Data Mining Technique Used in Order to Analysis the Capacitive Sensor

Nafise Masomi; Elham Ghanbari; Mohammad Taghi Adl

doi:doi:10.11648/j.ajdmkd.20190402.11

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Data Mining Technique Used in Order to Analysis the Capacitive Sensor

Nafise Masomi, Elham Ghanbari, Mohammad Taghi Adl

Published in American Journal of Data Mining and Knowledge Discovery (Volume 4, Issue 2)

Received: 31 May 2019 Accepted: 10 July 2019 Published: 23 October 2019

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Abstract

Data mining, also referred to as knowledge extraction from databases, is one of the most important analytical methods for identifying the relationships between the various elements of the information collected in order to discover the useful knowledge and support of strategic decision-making and sustainable development systems in various industries. Mathematical modeling, quantitative analysis of data and new algorithms can identify new relationships between different data, which in turn leads to competitive advantage. Olive oil is one of the most important agricultural crops due to its digestive properties and economic status. However, olive oil production is a costly process which causes an expensive price of the final product. The most jobbery ways during olive oil production consist of mixing other oils such as maize, sunflower, Canola and corn into the olive oil. So, the aim of this study was to develop a dielectric-based system to Authenticate in olive oil using cylindrical capacitive sensor. For categorizing of fake olive oil by using frequency specification, Support vector machine, linear regression, Ensemble Trees and Gaussian was developed. A set of 16 samples of olive oil, sunflower, canola and corn oil which mixed with different ratio of Authentication, were used for calibration and evaluation of developed system.

Published in	American Journal of Data Mining and Knowledge Discovery (Volume 4, Issue 2)
DOI	10.11648/j.ajdmkd.20190402.11
Page(s)	57-62
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), 2019. Published by Science Publishing Group

Keywords

Data Mining, Regression, Olive Oil, Authentication

References

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[4]	Tayyebi, A., & Pijanowski, B. C. (2014). Modeling multiple land use changes using ANN, CART and MARS: Comparing tradeoffs in goodness of fit and explanatory power of data mining tools. International Journal of Applied Earth Observation and Geoinformation, 28, 102-116.
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[6]	Mahani, R., Atia, F., Al Neklawy, M. M., & Fahem, A. (2016). Dielectric spectroscopic studies on the water hyacinth plant collected from agriculture drainage. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 162, 81-85.
[7]	Bertrand, S. (2018). Dielectric Properties of a Protein Probed by Reversal of a Buried Ion Pair. Journal of physical chemistry.
[8]	Gaikwad, S. V., Gaikwad, A. N., Harsh, R., & Gupta, A. (2015). Simulation modeling and implementation of RF and MW system to control the insect pests in agriculture. In India Conference (INDICON), pp. 1-4. IEEE.
[9]	Rodriguez-Morato, J., Xicota, L., Fito, M., Farre, M., Dierssen, M., & de la Torre, R. (2015). Potential role of olive oil phenolic compounds in the prevention of neurodegenerative diseases. Molecules, 20 (3), 4655-4680.
[10]	García, A., Rodríguez-Juan, E., Rodríguez-Gutiérrez, G., Rios, J. J., & Fernández-Bolaños, J. (2016). Extraction of phenolic compounds from virgin olive oil by deep eutectic solvents (DESs). Food chemistry, 197, 554-561.
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[13]	Soltani, M., Alimardani, R., & Omid, M. (2010). A new mathematical modeling of banana fruit and comparison with actual values of dimensional properties. Modern Applied Science, 4 (8), 104.
[14]	Ragni. L, P. Gradari, A. Berardinelli, A. Giunchi, and A. Guarnieri. (2006). Predicting quality parameters of shell eggs using a simple technique based on the dielectric properties. Biosystems Engineering, 94, 255–262.
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APA Style

Nafise Masomi, Elham Ghanbari, Mohammad Taghi Adl. (2019). Data Mining Technique Used in Order to Analysis the Capacitive Sensor. American Journal of Data Mining and Knowledge Discovery, 4(2), 57-62. https://doi.org/10.11648/j.ajdmkd.20190402.11

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ACS Style

Nafise Masomi; Elham Ghanbari; Mohammad Taghi Adl. Data Mining Technique Used in Order to Analysis the Capacitive Sensor. Am. J. Data Min. Knowl. Discov. 2019, 4(2), 57-62. doi: 10.11648/j.ajdmkd.20190402.11

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AMA Style

Nafise Masomi, Elham Ghanbari, Mohammad Taghi Adl. Data Mining Technique Used in Order to Analysis the Capacitive Sensor. Am J Data Min Knowl Discov. 2019;4(2):57-62. doi: 10.11648/j.ajdmkd.20190402.11

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@article{10.11648/j.ajdmkd.20190402.11,
  author = {Nafise Masomi and Elham Ghanbari and Mohammad Taghi Adl},
  title = {Data Mining Technique Used in Order to Analysis the Capacitive Sensor},
  journal = {American Journal of Data Mining and Knowledge Discovery},
  volume = {4},
  number = {2},
  pages = {57-62},
  doi = {10.11648/j.ajdmkd.20190402.11},
  url = {https://doi.org/10.11648/j.ajdmkd.20190402.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajdmkd.20190402.11},
  abstract = {Data mining, also referred to as knowledge extraction from databases, is one of the most important analytical methods for identifying the relationships between the various elements of the information collected in order to discover the useful knowledge and support of strategic decision-making and sustainable development systems in various industries. Mathematical modeling, quantitative analysis of data and new algorithms can identify new relationships between different data, which in turn leads to competitive advantage. Olive oil is one of the most important agricultural crops due to its digestive properties and economic status. However, olive oil production is a costly process which causes an expensive price of the final product. The most jobbery ways during olive oil production consist of mixing other oils such as maize, sunflower, Canola and corn into the olive oil. So, the aim of this study was to develop a dielectric-based system to Authenticate in olive oil using cylindrical capacitive sensor. For categorizing of fake olive oil by using frequency specification, Support vector machine, linear regression, Ensemble Trees and Gaussian was developed. A set of 16 samples of olive oil, sunflower, canola and corn oil which mixed with different ratio of Authentication, were used for calibration and evaluation of developed system.},
 year = {2019}
}

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TY  - JOUR
T1  - Data Mining Technique Used in Order to Analysis the Capacitive Sensor
AU  - Nafise Masomi
AU  - Elham Ghanbari
AU  - Mohammad Taghi Adl
Y1  - 2019/10/23
PY  - 2019
N1  - https://doi.org/10.11648/j.ajdmkd.20190402.11
DO  - 10.11648/j.ajdmkd.20190402.11
T2  - American Journal of Data Mining and Knowledge Discovery
JF  - American Journal of Data Mining and Knowledge Discovery
JO  - American Journal of Data Mining and Knowledge Discovery
SP  - 57
EP  - 62
PB  - Science Publishing Group
SN  - 2578-7837
UR  - https://doi.org/10.11648/j.ajdmkd.20190402.11
AB  - Data mining, also referred to as knowledge extraction from databases, is one of the most important analytical methods for identifying the relationships between the various elements of the information collected in order to discover the useful knowledge and support of strategic decision-making and sustainable development systems in various industries. Mathematical modeling, quantitative analysis of data and new algorithms can identify new relationships between different data, which in turn leads to competitive advantage. Olive oil is one of the most important agricultural crops due to its digestive properties and economic status. However, olive oil production is a costly process which causes an expensive price of the final product. The most jobbery ways during olive oil production consist of mixing other oils such as maize, sunflower, Canola and corn into the olive oil. So, the aim of this study was to develop a dielectric-based system to Authenticate in olive oil using cylindrical capacitive sensor. For categorizing of fake olive oil by using frequency specification, Support vector machine, linear regression, Ensemble Trees and Gaussian was developed. A set of 16 samples of olive oil, sunflower, canola and corn oil which mixed with different ratio of Authentication, were used for calibration and evaluation of developed system.
VL  - 4
IS  - 2
ER  -

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Author Information

Nafise Masomi

Department of Engineering, Yadegar-e-Imam Khomeini (RAH) Shahr-e-Rey Branch, Islamic Azad University, Tehran, Iran
Elham Ghanbari

Department of Engineering, Yadegar-e-Imam Khomeini (RAH) Shahr-e-Rey Branch, Islamic Azad University, Tehran, Iran
Mohammad Taghi Adl

Department of Engineering, Yadegar-e-Imam Khomeini (RAH) Shahr-e-Rey Branch, Islamic Azad University, Tehran, Iran

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APA Style

Nafise Masomi, Elham Ghanbari, Mohammad Taghi Adl. (2019). Data Mining Technique Used in Order to Analysis the Capacitive Sensor. American Journal of Data Mining and Knowledge Discovery, 4(2), 57-62. https://doi.org/10.11648/j.ajdmkd.20190402.11

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ACS Style

Nafise Masomi; Elham Ghanbari; Mohammad Taghi Adl. Data Mining Technique Used in Order to Analysis the Capacitive Sensor. Am. J. Data Min. Knowl. Discov. 2019, 4(2), 57-62. doi: 10.11648/j.ajdmkd.20190402.11

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AMA Style

Nafise Masomi, Elham Ghanbari, Mohammad Taghi Adl. Data Mining Technique Used in Order to Analysis the Capacitive Sensor. Am J Data Min Knowl Discov. 2019;4(2):57-62. doi: 10.11648/j.ajdmkd.20190402.11

Copy | Download

@article{10.11648/j.ajdmkd.20190402.11,
  author = {Nafise Masomi and Elham Ghanbari and Mohammad Taghi Adl},
  title = {Data Mining Technique Used in Order to Analysis the Capacitive Sensor},
  journal = {American Journal of Data Mining and Knowledge Discovery},
  volume = {4},
  number = {2},
  pages = {57-62},
  doi = {10.11648/j.ajdmkd.20190402.11},
  url = {https://doi.org/10.11648/j.ajdmkd.20190402.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajdmkd.20190402.11},
  abstract = {Data mining, also referred to as knowledge extraction from databases, is one of the most important analytical methods for identifying the relationships between the various elements of the information collected in order to discover the useful knowledge and support of strategic decision-making and sustainable development systems in various industries. Mathematical modeling, quantitative analysis of data and new algorithms can identify new relationships between different data, which in turn leads to competitive advantage. Olive oil is one of the most important agricultural crops due to its digestive properties and economic status. However, olive oil production is a costly process which causes an expensive price of the final product. The most jobbery ways during olive oil production consist of mixing other oils such as maize, sunflower, Canola and corn into the olive oil. So, the aim of this study was to develop a dielectric-based system to Authenticate in olive oil using cylindrical capacitive sensor. For categorizing of fake olive oil by using frequency specification, Support vector machine, linear regression, Ensemble Trees and Gaussian was developed. A set of 16 samples of olive oil, sunflower, canola and corn oil which mixed with different ratio of Authentication, were used for calibration and evaluation of developed system.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - Data Mining Technique Used in Order to Analysis the Capacitive Sensor
AU  - Nafise Masomi
AU  - Elham Ghanbari
AU  - Mohammad Taghi Adl
Y1  - 2019/10/23
PY  - 2019
N1  - https://doi.org/10.11648/j.ajdmkd.20190402.11
DO  - 10.11648/j.ajdmkd.20190402.11
T2  - American Journal of Data Mining and Knowledge Discovery
JF  - American Journal of Data Mining and Knowledge Discovery
JO  - American Journal of Data Mining and Knowledge Discovery
SP  - 57
EP  - 62
PB  - Science Publishing Group
SN  - 2578-7837
UR  - https://doi.org/10.11648/j.ajdmkd.20190402.11
AB  - Data mining, also referred to as knowledge extraction from databases, is one of the most important analytical methods for identifying the relationships between the various elements of the information collected in order to discover the useful knowledge and support of strategic decision-making and sustainable development systems in various industries. Mathematical modeling, quantitative analysis of data and new algorithms can identify new relationships between different data, which in turn leads to competitive advantage. Olive oil is one of the most important agricultural crops due to its digestive properties and economic status. However, olive oil production is a costly process which causes an expensive price of the final product. The most jobbery ways during olive oil production consist of mixing other oils such as maize, sunflower, Canola and corn into the olive oil. So, the aim of this study was to develop a dielectric-based system to Authenticate in olive oil using cylindrical capacitive sensor. For categorizing of fake olive oil by using frequency specification, Support vector machine, linear regression, Ensemble Trees and Gaussian was developed. A set of 16 samples of olive oil, sunflower, canola and corn oil which mixed with different ratio of Authentication, were used for calibration and evaluation of developed system.
VL  - 4
IS  - 2
ER  -

Copy | Download