The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
There are small amounts of bad data in power system real time data. If we do not correct them, they will have impact on security and stability of the power system. This text put forward a bad data correction algorithm based on genetic neural network algorithm. In order to overcome the BP neural network's own defects, we use the genetic algorithm to define the optimum structure and the best initialized...
With the rapid growth of information technology, the e-learning has become a major trend in the computer assisted teaching and learning field. Previously, many researchers put efforts into e-learning system with emphasizing the application of multimedia elements; they often neglected the importance of three crucial elements-personalization, contextual understanding and platform-independent standardized...
The Superfamily database provides structural assignments to protein sequences. This assignment enable us to analyze the distribution of specific superfamilies within and across the genomes. Here, we focus on the distributions of superfamilies in archaeal, bacterial and eukaryotic genomes. The distribution of the most common superfamilies in archaea and bacteria are very similar (6 of the top 10 superfamilies...
Based on the two-level model and the unified theory of low frequency relaxation processes for condensed matter, we studied the magnetic after-effect spectrum in the temperature range between 250 and 350 K for the amorphous Fe 50 Ni 30 B 20 alloy after an annealing treatment for 2 h at 480 K. The calculated infrared divergence exponentn = 0.11, and the characteristic...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.