12 resultados para Complex problems
em Universidade Federal do Rio Grande do Norte(UFRN)
Resumo:
The inter-subjectivity is the answer in the search for the solution of complex problems, which concerns interfaces of knowledge, respecting their borders. This paradigm is essential in the author's work. So, the search on screen is based on this perspective, by using inter-subject groups of work conduced by professionals of Computer Science, Social Communication, Architecture and Urbanism, Pedagogy, Psicopegagogy, Nutritional Science, Endocrinology, Occupational Therapy and Nursing, it was also part of this group an 8 year old child, daughter of one of the professional who took part of the group. This thesis aims to present the course of investigation developed, analyzing the action of inter-subject Occupational Therapy and Nutrition on the promotion of learning nutritional concepts through educative-nutritional games in order to prevent child's obesity in an educative context. The research was analytic, interventionist and almost experimental. It took place in a public school in Fortaleza, Ceará, Brazil, between August and December 2004. It was selected a sample non-probabilistic, by convenience, of 200 children, born from 1994 to 1996. It was selected almost nonprobabilistically, by convenience, 200 children born between 1994 and 1996. To analyze the results it was used a triangulation, associated by quantitative and qualitative approaches. The basis collect happened through games specially manufactured to these research- video-games, board games, memory games, puzzles, scramble, searching words and iterative basics. There were semi-structured interviews, direct and structured observations and focus in-groups. It was noticed the efficiency of educativenutritional games in the learning process, which lead to a changing of attitude towards the eating choices. These games gave similar results in relation to the compared variations preferences, experience and attitudes, theses attitudes were observed through the game; and the categories to compare the possibility of learning by playing, the fantasy in the learning process, learning concepts of nutritional education and the need of help in the learning process (mediation). It was proved that educativenutritional games could be used to teach nutritional concepts, in an inter-subjective action of Occupational Therapy and Nutrition in schools. The simultaneous application of these games lead to the optimization of child s learning process. It should be emphasized the need of studies about the adaptation of tools used in a child s Nutritional Education, with the help of inter-subjective action. Because just one subject, in a fractionated way can give an answer to complex problems and help to a change of the reality with effectiveness and resolution
Resumo:
The way of organization of the constitutional jurisdiction implies the possibility to extend the democratization of the same one in function of the popular participation in the active legitimacy to constitutional process (procedimentalist model) e, at the same time, to assure technical viable decisions fast and to the complex problems of the constitucional law (substancialist model). The comparison with the constitutional jurisdiction of U.S.A. becomes interesting from the knowledge of the wide power to decide experience of Supreme the Court that for a methodology of construction of rights and not simply of interpretation of the Constitution, brought up to date and reconstructed throughout its historical evolution the direction of the norms of basic rights and the North American principles constitutional. Construction while constitutional hermeneutic method of substancialist matrix works with techniques as the measurement of principles, the protection of interests of minorities and the entailing of the basic rights with values politicians, what it can be brought to evidence of the Brazilian constitutional jurisdiction in order to improve the construction of basic rights that comes being carried through for the judicial ativism in control of the diffuse and abstract constitutionality. To define the limits of construction is to search, on the other hand, a dialogue with the procedimentalists thesis, aiming at the widening of the participation of the citizen in the construction of the basic rights for the constitutional process and to argue forms of the society to evaluate the pronounced decisions activist in the controls diffuse and abstract of constitutionality
Resumo:
Nowadays, telecommunications is one of the most dynamic and strategic areas in the world. Organizations are always seeking to find new management practices within an ever increasing competitive environment where resources are getting scarce. In this scenario, data obtained from business and corporate processes have even greater importance, although this data is not yet adequately explored. Knowledge Discovery in Databases (KDD) appears then, as an option to allow the study of complex problems in different areas of management. This work proposes both a systematization of KDD activities using concepts from different methodologies, such as CRISP-DM, SEMMA and FAYYAD approaches and a study concerning the viability of multivariate regression analysis models to explain corporative telecommunications sales using performance indicators. Thus, statistical methods were outlined to analyze the effects of such indicators on the behavior of business productivity. According to business and standard statistical analysis, equations were defined and fit to their respective determination coefficients. Tests of hypotheses were also conducted on parameters with the purpose of validating the regression models. The results show that there is a relationship between these development indicators and the amount of sales
Resumo:
The frequency selective surfaces, or FSS (Frequency Selective Surfaces), are structures consisting of periodic arrays of conductive elements, called patches, which are usually very thin and they are printed on dielectric layers, or by openings perforated on very thin metallic surfaces, for applications in bands of microwave and millimeter waves. These structures are often used in aircraft, missiles, satellites, radomes, antennae reflector, high gain antennas and microwave ovens, for example. The use of these structures has as main objective filter frequency bands that can be broadcast or rejection, depending on the specificity of the required application. In turn, the modern communication systems such as GSM (Global System for Mobile Communications), RFID (Radio Frequency Identification), Bluetooth, Wi-Fi and WiMAX, whose services are highly demanded by society, have required the development of antennas having, as its main features, and low cost profile, and reduced dimensions and weight. In this context, the microstrip antenna is presented as an excellent choice for communications systems today, because (in addition to meeting the requirements mentioned intrinsically) planar structures are easy to manufacture and integration with other components in microwave circuits. Consequently, the analysis and synthesis of these devices mainly, due to the high possibility of shapes, size and frequency of its elements has been carried out by full-wave models, such as the finite element method, the method of moments and finite difference time domain. However, these methods require an accurate despite great computational effort. In this context, computational intelligence (CI) has been used successfully in the design and optimization of microwave planar structures, as an auxiliary tool and very appropriate, given the complexity of the geometry of the antennas and the FSS considered. The computational intelligence is inspired by natural phenomena such as learning, perception and decision, using techniques such as artificial neural networks, fuzzy logic, fractal geometry and evolutionary computation. This work makes a study of application of computational intelligence using meta-heuristics such as genetic algorithms and swarm intelligence optimization of antennas and frequency selective surfaces. Genetic algorithms are computational search methods based on the theory of natural selection proposed by Darwin and genetics used to solve complex problems, eg, problems where the search space grows with the size of the problem. The particle swarm optimization characteristics including the use of intelligence collectively being applied to optimization problems in many areas of research. The main objective of this work is the use of computational intelligence, the analysis and synthesis of antennas and FSS. We considered the structures of a microstrip planar monopole, ring type, and a cross-dipole FSS. We developed algorithms and optimization results obtained for optimized geometries of antennas and FSS considered. To validate results were designed, constructed and measured several prototypes. The measured results showed excellent agreement with the simulated. Moreover, the results obtained in this study were compared to those simulated using a commercial software has been also observed an excellent agreement. Specifically, the efficiency of techniques used were CI evidenced by simulated and measured, aiming at optimizing the bandwidth of an antenna for wideband operation or UWB (Ultra Wideband), using a genetic algorithm and optimizing the bandwidth, by specifying the length of the air gap between two frequency selective surfaces, using an optimization algorithm particle swarm
Resumo:
Artificial neural networks are usually applied to solve complex problems. In problems with more complexity, by increasing the number of layers and neurons, it is possible to achieve greater functional efficiency. Nevertheless, this leads to a greater computational effort. The response time is an important factor in the decision to use neural networks in some systems. Many argue that the computational cost is higher in the training period. However, this phase is held only once. Once the network trained, it is necessary to use the existing computational resources efficiently. In the multicore era, the problem boils down to efficient use of all available processing cores. However, it is necessary to consider the overhead of parallel computing. In this sense, this paper proposes a modular structure that proved to be more suitable for parallel implementations. It is proposed to parallelize the feedforward process of an RNA-type MLP, implemented with OpenMP on a shared memory computer architecture. The research consistes on testing and analizing execution times. Speedup, efficiency and parallel scalability are analyzed. In the proposed approach, by reducing the number of connections between remote neurons, the response time of the network decreases and, consequently, so does the total execution time. The time required for communication and synchronization is directly linked to the number of remote neurons in the network, and so it is necessary to investigate which one is the best distribution of remote connections
Resumo:
Although some individual techniques of supervised Machine Learning (ML), also known as classifiers, or algorithms of classification, to supply solutions that, most of the time, are considered efficient, have experimental results gotten with the use of large sets of pattern and/or that they have a expressive amount of irrelevant data or incomplete characteristic, that show a decrease in the efficiency of the precision of these techniques. In other words, such techniques can t do an recognition of patterns of an efficient form in complex problems. With the intention to get better performance and efficiency of these ML techniques, were thought about the idea to using some types of LM algorithms work jointly, thus origin to the term Multi-Classifier System (MCS). The MCS s presents, as component, different of LM algorithms, called of base classifiers, and realized a combination of results gotten for these algorithms to reach the final result. So that the MCS has a better performance that the base classifiers, the results gotten for each base classifier must present an certain diversity, in other words, a difference between the results gotten for each classifier that compose the system. It can be said that it does not make signification to have MCS s whose base classifiers have identical answers to the sames patterns. Although the MCS s present better results that the individually systems, has always the search to improve the results gotten for this type of system. Aim at this improvement and a better consistency in the results, as well as a larger diversity of the classifiers of a MCS, comes being recently searched methodologies that present as characteristic the use of weights, or confidence values. These weights can describe the importance that certain classifier supplied when associating with each pattern to a determined class. These weights still are used, in associate with the exits of the classifiers, during the process of recognition (use) of the MCS s. Exist different ways of calculating these weights and can be divided in two categories: the static weights and the dynamic weights. The first category of weights is characterizes for not having the modification of its values during the classification process, different it occurs with the second category, where the values suffers modifications during the classification process. In this work an analysis will be made to verify if the use of the weights, statics as much as dynamics, they can increase the perfomance of the MCS s in comparison with the individually systems. Moreover, will be made an analysis in the diversity gotten for the MCS s, for this mode verify if it has some relation between the use of the weights in the MCS s with different levels of diversity
Resumo:
The Reconfigurable Computing is an intermediate solution at the resolution of complex problems, making possible to combine the speed of the hardware with the flexibility of the software. An reconfigurable architecture possess some goals, among these the increase of performance. The use of reconfigurable architectures to increase the performance of systems is a well known technology, specially because of the possibility of implementing certain slow algorithms in the current processors directly in hardware. Amongst the various segments that use reconfigurable architectures the reconfigurable processors deserve a special mention. These processors combine the functions of a microprocessor with a reconfigurable logic and can be adapted after the development process. Reconfigurable Instruction Set Processors (RISP) are a subgroup of the reconfigurable processors, that have as goal the reconfiguration of the instruction set of the processor, involving issues such formats, operands and operations of the instructions. This work possess as main objective the development of a RISP processor, combining the techniques of configuration of the set of executed instructions of the processor during the development, and reconfiguration of itself in execution time. The project and implementation in VHDL of this RISP processor has as intention to prove the applicability and the efficiency of two concepts: to use more than one set of fixed instructions, with only one set active in a given time, and the possibility to create and combine new instructions, in a way that the processor pass to recognize and use them in real time as if these existed in the fixed set of instruction. The creation and combination of instructions is made through a reconfiguration unit, incorporated to the processor. This unit allows the user to send custom instructions to the processor, so that later he can use them as if they were fixed instructions of the processor. In this work can also be found simulations of applications involving fixed and custom instructions and results of the comparisons between these applications in relation to the consumption of power and the time of execution, which confirm the attainment of the goals for which the processor was developed
Resumo:
Significant advances have emerged in research related to the topic of Classifier Committees. The models that receive the most attention in the literature are those of the static nature, also known as ensembles. The algorithms that are part of this class, we highlight the methods that using techniques of resampling of the training data: Bagging, Boosting and Multiboosting. The choice of the architecture and base components to be recruited is not a trivial task and has motivated new proposals in an attempt to build such models automatically, and many of them are based on optimization methods. Many of these contributions have not shown satisfactory results when applied to more complex problems with different nature. In contrast, the thesis presented here, proposes three new hybrid approaches for automatic construction for ensembles: Increment of Diversity, Adaptive-fitness Function and Meta-learning for the development of systems for automatic configuration of parameters for models of ensemble. In the first one approach, we propose a solution that combines different diversity techniques in a single conceptual framework, in attempt to achieve higher levels of diversity in ensembles, and with it, the better the performance of such systems. In the second one approach, using a genetic algorithm for automatic design of ensembles. The contribution is to combine the techniques of filter and wrapper adaptively to evolve a better distribution of the feature space to be presented for the components of ensemble. Finally, the last one approach, which proposes new techniques for recommendation of architecture and based components on ensemble, by techniques of traditional meta-learning and multi-label meta-learning. In general, the results are encouraging and corroborate with the thesis that hybrid tools are a powerful solution in building effective ensembles for pattern classification problems.
Resumo:
Nowadays the rapid growth of urban centers, the accumulation of social and environmental demands, the relationship between public policy and increasingly complex problems accentuates the feeling that cities undergo an urban crisis. This crisis is especially characterized by its multidimensionality, which goes through economic, cultural, ethical, environmental and, above all, political issues. In order to study the core of this crisis that is manifested by the urbanization process and has in its exacerbation on the metropolitan areas was conducted conceptual and theoretical study of the meaning of sustainable development applied to the everyday reality of cities, extracting from this debate concepts, such as: sustainable territorial development, administrative sustainability and political sustainability. Looking forward to test this the practical applicability of these theoretical concepts studied, an empirical study was done on the reality of metropolitan solid waste in Natal, Rio Grande do Norte, Brasil. According to the recent theoretical debate, the waste comprises a sector of the urban environmental crisis that best represents the relationship between man and environment. Ensuring the multidimensionality of environmental issues through the “Saber Ambietal” (LEFF, 2005), was made a extensive qualitative study correlating the concepts of sustainable territorial development, metropolitan governance and “Saber Ambiental” applied on solid waste. The results point to the real challenges of municipal government in understanding the real situation, take action and change the inertia in which have operated in recent decades. The results also showed the importance of transforming environmental issues in political, in other words, struggle for ideas, ideological and ethical references.
Resumo:
Nowadays the rapid growth of urban centers, the accumulation of social and environmental demands, the relationship between public policy and increasingly complex problems accentuates the feeling that cities undergo an urban crisis. This crisis is especially characterized by its multidimensionality, which goes through economic, cultural, ethical, environmental and, above all, political issues. In order to study the core of this crisis that is manifested by the urbanization process and has in its exacerbation on the metropolitan areas was conducted conceptual and theoretical study of the meaning of sustainable development applied to the everyday reality of cities, extracting from this debate concepts, such as: sustainable territorial development, administrative sustainability and political sustainability. Looking forward to test this the practical applicability of these theoretical concepts studied, an empirical study was done on the reality of metropolitan solid waste in Natal, Rio Grande do Norte, Brasil. According to the recent theoretical debate, the waste comprises a sector of the urban environmental crisis that best represents the relationship between man and environment. Ensuring the multidimensionality of environmental issues through the “Saber Ambietal” (LEFF, 2005), was made a extensive qualitative study correlating the concepts of sustainable territorial development, metropolitan governance and “Saber Ambiental” applied on solid waste. The results point to the real challenges of municipal government in understanding the real situation, take action and change the inertia in which have operated in recent decades. The results also showed the importance of transforming environmental issues in political, in other words, struggle for ideas, ideological and ethical references.
Resumo:
The Artificial Neural Networks (ANN), which is one of the branches of Artificial Intelligence (AI), are being employed as a solution to many complex problems existing in several areas. To solve these problems, it is essential that its implementation is done in hardware. Among the strategies to be adopted and met during the design phase and implementation of RNAs in hardware, connections between neurons are the ones that need more attention. Recently, are RNAs implemented both in application specific integrated circuits's (Application Specific Integrated Circuits - ASIC) and in integrated circuits configured by the user, like the Field Programmable Gate Array (FPGA), which have the ability to be partially rewritten, at runtime, forming thus a system Partially Reconfigurable (SPR), the use of which provides several advantages, such as flexibility in implementation and cost reduction. It has been noted a considerable increase in the use of FPGAs for implementing ANNs. Given the above, it is proposed to implement an array of reconfigurable neurons for topologies Description of artificial neural network multilayer perceptrons (MLPs) in FPGA, in order to encourage feedback and reuse of neural processors (perceptrons) used in the same area of the circuit. It is further proposed, a communication network capable of performing the reuse of artificial neurons. The architecture of the proposed system will configure various topologies MLPs networks through partial reconfiguration of the FPGA. To allow this flexibility RNAs settings, a set of digital components (datapath), and a controller were developed to execute instructions that define each topology for MLP neural network.
Resumo:
The Artificial Neural Networks (ANN), which is one of the branches of Artificial Intelligence (AI), are being employed as a solution to many complex problems existing in several areas. To solve these problems, it is essential that its implementation is done in hardware. Among the strategies to be adopted and met during the design phase and implementation of RNAs in hardware, connections between neurons are the ones that need more attention. Recently, are RNAs implemented both in application specific integrated circuits's (Application Specific Integrated Circuits - ASIC) and in integrated circuits configured by the user, like the Field Programmable Gate Array (FPGA), which have the ability to be partially rewritten, at runtime, forming thus a system Partially Reconfigurable (SPR), the use of which provides several advantages, such as flexibility in implementation and cost reduction. It has been noted a considerable increase in the use of FPGAs for implementing ANNs. Given the above, it is proposed to implement an array of reconfigurable neurons for topologies Description of artificial neural network multilayer perceptrons (MLPs) in FPGA, in order to encourage feedback and reuse of neural processors (perceptrons) used in the same area of the circuit. It is further proposed, a communication network capable of performing the reuse of artificial neurons. The architecture of the proposed system will configure various topologies MLPs networks through partial reconfiguration of the FPGA. To allow this flexibility RNAs settings, a set of digital components (datapath), and a controller were developed to execute instructions that define each topology for MLP neural network.