201 resultados para Compressão de dados (Telecomunicações)

em Universidade Federal do Rio Grande do Norte(UFRN)


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The great amount of data generated as the result of the automation and process supervision in industry implies in two problems: a big demand of storage in discs and the difficulty in streaming this data through a telecommunications link. The lossy data compression algorithms were born in the 90’s with the goal of solving these problems and, by consequence, industries started to use those algorithms in industrial supervision systems to compress data in real time. These algorithms were projected to eliminate redundant and undesired information in a efficient and simple way. However, those algorithms parameters must be set for each process variable, becoming impracticable to configure this parameters for each variable in case of systems that monitor thousands of them. In that context, this paper propose the algorithm Adaptive Swinging Door Trending that consists in a adaptation of the Swinging Door Trending, as this main parameters are adjusted dynamically by the analysis of the signal tendencies in real time. It’s also proposed a comparative analysis of performance in lossy data compression algorithms applied on time series process variables and dynamometer cards. The algorithms used to compare were the piecewise linear and the transforms.

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Image compress consists in represent by small amount of data, without loss a visual quality. Data compression is important when large images are used, for example satellite image. Full color digital images typically use 24 bits to specify the color of each pixel of the Images with 8 bits for each of the primary components, red, green and blue (RGB). Compress an image with three or more bands (multispectral) is fundamental to reduce the transmission time, process time and record time. Because many applications need images, that compression image data is important: medical image, satellite image, sensor etc. In this work a new compression color images method is proposed. This method is based in measure of information of each band. This technique is called by Self-Adaptive Compression (S.A.C.) and each band of image is compressed with a different threshold, for preserve information with better result. SAC do a large compression in large redundancy bands, that is, lower information and soft compression to bands with bigger amount of information. Two image transforms are used in this technique: Discrete Cosine Transform (DCT) and Principal Component Analysis (PCA). Primary step is convert data to new bands without relationship, with PCA. Later Apply DCT in each band. Data Loss is doing when a threshold discarding any coefficients. This threshold is calculated with two elements: PCA result and a parameter user. Parameters user define a compression tax. The system produce three different thresholds, one to each band of image, that is proportional of amount information. For image reconstruction is realized DCT and PCA inverse. SAC was compared with JPEG (Joint Photographic Experts Group) standard and YIQ compression and better results are obtain, in MSE (Mean Square Root). Tests shown that SAC has better quality in hard compressions. With two advantages: (a) like is adaptive is sensible to image type, that is, presents good results to divers images kinds (synthetic, landscapes, people etc., and, (b) it need only one parameters user, that is, just letter human intervention is required

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The Telehealth Brazil Networks Program, created in 2007 with the aim of strengthening primary care and the unified health system (SUS - Sistema Único de Saúde), uses information and communication technologies for distance learning activities related to health. The use of technology enables the interaction between health professionals and / or their patients, furthering the ability of Family Health Teams (FHT). The program is grounded in law, which determines a number of technologies, protocols and processes which guide the work of Telehealth nucleus in the provision of services to the population. Among these services is teleconsulting, which is registered consultation and held between workers, professionals and managers of healthcare through bidirectional telecommunication instruments, in order to answer questions about clinical procedures, health actions and questions on the dossier of work. With the expansion of the program in 2011, was possible to detect problems and challenges that cover virtually all nucleus at different scales for each region. Among these problems can list the heterogeneity of platforms, especially teleconsulting, and low internet coverage in the municipalities, mainly in the interior cities of Brazil. From this perspective, the aim of this paper is to propose a distributed architecture, using mobile computing to enable the sending of teleconsultation. This architecture works offline, so that when internet connection data will be synchronized with the server. This data will travel on compressed to reduce the need for high transmission rates. Any Telehealth Nucleus can use this architecture, through an external service, which will be coupled through a communication interface.

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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

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This Master s Thesis proposes the application of Data Envelopment Analysis DEA to evaluate economies of scale and economies of scope in the performance of service teams involved with installation of data communication circuits, based on the study of a major telecommunication company in Brazil. Data was collected from the company s Operational Performance Division. Initial analysis of a data set, including nineteen installation teams, was performed considering input oriented methods. Subsequently, the need for restrictions on weights is analyzed using the Assurance Region method, checking for the existence of zero-valued weights. The resulting returns to scale are then verified. Further analyses using the Assurance Region Constant (AR-I-C) and Variable (AR-I-V) models verify the existence of variable, rather than constant, returns to scale. Therefore, all of the final comparisons use scores obtained through the AR-I-V model. In sequence, we verify if the system has economies of scope by analyzing the behavior of the scores in terms of individual or multiple outputs. Finally, conventional results, used by the company in study to evaluate team performance, are compared to those generated using the DEA methodology. The results presented here show that DEA is a useful methodology for assessing team performance and that it may contribute to improvements on the quality of the goal setting procedure.

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This Master s Thesis proposes the application of Data Envelopment Analysis DEA to evaluate the performance of sales teams, based on a study of their coverage areas. Data was collected from the company contracted to distribute the products in the state of Ceará. Analyses of thirteen sales coverage areas were performed considering first the output-oriented constant return to scale method (CCR-O), then this method with assurance region (AR-O-C) and finally the method of variable returns to scale with assurance region (AR-O-V). The method used in the first approach is shown to be inappropriate for this study, since it inconveniently generates zero-valued weights, allowing that an area under evaluation obtain the maximal score by not producing. Using weight restrictions, through the assurance region methods AR-O-C and AR-O-V, decreasing returns to scale are identified, meaning that the improvement in performance is not proportional to the size of the areas being analyzed. Observing data generated by the analysis, a study is carried out, aiming to design improvement goals for the inefficient areas. Complementing this study, GDP data for each area was compared with scores obtained using AR-O-V analysis. The results presented in this work show that DEA is a useful methodology for assessing sales team performance and that it may contribute to improvements on the quality of the management process.

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ln this work the implementation of the SOM (Self Organizing Maps) algorithm or Kohonen neural network is presented in the form of hierarchical structures, applied to the compression of images. The main objective of this approach is to develop an Hierarchical SOM algorithm with static structure and another one with dynamic structure to generate codebooks (books of codes) in the process of the image Vector Quantization (VQ), reducing the time of processing and obtaining a good rate of compression of images with a minimum degradation of the quality in relation to the original image. Both self-organizing neural networks developed here, were denominated HSOM, for static case, and DHSOM, for the dynamic case. ln the first form, the hierarchical structure is previously defined and in the later this structure grows in an automatic way in agreement with heuristic rules that explore the data of the training group without use of external parameters. For the network, the heuristic mIes determine the dynamics of growth, the pruning of ramifications criteria, the flexibility and the size of children maps. The LBO (Linde-Buzo-Oray) algorithm or K-means, one ofthe more used algorithms to develop codebook for Vector Quantization, was used together with the algorithm of Kohonen in its basic form, that is, not hierarchical, as a reference to compare the performance of the algorithms here proposed. A performance analysis between the two hierarchical structures is also accomplished in this work. The efficiency of the proposed processing is verified by the reduction in the complexity computational compared to the traditional algorithms, as well as, through the quantitative analysis of the images reconstructed in function of the parameters: (PSNR) peak signal-to-noise ratio and (MSE) medium squared error

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In this work, spoke about the importance of image compression for the industry, it is known that processing and image storage is always a challenge in petrobrás to optimize the storage time and store a maximum number of images and data. We present an interactive system for processing and storing images in the wavelet domain and an interface for digital image processing. The proposal is based on the Peano function and wavelet transform in 1D. The storage system aims to optimize the computational space, both for storage and for transmission of images. Being necessary to the application of the Peano function to linearize the images and the 1D wavelet transform to decompose it. These applications allow you to extract relevant information for the storage of an image with a lower computational cost and with a very small margin of error when comparing the images, original and processed, ie, there is little loss of quality when applying the processing system presented . The results obtained from the information extracted from the images are displayed in a graphical interface. It is through the graphical user interface that the user uses the files to view and analyze the results of the programs directly on the computer screen without the worry of dealing with the source code. The graphical user interface, programs for image processing via Peano Function and Wavelet Transform 1D, were developed in Java language, allowing a direct exchange of information between them and the user

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The objective of this thesis is proposes a method for a mobile robot to build a hybrid map of an indoor, semi-structured environment. The topological part of this map deals with spatial relationships among rooms and corridors. It is a topology-based map, where the edges of the graph are rooms or corridors, and each link between two distinct edges represents a door. The metric part of the map consists in a set of parameters. These parameters describe a geometric figure which adapts to the free space of the local environment. This figure is calculated by a set of points which sample the boundaries of the local free space. These points are obtained with range sensors and with knowledge about the robot s pose. A method based on generalized Hough transform is applied to this set of points in order to obtain the geomtric figure. The building of the hybrid map is an incremental procedure. It is accomplished while the robot explores the environment. Each room is associated with a metric local map and, consequently, with an edge of the topo-logical map. During the mapping procedure, the robot may use recent metric information of the environment to improve its global or relative pose

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This dissertation describes the use of new Technologies of the Areas of Telecommunications, Networks and Industrial Automation for increase of the Operational Safety and obtaining of Operational Improvements in the Platforms Petroliferous Offshore. The presented solution represents the junction of several modules of these areas, making possible the Supervision and Contrai of the Platforms Petroliferous Offshore starting from an Station Onshore, in way similar to a remote contral, by virtue of the visualization possibility and audition of the operational area through cameras and microphones, looking the operator of the system to be "present" in the platform. This way, it diminishes the embarked people's need, increasing the Operational Safety. As consequence, we have the obtaining of Operational Improvements, by virtue of the use of a digital link of large band it releases multi-service. In this link traffic simultaneously digital signs of data (Ethernet Network), telephony (Phone VoIP), image and sound

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This graduate thesis proposes a model to asynchronously replicate heterogeneous databases. This model singularly combines -in a systematic way and in a single project -different concepts, techniques and paradigms related to the areas of database replication and management of heterogeneous databases. One of the main advantages of the replication is to allow applications to continue to process information, during time intervals when they are off the network and to trigger the database synchronization, as soon as the network connection is reestablished. Therefore, the model introduces a communication and update protocol that takes in consideration the environment of asynchronous characteristics used. As part of the work, a tool was developed in Java language, based on the model s premises in order to process, test, simulate and validate the proposed model

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In recent decades, changes have been occurring in the telecommunications industry, allied to competition driven by the policies of privatization and concessions, have fomented the world market irrefutably causing the emergence of a new reality. The reflections in Brazil have become evident due to the appearance of significant growth rates, getting in 2012 to provide a net operating income of 128 billion dollars, placing the country among the five major powers in the world in mobile communications. In this context, an issue of increasing importance to the financial health of companies is their ability to retain their customers, as well as turn them into loyal customers. The appearance of infidelity from customer operators has been generating monthly rates shutdowns about two to four percent per month accounting for business management one of its biggest challenges, since capturing a new customer has meant an expenditure greater than five times to retention. For this purpose, models have been developed by means of structural equation modeling to identify the relationships between the various determinants of customer loyalty in the context of services. The original contribution of this thesis is to develop a model for loyalty from the identification of relationships between determinants of satisfaction (latent variables) and the inclusion of attributes that determine the perceptions of service quality for the mobile communications industry, such as quality, satisfaction, value, trust, expectation and loyalty. It is a qualitative research which will be conducted with customers of operators through simple random sampling technique, using structured questionnaires. As a result, the proposed model and statistical evaluations should enable operators to conclude that customer loyalty is directly influenced by technical and operational quality of the services offered, as well as provide a satisfaction index for the mobile communication segment

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This work presents simulation results of an identification platform compatible with the INPE Brazilian Data Collection System, modeled with SystemC-AMS. SystemC-AMS that is a library of C++ classes dedicated to the simulation of heterogeneous systems, offering a powerful resource to describe models in digital, analog and RF domains, as well as mechanical and optic. The designed model was divided in four parts. The first block takes into account the satellite s orbit, necessary to correctly model the propagation channel, including Doppler effect, attenuation and thermal noise. The identification block detects the satellite presence. It is composed by low noise amplifier, band pass filter, power detector and logic comparator. The controller block is responsible for enabling the RF transmitter when the presence of the satellite is detected. The controller was modeled as a Petri net, due to the asynchronous nature of the system. The fourth block is the RF transmitter unit, which performs the modulation of the information in BPSK ±60o. This block is composed by oscillator, mixer, adder and amplifier. The whole system was simulated simultaneously. The results are being used to specify system components and to elaborate testbenchs for design verification

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We propose a new approach to reduction and abstraction of visual information for robotics vision applications. Basically, we propose to use a multi-resolution representation in combination with a moving fovea for reducing the amount of information from an image. We introduce the mathematical formalization of the moving fovea approach and mapping functions that help to use this model. Two indexes (resolution and cost) are proposed that can be useful to choose the proposed model variables. With this new theoretical approach, it is possible to apply several filters, to calculate disparity and to obtain motion analysis in real time (less than 33ms to process an image pair at a notebook AMD Turion Dual Core 2GHz). As the main result, most of time, the moving fovea allows the robot not to perform physical motion of its robotics devices to keep a possible region of interest visible in both images. We validate the proposed model with experimental results

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Digital signal processing (DSP) aims to extract specific information from digital signals. Digital signals are, by definition, physical quantities represented by a sequence of discrete values and from these sequences it is possible to extract and analyze the desired information. The unevenly sampled data can not be properly analyzed using standard techniques of digital signal processing. This work aimed to adapt a technique of DSP, the multiresolution analysis, to analyze unevenly smapled data, to aid the studies in the CoRoT laboratory at UFRN. The process is based on re-indexing the wavelet transform to handle unevenly sampled data properly. The was efective presenting satisfactory results