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Storage Assignment using Nested Annealing and Hamming Distances

The assignment of products to storage locations significantly impacts the efficiency of warehouse operations. We propose a multi-phase optimizer for a Storage Location Assignment Problem (SLAP) where solution quality is based on a distance estimate of future-forecasted order picking. Candidate assignments are first sampled using a Markov Chain accept/reject method. Future-forecasted pick-rounds ar

Testing Abstractions for Cyber-Physical Control Systems

Control systems are ubiquitous and often at the core of Cyber-Physical Systems, like cars and aeroplanes. They are implemented as embedded software, that interacts in closed loop with the physical world through sensors and actuators. As a consequence, the software cannot just be tested in isolation. To close the loop in a testing environment and root causing failure generated by different parts of

Development and initial validation of a multivariable predictive Early Adversity Scale for Schizophrenia (EAS-Sz) using register data to quantify environmental risk for adult schizophrenia diagnosis after childhood exposure to adversity

Background Additional to a child's genetic inheritance, environmental exposures are associated with schizophrenia. Many are broadly described as childhood adversity; modelling the combined impact of these is complex. We aimed to develop and validate a scale on childhood adversity, independent of genetic and other environmental liabilities, for use in schizophrenia risk analysis models, using data

Implementation of Sequential Detection of Replay Attacks for a Cloud Native Controller

This paper focuses on the investigation of a sequential detection policy for combating the effect of the replay attack on a cloud-native controller. In reply attacks, an external attacker records true signals for some time duration and replays them later. The effect of such an attack is mitigated by adding random signals to the optimal control signal before the actuation process, which is known as

Which aspects of visual motivation aid the implicit learning of signs at first exposure?

We investigated whether sign-naïve learners can infer and learn the meaning of signs after minimal exposure to continuous, naturalistic input in the form of a weather forecast in Swedish Sign Language. Participants were L1-English adults. Two experimental groups watched the forecast once (N=40) or twice (N=42); a control group did not (N=42). Participants were then asked to assign meaning to 22 ta

From dilute to concentrated solutions of intrinsically disordered proteins : Interpretation and analysis of collected data

Intrinsically disordered proteins (IDPs) have a broad energy landscape and consequently sample many different conformations in solution. The innate flexibility of IDPs is exploited in their biological function, and in many instances allows a single IDP to regulate a range of processes in vivo. Due to their highly flexible nature, characterizing the structural properties of IDPs is not straightforw

Afterload system design for functional donor heart assessment

Heart transplantation is a life-saving procedure for patients with end-stage heart failure. However, conservative acceptance criteria result in most donated hearts being discarded. Enabling clinicians to assess heart function after organ procurement can pave the way for the safe use of hearts that are currently rejected. This thesis focuses on improving techniques for the direct, controlled assess

Highly Hygroscopic Aerosols Facilitate Summer and Early-Autumn Cloud Formation at Extremely Low Concentrations Over the Central Arctic Ocean

Arctic clouds are sensitive to atmospheric particles since these are sometimes in such low concentrations that clouds cannot always form under supersaturated water vapor conditions. This is especially true in the late summer, when aerosol concentrations are generally very low in the high Arctic. The environment changes rapidly around freeze-up as the open waters close and snow starts accumulating

Privacy Preserving Localization via Coordinate Permutations

Recent methods on privacy-preserving image-based localization use a random line parameterization to protect the privacy of query images and database maps. The lifting of points to lines effectively drops one of the two geometric constraints traditionally used with point-to-point correspondences in structure-based localization. This leads to a significant loss of accuracy for the privacy-preserving

Gas-to-Particle Partitioning of Products from Ozonolysis of Δ3-Carene and the Effect of Temperature and Relative Humidity

Formation of oxidized products from Δ3-carene (C10H16) ozonolysis and their gas-to-particle partitioning at three temperatures (0, 10, and 20 °C) under dry conditions (<2% RH) and also at 10 °C under humid (78% RH) conditions were studied using a time-of-flight chemical ionization mass spectrometer (ToF-CIMS) combined with a filter inlet for gases and aerosols (FIGAERO). The Δ3-carene ozonolysis p

Verification of Low-Dimensional Neural Network Control

We verify safety of a nonlinear continuous-time system controlled by a neural network controller. The system is decomposed into low-dimensional subsystems connected in a feedback loop. Our application is a rocket landing, and open-loop properties of the two-dimensional altitude subsystem are verified using worst-case simulations. Closed-loop safety properties (crash-avoidance) of the full system a

An Empirically Grounded Path Forward for Scenario-Based Testing of Autonomous Driving Systems

Testing of autonomous driving systems (ADS) is a crucial, yet complex task that requires different approaches to ensure the safety and reliability of the system in various driving scenarios. Currently, there is a lack of understanding of the industry practices for testing such systems, and also the related challenges. To this end, we conduct a secondary analysis of our previous exploratory study,

FuseRank (Demo) : Filtered Vector Search in Multimodal Structured Data

We describe and demonstrate our work on multimodal filtered vector search in tabular data. It offers a practical way for businesses to vectorize their product assortments or any other business-critical data and then simultaneously retrieve and filter this information using state-of-the-art similarity search. Our methodology is based on the extended vector space model, with multiple modalities repr

Force-based semantic representation and estimation of feature points for robotic cable manipulation with environmental contacts

This work demonstrates the utility of dual-arm robots with dual-wrist force-torque sensors in manipulating a Deformable Linear Object (DLO) within an unknown environment that imposes constraints on the DLO’s movement through contacts and fixtures. We propose a strategy to estimate the pose of unknown environmental contacts encountered during the manipulation of a DLO, classifying the induced const

Towards automated inclusion of autoxidation chemistry in models : from precursors to atmospheric implications

In the last few decades, atmospheric formation of secondary organic aerosols (SOA) has gained increasing attention due to their impact on air quality and climate. However, methods to predict their abundance are mainly empirical and may fail under real atmospheric conditions. In this work, a close-to-mechanistic approach allowing SOA quantification is presented, with a focus on a chain-like chemica