This research has presented a solution to the problem faced by alloys: the corrosion problem, by reducing corrosion and enhancing protection by using an inhibitor (Schiff base). The inhibitor (Schiff base) was synthesized by reacting of the substrates materials (4-dimethylaminobenzaldehyde and 4-aminoantipyrine). It was diagnosed by infrared technology IR, where the IR spectrum and through the visible beams proved that the Schiff base was well formed and with high purity. The corrosion behavior of carbon steel and stainless steel in a saline medium (artificial seawater 3.5%NaCl) before and after using the inhibitor at four temperatures: 20, 30, 40, and 50 C° was studied by using thr

This research has presented a solution to the problem faced by alloys: the corrosion problem, by reducing corrosion and enhancing protection by using an inhibitor (Schiff base). The inhibitor (Schiff base) was synthesized by reacting of the substrates materials (4-dimethylaminobenzaldehyde and 4-aminoantipyrine). It was diagnosed by infrared technology IR, where the IR spectrum and through the visible beams proved that the Schiff base was well formed and with high purity. The corrosion behavior of carbon steel and stainless steel in a saline medium (artificial seawater 3.5%NaCl) before and after using the inhibitor at four temperatures: 20, 30, 40, and 50 C° was studied by using three electrodes potentiostat. The corrosion behavior was

Background: Polymer surfaces usually present problems in bonding and finishing due to their low hydrophilicity. The aim of this study is to investigate the effect of plasma treatment with the use of two types of gases (oxygen and argon) on surface roughness, and chemical surface properties of acrylic resin denture base polymer material. Materials and Methods: Three heat cured acrylic resin specimens of (2*8*30 mm) dimensions were prepared for each test carried out in this study. Two tests were conducted, surface roughness test and chemical surface analysis test. Results: Application of plasma treatment increased surface roughness for both oxygen and argon plasma treated acrylic resin specimen groups compared with control untreated group,

This research deals with increasing the hardening and insulating the petroleum pipes against the conditions and erosion of different environments. So, basic material of epoxy has been mixed with Ceramic Nano Zirconia reinforcement material 35 nm with the percentages  (0,1,2,3,4,5) %, whereas the paint basis of broken petroleum pipes was used  to paint on it, then it was cut into dimensions (2 cm. × 2 cm.) and 0.3cm high. After the paint and percentages are completed, the samples were immersed into the paint. Then, the micro-hardness was checked according to Vickers method and thermal inspection of paint, which contained (Thermal conduction, thermal flux and Thermal diffusivity), the density of the painted samples was calculate

Abstract: The international community now places significant emphasis on achieving zero carbon emissions, requiring both new researchers and experienced policymakers to prioritise this goal. This article examines the effects of carbon taxes, carbon cap and trade, renewable energy (RE) production and consumption, and economic growth (EG) on carbon emission reduction in the United States, Japan, Canada, and Australia. The study collected secondary data from the World Development Indicators (WDI) secondary source spanning the years 1991 to 2022. The study examines the relationship between variables using the cross-sectionally augmented autoregressive distributed lag (CS-ARDL) approach. The findings indicate that carbon taxes, carbon cap and tr

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the