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Deep Reinforcement Learning: Framework, Applications, and Embedded Implementations [article]

Hongjia Li, Tianshu Wei, Ao Ren, Qi Zhu, Yanzhi Wang
2017 arXiv   pre-print
) 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

Manjunatha S, Annappa B
2020 Scalable Computing : Practice and Experience  
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

Yaxiong Zhao, Jie Wu, Cong Liu
2014 Tsinghua Science and Technology  
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

Mdoe Mwamnyange, Edith Luhanga, Sanket R.
2021 International Journal of Advanced Computer Science and Applications  
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

B. Dennis, S. Kocherlakota, A. Sawant, L. Tateosian, C.G. Healey
2005 IEEE Computer Graphics and Applications  
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

Jeong-Sig Kim, Eung-Sung Kim, Jin-Hong Kim
2016 International Journal of Software Engineering and Its Applications  
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

Hongjia Li, Tianshu Wei, Ao Ren, Qi Zhu, Yanzhi Wang
2017 2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)  
) 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

Osama Islam, Ahmed Alfakeeh, Farrukh Nadeem
2017 International Journal of Computer Networks And Applications  
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

Jiefei Ma, Franck Le, Alessandra Russo, Jorge Lobo
2016 IEEE Transactions on Knowledge and Data Engineering  
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

Raviya K, Mary Vennila S
2021 International Journal of Advanced Computer Science and Applications  
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

Francesca Calabrese, Alberto Regattieri, Marco Bortolini, Mauro Gamberi, Francesco Pilati
2021 Applied Sciences  
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

Jinwon Lee, Seungwoo Kang, Youngki Lee, Sang Jeong Lee, Junehwa Song
2009 IEEE Transactions on Knowledge and Data Engineering  
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

Emad A Mohammed, Behrouz H Far, Christopher Naugler
2014 BioData Mining  
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

Xiaoyu Zhang, Denis Gracanin
2011 Proceedings of the 2011 Winter Simulation Conference (WSC)  
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

Maria Carla Calzarossa, Marco L. Della Vedova, Daniele Tessera
2019 Future generations computer systems  
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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