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๐Ÿ” laszlo kozma ๐Ÿ“‚ Engineering
Showing 714 results for "laszlo kozma" in Engineering
Engineering Preprint PDF DOI

A Realistic Discrete Event Simulation model for Ambulance Location and Deployment within a regional Emergency Medical Service

Alberto De Santis, Stefania Iannazzo, Fabio Ingravalle, Stefano Lucidi, Massimo Maurici, Giulia Riccardi, Massimo Roma, Antonio Vinci ยท 2026

The objective of Emergency Medical Services (EMSs) is to promptly respond to calls from citizens for first aid, providing pre-hospital care and, if necessary, to transfer patients to an appropriate Emโ€ฆ

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Complex Approximate Message Passing with Non-separable Denoising

Vishnu Teja Kunde, Alessandro Mirri, Jean-Francois Chamberland, Enrico Paolini ยท 2026

Approximate Message Passing (AMP) is a general framework for iterative algorithms, originally developed for compressed sensing and later extended to a wide range of high-dimensional inference problemsโ€ฆ

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Predicting food taste with bound-driven optimization

Pagkratis Tagkopoulos, Dimitris Sfondilis, Ilias Tagkopoulos, Tarek Zohdi ยท 2026

The prediction of sensory attributes from ingredient-level formulations is an emerging challenge at the intersection of food science and artificial intelligence. We address the fundamental question ofโ€ฆ

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RSMA-Aided Full-Duplex Networks Under Imperfect CSI and SIC: Performance Evaluation

Farjam Karim, Nurul Huda Mahmood, Deepak Kumar, Arthur Sousa de Sena, Matti-Latva-aho ยท 2026

This work investigates a full-duplex (FD)-enhanced Rate-Splitting Multiple Access (RSMA) system under practical constraints, including imperfect channel state information (CSI) and successive interferโ€ฆ

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Engineering Preprint PDF DOI

Data-driven augmentation of first-principles models under constraint-free well-posedness and stability guarantees

Bendeguz Gyorok, Roel Drenth, Chris Verhoek, Tamas Peni, Maarten Schoukens, Roland Toth ยท 2026

The integration of first-principles models with learning-based components, i.e., model augmentation, has gained increasing attention, as it offers higher model accuracy and faster convergence propertiโ€ฆ

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Engineering Preprint PDF DOI

WARPED: Wrist-Aligned Rendering for Robot Policy Learning from Egocentric Human Demonstrations

Harry Freeman, Chung Hee Kim, George Kantor ยท 2026

Recent advancements in learning from human demonstration have shown promising results in addressing the scalability and high cost of data collection required to train robust visuomotor policies. Howevโ€ฆ

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Data-Driven Unknown Input Reconstruction for MIMO Systems with Convergence Guarantees

Enno Breukelman, Takumi Shinohara, Joowon Lee, Henrik Sandberg ยท 2026

In this paper, we consider data-driven reconstruction of unknown inputs to linear time-invariant (LTI) multiple-input multiple-output (MIMO) systems. We propose a novel autoregressive estimator based โ€ฆ

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Unlocking the Energy-Saving Potential in O-RAN Cell-Free Massive MIMO by Joint Orchestration of Radio, Wireless Fronthaul, and Cloud Resources

Ozan Alp Topal, Ozlem Tugfe Demir, Emil Bjornson, Cicek Cavdar ยท 2026

Network virtualization and cloudification in Open Radio Access Networks (O-RAN) enable joint orchestration of the processing and fronthaul resources, which are essential for realizing the energy-savinโ€ฆ

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Receding-Horizon Nonlinear Optimal Control With Safety Constraints Using Constrained Approximate Dynamic Programming

Ricardo Gutierrez, Jesse B. Hoagg ยท 2026

We present a receding-horizon optimal control for nonlinear continuous-time systems subject to state constraints. The cost is a quadratic finite-horizon integral. The key enabling technique is a new cโ€ฆ

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Influence of the geometry on the mechanical performance of tubular interlockings: A study of the Sine Block

Domen Macek, Meike Wei{ss}, Reymond Akpanya, Tim Brepols, Hagen Holthusen, Alice C. Niemeyer ยท 2026

Topological interlocking assemblies (TIA) are arrangements of blocks such that rigid-body motions of the blocks are fully constrained by their neighbours and a fixed frame. In this work, we investigatโ€ฆ

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Predictor-Based Output-Feedback Control of Linear Systems with Time-Varying Input and Measurement Delays via Neural-Approximated Prediction Horizons

Luke Bhan, Miroslav Krstic, Yuanyuan Shi ยท 2026

Due to simplicity and strong stability guarantees, predictor feedback methods have stood as a popular approach for time delay systems since the 1950s. For time-varying delays, however, implementation โ€ฆ

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LiZIP: An Auto-Regressive Compression Framework for LiDAR Point Clouds

Aditya Shibu, Kayvan Karim, Claudio Zito ยท 2026

The massive volume of data generated by LiDAR sensors in autonomous vehicles creates a bottleneck for real-time processing and vehicle-to-everything (V2X) transmission. Existing lossless compression mโ€ฆ

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Damage identification using noisy frequency response functions based on topology optimization

Akira Saito, Ryo Sugai, Zhongxu Wang, Hidetaka Saomoto ยท 2026

This paper proposes a robust damage identification method using noisy frequency response functions (FRFs) and topology optimization. We formulate the damage identification problem as an inverse probleโ€ฆ

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Linear-Quadratic Gaussian Games with Distributed Sparse Estimation

Tianyu Qiu, Filippos Fotiadis, Xinjie Liu, Christian Ellis, Jesse Milzman, Wesley Suttle, Ufuk Topcu, David Fridovich-Keil ยท 2026

Linear-quadratic Gaussian games provide a framework for modeling strategic interactions in multi-agent systems, where agents must estimate system states from noisy observations while also making decisโ€ฆ

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Bayesian and Classical Feature Ranking for Interpretable BLDC Fault Diagnosis

Waldemar Bauer, Jerzy Baranowski ยท 2026

This paper compares Bayesian and classical feature ranking methods for interpretable fault diagnosis of brushless DC (BLDC) motors. Two Bayesian approaches, spike-and-slab and ARD logistic ranking, arโ€ฆ

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Data-Driven Physics Embedded Dynamics with Predictive Control and Reinforcement Learning for Quadrupeds

Prakrut Kotecha, Aditya Shirwatkar, Shishir Kolathaya ยท 2026

State of the art quadrupedal locomotion approaches integrate Model Predictive Control (MPC) with Reinforcement Learning (RL), enabling complex motion capabilities with planning and terrain adaptive beโ€ฆ

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Load-Aware Locomotion Control for Humanoid Robots in Industrial Transportation Tasks

Lequn Fu, Yijun Zhong, Xiao Li, Yibin Liu, Zhiyuan Xu, Jian Tang, Shiqi Li ยท 2026

Humanoid robots deployed in industrial environments are required to perform load-carrying transportation tasks that tightly couple locomotion and manipulation. However, achieving stable and robust locโ€ฆ

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Characterizing Healthy & Post-Stroke Neuromotor Behavior During 6D Upper-Limb Isometric Gaming: Implications for Design of End-Effector Rehabilitation Robot Interfaces

Ajay Anand, Gabriel Parra, Chad A. Berghoff, Laura A. Hallock ยท 2026

Successful robot-mediated rehabilitation requires designing games and robot interventions that promote healthy motor practice. However, the interplay between a given user's neuromotor behavior, the gaโ€ฆ

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Robust Cooperative Output Regulation of Discrete-Time Heterogeneous Multi-Agent Systems

Kursad Metehan Gul, Selahattin Burak Sarsilmaz ยท 2026

This article considers robust cooperative output regulation of discrete-time uncertain heterogeneous (in dimension) multi-agent systems (MASs). We show that the solvability of this problem with an intโ€ฆ

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On the Spectrum of OTFS/VOFDM Signals: PSD Analysis and Bandwidth Allocation

Wei Wang, Xiang-Gen Xia ยท 2026

Orthogonal time frequency space (OTFS)/vector OFDM (VOFDM) is widely regarded as a promising waveform for next-generation mobile communications. However, its spectral characteristics are not yet fullyโ€ฆ

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