We—Waheed Ahmad, Andleeb Farooq, Tazeen, Maham Irfan and Nawal Naveed Abbasi— have made an attempt to explain the Retrospective review of microbial ecological processes to understand environmental biotechnology. The fields of environmental biotechnology and microbial ecology are two blossoming fields that have greatly benefited from the advancements in biology, engineering, computing and materials. Although both of the fields are traditionally varied, but the future of both the disciplines are linked to one another. Both the fields, together, provide and promise so much to help society, face and eradicate an environmental problems and challenges, sustainability, human health and security. Moreover, we have also talked about the microbial ecological processes to better understand environmental biotechnology, potential applications of these processes towards our own environment and the future perspective that where this technology is accelerating and heading towards, and what more methods and processes will be witnessed in near future to successfully eradicate and degrade the pollutants and contaminants from the environment through the interaction between microbial communities and their environment for a better, secure and sustainable ecosystem.
Liver plays a vital role in the human body that performs several crucial life functions. A number of liver diseases exist and it is a challenging task to diagnose the liver disease at its early stage. In recent years, several data mining techniques have been used in medical field for prediction but there can be further improvements for quick and accurate diagnose of liver disease. In this paper, a variety of Classifiers have been experimented on Indian liver disease patients dataset which is publicly available on Kaggle. Attribute subset selection is performed to identify significant attributes and the resulting dataset is named as Selected Attributes Dataset (SAD). SAD provides more accuracy in less computation time using Random forest classification algorithm and improved system including these parameters i.e., the efficiency of the system can be increased, early decision making, less time and space required. This research work will provide help to predict liver disease with less amount of data, i.e., number of attributes.
A user’s experience with a software product is crucial for the success of that product. For a long period of time, it was not considered to get an insight of what the users demanded from a product. User research is the best way to discover what the users need. With the increased use of mobile devices, the demand of software products has increased. Building an application is not as simple as hiring someone to code and deploy the application. A process has to be followed and user’s requirements must be understood before we start the design process. The research will help to take additional benefits from the results of user research. It would help to investigate and validate product ideas clearly. As more facts can help to reach a better conclusion, the results from multiple sources like interviews, surveys, user testing etc. Surveys has been conducted for different application i.e. E-commerce application and Facebook application. Proposed user experience (UX) model has been implemented on results and understands that how user experience (UX) research model helps to extract useful information. The recommended model is helpful in patching all the problems that come along during the user research process. The results produced by experiments can be processed through Atomic user experience (UX) model and a useful, shareable and easy to understand outcome can be drawn out of the research.
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