Araştırma Makalesi
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Use of Reflection Coefficients and Decision Tree Algorithm for Rapid Classification of Hazardous Chemical Liquids

Yıl 2022, Cilt: 10 Sayı: 1, 70 - 77, 01.01.2022
https://doi.org/10.21541/apjess.1060769

Öz

The purpose of occupational health and safety studies is to protect employees from work accidents and occupational diseases and to ensure that they work in a healthy environment. Most of the work accidents happen as a result of wrong storage, transportation and use of chemicals. In order to protect employees from chemical hazards and eliminate their possible risks, a risk assessment should first be carried out. Based on the results of the risk assessment, if not done before, bottles that contain hazardous chemicals must be classified and labelled according to their risk levels. The labels of bottles that contain chemical liquids must be checked and if the labels are worn or unreadable, they must be renewed. After these have been done, hazardous chemical liquids must be classified, stored and transported according to these labels. In this study, a non-contact, liquid measurement system based on microwave data is proposed to detect hazardous liquids. In order to select the most suitable algorithm for use in this measurement system, 3 different classification algorithms have been used and the performance analysis of the algorithms has made. In the study, 3 different classification processes have been applied according to the chemical properties of the liquids. It has been observed that Random Tree algorithm has achieved the best performance while Rep Tree algorithm has done the worst performance. Using this system, hazardous chemical liquids can be detected without opening the cover of the bottles that contain the liquids. Therefore, it can be used to quickly label hazardous liquids for their safe storage and transportation.

Kaynakça

  • R. H. Hill Jr, "Recognizing and understanding hazards—The key first step to safety," Journal of Chemica Health and Safety, vol. 26, no. 3, pp. 5-10, 2019.
  • S. Salminen, "Have young workers more injuries than older ones? An international literature review," Journal of safety research, vol. 35, no. 5, pp. 513-521, 2004.
  • A. Parent-Thirion et al., Sixth European Working Conditions Survey: Overview Report. Eurofound (European Foundation for the Improvement of Living and Working …, 2016.
  • A. Byzov, A. Telegina, I. Korotkiy, and J. Veber, "Consequence assessment of explosions for fuel-air mixtures at hazardous production facilities," in E3S Web of Conferences, vol. 140: EDP Sciences, p. 08014, (2019).
  • J. Casal, Evaluation of the effects and consequences of major accidents in industrial plants. Elsevier, 2017.
  • A. Z. Mendiburu, J. A. de Carvalho Jr, and C. R. Coronado, "Method for determination of flammability limits of gaseous compounds diluted with N2 and CO2 in air," Fuel, vol. 226, pp. 65-80, 2018.
  • D. K. Horton, Z. Berkowitz, G. S. Haugh, M. F. Orr, and W. E. Kaye, "Acute public health consequences associated with hazardous substances released during transit, 1993–2000," Journal of hazardous materials, vol. 98, no. 1-3, pp. 161-175, 2003.
  • K. Kempna et al., "Fire Safety Protection Assessment of Industrial Technologies," in Journal of Physics: Conference Series, 2018, vol. 1107, no. 4: IOP Publishing, p. 042036.
  • A. Nikulin and A. Y. Nikulina, "Assessment of occupational health and safety effectiveness at a mining company," Ecology, Environment and Conservation, no. 23, p. 1.
  • C. Wei, W. J. Rogers, and M. S. Mannan, "Application of screening tools in the prevention of reactive chemical incidents," Journal of Loss Prevention in the Process Industries, vol. 17, no. 4, pp. 261-269, 2004.
  • T. Hoppe, N. Jaeger, and J. Terry, "Safe handling of combustible powders during transportation, charging, discharging and storage," Journal of Loss Prevention in the Process Industries, vol. 13, no. 3-5, pp. 253-263, 2000.
  • W. L. Welles, R. E. Wilburn, J. K. Ehrlich, and C. M. Floridia, "New York hazardous substances emergency events surveillance: learning from hazardous substances releases to improve safety," Journal of hazardous materials, vol. 115, no. 1-3, pp. 39-49, 2004.
  • S. Kumar, "Liquid-contents verification for explosives, other hazards, and contraband by magnetic resonance," Appl. Magn. Reson., 2004, vol. 25, nos. 3–4, pp. 585–597.
  • S. Singh and M. Singh, "Explosives detection systems (EDS) for aviation security," Signal Process., vol. 83, no. 1, pp. 31–55, 2003.
  • L. Cardona, J. Jiménez and N. Vanegas, "Nuclear quadrupole resonance for explosive detection," Ingeniare Revista chilena de ingeniería, vol. 23, no. 3, pp. 458–472, 2015.
  • K. Choi, T. Hong, K. I. Sim, T. Ha, B.C. Park, J.H. Chung, et al. "Reflection terahertz time-domain spectroscopy of RDX and HMX explosives," J. Appl. Phys., vol. 115, no. 2, p. 023105, 2014.
  • Z.Z. Abidin, F.N. Omar, P. Yogarajah, D.R.A. Biak, and Y.B.C. Man, "Dielectric characterization of liquid containing low alcoholic content for potential halal authentication in the 0.5-50 GHz range,"Am. J. Appl. Sci., vol. 11, no. 7, pp. 1104–1112, 2014.
  • F. Yang , J. Gong , E. Yang , Y. Guan , X. He , S. Liu, X. Zhang , Y. Deng, " Microwave-absorbing properties of room-temperature ionic liquids, " Journal of Physics D: Applied Physics, 52(15):155302, 2019.
  • A. La Gioia et al., "Open-ended coaxial probe technique for dielectric measurement of biological tissues: Challenges and common practices," Diagnostics, vol. 8, no. 2, p. 40, 2018.
  • T. Karpisz, B. Salski, P. Kopyt, J. Krupka, "Measurement of Electromagnetic Properties of Food Products and Liquids," In: 2018 12th International Conference on Electromagnetic Wave Interaction with Water and Moist Substances (ISEMA): 2018: IEEE: 1-9, (2018).
  • S. Kayal, T. Shaw, D. Mitra, "Design of metamaterial based compact and highly sensitive microwave liquid sensor," Applied Physics A ,126:13, 2020.
  • M. Pal and P. M. Mather, "An assessment of the effectiveness of decision tree methods for land cover classification," Remote sensing of environment, vol. 86, no. 4, pp. 554-565, 2003.
  • M. A. Friedl and C. E. Brodley, "Decision tree classification of land cover from remotely sensed data," Remote sensing of environment, vol. 61, no. 3, pp. 399-409, 1997.
  • J. R. Quinlan, C4. 5: programs for machine learning. Elsevier, 2014.
  • W. Y. Loh, "Classification and regression trees," Wiley interdisciplinary reviews: data mining and knowledge discovery, vol. 1, no. 1, pp. 14-23, 2011.
  • J. Mingers, "An empirical comparison of pruning methods for decision tree induction," Machine learning, vol. 4, no. 2, pp. 227-243, 1989.
  • J. R. Quinlan, "Simplifying decision trees," 1986.
  • J. Li, S. Zhang, Y. Lu, and J. Yan, "Real-time P2P traffic identification," in IEEE GLOBECOM 2008-2008 IEEE Global Telecommunications Conference, 2008: IEEE, pp. 1-5.
  • M. F. Amasyali and O. Ersoy, "Evaluation of regression ensembles on drug design datasets," 2009.
  • Y. Freund and L. Mason, "The alternating decision tree learning algorithm," in icml, 1999, vol. 99, pp. 124-133.
Yıl 2022, Cilt: 10 Sayı: 1, 70 - 77, 01.01.2022
https://doi.org/10.21541/apjess.1060769

Öz

Kaynakça

  • R. H. Hill Jr, "Recognizing and understanding hazards—The key first step to safety," Journal of Chemica Health and Safety, vol. 26, no. 3, pp. 5-10, 2019.
  • S. Salminen, "Have young workers more injuries than older ones? An international literature review," Journal of safety research, vol. 35, no. 5, pp. 513-521, 2004.
  • A. Parent-Thirion et al., Sixth European Working Conditions Survey: Overview Report. Eurofound (European Foundation for the Improvement of Living and Working …, 2016.
  • A. Byzov, A. Telegina, I. Korotkiy, and J. Veber, "Consequence assessment of explosions for fuel-air mixtures at hazardous production facilities," in E3S Web of Conferences, vol. 140: EDP Sciences, p. 08014, (2019).
  • J. Casal, Evaluation of the effects and consequences of major accidents in industrial plants. Elsevier, 2017.
  • A. Z. Mendiburu, J. A. de Carvalho Jr, and C. R. Coronado, "Method for determination of flammability limits of gaseous compounds diluted with N2 and CO2 in air," Fuel, vol. 226, pp. 65-80, 2018.
  • D. K. Horton, Z. Berkowitz, G. S. Haugh, M. F. Orr, and W. E. Kaye, "Acute public health consequences associated with hazardous substances released during transit, 1993–2000," Journal of hazardous materials, vol. 98, no. 1-3, pp. 161-175, 2003.
  • K. Kempna et al., "Fire Safety Protection Assessment of Industrial Technologies," in Journal of Physics: Conference Series, 2018, vol. 1107, no. 4: IOP Publishing, p. 042036.
  • A. Nikulin and A. Y. Nikulina, "Assessment of occupational health and safety effectiveness at a mining company," Ecology, Environment and Conservation, no. 23, p. 1.
  • C. Wei, W. J. Rogers, and M. S. Mannan, "Application of screening tools in the prevention of reactive chemical incidents," Journal of Loss Prevention in the Process Industries, vol. 17, no. 4, pp. 261-269, 2004.
  • T. Hoppe, N. Jaeger, and J. Terry, "Safe handling of combustible powders during transportation, charging, discharging and storage," Journal of Loss Prevention in the Process Industries, vol. 13, no. 3-5, pp. 253-263, 2000.
  • W. L. Welles, R. E. Wilburn, J. K. Ehrlich, and C. M. Floridia, "New York hazardous substances emergency events surveillance: learning from hazardous substances releases to improve safety," Journal of hazardous materials, vol. 115, no. 1-3, pp. 39-49, 2004.
  • S. Kumar, "Liquid-contents verification for explosives, other hazards, and contraband by magnetic resonance," Appl. Magn. Reson., 2004, vol. 25, nos. 3–4, pp. 585–597.
  • S. Singh and M. Singh, "Explosives detection systems (EDS) for aviation security," Signal Process., vol. 83, no. 1, pp. 31–55, 2003.
  • L. Cardona, J. Jiménez and N. Vanegas, "Nuclear quadrupole resonance for explosive detection," Ingeniare Revista chilena de ingeniería, vol. 23, no. 3, pp. 458–472, 2015.
  • K. Choi, T. Hong, K. I. Sim, T. Ha, B.C. Park, J.H. Chung, et al. "Reflection terahertz time-domain spectroscopy of RDX and HMX explosives," J. Appl. Phys., vol. 115, no. 2, p. 023105, 2014.
  • Z.Z. Abidin, F.N. Omar, P. Yogarajah, D.R.A. Biak, and Y.B.C. Man, "Dielectric characterization of liquid containing low alcoholic content for potential halal authentication in the 0.5-50 GHz range,"Am. J. Appl. Sci., vol. 11, no. 7, pp. 1104–1112, 2014.
  • F. Yang , J. Gong , E. Yang , Y. Guan , X. He , S. Liu, X. Zhang , Y. Deng, " Microwave-absorbing properties of room-temperature ionic liquids, " Journal of Physics D: Applied Physics, 52(15):155302, 2019.
  • A. La Gioia et al., "Open-ended coaxial probe technique for dielectric measurement of biological tissues: Challenges and common practices," Diagnostics, vol. 8, no. 2, p. 40, 2018.
  • T. Karpisz, B. Salski, P. Kopyt, J. Krupka, "Measurement of Electromagnetic Properties of Food Products and Liquids," In: 2018 12th International Conference on Electromagnetic Wave Interaction with Water and Moist Substances (ISEMA): 2018: IEEE: 1-9, (2018).
  • S. Kayal, T. Shaw, D. Mitra, "Design of metamaterial based compact and highly sensitive microwave liquid sensor," Applied Physics A ,126:13, 2020.
  • M. Pal and P. M. Mather, "An assessment of the effectiveness of decision tree methods for land cover classification," Remote sensing of environment, vol. 86, no. 4, pp. 554-565, 2003.
  • M. A. Friedl and C. E. Brodley, "Decision tree classification of land cover from remotely sensed data," Remote sensing of environment, vol. 61, no. 3, pp. 399-409, 1997.
  • J. R. Quinlan, C4. 5: programs for machine learning. Elsevier, 2014.
  • W. Y. Loh, "Classification and regression trees," Wiley interdisciplinary reviews: data mining and knowledge discovery, vol. 1, no. 1, pp. 14-23, 2011.
  • J. Mingers, "An empirical comparison of pruning methods for decision tree induction," Machine learning, vol. 4, no. 2, pp. 227-243, 1989.
  • J. R. Quinlan, "Simplifying decision trees," 1986.
  • J. Li, S. Zhang, Y. Lu, and J. Yan, "Real-time P2P traffic identification," in IEEE GLOBECOM 2008-2008 IEEE Global Telecommunications Conference, 2008: IEEE, pp. 1-5.
  • M. F. Amasyali and O. Ersoy, "Evaluation of regression ensembles on drug design datasets," 2009.
  • Y. Freund and L. Mason, "The alternating decision tree learning algorithm," in icml, 1999, vol. 99, pp. 124-133.
Toplam 30 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Yapay Zeka
Bölüm Araştırma Makaleleri
Yazarlar

Ebru Efeoğlu Bu kişi benim 0000-0001-5444-6647

Gürkan Tuna Bu kişi benim 0000-0002-6466-4696

Erken Görünüm Tarihi 20 Ocak 2022
Yayımlanma Tarihi 1 Ocak 2022
Gönderilme Tarihi 12 Mayıs 2021
Yayımlandığı Sayı Yıl 2022 Cilt: 10 Sayı: 1

Kaynak Göster

IEEE E. Efeoğlu ve G. Tuna, “Use of Reflection Coefficients and Decision Tree Algorithm for Rapid Classification of Hazardous Chemical Liquids”, APJESS, c. 10, sy. 1, ss. 70–77, 2022, doi: 10.21541/apjess.1060769.

Academic Platform Journal of Engineering and Smart Systems