No abstract

No abstract

No abstract

This paper is devoted to the development of Arabic Text Categorization System. First, a stop-words list is generated using statistical approach which captures the inflation of different Arabic words. Second, a feature representation model based on Hidden Markov Model is developed to extract roots and morphological weights. Third, a semantic synonyms merge technique is presented for feature reduction. Finally a Dewey-Index Based Back-propagation Artificial Neural Network is developed for Arabic Document Categorization. The system was compared with other classifiers and the results reveal a promising architecture.

Salmonella enterica serovar Enteritidis throughout the world, is frequently linked to food-borne illness. Products made from poultry are important sources of transmission. Therefore, this study aimed to identify the incidence of Salmonella species in Kuwait's broiler flocks and determine which antibiotics are the most effective against the various Salmonella serotypes. A total of 2064 chicken samples (liver, intestine, and caecum) were collected from dead carcasses raised ten broiler flocks, between January and December 2017. The results revealed that S. enterica were found in the chicken older than 7 days old even though they did not have any signs of a clinical illness. It means that S. enterica can enter the human food supply through slaughterhouses and the contaminate carcasses. There was significant difference between the rate of Salmonella isolation and seasons, where the winter season had higher rate of Salmonella isolation compared to the other seasons. Salmonella Enteritidis and S. typhimurium were the most frequently isolated serotypes. Antimicrobials susceptibility testing showed that 88% to 60% of the isolates were sensitive to Amoxicillin Clavulanic acid. However, most of Salmonella isolates revealed high resistance to Cefotaxime, Ampicillin, Amoxicillin, Sulfamethoxazole trimethoprim followed by Gentamycin, Spiramycin, Doxycycline and Chloramphenicol. The study highlights the implementation of unique biosecurity and biocontrol strategies for Salmonella management that can prevent the negative effects of antibiotics and can make the environment and foods derived from animals safe.