In this paper, the data filtering based recursive least squares algorithm for a CARAR systems, and data filtering based recursive least squares algorithm for a CARARMA systems are derived for comparison. These algorithms are based on the decomposition technique and in this technique, the main algorithm transform into two sub algorithms with smaller sizes. First, System identification model and another is the noise identification model. The problem here is the unknown variables in the information vectors and the used idea for solving this problem is to replacing these unknown variables with their corresponding estimates. Thus, the parameters of these two identification models can be estimated using recursive least squares method. Finally, a simulation example is provided to support the comparison between these proposed algorithms. KEYWORDS: identification algorithm; parameter estimation; filtering technique; decomposition technique; information vector.

The emergence of China as a global superpower has presented numerous challenges, among which is the growing threat posed by Chinese cyber warfare units. Operating under the People's Liberation Army (PLA), these units have been implicated in various high-profile cyber-attacks targeting both civilian and military entities worldwide. This paper endeavors to offer a comprehensive analysis of the risks presented by Chinese cyber warfare units, encompassing their organizational structure, tactics, and capabilities. By elucidating the nature and extent of this menace, we hope to enable governments and organizations to implement measures for better protection against Chinese cyber-attacks, as 80% of them target government bodies. In this study, we utilize the MITRE ATT&CK framework as a foundation to deliver an accessible, informative overview.

A vehicle is a means of transportation, such as a car, truck, or train, that is capable of moving people or goods from one place to another. Vehicles can be classified based on various factors, such as the type of fuel they use (e.g. gasoline, diesel, electricity), the number of wheels they have (e.g. two, four, six), and their intended use (e.g. passenger transportation). Vehicles may have connectors, such as plug sockets or fuel ports, that allow them to be connected to other devices or systems to form Vehicle-to-Everything (V2X) technology. For example, an Electric Vehicle (EV) may have a charging port that allows it to be connected to an electric power source to recharge its batteries such Vehicle-to-Grid (V2G) as one of the V2X forms. One of the challenges in charging EVs is the availability of charging infrastructure. In many places, there are relatively few public charging stations, which can make it difficult for EV owners to find a place to charge their vehicles when they are away from home. Additionally, charging an electric vehicle can take significantly longer time than filling up a gasoline-powered vehicle, which can be inconvenient for some drivers. In this review, the various topologies of V2X, connectors, charging challenges, and EV impact types on the grid are conducted.

Electric Vehicles (EVs) as hotspot research are increasingly being used as alternative energy sources outside of transportation due to global variables like energy usage and environmental concerns. Gridable Electric Vehicle (GEV) is exploiting the opportunity for connecting EVs to the grid. EVs are now capable of contributing to addressing power limitations and acting as a reserve source of energy for the distribution grid in the Electric Vehicle Charging Facility (EVCF) to form Vehicle-to-Home (V2H). This paper is introduced to estimate impacts on the load for the uncertain behavior of EVs under domestic load after being sized using algorithms. Although, the integration of EVs provides an economical and environmental solution with a positive impact, however, it affects the power system when the uncertain number of EVs is provided as heavy duty. Sensitivity analysis has been considered in the study to investigate the expected changes in the system from the affected components.

The application of feature selection to fault diagnosis is presented. First, Filtered data identification algorithm is derived for controlled autoregressive autoregressive (CARAR) system in order to estimate the system parameters. The Proposed technique offers a high computational efficiency. These estimated parameters are referred as features and these features are not all have the same informative value. Next, features selection is carried out using principal components analysis. Finally, the simulation results demonstrate the value of the suggested procedures.

This work intends to improve the educational process through the development of teachers skills and raise the level of learning by reducing the problems and obstacles facing the teacher and providing many different learning methods. This is done through expert systems, which is one of the important fields of knowledge-based artificial intelligence, where the expert system acquires all the information acquired by the expert in the field of mathematics by transferring all his scientific experience and how the mathematics expert deals with it, so that the knowledge acquired by experts in the field of mathematics is collected. In order to prepare a knowledge base and deal with it through the expert system, as well as the possibility of making the expert system that the teacher deals with, ready to answer any inquiries or the possibility of explaining any part of the curriculum on demand.

this paper presents feature selection for fault diagnosis based on recursive generalized extended least squares algorithm (RGELS). RGELS model is derived and validation of this model is tested utilizing good statistical methods, which, namely best-fit criterion. The system parameters are estimated employing the proposed algorithm. Dimension reduction of the system parameters is done to get best important features using linear discriminant analysis. Finally, the simulation results confirm the effectiveness of the algorithm.

Class E power amplifier circuit consists mainly of a transistor operates as a switch, load network and series LC filter tuned to fundamental frequency. There is different configurations to realize class E power amplifier circuit according to the load network such as: shunt capacitance configuration, shunt inductance configuration and parallel circuit configuration. In this paper the performance parameters (such as: PAE, overall efficiency, drain efficiency, gain, drain voltage and current waveforms) of class E power amplifier with shunt capacitance configuration at frequencies [0.25, 0.5, 0.75 and 1 GHz] are observed

This paper presents a synthesizing design of a linear antenna array by adapting the Schelkunoff method. The idea behind this type of design is to produce nulls in radiation pattern of a structure without any notable effects on the main lobe. This design has been undertaken around 9 GHz, where both theoretical and simulation results are achieved and will be the target of this work. X-band searching radar system is considered where sing