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). The method was tested on Single-Input Single-Output (SISO),the 2×2 Alamouti space-time code,and 4×4 Quasi-Orthogonal Space-Time Block Coding (QO-STBC) in six standard situations: Nakagami fading,Log-Normal shadowing,Multipath fading,Gaussian,Rayleigh fading,and Rician fading. Channel identification was nearly perfect,and the SNR was robust,with most SNR errors being in adjacent bins indicating stable behaviour. The model reached 99.68% validation accuracy with 8.14 × 10−5 bit error rate (BER) and reduced complexity of 1.78 × 108 for high order of subcarriers The method’s novelty lies in accurate,low-complexity CE support from raw symbols and its demonstrated impact on end-to-end BER pilotless CE and SNR estimation to select equalizer without CSI reconstruction.
The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system
... Show MoreThyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise
... Show MoreAbstract
A two electrode immersion electrostatic lens used in the design
of an electron gun, with small aberration, has been designed using
the finite element method (FEM). By choosing the appropriate
geometrical shape of there electrodes the potential V(r,z) and the
axial potential distribution have been computed using the FEM to
solve Laplace's equation.
The trajectory of the electron beam and the optical properties of
this lens combination of electrodes have been computed under
different magnification conditions (Zero and infinite magnification
conditions) from studying the properties of the designed electron
gun can be supplied with Abeam current of 5.7*10-6 A , electron
gun with half acceptance
The research aims to reveal the methods of visual intertextuality used in the websites of the oriented satellite channel which is Arabic-speaking when addressing normalization with Israel. It also indicates the sources and types of intertextual images, the methodological and semiotic mechanisms for analyzing the intertextuality of news images used on the website of Alhurra satellite channel for the period from 1/6 - 30/8/2022, which included (94) images. The researcher analyzed (37) images with intertextual dimensions, excluding (57) images, which did not carry connotations connected with the inputs and objectives of the research.
The research reach
... Show MoreIn this paper, the method of estimating the variation of Zenith Path Delay (ZPD) estimation method will be illustrate and evaluate using Real Time Kinematic Differential Global Positioning System (RTK-DGPS). The GPS provides a relative method to remotely sense atmospheric water vapor in any weather condition. The GPS signal delay in the atmosphere can be expressed as ZPD. In order to evaluate the results, four points had been chosen in the university of Baghdad campus to be rover ones, with a fixed Base point. For each rover position a 155 day of coordinates measurements was collected to overcome the results. Many models and mathematic calculations were used to extract the ZPD using the Matlab environment. The result shows that the ZPD valu
... Show MoreSemi-parametric regression models have been studied in a variety of applications and scientific fields due to their high flexibility in dealing with data that has problems, as they are characterized by the ease of interpretation of the parameter part while retaining the flexibility of the non-parametric part. The response variable or explanatory variables can have outliers, and the OLS approach have the sensitivity to outliers. To address this issue, robust (resistance) methods were used, which are less sensitive in the presence of outlier values in the data. This study aims to estimate the partial regression model using the robust estimation method with the wavel
... Show MoreHydrocarbon production might cause changes in dynamic reservoir properties. Thus the consideration of the mechanical stability of a formation under different conditions of drilling or production is a very important issue, and basic mechanical properties of the formation should be determined.
There is considerable evidence, gathered from laboratory measurements in the field of Rock Mechanics, showing a good correlation between intrinsic rock strength and the dynamic elastic constant determined from sonic-velocity and density measurements.
The values of the mechanical properties determined from log data, such as the dynamic elastic constants derived from the measurement of the elastic wave velocities in the material, should be more a
Hydrocarbon production might cause changes in dynamic reservoir properties. Thus the consideration of the mechanical stability of a formation under different conditions of drilling or production is a very important issue, and basic mechanical properties of the formation should be determined. There is considerable evidence, gathered from laboratory measurements in the field of Rock Mechanics, showing a good correlation between intrinsic rock strength and the dynamic elastic constant determined from sonic-velocity and density measurements. The values of the mechanical properties determined from log data, such as the dynamic elastic constants derived from the measurement of the elastic wave velocities in the material, should be more accurate t
... Show Morecontent Analysis for Some Type of Pillows used in Iraqi houses