Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

The laser micro-cutting process is the most widely commonly applied machining process which can be applied to practically all metallic and non-metallic materials. While this had challenges in cutting quality criteria such as geometrical precision, surface quality and numerous others. This article investigates the laser micro-cutting of PEEK composite material using nano-fiber laser, due to their significant importunity and efficiency of laser in various manufacturing processes. Design of experiential tool based on Response Surface Methodology (RSM)-Central Composite Design (CCD) used to generate the statistical model. This method was employed to analysis the influence of parameters including laser speed,

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

Knowledge of the mineralogical composition of a petroleum reservoir's formation is crucial for the petrophysical evaluation of the reservoir. The Mishrif formation, which is prevalent in the Middle East, is renowned for its mineralogical complexity. Multi-mineral inversion, which combines multiple logs and inversions for multiple minerals at once, can make it easier to figure out what minerals are in the Mishrif Formation. This method could help identify minerals better and give more information about the minerals that make up the formation. In this study, an error model is used to find a link between the measurements of the tools and the petrophysical parameters. An error minimization procedure is subsequently applied to determine

To achieve safe security to transfer data from the sender to receiver, cryptography is one way that is used for such purposes. However, to increase the level of data security, DNA as a new term was introduced to cryptography. The DNA can be easily used to store and transfer the data, and it becomes an effective procedure for such aims and used to implement the computation. A new cryptography system is proposed, consisting of two phases: the encryption phase and the decryption phase. The encryption phase includes six steps, starting by converting plaintext to their equivalent ASCII values and converting them to binary values. After that, the binary values are converted to DNA characters and then converted to their equivalent complementary DN

<p>In this paper, a simple color image compression system has been proposed using image signal decomposition. Where, the RGB image color band is converted to the less correlated YUV color model and the pixel value (magnitude) in each band is decomposed into 2-values; most and least significant. According to the importance of the most significant value (MSV) that influenced by any simply modification happened, an adaptive lossless image compression system is proposed using bit plane (BP) slicing, delta pulse code modulation (Delta PCM), adaptive quadtree (QT) partitioning followed by an adaptive shift encoder. On the other hand, a lossy compression system is introduced to handle the least significant value (LSV), it is based on

Chaotic systems have been proved to be useful and effective for cryptography. Through this work, a new Feistel cipher depend upon chaos systems and Feistel network structure with dynamic secret key size according to the message size have been proposed. Compared with the classical traditional ciphers like Feistel-based structure ciphers, Data Encryption Standards (DES), is the common example of Feistel-based ciphers, the process of confusion and diffusion, will contains the dynamical permutation choice boxes, dynamical substitution choice boxes, which will be generated once and hence, considered static,

            While using chaotic maps, in the suggested system, called

Biometrics is widely used with security systems nowadays; each biometric modality can be useful and has distinctive properties that provide uniqueness and ambiguity for security systems especially in communication and network technologies. This paper is about using biometric features of fingerprint, which is called (minutiae) to cipher a text message and ensure safe arrival of data at receiver end. The classical cryptosystems (Caesar, Vigenère, etc.) became obsolete methods for encryption because of the high-performance machines which focusing on repetition of the key in their attacks to break the cipher. Several Researchers of cryptography give efforts to modify and develop Vigenère cipher by enhancing its weaknesses.

This paper presents the design of a longitudinal controller for an autonomous unmanned aerial vehicle (UAV). This paper proposed the dual loop (inner-outer loop) control based on the intelligent algorithm. The inner feedback loop controller is a Linear Quadratic Regulator (LQR) to provide robust (adaptive) stability. In contrast, the outer loop controller is based on Fuzzy-PID (Proportional, Integral, and Derivative) algorithm to provide reference signal tracking. The proposed dual controller is to control the position (altitude) and velocity (airspeed) of an aircraft. An adaptive Unscented Kalman Filter (AUKF) is employed to track the reference signal and is decreased the Gaussian noise. The mathematical model of aircraft