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.

It has been noted the wide spread of the use of composite materials due to their specific strength that made them the best alternative to many other materials, However, the high cost of synthetic fibers represents an obstacle to the use of composite materials in most applications. Therefore, research has tended to test natural fibers, which are the ideal solution for using composite materials in many industries such as furniture, flooring, decoration, and others. This paper concerned with the study of natural composite materials made of Libyan almond shells. Three different sizes of ground almond shells were studied: large size in the form of grains, medium size, and the small size (powder form). These crushed peels were mixed with the resinous polyester resin in four proportions: ratio of 80:20, 60:40, 40:60, and 20:80. Three basic tests were conducted to investigate the mechanical properties of the samples: impact test, tensile test, and flexural test. The results showed that samples made of almond peels in a powder form exhibits the best results among all other kind of specimens for three mentioned tests of mechanical properties.

Abstract

Depending on the type of configuration and connector arrangement, beam-to-column end-plate joints can be rigid, semi-rigid, or pinned. Fully restrained joints are required for rigid frames in which it is anticipated that the frame joints will have adequate rigidity to maintain the angles between intersecting parts in the service condition, ensuring full moment transfer. In contrast, partially restrained joints in semi-continuous frames are distinguished by relative rotations between crossing members, allowing the bending force to be transferred only partially. The concept of utilizing partially restricted, unstiffened joints in construction has gained traction since it looks to be more feasible and inexpensive. Bending transfer in partially constrained joints allows semi-continuous frames to withstand actions. Semi-continuous frames can survive actions due to bending transfer in partially restricted joints. At the same time, a certain degree of rotation is permitted, which improves the overall ductility of these structures. Using thinner end plates than those used in practical applications is one of the most effective ways to affect the ductility of end-plate beam-to-column joints. It was confirmed in a previous experimental study that the composite joints, where the thickness of the end plates is equivalent to about 60% of the diameter of the bolt used in composite joints, were taken into account in subsequent tests, and these studies can be confirmed using ABAQUS and Ls-Dyna modelling. All of these concerns are addressed, and recommendations for numerical modelling methodologies are made in order to ultimately analyse the reaction of the symmetric extended end plate joints with 8-bolts under hogging and sagging bending moments.

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.

In many missions of rotating machines such as compressors, engines, turbines and large centrifugal pumps use Journal bearings to support and guide rotating shafts due to the high load capacity of this type of bearing. The effect of operating conditions on heavy duty in the journal bearings will degrade machine performance, reduce life time and increase risk. The application of high-frequency Acoustic Emissions AE signals is used to carry information about the details of the micro-collision process. Furthermore, the AE for journal bearing diagnosis is gaining acceptance as a useful complementary tool for the condition monitoring. The experimental investigation has been conducted to demonstrate the effect AE characteristics of the journal bearing in different critical operating conditions. The parameters rotational speed and radial load as well as different lubricant viscosity are mainly measured. For the overcoming occurrence of the bearing failures a comprehensive monitoring method has developed between friction in asperity contact and energy release of AE signals for journal bearing. A mathematical model is applied in order to obtain an insightful understanding of the influences operating parameters on the energy of AE generated in rolling element bearing. The obtained results showed that the potential of AE technology and data analysis method applied for monitoring the asperities contact condition in journal bearings, which will be vital for developing a comprehensive monitoring system, supporting the optimal design by simulating the Stribeck curve and operation of journal bearings. 

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.