A high sensitivity, low power and low cost sensor has been developed for photoplethysmography (PPG) measurement. The PPG principle was applied to follow the dilatation and contraction of skin blood vessels during the cardiac cycle. A standard light emitting diodes (LEDs) has been used as a light emitter and detector, and in order to reduce the space, cost and power, the classical analogue-to-digital converters (ADCs) replaced by the pulse-based signal conversion techniques. A general purpose microcontroller has been used for the implementation of measurement protocol. The proposed approach leads to better spectral sensitivity, increased resolution, reduction in cost, dimensions and power consumption. The basic sensing configuration presented is capable of detecting the PPG signal from a finger or toe, and it is very simple to extract the heart rate and heart rate variability from such a signal.
In this paper, a simulation model and practical testbed for green Internet of Things (IoT) edge devices are proposed based on solar harvester with constant voltage-maximum power point tracking (CV-MPPT) technique. Billions of connected edge devices represent the essential part of the IoT through the IP-enabled sensor networks based on IPv6 over Low power Wireless Personal Area Network (6LoWPAN). In traditional IoT edge devices, the stored energy in the non-rechargeable battery determines the node lifetime while it is being depleted with time. Therefore, purchasing billions of such batteries is costly and must be disposed of efficiently. This paper is aimed at simulating and implementing a new class of green IoT edge devices that can report
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Abstract
The study seeks to use one of the techniques (Data mining) a (Logic regression) on the inherited risk through the use of style financial ratios technical analysis and then apply for financial fraud indicators,Since higher scandals exposed companies and the failure of the audit process has shocked the community and affected the integrity of the auditor and the reason is financial fraud practiced by the companies and not to the discovery of the fraud by the auditor, and this fraud involves intentional act aimed to achieve personal and harm the interests of to others, and doing (administration, staff) we can say that all frauds carried out through the presence of the motives and factors that help th
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The research aims to demonstrate the quality of the auditor’s report by analyzing a number of models represented by the auditor’s report based on the Iraqi audit evidence and the auditor’s report in light of the application of international auditing standards for the report and the auditor’s report in light of the application of the International Auditing Standard 701, in addition to explaining the impact of applying the International Auditing Standard 701. International Auditing 701 in enhancing the quality of the auditor's report, and in order to reach these goals, a comparison was made on international experiences before and after the application of the standard in addition to the results of the questionnaire distribut
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This study has been undertaken to postulate the mechanism of impact test at low velocities. Thin-walled tubes of 100Cr6 were deformed under axial compression. In the present work there are seven velocities (4.429,4.652,5.240,5.600,5.942,6.264, 6.569) m\sec were applied to show how they effect the load, change in length, also the kinetic energy. However, the comparison between the obtained results and the other studies (Alexandar[3] , Abramowicz[4], Ayad[5]) was made the present work and Ayad data show good agreement. Load, change in length, kinetic energy were determined to understand the impact test.
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In this research we solved numerically Boltzmann transport equation in order to calculate the transport parameters, such as, drift velocity, W, D/? (ratio of diffusion coefficient to the mobility) and momentum transfer collision frequency ?m, for purpose of determination of magnetic drift velocity WM and magnetic deflection coefficient ? for low energy electrons, that moves in the electric field E, crossed with magnetic field B, i.e; E×B, in the nitrogen, Argon, Helium and it's gases mixtures as a function of: E/N (ratio of electric field strength to the number density of gas), E/P300 (ratio of electric field strength to the gas pressure) and D/? which covered a different ranges for E/P300 at temperatures 300°k (Kelvin). The results show
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The numerical simulation for the low frequency waves in dusty plasma has been studied. The studying was done by taking two special cases depending on the direction of the propagation of the wave:First, when the propagation is parallel to the magnetic field K//B,this mode is called acoustic mode.Second,when K B this mode is called cyclotron mode.In addition, every one of the two modes divided into two modes depending on the range of the frequency.The Coulomb coupling parameter was studied, with temperature T,density of the dust particles Nd ,and the charge of the particle Qd.The low frequency electrostatic waves in dusty grains were studied. Also, the properties of ion-acoustic waves and ion-cyclotron waves are shown to modify even through
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A prepared PMMA/Anthracene film of thickness 70μm was irradiated under reduced pressure ~10-3 to 60Coγ-ray dose of (0.1mrad-10krad) range. The optical properties of the irradiated films were evaluated spectrophotometrically. The absorption spectrum showed induced absorption changes in the 200-400nm range. At 359nm, where there is a decrease in radiation-induced absorption, the optical density as a function of absorbed dose is linear from 10mrad-10Krad.It can therefore, be used as radiation dosimeter for gamma ray in the range 10mrd-10krad
Channel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T
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