data stream research papers 2011-2012 section 2

Astral: An algebraic approach for sensor data stream querying
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L Petit, CL Roncancio, C Labbé, FG Ottogalli ,2011 ,
Abstract The use of sensor based applications is in expansion in many contexts. Sensors
are involved at several scales ranging from the individual (eg personal monitoring, smart
homes) to regional and even world wide contexts (ie logistics, natural resource monitoring 

 Sensor Data Stream Exploration for Monitoring Applications
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ABSTRACT This paper presents StreamXPlore, a system that enables users to explore
historical stream data in order to determine what events to monitor in the future. At the heart
of StreamXPlore is a new event modeling mechanism. StreamXPlore enables the 

Multilevel secure data stream processing
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With sensors and mobile devices becoming ubiquitous, situation monitoring applications are
becoming a reality. Data Stream Management Systems (DSMSs) have been proposed to
address the data processing needs of such applications that require collection of high- 

 Approximate Maximal Frequent Itemset Mining over Data Stream?
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H Li, N Zhang ,2011
Abstract Maximal frequent itemsets are one of several condensed representations of
frequent itemsets, which store most of the information contained in frequent itemsets using
less space, thus being more suitable for stream mining. This paper focuses on mining 

 Task scheduling in data stream processing
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Z Falt, J Yaghob ,Proceedings of the Dateso 2011 Workshop, 2011
Abstract. One possible technique of data processing is its transformation into a data stream
and the execution of particular operations on the data tuples. These operations can be
usually processed concurrently especially when the plan of operations is branched. 

 Effective Parameters on Response Time of Data Stream Management Systems
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Abstract–considering rapid and time variant (bursty) nature of data streams, data would
rapidly lost its value while time is going on. So, the results with high response time are not
reliable in Data Stream Management Systems (DSMSs). In other words, one of the most 

SOStream: self organizing density-based clustering over data stream
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In this paper we propose a data stream clustering algorithm, called Self Organizing density
based clustering over data Stream (SOStream). This algorithm has several novel features.
Instead of using a fixed, user defined similarity threshold or a static grid, SOStream detects 

HUE-Stream: Evolution-Based Clustering Technique for Heterogeneous Data Streams with Uncertainty
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W Meesuksabai, T Kangkachit, K Waiyamai , Data Mining and Applications, 2011 ,Springer
Evolution-based stream clustering method supports the monitoring and the change
detection of clustering structures. E-Stream is an evolution-based stream clustering method
that supports different types of clustering structure evolution which are appearance, 

 Blockmon: Flexible and High-Performance Big Data Stream Analytics Platform and its Use Cases
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M Dusi, N d’Heureuse, F Huici, A di Pietro ,NEC TECHNICAL , 2012 ,
Abstract This paper describes Blockmon, a novel, configurable, software-based Big Data
platform for high-performance data stream analytics. Its design allows running applications
for a wide range of use cases. When used as network data processing and monitoring 

Efficient minimization of servo lag error in adaptive optics using data stream mining
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A Vyas, MB Roopashree, BR Prasad ,Advances in Power Electronics and , 2011 ,Springer
Prediction of the wavefronts helps in reducing the servo lag error in adaptive optics caused
by finite time delays (~ 1-5 ms) before wavefront correction. Piecewise linear segmentation
based prediction is not suitable in cases where the turbulence statistics of the atmosphere 

Creating ensemble classifiers through order and incremental data selection in a stream
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Abstract This paper presents an original time-sensitive traffic management application for
road safety diagnosis in signalized intersections. Such applications require to deal with data
streams that may be subject to concept drift over various time scales. The method for road 

Partially labeled data stream classification with the semi-supervised K-associated graph
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Abstract Regular data classification techniques are based mainly on two strong
assumptions:(1) the existence of a reasonably large labeled set of data to be used in
training; and (2) future input data instances conform to the distribution of the training set, ie 

Transfer estimation and the applications in data stream classification
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Z Zhang, J Zhou ,Proceedings of SPIE, 2011 ,
ABSTRACT Transfer estimation is a new parameter estimation method, which utilizes
samples from not only the target distribution but also related ones. It is based on traditional
estimators and can be used to solve the problem of small sample estimation. The key 

 Compact Tree for Associative Classification of Data Stream Mining
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KP Lakshmi, CRK Reddy ,2012
Abstract The data streams have recently emerged to address the problems of continuous
data. Mining with data streams is the process of extracting knowledge structures from
continuous, rapid data records [1]. An important goal in data stream mining is generation 

Sequential Pattern Mining from Stream Data
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Sequential Pattern Mining, briefly SPM, is an interesting issue in Data Mining that can be
applied for temporal or time series data. This paper is related to SPM algorithms that can
work with stream data. We present three new stream SPM methods, called SS-BE2, SS- 

 A Hybrid Method for Fast Predicate Matching in Data Stream Processing
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HGYU KIM, MHO KIM ,Journal of Information Science and , 2012 ,
Efficient predicate matching is essential to provide real-time responses in data stream
processing. Many predicate indexes have been introduced to address the predicate
matching problem. Among them, the IBS-tree handles predicates with open and closed 

Context-aware collaborative data stream mining in ubiquitous devices
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Recent advances in ubiquitous devices open an opportunity to apply new data stream
mining techniques to support intelligent decision making in the next generation of ubiquitous
applications. This paper motivates and describes a novel Context-aware Collaborative 

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Motivation The past decade has witnessed the explosive growth of real-time data
streams. The advent of sensory and communication technologies is advancing the
generation and consumption of streaming data (many are geo-referenced) in our daily 

 Statistical Data Analysis of Continuous Streams Using Stream DSMS
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N Akhtar ,International Journal of Database Management , 2011
ABSTRACT Several applications involve a transient stream of data which has to be modeled
and analyzed continuously. Their continuous arrival in multiple, rapid, time-varying and
possibly unpredictable and unbounded way make the analysis difficult and opens 

 QA/QC of measurements collected on very large scale-rainfall and stream flow data
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QA/QC of measurements collected on very large scale ,rainfall and stream flow data
Ross Sparks and Chris Okugami ISI 23 August 2011 Page 2. Outline • Measurement quality
an important issue • What are the issues with current practice? 

 Capturing the pulse of cities: A robust stream data reasoning approach
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Abstract. In a Smarter City, available resources are harnessed safely, sustainably and
efficiently to achieve positive, measurable economic and societal outcomes. Data (and then
information) from people, systems and things is the single most scalable resource 

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A Mala, FR Dhanaseelan ,International Journal on Computer , 2011
Abstract More and more applications such as traffic modeling, military sensing and tracking,
online data processing etc., generate a large amount of data streams every day. Efficient
knowledge discovery of such data streams is an emerging active research area in data 

 Online visualization of geospatial stream data using the worldwide telescope
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ABSTRACT This demo presents the ongoing effort to meld the stream query processing
capabilities of Microsoft StreamInsight with the visualization capabilities of the WorldWide
Telescope. This effort provides visualization opportunities to manage, analyze, and 

 A stream data model and query language for continuous/stream queries over EO image files and databases
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Executive Summary In the TELEIOS project, in particular NOA’s real-time fire monitoring use
case (work-package 7) requires continuous query processing functionality similar to that
known from event stream processing of publish/-subscribe scenarios. As opposed to ad- 

 A Data-Descriptive Feedback Framework for Data Stream Management Systems
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RJF Moctezuma ,2012 ,
ABSTRACT Data Stream Management Systems (DSMSs) provide support for continuous
query evaluation over data streams. Data streams provide processing challenges due to
their unbounded nature and varying characteristics, such as rate and density fluctuations. 

 Detection, tracking and event localization of jet stream features in 4-D atmospheric data
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S Limbach, E Schömer ,Geoscientific Model , 2012 ,
Abstract. We introduce a novel algorithm for the efficient detection and tracking of features in
spatiotemporal atmospheric data, as well as for the precise localization of the occurring
genesis, lysis, merging and splitting events. The algorithm works on data given on a four- 

Stream Traffic Data Archival, Querying, and Analysis with TransDec
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ABSTRACT The goal of research was to extend the traffic data analysis of the TransDec
(short for Transportation Decision-Making) system, which was developed under METRANS
09-26 research grant. The TransDec system is a real-data driven system to support 

 Simulating stream flow over data sparse areas–an application of internet based data
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MT Vu, SV Raghavan, SY Liong , . Earth Syst. Sci. , 2011
Abstract Many hydrological modeling studies suffer from lack of robust station observed
data, mainly rainfall and discharge. Where such a dearth of data exists, detailed modeling
studies in estimating and assessing change in water resources become difficult when 

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JW McConnell ,2012 ,
ABSTRACT This report provides the analytical data, and selected field data, obtained from
the seven detailedscale stream-sediment and stream-water surveys conducted in Labrador
by the Geological Survey during the period 1980 to 1995. A total of 1362 sediment