In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A

This study was focused on biotreatment of soil which polluted by petroleum compounds (Diesel) which caused serious environmental problems. One of the most effective and promising ways to treat diesel-contaminated soil is bioremediation. It is a choice that offers the potential to destroy harmful pollutants using biological activity.

Four bacterial strains were isolated from diesel contaminated soil samples. The isolates were identified by the Vitek 2 system, as Sphingomonas paucimobilis, Pentoae species, Staphylococcus aureus, and Enterobacter cloacae. The potential of biological surfactant production was tested using the Sigma 703D stand-alone tensiometer showed

This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

he assignment model represents a mathematical model that aims at expressing an important problem facing enterprises and companies in the public and private sectors, which are characterized by ensuring their activities, in order to take the appropriate decision to get the best allocation of tasks for machines or jobs or workers on the machines that he owns in order to increase profits or reduce costs and time As this model is called multi-objective assignment because it takes into account the factors of time and cost together and hence we have two goals for the assignment problem, so it is not possible to solve by the usual methods and has been resorted to the use of multiple programming The objectives were to solve the problem of

The present research aims at recognizing the difficulties and problems which hamper teachers and educators alike when using the internet for educational purposes.It discusses the benefits of the internet as a source of information or publication and as a communicative tool.Arandom sample of (30) teachers working at schools in Baghdad / Second Risafa,was selected.Three of the sample members use the internet for student project plans via internet centers, whereas 16 of them use it for chatting, emailing and research purposes.The rest of the sample have limited knowledge of the internet. The researcher used the interviewing method to gather data from

Cutaneous leishmaniasis is a disease caused by Leishmania tropica parasite. Current treatments for this parasite are undesirable because of their toxicity, resistance, and high cost. Macrophages are key players against pathogens. Nitric oxide (NO), a molecule produce by immune cells, controls intracellular killing of pathogens during infection. Silver nanoparticles (Ag NPs) demonstrated broad-spectrum activity against various types of infectious diseases. It has the ability to stimulate oxygen species production.  This study aims to analyze the macrophages activation through NO production and estimate the cytotoxicity based on the lactate dehydrogenase (LDH) release upon exposure to L. tropica and

A mixture of algae biomass (Chrysophyta, Cyanophyta, and Chlorophyte) has been investigated for its possible adsorption removal of cationic dyes (methylene blue, MB). Effect of pH (1-8), biosorbent dosage (0.2-2 g/100ml), agitated speed (100-300), particle size (1304-89μm), temperature (20-40˚C), initial dye concentration (20-300 mg/L), and sorption–desorption were investigated to assess the algal-dye sorption mechanism. Different pre-treatments, alkali, protonation, and CaCl2 have been experienced in order to enhance the adsorption capacity as well as the stability of the algal biomass. Equilibrium isotherm data were analyzed using Langmuir, Freundlich, and Temkin models. The maximum dye-sorption capacity was 26.65 mg/g at pH= 5, 25

This study was focused on biotreatment of soil which polluted by petroleum compounds (Diesel) which caused serious environmental problems. One of the most effective and promising ways to treat diesel-contaminated soil is bioremediation. It is a choice that offers the potential to destroy harmful pollutants using biological activity. Four bacterial strains were isolated from diesel contaminated soil samples. The isolates were identified by the Vitek 2 system, as Sphingomonas paucimobilis, Pentoae species, Staphylococcus aureus, and Enterobacter cloacae. The potential of biological surfactant production was tested using the Sigma 703D stand-alone tensiometer showed that these isolates are biological surfactant producers. The bet