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Deep Reinforcement Learning: Framework, Applications, and Embedded Implementations
[article]
2017
arXiv
pre-print
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) an online deep Q-learning phase, which adaptively derives the optimal action and updates value estimates. ...
In this paper, we first present the general DRL framework, which can be widely utilized in many applications with different optimization objectives. ...
ACKNOWLEDGEMENTS This work was supported in part by the National Science Foundation under grants CCF-1553757, CCF-1646381, CNS-1739748 and CNS-1704662, CASE Center at Syracuse University, and Riverside ...
arXiv:1710.03792v1
fatcat:kfhlh62sgjd4nkevry4rmxoqdy
Real-time Big Data Analytics Framework with Data Blending Approach for Multiple Data sources in Smart City Applications
2020
Scalable Computing : Practice and Experience
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This paper discusses the proposed real-time big data analytics framework with data blending approach using multiple data sources for smart city applications. ...
Data analytics plays a vital role in many such data-driven applications. ...
The authors would like to thank Ministry of Electronics and Information Technology (MeitY), Government of India, for their support in a part of the research. ...
doi:10.12694/scpe.v21i4.1759
fatcat:pqravn55q5g65i5jilfev3kaje
Dache: A data aware caching for big-data applications using the MapReduce framework
2014
Tsinghua Science and Technology
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Google's MapReduce and Apache's Hadoop, its open-source implementation, are the defacto software systems for big-data applications. ...
In this paper, we propose Dache, a data-aware cache framework for big-data applications. In Dache, tasks submit their intermediate results to the cache manager. ...
ECCS 1128209, CNS 1138963, CNS 1065444, and CCF 1028167). ...
doi:10.1109/tst.2014.6733207
fatcat:734utgkqi5gw5jp5abk4ad7maq
Big Data Analytics Framework for Childhood Infectious Disease Surveillance and Response System using Modified MapReduce Algorithm
2021
International Journal of Advanced Computer Science and Applications
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In this paper, the development of the Big Data Analytics Framework for Childhood Infectious Disease Surveillance and Response System is presented. ...
The framework was designed to guide healthcare professionals to track, monitor, and analyze infectious disease report cases from sources such as social media for prevention and control of infectious diseases ...
May 20, 2010, using Twitter's streaming application programmer's interface (API). ...
doi:10.14569/ijacsa.2021.0120345
fatcat:cixb7xkvvvh5pl3iqwk62hn4o4
Designing a Visualization Framework for Multidimensional Data
2005
IEEE Computer Graphics and Applications
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Acknowledgment This work is funded in part by the National Science Foundation grants IIS-9988507, ACI-0083421, and ACI-0092308. ...
The first two constraints represent application-independent input about the data and the viewer's analysis needs. ...
The use of perceptual rules at various stages of the framework is particularly helpful for presenting large amounts of data in ways that support rapid and accurate comprehension. ...
doi:10.1109/mcg.2005.128
pmid:16315471
fatcat:2tebj4iejjhk5dbnmnzm4ia6wu
Towards Conceptual Predictive Modeling for Big Data Framework
2016
International Journal of Software Engineering and Its Applications
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This competitive approach is interesting and seems fruitful, but one could ask if the framework provided by for example Gane Project based on big data framework gives a trustworthy resemblance of real-world ...
We will then describe a conceptual big data framework for approaching predictive modeling problems. ...
We have to describe more applicable methodologies for predictive modeling, we outlined a conceptual framework. ...
doi:10.14257/ijseia.2016.10.1.04
fatcat:dx7ckjmbebeahk6oes4ytsp2a4
Deep reinforcement learning: Framework, applications, and embedded implementations: Invited paper
2017
2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)
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) an online deep Qlearning phase, which adaptively derives the optimal action and updates value estimates. ...
In this paper, we first present the general DRL framework, which can be widely utilized in many applications with different optimization objectives. ...
ACKNOWLEDGEMENTS This work was supported in part by the National Science Foundation under grants CCF-1553757, CCF-1646381, CNS-1739748 and CNS-1704662, CASE Center at Syracuse University, and Riverside ...
doi:10.1109/iccad.2017.8203866
dblp:conf/iccad/LiWRZW17
fatcat:t4kgm4ky4je25b3lo4ibrjxbj4
A Framework for Effective Big data Analytics for Decision Support Systems
2017
International Journal of Computer Networks And Applications
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Therefore, with the advent of improved analytical methods for Big data sources new opportunities have emerged that can possibly enhance how decision makers analyze their problem and arrive at decisions ...
Finally, the paper proposes a framework that integrates the key components needed to ensure the quality and relevance of data being analyzed by decision support systems while providing the benefits of ...
and applications. ...
doi:10.22247/ijcna/2017/49227
fatcat:cjylpx4vszhbdeicnwts6ofe4m
Declarative Framework for Specification, Simulation and Analysis of Distributed Applications
2016
IEEE Transactions on Knowledge and Data Engineering
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In this paper we present a declarative framework for the specification, execution, simulation and analysis of distributed applications. ...
a distributed algorithm for pattern formation in multi-robot systems. ...
are generated and stored, data streams between nodes and table updates. ...
doi:10.1109/tkde.2016.2515604
fatcat:ci6nugh64ncxdjsylzberel6bq
An Implementation of Hybrid Enhanced Sentiment Analysis System using Spark ML Pipeline: A Big Data Analytics Framework
2021
International Journal of Advanced Computer Science and Applications
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The advancement in fields including Big Data and Deep Learning technology has influenced and overcome the traditional restrictions of distributed computing. ...
Today, we live in the Big Data age. Social networks, online shopping, mobile data are main sources generating huge text data by users. ...
It has been one of the main frameworks in the world for largescale data processing and analytics, achieving high efficiency for both batch and stream data. ...
doi:10.14569/ijacsa.2021.0120540
fatcat:m2v4jx7lmbhqnpmznqik7fmw4e
Predictive Maintenance: A Novel Framework for a Data-Driven, Semi-Supervised, and Partially Online Prognostic Health Management Application in Industries
2021
Applied Sciences
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data streams, a case study is presented. ...
In these cases, most applications rely on a large amount of historical data to train models for diagnostic and prognostic purposes. Industries, very often, are not able to obtain these data. ...
In Section 3, a novel framework and architecture for semisupervised and partially online PHM applications are introduced. ...
doi:10.3390/app11083380
fatcat:3s7bstt4mjforexdt4uzjfg3g4
BMQ-Processor: A High-Performance Border-Crossing Event Detection Framework for Large-Scale Monitoring Applications
2009
IEEE Transactions on Knowledge and Data Engineering
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In this paper, we present BMQ-Processor, a high performance border-crossing event detection framework for largescale monitoring applications. ...
It monitors the values of data streams and reports them only when data streams cross the borders of its range. ...
Locality of Data Streams We expect that data streams change gradually in many practical situations. In this appendix, we examine the locality of data streams with real data traces. ...
doi:10.1109/tkde.2008.140
fatcat:hh77s373hbdofe3vubgjcbitei
Applications of the MapReduce programming framework to clinical big data analysis: current landscape and future trends
2014
BioData Mining
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Data are stored in the HDFS and made available to the slave nodes for computation. ...
In this paper, we review the existing applications of the MapReduce programming framework and its implementation platform Hadoop in clinical big data and related medical health informatics fields. ...
Streamed data home monitoring, tele-health, handheld and sensor-based wireless are well established data sources for clinical data.
4-Social media analytics applications. ...
doi:10.1186/1756-0381-7-22
pmid:25383096
pmcid:PMC4224309
fatcat:zpis7kklerh2vna5le2gtxc5vi
Comparison of the experimental and simulation results for Distributed Virtual Environments applications framework
2011
Proceedings of the 2011 Winter Simulation Conference (WSC)
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In our previous work we developed Caffe Neve framework that allows application developers to create flexible and extensible Distributed Virtual Environments (DVEs) applications from the distributed components ...
We use various metrics such as the response latency and service load estimation to evaluate the framework performance. ...
We propose our framework Caffe Neve Gracanin 2008, Zhang and Gračanin 2008) as the standard approach for integrating distributed 3D resources to create flexible and extensible online 3D applications. ...
doi:10.1109/wsc.2011.6148021
dblp:conf/wsc/ZhangG11
fatcat:ifdqgsgkzngxdgtmfic2guu6bq
A methodological framework for cloud resource provisioning and scheduling of data parallel applications under uncertainty
2019
Future generations computer systems
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To test our framework, we consider data parallel applications characterized by a deadline constraint and we investigate the impact of their characteristics and of the variability of the cloud infrastructure ...
This framework allows cloud users to estimate in advance, i.e., prior to the actual execution of the applications, the resource settings that cope with uncertainty. ...
Acknowledgements The authors would like to thank the anonymous referees for their valuable comments and suggestions that improved the overall quality and clarity of the manuscript. ...
doi:10.1016/j.future.2018.10.037
fatcat:rxsdwai6mva45jfzlo5qc5pha4
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