Outputs (5)

De novo design of novel protease inhibitor candidates in the treatment of SARS-CoV-2 using deep learning, docking, and molecular dynamic simulations (2021)
Journal Article
Arshia, A. H., Shadravan, S., Solhjoo, A., Sakhteman, A., & Sami, A. (2021). De novo design of novel protease inhibitor candidates in the treatment of SARS-CoV-2 using deep learning, docking, and molecular dynamic simulations. Computers in Biology and Medicine, 139, Article 104967. https://doi.org/10.1016/j.compbiomed.2021.104967

The main protease of SARS-CoV-2 is a critical target for the design and development of antiviral drugs. 2.5 M compounds were used in this study to train an LSTM generative network via transfer learning in order to identify the four best candidates ca... Read More about De novo design of novel protease inhibitor candidates in the treatment of SARS-CoV-2 using deep learning, docking, and molecular dynamic simulations.

A large margin piecewise linear classifier with fusion of deep features in the diagnosis of COVID-19 (2021)
Journal Article
Azouji, N., Sami, A., Taheri, M., & Müller, H. (2021). A large margin piecewise linear classifier with fusion of deep features in the diagnosis of COVID-19. Computers in Biology and Medicine, 139, Article 104927. https://doi.org/10.1016/j.compbiomed.2021.104927

The world has experienced epidemics of coronavirus infections several times over the last two decades. Recent studies have shown that using medical imaging techniques can be useful in developing an automatic computer-aided diagnosis system to detect... Read More about A large margin piecewise linear classifier with fusion of deep features in the diagnosis of COVID-19.

Particular matter prediction using synergy of multiple source urban big data in smart cities (2021)
Journal Article
Honarvar, A. R., & Sami, A. (2021). Particular matter prediction using synergy of multiple source urban big data in smart cities. Intelligent Decision Technologies, 15(3), 371-385. https://doi.org/10.3233/idt-200147

At present, the issue of air quality in populated urban areas is recognized as an environmental crisis. Air pollution affects the sustainability of the city. In controlling air pollution and protecting its hazards from humans, air quality data are ve... Read More about Particular matter prediction using synergy of multiple source urban big data in smart cities.

An Empirical Study of C++ Vulnerabilities in Crowd-Sourced Code Examples (2021)
Presentation / Conference Contribution
Verdi, M., Sami, A., Akhondali, J., Khomh, F., Uddin, G., & Karami Motlagh, A. (2021, May). An Empirical Study of C++ Vulnerabilities in Crowd-Sourced Code Examples. Presented at 43rd International Conference on Software Engineering, Online

Software developers share programming solutions in Q&A sites like Stack Overflow, Stack Exchange, Android forum, and so on. The reuse of crowd-sourced code snippets can facilitate rapid prototyping. However, recent research shows that the shared code... Read More about An Empirical Study of C++ Vulnerabilities in Crowd-Sourced Code Examples.

Intrusion Detection, Measurement Correction, and Attack Localization of PMU Networks (2021)
Journal Article
Khalafi, Z. S., Dehghani, M., Khalili, A., Sami, A., Vafamand, N., & Dragicevic, T. (2022). Intrusion Detection, Measurement Correction, and Attack Localization of PMU Networks. IEEE Transactions on Industrial Electronics, 69(5), 4697-4706. https://doi.org/10.1109/tie.2021.3080212

Accurate state estimation is essential for correct supervision of power grids. With the existence of cyber-attacks, state estimation may become inaccurate, which can eventually lead to wrong supervisory decision making. To detect cyber-attacks in pow... Read More about Intrusion Detection, Measurement Correction, and Attack Localization of PMU Networks.