970 resultados para Learning Conditions


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Up to 15 people can participate in the game, which is supervised by a moderator. Households consisting of 1-5 people discuss options for diversification of household strategies. Aim of the game: By devising appropriate strategies, households seek to stand up to various types of events while improving their economic and social situation and, at the same time, taking account of ecological conditions. The annual General Community Meeting (GCM) provides an opportunity for households to create a general set-up at the local level that is more or less favourable to the strategies they are pursuing. The development of a community investment strategy, to be implemented by the GCM, and successful coordination between households will allow players to optimise their investments at the household level. The household who owns the most assets at the end of the game wins. Players participate very actively, as the game stimulates lively and interesting discussions. They find themselves confronted with different types of decision-making related to the reality of their daily lives. They explore different ways to model their own household strategies and discuss risks and opportunities. Reflections on the course of the game continually refer to the real-life situations of the participants.

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Three teams consisting of 2 to 5 persons each play the game. Each team represents a farm. Each team decides jointly on its strategy. In annual meetings in winter, the farm teams jointly discuss, evaluate and decide on how to proceed and actions to be taken. The farms make use of three different pasture areas (village pasture, intensive pasture and summer pasture) for grazing their livestock. The carrying capacity of each pasture area is different and varies according to the season. In each season, the farms have to decide on how many livestock units to graze on which pasture. Overgrazing and pasture degradation occur if the total number of livestock units exceeds the carrying capacity of a specific pasture area. Overgrazing results in a reduction of pasture productivity. To diversify and improve their livelihood strategy farms can make individual investments to increase productivity at the farm level, eg. in fodder production or in income generating activities. At the community level, collective investments can be made which may influence livestock and household economy, e.g. rehabilitate and improve pasture productivity, improve living conditions on remote pastures etc. Events occurring in the course of the game represent different types of (risk) factors such as meteorology, market, politics etc. that may positively or negatively influence livestock production and household economy. A sustainable management of pastures requires that farms actively regulate the development of their herds, that they take measures to prevent pasture degradation and to improve pasture productivity, and that they find a balance between livestock economy and other productive activities. The game has a double aim: a) each farm aims at its economic success and prosperity, and b) the three farm teams jointly have to find and implement strategies for a sustainable use of pasture areas.

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Au travers de stratégies appropriées, les ménages, appelés ici Unités de Production et de Consommation (UPC), cherchent à faire face à différents évènements et à améliorer leur situation économique et sociale tout en tenant compte des conditions écologiques. Au travers de l’Assemblée Générale Communale (AGC), les UPC peuvent créer des conditions cadres locales plus ou moins favorables aux stratégies qu’ils poursuivent. Par le développement d’une stratégie d’investissement communale mise en œuvre par l’AGC et une bonne coordination entre les UPC, les joueurs peuvent optimiser leurs investissements au niveau des ménages. Vainqueur est l’UPC qui à la fin du jeu dispose du plus grand patrimoine.

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Finite element (FE) analysis is an important computational tool in biomechanics. However, its adoption into clinical practice has been hampered by its computational complexity and required high technical competences for clinicians. In this paper we propose a supervised learning approach to predict the outcome of the FE analysis. We demonstrate our approach on clinical CT and X-ray femur images for FE predictions ( FEP), with features extracted, respectively, from a statistical shape model and from 2D-based morphometric and density information. Using leave-one-out experiments and sensitivity analysis, comprising a database of 89 clinical cases, our method is capable of predicting the distribution of stress values for a walking loading condition with an average correlation coefficient of 0.984 and 0.976, for CT and X-ray images, respectively. These findings suggest that supervised learning approaches have the potential to leverage the clinical integration of mechanical simulations for the treatment of musculoskeletal conditions.

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We investigated whether a pure perceptual stream is sufficient for probabilistic sequence learning to occur within a single session or whether correlated streams are necessary, whether learning is affected by the transition probability between sequence elements, and how the sequence length influences learning. In each of three experiments, we used six horizontally arranged stimulus displays which consisted of randomly ordered bigrams xo and ox. The probability of the next possible target location out of two was either .50/.50 or .75/.25 and was marked by an underline. In Experiment 1, a left vs. right key response was required for the x of a marked bigram in the pure perceptual learning condition and a response key press corresponding to the marked bigram location (out of 6) was required in the correlated streams condition (i.e., the ring, middle, or index finger of the left and right hand, respectively). The same probabilistic 3-element sequence was used in both conditions. Learning occurred only in the correlated streams condition. In Experiment 2, we investigated whether sequence length affected learning correlated sequences by contrasting the 3-elements sequence with a 6-elements sequence. Significant sequence learning occurred in all conditions. In Experiment 3, we removed a potential confound, that is, the sequence of hand changes. Under these conditions, learning occurred for the 3-element sequence only and transition probability did not affect the amount of learning. Together, these results indicate that correlated streams are necessary for probabilistic sequence learning within a single session and that sequence length can reduce the chances for learning to occur.

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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.

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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.

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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.

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This paper describes the collaboration among students and professors in four different subjects, to develop multidisciplinary projects. The objective is to simulate the conditions in a company environment. A new methodology based on student interaction and content development in a Wiki environment has been developed. The collaborative server created an ‘out of the classroom’ discussion forum for students of different subjects, and allowed them to compile a ‘project work’ portfolio. Students and professors participated with enthusiasm, due to the correct well-distributed work and the easiness of use of the selected platform in which only an internet connected computer is needed to create and to discuss the multidisciplinary projects. Quality of developed projects has been dramatically improved due to integration of results provided from the different teams.

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This work explores the automatic recognition of physical activity intensity patterns from multi-axial accelerometry and heart rate signals. Data collection was carried out in free-living conditions and in three controlled gymnasium circuits, for a total amount of 179.80 h of data divided into: sedentary situations (65.5%), light-to-moderate activity (17.6%) and vigorous exercise (16.9%). The proposed machine learning algorithms comprise the following steps: time-domain feature definition, standardization and PCA projection, unsupervised clustering (by k-means and GMM) and a HMM to account for long-term temporal trends. Performance was evaluated by 30 runs of a 10-fold cross-validation. Both k-means and GMM-based approaches yielded high overall accuracy (86.97% and 85.03%, respectively) and, given the imbalance of the dataset, meritorious F-measures (up to 77.88%) for non-sedentary cases. Classification errors tended to be concentrated around transients, what constrains their practical impact. Hence, we consider our proposal to be suitable for 24 h-based monitoring of physical activity in ambulatory scenarios and a first step towards intensity-specific energy expenditure estimators

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The main objective of this article is to focus on the analysis of teaching techniques, ranging from the use of the blackboard and chalk in old traditional classes, using slides and overhead projectors in the eighties and use of presentation software in the nineties, to the video, electronic board and network resources nowadays. Furthermore, all the aforementioned, is viewed under the different mentalities in which the teacher conditions the student using the new teaching technique, improving soft skills but maybe leading either to encouragement or disinterest, and including the lack of educational knowledge consolidation at scientific, technology and specific levels. In the same way, we study the process of adaptation required for teachers, the differences in the processes of information transfer and education towards the student, and even the existence of teachers who are not any longer appealed by their work due which has become much simpler due to new technologies and the greater ease in the development of classes due to the criteria described on the new Grade Programs adopted by the European Higher Education Area. Moreover, it is also intended to understand the evolution of students’ profiles, from the eighties to present time, in order to understand certain attitudes, behaviours, accomplishments and acknowledgements acquired over the semesters within the degree Programs. As an Educational Innovation Group, another key question also arises. What will be the learning techniques in the future?. How these evolving matters will affect both positively and negatively on the mentality, attitude, behaviour, learning, achievement of goals and satisfaction levels of all elements involved in universities’ education? Clearly, this evolution from chalk to the electronic board, the three-dimensional view of our works and their sequence, greatly facilitates the understanding and adaptation later on to the business world, but does not answer to the unknowns regarding the knowledge and the full development of achievement’s indicators in basic skills of a degree. This is the underlying question which steers the roots of the presented research.

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In this paper, we address the problem of dynamic pricing to optimize the revenue coming from the sales of a limited inventory in a finite time-horizon. A priori, the demand is assumed to be unknown. The seller must learn on the fly. We first deal with the simplest case, involving only one class of product for sale. Furthermore the general situation is considered with a finite number of product classes for sale. In particular, a case in point is the sale of tickets for events related to culture and leisure; in this case, typically the tickets are sold months before the event, thus, uncertainty over actual demand levels is a very a common occurrence. We propose a heuristic strategy of adaptive dynamic pricing, based on experience gained from the past, taking into account, for each time period, the available inventory, the time remaining to reach the horizon, and the profit made in previous periods. In the computational simulations performed, the demand is updated dynamically based on the prices being offered, as well as on the remaining time and inventory. The simulations show a significant profit over the fixed-price strategy, confirming the practical usefulness of the proposed strategy. We develop a tool allowing us to test different dynamic pricing strategies designed to fit market conditions and seller s objectives, which will facilitate data analysis and decision-making in the face of the problem of dynamic pricing.

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Usually, vehicle applications require the use of artificial intelligent techniques to implement control methods, due to noise provided by sensors or the impossibility of full knowledge about dynamics of the vehicle (engine state, wheel pressure or occupiers weight). This work presents a method to on-line evolve a fuzzy controller for commanding vehicles? pedals at low speeds; in this scenario, the slightest alteration in the vehicle or road conditions can vary controller?s behavior in a non predictable way. The proposal adapts singletons positions in real time, and trapezoids used to codify the input variables are modified according with historical data. Experimentation in both simulated and real vehicles are provided to show how fast and precise the method is, even compared with a human driver or using different vehicles.