In this paper we present a cardiovascular diseases prediction which is referred to as heart diseases. A detail review and application of genetic algorithms in healthcare systems including machine learning algorithms were evaluated. The cardiovascular disease involves narrowed or blocked blood vessels that can lead to a heart attack, angina or stroke, and other heart failures such as muscle, valves or rhythm, which is one of the largest causes of morbidity and mortality among the world population. According to our analysis and results obtained between 85-89 percent of ages greater than 40 years were seriously affected by cardiovascular diseases which provides an imperative result in regards to the previous Ebola outbreak in West Africa in 2014-2016 and the current COVID-19 pandemic of which the aging population were more affected. Our results also indicate, the higher the generation the better prediction and performance and more complex the algorithm. However, with GA and ML approaches are useful to predict the output from the existing data and to match-up the probability computation against the cardiovascular diseases’ dataset.

The advancement of emerging technological tools in software engineering is an important element in the design and development of software systems. In this paper, we present an analysis of theory and practice including methodology of software products for both large and complex requirements and development analysis, and synthesis. The paper is presented in two folds: Part-I describes a security-specific knowledge of modelling approach for securing software engineering and typical projects implemented in data centre infrastructure. In relation to software engineering practice and theory, we analysed the key parameters indicators of software development projects and the elements of a system that encapsulate the customer, developer, and the researcher as stakeholders in a software development project, whereas the elements of a system entail computer, data validation, mailroom, and computation with paychecks and pay-information. The modelling process and life cycle model includes some major processes in software development such as users’ resources, production of the final product, subprocesses with hierarchy links, process activity, guiding principles, and outcomes of a software requirement specification. In Part-II, an overview of data centre infrastructure and with some schematic illustration for each phase of the construction and implementation of a data centre. The project involves a system and process that creates it with prepare, design, acquire, and implement as a process model whereas actors create the project model. In the context of data centre life cycle model, prepare and design form the construct or build phase, and maintainability and optimization form the engineering phase. All these formulates the project model as the building blocks of data centre. The business need for the construction of the data centre (prepare, design, acquire, and implement) are the knowledge-based of the process model phases to produce an overall system we called the four phases of data centre project process.