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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.

Sharanya Anand's CV. Created with the Medium Length CV template.

Optical fiber technology and its applications

Ayesh Shafia's CV with personal, educational details. Created with this CV template.

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.

Avance previo de un proyecto para la universidad.

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.

Short biography of mathematician Emmy Noether

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.