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๐Ÿ” sven leyffer ๐Ÿ“‚ Engineering
Showing 9682 results for "sven leyffer" in Engineering
Engineering Preprint PDF DOI

Blind OFDM-ISAC Relying on Asymmetric Modem Constellations

Henglin Pu, Ahmad Musallam, Husheng Li, Lajos Hanzo ยท 2026

Integrated sensing and communication (ISAC) is increasingly expected to operate under aggressive spectrum reuse, where co-channel orthogonal frequency division multiplexing (OFDM) interference can be โ€ฆ

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Engineering Preprint PDF DOI

Similarity Choice and Negative Scaling in Supervised Contrastive Learning for Deepfake Audio Detection

Jaskirat Sudan, Hashim Ali, Surya Subramani, Hafiz Malik ยท 2026

Supervised contrastive learning (SupCon) is widely used to shape representations, but has seen limited targeted study for audio deepfake detection. Existing work typically combines contrastive terms wโ€ฆ

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Engineering Preprint PDF DOI

Backstepping Observer for the Quasilinear Heat Equation with Linear Design Gains: Beyond Local Stability

Mohamed Camil Belhadjoudja, Kirsten A. Morris ยท 2026

We consider the one-dimensional quasilinear heat equation with state-dependent heat capacity and thermal conductivity, and design a boundary-output observer based on the backstepping design for a lineโ€ฆ

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Engineering Preprint PDF DOI

ASAP: An Azimuth-Priority Strip-Based Search Approach to Planar Microphone Array DOA Estimation in 3D

Ming Huang, Shuting Xu, Leying Yang, Huanzhang Hu, Yujie Zhang, Jiang Wang, Yu Liu, Hao Zhao, He Kong ยท 2026

Direction-of-arrival (DOA) estimation is an important task in microphone array processing and many downstream applications. The steered response power with phase transform (SRP-PHAT) method has been wโ€ฆ

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Engineering Preprint PDF DOI

Comparative Evaluation of Modern Deep Learning Methodologies for Portfolio Optimization

Samuel Ozechi, Banjo Francis, Wisdom Yakanu, Joe Wayne Byers ยท 2026

This study proposes a portfolio optimization framework that integrates advanced deep learning architectures with traditional financial models to enhance risk-adjusted performance. Using historical datโ€ฆ

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Engineering Preprint PDF DOI

NL-COMM-Sat: Breaking the Direct Device-to-Satellite Communication Barrier via "Aggressive" Non-Orthogonal Transmissions and Non-Linear Processing

Konstantinos Nikitopoulos, Chathura Jayawardena ยท 2026

Direct Device-to-Satellite (D2S) communications, which enable direct satellite connectivity with unmodified user equipment (UE), not only expand global coverage but also reshape the evolution of futurโ€ฆ

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Engineering Preprint PDF DOI

SPLIT: Separating Physical-Contact via Latent Arithmetic in Image-Based Tactile Sensors

Wadhah Zai El Amri, Nicolas Navarro-Guerrero ยท 2026

Training machine learning models for robotic tactile sensing requires vast amounts of data, yet obtaining realistic interaction data remains a challenge due to physical complexity and variability. Simโ€ฆ

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Engineering Preprint PDF DOI

A Road-Mobile GNSS-Disciplined Oscillator for Accurate Synchronization of Vehicular Microwave Measurements

Maximilian Engelhardt, Carsten Andrich, Daniel Stanko, Alexander Ihlow, Markus Landmann ยท 2026

Precise synchronization is essential in various technical disciplines, being especially challenging in mobile scenarios. Unfortunately, state-of-the-art global navigation satellite system (GNSS) disciโ€ฆ

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Engineering Preprint PDF DOI

Safe Navigation in Unknown and Cluttered Environments via Direction-Aware Convex Free-Region Generation

Zhicheng Song, Yongjian Li, Kai Chen, Yulin Li, Fan Shi, Jun Ma ยท 2026

Convex free regions provide a structured and optimization-friendly representation of collision-free space for robot navigation in unknown and cluttered environments. However, existing methods typicallโ€ฆ

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Engineering Preprint PDF DOI

Unsupervised Learning for AC Optimal Power Flow with Fast Physics-Aware Layer

Jiebao Zhang, Haoyu Yan, Haoyu Wang, Ye Shi, Zhichao Sheng, Hongwen Yu, Shuang Ye, Zhifang Yang ยท 2026

Learning to solve the Alternating Current Optimal Power Flow (AC-OPF) problem by neural networks (NNs) is a promising approach in real-time applications. Existing methods to ensure the physical feasibโ€ฆ

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Engineering Preprint PDF DOI

Signal Processing Foundations of Reconfigurable Antennas in the Tri-Hybrid MIMO Architecture

Nitish Vikas Deshpande, Joseph Carlson, Siyun Yang, Mohamed Akrout, Alfredo Gonzalez, Miguel Rodrigo Castellanos, Tharmalingam Ratnarajah, Chan-Byoung Chae, Robert W. Heath Jr ยท 2026

To enable larger apertures in multipleinput multipleoutput MIMO systems the trihybrid MIMO architecture offers a promising lowcost and lowpower solution by introducing reconfigurable antennas as a thiโ€ฆ

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Engineering Preprint PDF DOI

An Efficient Beam Search Algorithm for Active Perception in Mobile Robotics

Kaixian Qu, Han Wang, Victor Klemm, Cesar Cadena, Marco Hutter ยท 2026

Active perception is a fundamental problem in autonomous robotics in which the robot must decide where to move and what to sense in order to obtain the most informative observations for accomplishing โ€ฆ

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Engineering Preprint PDF DOI

An Interactive Graphical Tool to Check the Coarray Continuity of Two-Fold Redundant Sparse Arrays (TFRSAs) Under Single Sensor Failures

Namya Malik, Ashish Patwari, Sangeetha N ยท 2026

Two-fold redundant sparse arrays possess inbuilt redundancy to tackle single-element failures. This property enables them to perform accurate direction of arrival (DOA) estimation even during single sโ€ฆ

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Engineering Preprint PDF DOI

A 99-Line Homogenization Code for Lattice-skin Plate Structures

Zhongkai Ji, Dawei Li, Yong Zhao, Wenhe Zhao ยท 2026

Recent years have seen growing application potential for Lattice-skin Plate Structures in advanced manufacturing fields such as aerospace and automotive engineering. For multiscale performance evaluatโ€ฆ

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Engineering Preprint PDF DOI

An Algebraic State Observer for a Class of Physical Systems

Alexey Bobtsov, Jose Guadalupe Romero, Romeo Ortega, Anton Pyrkin ยท 2026

In this paper we present a radically new approach to design state observers for nonlinear systems, with particular emphasis on physical ones. Our objective is to obtain an algebraic relation between tโ€ฆ

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Engineering Preprint PDF DOI

Equivariant Filter for Radar-Inertial Odometry

Giulio Delama, Jan Michalczyk, Morten Nissov, Martin Scheiber, Alessandro Fornasier, Kostas Alexis, Stephan Weiss ยท 2026

Radar-Inertial Odometry (RIO) based on the Extended Kalman Filter (EKF) relies on accurate extrinsic calibration between the radar and the Inertial Measurement Unit (IMU) and is sensitive to disturbanโ€ฆ

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Engineering Preprint PDF DOI

Triple-Phase Sequential Fusion Network for Hepatobiliary Phase Liver MRI Synthesis

Qiuli Wang, Xinhuan Sun, Fengxi Chen, Yongxu Liu, Jie Cheng, Lin Chen, Jiafei Chen, Yue Zhang, Xiaoming Li, Wei Chen ยท 2026

Gadoxetate disodium-enhanced MRI is essential for the detection and characterization of hepatocellular carcinoma. However, acquisition of the hepatobiliary phase (HBP) requires a prolonged post-contraโ€ฆ

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Engineering Preprint PDF DOI

A Kinematic Analysis of Palm Degrees of Freedom for Enhancing Thumb Opposability in Robotic Hands

HyoJae Kang, Yeong Jae Park, Hyunmok Jung, Joonho Lee, Dong Il Park ยท 2026

This study investigates the kinematic role of palm degrees of freedom (DoF) in enhancing thumb opposability in a five-finger robotic hand. A hand model consisting of a five DoF thumb and four fingers โ€ฆ

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Engineering Preprint PDF DOI

Multimodal Diffusion to Mutually Enhance Polarized Light and Low Resolution EBSD Data

Harry Dong, Timofey Efimov, Megna Shah, Jeff Simmons, Sean Donegan, Marc De Graef, Yuejie Chi ยท 2026

In spite of the utility of 3-D electron back-scattered diffraction (EBSD) microscopy, the data collection process can be time-consuming with serial-sectioning. Hence, it is natural to look at other moโ€ฆ

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Engineering Preprint PDF DOI

An LLM-Driven Closed-Loop Autonomous Learning Framework for Robots Facing Uncovered Tasks in Open Environments

Hong Su ยท 2026

Autonomous robots operating in open environments need the ability to continuously handle tasks that are not covered by predefined local methods. However, existing approaches often rely on repeated larโ€ฆ

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