5 resultados para Ultra wideband

em Universidade Federal do Rio Grande do Norte(UFRN)


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This work presents a theoretical and experimental investigation about the properties of microstrip antennas for ultra-wideband systems. Configurations of elliptic monopoles with different eccentricities and circular monopoles are considered. Two prototypes for each antenna configuration were built, one with the typical microstrip configuration and the other is similar to the first, except for a small aperture in the ground plane. Therefore, this work proposes to modify the configuration of the ground plane of the monopoles designed adding a rectangular stub, in order to optimize and improve the performance of such structures. The obtained results show that the introduction of that rectangular aperture in the ground plane allows an improvement of the frequency response for the considered antenna propotypes. It is observed a good agreement between the measured and simulated results. Finally, some proposals for future works are presented

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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

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This work is the analysis of a structure of the microstrip antenna designed for application in ultra wide band systems (Ultra Wideband - UWB). This is a prospective analytical study where they tested the changes in the geometry of the antenna, observing their suitability to the proposed objectives. It is known that the UWB antenna must operate in a range of at least 500 MHz, and answer a fractional bandwidth greater than or equal to 25%. It is also desirable that the antenna meets the specifications of track determined by FCC - Federal Communication Commission, which regulates the system in 2002 designating the UWB bandwidth of 7.5 GHz, a range that varies from 3.1 GHz to 10, 6 GHz. by setting the maximum power spectral density of operation in -41.3 dB / MHz, and defining the fractional bandwidth by 20%. The study starts of a structure of geometry in the form of stylized @, which evolves through changes in its form, in simulated commercial software CST MICROWAVE STUDIO, version 5.3.1, and then tested using the ANSOFT HFSS, version 9. These variations, based on observations of publications available from literature referring to the microstrip monopole planar antennas. As a result it is proposed an antenna, called Monopole Antenna Planar Spiral Almost Rectangular for applications in UWB systems - AMQEUWB, which presents simulated and measured results satisfactory, consistent with the objectives of the study. Some proposals for future work are mentioned

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This paper presents an evaluative study about the effects of using a machine learning technique on the main features of a self-organizing and multiobjective genetic algorithm (GA). A typical GA can be seen as a search technique which is usually applied in problems involving no polynomial complexity. Originally, these algorithms were designed to create methods that seek acceptable solutions to problems where the global optimum is inaccessible or difficult to obtain. At first, the GAs considered only one evaluation function and a single objective optimization. Today, however, implementations that consider several optimization objectives simultaneously (multiobjective algorithms) are common, besides allowing the change of many components of the algorithm dynamically (self-organizing algorithms). At the same time, they are also common combinations of GAs with machine learning techniques to improve some of its characteristics of performance and use. In this work, a GA with a machine learning technique was analyzed and applied in a antenna design. We used a variant of bicubic interpolation technique, called 2D Spline, as machine learning technique to estimate the behavior of a dynamic fitness function, based on the knowledge obtained from a set of laboratory experiments. This fitness function is also called evaluation function and, it is responsible for determining the fitness degree of a candidate solution (individual), in relation to others in the same population. The algorithm can be applied in many areas, including in the field of telecommunications, as projects of antennas and frequency selective surfaces. In this particular work, the presented algorithm was developed to optimize the design of a microstrip antenna, usually used in wireless communication systems for application in Ultra-Wideband (UWB). The algorithm allowed the optimization of two variables of geometry antenna - the length (Ls) and width (Ws) a slit in the ground plane with respect to three objectives: radiated signal bandwidth, return loss and central frequency deviation. These two dimensions (Ws and Ls) are used as variables in three different interpolation functions, one Spline for each optimization objective, to compose a multiobjective and aggregate fitness function. The final result proposed by the algorithm was compared with the simulation program result and the measured result of a physical prototype of the antenna built in the laboratory. In the present study, the algorithm was analyzed with respect to their success degree in relation to four important characteristics of a self-organizing multiobjective GA: performance, flexibility, scalability and accuracy. At the end of the study, it was observed a time increase in algorithm execution in comparison to a common GA, due to the time required for the machine learning process. On the plus side, we notice a sensitive gain with respect to flexibility and accuracy of results, and a prosperous path that indicates directions to the algorithm to allow the optimization problems with "η" variables

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INTRODUCTION: The high sensitivity C-reactive protein (hsCRP) constitutes an inflammatory mediator used as predictor of cardiovascular risk that comes being researched as indicative relation factor between cardiovascular and periodontal diseases. PROPOSITION: To compare serumals levels of C-reactive protein between patients with and without generalized severe chronic periodontitis. METHODOLOGY: A seccional study was realized using a sample with 62 patients, being 31 participants carriers of periodontal diseases (Group I) and 31 without periodontal diseases (Group II), grouped to the pairs by age and sex. As inclusion criterio were selected patients with diagnosis of generalized severe chronic periodontitis, being preculeds, individuals which presented systemic disease, recent infection history, historical of CVA or stroke, smokers, pregnants and lactants. The research consisted of two stages, a clinc and other biochemist. The clinical stage is constituted of periodontal examination and the biochemist stage, of the peripheral blood collection for determination hsCRP levels and a hemogram to inquire any panel which could suggest infectious and/or inflammatory process. RESULTS: Periodontal disease group presented a average of 0,36mg/dL, while the group without disease presented 0,17 mg/dL, do not existing significant difference statistically between the averages (p = 0,061). The cardiovascular risk for the group I was classified high for 27,6% of participants and low for 72,4% of them. In the group II, 6,45% presented high risk e 93,5% low risk, being this significant relation statistically gotten for Fisher s Test (p = 0,042) presenting OR = 5,33; IC = 95% (1,02 27,4). The independets variables reseacred do not presented significant association statistically with the levels of hsCRP. CONCLUSION: The study indicated that despite of carriers patients of periodontal diseases do not present differents serumals levels of hsCRP from the other group, the periodontal disease was considered as risk factor for hsCRP plasmatic levels elevation