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

Indicadores de cálcio e de voltagem codificados geneticamente na detecção de potenciais de ação e inputs sinápticos em cultura de neurônios hipocampais

Recently, genetically encoded optical indicators have emerged as noninvasive tools of high spatial and temporal resolution utilized to monitor the activity of individual neurons and specific neuronal populations. The increasing number of new optogenetic indicators, together with the absence of comparisons under identical conditions, has generated difficulty in choosing the most appropriate protein, depending on the experimental design. Therefore, the purpose of our study was to compare three recently developed reporter proteins: the calcium indicators GCaMP3 and R-GECO1, and the voltage indicator VSFP butterfly1.2. These probes were expressed in hippocampal neurons in culture, which were subjected to patchclamp recordings and optical imaging. The three groups (each one expressing a protein) exhibited similar values of membrane potential (in mV, GCaMP3: -56 ±8.0, R-GECO1: -57 ±2.5; VSFP: -60 ±3.9, p = 0.86); however, the group of neurons expressing VSFP showed a lower average of input resistance than the other groups (in Mohms, GCaMP3: 161 ±18.3; GECO1-R: 128 ±15.3; VSFP: 94 ±14.0, p = 0.02). Each neuron was submitted to current injections at different frequencies (10 Hz, 5 Hz, 3 Hz, 1.5 Hz, and 0.7 Hz) and their fluorescence responses were recorded in time. In our study, only 26.7% (4/15) of the neurons expressing VSFP showed detectable fluorescence signal in response to action potentials (APs). The average signal-to-noise ratio (SNR) obtained in response to five spikes (at 10 Hz) was small (1.3 ± 0.21), however the rapid kinetics of the VSFP allowed discrimination of APs as individual peaks, with detection of 53% of the evoked APs. Frequencies below 5 Hz and subthreshold signals were undetectable due to high noise. On the other hand, calcium indicators showed the greatest change in fluorescence following the same protocol (five APs at 10 Hz). Among the GCaMP3 expressing neurons, 80% (8/10) exhibited signal, with an average SNR value of 21 ±6.69 (soma), while for the R-GECO1 neurons, 50% (2/4) of the neurons had signal, with a mean SNR value of 52 ±19.7 (soma). For protocols at 10 Hz, 54% of the evoked APs were detected with GCaMP3 and 85% with R-GECO1. APs were detectable in all the analyzed frequencies and fluorescence signals were detected from subthreshold depolarizations as well. Because GCaMP3 is the most likely to yield fluorescence signal and with high SNR, some experiments were performed only with this probe. We demonstrate that GCaMP3 is effective in detecting synaptic inputs (involving Ca2+ influx), with high spatial and temporal resolution. Differences were also observed between the SNR values resulting from evoked APs, compared to spontaneous APs. In recordings of groups of cells, GCaMP3 showed clear discrimination between activated and silent cells, and reveals itself as a potential tool in studies of neuronal synchronization. Thus, our results indicate that the presently available calcium indicators allow detailed studies on neuronal communication, ranging from individual dendritic spines to the investigation of events of synchrony in neuronal networks genetically defined. In contrast, studies employing VSFPs represent a promising technology for monitoring neural activity and, although still to be improved, they may become more appropriate than calcium indicators, since neurons work on a time scale faster than events of calcium may foresee

Estudo do potencial da técnica de nanossísmica para o monitoramento de hidrofraturamento em reservatórios de hidrocarbonetos

Hydraulic fracturing is an operation in which pressurised fluid is injected in the geological formation surrounding the producing well to create new permeable paths for hydrocarbons. The injection of such fluids in the reservoir induces seismic events. The measurement of this reservoir stimulation can be made by location these induced microseismic events. However, microseismic monitoring is an expensive operation because the acquisition and data interpretation system using in this monitoring rely on high signal-to-noise ratios (SNR). In general, the sensors are deployed in a monitoring well near the treated well and can make a microseismic monitoring quite an expensive operation. In this dissertation we propose the application of a new method for recording and location of microseismic events called nanoseismic monitoring (Joswig, 2006). In this new method, a continuous recording is performed and the interpreter can separate events from noise using sonograms. This new method also allows the location of seismic sources even when P and S phases onsets are not clear like in situations of 0 dB SNR. The clear technical advantage of this new method is also economically advantageous since the sensors can potentially be installed on the surface rather than in observation well. In this dissertation field tests with controlled sources were made. In the first test small explosives using fire works at 28 m (slant distances) were detected yealding magnitudes between -2.4 ≤ ML ≤ -1.6.. In a second test, we monitored perforation shots in a producing oil field. In this second test, one perforation shot was located with slant distances of 861 m and magnitude 2.4 ML. Data from the tests allow us to say that the method has potential to be used in the oil industry to monitor hydrofracture