Implementação de classificador de tarefas mentais baseado em EEG

BARBOSA, André F. ; SOUZA, Bryan C. ; PEREIRA JUNIOR, Antônio ; MEDEIROS, Adelardo A. D.de, . Implementação de Classificador de Tarefas Mentais Baseado em EEG. In: CONGRESSO BRASILEIRO DE REDES NEURAIS, 9., 2009, Ouro Preto, MG. Anais... Ouro Preto, MG, 2009

Análise filogenética e funcional de dois genes de reparo homólogos a AP endonuclease em cana-de-açúcar: ScARP1 e ScARP3

The genome of all organisms constantly suffers the influence of mutagenic factors from endogenous and/or exogenous origin, which may result in damage for the genome. In order to keep the genome integrity there are different DNA repair pathway to detect and correct these lesions. In relation to the plants as being sessile organisms, they are exposed to this damage frequently. The Base Excision DNA Repair (BER) is responsible to detect and repair oxidative lesions. Previous work in sugarcane identified two sequences that were homologous to Arabidopsis thaliana: ScARP1 ScARP3. These two sequences were homologous to AP endonuclease from BER pathway. Then, the aim of this work was to characterize these two sequence using different approaches: phylogenetic analysis, in silico protein organelle localization and by Nicotiana tabacum transgenic plants with overexpression cassette. The in silico data obtained showed a duplication of this sequence in sugarcane and Poaceae probably by a WGD event. Furthermore, in silico analysis showed a new localization in nuclei for ScARP1 protein. The data obtained with transgenic plants showed a change in development and morphology. Transgenic plants had slow development when compared to plants not transformed. Then, these results allowed us to understand better the potential role of this sequence in sugarcane and in plants in general. More work is important to be done in order to confirm the protein localization and protein characterization for ScARP1 and ScARP3

STREAM-AP: um processo para sistematizar a escolha de padrões arquiteturais baseado em requisitos não-funcionais

The importance of non-functional requirements for computer systems is increasing. Satisfying these requirements requires special attention to the software architecture, since an unsuitable architecture introduces greater complexity in addition to the intrinsic complexity of the system. Some studies have shown that, despite requirements engineering and software architecture activities act on different aspects of development, they must be performed iteratively and intertwined to produce satisfactory software systems. The STREAM process presents a systematic approach to reduce the gap between requirements and architecture development, emphasizing the functional requirements, but using the non-functional requirements in an ad hoc way. However, non-functional requirements typically influence the system as a whole. Thus, the STREAM uses Architectural Patterns to refine the software architecture. These patterns are chosen by using non-functional requirements in an ad hoc way. This master thesis presents a process to improve STREAM in making the choice of architectural patterns systematic by using non-functional requirements, in order to guide the refinement of a software architecture

Classificador neural híbrido para imagens obtidas por sensoriamento remoto

Remote sensing is one technology of extreme importance, allowing capture of data from the Earth's surface that are used with various purposes, including, environmental monitoring, tracking usage of natural resources, geological prospecting and monitoring of disasters. One of the main applications of remote sensing is the generation of thematic maps and subsequent survey of areas from images generated by orbital or sub-orbital sensors. Pattern classification methods are used in the implementation of computational routines to automate this activity. Artificial neural networks present themselves as viable alternatives to traditional statistical classifiers, mainly for applications whose data show high dimensionality as those from hyperspectral sensors. This work main goal is to develop a classiffier based on neural networks radial basis function and Growing Neural Gas, which presents some advantages over using individual neural networks. The main idea is to use Growing Neural Gas's incremental characteristics to determine the radial basis function network's quantity and choice of centers in order to obtain a highly effective classiffier. To demonstrate the performance of the classiffier three studies case are presented along with the results.

Detecção e diagnóstico de falhas não-supervisionados baseados em estimativa de densidade recursiva e classificador fuzzy auto-evolutivo

In this work, we propose a two-stage algorithm for real-time fault detection and identification of industrial plants. Our proposal is based on the analysis of selected features using recursive density estimation and a new evolving classifier algorithm. More specifically, the proposed approach for the detection stage is based on the concept of density in the data space, which is not the same as probability density function, but is a very useful measure for abnormality/outliers detection. This density can be expressed by a Cauchy function and can be calculated recursively, which makes it memory and computational power efficient and, therefore, suitable for on-line applications. The identification/diagnosis stage is based on a self-developing (evolving) fuzzy rule-based classifier system proposed in this work, called AutoClass. An important property of AutoClass is that it can start learning from scratch". Not only do the fuzzy rules not need to be prespecified, but neither do the number of classes for AutoClass (the number may grow, with new class labels being added by the on-line learning process), in a fully unsupervised manner. In the event that an initial rule base exists, AutoClass can evolve/develop it further based on the newly arrived faulty state data. In order to validate our proposal, we present experimental results from a level control didactic process, where control and error signals are used as features for the fault detection and identification systems, but the approach is generic and the number of features can be significant due to the computationally lean methodology, since covariance or more complex calculations, as well as storage of old data, are not required. The obtained results are significantly better than the traditional approaches used for comparison

Caracterização de dois cDNAs homológos e uma AP endonuclease em cana-de-açúcar

The genome of all organisms is subject to injuries that can be caused by endogenous and environmental factors. If these lesions are not corrected, it can be fixed generating a mutation which can be lethal to the organisms. In order to prevent this, there are different DNA repair mechanisms. These mechanisms are well known in bacteria, yeast, human, but not in plants. Two plant models Oriza sativa and Arabidopsis thaliana had the genome sequenced and due to this some DNA repair genes have been characterized. The aim of this work is to characterized two sugarcane cDNAs that had homology to AP endonuclease: scARP1 and scARP3. In silico has been done with these two sequences and other from plants. It has been observed domain conservation on these sequences, but the cystein at 65 position that is a characteristic from the redox domain in APE1 protein was not so conservated in plants. Phylogenetic relationship showed two branches, one branch with dicots and monocots sequence and the other branch with only monocots sequences. Another approach in order to characterized these two cDNAs was to construct overexpression cassettes (sense and antisense orientation) using the 35S promoter. After that, these cassettes were transferred to the binary vector pPZP211. Furthermore, previously in the laboratory was obtained a plant from nicotiana tabacum containing the overexpression cassette in anti-sense orientation. It has been observed that this plant had a slow development and problems in setting seeds. After some manual crossing, some seeds were obtained (T2) and it was analyzed the T2 segregation. The third approach used in this work was to clone the promoter region from these two cDNAs by PCR walking. The sequences obtained were analyzed using the program PLANTCARE. It was observed in these sequences some motives that may be related to oxidative stress response

Classificador máquina de suporte vetorial com análise de Fourier aplicada em dados de EEG e EMG

The classifier support vector machine is used in several problems in various areas of knowledge. Basically the method used in this classier is to end the hyperplane that maximizes the distance between the groups, to increase the generalization of the classifier. In this work, we treated some problems of binary classification of data obtained by electroencephalography (EEG) and electromyography (EMG) using Support Vector Machine with some complementary techniques, such as: Principal Component Analysis to identify the active regions of the brain, the periodogram method which is obtained by Fourier analysis to help discriminate between groups and Simple Moving Average to eliminate some of the existing noise in the data. It was developed two functions in the software R, for the realization of training tasks and classification. Also, it was proposed two weights systems and a summarized measure to help on deciding in classification of groups. The application of these techniques, weights and the summarized measure in the classier, showed quite satisfactory results, where the best results were an average rate of 95.31% to visual stimuli data, 100% of correct classification for epilepsy data and rates of 91.22% and 96.89% to object motion data for two subjects.

Implementação de classificador de tarefas mentais baseado em EEG

BARBOSA, André F. ; SOUZA, Bryan C. ; PEREIRA JUNIOR, Antônio ; MEDEIROS, Adelardo A. D.de, . Implementação de Classificador de Tarefas Mentais Baseado em EEG. In: CONGRESSO BRASILEIRO DE REDES NEURAIS, 9., 2009, Ouro Preto, MG. Anais... Ouro Preto, MG, 2009

Análise filogenética e funcional de dois genes de reparo homólogos a AP endonuclease em cana-de-açúcar: ScARP1 e ScARP3

The genome of all organisms constantly suffers the influence of mutagenic factors from endogenous and/or exogenous origin, which may result in damage for the genome. In order to keep the genome integrity there are different DNA repair pathway to detect and correct these lesions. In relation to the plants as being sessile organisms, they are exposed to this damage frequently. The Base Excision DNA Repair (BER) is responsible to detect and repair oxidative lesions. Previous work in sugarcane identified two sequences that were homologous to Arabidopsis thaliana: ScARP1 ScARP3. These two sequences were homologous to AP endonuclease from BER pathway. Then, the aim of this work was to characterize these two sequence using different approaches: phylogenetic analysis, in silico protein organelle localization and by Nicotiana tabacum transgenic plants with overexpression cassette. The in silico data obtained showed a duplication of this sequence in sugarcane and Poaceae probably by a WGD event. Furthermore, in silico analysis showed a new localization in nuclei for ScARP1 protein. The data obtained with transgenic plants showed a change in development and morphology. Transgenic plants had slow development when compared to plants not transformed. Then, these results allowed us to understand better the potential role of this sequence in sugarcane and in plants in general. More work is important to be done in order to confirm the protein localization and protein characterization for ScARP1 and ScARP3