Rectification and signal averaging of weak electric fields by biological cells.

Oscillating electric fields can be rectified by proteins in cell membranes to give rise to a dc transport of a substance across the membrane or a net conversion of a substrate to a product. This provides a basis for signal averaging and may be important for understanding the effects of weak extremely low frequency (ELF) electric fields on cellular systems. We consider the limits imposed by thermal and "excess" biological noise on the magnitude and exposure duration of such electric field-induced membrane activity. Under certain circumstances, the excess noise leads to an increase in the signal-to-noise ratio in a manner similar to processes labeled "stochastic resonance." Numerical results indicate that it is difficult to reconcile biological effects with low field strengths.

Detectivity comparison of bolometric optical antennas

The practical application of optical antennas in detection devices strongly depends on its ability to produce an acceptable signal-to-noise ratio for the given task. It is known that, due to the intrinsic problems arising from its sub-wavelength dimensions, optical antennas produce very small signals. The quality of these signals depends on the involved transduction mechanism. The contribution of different types of noise should be adapted to the transducer and to the signal extraction regime. Once noise is evaluated and measured, the specific detectivity, D*, becomes the parameter of interest when comparing the performance of antenna coupled devices with other detectors. However, this parameter involves some magnitudes that can be defined in several ways for optical antennas. In this contribution we are interested in the evaluation and comparison of D_ values for several bolometric optical antennas working in the infrared and involving two materials. At the same time, some material and geometrical parameters involved in the definition of noise and detectivity will be discussed to analyze the suitability of D_ to properly account for the performance of optical antennas.

Signal Processing Techniques for Chipless UWB RFID Thermal Threshold Detector Detection.

This letter presents signal processing techniques to detect a passive thermal threshold detector based on a chipless time-domain ultrawideband (UWB) radio frequency identification (RFID) tag. The tag is composed by a UWB antenna connected to a transmission line, in turn loaded with a biomorphic thermal switch. The working principle consists of detecting the impedance change of the thermal switch. This change occurs when the temperature exceeds a threshold. A UWB radar is used as the reader. The difference between the actual time sample and a reference signal obtained from the averaging of previous samples is used to determine the switch transition and to mitigate the interferences derived from clutter reflections. A gain compensation function is applied to equalize the attenuation due to propagation loss. An improved method based on the continuous wavelet transform with Morlet wavelet is used to overcome detection problems associated to a low signal-to-noise ratio at the receiver. The average delay profile is used to detect the tag delay. Experimental measurements up to 5 m are obtained.

The performance of the maximum ratio combining method in correlated Rician-fading channels for antenna-diversity signal combining

The performance of the maximum ratio combining method for the combining of antenna-diversity signals in correlated Rician-fading channels is rigorously studied. The distribution function of the normalized signal-to-noise ratio (SNR) is expanded in terms of a power series and calculated numerically. This power series can easily take into account the signal correlations and antenna gains and can be applied to any number of receiving antennas. An application of the method to dual-antenna diversity systems produces useful distribution curves for the normalized SNR which can be used to find the diversity gain. It is revealed that signal correlation in Rician-fading channels helps to increase the diversity gain rather than to decrease it as in the Rayleigh fading channels. It is also shown that with a relative strong direct signal component, the diversity gain can be much higher than that without a direct signal component.

Analytical BER performance in differential n-PSK coherent transmission system influenced by equalization enhanced phase noise

Long-haul high speed optical transmission systems are significantly distorted by the interplay between the electronic chromatic dispersion (CD) equalization and the local oscillator (LO) laser phase noise, which leads to an effect of equalization enhanced phase noise (EEPN). The EEPN degrades the performance of optical communication systems severely with the increment of fiber dispersion, LO laser linewidth, symbol rate, and modulation format. In this paper, we present an analytical model for evaluating the performance of bit-error-rate (BER) versus signal-to-noise ratio (SNR) in the n-level phase shift keying (n-PSK) coherent transmission system employing differential carrier phase estimation (CPE), where the influence of EEPN is considered. Theoretical results based on this model have been investigated for the differential quadrature phase shift keying (DQPSK), the differential 8-PSK (D8PSK), and the differential 16-PSK (D16PSK) coherent transmission systems. The influence of EEPN on the BER performance in term of the fiber dispersion, the LO phase noise, the symbol rate, and the modulation format are analyzed in detail. The BER behaviors based on this analytical model achieve a good agreement with previously reported BER floors influenced by EEPN. Further simulations have also been carried out in the differential CPE considering EEPN. The results indicate that this analytical model can give an accurate prediction for the DQPSK system, and a leading-order approximation for the D8PSK and the D16PSK systems.

Fibre impairment compensation using artificial neural network equalizer for high-capacity coherent optical OFDM signals

We propose an artificial neural network (ANN) equalizer for transmission performance enhancement of coherent optical OFDM (C-OOFDM) signals. The ANN equalizer showed more efficiency in combating both chromatic dispersion (CD) and single-mode fibre (SMF)-induced non-linearities compared to the least mean square (LMS). The equalizer can offer a 1.5 dB improvement in optical signal-to-noise ratio (OSNR) compared to LMS algorithm for 40 Gbit/s C-OOFDM signals when considering only CD. It is also revealed that ANN can double the transmission distance up to 320 km of SMF compared to the case of LMS, providing a nonlinearity tolerance improvement of ∼0.7 dB OSNR.

Parameter design considerations in precision engineering

Parameter design is an experimental design and analysis methodology for developing robust processes and products. Robustness implies insensitivity to noise disturbances. Subtle experimental realities, such as the joint effect of process knowledge and analysis methodology, may affect the effectiveness of parameter design in precision engineering; where the objective is to detect minute variation in product and process performance. In this thesis, approaches to statistical forced-noise design and analysis methodologies were investigated with respect to detecting performance variations. Given a low degree of process knowledge, Taguchi's methodology of signal-to-noise ratio analysis was found to be more suitable in detecting minute performance variations than the classical approach based on polynomial decomposition. Comparison of inner-array noise (IAN) and outer-array noise (OAN) structuring approaches showed that OAN is a more efficient design for precision engineering. ^

Orthogonal Frequency Division Multiplexing Based Air Interfaces and Multiple Input Multiple Output Techniques in Cooperative Satellite Communications for 4th Generation Mobile Systems

Recently, wireless network technology has grown at such a pace that scientific research has become a practical reality in a very short time span. One mobile system that features high data rates and open network architecture is 4G. Currently, the research community and industry, in the field of wireless networks, are working on possible choices for solutions in the 4G system. The researcher considers one of the most important characteristics of future 4G mobile systems the ability to guarantee reliable communications at high data rates, in addition to high efficiency in the spectrum usage. On mobile wireless communication networks, one important factor is the coverage of large geographical areas. In 4G systems, a hybrid satellite/terrestrial network is crucial to providing users with coverage wherever needed. Subscribers thus require a reliable satellite link to access their services when they are in remote locations where a terrestrial infrastructure is unavailable. The results show that good modulation and access technique are also required in order to transmit high data rates over satellite links to mobile users. The dissertation proposes the use of OFDM (Orthogonal Frequency Multiple Access) for the satellite link by increasing the time diversity. This technique will allow for an increase of the data rate, as primarily required by multimedia applications, and will also optimally use the available bandwidth. In addition, this dissertation approaches the use of Cooperative Satellite Communications for hybrid satellite/terrestrial networks. By using this technique, the satellite coverage can be extended to areas where there is no direct link to the satellite. The issue of Cooperative Satellite Communications is solved through a new algorithm that forwards the received data from the fixed node to the mobile node. This algorithm is very efficient because it does not allow unnecessary transmissions and is based on signal to noise ratio (SNR) measures.

Classificação de atividade eletromiográfia facial de indivíduos saudáveis e com hanseníese por meio de máquina de vetores de suporte

A number of studies in the areas of Biomedical Engineering and Health Sciences have employed machine learning tools to develop methods capable of identifying patterns in different sets of data. Despite its extinction in many countries of the developed world, Hansen’s disease is still a disease that affects a huge part of the population in countries such as India and Brazil. In this context, this research proposes to develop a method that makes it possible to understand in the future how Hansen’s disease affects facial muscles. By using surface electromyography, a system was adapted so as to capture the signals from the largest possible number of facial muscles. We have first looked upon the literature to learn about the way researchers around the globe have been working with diseases that affect the peripheral neural system and how electromyography has acted to contribute to the understanding of these diseases. From these data, a protocol was proposed to collect facial surface electromyographic (sEMG) signals so that these signals presented a high signal to noise ratio. After collecting the signals, we looked for a method that would enable the visualization of this information in a way to make it possible to guarantee that the method used presented satisfactory results. After identifying the method's efficiency, we tried to understand which information could be extracted from the electromyographic signal representing the collected data. Once studies demonstrating which information could contribute to a better understanding of this pathology were not to be found in literature, parameters of amplitude, frequency and entropy were extracted from the signal and a feature selection was made in order to look for the features that better distinguish a healthy individual from a pathological one. After, we tried to identify the classifier that best discriminates distinct individuals from different groups, and also the set of parameters of this classifier that would bring the best outcome. It was identified that the protocol proposed in this study and the adaptation with disposable electrodes available in market proved their effectiveness and capability of being used in different studies whose intention is to collect data from facial electromyography. The feature selection algorithm also showed that not all of the features extracted from the signal are significant for data classification, with some more relevant than others. The classifier Support Vector Machine (SVM) proved itself efficient when the adequate Kernel function was used with the muscle from which information was to be extracted. Each investigated muscle presented different results when the classifier used linear, radial and polynomial kernel functions. Even though we have focused on Hansen’s disease, the method applied here can be used to study facial electromyography in other pathologies.

Classificação de atividade eletromiográfia facial de indivíduos saudáveis e com hanseníase por meio de máquina de vetores de suporte

A number of studies in the areas of Biomedical Engineering and Health Sciences have employed machine learning tools to develop methods capable of identifying patterns in different sets of data. Despite its extinction in many countries of the developed world, Hansen’s disease is still a disease that affects a huge part of the population in countries such as India and Brazil. In this context, this research proposes to develop a method that makes it possible to understand in the future how Hansen’s disease affects facial muscles. By using surface electromyography, a system was adapted so as to capture the signals from the largest possible number of facial muscles. We have first looked upon the literature to learn about the way researchers around the globe have been working with diseases that affect the peripheral neural system and how electromyography has acted to contribute to the understanding of these diseases. From these data, a protocol was proposed to collect facial surface electromyographic (sEMG) signals so that these signals presented a high signal to noise ratio. After collecting the signals, we looked for a method that would enable the visualization of this information in a way to make it possible to guarantee that the method used presented satisfactory results. After identifying the method's efficiency, we tried to understand which information could be extracted from the electromyographic signal representing the collected data. Once studies demonstrating which information could contribute to a better understanding of this pathology were not to be found in literature, parameters of amplitude, frequency and entropy were extracted from the signal and a feature selection was made in order to look for the features that better distinguish a healthy individual from a pathological one. After, we tried to identify the classifier that best discriminates distinct individuals from different groups, and also the set of parameters of this classifier that would bring the best outcome. It was identified that the protocol proposed in this study and the adaptation with disposable electrodes available in market proved their effectiveness and capability of being used in different studies whose intention is to collect data from facial electromyography. The feature selection algorithm also showed that not all of the features extracted from the signal are significant for data classification, with some more relevant than others. The classifier Support Vector Machine (SVM) proved itself efficient when the adequate Kernel function was used with the muscle from which information was to be extracted. Each investigated muscle presented different results when the classifier used linear, radial and polynomial kernel functions. Even though we have focused on Hansen’s disease, the method applied here can be used to study facial electromyography in other pathologies.

Sistemas de cálculo, análise e operação virtual: interferências de campos elétricos e magnéticos produzidas por estações radio base de acesso múltiplo por divisão de código em banda larga - WCDMA

In this work it was developed mathematical resolutions taking as parameter maximum intensity values for the interference analysis of electric and magnetic fields and was given two virtual computer system that supports families of CDMA and WCDMA technologies. The first family were developed computational resources to solve electric and magnetic field calculations and power densities in Radio Base stations , with the use of CDMA technology in the 800 MHz band , taking into account the permissible values referenced by the Commission International Protection on non-Ionizing Radiation . The first family is divided into two segments of calculation carried out in virtual operation. In the first segment to compute the interference field radiated by the base station with input information such as radio channel power; Gain antenna; Radio channel number; Operating frequency; Losses in the cable; Attenuation of direction; Minimum Distance; Reflections. Said computing system allows to quickly and without the need of implementing instruments for measurements, meet the following calculated values: Effective Radiated Power; Sector Power Density; Electric field in the sector; Magnetic field in the sector; Magnetic flux density; point of maximum permissible exposure of electric field and power density. The results are shown in charts for clarity of view of power density in the industry, as well as the coverage area definition. The computer module also includes folders specifications antennas, cables and towers used in cellular telephony, the following manufacturers: RFS World, Andrew, Karthein and BRASILSAT. Many are presented "links" network access "Internet" to supplement the cable specifications, antennas, etc. . In the second segment of the first family work with more variables , seeking to perform calculations quickly and safely assisting in obtaining results of radio signal loss produced by ERB . This module displays screens representing propagation systems denominated "A" and "B". By propagating "A" are obtained radio signal attenuation calculations in areas of urban models , dense urban , suburban , and rural open . In reflection calculations are present the reflection coefficients , the standing wave ratio , return loss , the reflected power ratio , as well as the loss of the signal by mismatch impedance. With the spread " B" seek radio signal losses in the survey line and not targeted , the effective area , the power density , the received power , the coverage radius , the conversion levels and the gain conversion systems radiant . The second family of virtual computing system consists of 7 modules of which 5 are geared towards the design of WCDMA and 2 technology for calculation of telephone traffic serving CDMA and WCDMA . It includes a portfolio of radiant systems used on the site. In the virtual operation of the module 1 is compute-: distance frequency reuse, channel capacity with noise and without noise, Doppler frequency, modulation rate and channel efficiency; Module 2 includes computes the cell area, thermal noise, noise power (dB), noise figure, signal to noise ratio, bit of power (dBm); with the module 3 reaches the calculation: breakpoint, processing gain (dB) loss in the space of BTS, noise power (w), chip period and frequency reuse factor. Module 4 scales effective radiated power, sectorization gain, voice activity and load effect. The module 5 performs the calculation processing gain (Hz / bps) bit time, bit energy (Ws). Module 6 deals with the telephone traffic and scales 1: traffic volume, occupancy intensity, average time of occupancy, traffic intensity, calls completed, congestion. Module 7 deals with two telephone traffic and allows calculating call completion and not completed in HMM. Tests were performed on the mobile network performance field for the calculation of data relating to: CINP , CPI , RSRP , RSRQ , EARFCN , Drop Call , Block Call , Pilot , Data Bler , RSCP , Short Call, Long Call and Data Call ; ECIO - Short Call and Long Call , Data Call Troughput . As survey were conducted surveys of electric and magnetic field in an ERB , trying to observe the degree of exposure to non-ionizing radiation they are exposed to the general public and occupational element. The results were compared to permissible values for health endorsed by the ICNIRP and the CENELEC .

Adaptive Brain-Computer Interface Systems For Communication in People with Severe Neuromuscular Disabilities

Brain-computer interfaces (BCI) have the potential to restore communication or control abilities in individuals with severe neuromuscular limitations, such as those with amyotrophic lateral sclerosis (ALS). The role of a BCI is to extract and decode relevant information that conveys a user's intent directly from brain electro-physiological signals and translate this information into executable commands to control external devices. However, the BCI decision-making process is error-prone due to noisy electro-physiological data, representing the classic problem of efficiently transmitting and receiving information via a noisy communication channel.

This research focuses on P300-based BCIs which rely predominantly on event-related potentials (ERP) that are elicited as a function of a user's uncertainty regarding stimulus events, in either an acoustic or a visual oddball recognition task. The P300-based BCI system enables users to communicate messages from a set of choices by selecting a target character or icon that conveys a desired intent or action. P300-based BCIs have been widely researched as a communication alternative, especially in individuals with ALS who represent a target BCI user population. For the P300-based BCI, repeated data measurements are required to enhance the low signal-to-noise ratio of the elicited ERPs embedded in electroencephalography (EEG) data, in order to improve the accuracy of the target character estimation process. As a result, BCIs have relatively slower speeds when compared to other commercial assistive communication devices, and this limits BCI adoption by their target user population. The goal of this research is to develop algorithms that take into account the physical limitations of the target BCI population to improve the efficiency of ERP-based spellers for real-world communication.

In this work, it is hypothesised that building adaptive capabilities into the BCI framework can potentially give the BCI system the flexibility to improve performance by adjusting system parameters in response to changing user inputs. The research in this work addresses three potential areas for improvement within the P300 speller framework: information optimisation, target character estimation and error correction. The visual interface and its operation control the method by which the ERPs are elicited through the presentation of stimulus events. The parameters of the stimulus presentation paradigm can be modified to modulate and enhance the elicited ERPs. A new stimulus presentation paradigm is developed in order to maximise the information content that is presented to the user by tuning stimulus paradigm parameters to positively affect performance. Internally, the BCI system determines the amount of data to collect and the method by which these data are processed to estimate the user's target character. Algorithms that exploit language information are developed to enhance the target character estimation process and to correct erroneous BCI selections. In addition, a new model-based method to predict BCI performance is developed, an approach which is independent of stimulus presentation paradigm and accounts for dynamic data collection. The studies presented in this work provide evidence that the proposed methods for incorporating adaptive strategies in the three areas have the potential to significantly improve BCI communication rates, and the proposed method for predicting BCI performance provides a reliable means to pre-assess BCI performance without extensive online testing.

Power spectrum model of visual masking: simulations and empirical data

In the study of the spatial characteristics of the visual channels, the power spectrum model of visual masking is one of the most widely used. When the task is to detect a signal masked by visual noise, this classical model assumes that the signal and the noise are previously processed by a bank of linear channels and that the power of the signal at threshold is proportional to the power of the noise passing through the visual channel that mediates detection. The model also assumes that this visual channel will have the highest ratio of signal power to noise power at its output. According to this, there are masking conditions where the highest signal-to-noise ratio (SNR) occurs in a channel centered in a spatial frequency different from the spatial frequency of the signal (off-frequency looking). Under these conditions the channel mediating detection could vary with the type of noise used in the masking experiment and this could affect the estimation of the shape and the bandwidth of the visual channels. It is generally believed that notched noise, white noise and double bandpass noise prevent off-frequency looking, and high-pass, low-pass and bandpass noises can promote it independently of the channel's shape. In this study, by means of a procedure that finds the channel that maximizes the SNR at its output, we performed numerical simulations using the power spectrum model to study the characteristics of masking caused by six types of one-dimensional noise (white, high-pass, low-pass, bandpass, notched, and double bandpass) for two types of channel's shape (symmetric and asymmetric). Our simulations confirm that (1) high-pass, low-pass, and bandpass noises do not prevent the off-frequency looking, (2) white noise satisfactorily prevents the off-frequency looking independently of the shape and bandwidth of the visual channel, and interestingly we proved for the first time that (3) notched and double bandpass noises prevent off-frequency looking only when the noise cutoffs around the spatial frequency of the signal match the shape of the visual channel (symmetric or asymmetric) involved in the detection. In order to test the explanatory power of the model with empirical data, we performed six visual masking experiments. We show that this model, with only two free parameters, fits the empirical masking data with high precision. Finally, we provide equations of the power spectrum model for six masking noises used in the simulations and in the experiments.

O uso de sondagens dipolo-dipolo em estudos hidrogeológicos e de depósitos de resíduos

Ensaios de sondagem e caminhamento elétrico têm sido realizados globalmente na avaliação de uma grande variedade de problemas em exploração mineral e hidrogeologia, bem como na caracterização de locais com risco de contaminação. A despeito da utilidade de ensaios geoelétricos em estudos hidrogeológicos e na caracterização de depósitos de resíduos desativados, um problema na utilização de sondagens elétricas ocorre em conseqüência da falta de espaço para aquisição de dados nessas áreas. Em áreas urbanas, isto constitui uma limitação importante devido à existência de construções, o que muitas vezes interrompe o desenvolvimento de ensaios de campo com arranjos de comprimentos adequados. Embora investigações rasas tendam a ser eficazes em caracterização geoambiental, a estimativa de parâmetros-chave pode depender da investigação de porções mais profundas. Entretanto, uma profundidade de investigação ligeiramente maior é obtida pelo arranjo dipolo-dipolo em comparação aos arranjos Schlumberger e Wenner de mesmo comprimento. Essa característica do arranjo dipolo-dipolo pode ser observada em vários estudos, mas provavelmente devido à tradição e à relação sinal-ruído, a grande maioria das sondagens elétricas é feita com os arranjos Schlumberger e Wenner.O arranjo dipolo-dipolo é mais utilizado em ensaios 2D. Até onde se sabe, essa maior capacidade de investigação em profundidade do arranjo dipolo-dipolo 1D não foi explorada em estudos geoambientais e nem em estudos hidrogeológicos em áreas urbanas. Este trabalho apresenta resultados de ensaios de campo que ressaltam a utilidade de sondagens dipolo-dipolo na investigação de tais áreas.

Supressão das anomalias de fase e batimentos laterais em espectros de RMN 13c obtidos com a sequência de precessão livre no estado estacionário

The Steady-State Free Precession (SSFP) sequence has been widely used in low-field and low-resolution imaging NMR experiments to increase the signal-to-noise ratio (s/n) of the signals. Here, we analyzed the Scrambled Steady State - SSS and Unscrambled Steady State - USS sequences to suppress phase anomalies and sidebands of the 13C NMR spectrum acquired in the SSFP regime. The results showed that the application of the USS sequence allowed a uniform distribution of the time interval between pulses (Tp), in the established time range, allowing a greater suppression of phase anomalies and sidebands, when compared with the SSS sequence.