928 resultados para Computational Intelligence System
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The second main cause of death in Brazil is cancer, and according to statistics disclosed by National Cancer Institute from Brazil (INCA) 466,730 new cases of cancer are forecast for 2008. The analysis of tumour tissues of various types and patients' clinical data, genetic profiles, characteristics of diseases and epidemiological data may lead to more precise diagnoses, providing more effective treatments. In this work we present a clinical decision support system for cancer diseases, which manages a relational database containing information relating to the tumour tissue and their location in freezers, patients and medical forms. Furthermore, it is also discussed some problems encountered, as database integration and the adoption of a standard to describe topography and morphology. It is also discussed the dynamic report generation functionality, that shows data in table and graph format, according to the user's configuration. © ACM 2008.
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This paper describes the development of a mechatronic system for a predictive maintenance grounded on wear particle analysis. The reckoning of wear particles containing in lubricating industrial oils brings the image acquisition system into being. The ISO 4406:1999 standard is a guide to establish the counting and evaluation processes of particles. The system applied to the acquisition and analysis of the data consists of a digital camera, a monocular microscope and an oil filtering system. A computational program was developed with the application of Visual Microsoft C++ in a way to detain the oil sample image from the microscope slide to the computer screen. Quantitative analyses of the wear debris particles bulk are exploited applying a graphical interface that was developed to render the image processing of the sample test. The implemented system has a reachable cost thus it can be applied for schooling goals and for bolstering laboratories of minor industries and medium size companies.
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The constant increase in digital systems complexity definitely demands the automation of the corresponding synthesis process. This paper presents a computational environment designed to produce both software and hardware implementations of a system. The tool for code generation has been named ACG8051. As for the hardware synthesis there has been produced a larger environment consisting of four programs, namely: PIPE2TAB, AGPS, TABELA, and TAB2VHDL. ACG8051 and PIPE2TAB use place/transition net descriptions from PIPE as inputs. ACG8051 is aimed at generating assembly code for the 8051 micro-controller. PIPE2TAB produces a tabular version of a Mealy type finite state machine of the system, its output is fed into AGPS that is used for state allocation. The resulting digital system is then input to TABELA, which minimizes control functions and outputs of the digital system. Finally, the output generated by TABELA is fed to TAB2VHDL that produces a VHDL description of the system at the register transfer level. Thus, we present here a set of tools designed to take a high-level description of a digital system, represented by a place/transition net, and produces as output both an assembly code that can be immediately run on an 8051 micro-controller, and a VHDL description that can be used to directly implement the hardware parts either on an FPGA or as an ASIC.
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Cuttings return analysis is an important tool to detect and prevent problems during the petroleum well drilling process. Several measurements and tools have been developed for drilling problems detection, including mud logging, PWD and downhole torque information. Cuttings flow meters were developed in the past to provide information regarding cuttings return at the shale shakers. Their use, however, significantly impact the operation including rig space issues, interferences in geological analysis besides, additional personel required. This article proposes a non intrusive system to analyze the cuttings concentration at the shale shakers, which can indicate problems during drilling process, such as landslide, the collapse of the well borehole walls. Cuttings images are acquired by a high definition camera installed above the shakers and sent to a computer coupled with a data analysis system which aims the quantification and closure of a cuttings material balance in the well surface system domain. No additional people at the rigsite are required to operate the system. Modern Artificial intelligence techniques are used for pattern recognition and data analysis. Techniques include the Optimum-Path Forest (OPF), Artificial Neural Network using Multilayer Perceptrons (ANN-MLP), Support Vector Machines (SVM) and a Bayesian Classifier (BC). Field test results conducted on offshore floating vessels are presented. Results show the robustness of the proposed system, which can be also integrated with other data to improve the efficiency of drilling problems detection. Copyright 2010, IADC/SPE Drilling Conference and Exhibition.
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One of the critical problems in implementing an intelligent grinding process is the automatic detection of workpiece surface burn. This work uses fuzzy logic as a tool to classify and predict burn levels in the grinding process. Based on acoustic emission signals, cutting power, and the mean-value deviance (MVD), linguistic rules were established for the various burn situations (slight, intermediate, severe) by applying fuzzy logic using the Matlab Toolbox. Three practical fuzzy system models were developed. The first model with two inputs resulted only in a simple analysis process. The second and third models have an additional MVD statistic input, associating information and precision. These two models differ from each other in terms of the rule base developed. The three developed models presented valid responses, proving effective, accurate, reliable and easy to use for the determination of ground workpiece burn. In this analysis, fuzzy logic translates the operator's human experience associated with powerful computational methods.
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This paper analyzes the non-linear dynamics of a MEMS Gyroscope system, modeled with a proof mass constrained to move in a plane with two resonant modes, which are nominally orthogonal. The two modes are ideally coupled only by the rotation of the gyro about the plane's normal vector. We demonstrated that this model has an unstable behavior. Control problems consist of attempts to stabilize a system to an equilibrium point, a periodic orbit, or more general, about a given reference trajectory. We also developed a particle swarm optimization technique for reducing the oscillatory movement of the nonlinear system to a periodic orbit. © 2010 Springer-Verlag.
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Numerous researchers have studied about nonlinear dynamics in several areas of science and engineering. However, in most cases, these concepts have been explored mainly from the standpoint of analytical and computational methods involving integer order calculus (IOC). In this paper we have examined the dynamic behavior of an elastic wide plate induced by two electromagnets of a point of view of the fractional order calculus (FOC). The primary focus of this study is on to help gain a better understanding of nonlinear dynamic in fractional order systems. © 2011 American Institute of Physics.
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Intrusion detection systems that make use of artificial intelligence techniques in order to improve effectiveness have been actively pursued in the last decade. Neural networks and Support Vector Machines have been also extensively applied to this task. However, their complexity to learn new attacks has become very expensive, making them inviable for a real time retraining. In this research, we introduce a new pattern classifier named Optimum-Path Forest (OPF) to this task, which has demonstrated to be similar to the state-of-the-art pattern recognition techniques, but extremely more efficient for training patterns. Experiments on public datasets showed that OPF classifier may be a suitable tool to detect intrusions on computer networks, as well as allow the algorithm to learn new attacks faster than the other techniques. © 2011 IEEE.
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Malicious programs (malware) can cause severe damage on computer systems and data. The mechanism that the human immune system uses to detect and protect from organisms that threaten the human body is efficient and can be adapted to detect malware attacks. In this paper we propose a system to perform malware distributed collection, analysis and detection, this last inspired by the human immune system. After collecting malware samples from Internet, they are dynamically analyzed so as to provide execution traces at the operating system level and network flows that are used to create a behavioral model and to generate a detection signature. Those signatures serve as input to a malware detector, acting as the antibodies in the antigen detection process. This allows us to understand the malware attack and aids in the infection removal procedures. © 2012 Springer-Verlag.
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Based on literature review, electronic systems design employ largely top-down methodology. The top-down methodology is vital for success in the synthesis and implementation of electronic systems. In this context, this paper presents a new computational tool, named BD2XML, to support electronic systems design. From a block diagram system of mixed-signal is generated object code in XML markup language. XML language is interesting because it has great flexibility and readability. The BD2XML was developed with object-oriented paradigm. It was used the AD7528 converter modeled in MATLAB / Simulink as a case study. The MATLAB / Simulink was chosen as a target due to its wide dissemination in academia and industry. From this case study it is possible to demonstrate the functionality of the BD2XML and make it a reflection on the design challenges. Therefore, an automatic tool for electronic systems design reduces the time and costs of the design.
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The software industry has become more and more concerned with the appropriate application of activities that composes requirement engineering as a way to improve the quality of its products. In order to support these activities, several computational tools have been available in the market, although it is still possible to find a lack of resources related to some activities. In this context, this paper proposes the inclusion of a module to aid in the requirements specification to a tool called Requirements Elicitation Support Tool. This module allows to specify requirements in accordance with IEEE 830 standard, thus contributing to the documentation of the requirements established for a software system, besides supporting the learning of concepts related to the requirements specification, which improves the skills of users of the tool. © 2012 IEEE.
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In the last thirty years, a relatively large group of cognitive scientists have begun characterising the mind in terms of two distinct, relatively autonomous systems. To account for paradoxes in empirical results of studies mainly on reasoning, Dual Process Theories were developed. Such Dual Process Theories generally agree that System 1 is rapid, automatic, parallel, and heuristic-based and System 2 is slow, capacity-demanding, sequential, and related to consciousness. While System 2 can still be decently understood from a traditional cognitivist approach, I will argue that it is essential for System 1 processing to be comprehended in an Embodied Embedded approach to Cognition.© MSM 2013.
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The increase in the number of spatial data collected has motivated the development of geovisualisation techniques, aiming to provide an important resource to support the extraction of knowledge and decision making. One of these techniques are 3D graphs, which provides a dynamic and flexible increase of the results analysis obtained by the spatial data mining algorithms, principally when there are incidences of georeferenced objects in a same local. This work presented as an original contribution the potentialisation of visual resources in a computational environment of spatial data mining and, afterwards, the efficiency of these techniques is demonstrated with the use of a real database. The application has shown to be very interesting in interpreting obtained results, such as patterns that occurred in a same locality and to provide support for activities which could be done as from the visualisation of results. © 2013 Springer-Verlag.
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Feature selection aims to find the most important information from a given set of features. As this task can be seen as an optimization problem, the combinatorial growth of the possible solutions may be inviable for a exhaustive search. In this paper we propose a new nature-inspired feature selection technique based on the Charged System Search (CSS), which has never been applied to this context so far. The wrapper approach combines the power of exploration of CSS together with the speed of the Optimum-Path Forest classifier to find the set of features that maximizes the accuracy in a validating set. Experiments conducted in four public datasets have demonstrated the validity of the proposed approach can outperform some well-known swarm-based techniques. © 2013 Springer-Verlag.
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Pós-graduação em Ciência da Computação - IBILCE