By Dr Reza Argha

Conference Papers

Afkhami H; Argha A, 2010, 'An optimal ILC method for two-dimensional systems', in SIISY 2010 - 8th IEEE International Symposium on Intelligent Systems and Informatics, pp. 511 - 517, http://dx.doi.org/10.1109/SISY.2010.5647072

Moattari M; Ahrari Nouri M; Argha A, 2010, 'Adopting fuzzy iterative learning control method for reactive power planning in distribution systems', in PEOCO 2010 - 4th International Power Engineering and Optimization Conference, Program and Abstracts, pp. 528 - 532, http://dx.doi.org/10.1109/PEOCO.2010.5559193

Argha A; Karimaghaee P; Roopaei M; Jahromi MZ, 2008, 'Fuzzy Iterative Learning Control in 2-D systems', in Ao SI; Gelman L; Hukins DWL; Hunter A; Korsunsky AM (eds.), WORLD CONGRESS ON ENGINEERING 2008, VOLS I-II, INT ASSOC ENGINEERS-IAENG, ENGLAND, Imperial Coll London, London, pp. 58 - +, presented at World Congress on Engineering 2008, ENGLAND, Imperial Coll London, London, 02 July 2008 - 04 July 2008, https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000259580600010&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=891bb5ab6ba270e68a29b250adbe88d1

Argha A; Karimaghaee P; Roopaei M, 2008, 'Iterative learning control for 2-D systems', in Proceedings of the International Joint Conference on Neural Networks, pp. 2164 - 2168, http://dx.doi.org/10.1109/IJCNN.2008.4634096

Conference Presentations

Celler B; Yong A; Rubenis I; Butlin M; Argha R; Rehan R; Avolio A, 2023, 'CAN RECORDING KOROTKOFF SOUNDS DURING BRACHIAL CUFF INFLATION PROVIDE MORE ACCURATE NON-INVASIVE ESTIMATES OF INTRA-ARTERIAL BLOOD PRESSURE?', http://dx.doi.org/10.1097/01.hjh.0000938960.09338.01

Preprints

Karami M; Alizadehsani R; Khadijeh ; Jahanian ; Argha A; Dehzangi I; Alinejad-Rokny H, 2023, Revolutionizing Genomics with Reinforcement Learning Techniques, , http://dx.doi.org/10.48550/arxiv.2302.13268

Labani M; Beheshti A; Argha A; Alinejad H, 2023, An Integrative Analysis of Chromatin Interactions, Gene Expression and Genomic Variants Identifies 30 Likely Regulatory Variants in Prostate Cancer, , http://dx.doi.org/10.20944/preprints202301.0343.v1

Nasab RZ; Ghamsari MRE; Argha A; Macphillamy C; Beheshti A; Alizadehsani R; Lovell NH; Lotfollahi M; Alinejad-Rokny H, 2022, Deep Learning in Spatially Resolved Transcriptomics: A Comprehensive Technical View, , http://dx.doi.org/10.48550/arxiv.2210.04453

Hansun S; Argha A; Liaw S-T; Celler BG; Marks GB, 2022, Machine and Deep Learning for Tuberculosis Detection on Chest X-Rays: Systematic Literature Review (Preprint), , http://dx.doi.org/10.2196/preprints.43154

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