995 resultados para organizing models
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In this paper, we present our research into self-organizing building algorithms. This idea of self-organization of animal/plants behaviour interests researchers to explore the mechanisms required for this emergent phenomena and try to apply them in other domains. We were able to implement a typical construction algorithm in a 3D simulation environment and reproduce the results of previous research in the area. LSystems, morphogenetic programming and wasp nest building are explained in order to understand self-organizing models. We proposed Grammatical swarm as a good tool to optimize building structures.
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As ideias propostas neste estudo teórico têm como objetivo ampliar as perspectivas de investigação sobre juízos e valores morais. Após uma reflexão crítica sobre teorias que contribuíram com importantes conceitos no campo da Psicologia Moral, foram feitos alguns apontamentos que nos parecem promissores nessa área, tendo por referencial teórico-metodológico a Teoria dos Modelos Organizadores do Pensamento. Essa teoria procura destacar que apenas os recursos cognitivos operatórios não são suficientes para explicar como o sujeito apreende e julga a realidade. Nessa perspectiva, conclui-se como fundamental o papel dos conteúdos na organização das representações mentais relacionadas aos juízos e valores morais.
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Pós-graduação em Psicologia - FCLAS
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The aim of this research was to investigate how the gender representations by young people affect how they interpret and resolve a situation of moral conflict at school. It starts from the references of the Theory of the Organizing Models of Thinking and of critical perspectives on the studies of gender as contributors of conceptual and methodological aspects in the analysis of the psychic functioning. Information was raised with 400 youngsters (15 to 21 years of age) from public and private schools, who answered in writing four questions about feelings, thoughts, and the duty of the characters (boys or girls) before a situation of homophobia at school. The perspective of the gender in the conflict resolution was analyzed taking into account the sex of the characters and the sex of the participants. The results show that the gender representations have an essential role in the manner in which the youngsters resolve interpersonal conflicts, highlighting the reproduction of stereotypes in the social relations among genders at school.
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We trace the evolution of the representation of management in cropping and grazing systems models, from fixed annual schedules of identical actions in single paddocks toward flexible scripts of rules. Attempts to define higher-level organizing concepts in management policies, and to analyse them to identify optimal plans, have focussed on questions relating to grazing management owing to its inherent complexity. “Rule templates” assist the re-use of complex management scripts by bundling commonly-used collections of rules with an interface through which key parameters can be input by a simulation builder. Standard issues relating to parameter estimation and uncertainty apply to management sub-models and need to be addressed. Techniques for embodying farmers' expectations and plans for the future within modelling analyses need to be further developed, especially better linking planning- and rule-based approaches to farm management and analysing the ways that managers can learn.
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Physics teachers are in a key position to form the attitudes and conceptions of future generations toward science and technology, as well as to educate future generations of scientists. Therefore, good teacher education is one of the key areas of physics departments education program. This dissertation is a contribution to the research-based development of high quality physics teacher education, designed to meet three central challenges of good teaching. The first challenge relates to the organization of physics content knowledge. The second challenge, connected to the first one, is to understand the role of experiments and models in (re)constructing the content knowledge of physics for purposes of teaching. The third challenge is to provide for pre-service physics teachers opportunities and resources for reflecting on or assessing their knowledge and experience about physics and physics education. This dissertation demonstrates how these challenges can be met when the content knowledge of physics, the relevant epistemological aspects of physics and the pedagogical knowledge of teaching and learning physics are combined. The theoretical part of this dissertation is concerned with designing two didactical reconstructions for purposes of physics teacher education: the didactical reconstruction of processes (DRoP) and the didactical reconstruction of structures (DRoS). This part starts with taking into account the required professional competencies of physics teachers, the pedagogical aspects of teaching and learning, and the benefits of the graphical ways of representing knowledge. Then it continues with the conceptual and philosophical analysis of physics, especially with the analysis of experiments and models role in constructing knowledge. This analysis is condensed in the form of the epistemological reconstruction of knowledge justification. Finally, these two parts are combined in the designing and production of the DRoP and DRoS. The DRoP captures the knowledge formation of physical concepts and laws in concise and simplified form while still retaining authenticity from the processes of how concepts have been formed. The DRoS is used for representing the structural knowledge of physics, the connections between physical concepts, quantities and laws, to varying extents. Both DRoP and DRoS are represented in graphical form by means of flow charts consisting of nodes and directed links connecting the nodes. The empirical part discusses two case studies that show how the three challenges are met through the use of DRoP and DRoS and how the outcomes of teaching solutions based on them are evaluated. The research approach is qualitative; it aims at the in-depth evaluation and understanding about the usefulness of the didactical reconstructions. The data, which were collected from the advanced course for prospective physics teachers during 20012006, consisted of DRoP and DRoS flow charts made by students and student interviews. The first case study discusses how student teachers used DRoP flow charts to understand the process of forming knowledge about the law of electromagnetic induction. The second case study discusses how student teachers learned to understand the development of physical quantities as related to the temperature concept by using DRoS flow charts. In both studies, the attention is focused on the use of DRoP and DRoS to organize knowledge and on the role of experiments and models in this organization process. The results show that students understanding about physics knowledge production improved and their knowledge became more organized and coherent. It is shown that the flow charts and the didactical reconstructions behind them had an important role in gaining these positive learning results. On the basis of the results reported here, the designed learning tools have been adopted as a standard part of the teaching solutions used in the physics teacher education courses in the Department of Physics, University of Helsinki.
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This paper describes a self-organizing neural model for eye-hand coordination. Called the DIRECT model, it embodies a solution of the classical motor equivalence problem. Motor equivalence computations allow humans and other animals to flexibly employ an arm with more degrees of freedom than the space in which it moves to carry out spatially defined tasks under conditions that may require novel joint configurations. During a motor babbling phase, the model endogenously generates movement commands that activate the correlated visual, spatial, and motor information that are used to learn its internal coordinate transformations. After learning occurs, the model is capable of controlling reaching movements of the arm to prescribed spatial targets using many different combinations of joints. When allowed visual feedback, the model can automatically perform, without additional learning, reaches with tools of variable lengths, with clamped joints, with distortions of visual input by a prism, and with unexpected perturbations. These compensatory computations occur within a single accurate reaching movement. No corrective movements are needed. Blind reaches using internal feedback have also been simulated. The model achieves its competence by transforming visual information about target position and end effector position in 3-D space into a body-centered spatial representation of the direction in 3-D space that the end effector must move to contact the target. The spatial direction vector is adaptively transformed into a motor direction vector, which represents the joint rotations that move the end effector in the desired spatial direction from the present arm configuration. Properties of the model are compared with psychophysical data on human reaching movements, neurophysiological data on the tuning curves of neurons in the monkey motor cortex, and alternative models of movement control.
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Thesis (Master's)--University of Washington, 2015
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Forecasting future sales is one of the most important issues that is beyond all strategic and planning decisions in effective operations of retail businesses. For profitable retail businesses, accurate demand forecasting is crucial in organizing and planning production, purchasing, transportation and labor force. Retail sales series belong to a special type of time series that typically contain trend and seasonal patterns, presenting challenges in developing effective forecasting models. This work compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties, Flats, Sandals and Shoes. On both methodologies the model with the minimum value of Akaike's Information Criteria for the in-sample period was selected from all admissible models for further evaluation in the out-of-sample. Both one-step and multiple-step forecasts were produced. The results show that when an automatic algorithm the overall out-of-sample forecasting performance of state space and ARIMA models evaluated via RMSE, MAE and MAPE is quite similar on both one-step and multi-step forecasts. We also conclude that state space and ARIMA produce coverage probabilities that are close to the nominal rates for both one-step and multi-step forecasts.
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Self-organizing maps (Kohonen 1997) is a type of artificial neural network developed to explore patterns in high-dimensional multivariate data. The conventional version of the algorithm involves the use of Euclidean metric in the process of adaptation of the model vectors, thus rendering in theory a whole methodology incompatible with non-Euclidean geometries. In this contribution we explore the two main aspects of the problem: 1. Whether the conventional approach using Euclidean metric can shed valid results with compositional data. 2. If a modification of the conventional approach replacing vectorial sum and scalar multiplication by the canonical operators in the simplex (i.e. perturbation and powering) can converge to an adequate solution. Preliminary tests showed that both methodologies can be used on compositional data. However, the modified version of the algorithm performs poorer than the conventional version, in particular, when the data is pathological. Moreover, the conventional ap- proach converges faster to a solution, when data is \well-behaved". Key words: Self Organizing Map; Artificial Neural networks; Compositional data
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The impact of new advanced technology on issues that concern meaningful information and its relation to studies of intelligence constitutes the main topic of the present paper. The advantages, disadvantages and implications of the synthetic methodology developed by cognitive scientists, according to which mechanical models of the mind, such as computer simulations or self-organizing robots, may provide good explanatory tools to investigate cognition, are discussed. A difficulty with this methodology is pointed out, namely the use of meaningless information to explain intelligent behavior that incorporates meaningful information. In this context, it is inquired what are the contributions of cognitive science to contemporary studies of intelligent behavior and how technology may play a role in the analysis of the relationships established by organisms in their natural and social environments. © John Benjamins Publishing Company.
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Males of Limnogonus aduncus were found to have the sex chromosome system X0 and chromosome number 2n = 23 (22A + X0). Testis cells were stained with lacto-acetic orcein and silver nitrate so that changes in the morphology and degree of staining of the heteropicnotic chromatin and the nucleolar material could be observed during meiosis and spermiogenesis. These structures share the same nuclear position and could be seen until almost the end of spermiogenesis. A chromosome region stained with silver nitrate was indicative of a nucleolar organizing region (NOR), which is rarely detected in Heteroptera with this technique. The NOR is located at one end of a single member of an autosome pair. The finding of this stained region enabled us to observe that the telomeric association of sister chromatids that characterizes the Heteroptera does not include the chromosome ends, where NORs are located; we also observed in anaphase that the chromosome end through which it is pulled to the pole is the one containing the NOR. Another observation was that the single nucleolar body present in the cells at anaphase never goes to the cell pole that does not receive the NOR. We conclude that L. aduncus is a good model for cytogenetic studies involving nucleolar activity and also may be useful for studying the mechanisms of activation and inactivation of kinetic activity at the chromosome ends. Although the chromosomes of Heteroptera are known to be holocentric, whether kinetic activity is restricted to one or involves both chromosome ends is still not well understood.
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The Asteraceae, one of the largest families among angiosperms, is chemically characterised by the production of sesquiterpene lactones (SLs). A total of 1,111 SLs, which were extracted from 658 species, 161 genera, 63 subtribes and 15 tribes of Asteraceae, were represented and registered in two dimensions in the SISTEMATX, an in-house software system, and were associated with their botanical sources. The respective 11 block of descriptors: Constitutional, Functional groups, BCUT, Atom-centred, 2D autocorrelations, Topological, Geometrical, RDF, 3D-MoRSE, GETAWAY and WHIM were used as input data to separate the botanical occurrences through self-organising maps. Maps that were generated with each descriptor divided the Asteraceae tribes, with total index values between 66.7% and 83.6%. The analysis of the results shows evident similarities among the Heliantheae, Helenieae and Eupatorieae tribes as well as between the Anthemideae and Inuleae tribes. Those observations are in agreement with systematic classifications that were proposed by Bremer, which use mainly morphological and molecular data, therefore chemical markers partially corroborate with these classifications. The results demonstrate that the atom-centred and RDF descriptors can be used as a tool for taxonomic classification in low hierarchical levels, such as tribes. Descriptors obtained through fragments or by the two-dimensional representation of the SL structures were sufficient to obtain significant results, and better results were not achieved by using descriptors derived from three-dimensional representations of SLs. Such models based on physico-chemical properties can project new design SLs, similar structures from literature or even unreported structures in two-dimensional chemical space. Therefore, the generated SOMs can predict the most probable tribe where a biologically active molecule can be found according Bremer classification.
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Classical Pavlovian fear conditioning to painful stimuli has provided the generally accepted view of a core system centered in the central amygdala to organize fear responses. Ethologically based models using other sources of threat likely to be expected in a natural environment, such as predators or aggressive dominant conspecifics, have challenged this concept of a unitary core circuit for fear processing. We discuss here what the ethologically based models have told us about the neural systems organizing fear responses. We explored the concept that parallel paths process different classes of threats, and that these different paths influence distinct regions in the periaqueductal gray - a critical element for the organization of all kinds of fear responses. Despite this parallel processing of different kinds of threats, we have discussed an interesting emerging view that common cortical-hippocampal-amygdalar paths seem to be engaged in fear conditioning to painful stimuli, to predators and, perhaps, to aggressive dominant conspecifics as well. Overall, the aim of this review is to bring into focus a more global and comprehensive view of the systems organizing fear responses.
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Logistics involves planning, managing, and organizing the flows of goods from the point of origin to the point of destination in order to meet some requirements. Logistics and transportation aspects are very important and represent a relevant costs for producing and shipping companies, but also for public administration and private citizens. The optimization of resources and the improvement in the organization of operations is crucial for all branches of logistics, from the operation management to the transportation. As we will have the chance to see in this work, optimization techniques, models, and algorithms represent important methods to solve the always new and more complex problems arising in different segments of logistics. Many operation management and transportation problems are related to the optimization class of problems called Vehicle Routing Problems (VRPs). In this work, we consider several real-world deterministic and stochastic problems that are included in the wide class of the VRPs, and we solve them by means of exact and heuristic methods. We treat three classes of real-world routing and logistics problems. We deal with one of the most important tactical problems that arises in the managing of the bike sharing systems, that is the Bike sharing Rebalancing Problem (BRP). We propose models and algorithms for real-world earthwork optimization problems. We describe the 3DP process and we highlight several optimization issues in 3DP. Among those, we define the problem related to the tool path definition in the 3DP process, the 3D Routing Problem (3DRP), which is a generalization of the arc routing problem. We present an ILP model and several heuristic algorithms to solve the 3DRP.