Year 2021,
, 40 - 44, 31.12.2021
Ebru Efeoğlu
,
Gürkan Tuna
References
- Zandieh, O. and Kim, S., "Sensitive and selective detection of adsorbed explosive molecules using opto-calorimetric infrared spectroscopy and micro-differential thermal analysis," Sensors and Actuators B: Chemical, vol. 231, pp. 393-398, 2016.
- Gares,K.,L, Hufziger, K. T., Bykov, S. V. and Asher, S. A.,"Review of explosive detection methodologies and the emergence of standoff deep UV resonance Raman," Journal of Raman Spectroscopy, vol. 47, no. 1, pp. 124-141, 2016.
- Zarei, A. R. and Ghazanchayi, B., "Design and fabrication of optical chemical sensor for detection of nitroaromatic explosives based on fluorescence quenching of phenol red immobilized poly (vinyl alcohol) membrane," Talanta, vol. 150, pp. 162-168, 2016.
- Mäkinen, M., Nousiainen, M. and Sillanpää, M., "Ion spectrometric detection technologies for ultra‐traces of explosives: A review," Mass spectrometry reviews, vol. 30, no. 5, pp. 940-973, 2011.
- Chrzanowski, L. von, Beckmann, J. Marchetti, B., Ewert, U. and Schade, U., "Terahertz time domain spectroscopy for non-destructive testing of hazardous liquids,"Materials Testing, vol. 54, no. 6, pp. 444-450, 2012.
- Botti, S., Almaviva, S., Cantarini, L., Palucci, A., Puiu, A. and Rufoloni, A., "Trace level detection and identification of nitro‐based explosives by surface‐enhanced Raman spectroscopy," Journal of Raman Spectroscopy, vol. 44, no. 3, pp. 463-468, 2013.
- Ramírez-Cedeño, M. L., Ortiz-Rivera, W., Pacheco-Londoño, L. C. and Hernández-Rivera, S. P., "Remote detection of hazardous liquids concealed in glass and plastic containers," IEEE Sensors Journal, vol. 10, no. 3, pp. 693-698, 2010.
- Krylatykh, N. A., Yakh’ya, V. F., Fakhrutdinov, A. R., Anashkin, V. N., Shagalov, V. A. and Khabipov, R. S., "Detection of explosive precursors using low-field magnetic resonance imaging," Applied Magnetic Resonance, vol. 47, no. 8, pp. 915-924, 2016.
- Castro-Suarez, J. R., Pacheco-Londoño, L. C., Aparicio-Bolaño, J. and Hernández-Rivera, S. P., "Active mode remote infrared spectroscopy detection of TNT and PETN on aluminum substrates," Journal of Spectroscopy, vol. 2017, 2017.
- Kehres, J., Lyksborg, M. and Olsen, U. L., "Threat detection of liquid explosives and precursors from their x-ray scattering pattern using energy dispersive detector technology," in Radiation Detectors in Medicine, Industry, and National Security XVIII, 2017, vol. 10393: International Society for Optics and Photonics, p. 1039302.
- Singh, P., Bhamidipati, S., Singh, R., Smith, R. and Nelson, P., "Evaluation of in-line sensors for prediction of soluble and total solids/moisture in continuous processing of fruit juices," Food Control, vol. 7, no. 3, pp. 141-148, 1996.
- Abduljabar, A. A., Hamzah, H. and Porch, A., "Multi‐resonators, microwave microfluidic sensor for liquid characterization," Microwave and Optical Technology Letters, vol. 63, no. 4, pp. 1042-1047, 2021.
- Hafdi, Z., Tao, J. and Chaabi, A., "Microstrip coupled high sensitivity sensor for water ethanol mixture characterization," Frequenz, vol. 75, no. 1-2, pp. 1-7, 2021.
- Efeoğlu E. and Tuna, G., "The Use of Microwave and K* Algorithm in Determination of Alcohol Concentration in Liquids," Russian Journal of Nondestructive Testing, vol. 56, no. 8, pp. 689-697, 2020.
- Yuan, S., Zhang, Z., Sun, Y., Kwon, J. S.-I. and Mashuga, C. V., "Liquid flammability ratings predicted by machine learning considering aerosolization," Journal of Hazardous Materials, vol. 386, p. 121640, 2020.
- Deng, F., Gu, W., Zeng, W., Zhang, Z. and Wang, F., "Hazardous Chemical Accident Prevention Based on K-Means Clustering Analysis of Incident Information," IEEE Access, vol. 8, pp. 180171-180183, 2020.
- Wang, X. and Wang, H., "Driving behavior clustering for hazardous material transportation based on genetic fuzzy C-means algorithm," IEEE Access, vol. 8, pp. 11289-11296, 2020.
- Rafsanjani, M. K., Varzaneh, Z. A. and Chukanlo, N. E., "A survey of hierarchical clustering algorithms," The Journal of Mathematics and Computer Science, vol. 5, no. 3, pp. 229-240, 2012.
- Murtagh, F. and Contreras, P., "Algorithms for hierarchical clustering: an overview, II," Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, vol. 7, no. 6, p. e1219, 2017.
CLASSIFICATION OF LIQUIDS USING A PATCH ANTENNA AND HIERARCHICAL CLUSTERING ALGORITHMS
Year 2021,
, 40 - 44, 31.12.2021
Ebru Efeoğlu
,
Gürkan Tuna
Abstract
Detection of hazardous liquids used in explosive production is important in terms of public safety and health. Because many threats can be prevented by detecting these liquids at security controls points. As existing methods have some disadvantages in terms of accuracy, practicality or reliability, there is a demand for new methods for hazardous liquid detection. In this paper, a circular patch antenna for hazardous liquid detection was designed and by connecting to a vector network analyzer a group of measurements was made. Then, this dataset was used by hierarchical clustering algorithms employed in this study to detect hazardous liquids. The results show that high classification accuracy can be achieved when Ward linkage method is preferred.
References
- Zandieh, O. and Kim, S., "Sensitive and selective detection of adsorbed explosive molecules using opto-calorimetric infrared spectroscopy and micro-differential thermal analysis," Sensors and Actuators B: Chemical, vol. 231, pp. 393-398, 2016.
- Gares,K.,L, Hufziger, K. T., Bykov, S. V. and Asher, S. A.,"Review of explosive detection methodologies and the emergence of standoff deep UV resonance Raman," Journal of Raman Spectroscopy, vol. 47, no. 1, pp. 124-141, 2016.
- Zarei, A. R. and Ghazanchayi, B., "Design and fabrication of optical chemical sensor for detection of nitroaromatic explosives based on fluorescence quenching of phenol red immobilized poly (vinyl alcohol) membrane," Talanta, vol. 150, pp. 162-168, 2016.
- Mäkinen, M., Nousiainen, M. and Sillanpää, M., "Ion spectrometric detection technologies for ultra‐traces of explosives: A review," Mass spectrometry reviews, vol. 30, no. 5, pp. 940-973, 2011.
- Chrzanowski, L. von, Beckmann, J. Marchetti, B., Ewert, U. and Schade, U., "Terahertz time domain spectroscopy for non-destructive testing of hazardous liquids,"Materials Testing, vol. 54, no. 6, pp. 444-450, 2012.
- Botti, S., Almaviva, S., Cantarini, L., Palucci, A., Puiu, A. and Rufoloni, A., "Trace level detection and identification of nitro‐based explosives by surface‐enhanced Raman spectroscopy," Journal of Raman Spectroscopy, vol. 44, no. 3, pp. 463-468, 2013.
- Ramírez-Cedeño, M. L., Ortiz-Rivera, W., Pacheco-Londoño, L. C. and Hernández-Rivera, S. P., "Remote detection of hazardous liquids concealed in glass and plastic containers," IEEE Sensors Journal, vol. 10, no. 3, pp. 693-698, 2010.
- Krylatykh, N. A., Yakh’ya, V. F., Fakhrutdinov, A. R., Anashkin, V. N., Shagalov, V. A. and Khabipov, R. S., "Detection of explosive precursors using low-field magnetic resonance imaging," Applied Magnetic Resonance, vol. 47, no. 8, pp. 915-924, 2016.
- Castro-Suarez, J. R., Pacheco-Londoño, L. C., Aparicio-Bolaño, J. and Hernández-Rivera, S. P., "Active mode remote infrared spectroscopy detection of TNT and PETN on aluminum substrates," Journal of Spectroscopy, vol. 2017, 2017.
- Kehres, J., Lyksborg, M. and Olsen, U. L., "Threat detection of liquid explosives and precursors from their x-ray scattering pattern using energy dispersive detector technology," in Radiation Detectors in Medicine, Industry, and National Security XVIII, 2017, vol. 10393: International Society for Optics and Photonics, p. 1039302.
- Singh, P., Bhamidipati, S., Singh, R., Smith, R. and Nelson, P., "Evaluation of in-line sensors for prediction of soluble and total solids/moisture in continuous processing of fruit juices," Food Control, vol. 7, no. 3, pp. 141-148, 1996.
- Abduljabar, A. A., Hamzah, H. and Porch, A., "Multi‐resonators, microwave microfluidic sensor for liquid characterization," Microwave and Optical Technology Letters, vol. 63, no. 4, pp. 1042-1047, 2021.
- Hafdi, Z., Tao, J. and Chaabi, A., "Microstrip coupled high sensitivity sensor for water ethanol mixture characterization," Frequenz, vol. 75, no. 1-2, pp. 1-7, 2021.
- Efeoğlu E. and Tuna, G., "The Use of Microwave and K* Algorithm in Determination of Alcohol Concentration in Liquids," Russian Journal of Nondestructive Testing, vol. 56, no. 8, pp. 689-697, 2020.
- Yuan, S., Zhang, Z., Sun, Y., Kwon, J. S.-I. and Mashuga, C. V., "Liquid flammability ratings predicted by machine learning considering aerosolization," Journal of Hazardous Materials, vol. 386, p. 121640, 2020.
- Deng, F., Gu, W., Zeng, W., Zhang, Z. and Wang, F., "Hazardous Chemical Accident Prevention Based on K-Means Clustering Analysis of Incident Information," IEEE Access, vol. 8, pp. 180171-180183, 2020.
- Wang, X. and Wang, H., "Driving behavior clustering for hazardous material transportation based on genetic fuzzy C-means algorithm," IEEE Access, vol. 8, pp. 11289-11296, 2020.
- Rafsanjani, M. K., Varzaneh, Z. A. and Chukanlo, N. E., "A survey of hierarchical clustering algorithms," The Journal of Mathematics and Computer Science, vol. 5, no. 3, pp. 229-240, 2012.
- Murtagh, F. and Contreras, P., "Algorithms for hierarchical clustering: an overview, II," Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, vol. 7, no. 6, p. e1219, 2017.