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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
Wed Apr 02 2014
Journal Name
Journal Of Theoretical And Applied Information Technology
TUMOR BRAIN DETECTION THROUGH MR IMAGES: A REVIEW OF LITERATURE
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Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by usin

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Publication Date
Sun Dec 01 2019
Journal Name
Al-nahrain Journal Of Science
Enhancing Sparse Adjacency Matrix for Community Detection in Large Networks
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Publication Date
Thu Jan 01 2015
Journal Name
Journal Of Al-mansoor College
An Improvement to Face Detection Algorithm for Non-Frontal Faces
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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Practical Study for the Properties of Hueckel Edge Detection Operator
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Publication Date
Tue Oct 26 2021
Journal Name
Remote Sensing Technologies And Applications In Urban Environments Vi
DTM Extraction and building detection in DSMs having large holes
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Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
: financial fraud ,Audit risks ,inherent risk ,Detection risk, Data Mining .
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Abstract

The study seeks to use one of the techniques (Data mining) a (Logic regression) on the inherited risk through the use of style financial ratios technical analysis and then apply for financial fraud indicators,Since higher scandals exposed companies and the failure of the audit process has shocked the community and affected the integrity of the auditor and the reason is financial fraud practiced by the companies and not to the discovery of the fraud by the auditor, and this fraud involves intentional act aimed to achieve personal and harm the interests of to others, and doing (administration, staff) we can say that all frauds carried out through the presence of the motives and factors that help th

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Publication Date
Sat Apr 05 2025
Journal Name
2025 Ieee 4th International Conference On Computing And Machine Intelligence (icmi)
From Pixels to Diagnosis: AI-Powered CNN for Pneumonia Detection
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Publication Date
Sun Dec 20 2020
Journal Name
International Journal Of Pharmaceutical Research
Synthesis, Characterization and Biological Activity of New Compounds Derived from Dapsone
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New derivatives of the anti-inflammatory, leprostatic drug dapsone 4 are synthesized, characterized and biologically screened by the treating the drug dapsone with chloroacetyl chloride in the presence of base. Both amino groups are acylated to give compound 6. The symmetrical acylated product then treated with Phenol, N-Acetyl-p-aminophenol, p-Chlorophenol, m-Chlorophenol, o-Hydroxybezoic acid and m-Hydroxybezoic acid to give compounds 8(a-f). The antimicrobial activity was tested for the synthesized compounds; activates were good compared to the parent drug. All the new compounds have scanned for their biological activities toward gram ‒ve and gram +ve (M. tuberculosis, S. pneumoniae, E. coli and P. mirabilis) bacteria, the synthesized

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Publication Date
Sun Mar 30 2008
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Effect of Promoters on the Catalytic Activity of the Iosmerization Catalyst
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The crystalline zeolite, namely faujasite type Y with SiO2/Al2O3 mole ratio of 5 was used as raw material for preparation of isomerization catalysts. A 0.5 wt % Pt/HY-zeolite catalyst was prepared by impregnation of the decationized HY-zeolite with chloroplatinic acid. The dectionized HY-zeolite was treated with HCl, HNO3 and HI promoters using different normalities and with different concentrations of Sn, Ni and Ti promoters by impregnation method to obtain acidic and metallic promoters' catalysts, respectively. A 0.5 wt% of Pt was added to above catalysts using impregnation method. Isomerization of n-hexane was carried out at different prepared catalysts. The isomerization temperature varied from 250–325° C over weight hourly space

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Publication Date
Wed Jun 29 2016
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
Study the Activity of some plant resources as natural antioxidant: Study the Activity of some plant resources as natural antioxidant
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This study was done to test the activity of some plant extracts as antioxidant agents. The plants were (Morus rubra, Hibiscus sabdariffa L ., Rhus coriaria L., Anethum graveolens and Petroselinum sativum).
Ethanolic 98% (24 hours/ 25˚c) and distilled water (30 minutes/ 25˚c have been used for extraction.The Total phenols, total flavonoids, total anthocyanin, antioxidant activities were studied.
The extract of Morus rubra was chosen because it has a higher antioxidant activity.
The phenolic extract of Morus rubra was prepare and examined by application it in burger . The antioxidant activity test of Morus rubra was made before and after 3,6 days of cold storage. The sensory evaluation of all treatments were done within 5,1

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