Výsledky vyhledávání - "GAYATHRI, R."

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FedAT: Federated Adversarial Training for Distributed Insider Threat Detection

Autor: Gayathri, R G, Sajjanhar, Atul, Uddin, Md Palash, Xiang, Yong

Insider threats usually occur from within the workplace, where the attacker is an entity closely associated with the organization. The sequence of actions the entities take on the resources to which they have access rights allows us to identify the i

Externí odkaz: http://arxiv.org/abs/2409.13083

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Akademický článek

Altered ribosomal profile in acquired resistance and reversal associates with pathological response to chemotherapy in inflammatory breast cancer

Autor: Gayathri R. Devi, Pritha Pai, Seayoung Lee, Matthew W. Foster, Dorababu S. Sannareddy, Francois Bertucci, Naoto Ueno, Steven Van Laere

Publikováno v: npj Breast Cancer, Vol 10, Iss 1, Pp 1-14 (2024)

Abstract Therapeutic resistance presents a significant hurdle in combating inflammatory breast cancer (IBC), adding to the complexity of its management. To investigate these mechanisms, we conducted a comprehensive analysis using transcriptomic and p

Externí odkaz: https://doaj.org/article/4ad7381aff3f42978a3abfc4857e03ff

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Akademický článek

A comprehensive health assessment approach using ensemble deep learning model for remote patient monitoring with IoT

Autor: Gayathri R, Maheswari S, Sandeep Kumar Mathivanan, Basu Dev Shivahare, Radha Raman Chandan, Mohd Asif Shah

Publikováno v: Scientific Reports, Vol 14, Iss 1, Pp 1-23 (2024)

Abstract The goal of this research is to create an ensemble deep learning model for Internet of Things (IoT) applications that specifically target remote patient monitoring (RPM) by integrating long short-term memory (LSTM) networks and convolutional

Externí odkaz: https://doaj.org/article/cf2b80879bca4f67a2ac94924ecdd80c

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Akademický článek

An efficient approach for automatic crack detection using deep learning

Autor: Usharani, Shola, Gayathri, R., Kovvuri, Uday Surya Deveswar Reddy, Nivas, Maddukuri, Md, Abdul Quadir, Tee, Kong Fah, Sivaraman, Arun Kumar

Publikováno v: International Journal of Structural Integrity, 2024, Vol. 15, Issue 3, pp. 434-460.

Externí odkaz: http://www.emeraldinsight.com/doi/10.1108/IJSI-10-2023-0102

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Akademický článek

Enhancing heart disease prediction with reinforcement learning and data augmentation

Autor: Gayathri R, Sangeetha S．K．B, Sandeep Kumar Mathivanan, Hariharan Rajadurai, Benjula Anbu Malar MB, Saurav Mallik, Hong Qin

Publikováno v: Systems and Soft Computing, Vol 6, Iss , Pp 200129- (2024)

The study presents a novel method to improve the prediction accuracy of cardiac disease by combining data augmentation techniques with reinforcement learning. The complex nature of cardiac data frequently presents challenges for traditional machine l

Externí odkaz: https://doaj.org/article/ae31ff12743f4a9d9782031d03b8dc43

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Hybrid Deep Learning Model using SPCAGAN Augmentation for Insider Threat Analysis

Autor: Gayathri, R G, Sajjanhar, Atul, Xiang, Yong

Cyberattacks from within an organization's trusted entities are known as insider threats. Anomaly detection using deep learning requires comprehensive data, but insider threat data is not readily available due to confidentiality concerns of organizat

Externí odkaz: http://arxiv.org/abs/2203.02855

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