The exponential growth of audio data shared over the internet and communication channels has raised significant concerns about the security and privacy of transmitted information. Due to high processing requirements, traditional encryption algorithms demand considerable computational effort for real-time audio encryption. To address these challenges, this paper presents a permutation for secure audio encryption using a combination of Tent and 1D logistic maps. The audio data is first shuffled using Tent map for the random permutation. The high random secret key with a length equal to the size of the audio data is then generated using a 1D logistic map. Finally, the Exclusive OR (XOR) operation is applied between the generated key and the sh

      Detecting and subtracting the Motion objects from backgrounds is one of the most important areas. The development of cameras and their widespread use in most areas of security, surveillance, and others made face this problem. The difficulty of this area is unstable in the classification of the pixels (foreground or background). This paper proposed a suggested background subtraction algorithm based on the histogram. The classification threshold is adaptively calculated according to many tests. The performance of the proposed algorithms was compared with state-of-the-art methods in complex dynamic scenes.

The gas-lift method is crucial for maintaining oil production, particularly from an established field when the natural energy of the reservoirs is depleted. To maximize oil production, a major field's gas injection rate must be distributed as efficiently as possible across its gas-lift network system. Common gas-lift optimization techniques may lose their effectiveness and become unable to replicate the gas-lift optimum in a large network system due to problems with multi-objective, multi-constrained & restricted gas injection rate distribution. The main objective of the research is to determine the possibility of using the genetic algorithm (GA) technique to achieve the optimum distribution for the continuous gas-lift injectio

    Water contamination is a pressing global concern, especially regarding the presence of nitrate ions. This research focuses on addressing this issue by developing an effective adsorbent for removing nitrate ions from aqueous solutions. two adsorbents Chitosan-Zeolite-Zirconium (Cs-Ze-Zr composite beads and Chitosan-Bentonite-Zirconium Cs-Bn-Zr composite beads were prepared. The study involved continuous experimentation using a fixed bed column with varying bed heights (1.5 and 3 cm) and inlet flow rates (1 and 3 ml/min). The results showed that the breakthrough time increased with higher bed heights for both Cs-Ze-Zr and Cs-Bn-Zr composite beads. Conversely, an increase in flow rate led to a decrease in breakthrough time. Notab

Liquid electrodes of domperidone maleate (DOMP) imprinted polymer were synthesis based on precipitation polymerization mechanism. The molecularly imprinted (MIP) and non-imprinted (NIP) polymers were synthesized using DOMP as a template. By methyl methacrylate (MMA) as monomer, N,Nmethylenebisacrylamide (NMAA) and ethylene glycol dimethacrylate (EGDMA) as cross-linkers and benzoyl peroxide (BP) as an initiator. The molecularly imprinted membranes were synthesis using acetophenone (APH), di-butyl sabacate (DBS), Di octylphthalate (DOPH) and triolyl phosphate (TP)as plasticizers in PVC matrix. The slopes and limit of detection of l

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images.

So, this study aimed at testing the system performance at poor s

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poo

We use of multi-choice Goal Programming (MCGP), which is a developed model of Goal Programming where it is used in circumstances of the multiplicity and difference of goals when choosing between decision alternatives in cases of allocating resources, as it is a model that seeks to find the closest and best solutions to the specific values ​​of the goals within the aspiration levels, as the first goal in the multi-choice goal programming model that is used to reduce the total cost of storage and shortage, while the other goal was to reduce the difference between the real demand that the hospitals need from the blood transfusion center and the units that already achieved. The case Iraqi Center