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Real Analytic Machines and Degrees

Tobias Gärtner, Martin Ziegler, Ning Zhong
2011 Logical Methods in Computer Science  
of three models of analytic computation: BSS machines (aka real-RAM) and strongly/weakly analytic machines as introduced by Hotz et. al. (1995).  ...  We study and compare in two degree-theoretic ways (iterated Halting oracles analogous to Kleene's arithmetical hierarchy and the Borel hierarchy of descriptive set theory) the capabilities and limitations  ...  Oracle Computation and Turing Degrees.  ... 
doi:10.2168/lmcs-7(3:11)2011 fatcat:ixlf4wy435gpjpxbzhpojy2q7m

Guest Editorial: Special Issue on Data Analytics and Machine Learning for Network and Service Management—Part II

Nur Zincir-Heywood, Giuliano Casale, David Carrera, Lydia Y. Chen, Amogh Dhamdhere, Takeru Inoue, Hanan Lutfiyya, Taghrid Samak
2021 IEEE Transactions on Network and Service Management  
Analytics and Machine Learning for Service Management, and (iii) Advanced Security Management based on Data Analytics and Machine Learning. 13) L.  ...  Data Analytics and Machine Learning for Network Management Ten papers in this special issue focus on data analytics and machine learning for management of networks.  ... 
doi:10.1109/tnsm.2021.3058742 fatcat:b6lx4i75krcovcqereinvjf6mu

Guest Editorial: Special Section on Data Analytics and Machine Learning for Network and Service Management–Part I

Nur Zincir-Heywood, Giuliano Casale, David Carrera, Lydia Y. Chen, Amogh Dhamdhere, Takeru Inoue, Hanan Lutfiyya, Taghrid Samak
2020 IEEE Transactions on Network and Service Management  
, (ii) Data Analytics and Machine Learning for Service Management, (iii) Data Analytics and Machine Learning for Mobile Networks, and (iv) Data Analytics and Machine Learning for Social Network Platforms  ...  Data Analytics and Machine Learning for Service Management Three papers in this special section focus on data analytics and machine learning for management of services.  ... 
doi:10.1109/tnsm.2020.3038736 fatcat:fg3hi7r5vjgpxgamnuq3itgbd4

Real-Time Big Data Analytics Pipeline

2018 Zenodo  
MATERIALS AND METHODS: The major constituents of the real-time big data analytics pipeline is as follows: • Data collection and extraction • Distribution of data to various nodes for further processing  ...  . • Analytic processing, to derive inferences from data, including the application of machine learning. • Data storage system for storing results and related information. • Interfaces or consumption of  ... 
doi:10.5281/zenodo.1185040 fatcat:ytqxcc2ztbatlbn7vvu4w5jrje

Real-Time Big Data Analytics Pipeline

2018 Zenodo  
The need of the hour is having an efficient, automated, centralized and real-time big data analytics pipeline which can derive insights from data and help businesses.  ...  Aim Considering the huge volume and the incredible rate at which data is being collected,having an efficient, automated, centralized and real-time big data analytics pipeline that should have the capability  ... 
doi:10.5281/zenodo.1184838 fatcat:vj2b57fr5re7lmafnaghpmfpay


2019 Issues in Information Systems  
Real-Time Streaming, Applied Data Analytics, Advanced Data Visualization Applications, Applied Big Data Analytics, and a Capstone Project.  ...  creating batch and real-time data processing pipelines, doing machine learning at scale, -deploying machine learning models into a production environment Join some of best Skills gained: Apache Hadoop  ... 
doi:10.48009/1_iis_2019_157-167 fatcat:hyti4qupbrcfxezge7bf7st5ly

On Perfect Completeness for QMA [article]

Scott Aaronson
2008 arXiv   pre-print
This note helps to explain why the problem is difficult, by using ideas from real analysis to give a "quantum oracle" relative to which they are different.  ...  Acknowledgments I thank Andy Drucker and the anonymous reviewers for helpful comments, and Greg Kuperberg and Dave Xiao for discussions of related problems several years ago.  ...  Combining these facts, we find that each b j (θ) is a real analytic function of θ (for note that cos θ and sin θ are real analytic functions, and real analytic functions are closed under composition).  ... 
arXiv:0806.0450v3 fatcat:nzvvtinisjafxm4owfuepbfeiq

Using Machine Learning Approach for Computational Substructure in Real-Time Hybrid Simulation [article]

Elif Ecem Bas, Mohamed A. Moustafa, David Feil-Seifer, Janelle Blankenburg
2020 arXiv   pre-print
Two different machine learning algorithms are evaluated to provide a valid and useful metamodeling solution for analytical substructure.  ...  One challenge for fast HS or real-time HS (RTHS) is associated with the analytical substructures of relatively complex structures, which could have large number of degrees of freedoms (DOFs), for instance  ...  machine (Speedgoat xPC Target); (4) Windows machine (Host PC) for MATLAB, OpenSees, and the HS middleware OpenFresco [19] ; and (5) SCRAMNet ring that provides shared memory locations for real-time communication  ... 
arXiv:2004.02037v1 fatcat:5hfiah4jvzctnjq632qnecgmki

Performance evaluation and comparison of multi-objective optimization algorithms for the analytical design of switched reluctance machines

Shen Zhang, Sufei Li, Ronald G. Harley, Thomas G. Habetler
2017 China Electrotechnical Society Transactions on Electrical Machines and Systems  
This paper systematically evaluates and compares three well-engineered and popular multi-objective optimization algorithms for the design of switched reluctance machines.  ...  The multi-physics and multi-objective nature of electric machine design problems are discussed, followed by benchmark studies comparing generic algorithms (GA), differential evolution (DE) algorithms and  ...  Sufei Li (S'15) received the B.S. degree in electrical engineering from Shanghai Jiao Tong University, Shanghai, China, in 2011, and the dual M.S. degree in electrical and computer engineering from Shanghai  ... 
doi:10.23919/tems.2017.7911109 fatcat:bz4c54f7lrgape4ntij6rd5idy

Editorial: Special issue on natural language processing and text analytics in industry

Ashwin Ittoo, Le Minh Nguyen, Antal van den Bosch
2016 Computers in industry (Print)  
From this review, the authors identify the challenges and constraints that real-world environments impose on text analytics applications, and subsequently, identify a set of desiderata that text analytics  ...  Natural Language Processing (NLP) and Text Analytics (TA) algorithms and techniques are increasingly being developed, adopted and deployed for addressing a wide spectrum of real-life, industrial problems  ... 
doi:10.1016/j.compind.2016.01.001 fatcat:tvvrmcqztvf55hjwlke7bx2wdq

Big Data Knowledge Discovery Platforms: A 360 Degree Perspective

2019 International Journal of Engineering and Advanced Technology  
These platforms and architecture are giving a cutting edge to the Big Data Knowledge Discovery process by using Artificial Intelligence, Machine Learning and Expert systems.  ...  New analytical techniques and high performance computing architecture came into picture to handle this explosion.  ...  Real time and near-real time data assimilation, modeling, optimization and visualization is another core area to deal with. B.  ... 
doi:10.35940/ijeat.b3901.129219 fatcat:2w7a5tkmsfah7oft4jacfbzdau

Enterprise Scale Artificial Intelligence Achieving Value In Your Organization Today

Sumeet Pelia
2018 Zenodo  
Director in PwC's Data Analytics practice, Canada  ...  •Machine Learning/ Digital Customer Experience Transformation Program -Large Fortune 500 US-based Airline Company: Recommended and aligned with senior management on strategy for real-time engagement with  ...  Led creation of customer profile and contextual data set that would be used for real time decisions.  ... 
doi:10.5281/zenodo.1185238 fatcat:ruvmkjulorchddfqceat2ugcua

REDTag: A Predictive Maintenance Framework for Parcel Delivery Services

Stefano Proto, Evelina Di Corso, Daniele Apiletti, Luca Cagliero, Tania Cerquitelli, Giovanni Malnati, Davide Mazzucchi
2020 IEEE Access  
INDEX TERMS Big data analytics, Industry 4.0, intelligent transports and logistics, Internet of Things, machine learning, predictive maintenance.  ...  The framework provides back-end functionalities for smart data transmission, management, storage, and analytics.  ...  Section V thoroughly describes the data analytics and mining steps. Section VI shows the experimental results achieved in a real scenario.  ... 
doi:10.1109/access.2020.2966568 fatcat:iqgmfzarujetxfuxkpdoupxql4

An Application of Predictive Analytics in Manufacturing Sector for Price Prediction and Demand Prediction

We have trained and tested different machine learning algorithms that can be used to predict price as well as demand of a particular product using historical data about that product's sales and other transactions  ...  Hence, it's feasible to increase manufacturing quality, and expect needs throughout the factory with predictive analytics.  ...  INTRODUCTION Predictive analytics includes different mathematical and statistical techniques from machine learning and data mining that analyze historical and real-time data to determine the pattern and  ... 
doi:10.35940/ijitee.h6465.079920 fatcat:2sjoc77vevbwhd7ybh3jvtlzdq

Data Science & Big Data Analytics

Mohamed Ali SOLA
2018 Zenodo  
Unlocking the power of natural language by machine translation: hot technologies and business benefits  ...  Dali had an engineer degree from at TEK-UP university in Tunisia and studied two Master degree in Business Intelligence and Innovation management from an international program called " Dicamp " at 3 universities  ...  As Content and topics change, and always will, Machine Translation engines and NLP tools can keep up with change using rapid adaptation approaches that learn continuously in near-real time.  ... 
doi:10.5281/zenodo.1229047 fatcat:45sq5536bnbnbfugd6d2biewue
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