RESUMEN
Conjunctivitis is one of the common and contagious ocular diseases which affects the conjunctiva of the human eye. Both the bacterial and viral types of it can be treated with eye drops and other medicines. It is important to diagnose the disease at its early stage to realise the connection between it and other diseases, especially COVID-19. Mobile applications like iConDet is such a solution that performs well for the initial screening of Conjunctivitis. In this work, we present with iConDet2 which provides an advanced solution than the earlier version of it. It is faster with a higher accuracy level (95%) than the previously released iConDet. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
RESUMEN
Increasing the productivity of flexible working during working hours is a common concern for employers. Employees working in different sectors use various tools to carry out their tasks and work in different working environments. With the Covid-19 pandemic that began in the beginning of 2020, remote working has become an essential part of life. However, one of the biggest problems faced by managers and employers is how to control remote workers. In this study, SmartRadar software was developed to track employee computer use behavior and detect anomalous behavior. Anomalous behavior is defined as computer-based activities or processes carried out during work time which are not related to the tasks for which the employee is responsible. Clicking, mouse wheel scrolling, copying and other similar actions by the user are processed, a summary of the data is generated, and a multi-dimensional dataset is created. Anomalous behavior can then be detected using support vector machines. The proposed software has been shown to detect anomalous computer use behavior by employees with a high degree of accuracy. The favorable results of the study show that the proposed method and the software could be used for tracking and reporting purposes both in workplaces and in flexible working conditions. © 2021 Elsevier B.V.