Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Seyed Amir Hoseinitabatabaei"'
Publikováno v:
ACM Transactions on the Web. 14:1-28
This article proposes a novel approach for enhancing the video popularity prediction models. Using the proposed approach, we enhance three popularity prediction techniques that outperform the accuracy of the prior state-of-the-art solutions. The majo
When dealing with a large number of devices, the existing indexing solutions for the discovery of Internet of Things (IoT) sources often fall short to provide an adequate scalability. This is due to the high computational complexity and communication
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9b61183b469d10b28eb08fe1390977b4
https://surrey.eprints-hosting.org/846112/
https://surrey.eprints-hosting.org/846112/
Autor:
Ann Ashburn, Emma Stack, Malcolm Burnett, William S. Harwin, Seyed Amir Hoseinitabatabaei, Fatemeh Tahavori, Veena Agarwal
Publikováno v:
2017 International Smart Cities Conference (ISC2).
Physical activity recognition plays a vital role in the application of wearable sensors in healthcare. This paper explores the capability of machine learning algorithms to recognise activities of healthy elderly adults and people with Parkinson's (Pw
Publikováno v:
iThings/GreenCom/CPSCom/SmartData
This work proposes a pattern identification and online prediction algorithm for processing Internet of Things (IoT) time-series data. This is achieved by first proposing a new data aggregation and data driven discretisation method that does not requi
Autor:
S. Shariat, Seiamak Vahid, M. Hasanpour, Payam Barnaghi, Seyed Amir Hoseinitabatabaei, Rahim Tafazolli
Publikováno v:
Quantum Information Processing. 16
This paper presents a novel approach in targeting load balancing in ad hoc networks utilizing the properties of quantum game theory. This approach benefits from the instantaneous and information-less capability of entangled particles to synchronize t
Publikováno v:
IEEE Transactions on Mobile Computing. 13:1981-1994
A novel method for a mobile phone centric observation of a user’s facing direction is presented. To estimate this direction, our proposed technique exploits the acceleration pattern that can be measured by a smartphone as the user is walking. For a
Autor:
Oluwakayode Onireti, Ali Imran, Muhammad Imran, Rahim Tafazolli, Seyed Amir Hoseinitabatabaei, Abdelrahim Mohamed
Publikováno v:
ICC
In research community, a new radio access network architecture with a logical separation between control plane (CP) and data plane (DP) has been proposed for future cellular systems. It aims to overcome limitations of the conventional architecture by
The ever-growing computation and storage capability of mobile phones have given rise to mobile-centric context recognition systems, which are able to sense and analyze the context of the carrier so as to provide an appropriate level of service. As no
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f0078725df14aeb2b549b1f64d9a3c8b
https://surrey.eprints-hosting.org/805515/
https://surrey.eprints-hosting.org/805515/
Publikováno v:
PerCom
In this paper we present the uDirect algorithm as a novel approach for mobile phone centric observation of a user's facing direction, through which the device and user orientations relative to earth coordinate are estimated. While the device orientat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4ef9d000546ddbbb5e23b8ef262d8baa
https://surrey.eprints-hosting.org/805514/
https://surrey.eprints-hosting.org/805514/
Autor:
Alexander Gluhak, Michele Nati, Niklas Palaghias, Seyed Amir Hoseinitabatabaei, Klaus Moessner
Publikováno v:
ACM Computing Surveys
Understanding human behavior in an automatic but nonintrusive manner is an important area for various applications. This requires the collaboration of information technology with human sciences to transfer existing knowledge of human behavior into se