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

General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

   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

The present work elucidates the utilization of activated carbon (AC) and activated carbon loaded with silver nanoparticles (AgNPs-AC) to remove tetracycline (TC) from synthetically polluted water. The activated carbon was prepared from tea residue and loaded with silver nanoparticles. Scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and Brunauer-Emmett-Teller (BET) were used to characterize the activated carbon (AC) and silver nanoparticles-loaded activated carbon (AgNPs-AC). The impact of various parameters on the adsorption effectiveness of TC was examined. These variables were the initial adsorbate concentration (Co), solution acidity (pH), adsorption time (t), and dosag

In this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. I

This paper presents a study to investigate the behavior of post-tensioned segmental concrete beams that exposed to high-temperature. The experimental program included fabricating and testing twelve simply supported beams that divided into three groups depending on the number of precasting concrete segments. All specimens were prepared with an identical length of 3150 mm and differed in the number of the incorporated segments of the beam (9, 7, or 5 segments). To simulate the genuine fire disasters, nine out of twelve beams were exposed to a high-temperature flame for one hour. Based on the standard fire curve (ASTM – E119), the temperatures of 300◦C (572◦F), 500◦C (932◦F), and 700◦C (1292◦F) were adopted. Consequently,

This paper presents a study to investigate the behavior of post-tensioned segmental concrete beams that exposed to high-temperature. The experimental program included fabricating and testing twelve simply supported beams that divided into three groups depending on the number of precasting concrete segments. All specimens were prepared with an identical length of 3150 mm and differed in the number of the incorporated segments of the beam (9, 7, or 5 segments). To simulate the genuine fire disasters, nine out of twelve beams were exposed to a high-temperature flame for one hour. Based on the standard fire curve (ASTM – E119), the temperatures of 300◦C (572◦F), 500◦C (932◦F), and 700◦C (1292◦F) were adopted. Consequently,

The main objective of this study is to characterize the main factors which may affect the behavior of segmental prestressed concrete beams comprised of multi segments. The 3-D finite element program ABAQUS was utilized. The experimental work was conducted on twelve simply supported segmental prestressed concrete beams divided into three groups depending on the precast segments number. They all had an identical total length of 3150mm, but each had different segment numbers (9, 7, and 5 segments), in other words, different segment lengths. To simulate the genuine fire disasters, nine beams were exposed to high-temperature flame for one hour, the selected temperatures were 300°C (572°F), 500°C (932°F) and 700°C (1292°F) as recomm

This paper presents the effect of relativistic and ponderomotive nonlinearity on cross-focusing of two intense laser beams in a collisionless and unmagnetized plasma. It should be noted here that while considering the self-focusing due to relativistic electron mass variation, the electron ponderomotive density depression in the channel may also be important. Therefore/these two nonlinearties may simultaneously affect the self-focusing process. These nonlinearities depend not only on the intensity of one laser but also on the second laser. Therefore, one laser beam affects the dynamics of the second beam and hence the process of cross-focusing takes place. The electric field amplitude of the excited electron plasma wave (EPW) has been cal