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Automatic voice activity detection using fuzzy-neuro classifier
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Voice Activity Detection (VAD) is considered as an important pre-processing step in speech processing systems such as speech enhancement, speech recognition, gender and age identification. VAD helps in reducing the time required to process speech data and to improve final system accuracy by focusing the work on the voiced part of the speech. An automatic technique for VAD using Fuzzy-Neuro technique (FN-AVAD) is presented in this paper. The aim of this work is to alleviate the problem of choosing the best threshold value in traditional VAD methods and achieves automaticity by combining fuzzy clustering and machine learning techniques. Four features are extracted from each speech segment, which are short term energy, zero-crossing rate, autocorrelation, and log energy. A modified version of fuzzy C-Means is then used to cluster speech segments into three clusters; two clusters for voice and one for unvoiced. After that, three feed forward neural networks are trained to adjust their weights, in which each network represents one cluster. To make the final decision regarding the class type of a given speech segment, the membership degrees of this segment in all clusters along with neural networks' decisions are given to a defuzzification step which finally gives the class type of that segment. The proposed FN-AVAD is tested on the public multimodal emotion database, Surrey AudioVisual Expressed Emotion (SAVEE), and the error rate was 2.08%. The achieved results are comparable to the results achieved by the current published works in the literature.

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Publication Date
Mon Jan 01 2024
Journal Name
2nd International Conference For Engineering Sciences And Information Technology (esit 2022): Esit2022 Conference Proceedings
Room temperature flexible sensor based on F-MWCNT modified by polypyrrole conductive polymer for NO2 gas detection
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This project sought to fabricate a flexible gas sensor based on a short functionalized multi-walled carbon nanotubes (f-MWCNTs) network for nitrogen dioxide gas detection. The network was prepared by filtration from the suspension (FFS) method and modified by coating with a layer of polypyrrole conductive polymer (PPy) prepared by the oxidative chemical polymerization to improve the properties of the network. The structural, optical, and morphological properties of the f-MWCNTs and f-MWCNTs/PPy network were studied using X-ray diffraction (XRD), Fourie-transform infrared (FTIR), with an AFM (atomic force microscopy). XRD proved that the structure of f-MWCNTs is unaffected by the synthesis procedure. The FTIR spectra verified the existence o

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Publication Date
Sun Nov 06 2022
Journal Name
Hiv Nursing
Synthesis, Structural Characterisation and Biological Activity of New Mannich Compounds Derived from Cyclohexanone Moiety
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The formation and structural investigation of three new Mannich bases are reported. The synthesis of these compounds was accomplished via a multicomponent one-pot reaction using CaCl2 as a catalyst. The reaction of the benzaldehyde, m-bromoaniline and cyclohexanone or 4-methylcyclohexanone resulted in the formation of L1 and L3, respectively. The synthesis of L2 was achieved by mixing benzaldehyde, o-bromoaniline and cyclohexanone. The isolated compounds were characterised using a range of analytical and spectroscopic techniques. These include; NMR (1H and 13C-NMR), ESMS, FTIR, electronic spectroscopy, microanalyses and melting points. The NMR data for L1 and L2 indicated the presence of one isomer in solutions, on the NMR time scale. How

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Publication Date
Thu Jun 01 2017
Journal Name
Journal Of Al-nahrain University Science
Synthesis and Biological Activity Study of New Some Schiff Bases Derived From D-Erythroascorbic Acid
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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Antimicrobial Activity of Locally Synthesized Carbon Nanosphere on Some Pathogenic Species of Bacteria and Parasites
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Antibacterial activity of CNSs against Staphylococcus aureus and Escherichia coli was estimated. Higher inhibition zone of 18 mm and 20 mm were observed against S. aureus and E.coli, respectively, at a concentration of 2 mg/ml of carbon nanosphere after 24 hrs of incubation at 37 ºC. In vitro cytotoxicity experiment was performed on two parasite strains of Leishmania donovani and Leishmania tropica by using MTT assay. L. donovani revealed more sensitiv to the CNSs than L. tropica. An intermediate level of cytotoxicity of 51.31 % was observed when 2.4 mg/ml of CNSs was incubated with L. donovani, while weak cytotoxicity of 37.20 % was shown when the

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Publication Date
Tue Jun 30 2020
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
DETECTION OF Staphylococcus aureus CAUSED OF FOOD POISONING IN RED & WHITE MEAT OFFERED IN LOCAL MARKETS: DETECTION OF Staphylococcus aureus CAUSED OF FOOD POISONING IN RED & WHITE MEAT OFFERED IN LOCAL MARKETS
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This study was conducted to investigate the presence of Staphylococcus aureus in the red and white meat available in local markets. They were selected ten samples of red and white meat randomly (Iraq, Saudi Arabia, Turkey, and Brazil) from different markets in Baghdad, and the results of reading the nutrition facts of media indication card showed that all models confirm to the Iraqi standard quality in terms of scanning all data of the media indication card, except for the birds of Bayader, where the date of expire & production date of the product was not mentioned. Also, the results of the study showed that there is no Staphylococcus aureus in local red and white meat as well as imported.

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Data Classification using Quantum Neural Network
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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

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Fuzzy Analytic Hierarchy Process FEAHP to Prioritize The Evaluation of The Main and Subsidiary Criteria in B2B Industrial Market Sectors – Applied Research
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The research aims to define the main and subsidiary criteria for evaluating the industrial market sectors and proposing a model for arranging these criteria according to priority and knowing the highest criteria in terms of relative importance in the General Company for Automobile Trade and Machinery, and for the purpose of establishing this model, experiences in the concerned company were approved, and this study proposes a multi-criteria decision model According to the FEAHP, the expanded fuzzy hierarchical analysis method enables the commercial company to develop clear strategic policies on which the company’s management system depends on determining criteria for evaluating and selecting market sectors and making appropriate

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Adoption of multi – model Assignment Fuzzy to find Optimizing for the use of internet line in the Ministry of Science and Technlogy
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We have provided in this research model multi assignment  with  fuzzy function goal has been to build programming model is correct Integer Programming fogging  after removing the case from the objective function data and convert it to real data .Pascal triangular graded mean using Pascal way to the center of the triangular.

The data processing to get rid of the case fogging which is surrounded by using an Excel 2007 either model multi assignment  has been used program LNDO to reach the optimal solution, which represents less than what can be from time to accomplish a number of tasks by the number of employees on the specific amount of the Internet, also included a search on some of the

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Publication Date
Thu May 01 2025
Journal Name
Microbes And Infectious Diseases
Molecular detection and the frequency of a pore-forming toxin in Enterococcus faecalis isolated from urinary tract infections
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Publication Date
Thu Feb 01 2018
Journal Name
European Journal Of General Medicine
The Value of Longitudinal Strain versus Coronary Angiography in Detection of Coronary Artery Disease
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Aims: The aim of this study was to evaluate the value and accuracy of longitudinal strain in detection of coronary artery disease compared to coronary angiography. Results: The left ventricular longitudinal strain-speckle tracking showed evidence of stenosis of left anterior descending artery, circumflex artery and right coronary artery in (86.1%), (76.4%), and (84.7%) respectively. For the stenosis in left anterior descending artery, the current study showed that the longitudinal strain was a good predictor for presence of significant stenosis with a sensitivity of (93.8%), specificity (75%) and accuracy (91.7%) compared with coronary angiography. For the stenosis in right coronary artery, the left ventricular longitudinal strain had

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