Biometric-based recognition is a method of verification that relies on the biological characteristics of each individual. It is processed based on its additional properties of being identical, portable and difficult to reproduce. The paper presents a palmprint recognition system based on texture features using wavelet transformation, for keeping personnel entry records in large enterprises. Using simple approaches-Discrete Wavelet Transformation (DWT) and Standard Deviation (s)-the study extracts some texture characteristics from the ROI images which are then matched using Canberra, Euclidean and Manhattan distance methods. Among all captured images of datasets, K images per user are used to create the training set, with K ranging from 1 to 4. In image recognition mode, they are compared with the remaining images. The true acceptance rate is used to represent the results.

Several different cloud companies have proposed numerous serverless solutions in response to the demand for Internet access that could be dynamically expanded to any capacity with little maintenance and operating expenses. Serverless computing, also known as Function-as-a-Service (FaaS), is a popular method for developing online applications, data processing, and backend services; nevertheless, it comes with a fee. The computing system provides automated resource provisioning and allocation, unlike Virtual Machines (VMs), allowing for elastic and automatic scalability. The study pertains to Web Application Programming Interface, or Web API, deployed on virtual machines and as FaaS. Despite the benefits of serverless computing, the study found that there is no obvious option between serverless and VMs for a Web API application since prices must be carefully calculated and all components included with FaaS must be included. Furthermore, the paper reviews some of the unique opportunities and potentials that serverless computing presents.

In determining the survival rate of fish eggs, stock evaluation, and monitoring fish population increase, computer usage is replacing the human counting technique. In most cases, counting fish eggs is done in a sequential procedure that requires a lot of time and effort, making it challenging to employ big datasets. Traditional counting methods have been used for many years, but many researchers have pointed out that they have several disadvantages, including requiring more time, exceptional human skills, and excessive human interference. A number of academics are working on developing several strategies to simplify the process of fish counting and assessment. In this paper, we provide a systematic review focusing on several factors which help to automate fish egg counting, using deep learning algorithms and Convolution Neural Network (CNN) from standard databases and research publications. Finally, this paper discusses the most suitable features of fish egg counting, deep learning algorithms, and the future direction of fish egg counting.

Technology innovations supporting Web 4.0 and Web 5.0 influence the quality of student learning and performance in blended and distant learning. Development of web technology extends the capabilities and varieties of e-learning. The Covid-19 pandemic drastically accelerated the changes in education and transformed the mode of teaching and learning. This paper analyzes the changes that have occured in e-learning following the evolution of World Wide Web. It also focuses on Web 3.0, Web 4.0 and the trends in Web 5.0 and Web 6.0 to outline the new features of e-learning. The symbiotic relationship between Artificial Intelligence (AI), Big Data, Linked Data, Cloud Computing, and Data-Driven Science is also focused on. "The Semantic Web" connecting Web's data performs context- based search and research. The Internet of Things lets Web-connected machines of all kinds to communicate with each other and with us, creating a rich flow of data about their location and status. In the near future Web 5.0 and Web 6.0 probably will completely alter our way of communication and acquiring knowledge. The simulating models of virtual and augmented reality with the power of AI will reshape all spheres of our social life, for good or bad.