The ability to forecast grass fire spread could be of a great importance for agencies making decisions about prescribed burns. However, the usefulness of the models used for fire-spread predictions is limited by the time required for completing the c...
We present a new realization of relativistic hadronic me- chanics and its underlying iso-Poincar'e symmetry specifically constructed for nuclear physics which: 1) permits the representation of nucleons as ex- tended, nonspherical and deformable cha...
We present an approach for mobile robots to recognize scenes in object arrangements distributed across cluttered environments. Recognition is enabled by intertwining the robot's search for objects and the assignment of found objects to scenes. Our sc...
This paper presents a gradient based motion estimation algorithm based on shape-motion prediction, which takes advantage of the correlation between neighboring Binary Alpha Blocks (BABs), to match with the Mpeg-4 shape coding case and speed up the...
Agent assistance during human-human customer support spoken interactions requires triggering workflows based on the caller's intent (reason for call). Timeliness of prediction is essential for a good user experience. The goal is for a system to detec...
We note that there is an exception to the general arguments that no falsifiable predictions can be made, on the basis of of presently available data, by applying the weak anthropic principle (WAP) to the landscape of string theory. If there are inf...
This paper is part of a publication series from the For5G project that has the goal of creating digital twins of sweet cherry trees. At the beginning a brief overview of the revious work in this project is provided. Afterwards the focus shifts to a c...
While diffusion models can successfully generate data and make predictions, they are predominantly designed for static images. We propose an approach for efficiently training diffusion models for probabilistic spatiotemporal forecasting, where genera...
We compare the predictions of the fundamentally motivated minimal coupling ($\hat{\boldsymbol{p}}\cdot\hat{\boldsymbol{A}}$) and the ubiquitous dipole coupling ($\hat{\boldsymbol{x}}\cdot\hat{\boldsymbol{E}}$) in the light-matter interaction. By stud...
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WOW this week episodes are so fun and full of twists so I just want to share some of my thoughts and predictions for the finale. • **Minasue vs Seungil vs Subeen:** \-\*sign\* Minasue…our drama ...
Machine Learning Interatomic Potentials (MLIP) are a novel in silico approach for molecular property prediction, creating an alternative to disrupt the accuracy/speed trade-off of empirical force fields and density functional theory (DFT). In this wh...
With former President **Yoon Suk-yeol**, who has been indicted and faces a death penalty demand on charges of being the ringleader of an insurrection, awaiting his first trial verdict on the 19th, a p...
Predicting the biophysical and functional properties of proteins is essential for in silico protein design. Machine learning has emerged as a promising technique for such prediction tasks. However, the relative scarcity of in vitro annotations means...
A fundamental difficulty of studying gas-liquid pipe flows is the prediction of the occurrence and characteristics of the slug flow regime, which plays a crucial role in the safety design of oil pipelines. Current empirical methods and one-dimensiona...
We present the results of a large library of cosmological N-body simulations, using power-law initial spectra. The nonlinear evolution of the matter power spectra is compared with the predictions of existing analytic scaling formulae based on the w...
This paper studies how insurers can chose which claims to investigate for fraud. Given a prediction model, typically only claims with the highest predicted propability of being fraudulent are investigated. We argue that this can lead to inconsistent...
A novel approach to wall modeling for the incompressible Navier-Stokes equations including flows of moderate and large Reynolds numbers is presented. The basic idea is that a problem-tailored function space allows prediction of turbulent boundary lay...
We present an analytic model for blue straggler formation in globular clusters. We assume that blue stragglers are formed only through stellar collisions and binary star evolution, and compare our predictions to observed blue straggler numbers taken...
Formula One (F1) race strategy takes place in a high-pressure and fast-paced environment where split-second decisions can drastically affect race results. Two of the core decisions of race strategy are when to make pit stops (i.e. replace the cars' t...