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A Proposal Based on Discrete Events for Improvement of the Transmission Channels in Cloud Environments and Big Data
Published in Rashmi Agrawal, Marcin Paprzycki, Neha Gupta, Big Data, IoT, and Machine Learning, 2020
Reinaldo Padilha Franca, Yuzo Iano, Ana Carolina Borges Monteiro, Rangel Arthur, Vania V. Estrela
Modulation is the technique where the characteristics of the signal (carrier) are modulated, where they are modified for the purpose of transmitting the information, making the combined changes of frequency, amplitude or phase. This modulated carrier wave travels over a communications channel carrying all information. Thus, a specific type is Differential Quadrature Phase Shift Keying (DQPSK) format, a particular form of Quadrature Phase Shift Keying (QPSK) modulation, rather than a symbol corresponding to a pure phase parameter; this symbol represents a phase variation, determined by 4 possible states 0, π, + π/2, -π/2, where constellation rotated by 45 ° from the previous point, referring that each symbol represents two bits of information and shifted to about π/4 or π/2, totaling 8 status positions, still taking into account withstanding the channel fading, being used by most of the cellular towers for transmission of the data and long-distance communication. Figure 8.1 shows the DBPSK constellation diagram (Bhat and Singh, 2017).
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Published in David W. Richerson, William E. Lee, Modern Ceramic Engineering, 2018
David W. Richerson, William E. Lee
A variety of functions must be conducted to encode information and successfully transfer it between the transmitter and the receiver. These include modulation, coupling, switching, multiplexing, and filtering. Modulation involves a change in frequency, amplitude, or phase of the signal to encode information. Coupling and switching involve transfer of information from the transmitter to the fiber and from one fiber to another. Multiplexing involves combination of several optical signals of different wavelength from separate fibers into one light beam. Filtering involves tuning the system to maintain a signal of a single wavelength. All these functions in initial systems could be accomplished only by converting back to an electrical signal, which was complex and inefficient. Electrooptical materials have been developed to accomplish these functions directly on the light beams without having to convert back to an electrical signal.
Centrifuge data acquisition systems
Published in Gopal Madabhushi, Centrifuge Modelling for Civil Engineers, 2015
A key stage in the data acquisition process as outlined in Figure 9.1 is the analog to digital conversion. As explained earlier, instruments produce an analog signal which is continuous with time. A digital signal by definition is a set of discrete values at each of the time increments. The range of the A/D card is divided into a number of steps. Thus, a continuous signal appears as a series of step functions. This is illustrated in Figure 9.2, which shows a continuous sinusoidal signal of ±1 V. This signal is digitized at 10 discrete levels, each a step of 0.2 V, and fits the continuous sine wave. At each time instant only a discrete value is logged. Clearly, the more discrete levels there are, the more closely the digital signal will match the analog signal.
Acoustic Analysis of the Effects of Vapor-Liquid Interfacial Morphology on Pool-Boiling Heat Transfer
Published in Nuclear Technology, 2022
Mustafa H. Almadih, T. Almudhhi, S. Ebrahim, A. Howell, G. R. Garrett, S. M. Bajorek, F. B. Cheung
The sound wave signals that were produced from the boiling surface of the heated rod during quenching were analog signals. Signals produced or generated from natural sources, such as speech, artificial sources, and heat sources, are considered to be analog signals.14 Any continuous signal whose time-varying function is a reflection of another time-varying quantity is called an analog signal. In this study, the signals produced from the superheated rod during the quenching process are the input signals called analog signals. The hydrophone is built to record vibrating wave sounds underwater. The main goal is to record the generated sounds from the superheated rod and to convert all the analog signals into digital signals and then store them in the computer for analysis by using a data acquisition system connected to the computer through LabVIEW engineering system software for measurement (Fig. 9).
Fractional sequential likelihood ascent search detector for interference cancelation in massive MIMO systems in 5G technology
Published in International Journal of Electronics, 2021
Anju V. Kulkarni, Radhika Menon, Pramodkumar H. Kulkarni
Interference is considered as the major problem in the next-generation wireless systems to attain higher throughput. The interference in the signals causes an error or imprecise estimation of the channel for future 5 G transmissions. The main aim of the research is to model a technique that eradicates the interference produced in the massive-MIMO systems. At first, the input signals are transmitted to the encoder for converting the signals from one format to another format. Then, the modulation of the encoded signal is carried out for converting the radio waves by adding information to the signal. The obtained modulated signal is fetched using the transmitting antenna, which helps to transmit the signals and the receiver receives the signals at the receiver side. The obtained modulated signals are demodulated for extracting the original signal from the carrier wave. Finally, the decoding of the signal is done to convert the received signal into codes and is used for recovering the signals sent from the noisy channel. Here, the interference of the signals is eradicated by applying the proposed Fractional-SLAS, which is devised by integrating FC and SLAS algorithm. The proposed interference mitigation method helps to mitigate the interference produced from the signals without any delay or loss of quality of the transmitted signal.
Effects of digital filtering on peak acceleration and force measurements for artistic gymnastics skills
Published in Journal of Sports Sciences, 2020
Rhiannon A. Campbell, Elizabeth J. Bradshaw, Nick Ball, Adam Hunter, Wayne Spratford
Digital filtering is a common method used in biomechanical data analysis. The primary purpose of filtering is to remove noise from raw signals. Noise is the part of the final signal that is not due to changes in the measurement variable, is generally random, and is found at higher frequencies than where the true signal for most human movement usually lies (Winter, 1990; Yu et al., 1999). Digital filters can be applied using different methods, depending on the type of signal and the purpose of the data collected. Filters can be either high-pass (designed to attenuate signals under a designated frequency), low-pass (attenuate signals above a designated frequency), band-pass (attenuate signals that occur outside a designated range of frequencies) or band-stop filters (attenuate signal that occurs within a designated range of frequencies). Most human movement (i.e. walking or running) occupies the lower end of the frequency spectrum, while noise tends to occur at higher frequencies (Yu et al., 1999). For this reason, low-pass filters, or Butterworth filters, are commonly applied to biomechanical data as it passes over the lower frequencies, maintaining the true movement signal, while attenuating the higher frequency noise (Winter, 1990; Yu et al., 1999).