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๐Ÿ” sam devlin ๐Ÿ“‚ Engineering
Showing 2174 results for "sam devlin" in Engineering
Engineering Preprint PDF DOI

Doppler Robust Vortex Wavefront Design for Integrated Sensing and Communication

Yuan Liu, Wen-Xuan Long, M. R. Bhavani Shankar, Marco Moretti, Rui Chen, Bjorn Ottersten ยท 2025

Integrated sensing and communication (ISAC) is a promising paradigm for future wireless systems due to spectrum reuse, hardware sharing, and joint waveform design. In dynamic scenes, Doppler shifts deโ€ฆ

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Engineering Preprint PDF DOI

A BTR-Based Approach for Detection of Infrared Small Targets

Ke-Xin Li ยท 2025

Infrared small target detection plays a crucial role in military reconnaissance and air defense systems. However,existing low-rank sparse based methods still face high computational complexity when deโ€ฆ

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Engineering Preprint PDF DOI

Crossing the Sim2Real Gap Between Simulation and Ground Testing to Space Deployment of Autonomous Free-flyer Control

Kenneth Stewart, Samantha Chapin, Roxana Leontie, Carl Glen Henshaw ยท 2025

Reinforcement learning (RL) offers transformative potential for robotic control in space. We present the first on-orbit demonstration of RL-based autonomous control of a free-flying robot, the NASA Asโ€ฆ

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Engineering Preprint PDF DOI

Zero-Forcing MU-MIMO Precoding under Power Amplifier Non-Linearities

Juan Vidal Alegria, Ashkan Sheikhi, Ove Edfors ยท 2025

In multi-user multiple-input multiple-output (MU-MIMO) systems, the non-linear behavior of the power amplifiers (PAs) may cause degradation of the linear precoding schemes dealing with interference beโ€ฆ

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Engineering Preprint PDF DOI

Deterministic Sort-Free Candidate Pruning for Scalable MIMO Box Decoding

Shengchun Yang, Amit Sravan Bora, Emil Matus, Gerhard Fettweis ยท 2025

Box Decoding is a sort-free tree-search MIMO detector whose complexity is independent of the QAM order, achieved by searching a fixed candidate box around a zero-forcing (ZF) estimate. However, withouโ€ฆ

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Engineering Preprint PDF DOI

What If They Took the Shot? A Hierarchical Bayesian Framework for Counterfactual Expected Goals

Mikayil Mahmudlu, Oktay Karakus, Hasan Arkadas ยท 2025

This study develops a hierarchical Bayesian framework that integrates expert domain knowledge to quantify player-specific effects in expected goals (xG) estimation, addressing a limitation of standardโ€ฆ

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Engineering Preprint PDF DOI

MICCAI STS 2024 Challenge: Semi-Supervised Instance-Level Tooth Segmentation in Panoramic X-ray and CBCT Images

Yaqi Wang, Zhi Li, Chengyu Wu, Jun Liu, Yifan Zhang, Jiaxue Ni, Qian Luo, Jialuo Chen, Hongyuan Zhang, Jin Liu, Can Han, Kaiwen Fu, Changkai Ji, Xinxu Cai, Jing Hao, Zhihao Zheng, Shi Xu, Junqiang Chen, Qianni Zhang, Dahong Qian, Shuai Wang, Huiyu Zhou ยท 2025

Orthopantomogram (OPGs) and Cone-Beam Computed Tomography (CBCT) are vital for dentistry, but creating large datasets for automated tooth segmentation is hindered by the labor-intensive process of manโ€ฆ

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Engineering Preprint PDF DOI

Comparing SAM 2 and SAM 3 for Zero-Shot Segmentation of 3D Medical Data

Satrajit Chakrabarty, Ravi Soni ยท 2025

Foundation models, such as the Segment Anything Model (SAM), have heightened interest in promptable zero-shot segmentation. Although these models perform strongly on natural images, their behavior on โ€ฆ

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Engineering Preprint PDF DOI

CoC-VLA: Delving into Adversarial Domain Transfer for Explainable Autonomous Driving via Chain-of-Causality Visual-Language-Action Model

Dapeng Zhang, Fei Shen, Rui Zhao, Yinda Chen, Peng Zhi, Chenyang Li, Rui Zhou, Qingguo Zhou ยท 2025

Autonomous driving represents a prominent application of artificial intelligence. Recent approaches have shifted from focusing solely on common scenarios to addressing complex, long-tail situations suโ€ฆ

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Engineering Preprint PDF DOI

Understanding Risk and Revenue in the Nordic 15-minute mFRR market: An EV Aggregation Study

Theodor Hagstrom, Lars Herre ยท 2025

Decarbonisation, decentralisation, and intermittency are driving the development of flexibility markets towards shorter market time units (MTU). Shorter MTUs and shorter gate closures lower the entranโ€ฆ

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A Multi-Stage Deep Learning Framework with PKCP-MixUp Augmentation for Pediatric Liver Tumor Diagnosis Using Multi-Phase Contrast-Enhanced CT

Wanqi Wang, Chun Yang, Jianbo Shao, Yaokai Zhang, Xuehua Peng, Jin Sun, Chao Xiong, Long Lu, Lianting Hu ยท 2025

Pediatric liver tumors are one of the most common solid tumors in pediatrics, with differentiation of benign or malignant status and pathological classification critical for clinical treatment. While โ€ฆ

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Engineering Preprint PDF DOI

Not Quite Anything: Overcoming SAMs Limitations for 3D Medical Imaging

Keith Moore ยท 2025

Foundation segmentation models such as SAM and SAM-2 perform well on natural images but struggle with brain MRIs where structures like the caudate and thalamus lack sharp boundaries and have low contrโ€ฆ

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Engineering Preprint PDF DOI

SAC-MoE: Reinforcement Learning with Mixture-of-Experts for Control of Hybrid Dynamical Systems with Uncertainty

Leroy D'Souza, Akash Karthikeyan, Yash Vardhan Pant, Sebastian Fischmeister ยท 2025

Hybrid dynamical systems result from the interaction of continuous-variable dynamics with discrete events and encompass various systems such as legged robots, vehicles and aircrafts. Challenges arise โ€ฆ

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Physics-informed Machine Learning for Static Friction Modeling in Robotic Manipulators Based on Kolmogorov-Arnold Networks

Yizheng Wang, Timon Rabczuk, Yinghua Liu ยท 2025

Friction modeling plays a crucial role in achieving high-precision motion control in robotic operating systems. Traditional static friction models (such as the Stribeck model) are widely used due to tโ€ฆ

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Engineering Preprint PDF DOI

Constellation Design and Detection under Generalized Hardware Impairments

Thrassos K. Oikonomou, Dimitrios Tyrovolas, Sotiris A. Tegos, Panagiotis D. Diamantoulakis, Panagiotis Sarigiannidis, George K. Karagiannidis ยท 2025

This paper presents a maximum-likelihood detection framework that jointly mitigates hardware (HW) impairments in both amplitude and phase. By modeling transceiver distortions as residual amplitude andโ€ฆ

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Deep Learning Analysis of Prenatal Ultrasound for Identification of Ventriculomegaly

Youssef Megahed, Inok Lee, Robin Ducharme, Aylin Erman, Olivier X. Miguel, Kevin Dick, Adrian D. C. Chan, Steven Hawken, Mark Walker, Felipe Moretti ยท 2025

The proposed study aimed to develop a deep learning model capable of detecting ventriculomegaly on prenatal ultrasound images. Ventriculomegaly is a prenatal condition characterized by dilated cerebraโ€ฆ

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Engineering Preprint PDF DOI

Over-the-Air Transmission of Zak-OTFS on mmWave Communications Testbed

Sabarinath Ramachandran, Venkatesh Khammammetti, Prasanthi Maddala, Narayan Mandayam, Ivan Seskar, Robert Calderbank ยท 2025

Millimeter-wave (mmWave) communication offers vast bandwidth for next-generation wireless systems but faces severe path loss, Doppler effects, and hardware impairments. Orthogonal Time Frequency Spaceโ€ฆ

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Engineering Preprint PDF DOI

SAMora: Enhancing SAM through Hierarchical Self-Supervised Pre-Training for Medical Images

Shuhang Chen, Hangjie Yuan, Pengwei Liu, Hanxue Gu, Tao Feng, Dong Ni ยท 2025

The Segment Anything Model (SAM) has demonstrated significant potential in medical image segmentation. Yet, its performance is limited when only a small amount of labeled data is available, while therโ€ฆ

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Engineering Preprint PDF DOI

Location-Informed Interference Suppression Precoding Methods for Distributed Massive MIMO Systems

Emiel Vanspranghels, Raquel Marina Noguera Oishi, Franco Minucci, Sofie Pollin ยท 2025

The evolution of mobile networks towards user-centric cell-free distributed Massive MIMO configurations requires the development of novel signal processing techniques. More specifically, digital precoโ€ฆ

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Engineering Preprint PDF DOI

Multi-Region Matrix Interpolation for Dynamic Analysis of Aperiodic Structures under Large Model Parameter Perturbations

J. Pereira, R. O. Ruiz ยท 2025

This work introduces a surrogate-based model for efficiently estimating the frequency response of dynamic mechanical metamaterials, particularly when dealing with large parametric perturbations and apโ€ฆ

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