Abstract

 Metal cutting processes still represent the largest class of manufacturing operations. Turning is the most commonly employed material removal process. This research focuses on analysis of the thermal field of the oblique machining process. Finite element method (FEM) software DEFORM 3D V10.2 was used together with experimental work carried out using infrared image equipment, which include both hardware and software simulations. The thermal experiments are conducted with AA6063-T6, using different tool obliquity, cutting speeds and feed rates. The results show that the temperature relatively decreased when tool obliquity increases at different cutting speeds and feed rates, also it

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Compression of speech signal is an essential field in signal processing. Speech compression is very important in today’s world, due to the limited bandwidth transmission and storage capacity. This paper explores a Contourlet transformation based methodology for the compression of the speech signal. In this methodology, the speech signal is analysed using Contourlet transformation coefficients with statistic methods as threshold values, such as Interquartile Filter (IQR), Average Absolute Deviation (AAD), Median Absolute Deviation (MAD) and standard deviation (STD), followed by the application of (Run length encoding) They are exploited for recording speech in different times (5, 30, and 120 seconds). A comparative study of performance

This paper is attempt to study the nonlinear second order delay multi-value problems. We want to say that the properties of such kind of problems are the same as the properties of those with out delay just more technically involved. Our results discuss several known properties, introduce some notations and definitions. We also give an approximate solution to the coined problems using the Galerkin's method.

In this paper, a new high-performance lossy compression technique based on DCT is proposed. The image is partitioned into blocks of a size of NxN (where N is multiple of 2), each block is categorized whether it is high frequency (uncorrelated block) or low frequency (correlated block) according to its spatial details, this done by calculating the energy of block by taking the absolute sum of differential pulse code modulation (DPCM) differences between pixels to determine the level of correlation by using a specified threshold value. The image blocks will be scanned and converted into 1D vectors using horizontal scan order. Then, 1D-DCT is applied for each vector to produce transform coefficients. The transformed coefficients will be qua

In this paper, we characterize normal composition operators induced by holomorphic self-map , when and .Moreover, we study other related classes of operators, and then we generalize these results to polynomials of degree n.

Images hold important information, especially in military and commercial surveillance as well as in industrial inspection and communication. Therefore, the protection of the image from abuse, unauthorized access, and damage became a significant demand. This paper introduces a new Beta chaotic map for encrypting and confusing the color image with Deoxyribonucleic Acid (DNA) sequence. First, the DNA addition operation is used for diffusing each component of the plain image. Then, a new Beta chaotic map is used for shuffling the DNA color image. In addition, two chaotic maps, namely the proposed new Beta and Sine chaotic maps, are used for key generation. Finally, the DNA XOR operation is applied between the generated key and shuffled DNA i

Current numerical research was devoted to investigating the effect of castellated steel beams without and with strengthening. The composite concrete asymmetrical double hot rolled steel channels bolted back to back to obtain a built-up I-shape form are used in this study. The top half part of the steel is smaller than the bottom half part, and the two parts were connected by bolting and welding. The ABAQUS/2019 program employed the same length and conditions of loading for four models: The first model is the reference without castellated and strengthening; the second model was castellated without strengthened; the third model was castellated and strengthened with reactive powder concrete encased in the

Micro-perforated panel (MPP) absorber is increasingly gaining popularity as an alternative sound absorber in buildings compared to the well-known synthetic porous materials. A single MPP has a typical feature of a Helmholtz resonator with a high amplitude of absorption but a narrow absorption frequency bandwidth. To improve the bandwidth, a single MPP can be cascaded with another single MPP to form a double-layer MPP. This paper proposes the introduction of inhomogeneous perforation in the double-layer MPP system (DL-iMPP) to enhance the absorption bandwidth of a double-layer MPP. Mathematical models are proposed using the equivalent electrical circuit model and are validated with experiments with good agreement. It is revealed that the DL-