The Gram-negative bacillus Serratia marcescens (S. marcescens) belongs to the Enterobacteriaceae family. S. marcescens was once thought to be a nonpathogenic saprophytic organism that appeared on decomposing organic matter, animals, plants, and foods, water, and soil. However, it has evolved into an opportunist pathogen that causes nosocomial infections, where it is linked to a variety of hospital-acquired infections, including conjunctivitis, septicemia, wound, and eye infections, pneumonia, meningitis, osteomyelitis, and endocarditis, in addition to respiratory tract and urinary tract infections (UTI). Chitinase, protease, nuclease, lipase, and hemolysin are among the products released by S. marcescens strains, and many of these c

natural and non-natural disasters, is an environmental challenges the society and the economy as well as a direct and indirect economic affect, and the units are part of the system overlapping among themselves and thus affected by external indicators, directly or indirectly, these direct effects appear in the destruction or damage inflicted by disasters in property , infrastructure , superstructure , accounting information systems and indirectly in the outcome of future business, comes research problem through access to accounting treatments issued by the Federal Office of financial supervision to address the damage caused by the disasters and prepare the missing financial accounts it turns out us that there is negligence of a nu

Clerodendrum plant is believed to be very useful in many countries for treating various health disorders .“in this study was undertaken to assess antimicrobial activity of ethanol and aqueous extracts of clerodendrum plant”. Display my alcoholic extract higher inhibition of the aqueous extract all of the bacteria (Esherichia Coli , Pseudomonas aeruginosa, Bacillus subtilis). While the inhibition of the aqueous extract bacteria (Streptococcus, Shigelladysenteria) in higher alcoholic extract. However, the bacteria (Klebseillapneumoniae) did not shown any inhibition zone for both aqueous and alcoholic extracts. From the above results,“ it is concluded the antibacterial properties of Clerodendrum against life threatening pathogens”. So,

The extraction process of chlorophyll from dehydrated and pulverized alfalfa plant were studied by percolation method. Two  solvent systems were used for the extraction namely; Ethanol-water and Hexane-Toluene systems . The effect of circulation rate, solvent concentration, and solvent volume to solid weight ratio were studied. In  both ethanol water, and Hexane-Toluene systems it appears that solvent concentration is the most effective variable.

The Internet of Things (IoT) is an expanding domain that can revolutionize different industries. Nevertheless, security is among the multiple challenges that it encounters. A major threat in the IoT environment is spoofing attacks, a type of cyber threat in which malicious actors masquerade as legitimate entities. This research aims to develop an effective technique for detecting spoofing attacks for IoT security by utilizing feature-importance methods. The suggested methodology involves three stages: preprocessing, selection of important features, and classification. The feature importance determines the most significant characteristics that play a role in detecting spoofing attacks. This is achieved via two techniques: decision tr

Methods of speech recognition have been the subject of several studies over the past decade. Speech recognition has been one of the most exciting areas of the signal processing. Mixed transform is a useful tool for speech signal processing; it is developed for its abilities of improvement in feature extraction. Speech recognition includes three important stages, preprocessing, feature extraction, and classification. Recognition accuracy is so affected by the features extraction stage; therefore different models of mixed transform for feature extraction were proposed. The properties of the recorded isolated word will be 1-D, which achieve the conversion of each 1-D word into a 2-D form. The second step of the word recognizer requires, the

The area of character recognition has received a considerable attention by researchers all over the world during the last three decades. However, this research explores best sets of feature extraction techniques and studies the accuracy of well-known classifiers for Arabic numeral using the Statistical styles in two methods and making comparison study between them. First method Linear Discriminant function that is yield results with accuracy as high as 90% of original grouped cases correctly classified. In the second method, we proposed algorithm, The results show the efficiency of the proposed algorithms, where it is found to achieve recognition accuracy of 92.9% and 91.4%. This is providing efficiency more than the first method.

Natural settings make it challenging to identify facial expressions since head position, illumination level, and ‎‎occlusion vary. Thus, developing a more generic model without front-facing images alone is quite crucial. This ‎research proposes a facial expression ‎recognition model based on pre-trained deep convolutional neural networks ‎with transfer learning. The model was trained ‎on several cases to classify face expressions into seven ‎classifications efficiently. The proposed system used the EfficientNetB0 model ‎that has one dense dropout layer. The model first rescales and norms the input dataset in the input ‎layer that takes images of a larger resolution to get better results. After entering 7 blocks sequential