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Automated covariate modeling using efficient simulation of pharmacokinetics

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

Generating Executable Test Scenarios from Autonomous Vehicle Disengagements using Natural Language Processing

With the emergence of autonomous vehicles comes requirements on adequate and rigorous testing techniques, particularly as systems continuously adapt to changing environments. Scenario-based, simulated testing is one approach that has received attention, where deriving relevant scenarios from various sources is still a challenge. We therefore explore creating executable test scenarios from textual

Hardware and Software Generation from Large Actor Machines in Streaming Applications

Streaming applications, such as MPEG video encoders or sensor processing pipelines, are increasing in complexity as well as the diversity of platforms that they run on. The toolchains handling these applications must keep up with this increase at all levels of abstraction. The Actor Machine (AM) is an intermediate representation in the toolchain that we make use of. Large AMs are difficult to work

Over 20 years of observations in the boreal forest reveal a decreasing trend of atmospheric new particle formation

New particle formation (NPF) events substantially contribute to the number concentration of atmospheric particles and cloud condensation nuclei (CCN) which can further influence radiative balance and Earth's climate. Many short-term studies have found that sulfuric acid (H2 SO4) and highly oxygenated organic molecules (HOM) are critical compounds in the early steps of NPF. However, it is not fully

HHAI 2024: Hybrid Human AI Systems for the Social Good : Proceedings of the Third International Conference on Hybrid Human-Artificial Intelligence

The field of hybrid human-artificial intelligence (HHAI), although primarily driven by developments in AI, also requires fundamentally new approaches and solutions. Multidisciplinary in nature, it calls for collaboration across various research domains, such as AI, HCI, the cognitive and social sciences, philosophy and ethics, and complex systems, to name but a few. This book presents the proceedi

Seamless integration of target-controlled infusion and closed-loop anesthesia

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

Autonomous navigation with convergence guarantees in complex dynamic environments

This article addresses the obstacle avoidance problem for setpoint stabilization tasks in complex dynamic 2-D environments that go beyond conventional scenes with isolated convex obstacles. A combined motion planner and controller is proposed that integrates the favorable convergence characteristics of closed-form motion planning techniques with the intuitive representation of system constraints t

Certified MaxSAT Preprocessing

Building on the progress in Boolean satisfiability (SAT) solving over the last decades, maximum satisfiability (MaxSAT) has become a viable approach for solving NP-hard optimization problems. However, ensuring correctness of MaxSAT solvers has remained a considerable concern. For SAT, this is largely a solved problem thanks to the use of proof logging, meaning that solvers emit machine-verifiable

Certifying Without Loss of Generality Reasoning in Solution-Improving Maximum Satisfiability

Proof logging has long been the established method to certify correctness of Boolean satisfiability (SAT) solvers, but has only recently been introduced for SAT-based optimization (MaxSAT). The focus of this paper is solution-improving search (SIS), in which a SAT solver is iteratively queried for increasingly better solutions until an optimal one is found. A challenging aspect of modern SIS solve

Pseudo-Boolean Reasoning About States and Transitions to Certify Dynamic Programming and Decision Diagram Algorithms

Pseudo-Boolean proof logging has been used successfully to provide certificates of optimality from a variety of constraint- and satisifability-style solvers that combine reasoning with a backtracking or clause-learning search. Another paradigm, occurring in dynamic programming and decision diagram solving, instead reasons about partial states and possible transitions between them. We describe a fr

Small Antenna Q and Gain – 80 Years of Progress

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.

Towards Declarative Specification of Static Analysis for Programming Tools

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,

Critical Scenario Identification for Testing of Realistic Autonomous Driving Systems

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

A socio-institutional perspective on the reluctance among the elderly concerning the commercialization of 3D surgical video technology in Sweden

The pursuit of commercialization is at the core of economic activity, and limited commercialization success is generally ascribed to the lower scalability or potential of the venture. Drawing on the anti-profit-taking socio-institutional perspective and innovation resistance theory, commercialization of a value-creating technology could be resisted from the demand side. We use a 3D surgical video

Human, What Must I Tell You?

Artificial intelligence (AI)-assisted code generation is everywhere these days. Undoubtedly, AI will help near-future developers substantially by providing code suggestions and automation. In this application, explainability will be a key quality attribute.

Channel hardening in massive mimo : Model parameters and experimental assessment

Reliability is becoming increasingly important for many applications envisioned for future wireless systems. A technology that could improve reliability in these systems is massive MIMO (Multiple- Input Multiple-Output). One reason for this is a phenomenon called channel hardening, which means that as the number of antennas in the system increases, the variations of channel gain decrease in both t

NO at low concentration can enhance the formation of highly oxygenated biogenic molecules in the atmosphere

The interaction between nitrogen monoxide (NO) and organic peroxy radicals (RO2) greatly impacts the formation of highly oxygenated organic molecules (HOM), the key precursors of secondary organic aerosols. It has been thought that HOM production can be significantly suppressed by NO even at low concentrations. Here, we perform dedicated experiments focusing on HOM formation from monoterpenes at l

Effect of frequency and load on efficiency of inductive wireless power transfer systems

Wireless charging of smartphones using inductive wireless power transfer (IWPT) has become very popular. However, the efficiency of IWPT systems can decrease substantially when the transmitting and receiving coils are not closely coupled. One popular approach to mitigate the efficiency degradation is to utilize higher frequency. However, the higher efficiency is only achieved at a specific range o

LassoBench : A High-Dimensional Hyperparameter Optimization Benchmark Suite for Lasso

While Weighted Lasso sparse regression has appealing statistical guarantees that would entail a major real-world impact in finance, genomics, and brain imaging applications, it is typically scarcely adopted due to its complex high-dimensional space composed by thousands of hyperparameters. On the other hand, the latest progress with high-dimensional hyperparameter optimization (HD-HPO) methods for