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.
Data sets are often too immense to fit completely inside the computer's main memory and must instead reside on disk. If data set will be kept in main memory it will be very costly. A computer must retrieve required data and place it in internal memory to process it. Efficient data structures, like B-tree, B+ tree, are used to process large datasets. Nodes of these data structures are buffered in memory...
Sentiment analysis has been shown to be a useful tool for quantitative analysis in the world of finance. Researchers have shown that the sentiment picked up from the news media can be correlated with movement of the stock market. Here we use the Harvard General Inquirer to determine the sentiment present in Reuter's articles. After first generating positive and negative sentiment data we use the Kalman...
Prior work in hardware prefetching has focused mostly on either predicting regular streams with uniform strides, or predicting irregular access patterns at the cost of large hardware structures. This paper introduces the Variable Length Delta Prefetcher (VLDP), which builds up delta histories between successive cache line misses within physical pages, and then uses these histories to predict the order...
A fuzzy algorithm is presented for image segmentation of 2D gray scale images whose quality have been degraded by various kinds of noise. Traditional Fuzzy C Means (FCM) algorithm is very sensitive to noise and does not give good results. To overcome this problem, a new fuzzy c means algorithm was introduced [1] that incorporated spatial information. The spatial function is the sum of all the membership...
Clustering is a familiar concept in the realm of Data mining and has wide applications in areas like image processing, pattern recognition and rule generation. Uncertainty in present day databases is a common feature. In order to handle these datasets, several clustering algorithms have been formulated in the literature. The first one being the Fuzzy C-Means (FCM) algorithm and it was followed by...
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.