According to high costs of phase shifters in antenna arrays, new methods for beam steering without phase shifter are introduced. FREQUENCY Diverse Array (FDA) concept is another approach to beam steering problem. In this structure, the subsequent antenna elements are fed with stepped discrete frequencies causing continuous scanning of space in time. So a range-angle dependent scanning is made possible. There are several ways to implement, which the simplest of them is using Linear FREQUENCY Modulated Continuous Wave (LFMCW) source. In this paper, a new implementation scheme is proposed and analyzed where a Square FREQUENCY Modulated Continuous Wave (SFMCW) source is used for feeding a special beam forming network. Also radiation pattern of SFMCW and LFMCW was compared.

Objective: The aim of the present study was to evaluate the etiology and FREQUENCY of neonatal seizure in hospitalized neonates.Materials and Methods: In this descriptive, cross-sectional study, we evaluated 1295 neonates with seizures admitted to neonatal and NICU wards in our center. Data was collected on age, sex, birth weight, serum levels of calcium, glucose, and sodium, CT scan findings, history of maternal opium abuse, blood and cerebrospinal fluid culture, and analyzed using SPSS 13.Results: Of a total of 1295patients, 34 (2.62%) had seizure. Mean age was 14.03±10.05 days (range, 1 to 29 days); twenty-five (73.5%) neonates were boys and 9 (26.5%) were girls. Of 34 neonates with neonatal seizures, 12 (35.3%), 11 (32.4%), 9 (26.5%), 7 (20.6%), and 3 (8.8%) had hypocalcemia, asphyxia, hypoglycemia, intracranial hemorrhage, and hypernatremia, respectively. Maternal addiction, meningitis, and sepsis were found in 3 (8.8%)/ 1 (2.9%) and 1 (2.9%) of neonates, respectively.Conclusion: The incidence rate of neonatal seizure in the neonates in our NICU and neonatal ward was 2.62%. Common causes of seizure in this study included hypocalcemia, asphyxia, hypoglycemia, intracranial hemorrhage, and hypernatremia. Maternal addiction, meningitis and sepsis had the lowest prevalence.

The paper addresses a problem of tracking multiple number of frequencies using Regularized Autoregressive (RAR) approximation. The RAR procedure allows to decrease approximation bias, comparing to other AR-based FREQUENCY detection methods, while still providing competitive variance of sample estimates. We show that the RAR estimates of multiple periodicities are consistent in probability and illustrate dynamics of RAR in respect to sample size and signal-to-noise ration by simulations.

In this research, from data of 26 hydrometric station records and l-moment approach, regional and stational flood FREQUENCY of Dez basin was analyzed. For identifying homogeneous regions, Ward hierarchical cluster method was used. The appropriate number of homogeneous regions was determinate from nonhomogeneity test and discordancy measure. The Dez Basin was divided into three homogeneous regions. In these regions parameters of the regional FREQUENCY distribution were evaluated by the L-moment ratios. The L-moment diagram, goodness of fit test, and plotting position methods were used for the selection of appropriate distribution and plotting position formula. Generalized Extreme-Value distribution and Chegodieve plotting position formula is appropriate for region A, generalized logistic distribution and Greengurten plotting position formula for region B and Generalized Extreme-Value distribution and Greengurten plotting position formula for region C were selected. The relative root mean square error (rRMSE) between observed and estimated data, in all stations, in high return periods is small and in small return periods is vicversa. Regional models evaluated for determination of flood discharge magnitude in different FREQUENCY by linear and multiple regression method. 

Summary Assessing a time-FREQUENCY representation of signal with an acceptable timeFREQUENCY resolution, and for specific purposes in different applied studies, has always been a challenge for signal processing researchers. In case of seismic data, using a time-FREQUENCY representation with high resolution will yield a higher precision in processing and interpretational applications of timeFREQUENCY analysis of data. In the most of time-FREQUENCY analysis methods, a form of smoothing is used for generating time-FREQUENCY map, which it causes energy dissipation in time-FREQUENCY plane and decreasing the resolution. Reassignment is an efficient technique for compensating this issue and increasing the resolution. It can provide a high time-FREQUENCY resolution through moving and concentrating the energy distribution in the time-FREQUENCY plane to true location. Reassignment has been applied to various time-FREQUENCY analysis methods and its performance has been presented in different researches. In this paper, the reassigned Stransform as a new development on S-transform to provide higher time and FREQUENCY resolution is utilized to extract some seismic attributes. The performance of the method in providing an acceptable time-FREQUENCY resolution is shown by testing on synthetic non-stationary chirp and seismic signals. As a seismic application, the reassigned S-transform is utilized in studying low FREQUENCY shadows through time-FREQUENCY analysis of seismic data set acquired on a hydrocarbon reservoir. For this purpose, some time-FREQUENCY attributes including single-FREQUENCY, instantaneous amplitude, instantaneous dominant FREQUENCY and sweetness factor are extracted by this method. The results show that the reassigned S-transform can provide much higher energy concentration rather than standard S-transform, and the events and anomalies can be interpreted with more precision due to their better time and space resolution in attribute sections. Introduction The time-FREQUENCY analysis methods are among the most common signal and image processing techniques in different applied fields of electric engineering, mechanical engineering, geoscience, etc. Time-FREQUENCY methods are employed in seismic data processing and interpretation applications for denoising, attenuation estimation, deconvolution, hydrocarbon detection, channels and faults visualization and so on. There are several time-FREQUENCY analysis methods. One of the main reasons of developing new time-FREQUENCY methods is to reach higher time-FREQUENCY resolution. The reassignment is one of the successful approaches in this field. The mission of reassignment method (RM) is to move the energy distribution of the time-FREQUENCY plane to true location. Through this way, a precise distribution of instantaneous FREQUENCY has been provided for any time sample. Reassigning is also carried out in time direction. The RM has been applied in several time-FREQUENCY methods such as wavelet transform, Wigner-Ville distribution, Gabor transform and S-transform. In this paper, the reassigned Stransform has been studied in seismic data time-FREQUENCY analysis. The method has been utilized for detection of low FREQUENCY shadows in a seismic dataset to locate probable gas reservoir. Methodology and Approaches Auger et al. (2013) state that the RM can be applied on any time-FREQUENCY energy distribution in which a form of smoothing is applied in generating it, as seen in S transform. Therefore, Fourer et al. (2015) have introduced the reassigned S-transform. As mentioned above, the mission of the RM is to move the distributed energy in time-FREQUENCY plane to true coordinates. Then, it is needed to determine the true center coordinates of energy distribution, known as reassigning operators. Concerning the S-transform, the operators are computed as (Fourer et al., 2015): (, ) ˆ (, ) Re (, ) Tg x x ST t t t t ST t            (, ) ˆ (, ) Im (, ) Dg x x ST t t ST t              where ( ) ( ) Tg t tg t  , () () dg t Dg t dt  and Re and Im represent the real and imaginary parts of the arguments inside the parentheses. Then, the reassigned representation of S-transform is determined as: 2 2 (, ) (, ) ( ˆ (, )) ( ˆ (, )). g x x R RST t     ST t   t  t         d d where  represents Dirac function. However, in this paper, the reassigning process is implemented using the Levenberg-Marquardt approach, developed by Auger et al. (2012), in which a damping parameter could adjust the timeFREQUENCY concentration. Results and Conclusions In this paper, the performance of reassigned S-transform has been studied by its application on synthetic chirp signal and seismic trace. The results show that the method is capable of providing a well-concentrated time-FREQUENCY maps. As an application in real seismic data, the method has been utilized for studying the low FREQUENCY shadows related to probable gas bearing zones. This approach extracts some attributes including single FREQUENCY, instantaneous amplitude, instantaneous dominant FREQUENCY and sweetness factor, through time-FREQUENCY analysis of the data. The results show that the reassigned S-transform can provide higher time and space resolution, and thus, the events and anomalies can be interpreted more precise compared to standard S-transform results.

Purpose: Formant structure is the most important acoustic characteristic of vowels and the vowel is the main center of syllables. Therefore, an investigationof their formants structure is of great importance. The aim of the present study was to investigate the nine Azeri vowel's formants. Methods: The present study was a cross-sectional and descriptive-analytic study. The participants of this study were 50 (25 males-25 females) students of Tabriz University of Medical Sciences with their age ranging from 18-24 years old. The fundamental FREQUENCY (F0) of /a/ and /i/ vowels and the first, second, and third formants (F1, F2, F3) of nine Azeri vowels were determined with using Praat software. Statistical analysis was performed with SPSS software. When the data were normally distributed, independent t-test was used. Otherwise, Mann-Whitney test was used. Results: F0 of /a/ and /i/ vowels are significantly higher in females than males. /æ / and /i/ vowels in the both sexes, respectively, have the most and least F1. The most F2 in the both sexes is /i/ and the least F2 in male /æ / and in females is /o/. Also, in both sexes, the most F3 is /i/ vowel and the least F3 is /ø / vowel. Conclusion: /æ / and /i/ vowels in the both sexes, respectively, are the most open and closed vowels. /i/ vowel in the both sexes and /æ / in males and /o/ in females respectively, are the most front and most back vowels. The roundest vowel in Azeri is /ø / and the most spread vowel is /i/.

Background/Objective: The brain response to temporal frequencies (TF) has been already reported. However, there is no study on different TF with respect to various spatial frequencies (SF). Materials and Methods: Functional magnetic resonance imaging (fMRI) was done by a 1.5 T General Electric system for 14 volunteers (9 males and 5 females, aged 19–26 years) during square-wave reversal checkerboard visual stimulation with different temporal frequencies of 4, 6, 8 and 10 Hz in 2 states of low SF of 0.4 and high SF of 8 cycles/degree (cpd). All subjects had normal visual acuity of 20/20 based on Snellen’s fraction in each eye with good binocular vision and normal visual field based on confrontation test. The mean luminance of the entire checkerboard was 161.4 cd/m2 and the black and white check contrast was 96%. The activation map was created using the data obtained from the block designed fMRI study. Pixels with a Z score above a threshold of 2.3, at a statistical significance level of 0.05, were considered activated. The average percentage blood oxygenation level dependent (BOLD) signal change for all activated pixels within the occipital lobe, multiplied by the total number of activated pixels within the occipital lobe, was used as an index for the magnitude of the fMRI signal at each state of TF&SF. Results: The magnitude of the fMRI signal in response to different TF’s was maximum at 6 Hz for a high SF value of 8 cpd; it was however, maximum at a TF of 8 Hz for a low SF of 0.4 cpd. Conclusion: The results of this study agree with those of animal invasive neurophysiologic studies showing SF and TF selectivity of neurons in visual cortex. These results can be useful for vision therapy and selecting visual tasks in fMRI studies.  

Grid impedance estimation is used in many power system applications such as grid connected renewable energy systems and power quality analysis of smart grids. The grid impedance estimation techniques based on signal injection uses Ohm’ s law for the estimation. In these methods, one or several signal(s) is (are) injected to Point of Common Coupling (PCC). Then the current through and voltage of PCC are measured. Finally, the impedance is assumed as ratio of voltage to current signals in FREQUENCY domain. In a noisy system, energy of the injected signal must be sufficient for an accurate approximation. However, power quality issues and regulations limit the energy and the voltage levels of the injected signal. There are three main issues in impedance estimation using signal injection: I) Power quality of grid, II) FREQUENCY range of estimation, and finally III) accuracy of estimation. In this paper, the stationary wavelet denoising algorithm is employed instead of increasing the energy of injection signal(s). In the paper, a novel method is proposed for impedance estimation based on selecting several appropriate injection signals and denoising the measured signals. The proposed method is able to impedance estimation in a wide FREQUENCY range without any effect on power quality. Finally, simulation results have been carried out to validate the proposed method.