Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file.  In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus,

Entropy generation was studied for new type of heat exchanger (shell and double concentric tubes heat exchanger). Parameters of hot oil flow rate, temperature of inlet hot oil and pressure drop were investigated with the concept of entropy generation. The results showed that the value of entropy generation increased with increasing the flow rate of hot oil and when cold water flow rate was doubled from 20 to 40 l/min, these values were larger. On the other hand, entropy generation increased with increasing the hot oil inlet temperature at a certain flow rate of hot oil. Furthermore, at a certain hot oil inlet temperature, the entropy generation increased with the pressure drop at different hot oil inlet flow rates. Final

The present work covers the Face-Hobbing method for generation and simulation of meshing of Face hobbed hypoid gear drive. In this work the generation process of hobbed hypoid gear has been achieved by determination of the generation function of blade cutter. The teeth surfaces have been drawn depending on the simulation of the cutting process and the head cutter motion. Tooth contact analysis (TCA) of such gear drive is presented to evaluate analytically the transmission error function for concave and convex tooth side due to misalignment errors. TCA results show that the gear is very sensitive to misalignment errors and
the increasing of the gear teeth number decrease the transmission error for both concave and convex tooth sides a

The increased size of grayscale images or upscale plays a central role in various fields such as medicine, satellite imagery, and photography. This paper presents a technique for improving upscaling gray images using a new mixing wavelet generation by tensor product. The proposed technique employs a multi-resolution analysis provided by a new mixing wavelet transform algorithm to decompose the input image into different frequency components. After processing, the low-resolution input image is effectively transformed into a higher-resolution representation by adding a zeroes matrix. Discrete wavelets transform (Daubechies wavelet Haar) as a 2D matrix is used but is mixed using tensor product with another wavelet matrix’s size. MATLAB R2021

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

In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi

The process of composting which involves the treatment of organic wastes to obtain a stable clean product, has become an increasingly desirable choice, at any scale from home to large waste treatment plants. Composting serves as an alternative to landfilling for managing biodegradable waste while also increasing or preserving soil organic matter, decreasing solid waste, and reducing disposal costs. The compost product improves the condition of the soil, reduces erosion, and helps reduce plant diseases without having adverse impacts on the environment. This study aims to manufacture high-quality compost as a solid waste management method by converting organic waste into a useful resource for the community in a financially and ecologi

Solid waste is a major issue in today's world. Which can be a contributing factor to pollution and the spread of vector-borne diseases. Because of its complicated nonlinear processes, this problem is difficult to model and optimize using traditional methods. In this study, a mathematical model was developed to optimize the cost of solid waste recycling and management. In the optimization phase, the salp swarm algorithm (SSA) is utilized to determine the level of discarded solid waste and reclaimed solid waste. An optimization technique SSA is a new method of finding the ideal solution for a mathematical relationship based on leaders and followers. It takes a lot of random solutions, as well as their outward or inward fluctuations, t

The bubbled slab, a type of reinforced concrete (RC) slab with plastic voids, is an innovative design that employs a biaxial distribution of voiding formers within the slab to reduce the slab’s self-weight while preserving a load-carrying capacity that is approximately comparable to that of solid slabs. This paper presents a new approach for figuring out the effective critical shear perimeter of voided slabs using the reduced-volume concept of concrete. This approach aims to reduce the coefficient of variation of the current design standards, namely the ACI 318-19 and Eurocode 2, for assessing the slabs’ resistance to punching shear. Our experimental program investigated the impact of voiding former patterns and the location of