Immersive Analytics: Exploring Future Interaction
and Visualization Technologies for Data Analytics
B
Bach, R Dachselt,
Immersive Analytics:
Exploring Future Interaction and Visualization Technologies for Data
Analytics. ... We propose to conduct a workshop on the
topic of Immersive Analytics: a new multidisciplinary initiative to
explore future interaction technologies for data analytics. ...
XS
Zhou, M Salganicoff - US Patent 20,160,321,402, 2016
... Thus, 2D image
processing and image analysis techniques can be applied to the
3D volume image data. ... Data analytics tools may
be invoked at each node to process the patient records for visualization,
online learning, decision support, or other applications. ...
Cloud Computing Approach for Intelligent Visualization of
Multidimensional Data
J
Bernatavičienė, G Dzemyda, O Kurasova… - Advances in Stochastic and
…, 2016
... doi:10.1145/1656274.1656278CrossRef.
13. Hofmann, M., Klinkenberg, R.: RapidMiner: Data Mining Use Cases
and Business Analytics Applications. Chapman and Hall/CRC,
[PDF] Microarray Integrated Analysis of a Gene
Network for the CD36 Myocardial Phenotype
I
Sabaouni, B Vannier, A Moussa, A Ibrahimi - Bioinformation, 2016
... and networks of
interactions that emerge from knocking CD3 and using different bioinformatics tools such
as STRING, GeneMANIA and Cytoscape. We were able list all the CD36-regulated genes,
their related function and their specific networks. Data analysis showed
that ...
Optimal execution of co-analysis for large-scale
molecular dynamics simulations
P
Malakar, V Vishwanath, C Knight, T Munson… - … , Storage and Analysis,
2016
... 34. V. Vishwanath,
M. Hereld, ME Papka, R. Hudson, G. Jordan, and C. Daley, "In Situ Data
Analytics and I/O Acceleration ... L. Adhianto, S.
Banerjee, M. Fagan, M. Krentel, G. Marin, J. Mellor-Crummey, and NR Tallent,
"HPCToolkit: Tools for performance analysis of
optimized ...
Caliper: performance introspection for HPC software stacks
D
Boehme, T Gamblin, D Beckingsale, PT Bremer… - … , Storage and Analysis,
2016
... This requires an
interoperable, cross-stack, general-purpose approach to performance data collection,
which neither application-specific performance measurement nor traditional
profile or trace analysis tools provide.
With ...
[PDF] Co-evolutionary Algorithm for Analyzing Gene Expression Data
JH
Claver, IS Ngongo - 2016
... The bottleneck in
dealing cogently with the upcoming data explosion is clearly
focused on the development of data analysis tools that
i) identify the difference in gene expression profiles and ii) capture or
predict the mutual or co-dependence of expression levels of pairs of
genes ...
MW
Klymkowsky,
... articulated
assumptions. In addition to the built in coding tools for text
and drawings, beSocratic also has built in automatic analysis tools to
cluster the coded data, which enables us to search for patterns in
student responses. ...
Understanding performance interference in next-generation HPC
systems
OH
Mondragon, PG Bridges, S Levy, KB Ferreira… - … , Storage and Analysis,
2016
... GoldRush: resource
efficient in situ scientific data analytics using
fine-grained interference aware execution ... of the
International Conference for High Performance Computing, Networking, Storage and Analysis. ... and
encapsulate it in an effort log tool to collect data on
development ...
U
Ayachit, A Bauer, EPN Duque, G Eisenhauer… - … , Storage and Analysis,
2016
... and S. Klasky,
"Goldrush: Resource efficient in situ scientific data analytics using
fine ... IEEE International Conference for High Performance
Computing, Networking, Storage and Analysis. ... 48. CD
Spradling, "Spec cpu2006 benchmark tools," ACM SIGARCH
Computer Architecture ...
U
Ayachit, A Bauer, EPN Duque, G Eisenhauer… - Proceedings of the …, 2016
... 1, pp. 17--29, Jan.
2012, lBNL-4370E. 33. J. Dayal, J. Lofstead, G. Eisenhauer, K. Schwan, M. Wolf,
H. Abbasi, and S. Klasky, "Soda: Science-driven orchestration
of data analytics," in e-Science (e-Science),
2015 IEEE 11th International Conference on. IEEE, 2015, pp. 475--484. ...
Winning on HR Analytics: Leveraging Data for
Competitive Advantage
R
Soundararajan, K Singh - 2016
Scalemine: scalable parallel frequent subgraph mining in a
single large graph
... and SS Chawathe,
"SEuS: Structure Extraction Using Summaries," in Discovery Science,
2002, pp. ... tasks Applications," in Proceedings of the
International Conference on Data Engineering (ICDE ... Towards
Predicting the Runtime of Large Scale Iterative Analytics,"
Proceedings of ...
Understanding performance interference in next-generation HPC systems
OH
Mondragon, PG Bridges, S Levy, KB Ferreira… - Proceedings of the …, 2016
... Statistical Science,
pages 153--167, 2000. 18. F. Hernandez-Campos, J. Marron, G. Samorodnitsky, and
FD Smith. ... Grid-based parallel data streaming
implemented for the gyrokinetic toroidal code. ... Scheduling
in-situ analytics in next-generation applications. ...
Optimal execution of co-analysis for large-scale molecular
dynamics simulations
P
Malakar, V Vishwanath, C Knight, T Munson… - Proceedings of the …, 2016
... Integrated Steering
Framework for Critical Weather Applications," in Proceedings of the International
Conference on Computational Science, vol. 4, 2011, pp. 116 -- 125.
34. V. Vishwanath, M. Hereld, ME Papka, R. Hudson, G. Jordan, and C. Daley,
"In Situ Data Analytics ...
M
Manaa, A Jalel - Handbook of Research on Geographic Information …, 2017
... to understanding
entities behaviors and activities from cognitive and analytics perspectives. ... Recent
advances in DBMS technology handle ontologies and semantic data in
semantic ... representation has been investigated by the
geographic information science community called ...
Cloud Computing Approach for Intelligent Visualization of
Multidimensional Data
J
Bernatavičienė, G Dzemyda, O Kurasova… - Advances in Stochastic and
…, 2016
... Hofmann, M.,
Klinkenberg, R.: RapidMiner: Data Mining Use Cases and
Business Analytics Applications. ... Lecture Notes
in Computer Science, vol ... Smailovič, J.,
Podpečan, V., Grčar, M., Žnidaršič, M., Lavrač, N.: Active
learning for sentiment analysis on data streams:
methodology ...
[PDF] Management Matters
K
Provan, A Osorio - Management, 2016
... Empirical proposals
will be evaluated based on the significance and quality of the research question,
design, methods, data, and implications ... be
abandoned” (Rorty, 2009, p. 6). In their articulation of the present state of
post-normal science, Funtowicz and Ravetz underscore the ...
Raising your Eminence inside the Enterprise Social Network
... ACM. 21. Kevan, L.
2015. The Biggest Social Science Study: What 4.8 Million
Tweets Say About the Best Time to Tweet. In buffersocial blog. ... 2011.
Charu C. Aggarwal, editor, Social Network Data Analytics,
chapter 7, 2011, 177--214. 35. Thom, J., Millen, D., & DiMicco, J.
2012. ...
Six Meanings of the History of Science: The Case of
Psychology
A
Toomela - Centrality of History for Theory Construction in …, 2016
... justification. So I
looked into the works of the founders of statistical data analysis
, into the works of those who introduced quantitative mathematical methods into
science in general and psychology in particular. The founders ...
B
Yüceoğlu, Şİ Birbil, I Öztürk - Decision Support Systems, 2016
... good retailer. The
proposed system is based on recent data analytics and
machine learning tools. The main steps of our development are data cleaning,
feature extraction and prediction with supervised learning methods. The ...
RiboCAT: A new capillary electrophoresis data
analysis tool for nucleic acid probing
WA
Cantara, J Hatterschide,
... a complementary
tool, RiboDOG (RiboCAT Data Output Generator) was designed to
facilitate the comparison of multiple datasets, highlighting potential
inconsistencies and inaccuracies that may have occurred during analysis.
Using these new tools, the secondary structure of ...
[PDF] GFA: Exploratory Analysis of Multiple Data Sources
with Group Factor Analysis
E
Leppäaho, M Ammad-ud-din,
... This kind of
sparsity is beneficial for exploratory data analysis and
integration. Our GFA package covers essential tools ranging
from preprocessing to modelling assumptions and from robustness analysis to
interpreting the model. Acknowledgments ...
[HTML] Big genomics and clinical data analytics strategies
for precision cancer prognosis
GS
Ow, VA Kuznetsov - Scientific Reports, 2016
... In the second part
of our study, we extended our analysis to the use of
classical ... well in specific situations and are sensitive to
sample size and the data input. ... We
suggest that our collective intelligence computational method could improve
the analytics strategy for translation of ...
Analytic data focus representations for
visualization generation in an information processing system
DS
Reiner, D Dietrich - US Patent 9,483,520, 2016
... representations can
be used to generate what are referred to herein as “generalized tag cloud visualizations”
or GTCVs that provide highly useful analytic tools even for
the complex data sources typically associated with “big data” analytics.
Thus, improved data analysis can be ...
A
Postel,
... Platforms for
sharing sequence information and providing standardized tools for
phylogenetic analyses are ... We present an application
example for the analysis of highly similar viral ... The
worldwide exchange of genome data from viruses causing severe
transboundary diseases ...
Business process optimization with big data
analytics under consideration of privacy
... BIG DATA ANALYTICS LIFECYCLE
PROCESS Conducting big data science ventures differs from ap-
proaches for projects using SQL data and Business Intelli-
gence BI methods and tools applied for data analysis aims
[3]. The approach used for big data is more explorative
in ...
An advanced data analytics framework for energy
efficiency in buildings
D
Schachinger, S Gaida,
... Systems Analysis,
A Review of Meta-Analysis Packages in R
JR
Polanin, EA Hennessy, EE Tanner-Smith - Journal of Educational and Behavioral
…, 2016
... R Archive Network
(CRAN) website (R Core Team, 2015), Revolution Analytics (2016),
and ... The package will also address missing data using
listwise deletion, handle hierarchically dependent ... Five
packages focus on tools for meta-analysis of
microarray data: MADAM (Kugler ...
Fuzzy logic–based evaluation of visualizations generated by
intelligent decision support systems
H
Ltifi, S
... methodology for
comparing memory and communication of analytic processes in visual analytics. ...
new approach for evaluating flow visualization methods based on eye
tracking analysis. ... Evaluating their usability
is challenging because visual data mining tools combine
several ...
J
Alderson, W Johnson - ISBS-Conference Proceedings Archive, 2016
... With continued
advances in; passive and active imaging, multi-sensor integration, advanced historical data mining,
scalable real-time processing architectures, and non-linear data science
analytics techniques (eg deep learning), it is clear that the
laboratory versus field nexus ...
An industrial analytics approach to predictive
maintenance for machinery applications
CP
Gatica, M Koester, T Gaukstern,
... Companies who offer
such services differentiate by their ability to perform offline analytics in
an efficient way. AGT, for instance, has built over time an extensive data science and
machine learning toolbox that allows assessing sample data in
short time frame. ...
Business process optimization with big data
analytics under consideration of privacy
Abstract:
One of the contemporary problems, and at the same time a big opportunity,
in business networks of supply chains are the issues associated with the
vast amounts of data arising there. The data may
be utilized by the decision support systems in supply chains; ...
[PDF] Practical Digital Curation Skills for Archivists in the 21st
Century
M
Lee, M Kendig, R Marciano, G Jansen, M Kurtz… - 2016
... & analytics Page
50. How Each Project Is Related to Computational Archival Science (CAS)
Themes: Project Computational Linguistics Data Modeling &
Evolutionary Prototyping Graph Analytics Crowdsourcing GIS 1. Human
Face of Big Data [Community Displacement] X X X ...
Big data meets big water: Analytics of
the AIS ship tracking data
Abstract:
IN THIS presentation we will argue that Big Data technologies
can contribute in an important way to an unprecedented breakthrough in
the understanding of oceans as a factor in climate change, in
transportation, and in supplying humanity with its important food ...
B
Yüceoğlu, Şİ Birbil, I Öztürk - Decision Support Systems, 2016
Development
of a decision support system using data analytics for
customer churn prediction for an online retailer. ... İlker
and Öztürk, Işıl (2016) Development of a decision support system
using data analytics for customer churn prediction for
an online retailer. (Submitted). ...
[PDF] Challenges of feature selection for big data analytics
J
Li, H Liu - arXiv preprint arXiv:1611.01875, 2016
Page
1. arXiv:1611.01875v1 [cs.LG] 7 Nov 2016 Challenges of Feature Selection for
Big Data Analytics ∗ Jundong Li and Huan Liu
Computer Science and Engineering Arizona State University, USA
{jundongl,huan.liu}@asu.edu ...
H
Kim, Y Ra - ISBS-Conference Proceedings Archive, 2016
... For instance, data collected
by KNSU for winter sports analytics are motion capture data of
3-dimensional motion analysis system (60Hz), EMG signal data ... In
Korea, research on the integrated management of data collection
was raised in the field of science and extended to ...
Strategic Analytics and SAS: Using
Aggregate Data to Drive Organizational Initiatives
RS
Collica - 2016
[HTML] Big genomics and clinical data analytics strategies
for precision cancer prognosis
GS
Ow, VA Kuznetsov - Scientific Reports, 2016
... Article | Open. Big
genomics and clinical data analytics strategies
for precision cancer prognosis. ... Abstract. The field of
personalized and precise medicine in the era of big data analytics is
growing rapidly. Previously, we proposed ...
A
Shiri - DATA ANALYTICS 2016, 2016
... The application
makes use of a broad range of technologies, including PHP (Hypertext Preprocessor)
and MySQL (Structured Query Language), information visualization technologies, and
text and data analysis tools. IV. LEARNING ANALYTICS TOOL
FUNCTIONALITIES The ...
Deep Network Analyzer (DNA): A Big Data Analytics Platform
for Cellular Networks
KAI
YANG, R Liu, Y Sun, X Chen - IEEE Internet of Things Journal, 2016
... DNA is motivated by
the growing scale and complexity of cellular networks along with the lack of
advanced big data analytics tools for
effective network management. It abstracts the root cause analysis process
into two modules, namely rule (fingerprint) learning and the module ...
[PDF] WACIC Method–A Web Analytics Process to Perform
Continuous Improvement in Digital Environments
AT
Figueiredo, MAF Borges, RLO Moraes - DATA ANALYTICS 2016, 2016
... identified.
Onwubiko [7] performed a research focused on the applicability of Web Analytics tools in data gathering
and analysis to enhanced cyber situational awareness for
monitoring critical online Web services. Many different ...
Tools for opportunistic information visualization: Visual analysis with
non-traditional data sources
GG
Méndez - Visual Languages and Human-Centric Computing (VL/ …, 2016
Abstract:
Information Visualization (InfoVis) often supports the analysis of
structured data that is organized in documents with
specific formats such as databases, Excel tables, or comma- separated files.
Informal analyses that take place without anticipation and away from the ...
[HTML] A fuzzy method for RNA-Seq differential expression analysis in
presence of multireads
A
Consiglio, C Mencar, G Grillo, F Marzano… - BMC Bioinformatics, 2016
... We have tested the
method on RNA-Seq data designed for case-control studies and
we have compared the obtained results with other existing tools for
read count estimation and differential expression analysis.
Conclusions. ...
Using lipidomics analysis to determine
signalling and metabolic changes in cells
A
Nguyen, SA Rudge, Q Zhang, MJO Wakelam - Current Opinion in Biotechnology, 2017
... This review focuses
on four points: how lipid data can be collected and processed
with the support of tools, software and databases; how
lipidomic analysis is performed at the molecular level; how to
integrate data analysis into a biological context;
how the results of such ...
SJC
Janssen, CH Porter, AD
... and implement the
next generation of data, models, and decision support tools for
agricultural ... challenge, the interoperability of data sources,
modular granular open models, reference data sets for applications
and specific user requirements analysis methodologies need
to ...
A Framework for Big Data Security Analysis and
the Semantic Technology
Y
Yao, L Zhang, J Yi, Y Peng,
... other terms are
also used, but a number of these refer to the analytics and
architectures ... complex; have unknown or low density of
value; and have multiple computation and analysis processes ...
on the general understanding of the concept of big data, the
big data techniques refer ...
Organizational and Societal Impacts of Big Data in
Crisis Management
H
Watson, RL Finn, K Wadhwa - Journal of Contingencies and Crisis Management,
2016
... Findings also
reveal that big data is able to contribute to predictive analytics and
more ... Here predictive analytics is related
to the response stage as well as in future planning efforts. ... This
could include 'trend analysis' and 'predicting which populations
are vulnerable' to health risks ...
Big data processing and analysis platform
for condition monitoring of electric power system
Y
Guo, S Feng, K Li, W Mo, Y Liu, Y Wang - Control (CONTROL), 2016 UKACC 11th …,
2016
... integrated
open-source algorithm packs are converged by many analysis tools developed
all over the world, which supplies a plenty of generic computing tools. ... Robust data analytics,
high performance computing, efficient data network management,
and cloud computing ...
Guest Editorial: Volume, variety and velocity in Data
Science
A
Alonso-Betanzos, JA Gámez, F Herrera, JM Puerta… - Knowledge-Based Systems,
2016
... converting data into
knowledge. Under the framework of Data science, several
important data based research paradigms are subsumed: data mining, data analytics,
machine learning and big data. Data Science covers
all the ...
J
Hendler, W Hall - Science, 2016
... The growth of
available information is also leading to increasing use of data analytics in
many fields, and the intersection of network science, data science,
and Web science is helping to bring new technologies to
scientists and engineers who grapple with large-scale problems ( ...
BK
Fitzgerald,
... Abstract: BHEF has
achieved particular success in operationalizing its National Higher Education
and Workforce Initiative (HEWI) through regional initiatives in data
science and analytics (DSA). Leveraging its
membership of ...
Storage and Read-Optimized Data Placement
Structures for High-Performance Analysis
... Abstract We present
state-of-art structures and methods for efficient data preparation
and representation for analysis. Our intent is to introduce the data science and analytics
communities to open source data placements, structures, and
methods. ...
Big Data Analytics: Service and Manufacturing
N
... 22 Page 44.
Big Data Analytics
Data science applications to improve accuracy of
thermocouples
H
Zhengbing, V Jotsov, S Jun, O Kochan, M Mykyichuk… - Intelligent Systems (IS),
…, 2016
... Suggested
innovations serve the more effective application of data science,
advanced analytics, (deep) data/web mining and/or
collective evolutionary components. The latter should be used to combine
logical and statistical results in one system, as stated in [30]. ...
[PDF] Real-Time Knowledge Map Services on National R&D Data
KR
Shon, CJ Chae, HJ Jeong, CS Lim - DATA ANALYTICS 2016, 2016
... National
Digital Science Library (NDSL),” URL http://www.
ndsl. kr/ [5] R. Kimball and R. Margy,“The data warehouse
toolkit: the complete guide to dimensional modeling,” John Wiley & Sons,
2011. 44 Copyright (c) IARIA, 2016. ISBN: 978-1-61208-510-4 DATA ANALYTICS 2016 ...
[PDF] Data analytics 2016: proceedings of the fifth
international conference on data analytics
... Processing of
terabytes to petabytes of data, or incorporating
non-structural data and multi-structured data sources
and types require advanced analytics and data science
mechanisms for both raw and partially-processed information. ...
Traffic-aware Geo-distributed Big Data Analytics with
Predictable Job Completion Time
P
Li, S Guo, T
... With this design, a
widely adopted approach for geo-distributed big data analytics is
to first aggregate all data to a single • P. Li, S.Guo, and T.
Miyazaki are with the School of Computer Science and
Engineering, The University of Aizu, Japan. ...
Digital product assurance for model-based open manufacturing of
small satellites
C
Runge, K Lynch, R Ramsey, T Pauline - … and Innovative Business Practices for
the …, 2016
... Analytics are
displayed on the OMIS console along with system health, workflow status, and
alerts of conditions requiring human decision or action. This extensive
automated surveillance of ... Data science is
employed for post-production analysis of the volumes of collected data. ...