The speaker identification is one of the fundamental problems in speech processing and voice modeling. The speaker identification applications include authentication in critical security systems and the accuracy of the selection. Large-scale voice recognition applications are a major challenge. Quick search in the speaker database requires fast, modern techniques and relies on artificial intelligence to achieve the desired results from the system. Many efforts are made to achieve this through the establishment of variable-based systems and the development of new methodologies for speaker identification. Speaker identification is the process of recognizing who is speaking using the characteristics extracted from the speech's waves like pitch, tone, and frequency. The speaker's models are created and saved in the system environment and used to verify the identity required by people accessing the systems, which allows access to various services that are controlled by voice, speaker identification involves two main parts: the first part is the feature extraction and the second part is the feature matching.
Fusobacterium are compulsory anaerobic gram-negative bacteria, long thin with pointed ends, it causes several illnesses to humans like pocket lesion gingivitis and periodontal disease; therefore our study is constructed on molecular identification and detection of the fadA gene which is responsible for bacterial biofilm formation. In this study, 10.2% Fusobacterium spp. were isolated from pocket lesion gingivitis. The isolates underwent identification depending on several tests under anaerobic conditions and biochemical reactions. All isolates were sensitive to Imipenem (IPM10) 42.7mm/disk, Ciprofloxacin (CIP10) 27.2mm/disk and Erythromycin (E15) 25mm/disk, respectively. 100% of
Petroleum is one of the most important substances consumed by man at present times, a major energy source in this century, petroleum oils can cause environmental pollution during various stages of production, transportation, refining and use, petroleum hydrocarbons pollutions ranging from soil, ground water to marine environment, become an inevitable problem in the modern life, current study focused on bioremediation process of hydrocarbons contaminants that remaining in the bottom of gas cylinders and discharged to the soil. Twenty-four bacterial isolates were isolated from contaminated soils all of them gram negative bacteria, bacterial isolates screening to investigate the ability of biodegradation of hydrocarbons, these isolates inocula
... Show MoreSludge worm samples were collected from the Tigers River sediment during the period from November 2018 to June 2019 in Al Sarafiya District/ Baghdad- Iraq. Biometric morphological measurements focusing on the form of penis sheath and chaetal morphology were used for species identification, in addition to molecular analysis by amplification of conserved 18s rRNA encoding gene using ITS1 and ITS4 universal primers.According to the morphological measurement records, the results revealed the existence of Limnodrilus hoffmeisteri Claparede 1862, L. claparedeianus Ratzel, 1868 and L. cervix Brinkhurst 1963. Other two groups of specimens, with short penis sheath, were identified by molecular technology as L
Yersinia enterocolitica has ranked a third among the pathogens that most frequently cause gastrointestinal disorders transmitted to humans through food materials, especially contaminated meats. The meat infected with Yersinia enterocolitica had no change in apparent texture or smell. The aim of this research is to survey the frequency of Y. enterocolitica in ovine meat, compare their ratio of infection between the season, To carry out this study (125) samples of local ovine meat were collected by random sampling from the middle region of Iraq. The samples were divided into two groups steak and mince, then many microbiological tests (culture, & staining, biochemical Tests Api 20E, Vitik 2 and species-specific PCR amplicon for 16S RNA gene) w
... Show MoreEimeriosis is a major problem affecting ruminants worldwide. The disease is primarily caused by Eimeria species, which are specialized for each host and grow in the small and large intestine of animals. The losses due to subclinical infections (especially weight loss) and clinical disease (diarrhea) make the species of this genus a very significant economic concern. Therefore, this study was conducted in some areas of Wasit Province. A total of 180 fecal samples from goats, of both sexes and covering different age groups and months, were collected. All fecal samples were examined microscopically, and 75 positive fecal samples were taken for molecular examination and further analyzed using conventional PCR, sequencing and phylogeneti
... Show MoreChurning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date. A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s
... Show MoreRecurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al
... Show MoreTwo Schiff bases, namely, 3-(benzylidene amino) -2-thioxo-6-methyl 2,5-dihydropyrimidine-4(3H)-one (LS])and 3-(benzylidene amino)-6-methyl pyrimidine 4(3H, 5H)-dione(LA)as chelating ligands), were used to prepare some complexes of Cr(III), La(III), and Ce(III)] ions. Standard physico-chemical procedures including metal analysis M%, element microanalysis (C.H.N.S) , magnetic susceptibility, conductometric measurements, FT-IR and UV-visible Spectra were used to identify Metal (III) complexes and Schiff bases (LS) and (LA). According to findings, a [Cr(III) complex] showed six coordinated octahedral geometry, while [La(III), and Ce(III) complexes]were structured with coordination number seven. Schiff's bases a
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