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

      As a new technology, blockchain provides the necessary capabilities to assure data integrity and data security through encryption. Mostly, all existing algorithms that provide security rely on the process of discovering a suitable key. Hence, key generation is considered the core of powerful encryption. This paper uses Zernike moment and Mersenne prime numbers to generate strong prime numbers by extracting the features from biometrics (speech). This proposed system sends these unique and strong prime numbers to the RSA algorithm to generate the keys. These keys represent a public address and a private key in a cryptocurrency wallet that is used to encrypt transactions. The benefit of this work is that it provides a high degree

Robots have become an essential part of modern industries in welding departments to increase the accuracy and rate of production. The intelligent detection of welding line edges to start the weld in a proper position is very important. This work introduces a new approach using image processing to detect welding lines by tracking the edges of plates according to the required speed by three degrees of a freedom robotic arm. The two different algorithms achieved in the developed approach are the edge detection and top-hat transformation. An adaptive neuro-fuzzy inference system ANFIS was used to choose the best forward and inverse kinematics of the robot. MIG welding at the end-effector was applied as a tool in this system, and the wel

<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

The use of online social network (OSN) has become essential to humans' lives whether for entertainment, business or shopping. This increasing use of OSN motivates designing and implementing special systems that use OSN users' data to provide better user experience using machine learning and data mining algorithms and techniques. One system that is used extensively for this purpose is friend recommendation system (FRS) in which it recommends users to other users in professional or entertaining online social networks.

For this purpose, this study proposes a novel friend recommendation system, namely Hybrid Friend Recommendation (FR) model. The Hybrid model applies dual-stage methodology on unlabeled data of 1241 users collected fro

The Internet of Things (IoT) is an information network that connects gadgets and sensors to allow new autonomous tasks. The Industrial Internet of Things (IIoT) refers to the integration of IoT with industrial applications. Some vital infrastructures, such as water delivery networks, use IIoT. The scattered topology of IIoT and resource limits of edge computing provide new difficulties to traditional data storage, transport, and security protection with the rapid expansion of the IIoT. In this paper, a recovery mechanism to recover the edge network failure is proposed by considering repair cost and computational demands. The NP-hard problem was divided into interdependent major and minor problems that could be solved in polynomial t

       In recent years, encryption technology has been developed rapidly and many image encryption methods have been put forward. The chaos-based image encryption technique is a modern encryption system for images. To encrypt images, it uses random sequence chaos, which is an efficient way to solve the intractable problem of simple and highly protected image encryption. There are, however, some shortcomings in the technique of chaos-based image encryption, such limited accuracy issue. The approach focused on the chaotic system in this paper is to construct a dynamic IP permutation and S-Box substitution by following steps. First of all, use of a new IP table for more diffusion of al

       In this work, a pollution-sensitive Photonic Crystal Fiber (PCF) based on Surface Plasmon Resonance (SPR) technology is designed and implemented for sensing refractive indices and concentrations of polluted  water . The overall construction of the sensor is achieved by splicing short lengths of PCF (ESM-12) solid core on one side with traditional multimode fiber (MMF) and depositing a gold nanofilm of 50nm thickness on the end of the PCF sensor. The PCF- SPR experiment was carried out with various samples of polluted water including(distilled water, draining water, dirty pond water, chemical water, salty  water and oiled water). The location of the resonant wavelength peaks is seen to move to longer wavelengths (red shift)

   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