Making Infection Prevention & Control Smarter and User-friendly

The editorial provides information about an infection prevention and control mobile application and a corresponding website that has been developed by members of infection control committee of a tertiary care hospital. The features of the mobile app are discussed along with information shared in the form of guidelines that cover various aspects of infection control practices relevant for healthcare workers. The app can be used in different clinical settings in hospital areas by anyone who has an android or Apple phone. 

Towards an Autonomous Self-Organizing Architecture for Green Computing in Networks

The last century can be identified with the transformation of mankind due to the large-scale adoption of technology. Significant changes have taken place in the planet due to continual outcomes from research. These technological advances have resulted in considerable changes in the overall quality as well as expectancy of human life. While technology has generally resulted in positive effects on the human civilization, such unplanned changes can also have numerous associated unexpected and emergent outcomes. Living in a linked world implies proliferation and diffusion of changes at the global level. While there are numerous aspects to the technological revolution, some of the key changes in urban environments can be attributed to the era of small and numerous connected computing devices. This has resulted in the texture of the ?Internet of Things? (IoT) ensuing more computing devices than the entire human population. Some of the resultant unexpected effects can perhaps be classified in three key areas; firstly in the form of greenhouse gas emissions, secondly, in the form of effects due to additional heat produced by computers and thirdly, residual effects of technological waste. Although there are solutions available which require human intervention and planning, the large-scale texture of connected devices forming this IoT offers opportunities to apply autonomic and self-organizing/nature-inspired techniques. The primary goal of this research is to examine how self-organizing techniques may be used to solve problems in setting up greener networks by solving problems from the above-mentioned domains. Specifically, algorithms and solutions to two common problems faced in computer networks are presented which can be helpful in developing greener networks. First, the solution for planning and correlation of up-time of computers in networks is presented. This is followed by a proposed self-organizing algorithm for hotspot reduction in large-scale data centers. This in turn minimizes the use of electricity as well as reduces the risks of electric failures due to overheating. To critically evaluate the proposed techniques, extensive simulation experiments using different modeling and simulation techniques such as Monte Carlo (?R? statistical tool) and Agent-based simulations (using NetLogo) have been performed. The first set of simulation experiments clearly demonstrates how the proposed Monte Carlo methods allow for an efficient allocation of carbon footprint in large-scale networks without requiring extensive communication. Furthermore, simulation experiments using agent-based models were used to evaluate the reduction of hot-spots by the use of proposed cellular automata algorithms. Results from extensive simulation experiments demonstrate the utility and effectiveness of utilizing autonomous self-organizing mechanisms as first steps towards making environment friendly large scale computer networks and clusters.