The concept of federated learning (FL) is becoming increasingly popular as a method for training collaborative models without loss the sensitive information. The term has become ubiquitous due to the extensive development of autonomous vehicles. Vehicular Networks and the Internet of Vehicles (IoV) enable cooperative learning through federated learning. It is still necessary to address several technical challenges. In recent years, Federated Learning (FL) has attracted significant interest in various sectors, including smart cities and transportation systems. FL-enabled attack detection for IoVs are still in its infancy. However, to determine the main challenges of deployment in real-world scenarios, there needs to be research efforts from various areas. Performance metrics are used to evaluate the effectiveness of the proposed FL framework. According to experiments, the proposed FL approach detected attacks in IOV networks with a maximum accuracy of 99.72%. In addition to precision, recall, and F1 scores, 99.70%, 99.20%, and 99.26% were achieved. A comparison of the proposed model with the existing model shows that the proposed model is more accurate.

Artificial Intelligence (AI) is revolutionizing the field of education by offering new possibilities for personalized and experiential learning along with data-driven insights. The advancement in AI to Generative Artificial Intelligence (GAI) has made the tables turn notably in the field of education. Generative AI application tool ChatGPT is emerging as a game changer offering personalized learning experiences by analyzing huge amounts of student data, generating study materials and pacing to individual needs. Intelligent educational tools powered by AI provide personalized guidance and feedback, adapting to curriculum to address knowledge gaps. GAI also automates the grading process, providing instant feedback and relieving teachers for qualitative assessments. This research paper offers a thorough examination of the potential uses, advantages, difficulties, and moral issues related to implementing ChatGPT in educational contexts. The authors closely analyze how ChatGPT can improve educational experiences, assist personalized learning, and encourage student- teacher interaction, while exploring the drawbacks of using generative AI models in education, such as concerns about bias, data privacy, and over-reliance on technology. This research article intends to offer educators & academicians useful insights into the usage of ChatGPT in the educational field through a critical analysis of the existing literature and real- world experiences.

Modeling of Buck Converter Models in MPPT using PID and FLC

With an increase of Green Technology applications, Photovoltaic have emerged as the most appropriate solution for electricity generation purposes. However, due to variable temperature and irradiance, under the partial or shaded conditions Maximum Power Point Tracking is needed to determine highest efficiency of the system. The paper describes dynamic modeling and control of variable temperature and irradiance on solar panel in SIMULINK-MATLAB environment. The implementation of Buck Converter is used for power switching and impedance matching on connecting the panel to the load. The effectiveness of the model, with enhanced efficiency through voltage stabilization, is performed using Proportional-Integral-Derivative and Fuzzy-Logic-Controllers. A comparative study is made for PID and FLC on the basis of outputs to deal with online set point variations. FLC gives closer results to Standard Test Conditions when compared with PID. The Fuzzy system developed, using tested membership functions serve as a platform for sustainable standalone and grid-based applications using distributed MPPT. With an increase of Green Technology applications, Photovoltaic have emerged as the most appropriate solution for electricity generation purposes. However, due to variable temperature and irradiance, under the partial or shaded conditions Maximum Power Point Tracking is needed to determine highest efficiency of the system. The paper describes dynamic modeling and control of variable temperature and irradiance on solar panel in SIMULINK-MATLAB environment. The implementation of Buck Converter is used for power switching and impedance matching on connecting the panel to the load. The effectiveness of the model, with enhanced efficiency through voltage stabilization, is performed using Proportional-Integral-Derivative and Fuzzy-Logic-Controllers. A comparative study is made for PID and FLC on the basis of outputs to deal with online set point variations. FLC gives closer results to Standard Test Conditions when compared with PID. The Fuzzy system developed, using tested membership functions serve as a platform for sustainable standalone and grid-based applications using distributed MPPT.