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Design and analysis of a multi-dimensional data sampling service for large scale data analysis applications

Xi Zhang, T. Kurc, J. Saltz, S. Parthasarathy
2006 Proceedings 20th IEEE International Parallel & Distributed Processing Symposium  
Sampling is a widely used technique to increase efficiency in database and data mining applications operating on large dataset.  ...  In this paper we present a scalable sampling implementation that supports efficient, multi-dimensional spatio-temporal sample generation on dynamic, large scale datasets stored on a storage cluster.  ...  There has been a lot of work on the use of sampling for data analysis applications.  ... 
doi:10.1109/ipdps.2006.1639315 dblp:conf/ipps/ZhangKSP06 fatcat:emeykbxpijdtxlqbwdfsid36s4

IoT Big-Data Centred Knowledge Granule Analytic and Cluster Framework for BI Applications: A Case Base Analysis

Hsien-Tsung Chang, Nilamadhab Mishra, Chung-Chih Lin, Yong Deng
2015 PLoS ONE  
The current rapid growth of Internet of Things (IoT) in various commercial and non-commercial sectors has led to the deposition of large-scale IoT data, of which the time-critical analytic and clustering  ...  In this work, we propose a knowledge granule analytic and clustering (KGAC) framework that explores and assembles knowledge granules from IoT big-data arrays for a business intelligence (BI) application  ...  Analyzed the data: NM CCL HTC. Contributed reagents/materials/analysis tools: NM CCL HTC. Wrote the paper: NM CCL HTC. Problem formulation, modelling, and mapping to BI service analytics: NM CCL HTC.  ... 
doi:10.1371/journal.pone.0141980 pmid:26600156 pmcid:PMC4657997 fatcat:urz3w5eperds5m3k55weszxacu

Research on Application Scenario of Large Data Cloud Service Platform for Power Energy Measurement

Angang Zheng, Xunan Ding, Huaiying Shang, Yan Liu
2019 IOP Conference Series: Materials Science and Engineering  
This paper studies the technical framework and composition of the large data cloud service platform for power energy measurement, and discusses the application scenario design of the platform for government  ...  We have accumulated a large number of data resources, and business data have been quite large-scale in terms of total amount and type.  ...  Acknowledgments This work is supported by Science and Technology Project of SGCC. (Research on measurement technology framework supporting "Internet +" smart energy, No. 52110418001P)  ... 
doi:10.1088/1757-899x/569/5/052079 fatcat:weug4d67b5e3xnr4c6tlsufzai

On the Processing of Extreme Scale Datasets in the Geosciences [chapter]

Sangmi Lee Pallickara, Matthew Malensek, Shrideep Pallickara
2011 Handbook of Data Intensive Computing  
Since FITS is designed for two-or three-dimensional images, it is naturally well-suited for other forms of multi-dimensional scientific data.  ...  NetCDF data format is widely used in scientific data analysis tools (e.g. MATLAB, R) and GIS applications (e.g. Ar-cGIS), and large-scale simulations.  ... 
doi:10.1007/978-1-4614-1415-5_20 fatcat:iz6q2gvk3rhvblekprn7e4lxcq

ICM: a web server for integrated clustering of multi-dimensional biomedical data

Song He, Haochen He, Wenjian Xu, Xin Huang, Shuai Jiang, Fei Li, Fuchu He, Xiaochen Bo
2016 Nucleic Acids Research  
Large-scale efforts for parallel acquisition of multiomics profiling continue to generate extensive amounts of multi-dimensional biomedical data.  ...  Here, we present a web tool, named Integrated Clustering of Multidimensional biomedical data (ICM), that provides an interface from which to fuse, cluster and visualize multi-dimensional biomedical data  ...  Annotations for genes, proteins and drugs are also growing rapidly. The construction of large-scale repositories of multi-dimensional biomedical data is underway.  ... 
doi:10.1093/nar/gkw378 pmid:27131784 pmcid:PMC4987925 fatcat:eflinagdpbf5vav3dsj7jfwuju

Multidimensional modeling and analysis of wireless users online activity and mobility

Saeed Moghaddam, Ahmed Helmy
2011 Proceedings of the 14th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems - MSWiM '11  
We introduce a systematic method for large-scale multi-dimensional modeling and analysis of online activity and mobility for thousands of mobile users across 79 buildings over a variety of web domains.  ...  We propose a modeling approach based on kind of neural-networks, called self-organizing maps (SOM), for discovering, organizing and visualizing different mobile users' trends from billions of WLAN records  ...  In addition, our work includes novel data analysis techniques to address the challenges provided by this large-scale multi-dimensional data.  ... 
doi:10.1145/2068897.2068965 dblp:conf/mswim/MoghaddamH11 fatcat:qkts7g245rbxbfww5gygmnrfaq

Data-driven Co-clustering Model of Internet Usage in Large Mobile Societies [article]

Saeed Moghaddam, Ahmed Helmy, Sanjay Ranka, Manas Somaiya
2010 arXiv   pre-print
We introduce a systematic method for large-scale multi-dimensional coclustering of web activity for thousands of mobile users at 79 locations.  ...  Design and simulation of future mobile networks will center around human interests and behavior.  ...  Our work also includes novel data processing techniques to address the challenges provided by this large-scale multi-dimensional data.  ... 
arXiv:1005.5180v1 fatcat:tml2hy47jbf2focchjzng3quby

A Framework for Cloud-Based Spatially-Explicit Uncertainty and Sensitivity Analysis in Spatial Multi-Criteria Models

Christoph Erlacher, Karl-Heinrich Anders, Piotr Jankowski, Gernot Paulus, Thomas Blaschke
2021 ISPRS International Journal of Geo-Information  
This paper presents the design of a framework to perform SEUSA as a Service in a cloud-based environment scalable to very large raster datasets and applicable to various domains, such as landscape assessment  ...  The current Spatially-Explicit Uncertainty and Sensitivity Analysis (SEUSA) approach employs a cluster-based parallel and distributed Python–Dask solution for large-scale spatial problems, which validates  ...  Therefore, scalable cloud-based storage services to host and share a large volume of spatial data have to be considered.  ... 
doi:10.3390/ijgi10040244 fatcat:t4gur366k5bvjavsp7erph2gsq

Emotional computing based on cross-modal fusion and edge network data incentive

Lei Ma, Feng Ju, Jing Wan, Xiaoyan Shen
2019 Personal and Ubiquitous Computing  
of large data collection and error detection.  ...  In large-scale emotional events and complex emotional recognition applications, how to improve the recognition accuracy, computing efficiency, and user experience quality becomes the first problem to be  ...  Cross-modal fusion network model Multi-modal data is very common in large data collection, processing, and analysis applications based on Internet of Things and cloud computing platforms.  ... 
doi:10.1007/s00779-019-01232-1 fatcat:6rpzw4lzyjcmrndoqmo2exoqty

Research on Cloud Computing and Its Application in Big Data Processing of Railway Passenger Flow

Y. Xiao, Y. Cheng, Y.J. Fang
2015 Chemical Engineering Transactions  
It not only brings the opportunities of railway transport capacity and volume, but also makes the data of various types of large-scale continuous growth.  ...  The algorithm divides the large training data set into a number of small training sets by Map, and then a new SVM is combined with these small t raining sets.  ...  It not only brings the opportunities of railway transport capacity and volume, but also makes the data of various types of large-scale continuous growth.  ... 
doi:10.3303/cet1546055 doaj:e8e6f21b58ea43e9a9e9b6cfb19cee1d fatcat:cox5t2rju5bbzdygrmnlnq56ea

Spatio-Temporal Modeling of Wireless Users Internet Access Patterns Using Self-Organizing Maps [article]

Saeed Moghaddam, Ahmed Helmy
2010 arXiv   pre-print
We introduce a systematic method for large-scale multi-dimensional analysis of online activity for thousands of mobile users across 79 buildings over a variety of web domains.  ...  We propose a modeling approach based on self-organizing maps (SOM) for discovering, organizing and visualizing different mobile users' trends from billions of WLAN records.  ...  One network application for multi-dimensional modeling is profile-based services.  ... 
arXiv:1008.4904v1 fatcat:kqkzpoglvfffpowp7ewbi4vwqa

A Vision for Cyberinfrastructure for Coastal Forecasting and Change Analysis [chapter]

Gagan Agrawal, Hakan Ferhatosmanoglu, Xutong Niu, Keith Bedford, Ron Li
2008 Lecture Notes in Computer Science  
This will include developments in middleware, model integration, analysis, and mining techniques, and the use of a service model for supporting two closely related applications.  ...  These applications will be real-time coastal nowcasting and forecasting, and long-term coastal erosion analysis and prediction. GATES Grid Service GATES Grid Service  ...  Our preliminary experiments on satellite images establish that both split-VQ and multi-stage VQ can be effectively employed to design negligibly small codebooks for a large-scale image database [35] .  ... 
doi:10.1007/978-3-540-79996-2_9 fatcat:5xtdxecx2ncvxkwbo2hztk22xy

Multiple Spatial Model Fusion in Heterogeneous Sensor Networks

Jiangfan Feng, Wei Wei
2014 International Journal of Multimedia and Ubiquitous Engineering  
With the growth of location-based services (LBS), location-based data is a crucial role for many sensor-network applications.  ...  Furthermore, we provide a method for the effective storage and management of massive and multi-source heterogeneous spatial data.  ...  Acknowledgements The work is supported by the National Nature Science Foundation of China (41101432, 41201378), the Natural Science Foundation Project of Chongqing (cstc2012jjA40014), scientific and Technological  ... 
doi:10.14257/ijmue.2014.9.2.01 fatcat:v46gqhokerhl5p5j2zfvzna5ni

YADING

Rui Ding, Qiang Wang, Yingnong Dang, Qiang Fu, Haidong Zhang, Dongmei Zhang
2015 Proceedings of the VLDB Endowment  
Fast and scalable analysis techniques are becoming increasingly important in the era of big data, because they are the enabling techniques to create real-time and interactive experiences in data analysis  ...  In this paper, we propose a novel end-to-end time series clustering algorithm, YADING, which automatically clusters large-scale time series with fast performance and quality results.  ...  We also thank our partners in Microsoft product teams who used our tool and provided valuable feedback. We thank Tao Pei for sharing with us the source code of DECODE.  ... 
doi:10.14778/2735479.2735481 fatcat:6idwfzieanbivd7ztg537ptx4a

BioCyBig: A Cyberphysical System for Integrative Microfluidics-Driven Analysis of Genomic Association Studies

Mohamed Ibrahim, Krishnendu Chakrabarty, Jun Zeng
2016 IEEE Transactions on Big Data  
This paper presents a research vision to design a large-scale cyberphysical systems (CPS) experimental framework to enable collaborative and coordinated molecular biology studies.  ...  This framework therefore leads to a better understanding of diseases such as cancer, and helps researchers in identifying effective treatments.  ...  Apache Spark is a centralized scheme that designed to handle a large amount of data by simultaneously processing it at scale.  ... 
doi:10.1109/tbdata.2016.2643683 fatcat:u5ws25dwdnbmbj4bb4qyppbl2a
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