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SPEECH RECOGNITION OF ARABIC WORDS USING ARTIFICIAL NEURAL NETWORKS
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The speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. Twenty three Arabic words were recorded fifteen different times in a studio
by one speaker to form a database. The performance of the proposed system using this
database has been evaluated by computer simulation using MATLAB package. The result
shows recognition accuracy of 65%, 70% and 80% using DWT (Db1), DWT (Db4) and SLT
respectively.

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Publication Date
Fri Jan 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
BotDetectorFW: an optimized botnet detection framework based on five features-distance measures supported by comparisons of four machine learning classifiers using CICIDS2017 dataset
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<p><span>A Botnet is one of many attacks that can execute malicious tasks and develop continuously. Therefore, current research introduces a comparison framework, called BotDetectorFW, with classification and complexity improvements for the detection of Botnet attack using CICIDS2017 dataset. It is a free online dataset consist of several attacks with high-dimensions features. The process of feature selection is a significant step to obtain the least features by eliminating irrelated features and consequently reduces the detection time. This process implemented inside BotDetectorFW using two steps; data clustering and five distance measure formulas (cosine, dice, driver &amp; kroeber, overlap, and pearson correlation

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Publication Date
Thu Jun 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Clients' Satisfaction with Nursing Services by Using the Patient Satisfaction with Nursing Care (PSNCS): An Applied Research in some of Baghdad Teaching Hospitals
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Abstract:

     This study aims to identify the level of patients’ satisfaction among a sample of hospitalized patients in the targeted hospital (Al-Kindy Teaching Hospital, and Al-Yarmook Teaching Hospital). Moreover, this study highlights the reality of services for patients, especially in the targeted governmental teaching hospitals. The Patient Satisfaction with Nursing Care (PSNCS) has been measured in these hospitals through the revised scale by Tang et al, (2013).This scale includes four major domains; Health Information (5 items), Influencing Support (4 items), Decision Control (4 items), Specialized Technical Competence (7 items). The method of surveying patients’ opinions about the degree

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Publication Date
Wed Nov 26 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Management of Independent Middle Mesial Canal in Mandibular First Molar Using Cone Beam Computed Tomography Imaging as an Adjunct – A Case Report
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The primary objective of root canal therapy is adequate biomechanical preparation of root canal system followed by 3D obturation.in clinics we are encountered with several anatomical variations, which we need to manage efficiently. One of the major factors responsible for failure of root canal therapy is missed canals. Recent technological advances have given the clinician opportunity to identify anatomical variations and treat them to satisfaction.

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Publication Date
Wed Jun 29 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Kinetics and Energetic Parameters Study of Phenol Removal from Aqueous Solution by Electro-Fenton Advanced Oxidation Using Modified Electrodes with PbO2 and Graphene
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The Electro-Fenton oxidation process is one of the essential advanced electrochemical oxidation processes used to treat Phenol and its derivatives in wastewater. The Electro-Fenton oxidation process was carried out at an ambient temperature at different current density (2, 4, 6, 8 mA/cm2) for up to 6 h. Sodium Sulfate at a concentration of 0.05M was used as a supporting electrolyte, and 0.4 mM of Ferrous ion concentration (Fe2+) was used as a catalyst. The electrolyte cell consists of graphite modified by an electrodepositing layer of PbO2 on its surface as anode and carbon fiber modified with Graphene as a cathode. The results indicated that Phenol concentration decreases with an increase in current dens

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Publication Date
Sat Jan 01 2022
Journal Name
Ssrn Electronic Journal
Developing a Predictive Model and Multi-Objective Optimization of a Photovoltaic/Thermal System Based on Energy and Exergy Analysis Using Response Surface Methodology
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Publication Date
Fri Jan 01 2021
Journal Name
Int. J. Agricult.
FORECASTING THE EXCHANGE RATES OF THE US DOLLAR AGAINST THE IRAQI DINAR USING THE BOX-JENKINS METHODOLOGY IN TIME SERIES WITH PRACTICAL APPLICATION
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The goal of the study is to discover the best model for forecasting the exchange rate of the US dollar against the Iraqi dinar by analyzing time series using the Box Jenkis approach, which is one of the most significant subjects in the statistical sciences employed in the analysis. The exchange rate of the dollar is considered one of the most important determinants of the relative level of the health of the country's economy. It is considered the most watched, analyzed and manipulated measure by the government. There are factors affecting in determining the exchange rate, the most important of which are the amount of money, interest rate and local inflation global balance of payments. The data for the research that represents the exchange r

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Scopus
Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Engineering
A Mathematical Model of a Thermally Activated Roof (TAR) Cooling System Using a Simplified RC-Thermal Model with Time Dependent Supply Water Temperature
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This paper presents a computer simulation model of a thermally activated roof (TAR) to cool a room using cool water from a wet cooling tower. Modeling was achieved using a simplified 1-D resistance-capacitance thermal network (RC model) for an infinite slab. Heat transfer from the cooling pipe network was treated as 2-D heat flow. Only a limited number of nodes were required to obtain reliable results. The use of 6th order RC-thermal model produced a set of ordinary differential equations that were solved using MATLAB - R2012a. The computer program was written to cover all possible initial conditions, material properties, TAR system geometry and hourly solar radiation. The cool water supply was considered time

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Publication Date
Sun Feb 17 2019
Journal Name
Iraqi Journal Of Physics
Nucleon momentum distributions and elastic electron scattering form factors for 58Ni, 60Ni, 62Ni, and 64Ni isotopes using the framework of coherent fluctuation model
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The nucleon momentum distributions (NMD) and elastic electron scattering form factors of the ground state for some 1f-2p-shell nuclei, such as 58Ni, 60Ni, 62Ni, and 64Ni
isotopes have been calculated in the framework of the coherent fluctuation model (CFM) and expressed in terms of the weight function lf(x)l. The weight function (fluctuation function) has been related to the nucleon density distribution (NDD) of the nuclei and determined from the theory and experiment. The NDD is derived from a simple method based on the use of the single particle wave functions of the harmonic oscillator potential and the occupation numbers of the states. The feature of the l

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Publication Date
Sun Jan 01 2017
Journal Name
Analytical Methods
Determination of pharmaceuticals in freshwater sediments using ultrasonic-assisted extraction with SPE clean-up and HPLC-DAD or LC-ESI-MS/MS detection
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A robust and sensitive analytical method is presented for the extraction and determination of six pharmaceuticals in freshwater sediments.

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Publication Date
Fri Jan 01 2021
Journal Name
Artificial Intelligence For Covid-19
An Efficient Mixture of Deep and Machine Learning Models for COVID-19 and Tuberculosis Detection Using X-Ray Images in Resource Limited Settings
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Scopus (33)
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