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.
During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
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The aim of this research is to determine the most important and main factors that lead to Preeclampsia. It is also about finding suitable solutions to eradicate these factors and avoid them in order to prevent getting Preeclampsia. To achieve this, a case study sample of (40) patients from Medical City - Oncology Teaching Hospital was used to collect data by a questionnaire which contained (17) reasons to be investigated. The statistical package (SPSS) was used to compare the results of the data analysis through two methods (Radial Bases Function Network) and (Factorial Analysis). Important results were obtained, the two methods determined the same factors that could represent the direct reason which causes Preecla
... Show MoreThe aim of this study is to evaluating the antibacterial activity of Laurus nobilis leaves extract on E. coli isolates. Maceration and Soxhlet apparatus were used to prepare aqueous and methanolic extracts; total phenolic content and 2,2-diphenyl-1-picrylhydrazyl (DPPH) were conducted to determine the active compounds in the extracts. The results showed that both Laurus nobilis methanolic and aqueous extracts have a noticeable effect on scavenging free radicals. Free radical scavenging activity. The total phenolic contents were 28.60 ±0.12 and 16.58 ±0.11mg/g in 50 mg/ml, in methanolic and aqueous extracts respectively. The antibacterial activity of Laurus nobilis leaves extracts showed that the methanolic extract was more effective than
... Show More2-(2-amino-5-nitro-phenylazo),-phenol was ready by grouping the diazonium salt of 2-aminophenol with 4-nitroaniline.Thegeometry of azo ligand(HL)was resolved on the origin of (C.H.N) analysis,1H and 13CNMR spectra, infrared spectra and UV–vis electronic absorption spectra. Dealing with the azo ligand produced with Rh+3 and La+3ataqueous ethanol for a 1:3 metal: ligand rate, and in perfect ph. The formation for compounds have been described by utilizing flame atomic, absorption,(C.H.N),Analyses, conductivity, infrared spectra and UV–vis spectral procedures. Nature in the produced compounds, have been studied, obey the ratio of mole and continuous, variance, manners, Beer's law, yielded up a concentration, rate (1×10-4- 3×10-4M),. High
... Show More2-(2-amino-5-nitro-phenylazo) -phenol was ready by grouping the diazonium salt of 2-aminophenol with 4-nitroaniline.Thegeometry of azo ligand(HL)was resolved on the origin of (C.H.N) analysis, 1H and 13CNMR spectra, infrared spectra and UV–vis electronic absorption spectra. Dealing with the azo ligand produced with Nd+3,Cd+3,Dy+3 and Er+3at aqueous ethanol for a 1:2 metal: ligand rate, and in perfect ph. The formation for compounds have been described by utilizing flame atomic absorption,(C.H.N) Analyses, conductivity, infrared spectra and UV–vis spectral procedures. Nature in the produced compounds have been studied obey the ratio of mole and continuous variance manners, Beer's law yielded up a concentration rate (1×10-4 - 3×10-4M) .
... Show MoreThe antimicrobial activity of ginger extracts ( cold-water, hot-water, ethanolic and essential oil ) against some of pathogenic bacteria ( Escherichia coli , Salmonella sp , Klebsiella sp , Serratia marcescens, Vibrio cholerae , Staphylococcus aureus , Streptococcus sp) was investigated using Disc diffusion method , and the results were compared with the antimicrobial activity of 12 antibiotics on the same bacteria . The results showed that the ginger extracts were more effective on gram-positive bacteria than gram-negative . V. cholerae and S. marcescens,were the most resistant bacteria to the extracts used , while highest inhibition was noticed against Streptococcus sp (28 mm) . The ethanolic extract showed the broadest antibacterial ac
... Show MoreFor the period from February 2014 till May 2014, one hundred and nine lactose fermenter clinical isolates from different samples (urine, stool, wound swab, blood, and sputum) were collected from Alyarmok, Alkadimiya, and Baghdad teaching hospitals at Baghdad governorate. Identification of all Klebsiella pneumoniae isolates were carried out depending on macroscopic, microscopic characterizations, conventional biochemical tests, and Api 20E system. Fifty-three (48.62%) isolates represented K. pneumoniae; however, 51.73% represented other bacteria. Susceptibility test was achieved to all fifty-three K. pneumoniae isolates using five antibiotic disks (Ceftazidime, Ceftriaxone, Cefotaxime, Imipenem, and Meropenem). Most of tested isolates (90
... Show MoreIn the early 90s military operations and United Nations Special Commission “UNSCOM” teams have been destroyed the past Iraqi chemical program. Both operations led an extensive number of scattered remnants of contaminated areas. The quantities of hazardous materials, incomplete destructed materials, and toxic chemicals were sealed in two bunkers. Deficiency of appropriate destruction technology led to spreading the contamination around the storage site. This paper aims to introduce the environmental detection of the contamination in the storage site area using geospatial analysis technique. The environmental contamination level of nutrients and major ions such as sulphate (SO4), potassium (K), sodium (Na), magnesi
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