Tootfinder

Potential and challenges of generative adversarial networks for super-resolution in 4D Flow MRI
Oliver Welin Odeback, Arivazhagan Geetha Balasubramanian, Jonas Schollenberger, Edward Ferdiand, Alistair A. Young, C. Alberto Figueroa, Susanne Schnell, Outi Tammisola, Ricardo Vinuesa, Tobias Granberg, Alexander Fyrdahl, David Marlevi
https://…

Potential and challenges of generative adversarial networks for super-resolution in 4D Flow MRI
4D Flow Magnetic Resonance Imaging (4D Flow MRI) enables non-invasive quantification of blood flow and hemodynamic parameters. However, its clinical application is limited by low spatial resolution and noise, particularly affecting near-wall velocity measurements. Machine learning-based super-resolution has shown promise in addressing these limitations, but challenges remain, not least in recovering near-wall velocities. Generative adversarial networks (GANs) offer a compelling solution, having…

Low-Complexity Equalization of Zak-OTFS in the Frequency Domain
Sandesh Rao Mattu, Nishant Mehrotra, Saif Khan Mohammed, Venkatesh Khammammetti, Robert Calderbank
https://arxiv.org/abs/2508.07148

Low-Complexity Equalization of Zak-OTFS in the Frequency Domain
4G/5G wireless standards use orthogonal frequency division multiplexing (OFDM) which is robust to frequency selectivity. Equalization is possible with a single tap filter, and low-complexity equalization makes OFDM an attractive physical layer. However the performance of OFDM degrades with mobility, since Doppler spreads introduce inter-carrier interference (ICI) between subcarriers and they are no longer orthogonal. Zak-transform based orthogonal time frequency space (Zak-OTFS) modulation has …

An Ecosystem for Ontology Interoperability
Zhangcheng Qiang
https://arxiv.org/abs/2507.12311 https://arxiv.org/pdf/2507.12311

An Ecosystem for Ontology Interoperability
Ontology interoperability is one of the complicated issues that restricts the use of ontologies in knowledge graphs (KGs). Different ontologies with conflicting and overlapping concepts make it difficult to design, develop, and deploy an interoperable ontology for downstream tasks. We propose an ecosystem for ontology interoperability. The ecosystem employs three state-of-the-art semantic techniques in different phases of the ontology engineering life cycle: ontology design patterns (ODPs) in t…

A Survey of End-to-End Modeling for Distributed DNN Training: Workloads, Simulators, and TCO
Jonas Svedas, Hannah Watson, Nathan Laubeuf, Diksha Moolchandani, Abubakr Nada, Arjun Singh, Dwaipayan Biswas, James Myers, Debjyoti Bhattacharjee
https://arxiv.org/abs/2506.09275

A Survey of End-to-End Modeling for Distributed DNN Training: Workloads, Simulators, and TCO
Distributed deep neural networks (DNNs) have become a cornerstone for scaling machine learning to meet the demands of increasingly complex applications. However, the rapid growth in model complexity far outpaces CMOS technology scaling, making sustainable and efficient system design a critical challenge. Addressing this requires coordinated co-design across software, hardware, and technology layers. Due to the prohibitive cost and complexity of deploying full-scale training systems, simulators …

[Announce] Create: Harvard Crimson on Discrimination ComplaintsNearly…
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CoSight: Exploring Viewer Contributions to Online Video Accessibility Through Descriptive Commenting
Ruolin wang, Xingyu Liu, Biao Wang, Wayne Zhang, Ziqian Liao, Ziwen Li, Amy Pavel, Xiang 'Anthony' Chen
https://arxiv.org/abs/2508.08582

CoSight: Exploring Viewer Contributions to Online Video Accessibility Through Descriptive Commenting
The rapid growth of online video content has outpaced efforts to make visual information accessible to blind and low vision (BLV) audiences. While professional Audio Description (AD) remains the gold standard, it is costly and difficult to scale across the vast volume of online media. In this work, we explore a complementary approach to broaden participation in video accessibility: engaging everyday video viewers at their watching and commenting time. We introduce CoSight, a Chrome extension th…

Enhancing Software Vulnerability Detection Through Adaptive Test Input Generation Using Genetic Algorithm
Yanusha Mehendran, Maolin Tang, Yi Lu
https://arxiv.org/abs/2508.05923 …

Enhancing Software Vulnerability Detection Through Adaptive Test Input Generation Using Genetic Algorithm
Software vulnerabilities continue to undermine the reliability and security of modern systems, particularly as software complexity outpaces the capabilities of traditional detection methods. This study introduces a genetic algorithm-based method for test input generation that innovatively integrates genetic operators and adaptive learning to enhance software vulnerability detection. A key contribution is the application of the crossover operator, which facilitates exploration by searching acros…

Adaptive Job Scheduling in Quantum Clouds Using Reinforcement Learning
Waylon Luo (Kent State University), Jiapeng Zhao (Cisco), Tong Zhan (Meta), Qiang Guan (Kent State University)
https://arxiv.org/abs/2506.10889

Adaptive Job Scheduling in Quantum Clouds Using Reinforcement Learning
Present-day quantum systems face critical bottlenecks, including limited qubit counts, brief coherence intervals, and high susceptibility to errors-all of which obstruct the execution of large and complex circuits. The advancement of quantum algorithms has outpaced the capabilities of existing quantum hardware, making it difficult to scale computations effectively. Additionally, inconsistencies in hardware performance and pervasive quantum noise undermine system stability and computational accu…

Zak-OFDM: Low Complexity Joint Equalization of OFDM Carriers in Doubly-Spread Channels
Saif Khan Mohammed, Sandesh Rao Mattu, Nishant Mehrotra, Venkatesh Khammammetti, Robert Calderbank
https://arxiv.org/abs/2506.23045

Zak-OFDM: Low Complexity Joint Equalization of OFDM Carriers in Doubly-Spread Channels
We communicate over wireless channels by first estimating and then equalizing the effective channel. In Zak-OTFS (orthogonal time frequency space) modulation the carrier waveform is a pulse in the delay-Doppler (DD) domain, formally a quasi-periodic localized function with specific periods along delay and Doppler. When the channel delay spread is less than the delay period, and the channel Doppler spread is less than the Doppler period, the response to a single Zak-OTFS carrier provides an imag…

Delay-Doppler Domain Signal Processing Aided OFDM (DD-a-OFDM) for 6G and Beyond
Yiyan Ma, Bo Ai, Jinhong Yuan, Shuangyang Li, Qingqing Cheng, Zhenguo Shi, Weijie Yuan, Zhiqiang Wei, Akram Shafie, Guoyu Ma, Yunlong Lu, Mi Yang, Zhangdui Zhong
https://arxiv.org/abs/2508.04253

Delay-Doppler Domain Signal Processing Aided OFDM (DD-a-OFDM) for 6G and Beyond
High-mobility scenarios will be a critical part of 6G systems. Since the widely deployed orthogonal frequency division multiplexing (OFDM) waveform suffers from subcarrier orthogonality loss under severe Doppler spread, delay-Doppler domain multi-carrier (DDMC) modulation systems, such as orthogonal time frequency space (OTFS), have been extensively studied. While OTFS can exploit time-frequency (TF) domain channel diversity, it faces challenges including high receiver complexity and inflexible…