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

Caracterização comportamental endócrina das fases ontogenéticas de sagüi comum (Callithrix jacchus)

The use of animal models in biomedical research is ever increasing. Models that use primates might also have advantages in terms of low maintenance costs and availability of biological knowledge, thereby favoring their use in different experimental protocols. Many current stress studies use animal models at different developmental stages since biological response differs during ontogeny. The aims of this study were to perform a detailed characterization of the developmental stages of common marmosets (Callithrix jacchus), a very important animal model used in biomedical research. Ten subjects, 6 females and 4 males, were followed from birth to initial adult age (16 months). Behavioral and fecal collection for measurement of adrenal (cortisol) and sex (progesterone, estradiol and androgens) hormones took place twice a week during the first month of life and once a week for the remainder of the study. Behavior was observed for 30 minutes in the morning (0700-09:00h) and afternoon (12:00-14:00h). Behavioral profile showed changes during ontogeny, characterizing the 4 developmental stages and the respective phases proposed by Leão et al (2009).. Differentiation of developmental stages was considered using the onset, end, change and stabilization of the behavioral profile parental care (weaning and carrying), ingestion (solid food), affiliation (social grooming) and autogrooming, agonism (scent marking and piloerection) and play behavior and endocrine profile. Infant weaning and carrying terminated within the infantile stage and the peak of solid food ingestion was recorded in the infantile III phase. Receiving grooming was recorded earlier than grooming performed by the infant and autogrooming. The first episode of scent marking was recorded in the 4th week and it was the least variable behavior, in terms of its onset, which, in almost all animals, was between the 5th and 7th week of life. Solitary play and play with the twin started around the 7th week and play with other members of the group started 8 weeks later. Sex hormone secretion started to differ from basal levels between the 21st and 23rd week of life, in males and females, suggesting that puberty occurs simultaneously in both sexes. Basal cortisol, even at an early age, was higher in females than in males. However, cortisol was not correlated with the juvenile stage, as expected, since this stage corresponds to the transition between infancy and adult age and most behaviors are intensified by this time. The behavioral and endocrine profile of subadult animals did not differ from that of the adults. These results provide more detailed parameters for the developmental process of C. jacchus and open new perspectives for the use of experimental approaches focused on the intermediate ontogenetic phases of this species

Padrão de atividades e de interações sociais de animais juvenis em dois grupos selvagens de Callithrix jacchus

The juvenile period represents the developmental phase between weaning and sexual maturity. Weaning occurs when the youngster does not receive direct care from the caretakers anymore. Individuals in the species Callithrix jacchus live in groups composed by the reproductive pair and successive twin sets. Cooperative care is the rule. Infants are weaned early, and from then on, food is provided by the adults in the group. These animals present high levels of social interactions, through play, grooming and social contact. During infant age, the twin becomes the main partner. There are few studies about the juvenile period, especially on Callithrix gender. The objective of this study was describing the pattern of activities and social interactions of four sets (one single and three twin sets) during juvenile phase in two Callithrix jacchus groups. We used instantaneous and continuous focal sampling for juveniles and scan sampling for adults behavioral recordings. Juveniles presented the same behavioral pattern as the adults relating the activity budget, in particular, foraging along the months. The composition of the diet was the same as that of the adults. Food transfer ended along the juvenile period. Social play as much as grooming were important socializing activities for the juveniles. The young individuals in the group were the main partners in social play, specially the twin. Adults were the main partners in grooming interactions. Scent marking differed between twins in the male/female sets, the female presenting the highest levels of marking. The juveniles were independent from adults in foraging activity. Social interaction varied according to group composition, but in general, interacted more with the twin and with the youngsters (infants and subadults), except in grooming. Even presenting many similarities, juveniles showed some differences between genders, which indicates the differentiation in behavior towards reproductive strategies early in the juvenile period

Estudo dos efeitos comportamentais do neuropeptídeos em camundongos submetidos a modelos animais de Parkinson

Neuropeptide S (NPS) is the endogenous ligand of a G-protein coupled receptor. Preclinical studies have shown that NPSR receptor activation can promote arousal, anxiolytic-like behavioral, decrease in food intake, besides hyperlocomotion, which is a robust but not well understood phenomenon. Previous findings suggest that dopamine transmission plays a crucial role in NPS hyperactivity. Considering the close relationship between dopamine and Parkinson Disease (PD), and also that NPSR receptors are expressed on dopaminergic nuclei in the brain, the current study attempted to investigate the effects of NPS in motor deficits induced by intracerebroventricular (icv) administration of 6-OHDA and systemic administration of haloperidol. Motor deficits induced by 6-OHDA and haloperidol were evaluated on Swiss mice in the rota-rod and catalepsy test. Time on the rotating rod and time spent immobile in the elevated bar were measured respectively in each test. L-Dopa, a classic antiparkinsonian drug, and NPS were administrated in mice submitted to one of the animal models of PD related above. 6-OHDA injection evoked severe motor impairments in rota-rod test, while the cataleptic behavior of 6-OHDA injected mice was largely variable. The administration of L-Dopa (25 mg/kg) and NPS (0,1 and 1 nmol) reversed motor impairments induced by 6-OHDA in the rota-rod. Haloperidolinduced motor deficits on rota-rod and catalepsy tests which were reversed by L-Dopa (100 e 400 mg/kg), but not by NPS (0,1 and 1 nmol) administration. The association of L-Dopa 10 mg/kg and NPS 1 nmol was also unable to counteract haloperidol-induced motor deficits. To summarize, 6-OHDA-, but not haloperidol-, induced motor deficits were reversed by the central administration of NPS. These data suggest that NPS possibly facilitates dopamine release in basal ganglia, what would explain the overcome of motor performance promoted by NPS administration in animals pretreated with 6-OHDA, but not haloperidol. Finally, the presented findings point, for the first time, to the potential of NPSR agonist as an innovative treatment for PD.

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

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