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This Ph.D. dissertation contains results in two different but related fields: the implementation of model predictive control (MPC) in embedded systems using first order methods, and restart schemes for accelerated first order methods…
This paper proposes an iterative distributionally robust model predictive control (MPC) scheme to solve a risk-constrained infinite-horizon optimal control problem. In each iteration, the algorithm generates a trajectory from the starting…
Complex dynamical systems frequently encounter a recurrent structural instability: the collapse of the spectral gap, driving the system toward a low-dimensional "Zero-Mode Attractor" (e.g., spectral pile-up or over-smoothing). Building upon…
Colorectal cancer (CRC) is highly heterogeneous, with five-year survival rates dropping from $\sim$90% in localized disease to $\sim$15% with distant metastases. Disease progression is shaped not only by tumor-intrinsic alterations but also…
Automated vehicles require efficient and safe planning to maneuver in uncertain environments. Largely this uncertainty is caused by other traffic participants, e.g., surrounding vehicles. Future motion of surrounding vehicles is often…
Understanding the effects of spin-orbit coupling (SOC) and many-body interactions on spin transport is important in condensed matter physics and spintronics. This topic has been intensively studied for spin carriers such as electrons but…
Lasso peptides constitute a class of bioactive peptides sharing a knotted structure where the C-terminal tail of the peptide is threaded through and trapped within an N-terminalmacrolactamring. The structural characterization of lasso…
Solar sails enable propellant-free space missions by utilizing solar radiation pressure as thrust. However, disturbance torques act on the solar sail and effective attitude control leads to the continuous accumulation of reaction wheel…
The spin splitting driven by spin-orbit coupling in monolayer (ML) transition metal dichalcogenides (TMDCs) family has been widely studied only for the 1H-phase structure, while it is not profound for the 1T-phase structure due to the…
Magic-sized clusters (MSCs) are renowned for their identical size and closed-shell stability that inhibit conventional nanoparticle (NP) growth processes. Though MSCs have been of increasing interest, understanding the reaction pathways…
CLIC is a proposed linear $e^+e^-$ collider with center-of-mass energies of up to 3 TeV. Its main objectives are precise top quark, Higgs boson and Beyond Standard Model physics. In addition to spatial resolutions of a few micrometers and a…
Here we present the theoretical clarification of possibility of eight Majorana-like modes (quasi-particles which are self-conjugate) close to the experimentally inaccessible Dirac points of a two-dimensional monolayer Dirac system. The…
Certification for machine learning is proving that no adversarial sample can evade a model within a range under certain conditions, a necessity for safety-critical domains. Common certification methods for segmentation use a flat set of…
Deep learning models for medical image classification usually achieve promising results but typically rely on large, annotated datasets or standard transfer learning from ImageNet. Self-Supervised Learning (SSL) has emerged as a powerful…
Detecting fraudulent credit card transactions remains a significant challenge, due to the extreme class imbalance in real-world data and the often subtle patterns that separate fraud from legitimate activity. Existing research commonly…
To improve logical anomaly detection, some previous works have integrated segmentation techniques with conventional anomaly detection methods. Although these methods are effective, they frequently lead to unsatisfactory segmentation results…
Control of non-condensing non-ideal-gas power cycles is challenging because their output power dynamics depend on complex system interactions, non-ideal-gas effects complicate turbomachinery behavior, and state constraints must be…
We propose a robust adaptive Model Predictive Control (MPC) strategy with online set-based estimation for constrained linear systems with unknown parameters and bounded disturbances. A sample-based test applied to predicted trajectories is…
The optimal performance of robotic systems is usually achieved near the limit of state and input bounds. Model predictive control (MPC) is a prevalent strategy to handle these operational constraints, however, safety still remains an open…
Electronic spin superposition states enable nanoscale sensing through their sensitivity to the local environment, yet their sensitivity to vibrational motion also limits their coherence times. In molecular spin systems, chemical tunability…