within more institutionalized settings share a framework of opportunity for addressing change through learning and education. This thesis investigates formal and informal learning environments and how architecture can stimulate curiosity, enrich learning, create common ground, and expand access to education. The reason for this thesis exploration is to better understand how architects might design inclusive environments that bring people together to build sustainable infrastructure encouraging innovation and adaptation to change for years to come. The context of this thesis is largely based on Colin McFarlane’s theory that the “city is an assemblage for learning” The socio-spatial perspective in urbanism, considers how built infrastructure and society interact. Through the urban realm, inhabitants learn to negotiate people, space, politics, and resources affecting their daily lives. The city is therefore a dynamic field of emergent possibility. This thesis uses the city as a lens through which the boundaries between informal and formal logics as well as the public and private might be blurred. Through analytical processes I have examined the environmental devices and assemblage of factors that consistently provide conditions through which learning may thrive. These parameters that make a creative space significant can help suggest the design of common ground environments through which innovation is catalyzed.
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In this thesis, I studied self-efficacy in the learning of English and Swedish in Finland. The theory of self-efficacy, which was created by Albert Bandura, suggests that the beliefs a person has of his or her capabilities in a certain task affect the person’s performance in the task. My aim was to study whether there are differences in self-efficacy beliefs between the learners of English and Swedish, and whether these beliefs correlate with the performance in the language in question. My hypotheses were that the learners of English have higher self-efficacy beliefs than the learners of Swedish and that self-efficacy beliefs correlate with language performance. The study was quantitative, and it consisted of a self-efficacy questionnaire and a language test which were distributed to students of English and Swedish in an upper secondary school in Rovaniemi. The study was answered by 137 students, of whom 93 were learners of English and 44 were learners of Swedish. The results indicated that the learners of English had a higher sense of efficacy than the learners of Swedish. The analysis proved that there was a significant correlation between English students’ self-efficacy and their performance in the language measured by the test and the grades. In addition, a significant correlation existed between Swedish students’ self-efficacy and their grades. However, there was no correlation between the Swedish students’ self-efficacy and their test results. The difference in the self-efficacy beliefs of the two language groups indicates that people in Finland are more confident in using English than Swedish, which also implies that English is more valued in Finnish society than Swedish. It is important to acknowledge the lower self-efficacy beliefs in Swedish because various studies have proven that self-efficacy affects academic achievement. As a suggestion for further research, the self-efficacy beliefs of different language groups could be compared in a qualitative study in order to understand the development of self-efficacy more profoundly.
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This work presents a study about a the Baars-Franklin architecture, which defines a model of computational consciousness, and use it in a mobile robot navigation task. The insertion of mobile robots in dynamic environments carries a high complexity in navigation tasks, in order to deal with the constant environment changes, it is essential that the robot can adapt to this dynamism. The approach utilized in this work is to make the execution of these tasks closer to how human beings react to the same conditions by means of a model of computational consci-ousness. The LIDA architecture (Learning Intelligent Distribution Agent) is a cognitive system that seeks tomodel some of the human cognitive aspects, from low-level perceptions to decision making, as well as attention mechanism and episodic memory. In the present work, a computa-tional implementation of the LIDA architecture was evaluated by means of a case study, aiming to evaluate the capabilities of a cognitive approach to navigation of a mobile robot in dynamic and unknown environments, using experiments both with virtual environments (simulation) and a real robot in a realistic environment. This study concluded that it is possible to obtain benefits by using conscious cognitive models in mobile robot navigation tasks, presenting the positive and negative aspects of this approach.
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The generation of functional, vascularized tissues is a key challenge for the field of tissue engineering. Before clinical implantations of tissue engineered bone constructs can succeed, in vitro fabrication needs to address limitations in large-scale tissue development, including controlled osteogenesis and an inadequate vasculature network to prevent necrosis of large constructs. The tubular perfusion system (TPS) bioreactor is an effective culturing method to augment osteogenic differentiation and maintain viability of human mesenchymal stem cell (hMSC)-seeded scaffolds while they are developed in vitro. To further enhance this process, we developed a novel osteogenic growth factors delivery system for dynamically cultured hMSCs using microparticles encapsulated in three-dimensional alginate scaffolds. In light of this increased differentiation, we characterized the endogenous cytokine distribution throughout the TPS bioreactor. An advantageous effect in the ‘outlet’ portion of the uniaxial growth chamber was discovered due to the system’s downstream circulation and the unique modular aspect of the scaffolds. This unique trait allowed us to carefully tune the differentiation behavior of specific cell populations. We applied the knowledge gained from the growth profile of the TPS bioreactor to culture a high-volume bone composite in a 3D-printed femur mold. This resulted in a tissue engineered bone construct with a volume of 200cm3, a 20-fold increase over previously reported sizes. We demonstrated high viability of the cultured cells throughout the culture period as well as early signs of osteogenic differentiation. Taking one step closer toward a viable implant and minimize tissue necrosis after implantation, we designed a composite construct by coculturing endothelial cells (ECs) and differentiating hMSCs, encouraging prevascularization and anastomosis of the graft with the host vasculature. We discovered the necessity of cell to cell proximity between the two cell types as well as preference for the natural cell binding capabilities of hydrogels like collagen. Notably, the results suggested increased osteogenic and angiogenic potential of the encapsulated cells when dynamically cultured in the TPS bioreactor, suggesting a synergistic effect between coculture and applied shear stress. This work highlights the feasibility of fabricating a high-volume, prevascularized tissue engineered bone construct for the regeneration of a critical size defect.
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ICEMST 2014 INTERNATIONAL CONFERENCE ON EDUCATION IN MATHEMATICS, SCIENCE & TECHNOLOGY PROCEEDING BOOK (pp.865-869). Disponível em http://www.2014.icemst.com/
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Knowledge is one of the most important assets for surviving in the modern business environment. The effective management of that asset mandates continuous adaptation by organizations, and requires employees to strive to improve the company's work processes. Organizations attempt to coordinate their unique knowledge with traditional means as well as in new and distinct ways, and to transform them into innovative resources better than those of their competitors. As a result, how to manage the knowledge asset has become a critical issue for modern organizations, and knowledge management is considered the most feasible solution. Knowledge management is a multidimensional process that identifies, acquires, develops, distributes, utilizes, and stores knowledge. However, many related studies focus only on fragmented or limited knowledge-management perspectives. In order to make knowledge management more effective, it is important to identify the qualitative and quantitative issues that are the foundation of the challenge of effective knowledge management in organizations. The main purpose of this study was to integrate the fragmented knowledge management perspectives into the holistic framework, which includes knowledge infrastructure capability (technology, structure, and culture) and knowledge process capability (acquisition, conversion, application, and protection), based on Gold's (2001) study. Additionally, because the effect of incentives ̶̶ which is widely acknowledged as a prime motivator in facilitating the knowledge management process ̶̶ was missing in the original framework, this study included the importance of incentives in the knowledge management framework. This study also identified the relationship of organizational performance from the standpoint of the Balanced Scorecard, which includes the customer-related, internal business process, learning & growth, and perceptual financial aspects of organizational performance in the Korean business context. Moreover, this study identified the relationship with the objective financial performance by calculating the Tobin's q ratio. Lastly, this study compared the group differences between larger and smaller organizations, and manufacturing and nonmanufacturing firms in the study of knowledge management. Since this study was conducted in Korea, the original instrument was translated into Korean through the back translation technique. A confirmatory factor analysis (CFA) was used to examine the validity and reliability of the instrument. To identify the relationship between knowledge management capabilities and organizational performance, structural equation modeling (SEM) and multiple regression analysis were conducted. A Student's t test was conducted to examine the mean differences. The results of this study indicated that there is a positive relationship between effective knowledge management and organizational performance. However, no empirical evidence was found to suggest that knowledge management capabilities are linked to the objective financial performance, which remains a topic for future review. Additionally, findings showed that knowledge management is affected by organization's size, but not by type of organization. The results of this study are valuable in establishing a valid and reliable survey instrument, as well as in providing strong evidence that knowledge management capabilities are essential to improving organizational performance currently and making important recommendations for future research.
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Motor learning is based on motor perception and emergent perceptual-motor representations. A lot of behavioral research is related to single perceptual modalities but during last two decades the contribution of multimodal perception on motor behavior was discovered more and more. A growing number of studies indicates an enhanced impact of multimodal stimuli on motor perception, motor control and motor learning in terms of better precision and higher reliability of the related actions. Behavioral research is supported by neurophysiological data, revealing that multisensory integration supports motor control and learning. But the overwhelming part of both research lines is dedicated to basic research. Besides research in the domains of music, dance and motor rehabilitation, there is almost no evidence for enhanced effectiveness of multisensory information on learning of gross motor skills. To reduce this gap, movement sonification is used here in applied research on motor learning in sports. Based on the current knowledge on the multimodal organization of the perceptual system, we generate additional real-time movement information being suitable for integration with perceptual feedback streams of visual and proprioceptive modality. With ongoing training, synchronously processed auditory information should be initially integrated into the emerging internal models, enhancing the efficacy of motor learning. This is achieved by a direct mapping of kinematic and dynamic motion parameters to electronic sounds, resulting in continuous auditory and convergent audiovisual or audio-proprioceptive stimulus arrays. In sharp contrast to other approaches using acoustic information as error-feedback in motor learning settings, we try to generate additional movement information suitable for acceleration and enhancement of adequate sensorimotor representations and processible below the level of consciousness. In the experimental setting, participants were asked to learn a closed motor skill (technique acquisition of indoor rowing). One group was treated with visual information and two groups with audiovisual information (sonification vs. natural sounds). For all three groups learning became evident and remained stable. Participants treated with additional movement sonification showed better performance compared to both other groups. Results indicate that movement sonification enhances motor learning of a complex gross motor skill-even exceeding usually expected acoustic rhythmic effects on motor learning.
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The size of online image datasets is constantly increasing. Considering an image dataset with millions of images, image retrieval becomes a seemingly intractable problem for exhaustive similarity search algorithms. Hashing methods, which encodes high-dimensional descriptors into compact binary strings, have become very popular because of their high efficiency in search and storage capacity. In the first part, we propose a multimodal retrieval method based on latent feature models. The procedure consists of a nonparametric Bayesian framework for learning underlying semantically meaningful abstract features in a multimodal dataset, a probabilistic retrieval model that allows cross-modal queries and an extension model for relevance feedback. In the second part, we focus on supervised hashing with kernels. We describe a flexible hashing procedure that treats binary codes and pairwise semantic similarity as latent and observed variables, respectively, in a probabilistic model based on Gaussian processes for binary classification. We present a scalable inference algorithm with the sparse pseudo-input Gaussian process (SPGP) model and distributed computing. In the last part, we define an incremental hashing strategy for dynamic databases where new images are added to the databases frequently. The method is based on a two-stage classification framework using binary and multi-class SVMs. The proposed method also enforces balance in binary codes by an imbalance penalty to obtain higher quality binary codes. We learn hash functions by an efficient algorithm where the NP-hard problem of finding optimal binary codes is solved via cyclic coordinate descent and SVMs are trained in a parallelized incremental manner. For modifications like adding images from an unseen class, we propose an incremental procedure for effective and efficient updates to the previous hash functions. Experiments on three large-scale image datasets demonstrate that the incremental strategy is capable of efficiently updating hash functions to the same retrieval performance as hashing from scratch.
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Nowadays the organizational scenario is changing in several aspects that affect organization commitment. Team learning construct has emerged as a tool to deal with these changes and the dynamic nature of this situation. Although team learning has acquired importance in recent years, instruments to measure team learning should be developed. The aim of this paper is to develop and validate a team learning scale, the Team Learning Questionnaire, attending to four dimensions of team learning: Continued Improvement Seeking, Dialogue Promotion and Open Communication, Collaborative Learning, and Strategic and Proactive Leadership that Promote Learning. Results provide evidence of the reliability and validity of the scale.
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El presente estudio analiza las percepciones y actitudes que tienen los adultos mayores de la ciudad de Cuenca, Ecuador hacia el aprendizaje del inglés. Un total de 151 adultos mayores (con edad promedio de 70.3 años) respondió a un cuestionario con 50 ítems. Se llevó a cabo análisis factoriales, de regresión múltiple y cluster con el propósito de definir las dimensiones subyacentes en las percepciones, motivaciones y ambiciones de los adultos mayores para aprender un idioma extranjero, y su relación con las características sociodemográficas de los participantes. Los resultados señalan que el interés por estudiar un idioma extranjero está basado en la percepción de que aquello mejora la interacción social de las personas, su desarrollo personal, el funcionamiento y mantenimiento de la mente y memoria, y que activa y vuelve su vida más dinámica. Los resultados además revelaron que la principal motivación de los participantes para tomar un curso de inglés está relacionada con el potencial de usar este idioma en la vida diaria y el de leer profusamente en esa lengua extranjera. La duración del curso y la obtención de un certificado fueron factores determinantes que permitieron agrupar a los participantes en función de sus preferencias en lo que respecta al diseño práctico de un curso de inglés. Adicionalmente, la edad y el nivel de instrucción fueron variables determinantes de motivación que influyeron en la mayor parte de las respuestas dadas por los participantes.
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This master dissertation presents the study and implementation of inteligent algorithms to monitor the measurement of sensors involved in natural gas custody transfer processes. To create these algoritmhs Artificial Neural Networks are investigated because they have some particular properties, such as: learning, adaptation, prediction. A neural predictor is developed to reproduce the sensor output dynamic behavior, in such a way that its output is compared to the real sensor output. A recurrent neural network is used for this purpose, because of its ability to deal with dynamic information. The real sensor output and the estimated predictor output work as the basis for the creation of possible sensor fault detection and diagnosis strategies. Two competitive neural network architectures are investigated and their capabilities are used to classify different kinds of faults. The prediction algorithm and the fault detection classification strategies, as well as the obtained results, are presented
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Technologies for Big Data and Data Science are receiving increasing research interest nowadays. This paper introduces the prototyping architecture of a tool aimed to solve Big Data Optimization problems. Our tool combines the jMetal framework for multi-objective optimization with Apache Spark, a technology that is gaining momentum. In particular, we make use of the streaming facilities of Spark to feed an optimization problem with data from different sources. We demonstrate the use of our tool by solving a dynamic bi-objective instance of the Traveling Salesman Problem (TSP) based on near real-time traffic data from New York City, which is updated several times per minute. Our experiment shows that both jMetal and Spark can be integrated providing a software platform to deal with dynamic multi-optimization problems.
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This study took place at one of the intercultural universities (IUs) of Mexico that serve primarily indigenous students. The IUs are pioneers in higher education despite their numerous challenges (Bertely, 1998; Dietz, 2008; Pineda & Landorf, 2010; Schmelkes, 2009). To overcome educational inequalities among their students (Ahuja, Berumen, Casillas, Crispín, Delgado et al., 2004; Schmelkes, 2009), the IUs have embraced performance-based assessment (PBA; Casillas & Santini, 2006). PBA allows a shared model of power and control related to learning and evaluation (Anderson, 1998). While conducting a review on PBA strategies of the IUs, the researcher did not find a PBA instrument with valid and reliable estimates. The purpose of this study was to develop a process to create a PBA instrument, an analytic general rubric, with acceptable validity and reliability estimates to assess students’ attainment of competencies in one of the IU’s majors, Intercultural Development Management. The Human Capabilities Approach (HCA) was the theoretical framework and a sequential mixed method (Creswell, 2003; Teddlie & Tashakkori, 2009) was the research design. IU participants created a rubric during two focus groups, and seven Spanish-speaking professors in Mexico and the US piloted using students’ research projects. The evidence that demonstrates the attainment of competencies at the IU is a complex set of actual, potential and/or desired performances or achievements, also conceptualized as “functional capabilities” (FCs; Walker, 2008), that can be used to develop a rubric. Results indicate that the rubric’s validity and reliability estimates reached acceptable estimates of 80% agreement, surpassing minimum requirements (Newman, Newman, & Newman, 2011). Implications for practice involve the use of PBA within a formative assessment framework, and dynamic inclusion of constituencies. Recommendations for further research include introducing this study’s instrument-development process to other IUs, conducting parallel mixed design studies exploring the intersection between HCA and assessment, and conducting a case study exploring assessment in intercultural settings. Education articulated through the HCA empowers students (Unterhalter & Brighouse, 2007; Walker, 2008). This study aimed to contribute to the quality of student learning assessment at the IUs by providing a participatory process to develop a PBA instrument.
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Motivation should be seen as a very important factor in the learning process. The motivated student has the inner strength to learn, to discover and capitalize on capabilities, to improve academic performance and to adapt to the demands of the school context. Contextual factors like the psychological sense of school membership may be also especially important to students’ classroom engagement, their motivation and learning success. So with this study we intend to examine how the sense of school belonging and intrinsic motivation influences perceived learning.A structural model reveals that the negative sense of school belonging has a negative impact on intrinsic motivation and on perceived learning. In turn, intrinsic motivation positively and significantly influences perceived learning in the course.
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Integration, inclusion, and equity constitute fundamental dimensions of democracy in post-World War II societies and their institutions. The study presented here reports upon the ways in which individuals and institutions both use and account for the roles that technologies, including ICT, play in disabling and enabling access for learning in higher education for all. Technological innovations during the 20th and 21st centuries, including ICT, have been heralded as holding significant promise for revolutionizing issues of access in societal institutions like schools, healthcare services, etc. (at least in the global North). Taking a socially oriented perspective, the study presented in this paper focuses on an ethnographically framed analysis of two datasets that critically explores the role that technologies, including ICT, play in higher education for individuals who are “differently abled” and who constitute a variation on a continuum of capabilities. Functionality as a dimension of everyday life in higher education in the 21st century is explored through the analysis of (i) case studies of two “differently abled” students in Sweden and (ii) current support services at universities in Sweden. The findings make visible the work that institutions and their members do through analyses of the organization of time and space and the use of technologies in institutional settings against the backdrop of individuals’ accountings and life trajectories. This study also highlights the relevance of multi-scale data analyses for revisiting the ways in which identity positions become framed or understood within higher education.