2026
article
OpenAlex
Matthew A. Powell, Lars Christian Hanker, Sharad Ghamande, Lucy Gilbert et autres
us, de, no, ca, it, gb, nl, be, by, dk
(code pays fourni par la source)
2025
article
OpenAlex
Brian M. Slomovitz, Kristina Lindemann, Matthew Powell, Filip Frühauf et autres
us, no, cz, ca, it, de, nl, dk
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2025
conference-paper
OpenAlex
Sudarshan Kumar Sharma, Jinhyeok Park, Hemant Kumawat, Saibal Mukhopadhyay
Static Frequency Modulated Continuous Wave (FMCW) radar sensing treats all scenes uniformly, resulting in inefficient resource usage given that naturally occurring scenes vary in complexity. Prior adaptive schemes depend on compute heavy online learning methods, leading to high compute cost and latency, …
us
(code pays fourni par la source)
2025
conference-paper
OpenAlex
Jinhyeok Park, Sudarshan Kumar Sharma, W. J. Wang, Alex Saad-Falcon et autres
Radar sensor systems often suffer from suboptimal performance in dynamic environments due to static front-end configurations. While cognitive radar approaches have been proposed to address this issue through adaptive processing, they are often computationally intensive and unsuitable for real-time deployment. This work …
us
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2025
article
OpenAlex
Bhavana Pothuri, Jørn Herrstedt, Evelyn L. Fleming, Олена Миколаївна Сухіна et autres
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Accès ouvert
2025
article
OpenAlex
Matthew A. Powell, Line Bjørge, Lyndsay J. Willmott, Z. Novák et autres
Summary What is the purpose of this PLS-P? The purpose of this plain language summary of publication is to help you understand recent findings from Part 1 of the RUBY study (full name ENGOT-EN6/GOG3031/RUBY trial). • Researchers sometimes study new combinations of …
us, no, hu, ca, it, de, nl, il, be, dk
(code pays fourni par la source)
2025
conference-paper
OpenAlex
Alex Saad–Falcon, Yashas Devarajaiah, Wei‐Chun Wang, Sudarshan Kumar Sharma et autres
Testing array processing algorithms requires realistic data that captures both hardware non-idealities and environmental complexities, but collecting comprehensive experimental datasets is often impractical. We present an open-source end-to-end simulator that addresses this challenge by providing a modular, GPU-accelerated framework for evaluating array …
us
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2025
article
OpenAlex
Coleman DeLude, Sudarshan Kumar Sharma, Wei Chun Wang, Saibal Mukhopadhyay et autres
The demands of modern multi-sensor array applications put stress on every aspect of the processing pipeline, resulting in extremely power-hungry systems. In this paper we investigate a new method of broadband beamforming which, leveraging reduced dimension Slepian processing, has been demonstrated to …
us
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2025
conference-paper
OpenAlex
Narasimha Vasishta Kidambi, Wen Wang, Daehyun Kim, Sudarshan Kumar Sharma et autres
An 8T-SRAM-based Mixed-Signal Computing-In-Memory (MS-CIM) is demonstrated in 65nm CMOS for solving Integer-Constrained Least Square problems. The test-chip consumes 21.76mW (at 1.2V) and requires 720us to solve a 20-input 16-output Integer Constrained Least Square (ICLS) problem generating solutions with quality ranking in …
us
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Accès ouvert
2025
article
OpenAlex
Benoît You, Charles K Anderson, Sabrina Chiara Cecere, Aurore Carrot et autres
PURPOSE: Adding the anti-PD-L1 antibody atezolizumab to frontline chemotherapy-bevacizumab regimen did not improve progression-free survival (PFS) in ovarian cancer (OC) patients in IMagyn050 trial. This post-hoc analysis assessed the efficacy of atezolizumab in a subgroup of patients with particularly poor prognosis, as …
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Accès ouvert
2025
article
OpenAlex
Lalita Negi, Sudarshan Kumar Sharma, Kavita Mardi, Shivani Sood et autres
Histoplasmosis mostly shows bilateral adrenal gland involvement in immunocompromised patients. Our case is of a 43 years old immunocompetent male patient having pain in the left flank for one month. CECT abdomen revealed a well-defined hypodense mass measuring 64×61×56 mm with necrotic …
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2025
article
OpenAlex
Minah Lee, Sudarshan Kumar Sharma, Wei Chun Wang, Saibal Mukhopadhyay
This paper introduces the Artificial Intelligence-Driven Energy-efficient Analog-to-Learning system (AIDEAL), an AI-enabled in-sensor computing platform designed to enhance energy efficiency in edge devices through in situ data processing. AIDEAL extracts task-relevant features from analog inputs, significantly reducing the data volume for digitization …
us
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