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Salgınlarda Güvenilir Sosyo-Ekonomik İlişkiler İçin Kullanılabilecek Bir Yazılım Mimarisi

Year 2021, Volume: 12 Issue: 1, 40 - 52, 30.06.2021

Abstract

Dünya genelinde yayılan ve Covid-19 adı ile bilinen salgın, sosyal ve ekonomik yaşamı olumsuz etkilemektedir. Halihazırda bir tedavinin olmaması nedeni ile insanlık bu salgına hazırlıksız yakalanmıştır. Salgın durumunda alışveriş, seyahat, market gibi insanların etkileşimde olması gereken sosyal ve ekonomik ilişkilerin güvenli bir şekilde yerine getirilmesi gerekmektedir. Bu bağlamda güvenlik görevlileri kontrolünde uygulanan tedbirler ise devlete ek yük gerektirmektedir. Sokağa çıkma yasağı ve kısmi karantinalar ise hastalık bulaşmamış ve izole insanların yaşamlarını kısıtlamakta ve ekonomiyi durma noktasında getirmektedir. Bu çalışmada salgın hastalık durumlarında kullanılabilecek bir yazılım mimarisi önerilmektedir. Büyük veri ve graf veritabanı kullanan yaklaşımda her birey ya da işletmenin devlet eliyle uygulamaya dahil edildiği varsayılmıştır. Bu sayede her birey benzersiz bir kimlik ile temsil edilebilecektir. Hastalık düzeyinin temsil edilmesi için ise dört durumlu bir sağlık kodu kullanılmaktadır. E-devlet hizmetleri, büyük veri yaklaşımı ve mobil şebeke hizmetleri kullanılarak elde edilecek bu kodlardan üç tanesi kişinin pozitif vaka olması, tamamen sağlıklı olması ve pozitif vakayla temaslı olması durumlarını temsil etmektedir. Son kod ise uygulamayı kullanan ancak bireylerin belirli bir işletme ya da diğer bireyi raporlaması için kullanılacaktır. Uygulamayı kullanmayan veya barkod ile uyuşmayan kullanıcıların belirlenmesi ve raporlanması için kullanılacaktır. Çalışma kapsamında yazılım mimarisi tasarımı ve mobil uygulama ara yüzü gerçekleştirilerek, simülasyon çalışması ile örnek senaryolar üzerinden sunulan yaklaşım doğrulanmıştır.

References

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  • Nogatz, F., Seipel, D. (2017). Implementing GraphQL as A Query Language for Deductive Databases in SWI-Prolog Using DCGs, Quasi Quotations, And Dicts. arXiv preprint arXiv:1701.00626.
  • Noulas, A., Scellato, S., Mascolo, C., Pontil, M. (2011, July). An Empirical Study of Geographic User Activity Patterns in Foursquare. In Fifth international AAAI Conference on Weblogs and Social Media.
  • Oliphant, T. E. (2007). Python For Scientific Computing. Computing in Science & Engineering, 9(3), 10-20.
  • Robinson, I., Webber, J., & Eifrem, E. (2013). Graph Databases. O'Reilly Media, Inc.
  • Shan, F., Gao, Y., Wang, J., Shi, W., Shi, N., Han, M., Xue, Z., Shen, D., & Shi, Y. (2020). Lung Infection Quantification of COVID-19 in CT Images with Deep Learning. arXiv preprint arXiv:2003.04655.
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  • HES, https://hayatevesigar.saglik.gov.tr/hes.html (Erişim Tarihi: 2020)

A Software Architecture That Can Be Used for Reliable Socio-Economic Relations in Epidemic

Year 2021, Volume: 12 Issue: 1, 40 - 52, 30.06.2021

Abstract

The epidemic, spread around the world and known as Covid-19, negatively affects social and economic life. Humanity has been caught unprepared for this epidemic, as there is currently no cure. In the case of epidemic, social and economic relations that people like shopping, travel, market should interact must be safely implemented. In this context, the measures applied under the control of security officers require additional burden on the state. Curfews and partial quarantines restrict the lives of uninfected and isolated people and bring the economy to a halt. In this study, a software architecture that can be used in cases of epidemics is suggested. In the approach that uses big data and graph database, it is assumed that every individual or business is included in the application by the state. In this way, each individual can be represented with a unique identity. A four-state health code is used to represent the level of the disease. Three of these codes, which will be obtained by using e-government services, big data approach and mobile network services, represent situations where a person is a positive case, is completely healthy and is in contact with a positive case. The last code will be used to report individuals using the application, but to a particular business or other individual. It will be used to identify and report users who do not use the application or do not match the barcode. Within the scope of the study, software architecture design and mobile application interface were realized, and the approach presented through simulation study and sample scenarios were verified.

References

  • Anderson, R. M., Heesterbeek, H., Klinkenberg, D., & Hollingsworth, T. D. (2020). How Will Country-Based Mitigation Measures Influence the Course of the COVID-19 Epidemic? The Lancet, 395(10228), 931-934.
  • Chinazzi, M., Davis, J. T., Ajelli, M., Gioannini, C., Litvinova, M., Merler, S. et al. (2020). The Effect of Travel Restrictions on The Spread of the 2019 Novel Coronavirus (COVID-19), Science, 368(6489), 395-400
  • Eisenman, B. (2015). Learning React Native: Building Native Mobile Apps with Javascript. O'Reilly Media, Inc. E-devlet, https://www.turkiye.gov.tr (Erişim Tarihi: 2020)
  • Fernandes, R., & D’Souza, R. (2015). Survey on Web Service Discovery and Availability in Mobile Environments and Future Trends in Mobile Web Services. International Journal of Computer Applications, 132(12), 16-19.
  • Gozes, O., Frid-Adar, M., Greenspan, H., Browning, P. D., Zhang, H., Ji, W., Bernheim, A., & Siegel, E. (2020). Rapid AI Development Cycle for The Coronavirus (Covid-19) Pandemic: Initial Results for Automated Detection & Patient Monitoring Using Deep Learning CT Image Analysis. arXiv preprint arXiv:2003.05037.
  • https://www.hurriyet.com.tr/teknoloji/turk-firmalari-kovid-19a-karsi-pandemi-yonetim-sistemi-gelistirdi-41486008?utm_source=kisa-haber (Erişim Tarihi: 2020)
  • https://patents.google.com/patent/US20200016286A1/en (Erişim Tarihi: 2020)
  • https://covid19.saglik.gov.tr/ (Erişim Tarihi: 2020)
  • Kang, Y. S., Park, I. H., Rhee, J., & Lee, Y. H. (2015). MongoDB-Based Repository Design for IoT-Generated RFID/Sensor Big Data. IEEE Sensors Journal, 16(2), 485-497.
  • Lam, C. (2010). Hadoop in Action. Manning Publications Co.
  • Liu, S., Yang, L., Zhang, C., Xiang, Y. T., Liu, Z., Hu, S., & Zhang, B. (2020). Online Mental Health Services in China During the COVID-19 Outbreak. The Lancet Psychiatry, 7(4), e17-e18.
  • Madakam, S., Ramaswamy, R., & Tripathi, S. (2015). Internet of Things (IoT): A literature Review. Journal of Computer and Communications, 3(05), 164-173.
  • Nogatz, F., Seipel, D. (2017). Implementing GraphQL as A Query Language for Deductive Databases in SWI-Prolog Using DCGs, Quasi Quotations, And Dicts. arXiv preprint arXiv:1701.00626.
  • Noulas, A., Scellato, S., Mascolo, C., Pontil, M. (2011, July). An Empirical Study of Geographic User Activity Patterns in Foursquare. In Fifth international AAAI Conference on Weblogs and Social Media.
  • Oliphant, T. E. (2007). Python For Scientific Computing. Computing in Science & Engineering, 9(3), 10-20.
  • Robinson, I., Webber, J., & Eifrem, E. (2013). Graph Databases. O'Reilly Media, Inc.
  • Shan, F., Gao, Y., Wang, J., Shi, W., Shi, N., Han, M., Xue, Z., Shen, D., & Shi, Y. (2020). Lung Infection Quantification of COVID-19 in CT Images with Deep Learning. arXiv preprint arXiv:2003.04655.
  • Vukotic, A., Watt, N., Abedrabbo, T., Fox, D., & Partner, J. (2014). Neo4j in action. Manning Publications Co. World Health Organization. (2020). Coronavirus Disease 2019 (COVID-19): Situation Report, 67.
  • Xu, Z., Shi, L., Wang, Y., Zhang, J., Huang, L., Zhang, C. et al. (2020). Pathological Findings of COVID-19 Associated with Acute Respiratory Distress Syndrome. The Lancet Respiratory Medicine, 8, 420-422.
  • HES, https://hayatevesigar.saglik.gov.tr/hes.html (Erişim Tarihi: 2020)
There are 20 citations in total.

Details

Primary Language English
Subjects Software Engineering (Other)
Journal Section Research Article
Authors

Yunus Santur

Mehmet Karaköse

Publication Date June 30, 2021
Published in Issue Year 2021 Volume: 12 Issue: 1

Cite

APA Santur, Y., & Karaköse, M. (2021). A Software Architecture That Can Be Used for Reliable Socio-Economic Relations in Epidemic. İnternet Uygulamaları Ve Yönetimi Dergisi, 12(1), 40-52.