Results (4)
Search Parameters:
Keyword: Data streams
Enhancing Decision Trees for Data Stream Mining
Data stream gained obvious attention by research for years. Mining this type of data generates special challenges because of their unusual nature. Data streams flows are continuous, infinite and with unbounded size. Because of its accuracy, decision tree is one of the most common methods in classifying data streams. The aim of classification is to…
Read More Data Stream Summary in Big Data Context: Challenges and Opportunities
With the advent of Big Data, we are witnessing a rapid and varied production of huge amounts of sequential data that can have multiple dimensions, we speak of data streams. The characteristics of these data streams make their processing and storage very difficult and at the same time reduce the possibilities of querying them a…
Read More Optimized Multi-Core Parallel Tracking for Big Data Streaming Applications
Efficient real-time clustering is a relevant topic in big data streams. Data stream clustering needs necessarily a short time execution frame with bounded memory utilizing a one-scan process. Because of the massive volumes and dynamics of data streams, parallel clustering solutions are urgent. This paper presents a new approach for this trend, with advantages to…
Read More Design of True Random Numbers Generators with Ternary Physical Unclonable Functions
Memory based ternary physical unclonable functions contain cells with fuzzy states that are exploited to create multiple sources of physical randomness, and design true random numbers generators. A XOR compiler enhances the randomness of the binary data streams generated with such components, while a modulo-3 addition enhances the randomness of the native ternary data streams,…
Read More