The future of alternative energy storage for vehicles is
bright because the use of hydrogen in the economy provides
various solutions to environmental situations. Hydrogen is
as flexible as electricity in that it can be produced in both
renewable and non-renewable sources of energy. However,
the literature written focuses on the conditions that are
needed to be accounted for when it comes to switching to
hydrogen as an alternative energy storage using statistical
analysis. By taking an economic and environmental investigation, hydrogen has the best air pollution emissions in
comparison to conventional, hybrid and electric vehicles. It
is also found that hydrogen fuel cell vehicles are simpler in
design which accounts for its weight that is much lighter
than most vehicles. Ergo, hydrogen is the preferred fuel for
fuel cell vehicles because of efficiency that can increase the
potential for a sustainable climate.
Sleeper's Attendance is a paper describing a method to be used on a University's attendance system that can essentially bypass it and allow the attacker to register for all their classes. The paper also briefly describes about QR attendance systems in general and some ways to improve it.
This is a review of journals in the area
of using Artificial Intelligence for Intrusion Detection
and Prevention Systems. The journals have discussed the
milestones that have been achieved in the area of network
security particularly intrusion detection. They has also
highlighted several Machine Learning algorithms that
can be applied in this area to improve the IDS systems.
Super-resolution microscopy has become essential for the study of nanoscale biological processes. This type of imaging often requires the use of specialised image analysis tools to process a large volume of recorded data and extract quantitative information. In recent years, our team has built an open-source image analysis framework for super-resolution microscopy designed to combine high performance and ease of use. We named it NanoJ - a reference to the popular ImageJ software it was developed for. In this paper, we highlight the current capabilities of NanoJ for several essential processing steps: spatio-temporal alignment of raw data (NanoJ-Core), super-resolution image reconstruction (NanoJ-SRRF), image quality assessment (NanoJ-SQUIRREL), structural modelling (NanoJ-VirusMapper) and control of the sample environment (NanoJ-Fluidics). We expect to expand NanoJ in the future through the development of new tools designed to improve quantitative data analysis and measure the reliability of fluorescent microscopy studies.
Romain F. Laine, Kalina L. Tosheva, Nils Gustafsson, Robert D. M. Gray, Pedro Almada, David Albrecht, Gabriel T. Risa, Fredrik Hurtig, Ann-Christin Lindås, Buzz Baum, Jason Mercer, Christophe Leterrier, Pedro M. Pereira, Siân Culley, Ricardo Henriques