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.

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.

The spread of ICT in education and learning has changed the way of teaching and learning, and

this raised the issue of getting e-learning systems to adapt/personalize with respect to student's

knowledge achievement. However, the relation between the concepts in the programming domain

are not definitive and they are fuzzily related. In this Paper, we describe a practical experience for

developing adaptable e-learning system using fuzzy logic to model and evaluate student's

knowledge for the purpose of adaptation in the field of Computer Programming. Fuzzy logic

technique modeled as a plugin on MOODLE Learning Management System at the Libyan

Academy for Postgraduate Studies is developed. Conclusions highlighted some important lessons

in increasing learning effectiveness and learner's satisfaction.

For Arabic letters recognition, we achieve three of pattern recognition approaches namely gray level co-occurrence matrix (GLCM), local binary pattern recognition (LBP) and artificial neural network (ANN) and compare between them to result best performance. Two of these methods level co-occurrence matrix and local binary pattern recognition are used for feature extraction whereas in artificial neural network (ANN) we use the intensity values of pixels for input of the neural network. Two classifiers are used, the K-Nearest Neighbor classifier (KNN) for the LBP, GLCM and neural network classifier for (ANN) artificial neural network. Also, we evaluate the results by using leave one person out approach, fold classification and leave one out.

This paper aims to demonstrate the application of two different control techniques, namely the Linear Quadratic Regulator (LQR) and a neural network-based controller to evaluate and control the vibrations that occurred in the car's suspension system. When the car suspension is designed, a quarter car model with 1-DOF is used. A complete control system is needed to provide the desired suspension performance and characteristics such as passenger comfort, road handling, and suspension deflection, this control system performed by using the Matlab software and includes three parts: input signals (actuator force and road profile), Controller, and the suspension system model. The simulation results show a comparison between the uncontrolled suspension system and the suspension system with a neural network-based controller and the active suspension system of the car based on the linear-quadratic regulator, and it is explained thoroughly.

Vehicle safety and control is attracting attention increasingly in an attempt to improve the stability and manoeuvrability of vehicles. Three degrees of freedom vehicle dynamic model (called planar vehicle model) is established. Based on theories of fuzzy PID control and neural network based-Controller, controller of vehicle stability is designed by using the method of direct yaw rate control and the two different control strategies. The controllers were compared under one road condition which is a lane change of manoeuvre. By comparing and analyzing the control effect of fuzzy PID control and neural network based-Controller, the result shows as follows: the two controllers improved the yaw rate to follow the reference yaw rate but, using the fuzzy PID controller gave a better and closer path for the desired path of yaw rate compared to using of the neural network controller.