Data processing revisited in electrical and electromagnetic survey data using digital filters.

Concurrently functioning relays using FPGA technology are the primary focus of the project. The suggested FPGA-based relays are much faster than microprocessor- or microcontroller-based relays because they use continuous sense-process communicate cycles. The Xilinx Virtex-II FPGA Board's implementation of overcurrent, impedance, reactance, and mho was evaluated using the 400 kv line transmission hardware simulator. Fault currents in power systems may contain a component of direct current (DC) that decays exponentially in the case of transient failures. Extracting the fundamental frequency element is essential for avoiding false tripping. To do this, we make use from the VHDL FFT IP core. A Fast Fourier Transform (FFT) filter is used to implement overcurrent, impedance, reactance, and mho dependence. The FFT filter is also used to evaluate the DC decaying portion.

PURPOSE: Electromagnetic (EM) kinematic tracking systems have gained popularity in recent years due to their ability to quickly capture 6 degree-of-freedom position data. EM systems work by sequentially creating orthogonally oriented magnetic fields in which the receivers locate themselves. The purpose of this investigation was to determine the impact of the EM signal on surface EMG data and to provide suggested methods for reducing any detrimental effects. EQUIPMENT / METHODS: EM signals are produced by EM kinematic tracking systems. The EM field-strength varies as a function of the distance from the transmitter. The frequency varies as a function of the selected kinematic sampling rate. These combine to produce a non-stationary signal that can contaminate EMG data. Raw EMG data was collected from the quadriceps and hamstring muscles on subjects performing a squatting task and a jumping task in the presence of an EM transmitter. Both tasks were performed with and without the transmitter on. Data were collected at 1000 Hz. ANALYSIS Data from all trials were qualitatively assessed for the appearance of EM contamination. These data were then processed to evaluate the impact of the EM signal on muscle timing analyses. Power spectrums of the data were computed using a Fast Fourier Transform (FFT) algorithm. This spectral information was used to create digital filters to remove the EM signal from the raw data. RESULTS The EM signal was present in the EMG data for all trials performed in the presence of an active EM transmitter. In many cases, this signal was strong enough to completely mask the EMG signal. The muscle timing analysis of contaminated data were unable to accurately quantify onsets. Digital filtering successfully removed the EM noise and provided muscle latencies that were comparable to those found from the analysis of the uncontaminated data. CONCLUSIONS Digital filtering is an effective way of removing EM contamination from EMG data. When using this method, care should be taken to collect raw EMG data at a sampling rate that is consistent with the digital filtering requirements. RELEVANCE Extraneous EM signals have historically been part of EMG data collection. Many commercial systems have built-in notch filters to contend with 60Hz interference. The advent of EM tracking systems produces a need to re-evaluate processing techniques for EMG data collected in these environments.

The water-rich zones in the coal fields of Northern China have seriously threatened the safe production of coal mines. It is necessary to accurately locate the deep seated and complex water bodies which are usually located in Ordovician limestone. Due to the relatively high cost of seismic exploration, the development effective electromagnetic detection methods and corresponding data processing techniques for the detection of these water-rich areas becomes a topic for the EM geophysicist. In this study, a method of rapidly estimating the burial depth and undulating morphology of coal bed foundations by employing frequency domain electromagnetic sounding data was proposed. The method uses the overshoot/undershoot phenomenon of the apparent resistivity for the frequency domain electromagnetic measurement to quantitatively determine the burial depth of the northern China coal structure bases. First, the featured frequency points were confirmed, where the overshoot and undershoot effects appeared in the electromagnetic sounding curves beside the borehole drilling sites. Then, the correlation coefficient between the confirmed frequency points and the burial depth of coal seam bed was obtained according to the drilling data. Finally, the burial depth of the coal seam beds in the entire survey area was evaluated based on the correlation coefficient and electromagnetic data. This method was applied in the northern areas of Taiyuan City in Shanxi Province, and achieved good results.

Historically, computationally-intensive data processing for space-borne instruments has heavily relied on ground-based computing resources. But with recent advances in functional densities of Field-Programmable Gate-Arrays (FPGAs), there has been an increasing desire to shift more processing on-board; therefore relaxing the downlink data bandwidth requirements. Fast Fourier Transforms (FFTs) are commonly-used building blocks for data processing applications, with a growing need to increase the FFT block size. Many existing FFT architectures have mainly emphasized on low power consumption or resource usage; but as the block size of the FFT grows, the throughput is often compromised first. In addition to power and resource constraints, space-borne digital systems are also limited to a small set of space-qualified memory elements, which typically lag behind the commercially available counterparts in capacity and bandwidth. The bandwidth limitation of the external memory creates a bottleneck for a large, high-throughput FFT design with large block size. In this paper, we present the Multi-Pass Wide Kernel FFT (MPWK-FFT) architecture for a moderately large block size (32K) with considerations to power consumption and resource usage, as well as throughput. We will also show that the architecture can be easily adapted for different FFT block sizes with different throughput and power requirements. The result is completely contained within an FPGA without relying on external memories. Implementation results are summarized.

The Autoregressive Integrated Moving Average model (ARIMA) is a popular time-series model used to predict future trends in economics, energy markets, and stock markets. It has not been widely applied to enrollment forecasting in higher education. The accuracy of the ARIMA model heavily relies on the length of time series. Researchers and practitioners often utilize the most recent - to -years of historical data to predict future enrollment; however, the accuracy of enrollment projection under different lengths of time series has never been investigated and compared. A simulation and an empirical study were conducted to thoroughly investigate the accuracy of ARIMA forecasting under four different lengths of time series. When the ARIMA model completely captured the historical changing trajectories, it provided the most accurate predictions of student enrollment with 20-years of historical data and had the lowest forecasting accuracy with the shortest time series. The results of this paper contribute as a reference to studies in the enrollment projection and time-series forecasting. It provides a practical impact on enrollment strategies, budges plans, and financial aid policies at colleges and institutions across countries.

A network of drainage patterns and associated morphometric analysis are important as it forms various attributes of a watershed. Analysis of these attributes is carried out by spatial analysis which is essential for studying several hydrological response interactions within the watershed catchment area. In the present work, five stream networks of a head watershed Verakhadi were derived from SOI toposheet (scale = 1:50,000), SRTM-GL1, AW3D30, GDEM-V2 and CartoDEM-V3.1. The calculated basin morphometric attributes of drainage network derived from all four 30-m-resolution satellite-based DEMs were compared with SOI toposheet-based drainage network which is essential for estimating the accuracy of watershed hydrological response to a natural event (storm). The capability of all four satellite-based DEMs to represent linear, areal and relief aspect of the drainage basin was evaluated. Morphometric parameter comparison of stream network derived from various DEMs is an indirect way of assessing the relative vertical accuracy of DEM. It is observed that DEMs with same spatial resolution can have variable morphometry derivatives due to different data acquisition and data processing techniques used for DEM generation. The outcome of this study will help to understand the complexity and susceptibility of the various morphometric factors arises while dealing with different data acquisition and processing techniques. The study suggests that SRTM-GL1 performs better in terms of drainage delineation and basin morphometry, followed by AW3D30, CartoDEM-V3.1 and GDEM-V2 when compared with SOI toposheet-derived terrain attributes.

Data processing is one of the essential steps to obtain optimum response function of the Earth’s subsurface. The MT Data processing is based on the Fast Fourier Transform (FFT) algorithm which converts the time series data into its frequency domain counterpart. The FFT combined with statistical algorithm constitute the Robust Processing algorithm which is widely implemented in MT data processing software. The Robust Processing has three variants, i.e. No Weight (NW), Rho Variance (RV), and Ordinary Coherency (OC). The RV and OC options allow for denoising the data but in many cases the Robust Processing still results in not so smooth sounding curve due to strong noise presence during measurement, such that the Crosspower (XPR) analysis must be conducted in the data processing. The XPR analysis is very time consuming step within the data processing. The collaboration of B-Spline algorithm and Qualitative Spectral Analysis in the frequency domain could be of advantages as an alternative for these steps. The technique is started by using the best coherency from the Robust Processing results. In the Qualitative Spectral Analysis one can determine which part of the data based on frequency that is more or less reliable, then the next process invokes B-Spline algorithm for data smoothing. This algorithm would select the best fit of the data trend in the frequency domain. The smooth apparent resistivity and phase sounding curves can be considered as more appropriate to represent the subsurface. This algorithm has been applied to the real MT data from several survey and give satisfactory results.

This paper presents design algorithms for hybrid filter banks (HFBs) for high-speed, high-resolution conversion between analog and digital signals. The HFB is an unconventional class of filter bank that employs both analog and digital filters. When used in conjunction with an array of slower speed converters, the HFB improves the speed and resolution of the conversion compared with the standard time-interleaved array conversion technique. The analog and digital filters in the HFB must be designed so that they adequately isolate the channels and do not introduce reconstruction errors that limit the resolution of the system. To design continuous-time analog filters for HFBs, a discrete-time-to-continuous-time ("Z-to-S") transform is developed to convert a perfect reconstruction (PR) discrete-time filter bank into a near-PR HFB; a computationally efficient algorithm based on the fast Fourier transform (FFT) is developed to design the digital filters for HFBs. A two-channel HFB is designed with sixth-order continuous-time analog filters and length 64 FIR digital filters that yield -86 dB average aliasing error. To design discrete-time analog filters (e.g., switched-capacitors or charge-coupled devices) for HFBs, a lossless factorization of a PR discrete-time filter bank is used so that the reconstruction error is not affected by filter coefficient quantization. A gain normalization technique is developed to maximize the dynamic range in the finite-precision implementation. A four-channel HFB is designed with 9-bit (integer) filter coefficients. With internal precision limited to the equivalent of 15 bits, the maximum aliasing error is -70 dB, and with the equivalent of 20 bits internal precision, maximum aliasing is -100 dB. The 9-bit filter coefficients degrade the stopband attenuation (compared with unquantized coefficients) by less than 3 dB.

Research work is one of the most difficult types of independent work of applicants for the second level of higher education (master's students), the implementation of which requires special knowledge and skills. For master's cadets, preparing and writing a master's thesis is the first experience of research activity. In the Kherson State Maritime Academy, for master's cadets specializing in «Navigation and Management of Sea Vessels», the course «Modern Methods of Scientific Research and Data Processing» (MMSRDP) is provided, which, according to the curriculum and educational and professional program, is included in the cycle of professional training. The program of the academic discipline «Modern Methods of Scientific Research and Data Processing» is drawn up in accordance with the Code of Training, Certification and Watchkeeping for Seafarers STCW-78, IMO-MODEL COURSE 7.01, 7.03. and according to EPP. The direction of our research is to improve the teaching of the course «Modern Methods of Scientific Research and Data Processing» in the Kherson State Maritime Academy to achieve more significant standards of professional competence of applicants for the second level of higher education (master's students) in the specialization «Navigation and Management of Marine Vessels» of KhSMA. This article examines two of the most important components of the MMSRDP course. The first is the «starting» knowledge of the methodology and methods of scientific research, namely, the most significant classical paradigms that determine the essence of the concepts of methodology and methods of scientific research, concepts and issues of modern methods of empirical and theoretical research. The second, no less important component of the MMSRDP course is the study by master's students of specific methods and techniques of data processing and analysis. Our further research is aimed at a more detailed consideration of the second component of the MMSRDP course - the study by master's students of specific methods and techniques of data processing and analysis in the field of technical sciences, in particular, in the field of navigation, which are most necessary for master's students of the navigation specialty, as well as the development of a set of individual tasks for master's students aimed at the application of specific methods and techniques of data collection and analysis

We present an overview of a mature, robust and general algorithm providing a single framework for the inversion of most electromagnetic and electrical data types and instrument geometries. The implementation mainly uses a 1D earth formulation for electromagnetics and magnetic resonance sounding (MRS) responses, while the geoelectric responses are both 1D and 2D and the sheet’s response models a 3D conductive sheet in a conductive host with an overburden of varying thickness and resistivity. In all cases, the focus is placed on delivering full system forward modelling across all supported types of data. Our implementation is modular, meaning that the bulk of the algorithm is independent of data type, making it easy to add support for new types. Having implemented forward response routines and file I/O for a given data type provides access to a robust and general inversion engine. This engine includes support for mixed data types, arbitrary model parameter constraints, integration of prior information and calculation of both model parameter sensitivity analysis and depth of investigation. We present a review of our implementation and methodology and show four different examples illustrating the versatility of the algorithm. The first example is a laterally constrained joint inversion (LCI) of surface time domain induced polarisation (TDIP) data and borehole TDIP data. The second example shows a spatially constrained inversion (SCI) of airborne transient electromagnetic (AEM) data. The third example is an inversion and sensitivity analysis of MRS data, where the electrical structure is constrained with AEM data. The fourth example is an inversion of AEM data, where the model is described by a 3D sheet in a layered conductive host.

The spectrum of a musical signal contains features that are important in our perception of musical sounds. We know that the timbre or tone quality depends, in part, on the spectrum of the tone (Grey:1978). Also, the location of prominent frequency components in the spectrum have been shown to relate to the perceived pitch of the tone as well (Piszczalski and Galler: 1978). Unfortunately, a single spectrum provides no information on the time-varying aspects of sound. Consequently, methods have been devised to capture and display the time-varying spectrum of sounds. Perhaps the best known display of amplitude -frequencytime information is in spectrograms, more commonly known as voiceprints. The speech community has long used the analog spectrograph to generate these images, and musical examples were studied using this technique as early as 1947 (Potter et al.). More recently digital methods have been employed to capture the spectrographic image. Both digital filters and the Fast Fourier Transform (FFT) can give spectrographic information, with the FFT being the method used in the figures presented here. For more information on the actual computer implementation cf. (Piszczalski and Galler: 1978.) For spectrographic analysis, the digital computer has advantages over the analog spectrograph by providing more sophisticated graphics displays, including a three-dimensional representation, which we refer to as the surface of the sound. Also, digitized data is more amenable to further analysis and processing. Spectrographic displays in general offer a unique graphic perspective for music acoustics research; in particular, in studying sounds produced on traditional musical instruments. We can study how the harmonic envelope changes during the course of a single sustained tone. We can also view how the spectrum changes between played notes. We can also watch the effect of articulation, such as legato-tonguing, on the resulting spectrum. Spectrograms also reduce the danger of incorrectly assuming that an arbitrary spectrum is representative for all tones produced on that instrument. The variety of shapes the harmonic envelope may take can be especially dramatic when a sequence of notes is simultaneously displayed, as is often the case in the following figures. Depending on what perceptual features are sought, different frequency and time scales should be used. We wanted the melodic patterns to be as visually obvious as possible, so we optimized towards identifying the note sequences. In the following spectral surfaces a new spectrum was calculated for every 32 msec of music. We have found this time interval to be sufficiently dense to capture the most rapidly played note sequences that we have studied to date (up to 14 notes/sec). The frequency scale is subdivided into 128 equally spaced points between 0 Hz and the maximum frequency indicated on the respective graphs. The hidden-line, three-dimensional algorithm used for our graphics was implemented on a Hewlett-Packard minicomputer system by Frederick Looft. The frequency, amplitude and time scales are linear in all cases. These images were generated in the course of our larger study of musical psychoacoustics, and more specifically have served as an aid in the areas of automatic pitch-tracking and melodic pattern recognition of performed music. While we have found the spectral representations quite helpful, many of these graphs have generated fascinating questions which we simply have not had time yet to explore to any depth or to evaluate using other techniques. Hearing the source of the sounds while viewing the figures makes them particularly effective. Still, this collection of sound images, by themselves, should be informative for those in the music analysis/synthesis area. Except where otherwise noted, audio sources were recorded at the University of Michigan. This research is supported by the National Science Foundation (Grant No. MC578-09052).

Refractive index profile of surface channel waveguides can be determined by analyzing the near-field intensity pattern. A mathematical model, the inverse Helmholtz equation, is derived in order to use these data to reconstruct the refractive index profile under consideration. In this work, the measured near-field intensities are preprocessed by means of gamma correction, background noise subtraction, Fast Fourier Transform, and low pass finite impulse response (FIR) digital filter. Several types of FIR windows are chosen. The results are used to reconstruct the refractive index profile of the waveguide. The results show that the application of low pass FIR digital filter by using Hamming window reduces noises better than other windows. The application of this method in determination of refractive index profile of annealed proton exchange LiNbO<SUB>3</SUB> channel waveguides is demonstrated.

Fast Fourier transformation (FFT), a kernel data processing task in communication systems, has been studied intensively for efficient software and hardware implementations. Nowadays, various orthogonal frequency division multiplexing (OFDM)-based wireless communication standards have raised more stringent requirements on both throughput and flexibility for FFT computation. Application-specific instruction set processor (ASIP) has emerged as a promising solution to meet these requirements. This paper presents a novel hierarchical design of an ASIP tailored for FFT. We reconstruct the FFT computation flow into a scalable array structure based on an 8-point butterfly unit (BU). The array structure can easily expand along both the horizontal and vertical dimensions for any-point FFT computation. We incorporate custom register files to reduce memory access and derive a regular data addressing rule accordingly. With the microarchitecture modifications, we extend the instruction set architecture (ISA) with new instructions to accelerate FFT operations. An FFT ASIP is implemented on Tensilica's reconfigurable processor platform. Our FFT ASIP achieves the data throughput of 405.7 Mb/s for 1 K-point FFT, which attains UWB-OFDM specifications. The area of our custom processor is 147 kilo gates and the total processor power consumption is 60.7 mW, which are acceptable compared to several other designs such as application specific integrated circuit, digital signal processing, field-programmable gate array, and other ASIP implementations. We also extend the implementation for up to 8 K-point FFTs, with degraded performance but still meeting the requirements of those communications standards that demand large-size FFT computations.

The utilization of open and free-environment programming has increased drastically in education and research fields in the current pandemic situation. SCILAB programming originated from a laboratory INRIA in France and it is the overall open and free-environment reference in mathematical calculation programming. It is an alternative open-source with an easy syntax to the licensed software MATLAB. This preliminary study paper describes about the design and simulation of the discrete-time signal processing laboratory concepts with the SCILAB open-source software. The transform techniques in signal processing like Fourier Transform of discrete signals, fast Fourier Transform, Fourier series for discrete-time periodic signals and digital filters are better understood with the simulation results obtained in SCILAB. The student feedback shows that the student attention has improved with SCILAB based signal processing teaching.

Traditional security systems use passwords or ID cards have been used to moderate access to restricted systems, but these kind of systems have a poor performance because the security can be easily breached. Based in this disadvantage, the biometrics systems have a great popularity, the mains biometrics systems are: face recognition, iris recognition, voice recognition, fingerprint recognition and sinning recognition. The fingerprint recognition is the oldest method used to recognition or verification of person. Our proposed a people recognition system with verification by invariant moments using two methodologies for the fingerprint enhancement. The goal in this work is to get a robust system in security issues. In this work a method for fingerprint verification is considered using a combination of Fast Fourier Transform (FFT) and Gabor Filters by image enhancement, both methods are first applied separately and later on an algebraic sum is done to obtain a single output. After that, a thinning algorithm is applied to get an image with the minimum thickness of 1 pixel. After this thinning algorithm, we apply an algorithm to look minutiae using a window of 3 by 3 pixels to scan the image. In this work we extract two types of minutiae, bifurcation and ending. Then, the feature vector is generated with the distance between minutiae, angle between minutiae and coordinates. In the recognition stage using the coordinates from the minutiae position on the image a comparison is done. After that, apply a verification stage using the invariant moments. With the invariant moments values a comparison is done. The comparison was done using the values obtained for the images into database and the test image for to get the output. The results obtained in this research are better when we used FFT and Gabor filters algorithms to image enhancement than we used separately.