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Noise Removal of ECG Signal Using Recursive Least Square Algorithms
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This paper shows an approach for Electromyography (ECG) signal processing based on linear and nonlinear adaptive filtering using Recursive Least Square (RLS) algorithm to remove two kinds of noise that affected the ECG signal. These are the High Frequency Noise (HFN) and Low Frequency Noise (LFN). Simulation is performed in Matlab. The ECG, HFN and LFN signals used in this study were downloaded from ftp://ftp.ieee.org/uploads/press/rangayyan/, and then the filtering process was obtained by using adaptive finite impulse response (FIR) that illustrated better results than infinite impulse response (IIR) filters did.

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Publication Date
Tue Mar 01 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
The suggested threshold to reduce data noise for a factorial experiment
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In this research, a factorial experiment (4*4) was studied, applied in a completely random block design, with a size of observations, where the design of experiments is used to study the effect of transactions on experimental units and thus obtain data representing experiment observations that The difference in the application of these transactions under different environmental and experimental conditions It causes noise that affects the observation value and thus an increase in the mean square error of the experiment, and to reduce this noise, multiple wavelet reduction was used as a filter for the observations by suggesting an improved threshold that takes into account the different transformation levels based on the logarithm of the b

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Publication Date
Tue Jan 01 2013
Journal Name
Brain Research Bulletin
A note on the probability distribution function of the surface electromyogram signal
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Publication Date
Sun May 01 2016
Journal Name
Journal Of Engineering
Improving the Accuracy of Handheld GPS Receivers Based on NMEA File Generating and Least Squares Adjustment
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This study aims to improve the quality of satellites signals in addition to increase accuracy level delivered from handheld GPS data by building up a program to read and decode data of handheld GPS. Where, the NMEA protocol file, which stands for the National Marine Electronics Association, was generated from handheld GPS receivers in real time using in-house design program. The NMEA protocol file provides ability to choose points positions with best status level of satellites such as number of visible satellite, satellite geometry, and GPS mode, which are defined as accuracy factors. In addition to fix signal quality, least squares technique was adopted in this study to minimize the residuals of GPS observations and enh

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Publication Date
Mon Mar 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Removal of Dyes from Wastewater of Textile Industries Using Activated Carbon and Activated Alumina
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This work was carried to study the capability of activated alumina from bauxite compared with activated carbon adsorption capability to reduce the color content from Al-Hilla Textile Company wastewater. Six dyes were studied from two types(reactive and dispersed) namely (blue, red, yellow) from wastewater and aqueous solutions.
Forty eight experiments were carried out to study the effect of various initial conditions (bed height, flow rate, initial concentration, pH value, temperature, and competitive adsorption) on adsorption process.
The results showed that the adsorption process using activated carbon insured a good degree of color reduction reaching (99.7%) and was better than activated bauxite which reached (95%).

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Publication Date
Tue Sep 01 2015
Journal Name
2015 Ieee International Circuits And Systems Symposium (icsys)
Investigating the impact of on-chip interconnection noise on Dynamic Thermal Management efficiency
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Dynamic Thermal Management (DTM) emerged as a solution to address the reliability challenges with thermal hotspots and unbalanced temperatures. DTM efficiency is highly affected by the accuracy of the temperature information presented to the DTM manager. This work aims to investigate the effect of inaccuracy caused by the deep sub-micron (DSM) noise during the transmission of temperature information to the manager on DTM efficiency. A simulation framework has been developed and results show up to 38% DTM performance degradation and 18% unattended cycles in emergency temperature under DSM noise. The finding highlights the importance of further research in providing reliable on-chip data transmission in DTM application.

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
An Adaptive Harmony Search Part-of-Speech tagger for Square Hmong Corpus
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Data-driven models perform poorly on part-of-speech tagging problems with the square Hmong language, a low-resource corpus. This paper designs a weight evaluation function to reduce the influence of unknown words. It proposes an improved harmony search algorithm utilizing the roulette and local evaluation strategies for handling the square Hmong part-of-speech tagging problem. The experiment shows that the average accuracy of the proposed model is 6%, 8% more than HMM and BiLSTM-CRF models, respectively. Meanwhile, the average F1 of the proposed model is also 6%, 3% more than HMM and BiLSTM-CRF models, respectively.

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Publication Date
Mon Dec 11 2017
Journal Name
Al-khwarizmi Engineering Journal
Proposed Hybrid Sparse Adaptive Algorithms for System Identification
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Abstract 

For sparse system identification,recent suggested algorithms are  -norm Least Mean Square (  -LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named  -ZA-LMS, 

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Publication Date
Fri Oct 02 2015
Journal Name
American Journal Of Applied Sciences
Advances in Document Clustering with Evolutionary-Based Algorithms
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Document clustering is the process of organizing a particular electronic corpus of documents into subgroups of similar text features. Formerly, a number of conventional algorithms had been applied to perform document clustering. There are current endeavors to enhance clustering performance by employing evolutionary algorithms. Thus, such endeavors became an emerging topic gaining more attention in recent years. The aim of this paper is to present an up-to-date and self-contained review fully devoted to document clustering via evolutionary algorithms. It firstly provides a comprehensive inspection to the document clustering model revealing its various components with its related concepts. Then it shows and analyzes the principle research wor

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Publication Date
Thu Jun 16 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Optimization algorithms for transportation problems with stochastic demand
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The purpose of this paper is to solve the stochastic demand for the unbalanced transport problem using heuristic algorithms to obtain the optimum solution, by minimizing the costs of transporting the gasoline product for the Oil Products Distribution Company of the Iraqi Ministry of Oil. The most important conclusions that were reached are the results prove the possibility of solving the random transportation problem when the demand is uncertain by the stochastic programming model. The most obvious finding to emerge from this work is that the genetic algorithm was able to address the problems of unbalanced transport, And the possibility of applying the model approved by the oil products distribution company in the Iraqi Ministry of Oil to m

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Scopus (15)
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Publication Date
Mon Apr 05 2021
Journal Name
Solid State Technology
Genetic Algorithms in Construction Project Management: A Review
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Genetic algorithms (GA) are a helpful instrument for planning and controlling the activities of a project. It is based on the technique of survival of the fittest and natural selection. GA has been used in different sectors of construction and building however that is rarely documented. This research aimed to examine the utilisation of genetic algorithms in construction project management. For this purpose, the research focused on the benefits and challenges of genetic algorithms, and the extent to which genetic algorithms is utilised in construction project management. Results showed that GA provides an ability of generating near optimal solutions which can be adopted to reduce complexity in project management and resolve difficult problem

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