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Empowering automatic data-center management with machine learning

Josep Ll. Berral, Ricard Gavaldà, Jordi Torres
2013 Proceedings of the 28th Annual ACM Symposium on Applied Computing - SAC '13  
Here we show how a combination of scheduling algorithms and data mining techniques helps improving the performance and profitability of a data-center running virtualized web-services.  ...  Managing and optimizing its performance on a moment-by-moment basis is not easy given as the amount and diversity of elements involved (hardware, applications, workloads, customer needs. . . ).  ...  CONCLUSIONS In this work we presented a methodology for modeling cloud computing resources of a web-service based data-center using machine learning, obtaining good predictors to empower and drive decision-making  ... 
doi:10.1145/2480362.2480397 dblp:conf/sac/BerralGT13 fatcat:mlfhezgapzf2rimaaykzmvqvri

Guest Editorial: AI-Empowered Mobile Edge Computing in the Internet of Vehicles

Jun Huang, Jalel Ben Othman, Shiqiang Wang, Ricky Y. K. Kwok, Victor C. M. Leung, Wei Sun
2021 IEEE Network  
So far AI-empowered MEC in IoVs mainly depends on a centralized approach, because an AI management center is required to collect the information and react according to the environment.  ...  The article "Machine-Learning-Enabled Cooperative Perception for Connected Autonomous Vehicles: Challenges and Opportunities" presents the research challenges and opportunities in machine-learning-enabled  ...  So far AI-empowered MEC in IoVs mainly depends on a centralized approach, because an AI management center is required to collect the information and react according to the environment.  ... 
doi:10.1109/mnet.2021.9454596 fatcat:b5o6zzcdirfr3lwews6eziyoqe

Facts4Workers: Worker Centric Workplaces In Smart Factories

Dörthe Arndt, Joachim Van Herwegen, Ruben Verborgh, Erik Mannens, Rik Van De Walle
2015 Zenodo  
Factories of the future will autonomously deal with the ever increasing amount of available data. Processes will be planned automatically.  ...  Computers will keep track of machine parameters, product quality and workforce activities.  ...  The Facts4Workers Project Factories of the future will autonomously deal with the ever increasing amount of available data. Processes will be planned automatically.  ... 
doi:10.5281/zenodo.825405 fatcat:a4hmdeoxv5blfghpju4wkcbvfi

Artificial Intelligence-Enabled Intelligent 6G Networks [article]

Helin Yang, Arokiaswami Alphones, Zehui Xiong, Dusit Niyato, Jun Zhao, Kaishun Wu
2019 arXiv   pre-print
Therefore, this article proposes an AI-enabled intelligent architecture for 6G networks to realize knowledge discovery, smart resource management, automatic network adjustment and intelligent service provisioning  ...  mobile edge computing, intelligent mobility and handover management, and smart spectrum management.  ...  Such function is realized by applying AI techniques in 6G networks, where each agent is equipped with an intelligent brain (learning model) to automatically learn to make decisions by itself.  ... 
arXiv:1912.05744v1 fatcat:guqihjrkxbezpa7dno7twecoda

Table of Contents

2021 2021 International Conference on Artificial Intelligence and Computer Science Technology (ICAICST)  
M O P R S T Y Random Forest For Hijab Style Selection Based on Face Shape Using Morphological Facial Index risk management system for operational services in Data Center (DC Papa Oscar Cikeas case study  ...  Fraud Detection Machine Learning Approach to Predict SGPA and CGPA Method Comparison for Increasing Data Rate on 5G-IoT Technology Modelling MIMO Transfer Functions for Analysis of The Relationship Between  ... 
doi:10.1109/icaicst53116.2021.9497821 fatcat:6zwpqogtmzgyhfc3bfppzqpsgu

A Preface to the Special Issue on Emerging and Intelligent Information Services

Maozhen Li, Zhijun Ding
2020 Computing and informatics  
He et al. [2] employed a stochastic Petri net to model resource scheduling in cloud data centers with an aim to improve energy efficiency.  ...  Information services have evolved from centralized monolithic systems to distributed and intelligent systems especially empowered with the emerging technologies such as big data, artificial intelligence  ...  [2] employed a stochastic Petri net to model resource scheduling in cloud data centers with an aim to improve energy efficiency.  ... 
doi:10.31577/cai_2020_1-2_1 fatcat:76usud75gvg73mfqtuii2dfoou

Getting Smart

Detelina Marinova, Ko de Ruyter, Ming-Hui Huang, Matthew L. Meuter, Goutam Challagalla
2016 Journal of Service Research  
Moreover, faced with technology-empowered  ...  In turn, health care professionals can make better decisions, and patients can learn how to combat illness and manage their personal health.  ...  Such outcomes rely on advances in unsupervised (i.e., performed by the machine automatically, with no human intervention), supervised (performed by the machine using input from humans), and semisupervised  ... 
doi:10.1177/1094670516679273 fatcat:bozw66tugze3leagpk5qtyorki

Utilizing machine learning techniques to process customer claims automatically

S. Sader
2019 Hungarian Agricultural Engineering  
Supervised machine learning was used with accurate data in order to develop a machine learning model.  ...  The goal of this experiment was to show evidence on the ability of new technologies such as Machine Learning to automate quality management traditional activities, improve efficiency and effectiveness,  ...  Robert Csombordi, Head of Quality Management, for their endless support in conducting this research work.  ... 
doi:10.17676/hae.2019.36.15 fatcat:szbwu2hdbvfwzl4beia5ryexsm

Guest Editorial for "Artificial Intelligence for Cognitive Wireless Communications"

Kai Hwang, Min Chen, Hamid Gharavi, Victor C M Leung
2019 IEEE wireless communications  
, advanced wireless signal processing based on deep learning, optimized wireless communication physical layer design based on reinforcement learning, adaptive wireless resource management based on cognitive  ...  Furthermore, wireless communication and network ecosystems have to be upgraded with new capabilities, such as the provisioning of personalized and smart 5G network services assisted by data cognitive intelligence  ...  The DRL empowered edge resource management and optimization mechanism is an elegant breakthrough to deal with the conflict between heterogeneous requirements of on-vehicle applications and the complexity  ... 
pmid:31579263 pmcid:PMC6774379 fatcat:43co5nivn5binkgrg5gewhjb3u

Big Data Systems Meet Machine Learning Challenges: Towards Big Data Science as a Service [article]

Radwa Elshawi, Sherif Sakr
2017 arXiv   pre-print
, analyze and understand this data.  ...  We analyze in details the building blocks of the software stack for supporting big data science as a commodity service for data scientists.  ...  It is designed to manage all data movement, data persistence, and machine-learning related optimizations automatically.  ... 
arXiv:1709.07493v1 fatcat:ja7rrbfk7vhnpjvqadlr5vvhyy

Hybrid Approach to Automation, RPA and Machine Learning: a Method for the Human-centered Design of Software Robots [article]

Wiesław Kopeć, Marcin Skibiński, Cezary Biele, Kinga Skorupska, Dominika Tkaczyk, Anna Jaskulska, Katarzyna Abramczuk, Piotr Gago, Krzysztof Marasek
2018 arXiv   pre-print
learning processes with the use of tailored high-level RPA Domain Specific Languages (DSLs) to adjust the functioning of the robots and maintain operational flexibility.  ...  To achieve these goals we propose a hybrid, human-centered approach to the development of software robots.  ...  Distributed and Crowdsourced Machine Learning Approach This postulate coresponds with the novel interactive and collaborative apprach to machine learning [8] .  ... 
arXiv:1811.02213v1 fatcat:s2mdh4zkcvaxhoi3pyxjxgskau

Preface to the Special Issue on Artificial Intelligence for Business Process Management 2019

Fabrizio Maria Maggi, Andrea Marrella
2021 Journal on Data Semantics  
We are at the beginning of a profound transformation of Business Process Management (BPM) due to advances in Artificial Intelligence (AI) and Machine Learning (ML).  ...  applied to Read-Write Linked Data The paper "AI-empowered Process Mining for Complex Application Scenarios: Survey and Discussion," authored by Pontieri et al., investigates how classical process mining  ... 
doi:10.1007/s13740-021-00131-0 fatcat:d4ja7bbnfnduljkrtv3kgkqcvm

A Self-Configurable Edge Computing for Industrial IoT

2019 International Journal of Engineering and Advanced Technology  
Therefore, with the rapid development of IIoT technology, the proposed work incorporates with Edge Computing (EC).  ...  The current manufacturing process and automation, computing and wireless network reaches out to headways in innovation from easy to the point where all things (devices) and machines can interface through  ...  The data center networks are connecting through internal edge network, this model empowers less computation and unpredictable storage at the edge hubs.  ... 
doi:10.35940/ijeat.b3868.129219 fatcat:5ex4ldpjrndmbihdr2tn2ikc4q

Empowering Things with Intelligence: A Survey of the Progress, Challenges, and Opportunities in Artificial Intelligence of Things [article]

Jing Zhang, Dacheng Tao
2020 arXiv   pre-print
In the Internet of Things (IoT) era, billions of sensors and devices collect and process data from the environment, transmit them to cloud centers, and receive feedback via the internet for connectivity  ...  This paper presents a comprehensive survey on AIoT to show how AI can empower the IoT to make it faster, smarter, greener, and safer.  ...  Data mining and machine learning approaches have been used for IoT data processing and analysis [52] , [53] .  ... 
arXiv:2011.08612v1 fatcat:dflut2wdrjb4xojll34c7daol4

Human-centered artificial intelligence in education: seeing the invisible through the visible

Stephen J.H. Yang, Hiroaki Ogata, Tatsunori Matsui, Nian-Shing Chen
2021 Computers and Education: Artificial Intelligence  
Acknowledgments We would like to thank Academician Chao-Han Liu and Academician Wing-Huen Ip of the Academia Sinica, Taiwan, for their inspiration and leadership toward the achievement of human-centered  ...  Automatic evaluation of students' learning outcome with grading policy 5. Intelligent assessment and evaluation 6. Automatic question generation 7. Automatic grading 8.  ...  Learning technology must be human-centered because it involves teaching and interacting with people.  ... 
doi:10.1016/j.caeai.2021.100008 fatcat:cw6pt6ip4rea3fuqd45puft7xm
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