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The anesthetic drug propofol is commonly used to control hypnotic depth (suppression of awareness) in patients undergoing surgery or intensive care. In addition to manual titration, a model-based open-loop feed-forward strategy called target-controlled infusion (TCI) has attained some clinical popularity. Research on closed-loop control, with awareness estimates derived from an electroencephalogra
Normalizing flows (NFs) have been shown to be advantageous in modeling complex distributions and improving sampling efficiency for unbiased sampling. In this work, we propose a new class of continuous NFs, ascent continuous normalizing flows (ACNFs), that makes a base distribution converge faster to a target distribution. As solving such a flow is non-trivial and barely possible, we propose a prac
The understanding of small antennas has evolved tremendously since the initial investigations close to 80 years ago. In this presentation, we highlight some fundamental results on Q-factor, bandwidth, and gain.
Static program analysis plays a crucial role in ensuring the quality and security of software applications by detecting bugs and potential vulnerabilities in the code. Traditionally, these analyses are performed offline, either as part of the continuous integration/continuous deployment pipeline or overnight on the entire repository. However, this delayed feedback disrupts developer productivity,
Background: Testing is imperative to validate the functionalities and safety of autonomous driving systems. Simulated scenario-based testing is commonly adopted for autonomous driving systems, which aims to construct various driving scenarios and validate the autonomous driving systems in simulation. Nevertheless, identifying relevant test scenarios, especially critical ones that expose hazards or
Researchers have envisioned and pioneered data-driven programming assistance for developers based on their interaction with the tools via multiple sensors such as eye trackers, microphones, and AI. However, these new sensors gather sensitive data from programmers, to what extent users can accept them and in what form they may work well are largely unclear. Meanwhile, developer tools such as static
Static analysis tools play a crucial role in software development by detecting bugs and vulnerabilities. However, running these tools separately from the code editing process often causes developers to switch contexts, which can reduce productivity. Previous work has shown how Reference Attribute Grammars (RAGs) can be used for declarative implementation of competitive tooling for intraprocedural
Background and objective:This study aims to enhance the performance of a closed-loop anesthetic depth control system by fusing noise-corrupted clinical measurements with a non-perfect pharmacological model.Methods:We implement a Kalman filter to constitute a trade-off between model prediction and measurement signal dependence for depth of hypnosis (DoH) control using a previously evaluated PID con
Understanding and effectively managing Technical Debt (TD) remains a vital challenge in software engineering. While many studies on code-level TD have been published, few illustrate the business impact of low-quality source code. In this study, we combine two publicly available datasets to study the association between code quality on the one hand, and defect count and implementation time on the o
In this paper we propose a technique to enhance the performance of a Proportional-Integral-Derivative (PID)-based control structure for Depth-of-Hypnosis control in total intravenous anesthesia when set-point changes are required during the maintenance phase. In particular, the PID controller, tuned for disturbance rejection, is integrated with a feedforward action based on Model Predictive Contro
Two-view estimation is a fundamental problem in 3D computer vision, and an important sub-task of multi-view estimation pipelines such as Structure-from-Motion (SfM) and Simultaneous Localization and Mapping (SLAM). In recent years, the main focus in the field has been on keypoint-based methods, where interest points are first detected and matched across the two images, followed by robust estimatio
Internet of Things (IoT) are one of the key enablers of personalized health. However, IoT devices often have stringent constraints in terms of resources, e.g., energy budget, and, therefore, limited possibilities to exploit the state-of-the-art Deep Neural Networks (DNNs). Energy-aware Neural Architecture Search (NAS) is proposed to tackle this challenge, by exploring lightweight DNN (DNN) archite
Many problems in computer vision can be formulated as geometric estimation problems, i.e. given a collection of measurements (e.g. point correspondences) we wish to fit a model (e.g. an essential matrix) that agrees with our observations. This necessitates some measure of how much an observation 'agrees' with a given model. A natural choice is to consider the smallest perturbation that makes the o
JavaDL ArtifactJavaDL is a language and toolchain for analyzing Java at the source level. JavaDL is based on MetaDL, a variant of Datalog that adds syntactic pattern matching, here specialized to pattern matching on Java.
Linear quadratic (LQ) control optimizes a quadratic cost function while following a linear model. It is commercially available in the process industry but often not labeled as such and infrequently used. Froth flotation is a process in the minerals industry that extracts precious metals from a slurry of finely ground rock in consecutive tanks called cells. Flotation cells are often arranged in two
In the last column, we promised to return to one of the inevitable challenges that vibe coding leaves us with. At the AI Engineer World’s Fair 2025, OpenAI’s Sean Grove claimed that whoever writes the specification is now the programmer since AI can take it from there. Sounds amazing, but what gets lost along the way? To explore this, I’m joined by Jan-Philipp Steghöfer, a researcher at XITASO and
Driving automation systems, including autonomous driving and advanced driver assistance, are an important safety-critical domain. Such systems often incorporate perception systems that use machine learning to analyze the vehicle environment. We explore new or differing topics and challenges experienced by practitioners in this domain, which relate to requirements engineering (RE), quality, and sys
Pharmacometric modeling plays an important role in drug development and personalized medicine. Pharmacometric covariate models can be used to describe the relationships between patient characteristics (such as age and weight) and pharmacokinetic (PK) parameters. Traditionally, the functional structure of these relationships are obtained manually. This is a time-consuming task, and consequently lim
We present property probes, a mechanism for helping a developer explore partial program analysis results in terms of the source program interactively while the program is edited. A node locator data structure is introduced that maps between source code spans and program representation nodes, and that helps identify probed nodes in a robust way, after modifications to the source code. We have devel
Human physiology is the study of how organisms, organ systems, and individual organs function under normal circumstances. As a consequence of its paramount importance to medicine, physiology has been studied since ancient times, but the models studied in this book follow the tradition of modern physiology pioneered by Claude Bernard in the mid 1800s.The focus of the book lies on how dynamical mech
