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JCR Impact Factor: 0.699
JCR 5-Year IF: 0.674
Issues per year: 4
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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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Clarivate Analytics published the InCites Journal Citations Report for 2017. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.699, and the JCR 5-Year Impact Factor is 0.674.

Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

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  4/2017 - 3

Mobile@Old: A Smart Home Platform for Enhancing the Elderly Mobility

MOCANU, I. See more information about MOCANU, I. on SCOPUS See more information about MOCANU, I. on IEEExplore See more information about MOCANU, I. on Web of Science, SCHPOR, O.-A. See more information about  SCHPOR, O.-A. on SCOPUS See more information about  SCHPOR, O.-A. on SCOPUS See more information about SCHPOR, O.-A. on Web of Science, CRAMARIUC, B. See more information about  CRAMARIUC, B. on SCOPUS See more information about  CRAMARIUC, B. on SCOPUS See more information about CRAMARIUC, B. on Web of Science, RUSU, L. See more information about RUSU, L. on SCOPUS See more information about RUSU, L. on SCOPUS See more information about RUSU, L. on Web of Science
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (1,637 KB) | Citation | Downloads: 335 | Views: 590

Author keywords
smart homes, gesture recognition, health information management, knowledge engineering, affective computing

References keywords
elderly(13), health(9), physical(8), link(8), games(8), activity(7), game(6), exercise(6), system(5), older(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2017-11-30
Volume 17, Issue 4, Year 2017, On page(s): 19 - 26
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2017.04003
Web of Science Accession Number: 000417674300003
SCOPUS ID: 85035752682

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Regular physical exercises are widely considered to be a key factor for living a healthy life. In this paper we present Mobile@Old, an integrated platform for assisting elderly people to maintain a healthy lifestyle in their homes. Our aim is to highlight the main concepts, technologies, and findings this system rests on. To this end we integrate Mobile@Old in the general conceptual framework of serious games. We provide details about the designing and implementation of Vital Signs Monitoring (VSM) and Physical Activity Trainer (PAT) components of Mobile@Old. Relevant exercises and utilization scenarios are also presented in order to emphases the practical applicability of our approach. We evaluate the usability of platform using the System Usability Scale (SUS). Experimental data regarding the accuracy of whole body movements are also presented

References | Cited By  «-- Click to see who has cited this paper

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References Weight

Web of Science® Citations for all references: 753 TCR
SCOPUS® Citations for all references: 1,311 TCR

Web of Science® Average Citations per reference: 17 ACR
SCOPUS® Average Citations per reference: 29 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2018-10-21 03:08 in 179 seconds.

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