Corona virus sickness has become a big public health issue in 2019. Because of its contact-transparent characteristics, it is rapidly spreading. The use of a face mask is among the most efficient methods for preventing the transmission of the Covid-19 virus. Wearing the face mask alone can cut the chance of catching the virus by over 70\%. Consequently, World Health Organization (WHO) advised wearing masks in crowded places as precautionary measures. Because of the incorrect use of facial masks, illnesses have spread rapidly in some locations. To solve this challenge, we needed a reliable mask monitoring system. Numerous government entities are attempting to make wearing a face mask mandatory; this process can be facilitated by using face mask detection software based on AI and image processing techniques. For face detection, helmet detection, and mask detection, the approaches mentioned in the article utilize Machine learning, Deep learning, and many other approaches. It will be simple to distinguish between persons having masks and those who are not having masks using all of these ways. The effectiveness of mask detectors must be improved immediately. In this article, we will explain the techniques for face mask detection with a literature review and drawbacks for each technique.
Lipase enzyme has attracted a lot of attention in recent years because of its diverse biotechnological applications. The present study was conducted to screen germinated seeds of four crops, namely sunflower (Helianthus annuus), flaxor linseed (Linum usitatissimum ), peanut (Arachis hypogaea ) and castor bean (Ricinus communis), for the activity of their lipases. to the study also included the extraction and purification of lipase from the seeds of the most promising crop using different solvents. The results indicated that the maximum enzymatic activity (0.669 U/ml) was obtained when 0.1 M Tris-HCl buffer extract was used after 3 days of seed germination of all the tested species, as compared to the other test solvents
... Show MoreStability of laminated plate under thermal load varied linearly along thickness, is developed using a higher order displacement field which depend on a parameter “m”, whose value is optimized to get results closest to three-dimension elasticity results. Hamilton, s principle is used to derive equations of motion for laminated plates. These equations are solved using Navier-type for simply supported boundary conditions to obtain non uniform critical thermal buckling and fundamental frequency under a ratio of this load. Many design parameters of cross ply and angle ply laminates such as, number of layers, aspect ratios and E1/E2 ratios for thick and thin plates are investigated. It is observed that linear and uniform distribution of
... Show MoreInvestigation of mesomorphic properties of new 1,3,4-thiadiazolines (which are synthesised via many steps in Scheme 1) was carried out in this study. These compounds are designed to have a heterocyclic unit, a carboxylate linkage group and a polar ether chain at the end of the molecule adjacent to the benzene ring, which enhance the dipolar interactions forces (varied from one to eight carbons) to investigate the association properties of their phases. The structure of the target compounds and the intermediates were confirmed by 1H NMR, 13C NMR, mass and FTIR spectral techniques. Polarised microscopic studies revealed that all the compounds in the series exhibited enantiotropic liquid crystalline properties. This was further confirmed using
... Show MoreAtorvastatin (ATR) is a poorly water-soluble anti-hyperlipidemic drug. The drug belongs to the class II group according to the biopharmaceutical classification system (BCS) with low bioavailability due to its low solubility. Solid dispersion is an effective technique for enhancing the solubility and dissolution of drugs. Phospholipid solid dispersion (PSD) using phosphatidylcholine (PC) as a carrier with or without adsorbent (magnesium aluminum silicate, silicon dioxide 15nm, silicon dioxide 30nm, calcium silicate) was used to prepare ATR PSD using different drug: PC: adsorbent ratios by solvent evaporation method. The resulted PSD was evaluated for its percentage yield, drug content, solubility, dissolution rate, Fourier transforma
... Show MoreDeep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to
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The aim of this study was to prepare rebamipide ocular inserts in order to extend its release on the ocular surface for dry eye treatment. Solubility study was applied to the drug with or without l-arginine using different solvents. Solvent casting technique was used to prepare the inserts; l-arginine was used to solubilize the drug, hydroxypropyl methylcellulose grades (E5 and K15M) and poly ethylene glycol 200 were used as excipients. The inserts were evaluated for their physical and mechanical properties, moisture loss% and absorption %, surface pH, and in-vitro drug release. The use l-arginine exhibited an enhancement of rebamipide solubility in both deionized water and phosphate buffer (pH 7.4) by a
... Show MoreData generated from modern applications and the internet in healthcare is extensive and rapidly expanding. Therefore, one of the significant success factors for any application is understanding and extracting meaningful information using digital analytics tools. These tools will positively impact the application's performance and handle the challenges that can be faced to create highly consistent, logical, and information-rich summaries. This paper contains three main objectives: First, it provides several analytics methodologies that help to analyze datasets and extract useful information from them as preprocessing steps in any classification model to determine the dataset characteristics. Also, this paper provides a comparative st
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