New ML models improve VVLC channel characterization for vehicular OWC.
problem Inaccurate channel models for VVLC due to mobility effects.
method Machine learning (ML) models incorporating ambient light, turbulence, and reflection effects.
result ML models predict VVLC channel loss and CFR more accurately than existing methods.
A fusion of multiple classifiers improves indoor localization using visible light.
problem Indoor localization accuracy and robustness using visible light.
method Transmit different intensity modulated sinusoidal signals, capture peaks of PSD, train multiple classifiers, and combine their outputs using robust fusion algorithms.
result The proposed algorithms significantly improve localization accuracy and robustness compared to existing methods.
Paper explores ML demodulation for VLC, presenting three methods and testing accuracy.
problem Improving demodulation accuracy in VLC systems.
method Three ML demodulation methods: CNN, DBN, AdaBoost.
result AdaBoost achieves the best performance among the three methods.
Study shows high-rise buildings in Dhaka affect mental health, especially lower-income residents.
problem Mental health risks due to high-rise buildings in Dhaka.
method Computer vision pipeline to analyze sky visibility, greenery, and colors in streets.
result Lower-income residents suffer more from lack of sky visibility and greenery in their environment.
Optimizes UAV deployment for VLC-enabled UAVs considering illumination distribution.
problem Optimizing UAV deployment for VLC-enabled UAVs with illumination distribution consideration.
method Formulated as an optimization problem, solved using GRUs and Gaussian mixture model.
result Achieves up to 22.1% reduction in transmit power compared to conventional methods.
Measuring supernova neutrinos removes spacetime's conformal freedom.
problem Determining the conformal factor of spacetime's visible part.
method Measuring neutrino cones in addition to light cones.
result The conformal factor can now be determined.
Designs chiral photonic structures using machine learning for efficient optical properties.
problem Optimizing chiral photonic nanostructures for light-matter interactions.
method Evolutionary algorithm and neural network approach for rapid optimization.
result Frequency-dependent modification in reflected light's degree of circular polarization.
Study uses cGAN to translate multispectral to nighttime satellite imagery.
problem Limited understanding of nighttime satellite imagery composition.
method Adopted and modified pix2pix cGAN framework for multispectral-to-nighttime translation.
result Proves feasibility of multispectral-to-nighttime translation.
NCV uses neural networks to improve Monte Carlo integration.
problem Improving variance reduction in parametric Monte Carlo integration.
method NCV combines a normalizing flow and a neural network to approximate the integrand and solve the integral equation, with a neural importance sampler to estimate the difference.
result NCV achieves state-of-the-art performance in light transport simulation with reduced noise and negligible bias.
Visible Lagrangians in Hitchin systems are studied for pillowcase covers.
problem Visible Lagrangians in Hitchin systems intersecting non-trivially.
method Computation of Fourier-Mukai transforms and study of mirror dual branes.
result Mirror dual branes are closely related to Hausel's toy model.
Characterizes visibility and geodesic loops in complex domains.
problem Visibility and geodesic loops in complex domains.
method Using quasi-geodesic frames to characterize visibility and geodesic loops.
result Characterizes visibility and existence of geodesic loops in Kobayashi complete hyperbolic and Gromov hyperbolic domains.
Study visibility properties of Kobayashi distance on unbounded domains.
problem Understanding visibility properties of Kobayashi distance on unbounded domains.
method Analyzing visibility properties in the context of Kobayashi hyperbolic domains, focusing on unbounded domains and their boundary behavior.
result Carathéodory-type extension theorem for biholomorphisms between planar domains, including infinitely-connected domains.
We show that the translation length of any parabolic isometry on a complete semi-uniformly visible CAT(0) space is always zero. As a consequence, we will classify the isometries on visible CAT(0) spaces in terms of translation lengths. We will also show that the moduli space M(Sg,n) of surface Sg,n o…
Image visibility graphs map images into graphs for processing and classification.
problem Mapping image structures into graphs for processing and classification.
method Introduced image visibility graphs (IVGs) and explored their use in image processing and classification.
result IVGs encapsulate relevant image structure information and are computationally efficient.
Recently, the visibility graph has been introduced as a novel view for analyzing time series, which maps it to a complex network. In this paper, we introduce new algorithm of visibility, "cross-visibility", which reveals the conjugation of two coupled time series. The correspondence between the two time series is mappe…
This article is devoted to the study of prime alternating +achiral knots. In the case of arborescent knots, we prove in +AAA Visibility Theorem 5.1, that the symmetry is visible on a certain projection (not necessarily minimal) and that it is realised by a homeomorphism of order 4. In the general case (arborescent or n…
Improved visibility forecasts using statistical post-processing.
problem Accurate and reliable predictions of visibility are crucial in aviation and transportation.
method Calibrated ensemble forecasts using locally, semi-locally, and regionally trained POLR and MLP classifiers.
result Post-processing improves forecast skill and POLR models outperform MLPs.
The visibility transformation embeds data position into signature features for efficient pattern recognition.
problem Embedding absolute position into signature features for efficient pattern recognition.
method The visibility transformation is put on a theoretical footing and used to embed absolute position into signature features efficiently.
result The generated feature set simplifies pattern recognition by accommodating nonlinear functions of absolute and relative values.
The study shows that the visible range from a point on harmonic manifolds follows an exponential distribution.
problem Understanding the visible range from a point on harmonic manifolds.
method Analyzing Poisson Boolean models on harmonic manifolds, focusing on the geometric mechanism of tube volumes around geodesic segments.
result The visible range from a point on harmonic manifolds follows an exponential distribution.
Optimizes when to post to maximize visibility in social networks.
problem Maximizing post visibility in online social networks.
method Temporal point processes model and convex optimization framework.
result Developed a method to find optimal posting times with provable guarantees.
The Riemann-Theta Boltzmann machine's visible sector is sampled using a discrete multi-variate Gaussian.
problem Sampling the visible sector of the Riemann-Theta Boltzmann machine.
method Discrete multi-variate Gaussian over the hidden state space.
result The visible sector probability density function is an infinite mixture of multi-variate Gaussians.
Proposes MV-Co-VH for multi-view clustering using visible and hidden views.
problem Lack of efficient algorithms for fully utilizing multi-view data.
method Projects multiple views to a common hidden space using NMF, then applies collaborative learning.
result Competitive clustering performance on UCI and real-world datasets.
We study relations of some classes of k-convex, k-visible bodies in Euclidean spaces. We introduce and study \textrm{circular projections} in normed linear spaces and classes of bodies related with families of such maps, in particular, \textrm{k-circular convex} and \textrm{k-circular visible} ones. Investigati…
A visible action on a complex manifold is a holomorphic action that admits a J-transversal totally real submanifold S. It is said to be strongly visible if there exists an orbit-preserving anti-holomorphic diffeomorphism σ such that σ∣S=id. In this paper, we prove that for any Hermitian symmetric sp…
We show that complete uniform visibility manifolds of finite volume with sectional curvature −1≤K≤0 have positive simplicial volumes. This implies that their minimal volumes are non-zero.
Enhances nighttime vehicle detection using style transfer and augmentation.
problem Nighttime object detection challenges due to lack of lighting and glare.
method Day-to-night style transfer and labeling-free augmentation with CARLA synthetic data.
result Significant improvements in nighttime vehicle detection with YOLO11 model.
The paper connects geodesic flows and limit sets on visibility manifolds.
problem Understanding dynamics and ergodic properties on non-compact visibility manifolds.
method Analyzing geodesic flows and Patterson-Sullivan measures on visibility manifolds without conjugate points.
result The positivity of the Patterson-Sullivan measure of the Myrberg limit set is equivalent to the conservativity of the geodesic flow.
Study on visibility properties of spiral sets in higher dimensions.
problem Characterizing density properties of spiral sets.
method Employing visibility concepts from discrete geometry.
result Established conditions for various density properties of spirals.
Structural RBM reduces parameters for image denoising and classification.
problem High parameter count in RBMs limits their applicability to large datasets.
method Introduces SRBM with constrained connections to reduce parameters.
result SRBM achieves better performance and faster training than vanilla RBM.
Characterizes causal structure dominance for latent variables.
problem Determining dominance relations between causal structures with latent variables.
method Complete characterization for three visible variables, partial for four; uses nontrivial inequality constraints.
result Equivalence classes with nontrivial inequality constraints become ubiquitous as the number of visible variables increases.
Extends curvature results to manifolds with close-to-zero curvature.
problem Control homology of manifolds with close-to-zero curvature.
method Constructs efficient simplicial models for the thick part.
result Extends torsion control results to more general curvature conditions.
Study financial market efficiency using visibility graphs and ARCH models.
problem Estimating market efficiency and predicting financial instability.
method Building visibility graphs from financial time series and validating links against ARCH models.
result Proposed market indicator highly correlated with financial instability periods.
The investigations of financial markets from a complex network perspective have unveiled many phenomenological properties, in which the majority of these studies map the financial markets into one complex network. In this work, we investigate 30 world stock market indices through their visibility graphs by adopting the…
Enhanced visibility forecasts using CAMS data improve accuracy.
problem Improving the accuracy of visibility predictions in weather forecasts.
method Statistical post-processing with historical observations and CAMS forecasts.
result Post-processed forecasts with CAMS data are substantially superior to raw and climatological predictions.
Sunshine trading theory predicts lower execution costs and liquidity provision through explicit preannouncements, but evidence is scarce in traditional markets.
problem Adverse selection on liquidity provision
method Reconstructing metaorders and comparing them with visible TWAP executions
result Visible TWAPs face lower execution costs and leave a smaller permanent price impact compared to hidden metaorders.
Paper tackles image recovery from blurry measurements using deep generative priors.
problem Jointly recovering two real-valued signals from phaseless circular convolutions.
method Alternating gradient descent algorithm with deep generative priors.
result Reconstructs quality images from blurry measurements.
Measuring the impact of scientific articles is important for evaluating the research output of individual scientists, academic institutions and journals. While citations are raw data for constructing impact measures, there exist biases and potential issues if factors affecting citation patterns are not properly account…
This paper studies periodic and free periodic knots in alternating projections.
problem Understanding periodic and free periodic knots in alternating projections.
method Analyzing the essential Conway decomposition and Murasugi decomposition of alternating knots.
result Conditions for an alternating knot to be freely periodic are identified.
VGRSI uses price visibility graphs to generate profitable trading signals.
problem Ineffective traditional technical analysis indicators in financial markets.
method Visibility Graphs Relative Strength Index (VGRSI) based on backward visibility relations in price data.
result VGRSI signals generated substantial profits across different asset classes.
Efficiently synthesizes atmospheric cloud images using neural networks and Monte Carlo integration.
problem Rendering atmospheric clouds, especially their characteristic silverlining and whiteness, is challenging.
method Pre-learning the radiant flux distribution from cloud exemplars and using a deep neural network to predict radiance.
result The method synthesizes clouds nearly indistinguishable from reference solutions in seconds.
Study equilibrium measures on manifolds without conjugate points with visibility covering.
problem Uniqueness and properties of equilibrium measures on manifolds without conjugate points.
method Analysis of geodesic flows, study of equilibrium measures, ergodic properties, and pressure gap.
result Equilibrium measures satisfy a weak pressure gap under certain conditions.
A Kronecker product model is the set of visible marginal probability distributions of an exponential family whose sufficient statistics matrix factorizes as a Kronecker product of two matrices, one for the visible variables and one for the hidden variables. We estimate the dimension of these models by the maximum rank …
Transforms web content for better visibility in AI-driven search engines.
problem Disruption of traditional SEO by generative AI search engines.
method Fine-tunes a BART-base transformer on synthetically generated training data.
result Significant improvements in ROUGE-L and BLEU scores, and substantial visibility gains in generative search responses.
The Tits alternative applies to groups acting on specific CAT(0) spaces.
problem Understanding the structure of groups acting on CAT(0) spaces.
method Proving the Tits alternative for groups acting on visibility CAT(0) spaces with bounded packing property.
result Groups either almost nilpotent or contain a free nonabelian subgroup of rank 2.
Introduces a Boltzmann machine with Riemann-Theta functions for continuous and discrete states.
problem Modeling continuous and discrete states in neural networks.
method Develops a Boltzmann machine with continuous visible and discrete hidden states, solving probability density and conditional expectation analytically.
result Derives a novel parametric density function involving Riemann-Theta functions and uses it as an activation function in a feedforward neural network.
The paper confirms a conjecture about the fundamental groups of ends of certain noncompact manifolds.
problem Understanding the fundamental groups of ends of noncompact manifolds with specific curvature properties.
method Analyzing the universal cover and using the concept of visibility manifolds.
result The fundamental group of each end of a manifold is almost nilpotent if its universal cover is a visibility manifold.
This study analyzes economic policy uncertainty indices using visibility graphs.
problem Understanding the role of economic policy uncertainty in global economies.
method Visibility graph algorithm applied to economic policy uncertainty indices.
result The economic policy uncertainty indices exhibit persistent behavior and scale-free networks.
Conditional probabilities modeled using Riemann-Theta Boltzmann Machines.
problem Modeling conditional probabilities in Boltzmann machines.
method Deriving conditional density functions from Riemann-Theta Boltzmann machines.
result Conditional densities can be directly inferred from Riemann-Theta Boltzmann machines.