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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 Aug 05 2015
Journal Name
Iraqi Journal Of Science
Antimicrobial and Antibiofilm Activity of Mango Seeds Extract
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Mango fruit is one of the most nutritionally rich fruits with unique flavor, this fruit belonged to family of Anacardiaceae and it is an excellent source of vitamins specially vitamin A, carotene pigments and potassium. In this study the antimicrobial activity of mango seeds extract has been investigated against gram positive bacteria (Staphylococcus aureus and Bacillus spp.) and gram negative bacteria (Pseudomonas aeruginosa and E. coli) and yeast Candida albicans by well diffusion method in nutrient agar and the results were expressed as the diameter of bacterial inhibition zones surrounding the wells, and the antibiofilm of its extracts was observed against Staphylococcus aureus. The seeds extractions prepared by two solvents: 8

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Publication Date
Wed Nov 07 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Early detection of first degree relatives to type-II diabetes mellitus
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Objective(s): The study aims to assess the early detection of early detection of first degree relatives to type-II
diabetes mellitus throughout the diagnostic tests of Glycated Hemoglobin A1C. (HgbA1C), Oral Glucose Tolerance
Test (OGTT) and to find out the relationship between demographic data and early detection of first degree
relatives to type-II diabetes mellitus.
Methodology: A purposive "non-probability" sample of (200) subjects first degree relatives to type-II diabetes
mellitus was selected from National Center for Diabetes Mellitus/Al-Mustansria University and Specialist Center
for Diabetes Mellitus and Endocrine Diseases/Al-kindy. These related persons have presented the age of (40-70)
years old. A questio

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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
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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Publication Date
Thu Jan 01 2026
Journal Name
Rsc Advances
A dual-angle optoelectronic flow injection platform for ferrous ion (Fe <sup>2+</sup> ) determination using blue LED excitation and solar cell detection
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A new optoelectronic flow injection method is proposed for the determination of ferrous ions (Fe 2+ ) based on thiocyanate complexation to form a deep-red FeSCN 2+ complex.

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Publication Date
Sun Feb 01 2026
Journal Name
Russian Microelectronics
Structure, Optical and a Novel Approach to Low-Temperature Gas Sensing Using (SnO2)1–x(TiO2:Bi2O3)x Thin Films for NO2 Detection
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Tin oxide: titanium oxide: bismuth oxide (SnO2 )1–x(TiO 2 :Bi 2O3 ) x composites with different loading ratios (0, 0.1, 0.15, 0.2, 0.25 and 0.3) have numerous new application in microelectronics, sensors, and capacitors. This work concerned with the synthesis of (SnO 2 )1–x(TiO 2 :Bi 2O3 ) xcomposites as well as, thin films which were deposited on glass substrates as well as, silicon wafers by using pulsed laser deposition. The diffraction pattern confirms the anatase teteragonal phase of undoped tin oxide. It was observed some peaks related with titanium and bismuth oxides appeared at high loading ratios. Upon the transmission-spectra analysis, the undoped samples declared transmittance 60–67% in a visible spectrum, and the energy ga

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Theoretical And Applied Information Technology
Matching Algorithms for Intrusion Detection System based on DNA Encoding
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Pattern matching algorithms are usually used as detecting process in intrusion detection system. The efficiency of these algorithms is affected by the performance of the intrusion detection system which reflects the requirement of a new investigation in this field. Four matching algorithms and a combined of two algorithms, for intrusion detection system based on new DNA encoding, are applied for evaluation of their achievements. These algorithms are Brute-force algorithm, Boyer-Moore algorithm, Horspool algorithm, Knuth-Morris-Pratt algorithm, and the combined of Boyer-Moore algorithm and Knuth–Morris– Pratt algorithm. The performance of the proposed approach is calculated based on the executed time, where these algorithms are applied o

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Publication Date
Fri May 17 2019
Journal Name
Lecture Notes In Networks And Systems
Features Selection for Intrusion Detection System Based on DNA Encoding
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Intrusion detection systems detect attacks inside computers and networks, where the detection of the attacks must be in fast time and high rate. Various methods proposed achieved high detection rate, this was done either by improving the algorithm or hybridizing with another algorithm. However, they are suffering from the time, especially after the improvement of the algorithm and dealing with large traffic data. On the other hand, past researches have been successfully applied to the DNA sequences detection approaches for intrusion detection system; the achieved detection rate results were very low, on other hand, the processing time was fast. Also, feature selection used to reduce the computation and complexity lead to speed up the system

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Publication Date
Sun Sep 06 2015
Journal Name
Baghdad Science Journal
Synthesis, Characterization and Antibacterial Activity of Cefalexin Dervatives
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New series of Schiff bases 2(a-j) and corresponding beta-lactam derivatives 3(a-j) were synthesized from cefalexin (1) as starting material. The compound (1) was reacted with different aldehydes and ketones to give Schiff bases derivatives 2(a-j). The synthesized Schiff bases were cyclized by chloroacetyl chloride in the presence of triethylamine to form beta-lactam derivatives 3(a-j). The compounds were characterized by deremination melting point, FT-IR and 1H NMR. The beta-lactam derivatives were screened in vitro antibacterial against some bacterial species

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