893 resultados para mapas estratégicos


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Repertorio geral alfabetico da Novissima Refórma Judiciaria.

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Reprinted from Retana's Archivo del bibliófilo filipino, t. 3, p. 443-497.

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Fil: Merino, Gabriel Esteban. Universidad Nacional de La Plata. Facultad de Humanidades y Ciencias de la Educación; Argentina.

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Fil: Merino, Gabriel Esteban. Universidad Nacional de La Plata. Facultad de Humanidades y Ciencias de la Educación; Argentina.

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Se presenta en este trabajo una aproximación metodológica al estudio de uso de revistas por parte de los investigadores del Centro de Investigaciones Opticas. Integrando la técnica de Análisis de Citaciones y de Análisis de Redes Sociales se realiza la construcción de mapas con gran capacidad de síntesis de información compleja. Se estima que su elaboración contribuiría con información valiosa a la hora de pensar la distribución equitativa de recursos económicos para compra de títulos

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La mejora de las capacidades de búsqueda y de las interfaces de los OPACs sigue siendo uno de los principales desafíos para las bibliotecas, especialmente en lo que respecta al acceso por materias. Las interfaces visuales pueden ser una alternativa para facilitar la recuperación. El objetivo del presente trabajo es explorar si la combinación de técnicas de análisis de co-términos y de redes sociales resulta ser una metodología válida para la generación de mapas temáticos de la colección. La principal conclusión es que el método es válido, y que los mapas obtenidos podrían servir tanto como una alternativa de interfaz visual para el acceso por materias, como también para detectar problemas en los criterios de indización, y contribuir a la mejora de la calidad de la descripción temática del conjunto documental

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When combining remote sensing imagery with statistical classifiers to obtain categorical thematic maps it is not usual to provide data about the spatial distribution of the error and uncertainty of the resulting maps. This paper describes, in the context of GeoViQua FP7 project, feasible approaches for methods based on several steps such as hybrid classifiers. Both for “per pixel” and “per polygon” strategies, the proposal is based on the use of the available ground truth, which is used to properly model the spatial distribution of the errors. Results allow mapping the classification success with a very high level of reliability (R2>0,94), providing users a sound knowledge of the accuracy at every area of the map.

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BACKGROUND: Among the wide range of skills displayed by a medical doctor is undoubtedly the need to use cohesive and well grounded clinical reasoning in order for medical care to be indeed effective. It is in this respect that conceptual maps emerge; these are a methodological innovation that allows a comprehensive, panoramic and associative outlook of theoretical content, making it more practical and applicable to the reality of clinical observation. Promoting learning, learning resources and a feedback system between professor and students, as well as assessing and monitoring the performance of students during their academic training, are the main features of this tool. OBJETIVE: Assess the use of conceptual maps as a teaching-learning tool in the training of undergraduate medical students at Universidade Federal do Rio Grande do Norte (UFRN). METHODOLOGY: Interventional, randomized, cross-sectional study conducted with students from the 3rd and 5th periods of the medical course at UFRN, during the second semester of 2014, totaling 86 participants, divided into two groups: GI (intervention – clinical case resolution with a conceptual map) and GII (control – clinical case resolution without a conceptual map) in each period. RESULTS: The use of conceptual maps to teach liver failure syndrome resulted in a statistically significant cognitive gain for G1 students from the 5th period (GI: 6.8±1.6 and 8.0±1.5, p = 0.024; GII: 7.2±2.1 and 8.0±1.7, p = 0.125, pre and post-intermediate means, respectively), a result not observed in the period 3rd (GI: 7.7±1.3 and 8.0±1.4, p = 0.501; GII: 6.7±1.8 and 7.8±1.8; p=0.068, pre and post-intermediate means, respectively). Students in the 3 rd period gave better responses to the first clinical case, with a larger number of suitable concepts and crosslinks, when they used conceptual maps (GI: 91.3±13.15 and GII: 64.84±22.84, p=0,002). Students in the 5th period exhibited better clinical reasoning and more complete responses using the tool (p=0,01). Most of the students were not aware of the tool (53.8% from the 3rd period and 65.3% from the 5th period). Among those who knew about conceptual maps, most (59.3%) had only used them during high school, 14.8% had never used them and only seven students (25.9%) used them during the medical course. Analysis of open responses, obtained in process assessment showed clear satisfaction and enthusiasm with learning about the new tool, and frequent suggestions to use it at other moments in the course. Assessment of learning profile, using the VARK questionnaire, showed that most students from both periods exhibited a multimodal style. CONCLUSION: Despite their scant knowledge regarding the tool, good acceptability and understanding was observed in the study participants. The conceptual maps allowed cognitive gains, better responses and clinical reasoning in teaching liver failure syndrome to 5th period students.

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Nowadays, the amount of customers using sites for shopping is greatly increasing, mainly due to the easiness and rapidity of this way of consumption. The sites, differently from physical stores, can make anything available to customers. In this context, Recommender Systems (RS) have become indispensable to help consumers to find products that may possibly pleasant or be useful to them. These systems often use techniques of Collaborating Filtering (CF), whose main underlying idea is that products are recommended to a given user based on purchase information and evaluations of past, by a group of users similar to the user who is requesting recommendation. One of the main challenges faced by such a technique is the need of the user to provide some information about her preferences on products in order to get further recommendations from the system. When there are items that do not have ratings or that possess quite few ratings available, the recommender system performs poorly. This problem is known as new item cold-start. In this paper, we propose to investigate in what extent information on visual attention can help to produce more accurate recommendation models. We present a new CF strategy, called IKB-MS, that uses visual attention to characterize images and alleviate the new item cold-start problem. In order to validate this strategy, we created a clothing image database and we use three algorithms well known for the extraction of visual attention these images. An extensive set of experiments shows that our approach is efficient and outperforms state-of-the-art CF RS.