The ratio of draft tube to reactor diameters is of decisive importance for the operation behavior of air lift loop reactors. The influence of draft tube geometry was investigated with respect to oxygen mass transfer and mixing time. The diameter ratio was varied between 0.33 and 0.80. The measurements were performed in two loop reactors with liquid capacities of 11.775 and 26.49 liters using aqueous with solutions of different coalescence behavior. The results show that there is no single diameter ratio which would produce most favorable conditions for the two process parameters. With respect to the more important requirements of aerobic cultures, i.e high oxygen mass transfer and efficient mixing, a diameter ratio between 0.5 and 0.6 is

In this research is to study the influence of the aging heat treatment on the pitting corrosion resistance of martensitic stainless steel (MSS), where a number of specimens from martensitic stainless steel were subjected to solution treatment at 1100 ^oC for one hour followed by water quenching then aging in the temperatures range (500-750) ^oC for different holding times (1,5,10,15&20) hr. Accelerated chemical corrosion test and immersion chemical corrosion test were performed on samples after heat treatment. The results of the research showed that the pitting corrosion resistance is significantly affected by the aging temperature. Where found that the aging samples at a temperature of 500 °C have the highest ra

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

Aluminum doped zinc selenide ZnSe/n-Si thin films of (250∓20 nm) thickness with (0.01, 0.02 and 0.03), are depositing on the two type of substrate (glass and n-Si) to manufacture (ZnSe/n-Si) solar cell through using thermal vacuum evaporation procedure. physical and optoelectronic properties were examined for the samples. X-Ray and AFM techniques are using to study the structure properties. The energy band gap of as-deposited ZnSe thin films for changed dopant ratio were ranging from (2.6-2.68 eV). The results of Hall effect show that pure and doping films were (p-type), and the concentration carriers and the carriers mobility increases with increase Al-dopant ratio. The (C-V) have shown that the heterojunction were of abrupt type. In add