PATENT PROTECTION OF DIGITAL TECHNOLOGIES FOR FOOD SAFETY SUPERVISION

http://dx.doi.org/10.31703/glsr.2023(VIII-II).04      10.31703/glsr.2023(VIII-II).04      Published : Jun 2023
Authored by : Li Tian-zhi , Ilyas Khan , Sobia Bashir

04 Pages : 27-35

References

  • Boushey, C. J., Spoden, M., Zhu, F. M., Delp, E. J., & Kerr, D. A. (2016). New mobile methods for dietary assessment: review of image-assisted and image-based dietary assessment methods. Proceedings of the Nutrition Society, 76(03), 283–294. https://doi.org/10.1017/s0029665116002913
  • Bouzembrak, Y., & Marvin, H. J. P. (2016). Prediction of food fraud type using data from Rapid Alert System for Food and Feed (RASFF) and Bayesian network modelling. Food Control, 61, 180–187. https://doi.org/10.1016/j.foodcont.2015.09.026
  • arcia-Esteban, J. A., Curto, B., Moreno, V., Gonzalez-Martin, I., Revilla, I., & Vivar-Quintana, A. (2018). A digitalization strategy for quality control in food industry based on Artificial Intelligence techniques. 2018 IEEE 16th International Conference on Industrial Informatics (INDIN ). https://doi.org/10.1109/indin.2018.8471994
  • Langmead, B., & Nellore, A. (2018). Cloud computing for genomic data analysis and collaboration. Nature Reviews Genetics, 19(4), 208–219. https://doi.org/10.1038/nrg.2017.113
  • Lokers, R., Knapen, R., Janssen, S., van Randen, Y., & Jansen, J. (2016). Analysis of Big Data technologies for use in agro-environmental science. Environmental Modelling & Software, 84, 494–504. https://doi.org/10.1016/j.envsoft.2016.07.017
  • Piao, J. (2011). Research on the Problems of China's Computer Software Patent Protection System. Electronics Intellectual Property, 8, 92–94.
  • Qi, A., & Cheng, G. (2015). Determining Patent Suitability of 'Method Patents' in the Data Technology Era: A Review of the USPTO's 2014 nterim Guidelines on Patent Subject Matter Suitability. Social Sciences in Hunan, 3, 60–64. Robbins, M. (2016, February 18). Has a rampaging AI algorithm really killed thousands in Pakistan? Inkl. https://www.inkl.com/news/has-a-rampaging-ai-algorithm-really-killed-thousands-in-pakistan
  • Tencent Research Institute. (2017). Artificial Intelligence: The grip of national AI strategic action. China Renmin University Press
  • Van Asselt, E. D., Noordam, M. Y., Pikkemaat, M. G., & Dorgelo, F. O. (2018). Risk-based monitoring of chemical substances in food: Prioritization by decision trees. Food Control, 93, 112–120. https://doi.org/10.1016/j.foodcont.2018.06.001
  • Wang, P., Wang, Z., & Ma, Q. (2019). Research on the Association of Mobile Social Network Users Privacy Information Based on Big Data Analysis. Journal of Information Hiding and Privacy Protection, 1(1), 35–42. https://doi.org/10.32604/jihpp.2019.05942
  • Yao, M., Ling, Y., Xing, X., Yao, G., Liu, H., & Zhang, F. (2021). Comparative Study on Response Mechanisms to Food Safety Emergencies. Journal of Food Safety & Quality, 12(10), 4221– 4229
  • Zhang, Y. (2020). On the Legal Standard of Patentability of Artificial Intelligence Inventions. Studies in Law and Business, 6, 181–192
  • Zhao, C., & Zhou, S. (2017). EPO Review of Patentability in the Computer Field. China Invention & Patent, 5, 100–105.
  • Zong, X., & Wang, Y. (2017). The Implications of the Open FDA Data Policy in the United States for Food and Drug Regulatory Data Management in China. Chinese Pharmaceutical Affairs, 31(9), 976–979.
  • Boushey, C. J., Spoden, M., Zhu, F. M., Delp, E. J., & Kerr, D. A. (2016). New mobile methods for dietary assessment: review of image-assisted and image-based dietary assessment methods. Proceedings of the Nutrition Society, 76(03), 283–294. https://doi.org/10.1017/s0029665116002913
  • Bouzembrak, Y., & Marvin, H. J. P. (2016). Prediction of food fraud type using data from Rapid Alert System for Food and Feed (RASFF) and Bayesian network modelling. Food Control, 61, 180–187. https://doi.org/10.1016/j.foodcont.2015.09.026
  • arcia-Esteban, J. A., Curto, B., Moreno, V., Gonzalez-Martin, I., Revilla, I., & Vivar-Quintana, A. (2018). A digitalization strategy for quality control in food industry based on Artificial Intelligence techniques. 2018 IEEE 16th International Conference on Industrial Informatics (INDIN ). https://doi.org/10.1109/indin.2018.8471994
  • Langmead, B., & Nellore, A. (2018). Cloud computing for genomic data analysis and collaboration. Nature Reviews Genetics, 19(4), 208–219. https://doi.org/10.1038/nrg.2017.113
  • Lokers, R., Knapen, R., Janssen, S., van Randen, Y., & Jansen, J. (2016). Analysis of Big Data technologies for use in agro-environmental science. Environmental Modelling & Software, 84, 494–504. https://doi.org/10.1016/j.envsoft.2016.07.017
  • Piao, J. (2011). Research on the Problems of China's Computer Software Patent Protection System. Electronics Intellectual Property, 8, 92–94.
  • Qi, A., & Cheng, G. (2015). Determining Patent Suitability of 'Method Patents' in the Data Technology Era: A Review of the USPTO's 2014 nterim Guidelines on Patent Subject Matter Suitability. Social Sciences in Hunan, 3, 60–64. Robbins, M. (2016, February 18). Has a rampaging AI algorithm really killed thousands in Pakistan? Inkl. https://www.inkl.com/news/has-a-rampaging-ai-algorithm-really-killed-thousands-in-pakistan
  • Tencent Research Institute. (2017). Artificial Intelligence: The grip of national AI strategic action. China Renmin University Press
  • Van Asselt, E. D., Noordam, M. Y., Pikkemaat, M. G., & Dorgelo, F. O. (2018). Risk-based monitoring of chemical substances in food: Prioritization by decision trees. Food Control, 93, 112–120. https://doi.org/10.1016/j.foodcont.2018.06.001
  • Wang, P., Wang, Z., & Ma, Q. (2019). Research on the Association of Mobile Social Network Users Privacy Information Based on Big Data Analysis. Journal of Information Hiding and Privacy Protection, 1(1), 35–42. https://doi.org/10.32604/jihpp.2019.05942
  • Yao, M., Ling, Y., Xing, X., Yao, G., Liu, H., & Zhang, F. (2021). Comparative Study on Response Mechanisms to Food Safety Emergencies. Journal of Food Safety & Quality, 12(10), 4221– 4229
  • Zhang, Y. (2020). On the Legal Standard of Patentability of Artificial Intelligence Inventions. Studies in Law and Business, 6, 181–192
  • Zhao, C., & Zhou, S. (2017). EPO Review of Patentability in the Computer Field. China Invention & Patent, 5, 100–105.
  • Zong, X., & Wang, Y. (2017). The Implications of the Open FDA Data Policy in the United States for Food and Drug Regulatory Data Management in China. Chinese Pharmaceutical Affairs, 31(9), 976–979.

Cite this article

    CHICAGO : Tian-zhi, Li, Ilyas Khan, and Sobia Bashir. 2023. "Patent Protection of Digital Technologies for Food Safety Supervision." Global Legal Studies Review, VIII (II): 27-35 doi: 10.31703/glsr.2023(VIII-II).04
    HARVARD : TIAN-ZHI, L., KHAN, I. & BASHIR, S. 2023. Patent Protection of Digital Technologies for Food Safety Supervision. Global Legal Studies Review, VIII, 27-35.
    MHRA : Tian-zhi, Li, Ilyas Khan, and Sobia Bashir. 2023. "Patent Protection of Digital Technologies for Food Safety Supervision." Global Legal Studies Review, VIII: 27-35
    MLA : Tian-zhi, Li, Ilyas Khan, and Sobia Bashir. "Patent Protection of Digital Technologies for Food Safety Supervision." Global Legal Studies Review, VIII.II (2023): 27-35 Print.
    OXFORD : Tian-zhi, Li, Khan, Ilyas, and Bashir, Sobia (2023), "Patent Protection of Digital Technologies for Food Safety Supervision", Global Legal Studies Review, VIII (II), 27-35
    TURABIAN : Tian-zhi, Li, Ilyas Khan, and Sobia Bashir. "Patent Protection of Digital Technologies for Food Safety Supervision." Global Legal Studies Review VIII, no. II (2023): 27-35. https://doi.org/10.31703/glsr.2023(VIII-II).04