The problem of frequency estimation of a single sinusoid observed in colored noise is addressed. Our estimator is based on the operation of the sinusoidal digital phase-locked loop (SDPLL) which carries the frequency information in its phase error after the noisy sinusoid has been acquired by the SDPLL. We show by computer simulations that this frequency estimator beats the Cramer-Rao bound (CRB) on the frequency error variance for moderate and high SNRs when the colored noise has a general low-pass filtered (LPF) characteristic, thereby outperforming, in terms of frequency error variance, several existing techniques some of which are, in addition, computationally demanding. Moreover, the present approach generalizes on existing work tha

The special core analysis tests were accomplished on a set of core plugs for Mishrif Formation (mA, mB1, and mB2cde/mC units) in West Qurna/1 oilfield, southern Iraq. Oil relative permeability (Kro) data and the Corey-type fit of the data as functions of the brine saturation at the core outlet face for individual samples in the water-oil imbibition process to estimate relative permeability measurements by the centrifuge method were utilized. Identical correlations for oil and water relative permeabilities were extracted by steady-state and unsteady-state methods. For the mA samples, the gas-water capillary pressure curves were within a narrow range (almost identical) indicating that mA is a homogeneous unit. Kro curves for three mB2

The special core analysis tests were accomplished on a set of core plugs for Mishrif Formation (mA, mB1, and mB2cde/mC units) in West Qurna/1 oilfield, southern Iraq. Oil relative permeability (K_ro) data and the Corey-type fit of the data as functions of the brine saturation at the core outlet face for individual samples in the water-oil imbibition process to estimate relative permeability measurements by the centrifuge method were utilized. Identical correlations for oil and water relative permeabilities were extracted by steady-state and unsteady-state methods. For the mA samples, the gas-water capillary pressure curves were within a narrow range (almost identical) indicating that mA is a homogeneous unit. Kro curves for thr

This investigation was carried out to study the treatment and recycling of wastewater in the cotton textile industry for an effluent containing three dyes: direct blue, sulphur black and vat yellow. The reuse of such effluent can only be made possible by appropriate treatment method such as chemical coagulation. Ferrous and ferric sulphate with and without calcium hydroxide were employed in this study as the chemical coagulants.
The results showed that the percentage removal of direct blue ranged between 91.4 and 94 , for sulphur black ranged between 98.7 and 99.5 while for vat yellow it was between 97 and 99.

— In light of the pandemic that has swept the world, the use of e-learning in educational institutions has become an urgent necessity for continued knowledge communication with students. Educational institutions can benefit from the free tools that Google provide and from these applications, Google classroom which is characterized by ease of use, but the efficiency of using Google classroom is affected by several variables not studied in previous studies Clearly, this study aimed to identify the use of Google classroom as a system for managing e-learning and the factors affecting the performance of students and lecturer. The data of this study were collected from 219 members of the faculty and students at the College of Administra

Abstract: In accordance with contemporary Western thinking, power is an organized force with a high ability to achieve stability and social security because it possesses tools based on rational organization, which helps it to control the behavior of the individual and society and prevent them from practicing the processes of exclusion and discrimination against others in pursuit of their interests and needs. Vision The philosophers and thinkers of the theory of social contract can consolidate it, which changed the form and nature of power from the traditional heritage to the constructionWhich has contributed to the development and development of civil society - Western political, and despite the success of this experiment, especially aft

Data hiding is the process of encoding extra information in an image by making small modification to its pixels. To be practical, the hidden data must be perceptually invisible yet robust to common signal processing operations. This paper introduces a scheme for hiding a signature image that could be as much as 25% of the host image data and hence could be used both in digital watermarking as well as image/data hiding. The proposed algorithm uses orthogonal discrete wavelet transforms with two zero moments and with improved time localization called discrete slantlet transform for both host and signature image. A scaling factor ? in frequency domain control the quality of the watermarked images. Experimental results of signature image

A loS.sless (reversible) data hiding (embedding) method  inside  an image  (translating medium)  - presented   in  the  present  work  using  L_SB (least  significant  bit). technique  which  enables  us to translate   data  using an  image  (host  image),  using  a  secret  key, to  be  undetectable  without losing  any  data  or  without   changing   the  size  and  the  external   scene (visible  properties) of the image, the hid-ing data is then can  be extracted (without  losing)   by reversing &n

In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that