31 resultados para Sistema telefônico digital


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This dissertation presents a new proposal for the Direction of Arrival (DOA) detection problem for more than one signal inciding simultaneously on an antennas array with linear or planar geometry by using intelligent algorithms. The DOA estimator is developed by using techniques of Conventional Beam-forming (CBF), Blind Source Separation (BSS), and the neural estimator MRBF (Modular Structure of Radial Basis Functions). The developed MRBF estimator has its capacity extended due to the interaction with the BSS technique. The BSS makes an estimation of the steering vectors of the multiple plane waves that reach the array in the same frequency, that means, obtains to separate mixed signals without information a priori. The technique developed in this work makes possible to identify the multiple sources directions and to identify and to exclude interference sources

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The vision is one of the five senses of the human body and, in children is responsible for up to 80% of the perception of world around. Studies show that 50% of children with multiple disabilities have some visual impairment, and 4% of all children are diagnosed with strabismus. The strabismus is an eye disability associated with handling capacity of the eye, defined as any deviation from perfect ocular alignment. Besides of aesthetic aspect, the child may report blurred or double vision . Ophthalmological cases not diagnosed correctly are reasons for many school abandonments. The Ministry of Education of Brazil points to the visually impaired as a challenge to the educators of children, particularly in literacy process. The traditional eye examination for diagnosis of strabismus can be accomplished by inducing the eye movements through the doctor s instructions to the patient. This procedure can be played through the computer aided analysis of images captured on video. This paper presents a proposal for distributed system to assist health professionals in remote diagnosis of visual impairment associated with motor abilities of the eye, such as strabismus. It is hoped through this proposal to contribute improving the rates of school learning for children, allowing better diagnosis and, consequently, the student accompaniment

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Wireless sensor networks are reality nowadays. The growing necessity of connectivity between existing industrial plant equipments pushes the research and development of several technologies. The IEEE 802.15.4 LR-WPAN comes as a low-cost and powersaving viable solution, which are important concerns while making decisions on remote sensoring projects. This study intends to propose a wireless communication system which makes possible the monitoring of analogic and/or digital variables (i. e., the pressure studied) involved on the artificial methods for oil and gas lifting. The main issues are: To develop a software based on SMAC Standard in order to create a wireless network to monitoring analogic and/or digital variables; To evaluate the communication link based on the number of lost packets tested in different environments (indoor and outdoor) and To propose an instrumentation system consisting of wireless devices

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Oil spill on the sea, accidental or not, generates enormous negative consequences for the affected area. The damages are ambient and economic, mainly with the proximity of these spots of preservation areas and/or coastal zones. The development of automatic techniques for identification of oil spots on the sea surface, captured through Radar images, assist in a complete monitoring of the oceans and seas. However spots of different origins can be visualized in this type of imaging, which is a very difficult task. The system proposed in this work, based on techniques of digital image processing and artificial neural network, has the objective to identify the analyzed spot and to discern between oil and other generating phenomena of spot. Tests in functional blocks that compose the proposed system allow the implementation of different algorithms, as well as its detailed and prompt analysis. The algorithms of digital image processing (speckle filtering and gradient), as well as classifier algorithms (Multilayer Perceptron, Radial Basis Function, Support Vector Machine and Committe Machine) are presented and commented.The final performance of the system, with different kind of classifiers, is presented by ROC curve. The true positive rates are considered agreed with the literature about oil slick detection through SAR images presents

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In this work, we propose a multi agent system for digital image steganalysis, based on the poliginic bees model. Such approach aims to solve the problem of automatic steganalysis for digital media, with a case study on digital images. The system architecture was designed not only to detect if a file is suspicious of covering a hidden message, as well to extract the hidden message or information regarding it. Several experiments were performed whose results confirm a substantial enhancement (from 67% to 82% success rate) by using the multi-agent approach, fact not observed in traditional systems. An ongoing application using the technique is the detection of anomalies in digital data produced by sensors that capture brain emissions in little animals. The detection of such anomalies can be used to prove theories and evidences of imagery completion during sleep provided by the brain in visual cortex areas

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The process for choosing the best components to build systems has become increasingly complex. It becomes more critical if it was need to consider many combinations of components in the context of an architectural configuration. These circumstances occur, mainly, when we have to deal with systems involving critical requirements, such as the timing constraints in distributed multimedia systems, the network bandwidth in mobile applications or even the reliability in real-time systems. This work proposes a process of dynamic selection of architectural configurations based on non-functional requirements criteria of the system, which can be used during a dynamic adaptation. This proposal uses the MAUT theory (Multi-Attribute Utility Theory) for decision making from a finite set of possibilities, which involve multiple criteria to be analyzed. Additionally, it was proposed a metamodel which can be used to describe the application s requirements in terms of the non-functional requirements criteria and their expected values, to express them in order to make the selection of the desired configuration. As a proof of concept, it was implemented a module that performs the dynamic choice of configurations, the MoSAC. This module was implemented using a component-based development approach (CBD), performing a selection of architectural configurations based on the proposed selection process involving multiple criteria. This work also presents a case study where an application was developed in the context of Digital TV to evaluate the time spent on the module to return a valid configuration to be used in a middleware with autoadaptative features, the middleware AdaptTV

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In February 2011, the National Agency of Petroleum, Natural Gas and Biofuels (ANP) has published a new Technical Rules for Handling Land Pipeline Petroleum and Natural Gas Derivatives (RTDT). Among other things, the RTDT made compulsory the use of monitoring systems and leak detection in all onshore pipelines in the country. This document provides a study on the method for detection of transient pressure. The study was conducted on a industrial duct 16" diameter and 9.8 km long. The pipeline is fully pressurized and carries a multiphase mixture of crude oil, water and natural gas. For the study, was built an infrastructure for data acquisition and validation of detection algorithms. The system was designed with SCADA architecture. Piezoresistive sensors were installed at the ends of the duct and Digital Signal Processors (DSPs) were used for sampling, storage and processing of data. The study was based on simulations of leaks through valves and search for patterns that characterize the occurrence of such phenomena

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The fundamental senses of the human body are: vision, hearing, touch, taste and smell. These senses are the functions that provide our relationship with the environment. The vision serves as a sensory receptor responsible for obtaining information from the outside world that will be sent to the brain. The gaze reflects its attention, intention and interest. Therefore, the estimation of gaze direction, using computer tools, provides a promising alternative to improve the capacity of human-computer interaction, mainly with respect to those people who suffer from motor deficiencies. Thus, the objective of this work is to present a non-intrusive system that basically uses a personal computer and a low cost webcam, combined with the use of digital image processing techniques, Wavelets transforms and pattern recognition, such as artificial neural network models, resulting in a complete system that performs since the image acquisition (including face detection and eye tracking) to the estimation of gaze direction. The obtained results show the feasibility of the proposed system, as well as several feature advantages.

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In the current work are presented the results about the study of digital mapping of analogs referents the fluvial oil reservoirs in the Açu Formation. With the regional recognizing in the south corner of Potiguar Basin was selected a area of 150 Km square in the west of Assu city. In this area was chosen the outcrops for the digital mapping and from the data fields and remote sensors were done the depositional architectural for the fluvial deposits, which it was named coarse meandering fluvial systems. In the deposits were individualized 3 (three) fluvial cycles, which they was separated by bounding surface of fifth order. Such cycles are preferentially sandy, with fining-upward sequence finished in flood plain deposits. Inner of the sandy levels of the filling channels were characterized least cycles, normaly incomplete, constituted by braided sandy bodies and bounding surfaces of fourth order. In the mapped area was chosen a outcrop with great exposition, where it was possible to see tipical deposits of filling channel and was in this outcrop that was done the digital mapping. In this outcrop was used diverse technics and tools, which they integrated sedimentological, altimetric (GPS, Total Station), LIDAR (Light Detection and Ranging), digital photomosaic of high resolution and of the inner geometries (Ground Penetration Radar) data sets. For the integrating, interpretation and visualization of data was used software GoCAD®. The final product of the outcrop digital mapping was the photorealistic model of part of the cliff (or slope) because the observed reflectors in the radargrams were absents. A part of bar oblique accretion was modeled according to GPR gride of 200x200 meters in the alluvial Assu river probable recent analog. With the data of inner geometries was developed the three-dimentional sedimentary architectural, where it was possible characterize sand sheet deposits and many hierarchy of braided channels. At last, simulations of sedimentary geometries and architectures of the Potiguar Basin Fluvial Reservoirs were done with PetBool software, in order to understand the capacity of this program in simulations with a lot of numbers of conditioning wells. In total, 45 simulations was acquired, where the time and the channel numbers increase in relation of the conditioning wells quantity. The deformation of the meanders was detected from the change of simulated dominion dimensions. The presence of this problem was because the relationship between the simulated dominion and the width of the meander

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Mathematical Morphology presents a systematic approach to extract geometric features of binary images, using morphological operators that transform the original image into another by means of a third image called structuring element and came out in 1960 by researchers Jean Serra and George Matheron. Fuzzy mathematical morphology extends the operators towards grayscale and color images and was initially proposed by Goetherian using fuzzy logic. Using this approach it is possible to make a study of fuzzy connectives, which allows some scope for analysis for the construction of morphological operators and their applicability in image processing. In this paper, we propose the development of morphological operators fuzzy using the R-implications for aid and improve image processing, and then to build a system with these operators to count the spores mycorrhizal fungi and red blood cells. It was used as the hypothetical-deductive methodologies for the part formal and incremental-iterative for the experimental part. These operators were applied in digital and microscopic images. The conjunctions and implications of fuzzy morphology mathematical reasoning will be used in order to choose the best adjunction to be applied depending on the problem being approached, i.e., we will use automorphisms on the implications and observe their influence on segmenting images and then on their processing. In order to validate the developed system, it was applied to counting problems in microscopic images, extending to pathological images. It was noted that for the computation of spores the best operator was the erosion of Gödel. It developed three groups of morphological operators fuzzy, Lukasiewicz, And Godel Goguen that can have a variety applications

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The increasing in world population, with higher proportion of elderly, leads to an increase in the number of individuals with vision loss and cataracts are one of the leading causes of blindness worldwide. Cataract is an eye disease that is the partial or total opacity of the crystalline lens (natural lens of the eye) or its capsule. It can be triggered by several factors such as trauma, age, diabetes mellitus, and medications, among others. It is known that the attendance by ophthalmologists in rural and poor areas in Brazil is less than needed and many patients with treatable diseases such as cataracts are undiagnosed and therefore untreated. In this context, this project presents the development of OPTICA, a system of teleophthalmology using smartphones for ophthalmic emergencies detection, providing a diagnostic aid for cataract using specialists systems and image processing techniques. The images are captured by a cellphone camera and along with a questionnaire filled with patient information are transmitted securely via the platform Mobile SANA to a online server that has an intelligent system available to assist in the diagnosis of cataract and provides ophthalmologists who analyze the information and write back the patient’s report. Thus, the OPTICA provides eye care to the poorest and least favored population, improving the screening of critically ill patients and increasing access to diagnosis and treatment.

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The Physical Rehabilitation services (PR) are of fundamental importance in combating the global epidemic of Traffic Accidents (TA). Considering the numerous physical and social consequences of the survivors, quality problems in access to PR are a hazard to recovery of victims. It is necessary to improve the management of quality of services, assessing priority dimensions and intervening in their causes, to ensure rehabilitation available in time and suitable conditions. This study aimed to identify barriers to access to rehabilitation considering the perception of TA victims and professionals. The aim is also to estimate the access to rehabilitation and their associated factors. This is a qualitative and quantitative study of exploratory nature developed in Natal / RN with semi-structured interviews with 19 health professionals and telephone survey to 155 victims of traffic accidents. To explore barriers to access the speeches were transcribed and analyzed using the Alceste software (version 4.9). During the interviews used the following guiding question: “What barriers hinder or prevent access to physical rehabilitation for victims of traffic accidents?”. The names of classes and axes resulting from Alceste was performed by ad hoc query to three external researchers with subsequent consensus of the most representative name of analysis. We conducted multivariate analysis of the influence of the variables of the accident, sociodemographic, clinical and assistance on access to rehabilitation. Associations with p <0.20 in the bivariate analysis were submitted to logistic regression, step by step, with p <0.05 and confidence interval (CI) of 95%. The main barriers identified were: “Bureaucratic regulation”, “Long time to start rehabilitation”, “No post-surgery referral” and “inefficiency of public services”. These barriers were divided into a theoretical model built from the cause-effect diagram, in which we observed that insufficient access to rehabilitation is the product of causes related to organizational structure, work processes, professional and patients. Was constructed two logistic regression models: “General access to rehabilitation” and “Access to rehabilitation to public service”. 51.6% of patients had access to rehabilitation, and 32.9% in public and 17.9% in the private sector. The regression model “General access to rehabilitation” included the variables Income (OR:3.7), Informal Employment (OR:0.11), Unemployment (OR:0.15), Perceived Need for PR (OR:10) and Referral (OR: 27.5). The model “Access to rehabilitation in the public service” was represented by the “Referral to Public Service” (OR: 23.0) and “Private Health Plan” (OR: 0.07). Despite the known influence of social determinants on access to health services, a situation difficult to control by the public administration, this study found that the organizational and bureaucratic procedures established in health care greatly determine access to rehabilitation. Access difficulties show the seriousness of the problem and the factors suggest the need for improvements in comprehensive care for TA survivors and avoid unnecessary prolongation of the suffering of the victims of this epidemic.

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Several are the areas in which digital images are used in solving day-to-day problems. In medicine the use of computer systems have improved the diagnosis and medical interpretations. In dentistry it’s not different, increasingly procedures assisted by computers have support dentists in their tasks. Set in this context, an area of dentistry known as public oral health is responsible for diagnosis and oral health treatment of a population. To this end, oral visual inspections are held in order to obtain oral health status information of a given population. From this collection of information, also known as epidemiological survey, the dentist can plan and evaluate taken actions for the different problems identified. This procedure has limiting factors, such as a limited number of qualified professionals to perform these tasks, different diagnoses interpretations among other factors. Given this context came the ideia of using intelligent systems techniques in supporting carrying out these tasks. Thus, it was proposed in this paper the development of an intelligent system able to segment, count and classify teeth from occlusal intraoral digital photographic images. The proposed system makes combined use of machine learning techniques and digital image processing. We first carried out a color-based segmentation on regions of interest, teeth and non teeth, in the images through the use of Support Vector Machine. After identifying these regions were used techniques based on morphological operators such as erosion and transformed watershed for counting and detecting the boundaries of the teeth, respectively. With the border detection of teeth was possible to calculate the Fourier descriptors for their shape and the position descriptors. Then the teeth were classified according to their types through the use of the SVM from the method one-against-all used in multiclass problem. The multiclass classification problem has been approached in two different ways. In the first approach we have considered three class types: molar, premolar and non teeth, while the second approach were considered five class types: molar, premolar, canine, incisor and non teeth. The system presented a satisfactory performance in the segmenting, counting and classification of teeth present in the images.

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Several are the areas in which digital images are used in solving day-to-day problems. In medicine the use of computer systems have improved the diagnosis and medical interpretations. In dentistry it’s not different, increasingly procedures assisted by computers have support dentists in their tasks. Set in this context, an area of dentistry known as public oral health is responsible for diagnosis and oral health treatment of a population. To this end, oral visual inspections are held in order to obtain oral health status information of a given population. From this collection of information, also known as epidemiological survey, the dentist can plan and evaluate taken actions for the different problems identified. This procedure has limiting factors, such as a limited number of qualified professionals to perform these tasks, different diagnoses interpretations among other factors. Given this context came the ideia of using intelligent systems techniques in supporting carrying out these tasks. Thus, it was proposed in this paper the development of an intelligent system able to segment, count and classify teeth from occlusal intraoral digital photographic images. The proposed system makes combined use of machine learning techniques and digital image processing. We first carried out a color-based segmentation on regions of interest, teeth and non teeth, in the images through the use of Support Vector Machine. After identifying these regions were used techniques based on morphological operators such as erosion and transformed watershed for counting and detecting the boundaries of the teeth, respectively. With the border detection of teeth was possible to calculate the Fourier descriptors for their shape and the position descriptors. Then the teeth were classified according to their types through the use of the SVM from the method one-against-all used in multiclass problem. The multiclass classification problem has been approached in two different ways. In the first approach we have considered three class types: molar, premolar and non teeth, while the second approach were considered five class types: molar, premolar, canine, incisor and non teeth. The system presented a satisfactory performance in the segmenting, counting and classification of teeth present in the images.

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MEDEIROS, Rildeci; MELO, Erica S. F.; NASCIMENTO, M. S. Hemeroteca digital temática: socialização da informação em cinema.In:SEMINÁRIO NACIONAL DE BIBLIOTECAS UNIVERSITÁRIAS,15.,2008,São Paulo. Anais eletrônicos... São Paulo:CRUESP,2008. Disponível em: http://www.sbu.unicamp.br/snbu2008/anais/site/pdfs/3018.pdf