Identification and Classification of Processing Unit Eligibility for Ubiquitous Computing Using Feature Selection Mechanism and Artificial Neural Network

Patience Spencer; Enoch O. Nwachukwu

doi:doi:10.11648/j.wcmc.20160402.12

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Identification and Classification of Processing Unit Eligibility for Ubiquitous Computing Using Feature Selection Mechanism and Artificial Neural Network

Patience Spencer, Enoch O. Nwachukwu

Published in International Journal of Wireless Communications and Mobile Computing (Volume 4, Issue 2)

Received: 25 February 2016 Accepted: 11 March 2016 Published: 28 March 2016

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Abstract

Ubiquitous Computing is a trending innovation that allows a user to have access to many computers in a transparent manner anytime anywhere thereby enhancing computing confidence. However, the full potential of ubiquitous computing is not yet realised due to challenges including changing location of mobile users, poor network infrastructure, limited system resources, and poor transaction processing model. This work is concerned with the development of a proactive support for active transaction coordination in ubiquitous computing environment. The specific objectives are to identify relevant values of predefined key features of processing units that greatly impact on ubiquitous computing and to predict the processing capability of processing units using relevant values of the predefined features. An object-oriented analysis and system design methodology is employed and the proposed processing unit eligibility identification mechanism and neural network-based classifier is shown to effectively support ubiquitous computing.

Published in	International Journal of Wireless Communications and Mobile Computing (Volume 4, Issue 2)
DOI	10.11648/j.wcmc.20160402.12
Page(s)	18-24
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Ubiquitous Computing, Transaction, Multi-Layer Perceptrons, Neural Network, Feature Selection

References

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[6]	Silberschatz, A., Korth, H. F., Sudarshan, S. (2002) Database System Concepts McGraw Hill, New York.
[7]	Tang, F., and Li, M. (2012). Context- adaptive and energy-efficient mobile transaction management in pervasive environments. The Journal of Supercomputing, 60(1), 62- 86.
[8]	Silberschatz, A., Korth, H. F., and Sudarshan, S. (2006) Database System Concepts McGraw Hill, New York.
[9]	Beetz, M., Buss, M., and Wollherr, D. (2007). Cognitive technical systems—what is the role of artificial intelligence? In KI 2007: Advances in Artificial Intelligence (pp. 19-42). Springer Berlin Heidelberg.
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[11]	Rughani, A. I., Dumont, T. M., Lu, Z., Bongard, J., Horgan, M. A., Penar, P. L., and Tranmer, B. I. (2010). Use of an artificial neural network to predict head injury outcome: clinical article. Journal of neurosurgery, 113(3), 585-590.
[12]	Karlik, B., & Olgac, A. V. (2011). Performance analysis of various activation functions in generalized MLP architectures of neural networks. International Journal of Artificial Intelligence and Expert Systems, 1(4), 111-122.
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[14]	Schilit, B., Adams, N., & Want, R. (1994, December). Context-aware computing applications. In Mobile Computing Systems and plications, 1994. WMCSA 1994. First Workshop on (pp. 85-90). IEEE.

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APA Style

Patience Spencer, Enoch O. Nwachukwu. (2016). Identification and Classification of Processing Unit Eligibility for Ubiquitous Computing Using Feature Selection Mechanism and Artificial Neural Network. International Journal of Wireless Communications and Mobile Computing, 4(2), 18-24. https://doi.org/10.11648/j.wcmc.20160402.12

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ACS Style

Patience Spencer; Enoch O. Nwachukwu. Identification and Classification of Processing Unit Eligibility for Ubiquitous Computing Using Feature Selection Mechanism and Artificial Neural Network. Int. J. Wirel. Commun. Mobile Comput. 2016, 4(2), 18-24. doi: 10.11648/j.wcmc.20160402.12

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AMA Style

Patience Spencer, Enoch O. Nwachukwu. Identification and Classification of Processing Unit Eligibility for Ubiquitous Computing Using Feature Selection Mechanism and Artificial Neural Network. Int J Wirel Commun Mobile Comput. 2016;4(2):18-24. doi: 10.11648/j.wcmc.20160402.12

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@article{10.11648/j.wcmc.20160402.12,
  author = {Patience Spencer and Enoch O. Nwachukwu},
  title = {Identification and Classification of Processing Unit Eligibility for Ubiquitous Computing Using Feature Selection Mechanism and Artificial Neural Network},
  journal = {International Journal of Wireless Communications and Mobile Computing},
  volume = {4},
  number = {2},
  pages = {18-24},
  doi = {10.11648/j.wcmc.20160402.12},
  url = {https://doi.org/10.11648/j.wcmc.20160402.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.wcmc.20160402.12},
  abstract = {Ubiquitous Computing is a trending innovation that allows a user to have access to many computers in a transparent manner anytime anywhere thereby enhancing computing confidence. However, the full potential of ubiquitous computing is not yet realised due to challenges including changing location of mobile users, poor network infrastructure, limited system resources, and poor transaction processing model. This work is concerned with the development of a proactive support for active transaction coordination in ubiquitous computing environment. The specific objectives are to identify relevant values of predefined key features of processing units that greatly impact on ubiquitous computing and to predict the processing capability of processing units using relevant values of the predefined features. An object-oriented analysis and system design methodology is employed and the proposed processing unit eligibility identification mechanism and neural network-based classifier is shown to effectively support ubiquitous computing.},
 year = {2016}
}

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TY  - JOUR
T1  - Identification and Classification of Processing Unit Eligibility for Ubiquitous Computing Using Feature Selection Mechanism and Artificial Neural Network
AU  - Patience Spencer
AU  - Enoch O. Nwachukwu
Y1  - 2016/03/28
PY  - 2016
N1  - https://doi.org/10.11648/j.wcmc.20160402.12
DO  - 10.11648/j.wcmc.20160402.12
T2  - International Journal of Wireless Communications and Mobile Computing
JF  - International Journal of Wireless Communications and Mobile Computing
JO  - International Journal of Wireless Communications and Mobile Computing
SP  - 18
EP  - 24
PB  - Science Publishing Group
SN  - 2330-1015
UR  - https://doi.org/10.11648/j.wcmc.20160402.12
AB  - Ubiquitous Computing is a trending innovation that allows a user to have access to many computers in a transparent manner anytime anywhere thereby enhancing computing confidence. However, the full potential of ubiquitous computing is not yet realised due to challenges including changing location of mobile users, poor network infrastructure, limited system resources, and poor transaction processing model. This work is concerned with the development of a proactive support for active transaction coordination in ubiquitous computing environment. The specific objectives are to identify relevant values of predefined key features of processing units that greatly impact on ubiquitous computing and to predict the processing capability of processing units using relevant values of the predefined features. An object-oriented analysis and system design methodology is employed and the proposed processing unit eligibility identification mechanism and neural network-based classifier is shown to effectively support ubiquitous computing.
VL  - 4
IS  - 2
ER  -

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Author Information

Patience Spencer

Department of Computer Science, Ignatius Ajuru University of Education, Rumuolumeni, Rivers State, Nigeria
Enoch O. Nwachukwu

Department of Computer Science, Ignatius Ajuru University of Education, Rumuolumeni, Rivers State, Nigeria

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Plain Text BibTeX RIS

APA Style

Patience Spencer, Enoch O. Nwachukwu. (2016). Identification and Classification of Processing Unit Eligibility for Ubiquitous Computing Using Feature Selection Mechanism and Artificial Neural Network. International Journal of Wireless Communications and Mobile Computing, 4(2), 18-24. https://doi.org/10.11648/j.wcmc.20160402.12

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ACS Style

Patience Spencer; Enoch O. Nwachukwu. Identification and Classification of Processing Unit Eligibility for Ubiquitous Computing Using Feature Selection Mechanism and Artificial Neural Network. Int. J. Wirel. Commun. Mobile Comput. 2016, 4(2), 18-24. doi: 10.11648/j.wcmc.20160402.12

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AMA Style

Patience Spencer, Enoch O. Nwachukwu. Identification and Classification of Processing Unit Eligibility for Ubiquitous Computing Using Feature Selection Mechanism and Artificial Neural Network. Int J Wirel Commun Mobile Comput. 2016;4(2):18-24. doi: 10.11648/j.wcmc.20160402.12

Copy | Download

@article{10.11648/j.wcmc.20160402.12,
  author = {Patience Spencer and Enoch O. Nwachukwu},
  title = {Identification and Classification of Processing Unit Eligibility for Ubiquitous Computing Using Feature Selection Mechanism and Artificial Neural Network},
  journal = {International Journal of Wireless Communications and Mobile Computing},
  volume = {4},
  number = {2},
  pages = {18-24},
  doi = {10.11648/j.wcmc.20160402.12},
  url = {https://doi.org/10.11648/j.wcmc.20160402.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.wcmc.20160402.12},
  abstract = {Ubiquitous Computing is a trending innovation that allows a user to have access to many computers in a transparent manner anytime anywhere thereby enhancing computing confidence. However, the full potential of ubiquitous computing is not yet realised due to challenges including changing location of mobile users, poor network infrastructure, limited system resources, and poor transaction processing model. This work is concerned with the development of a proactive support for active transaction coordination in ubiquitous computing environment. The specific objectives are to identify relevant values of predefined key features of processing units that greatly impact on ubiquitous computing and to predict the processing capability of processing units using relevant values of the predefined features. An object-oriented analysis and system design methodology is employed and the proposed processing unit eligibility identification mechanism and neural network-based classifier is shown to effectively support ubiquitous computing.},
 year = {2016}
}

Copy | Download

TY  - JOUR
T1  - Identification and Classification of Processing Unit Eligibility for Ubiquitous Computing Using Feature Selection Mechanism and Artificial Neural Network
AU  - Patience Spencer
AU  - Enoch O. Nwachukwu
Y1  - 2016/03/28
PY  - 2016
N1  - https://doi.org/10.11648/j.wcmc.20160402.12
DO  - 10.11648/j.wcmc.20160402.12
T2  - International Journal of Wireless Communications and Mobile Computing
JF  - International Journal of Wireless Communications and Mobile Computing
JO  - International Journal of Wireless Communications and Mobile Computing
SP  - 18
EP  - 24
PB  - Science Publishing Group
SN  - 2330-1015
UR  - https://doi.org/10.11648/j.wcmc.20160402.12
AB  - Ubiquitous Computing is a trending innovation that allows a user to have access to many computers in a transparent manner anytime anywhere thereby enhancing computing confidence. However, the full potential of ubiquitous computing is not yet realised due to challenges including changing location of mobile users, poor network infrastructure, limited system resources, and poor transaction processing model. This work is concerned with the development of a proactive support for active transaction coordination in ubiquitous computing environment. The specific objectives are to identify relevant values of predefined key features of processing units that greatly impact on ubiquitous computing and to predict the processing capability of processing units using relevant values of the predefined features. An object-oriented analysis and system design methodology is employed and the proposed processing unit eligibility identification mechanism and neural network-based classifier is shown to effectively support ubiquitous computing.
VL  - 4
IS  - 2
ER  -

Copy | Download