Classificação Automática de Modulação Digital com uso de Correntropia para Ambientes de Rádio Cognitivo

Modern wireless systems employ adaptive techniques to provide high throughput while observing desired coverage, Quality of Service (QoS) and capacity. An alternative to further enhance data rate is to apply cognitive radio concepts, where a system is able to exploit unused spectrum on existing licensed bands by sensing the spectrum and opportunistically access unused portions. Techniques like Automatic Modulation Classification (AMC) could help or be vital for such scenarios. Usually, AMC implementations rely on some form of signal pre-processing, which may introduce a high computational cost or make assumptions about the received signal which may not hold (e.g. Gaussianity of noise). This work proposes a new method to perform AMC which uses a similarity measure from the Information Theoretic Learning (ITL) framework, known as correntropy coefficient. It is capable of extracting similarity measurements over a pair of random processes using higher order statistics, yielding in better similarity estimations than by using e.g. correlation coefficient. Experiments carried out by means of computer simulation show that the technique proposed in this paper presents a high rate success in classification of digital modulation, even in the presence of additive white gaussian noise (AWGN)

Algoritmos genéticos aplicados a um comitê de LS-SVM em problemas de classificação

The pattern classification is one of the machine learning subareas that has the most outstanding. Among the various approaches to solve pattern classification problems, the Support Vector Machines (SVM) receive great emphasis, due to its ease of use and good generalization performance. The Least Squares formulation of SVM (LS-SVM) finds the solution by solving a set of linear equations instead of quadratic programming implemented in SVM. The LS-SVMs provide some free parameters that have to be correctly chosen to achieve satisfactory results in a given task. Despite the LS-SVMs having high performance, lots of tools have been developed to improve them, mainly the development of new classifying methods and the employment of ensembles, in other words, a combination of several classifiers. In this work, our proposal is to use an ensemble and a Genetic Algorithm (GA), search algorithm based on the evolution of species, to enhance the LSSVM classification. In the construction of this ensemble, we use a random selection of attributes of the original problem, which it splits the original problem into smaller ones where each classifier will act. So, we apply a genetic algorithm to find effective values of the LS-SVM parameters and also to find a weight vector, measuring the importance of each machine in the final classification. Finally, the final classification is obtained by a linear combination of the decision values of the LS-SVMs with the weight vector. We used several classification problems, taken as benchmarks to evaluate the performance of the algorithm and compared the results with other classifiers

Medição da densidade óssea através de ondas eletromagnéticas e classificação por MVS

This work holds the purpose of presenting an auxiliary way of bone density measurement through the attenuation of electromagnetic waves. In order to do so, an arrangement of two microstrip antennas with rectangular configuration has been used, operating in a frequency of 2,49 GHz, and fed by a microstrip line on a substrate of fiberglass with permissiveness of 4.4 and height of 0,9 cm. Simulations were done with silica, bone meal, silica and gypsum blocks samples to prove the variation on the attenuation level of different combinations. Because of their good reproduction of the human beings anomaly aspects, samples of bovine bone were used. They were subjected to weighing, measurement and microwave radiation. The samples had their masses altered after mischaracterization and the process was repeated. The obtained data were inserted in a neural network and its training was proceeded with the best results gathered by correct classification on 100% of the samples. It comes to the conclusion that through only one non-ionizing wave in the 2,49 GHz zone it is possible to evaluate the attenuation level in the bone tissue, and that with the appliance of neural network fed with obtained characteristics in the experiment it is possible to classify a sample as having low or high bone density

Arquiteturas eficientes para sensoriamento espectral e classificação automática de modulações usando características cicloestacionárias

The increasing demand for high performance wireless communication systems has shown the inefficiency of the current model of fixed allocation of the radio spectrum. In this context, cognitive radio appears as a more efficient alternative, by providing opportunistic spectrum access, with the maximum bandwidth possible. To ensure these requirements, it is necessary that the transmitter identify opportunities for transmission and the receiver recognizes the parameters defined for the communication signal. The techniques that use cyclostationary analysis can be applied to problems in either spectrum sensing and modulation classification, even in low signal-to-noise ratio (SNR) environments. However, despite the robustness, one of the main disadvantages of cyclostationarity is the high computational cost for calculating its functions. This work proposes efficient architectures for obtaining cyclostationary features to be employed in either spectrum sensing and automatic modulation classification (AMC). In the context of spectrum sensing, a parallelized algorithm for extracting cyclostationary features of communication signals is presented. The performance of this features extractor parallelization is evaluated by speedup and parallel eficiency metrics. The architecture for spectrum sensing is analyzed for several configuration of false alarm probability, SNR levels and observation time for BPSK and QPSK modulations. In the context of AMC, the reduced alpha-profile is proposed as as a cyclostationary signature calculated for a reduced cyclic frequencies set. This signature is validated by a modulation classification architecture based on pattern matching. The architecture for AMC is investigated for correct classification rates of AM, BPSK, QPSK, MSK and FSK modulations, considering several scenarios of observation length and SNR levels. The numerical results of performance obtained in this work show the eficiency of the proposed architectures

Teoria semi-clássica para super rede magnética formada por materiais ferromagnético e antiferromagnético

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Anisotropia magnética (110) em Nanofilmes de Permalloy sobre MgO(100)

The study and fabrication of nanostructured systems composed of magnetic materials has been an area of great scientific and technological interest. Soft magnetic materials, in particular, have had great importance in the development of magnetic devices. Among such materials we highlight the use of alloys of Ni and Fe, known as Permalloy. We present measurement results of structural characterization and magnetic films in Permalloy (Ni81Fe19), known to be a material with high magnetic permeability, low coercivity and small magneto- crystalline anisotropy, deposited on MgO (100) substrates. The Magnetron Sputtering technique was used to obtain the samples with thicknesses varying between 9 150 nm. The techniques of X- ray Diffraction at high and low angle were employed to confirm the crystallographic orientation and thickness of the films. In order to investigate the magnetic properties of the films the techniques of Vibrant Sample Magnetometry (VSM), Ferromagnetic Resonance (FMR) and Magnetoimpedance were used. The magnetization curves revealed the presence of anisotropy for the films of Py/MgO (100), where it was found that there are three distinct axis - an easy-axis for θH = 0°, a hard-axis for θH = 45° and an intermediate for θH = 90°. The results of the FMR and Magnetoimpedance techniques confirm that there are three distinct axes, that is, there is a type C2 symmetry. Then we propose, for these results, the interpretation of the magnetic anisotropy of Py/MgO ( 100 ) is of type simple C2, ie a cubic magnetic anisotropy type ( 110 )

Caracterização magnética e estrutural de filmes depositados por gaiola catódica

Iron nitrite films, with hundred of nanometers thick, were deposited using the Cathodic cage plasma nitriding method, with a N2/H2 plasma, over a common glass substract. The structure, surface morphology and magnetic properties were investigated using X-ray diffractometry (XRD), atomic force microscopy (AFM) and vibrating sample magnetometer (VSM). XRD shows the formation of γ FeN phase and a combination of ζFe2N + ɛFe3N phases. The film s saturation magnetization and coercivity depends on morphology, composition, grain size and treatment temperature. Temperature raising from 250 ºC to 350 ºC were followed by an increase in saturation magnetization and film s surface coercivity on the parallel direction in relative proportion. This fact can be attributed to the grain sizes and to the different phases formed, since iron rich fases, like the ɛFe3N phase, emerges more frequently on more elevated treatment s temperature. Using this new and reasonably low cost method, it was possible to deposit films with both good adhesion and good magnetic properties, with wide application in magnetic devices

Alterações da default mode network provocadas pela ingestão de Ayahuasca investigadas por Ressonância Magnética Funcional

Ayahuasca is psychotropic beverage that has been used for ages by indigenous populations in South America, notably in the Amazon region, for religious and medicinal purposes. The tea is obtained by the decoction of leaves from the Psychotria viridis with the bark and stalk of a shrub, the Banisteriopsis caapi. The first is rich in N-N-dimethyltryptamine (DMT), which has an important and well-known hallucinogenic effect due to its agonistic action in serotonin receptors, specifically 5-HT2A. On the other hand, β-carbolines present in B. caapi, particularly harmine and harmaline, are potent monoamine oxidase inhibitors (MAOi). In addition, the tetrahydroharmine (THH), also present in B. caapi, acts as mild selective serotonin reuptake inhibitor and a weak MAOi. This unique composition induces a number of affective, sensitive, perceptual and cognitive changes in individuals under the effect of Ayahuasca. On the other hand, there is growing interest in the Default Mode Network (DMN), which has been consistently observed in functional neuroimaging studies. The key components of this network include structures in the brain midline, as the anterior medial frontal cortex, ventral medial frontal cortex, posterior cingulate cortex, precuneus, and some regions within the inferior parietal lobe and middle temporal gyrus. It has been argued that DMN participate in tasks involving self-judgments, autobiographical memory retrieval, mental simulations, thinking in perspective, meditative states, and others. In general, these tasks require an internal focus of attention, hence the conclusion that the DMN is associated with introspective mental activity. Therefore, this study aimed to evaluate by functional magnetic resonance imaging (fMRI) changes in DMN caused via the ingestion of Ayahuasca by 10 healthy subjects while submitted to two fMRI protocols: a verbal fluency task and a resting state acquisition. In general, it was observed that Ayahuasca causes a reduction in the fMRI signal in central nodes of DMN, such as the anterior cingulate cortex, the medial prefrontal cortex, the posterior cingulate cortex, precuneus and inferior parietal lobe. Furthermore, changes in connectivity patterns of the DMN were observed, especially a decrease in the functional connectivity of the precuneus. Together, these findings indicate an association between the altered state of consciousness experienced by individuals under the effect of Ayahuasca, and changes in the stream of spontaneous thoughts leading to an increased introspective mental activity

Avaliação por ressonância magnética funcional e estimulação magnética transcraniana da intervenção única da terapia espelho em pacientes após acidente vascular cerebral isquêmico

Mirror therapy (MT) is being used as a rehabilitation tool in various diseases, including stroke. Although some studies have shown its effectiveness, little is known about neural mechanisms that underlie the rehabilitation process. Therefore, this study aimed at assessing cortical neuromodulation after a single MT intervention in ischemic stroke survivors, by means of by functional Magnetic Resonance Imaging (fMRI) and Transcranial Magnetic Stimulation (TMS). Fifteen patients participated in a single thirty minutes MT session. fMRI data was analyzed bilaterally in the following Regions of Interest (ROI): Supplementary Motor Area (SMA), Premotor cortex (PMC), Primary Motor cortex (M1), Primary Sensory cortex (S1) and Cerebellum. In each ROI, changes in the percentage of occupation and beta values were computed. Group fMRI data showed a significant decreased in the percentage of occupation in PMC and cerebellum, contralateral to the affected hand (p <0.05). Significant increase in beta values was observed in the following contralateral motor areas: SMA, Cerebellum, PMC and M1 (p<0,005). Moreover, a significant decrease was observed in the following ipsilateral motor areas: PMC and M1 (p <0,001). In S1 a bilateral significant decrease (p<0.0005) was observed.TMS consisted of the analysis of Motor Evoked Potential (MEP) of M1 hotspot. A significant increase in the amplitude of the MEP was observed after therapy in the group (p<0,0001) and individually in 4 patients (p <0.05). Altogether, our results imply that single MT intervention is already capable of promoting changes in neurobiological markers toward patterns observed in healthy subjects. Furthermore, the contralateral hemisphere motor areas changes are opposite to the ones in the ipsilateral side, suggesting an increase system homeostasis.

Estudo comportamental, hormonal e histopatológico de animais com perda de peso progressina (SEP) e da variável peso associada a uma nova classificação ontogenética em Callithrix jacchus

The use of non-human primates in scientific research has contributed significantly to the biomedical area and, in the case of Callithrix jacchus, has provided important evidence on physiological mechanisms that help explain its biology, making the species a valuable experimental model in different pathologies. However, raising non-human primates in captivity for long periods of time is accompanied by behavioral disorders and chronic diseases, as well as progressive weight loss in most of the animals. The Primatology Center of the Universidade Federal do Rio Grande do Norte (UFRN) has housed a colony of C. jacchus for nearly 30 years and during this period these animals have been weighed systematically to detect possible alterations in their clinical conditions. This procedure has generated a volume of data on the weight of animals at different age ranges. These data are of great importance in the study of this variable from different perspectives. Accordingly, this paper presents three studies using weight data collected over 15 years (1985-2000) as a way of verifying the health status and development of the animals. The first study produced the first article, which describes the histopathological findings of animals with probable diagnosis of permanent wasting marmoset syndrome (WMS). All the animals were carriers of trematode parasites (Platynosomum spp) and had obstruction in the hepatobiliary system; it is suggested that this agent is one of the etiological factors of the syndrome. In the second article, the analysis focused on comparing environmental profile and cortisol levels between the animals with normal weight curve evolution and those with WMS. We observed a marked decrease in locomotion, increased use of lower cage extracts and hypocortisolemia. The latter is likely associated to an adaptation of the mechanisms that make up the hypothalamus-hypophysis-adrenal axis, as observed in other mammals under conditions of chronic malnutrition. Finally, in the third study, the animals with weight alterations were excluded from the sample and, using computational tools (K-means and SOM) in a non-supervised way, we suggest found new ontogenetic development classes for C. jacchus. These were redimensioned from five to eight classes: infant I, infant II, infant III, juvenile I, juvenile II, sub-adult, young adult and elderly adult, in order to provide a more suitable classification for more detailed studies that require better control over the animal development

Publicação e avaliação de periódicos científicos: paradoxos da classificação Qualis em Psicologia

Recently, Brazilian scientific production has increased greatly, due to demands for productivity from scientific agencies. However, this high increases requires a more qualified production, since it s essential that publications are relevant and original. In the psychological field, the assessment scientific journals of the CAPES/ANPEPP Commission had a strong effect on the scientific community and raised questions about the chosen evaluation method. Considering this impact, the aim of this research is a meta-analysis on the assessment of Psychological journals by CAPES to update the Qualis database. For this research, Psychology scientific editors (38 questionnaires were applied by e-mail) were consulted, also 5 librarians who work with scientific journals assessment (semi-structured interviews) and 8 members who acted as referees in the CAPES/ANPEPP Commission (open questions were sent by e-mail). The results are shown through 3 analysis: general evaluation of the Qualis process (including the Assessment Committee constitution), evaluation criteria used in the process and the effect of the evaluation on the scientific community (changes on the editing scene included). Some important points emerged: disagreement among different actors about the suitability of this evaluation model; the recognition of the improvement of scientific journals, mainly toward normalization and diffusion; the verification that the model does not point the quality of the journal, i.e., the content of the scientific articles published in the journal; the disagreement with the criteria used, seemed necessary and useful but needed to be discussed and cleared between the scientific community. Despite these points, the scientific journals evaluation still is the main method to assure quality for Psychology publications

Ferramentas quimiométricas aplicadas a classificação de amostras de leite em pó e quantificação de proteínas

In this work we used chemometric tools to classify and quantify the protein content in samples of milk powder. We applied the NIR diffuse reflectance spectroscopy combined with multivariate techniques. First, we carried out an exploratory method of samples by principal component analysis (PCA), then the classification of independent modeling of class analogy (SIMCA). Thus it became possible to classify the samples that were grouped by similarities in their composition. Finally, the techniques of partial least squares regression (PLS) and principal components regression (PCR) allowed the quantification of protein content in samples of milk powder, compared with the Kjeldahl reference method. A total of 53 samples of milk powder sold in the metropolitan areas of Natal, Salvador and Rio de Janeiro were acquired for analysis, in which after pre-treatment data, there were four models, which were employed for classification and quantification of samples. The methods employed after being assessed and validated showed good performance, good accuracy and reliability of the results, showing that the NIR technique can be a non invasive technique, since it produces no waste and saves time in analyzing the samples

Uso de confiabilidade na rotulação de exemplos em problemas de classificação multirrótulo com aprendizado semissupervisionado

The techniques of Machine Learning are applied in classification tasks to acquire knowledge through a set of data or information. Some learning methods proposed in literature are methods based on semissupervised learning; this is represented by small percentage of labeled data (supervised learning) combined with a quantity of label and non-labeled examples (unsupervised learning) during the training phase, which reduces, therefore, the need for a large quantity of labeled instances when only small dataset of labeled instances is available for training. A commom problem in semi-supervised learning is as random selection of instances, since most of paper use a random selection technique which can cause a negative impact. Much of machine learning methods treat single-label problems, in other words, problems where a given set of data are associated with a single class; however, through the requirement existent to classify data in a lot of domain, or more than one class, this classification as called multi-label classification. This work presents an experimental analysis of the results obtained using semissupervised learning in troubles of multi-label classification using reliability parameter as an aid in the classification data. Thus, the use of techniques of semissupervised learning and besides methods of multi-label classification, were essential to show the results

Síntese e caracterização estrutural e magnética da ferrita de cálcio

The calcium ferrite (Ca2Fe2O5) has a perovskite-type structure with oxygen deficiency and is used as a chemical catalyst. With the advent of nanoscience and nanotechnology, methods of preparation, physical and chemical characterizations, and the technological applications of nanoparticles have attracted great scientific interest. Calcium nanostructured ferrites were produced via high-energy milling, with subsequent heat treatment. The milling products were characterized by X-ray diffraction, magnetization and Mössbauer spectroscopy. Samples of the type Ca2Fe2O5 were obtained from the CaCO3 and Fe2O3 powder precursors, which were mixed stoichiometrically and milled for 10h and thermally treated at 700ºC, 900ºC and 1100ºC. The Mössbauer spectra of the treated samples were adjusted three subespectros: calcium ferrite (octahedral and tetrahedral sites) and a paramagnetic component, related to very small particles of calcium ferrite, which are in a superparamagnetic state. For samples beats in an atmosphere of methyl alcohol, there is a significant increase in area associated with the paramagnetic component. Hysteresis curves obtained are characteristic of a weak ferromagnetic-like material

Investigando a combinação de técnicas de aprendizado semissupervisionado e classificação hierárquica multirrótulo

Data classification is a task with high applicability in a lot of areas. Most methods for treating classification problems found in the literature dealing with single-label or traditional problems. In recent years has been identified a series of classification tasks in which the samples can be labeled at more than one class simultaneously (multi-label classification). Additionally, these classes can be hierarchically organized (hierarchical classification and hierarchical multi-label classification). On the other hand, we have also studied a new category of learning, called semi-supervised learning, combining labeled data (supervised learning) and non-labeled data (unsupervised learning) during the training phase, thus reducing the need for a large amount of labeled data when only a small set of labeled samples is available. Thus, since both the techniques of multi-label and hierarchical multi-label classification as semi-supervised learning has shown favorable results with its use, this work is proposed and used to apply semi-supervised learning in hierarchical multi-label classication tasks, so eciently take advantage of the main advantages of the two areas. An experimental analysis of the proposed methods found that the use of semi-supervised learning in hierarchical multi-label methods presented satisfactory results, since the two approaches were statistically similar results