Machine learning algorithms are being used extensively in biomedical fields for segmentation and analysis. These algorithms use features derived from images as input to make a conclusion. So, choosing proper feature extraction methods pooled with suitable Machine Learning (ML) algorithms is very important to accomplish good classification accuracy. During the literature survey, we found that there is a deficiency of information about machine learning algorithms for skin disease classification. Image Processing and machine learning based examinations are being utilized in a few territories; for example, face recognition, unique finger impression recognition, tumor identification and segmentation. Generally used ML algorithms are Linear Differential Analysis (LDA), Support Vector Machine (SVM), Artificial Neural Networks (ANN), Nave Bias Classier, K-Nearest Neighbor (KNN) and Deep Learning Algorithm. The choice of information include is crucial in any classification task, utilizing ML calculations.

The Corona Virus Disease of 2019 (COVID-19) has brought global pandemic along with it. It has affected almost every sector of humankind. To be more specific, on education sector, due to Covid-19 pandemic educational institutions got completely shut down and students returned back to their home. The temporarily closures of educational institutions throughout the world due to outbreak of COVID-19 have impact on only on learners, teachers or parents but have far reaching economical and societal up-shots too. In this difficult time of Covid-19, online learning is a buzzing words during pandemic situation among the students and teachers and is an alternative to ordinary face to traditional class-room and it will continue play a key role in educator sector. The aim of the paper is to study about the various impacts of COVID-19 on Indian Education System and to analyse the various advantages and disadvantages of online education.

Promising new data management technologies like Blockchain, the Internet of Things (IoT), and Machine Learning (ML) offer significant benefits for Knowledge Management (KM) and Human Resource Management (HRM) procedures. This paper discusses how these technologies, when integrated, address issues such as data security, trust, and effective knowledge exchange. IoT enables scalable and reliable networks for real-time data management, while blockchain offers a secure foundation for information exchange through its decentralized, transparent, and trustless nature. ML enhances decision-making by analyzing data and using predictive models, optimizing HR strategies. By leveraging these technologies, companies can gain an advantage in the ever-evolving digital economy, in alignment with Industry 4.0 standards. The report also highlights future research opportunities that could transform organizational learning, sustainability, and decision-making through KM solutions based on Blockchain and IoT.