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

Psidium guajava, belonging to the Myrtaceae family, thrives in tropical and subtropical regions worldwide. This important tropical fruit finds widespread cultivation in countries like India, Indonesia, Syria, Pakistan, Bangladesh, and South America. Throughout its various parts, including fruits, leaves, and barks, guava boasts a rich reservoir of bioactive compounds that have been traditionally utilized as folkloric herbal medicines, offering numerous therapeutic applications. Within guava, an extensive array of Various compounds with antioxidative properties and phytochemical constituents are present, including essential oils, polysaccharides, minerals, vitamins, enzymes, triterpenoids, alkaloids, steroids, glycosides, tannins, fl

   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 study aims to identify the level of existential frustration and the level of recrimination among the students of universities, identify the statistical differences between the existential frustration and recrimination based on gender, and finally, identify the correlation between the existential frustration and recrimination. To do this, the researcher adopted the existential frustration scale of ( al-saaedi, 2009) that consisted of (43) item, he also adopted the recrimination scale of ( al-zugeibi,2008) which composed of (31) item. The total sample was (120) male and female student were chosen randomly from four colleges within the university of Baghdad for the academic year ( 2015-2016). The results revealed that the targeted sampl

Take the teacher's key position in the educational system as a foundation stone and primarily responsible for achieving the goals of Education , and efficient teacher conscious is the teacher who prepared educationally and specialized training well add to the enjoyment of a range of features that enable them to adjust and compatibility with educational developments
Hence the problem of the study questioning the Kindergarten Does teacher professional awareness that enable it to perform its work learned from experienceThe research sought to measure
1-Professional awareness among teacher Kindergarten
2-Professional awareness of Kindergarten parameters depending on the type of kindergarten.
Limited search parameters Riyadh govern

This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

Cryptocurrency became an important participant on the financial market as it attracts large investments and interests. With this vibrant setting, the proposed cryptocurrency price prediction tool stands as a pivotal element providing direction to both enthusiasts and investors in a market that presents itself grounded on numerous complexities of digital currency. Employing feature selection enchantment and dynamic trio of ARIMA, LSTM, Linear Regression techniques the tool creates a mosaic for users to analyze data using artificial intelligence towards forecasts in real-time crypto universe. While users navigate the algorithmic labyrinth, they are offered a vast and glittering selection of high-quality cryptocurrencies to select. The