نتایج جستجو برای: zaringol stream
تعداد نتایج: 57939 فیلتر نتایج به سال:
The events generated by such an active database could be used by themselves, but it is much more interesting if they can be reuse as primitive events for more complex events. For example combining events from multiple active databases and also other sources. This implies that we do the event detection in the network, or have a way of getting notified every time when an interesting event occurs ...
Online, one-pass mining Web click streams poses some interesting computational issues, such as unbounded length of streaming data, possibly very fast arrival rate, and just one scan over previously arrived Web click-sequences. In this paper, we propose a new, single-pass algorithm, called DSM-TKP (Data Stream Mining for Top-K Path traversal patterns), for mining a set of top-k path traversal pa...
Much of the research regarding streaming data has focused only on real time querying and analysis of recent data stream allowable in memory. However, as data stream mining, or tracking of past data streams, is often required, it becomes necessary to store large volumes of streaming data in stable storage. Moreover, as stable storage has restricted capacity, past data stream must be summarized. ...
Distributed Stream Processing frameworks are being commonly used with the evolution of Internet of Things(IoT). These frameworks are designed to adapt to the dynamic input message rate by scaling in/out.Apache Storm, originally developed by Twitter is a widely used stream processing engine while others includes Flink [8] Spark streaming [73]. For running the streaming applications successfully ...
Data stream processing has become increasingly important as many emerging applications call for sophisticated realtime processing over data streams, such as stock trading surveillance, network traffic monitoring, and sensor data analysis. Stream joins are among the most important stream processing operations, which can be used to detect linkages and correlations between different data streams. ...
Most available static data are becoming more and more highdimensional. Therefore, subspace clustering, which aims at finding clusters not only within the full dimension but also within subgroups of dimensions, has gained a significant importance. Recently, OpenSubspace framework was proposed to evaluate and explorate subspace clustering algorithms in WEKA with a rich body of most state of the a...
A new class of data management systems that operate on highvolume streaming data is becoming increasingly important. As this kind of systems has to process unpredictable streaming data in real-time and deliver instantaneous responses, it becomes very difficult to precisely validate stream processing results in timely manner, verify stream computation that took place and investigate processing s...
Activity recognition has become one of the emerging applications in the area of ubiquitous computing. This research aims at leveraging ubiquitous data stream mining and context reasoning for mobile activity recognition. The novel system allows dynamic adaptation and personalisation of the learning model to reflect the realistic activity changes emerged over time. Sensors fusion to attain a cont...
Current runtime verification tools seldom make use of multi-threading to speed up the evaluation of a property on a large event trace. In this paper, we present an extension to the BeepBeep 3 event stream engine that allows the use of multiple threads during the evaluation of a query. Various parallelization strategies are presented and described on simple examples. The implementation of these ...
The performance characteristics of a tidal stream turbine are critical when assessing its economical viability. The solidity of the rotor, which is a function of the blade chord length and the number of blades, will affect the performance characteristics, from both a power output and a structural
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