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

Digital Elevation Models (DEMs) are used to estimate different morphologies, analysis of river profile, delineating drainage basin and drainage pattern associated with lithological and structural changes. The study area is Maroon River located in Khuzestan Province, Iran. In this study geomorphometric analysis based on DEM carried out to understand Maroon river uplift rate and tectonic- erosion...

In resource-constrained devices, adaptation of data stream processing to variations of data rates, availability of resources and environment changes is crucial for consistency and continuity of running applications. Context-aware and resource-aware adaptation, as a new dimension of research in data stream mining, enhances and improves distributed data stream processing tasks. Context-awareness ...

How to preserve users’ privacy while supporting high-utility analytics for low-latency stream processing? To answer this question: we describe the design, implementation and evaluation of PRIVAPPROX, a data analytics system for privacy-preserving stream processing. PRIVAPPROX provides three important properties: (i) Privacy: zero-knowledge privacy guarantee for users, a privacy bound tighter th...

Our research project aims to build an infrastructure that can efficiently and seamlessly to meet the demanding requirements of business event stream-based analytical applications. We focus on the complex event analysis on event streams, QoS-aware event processing services, and a novel event stream processing model that seamlessly and efficiently combines event processing services. That model is...