Tootfinder

Long time behavior of a degenerate stochastic system modeling the response of a population face to environmental impacts
Pierre Collet (CPHT), Claire Ecoti\`ere (CMAP,MERGE), Sylvie M\'el\'eard (CMAP,MERGE)
https://arxiv.org/abs/2405.01898

Long time behavior of a degenerate stochastic system modeling the response of a population face to environmental impacts
We study the asymptotics of a two-dimensional stochastic differential system with a degenerate diffusion matrix. This system describes the dynamics of a population where individuals contribute to the degradation of their environment through two different behaviors. We exploit the almost one-dimensional form of the dynamical system to compute explicitly the Freidlin-Wentzell action functional. That allows to give conditions under which the small noise regime of the invariant measureis concentrat…

This https://arxiv.org/abs/2307.06647 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

DeepIPCv2: LiDAR-powered Robust Environmental Perception and Navigational Control for Autonomous Vehicle
We present DeepIPCv2, an autonomous driving model that perceives the environment using a LiDAR sensor for more robust drivability, especially when driving under poor illumination conditions where everything is not clearly visible. DeepIPCv2 takes a set of LiDAR point clouds as the main perception input. Since point clouds are not affected by illumination changes, they can provide a clear observation of the surroundings no matter what the condition is. This results in a better scene understandin…

This https://arxiv.org/abs/2307.06647 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

DeepIPCv2: LiDAR-powered Robust Environmental Perception and Navigational Control for Autonomous Vehicle
We present DeepIPCv2, an autonomous driving model that perceives the environment using a LiDAR sensor for more robust drivability, especially when driving under poor illumination conditions where everything is not clearly visible. DeepIPCv2 takes a set of LiDAR point clouds as the main perception input. Since point clouds are not affected by illumination changes, they can provide a clear observation of the surroundings no matter what the condition is. This results in a better scene understandin…

Morphodynamics of chloroplast network control light-avoidance response in the non-motile dinoflagellate Pyrocystis lunula
Nico Schramma, Gloria Casas Canales, Maziyar Jalaal
https://arxiv.org/abs/2404.19570 https://arxiv.org/pdf/2404.19570
arXiv:2404.19570v1 Announce Type: new
Abstract: Photosynthetic algae play a significant role in oceanic carbon capture. Their performance, however, is constantly challenged by fluctuations in environmental light conditions. Here, we show that the non-motile single-celled marine dinoflagellate Pyrocystis lunula can internally contract its chloroplast network in response to light. By exposing the cell to various physiological light conditions and applying temporal illumination sequences, we find that network morphodynamics follows simple rules, as established in a mathematical model. Our analysis of the chloroplast structure reveals that its unusual reticulated morphology constitutes properties similar to auxetic metamaterials, facilitating drastic deformations for light-avoidance, while confined by the cell wall. Our study shows how the topologically complex network of chloroplasts is crucial in supporting the dinoflagellate's adaptation to varying light conditions, thereby facilitating essential life-sustaining processes.

This https://arxiv.org/abs/2404.14563 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

Exploring Algorithmic Explainability: Generating Explainable AI Insights for Personalized Clinical Decision Support Focused on Cannabis Intoxication in Young Adults
This study explores the possibility of facilitating algorithmic decision-making by combining interpretable artificial intelligence (XAI) techniques with sensor data, with the aim of providing researchers and clinicians with personalized analyses of cannabis intoxication behavior. SHAP analyzes the importance and quantifies the impact of specific factors such as environmental noise or heart rate, enabling clinicians to pinpoint influential behaviors and environmental conditions. SkopeRules simpl…

Assessing Quality Metrics for Neural Reality Gap Input Mitigation in Autonomous Driving Testing
Stefano Carlo Lambertenghi, Andrea Stocco
https://arxiv.org/abs/2404.18577

Assessing Quality Metrics for Neural Reality Gap Input Mitigation in Autonomous Driving Testing
Simulation-based testing of automated driving systems (ADS) is the industry standard, being a controlled, safe, and cost-effective alternative to real-world testing. Despite these advantages, virtual simulations often fail to accurately replicate real-world conditions like image fidelity, texture representation, and environmental accuracy. This can lead to significant differences in ADS behavior between simulated and real-world domains, a phenomenon known as the sim2real gap. Researchers have u…

Enhancing Robot Navigation Efficiency Using Cellular Automata with Active Cells
Saleem Alzoubi, Mahdi H. Miraz
https://arxiv.org/abs/2404.01885 https://

Enhancing Robot Navigation Efficiency Using Cellular Automata with Active Cells
Enhancing robot navigation efficiency is a crucial objective in modern robotics. Robots relying on external navigation systems are often susceptible to electromagnetic interference (EMI) and encounter environmental disturbances, resulting in orientation errors within their surroundings. Therefore, the study employed an internal navigation system to enhance robot navigation efficacy under interference conditions, based on the analysis of the internal parameters and the external signals. This art…

Towards Environmental Preference Based Speech Enhancement For Individualised Multi-Modal Hearing Aids
Jasper Kirton-Wingate, Shafique Ahmed, Adeel Hussain, Mandar Gogate, Kia Dashtipour, Jen-Cheng Hou, Tassadaq Hussain, Yu Tsao, Amir Hussain
https://arxiv.org/abs/2402.16757

Towards Environmental Preference Based Speech Enhancement For Individualised Multi-Modal Hearing Aids
Since the advent of Deep Learning (DL), Speech Enhancement (SE) models have performed well under a variety of noise conditions. However, such systems may still introduce sonic artefacts, sound unnatural, and restrict the ability for a user to hear ambient sound which may be of importance. Hearing Aid (HA) users may wish to customise their SE systems to suit their personal preferences and day-to-day lifestyle. In this paper, we introduce a preference learning based SE (PLSE) model for future mul…

Outdoor Environment Reconstruction with Deep Learning on Radio Propagation Paths
Hrant Khachatrian, Rafayel Mkrtchyan, Theofanis P. Raptis
https://arxiv.org/abs/2402.17336

Outdoor Environment Reconstruction with Deep Learning on Radio Propagation Paths
Conventional methods for outdoor environment reconstruction rely predominantly on vision-based techniques like photogrammetry and LiDAR, facing limitations such as constrained coverage, susceptibility to environmental conditions, and high computational and energy demands. These challenges are particularly pronounced in applications like augmented reality navigation, especially when integrated with wearable devices featuring constrained computational resources and energy budgets. In response, th…

Estimating Metocean Environments Associated with Extreme Structural Response
Matthew Speers, David Randell, Jonathan Angus Tawn, Philip Jonathan
https://arxiv.org/abs/2404.16775 <…

Estimating Metocean Environments Associated with Extreme Structural Response
Extreme value analysis (EVA) uses data to estimate long-term extreme environmental conditions for variables such as significant wave height and period, for the design of marine structures. Together with models for the short-term evolution of the ocean environment and for wave-structure interaction, EVA provides a basis for full probabilistic design analysis. Environmental contours provide an alternate approach to estimating structural integrity, without requiring structural knowledge. These con…

This https://arxiv.org/abs/2403.18703 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Fpga-Based Neural Thrust Controller for UAVs
The advent of unmanned aerial vehicles (UAVs) has improved a variety of fields by providing a versatile, cost-effective and accessible platform for implementing state-of-the-art algorithms. To accomplish a broader range of tasks, there is a growing need for enhanced on-board computing to cope with increasing complexity and dynamic environmental conditions. Recent advances have seen the application of Deep Neural Networks (DNNs), particularly in combination with Reinforcement Learning (RL), to i…

Environmental monitoring using orbital angular momentum mode decomposition enhanced machine learning
Zhaozhong Chen, Ultan Daly, Aleksandr Boldin, Lenny Hirsch, Mingjian Cheng, Martin P. J. Lavery
https://arxiv.org/abs/2403.19179

Environmental monitoring using orbital angular momentum mode decomposition enhanced machine learning
Atmospheric interaction with light has been an area of fascination for many researchers over the last century. Environmental conditions, such as temperature and wind speed, heavily influence the complex and rapidly varying optical distortions propagating optical fields experience. The continuous random phase fluctuations commonly make deciphering the exact origins of specific optical aberrations challenging. The generation of eddies is a major contributor to atmospheric turbulence, similar in g…

This https://arxiv.org/abs/2402.16177 has been replaced.
initial toot: https://mastoxiv.page/@arX…

Enhancing the Environmental Stability of Perovskite Thin Films via PMMA and AZ5214-Photoresist Coatings
We introduce a pioneering strategy to enhance the environmental stability of perovskite thin films, a critical step forward in advancing their application in optoelectronics. Through the innovative application of matrix encapsulation techniques, we focus on the stabilization of methylammonium lead iodide (MAPbI3) and methylammonium lead bromide (MAPbBr3) films. These films are meticulously prepared via a two-step solution deposition method under controlled ambient conditions. Our approach invol…

This https://arxiv.org/abs/2402.03346 has been replaced.
link: https://scholar.google.com/scholar?q=a

Models, methods and algorithms for monitoring environmental impact on agricultural production
The article analyzes the impact of environmental conditions on agricultural production in the Aral Sea region. The development of mathematical models for solving the problems of optimizing agricultural production, the spread of dust and salt particles from above-ground sources of heavy and light aerosols, depending on meteorological conditions, algorithmic and managerial decision-making methods is scientifically substantiated. It is also proposed to develop methods and tools for interactive ana…

This https://arxiv.org/abs/2312.07204 has been replaced.
initial toot: https://mastoxiv.page/@ar…

Performance testing of gas-tight portable RPC for muography applications
This paper reports the latest developmental efforts for a position-sensitive glass-based Resistive Plate Chamber (RPC) and a multi-channel Data AcQuisition (DAQ) system tailored for muon tracking in muography applications. The designed setup prioritizes portability, aiming for field applications where both the detector and the DAQ operate effectively in external environmental conditions. Comprehensive discussions on hardware development activities and signal processing techniques are included, …

Exploring Algorithmic Explainability: Generating Explainable AI Insights for Personalized Clinical Decision Support Focused on Cannabis Intoxication in Young Adults
Tongze Zhang, Tammy Chung, Anind Dey, Sang Won Bae
https://arxiv.org/abs/2404.14563

Exploring Algorithmic Explainability: Generating Explainable AI Insights for Personalized Clinical Decision Support Focused on Cannabis Intoxication in Young Adults
This study explores the possibility of facilitating algorithmic decision-making by combining interpretable artificial intelligence (XAI) techniques with sensor data, with the aim of providing researchers and clinicians with personalized analyses of cannabis intoxication behavior. SHAP analyzes the importance and quantifies the impact of specific factors such as environmental noise or heart rate, enabling clinicians to pinpoint influential behaviors and environmental conditions. SkopeRules simpl…

Environmental monitoring using orbital angular momentum mode decomposition enhanced machine learning
Zhaozhong Chen, Ultan Daly, Aleksandr Boldin, Lenny Hirsch, Mingjian Cheng, Martin P. J. Lavery
https://arxiv.org/abs/2403.19179

Environmental monitoring using orbital angular momentum mode decomposition enhanced machine learning
Atmospheric interaction with light has been an area of fascination for many researchers over the last century. Environmental conditions, such as temperature and wind speed, heavily influence the complex and rapidly varying optical distortions propagating optical fields experience. The continuous random phase fluctuations commonly make deciphering the exact origins of specific optical aberrations challenging. The generation of eddies is a major contributor to atmospheric turbulence, similar in g…

This https://arxiv.org/abs/2402.05243 has been replaced.
link: https://scholar.google.com/scholar?q=a

Biological computation through recurrence
One of the defining features of living systems is their adaptability to changing environmental conditions. This requires organisms to extract temporal and spatial features of their environment, and use that information to compute the appropriate response. In the last two decades, a growing body or work, mainly coming from the machine learning and computational neuroscience fields, has shown that such complex information processing can be performed by recurrent networks. In those networks, tempo…

Fpga-Based Neural Thrust Controller for UAVs
Sharif Azem, David Scheunert, Mengguang Li, Jonas Gehrunger, Kai Cui, Christian Hochberger, Heinz Koepp
https://arxiv.org/abs/2403.18703

Fpga-Based Neural Thrust Controller for UAVs
The advent of unmanned aerial vehicles (UAVs) has improved a variety of fields by providing a versatile, cost-effective and accessible platform for implementing state-of-the-art algorithms. To accomplish a broader range of tasks, there is a growing need for enhanced on-board computing to cope with increasing complexity and dynamic environmental conditions. Recent advances have seen the application of Deep Neural Networks (DNNs), particularly in combination with Reinforcement Learning (RL), to i…

This https://arxiv.org/abs/2401.09678 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

Integrating Graceful Degradation and Recovery through Requirement-driven Adaptation
Cyber-physical systems (CPS) are subject to environmental uncertainties such as adverse operating conditions, malicious attacks, and hardware degradation. These uncertainties may lead to failures that put the system in a sub-optimal or unsafe state. Systems that are resilient to such uncertainties rely on two types of operations: (1) graceful degradation, to ensure that the system maintains an acceptable level of safety during unexpected environmental conditions and (2) recovery, to facilitate …

This https://arxiv.org/abs/2309.08909 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

CARLA-Loc: Synthetic SLAM Dataset with Full-stack Sensor Setup in Challenging Weather and Dynamic Environments
The robustness of SLAM (Simultaneous Localization and Mapping) algorithms under challenging environmental conditions is critical for the success of autonomous driving. However, the real-world impact of such conditions remains largely unexplored due to the difficulty of altering environmental parameters in a controlled manner. To address this, we introduce CARLA-Loc, a synthetic dataset designed for challenging and dynamic environments, created using the CARLA simulator. Our dataset integrates a…

This https://arxiv.org/abs/1904.09300 has been replaced.
link: https://scholar.google.com/scholar?q=a

Merging galaxies in isolated environments I. Multiband photometry, classification, stellar masses, and star formation rates
Extragalactic surveys provide significant statistical data for the study of crucial galaxy parameters used to constrain galaxy evolution, e.g. stellar mass (M$_*$) and star formation rate (SFR), under different environmental conditions. These quantities are derived using manual or automatic methods for galaxy detection and flux measurement in imaging data at different wavelengths. The reliability of these automatic measurements, however, is subject to mis-identification and poor fitting due to …

This https://arxiv.org/abs/2310.17625 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

The metallicity dependence and evolutionary times of merging binary black holes: Combined constraints from individual gravitational-wave detections and the stochastic background
The advent of gravitational-wave astronomy is now allowing for the study of compact binary merger demographics throughout the Universe. This information can be leveraged as tools for understanding massive stars, their environments, and their evolution. One active question is the nature of compact binary formation: the environmental and chemical conditions required for black hole birth and the time delays experienced by binaries before they merge. Gravitational-wave events detected today, howeve…

Toward a realistic model of multilayered bacterial colonies
M. T. Khan, J. Cammann, A. Sengupta, E. Renzi, M. G. Mazza
https://arxiv.org/abs/2403.14855 htt…

Toward a realistic model of multilayered bacterial colonies
Bacteria are prolific at colonizing diverse surfaces under a widerange of environmental conditions, and exhibit fascinating examples of self-organization across scales. Though it has recently attracted considerable interest, the role of mechanical forces in the collective behavior of bacterial colonies is not yet fully understood. Here, we construct a model of growing rod-like bacteria, such as Escherichia coli based purely on mechanical forces. We perform overdamped molecular dynamics simulati…

Solar Power Generation Profile Estimation for Lunar Surface Solar PV Systems
Jesus Silva-Rodriguez, Xingpeng Li
https://arxiv.org/abs/2402.14783 https://…

Solar Power Generation Profile Estimation for Lunar Surface Solar PV Systems
As NASA prepares to carry out its Artemis lunar missions, the design and planning of robust power systems tailored to the lunar environment become necessary and urgent. Solar photovoltaic (PV) systems are among the most suitable power generators for lunar applications given the abundant solar irradiance the lunar surface receives as a result of the lack of an atmosphere. However, the vastly different environmental conditions of the moon compared to those on Earth call for special reconsideratio…

ML-based Calibration and Control of the GlueX Central Drift Chamber
Thomas Britton, Michael Goodrich, Naomi Jarvis, Torri Jeske, Nikhil Kalra, David Lawrence, Diana McSpadden, Kishan Rajput
https://arxiv.org/abs/2403.13823

ML-based Calibration and Control of the GlueX Central Drift Chamber
The GlueX Central Drift Chamber (CDC) in Hall D at Jefferson Lab, used for detecting and tracking charged particles, is calibrated and controlled during data taking using a Gaussian process. The system dynamically adjusts the high voltage applied to the anode wires inside the chamber in response to changing environmental and experimental conditions such that the gain is stabilized. Control policies have been established to manage the CDC's behavior. These policies are activated when the model's…

HortiBot: An Adaptive Multi-Arm System for Robotic Horticulture of Sweet Peppers
Christian Lenz, Rohit Menon, Michael Schreiber, Melvin Paul Jacob, Sven Behnke, Maren Bennewitz
https://arxiv.org/abs/2403.15306

HortiBot: An Adaptive Multi-Arm System for Robotic Horticulture of Sweet Peppers
Horticultural tasks such as pruning and selective harvesting are labor intensive and horticultural staff are hard to find. Automating these tasks is challenging due to the semi-structured greenhouse workspaces, changing environmental conditions such as lighting, dense plant growth with many occlusions, and the need for gentle manipulation of non-rigid plant organs. In this work, we present the three-armed system HortiBot, with two arms for manipulation and a third arm as an articulated head for…

This https://arxiv.org/abs/1904.09300 has been replaced.
link: https://scholar.google.com/scholar?q=a

Merging galaxies in isolated environments I. Multiband photometry, classification, stellar masses, and star formation rates
Extragalactic surveys provide significant statistical data for the study of crucial galaxy parameters used to constrain galaxy evolution, e.g. stellar mass (M$_*$) and star formation rate (SFR), under different environmental conditions. These quantities are derived using manual or automatic methods for galaxy detection and flux measurement in imaging data at different wavelengths. The reliability of these automatic measurements, however, is subject to mis-identification and poor fitting due to …

This https://arxiv.org/abs/2310.14667 has been replaced.
initial toot: https://mastoxiv.page/@ar…

Molecular integral equations theory in the near critical region of CO2
Environmental concerns advocate for greener yet efficient solvents. Supercritical CO2 (scCO2) is a promising candidate due to its non-toxicity and potential for reusing CO2 emissions. It also offers a versatile range of properties, finely tunable by pressure adjustments. This adaptability is exploited in chemical industry processes (separation, extraction). Developing new green processes using scCO2 requires an efficient predictive tool for the solvation properties under different conditions. E…

This https://arxiv.org/abs/2402.16177 has been replaced.
initial toot: https://mastoxiv.page/@arX…

Enhancement of the Environmental Stability of Perovskite Thin Films via PMMA and AZ5214-Photoresist Coatings
We introduce a pioneering strategy to enhance the environmental stability of perovskite thin films, a critical step forward in advancing their application in optoelectronics. Through the innovative application of matrix encapsulation techniques, we focus on the stabilization of methylammonium lead iodide (MAPbI3) and methylammonium lead bromide (MAPbBr3) films. These films are meticulously prepared via a two-step solution deposition method under controlled ambient conditions. Our approach invol…

Learning Dynamical Systems Encoding Non-Linearity within Space Curvature
Bernardo Fichera, Aude Billard
https://arxiv.org/abs/2403.11948 https://

Learning Dynamical Systems Encoding Non-Linearity within Space Curvature
Dynamical Systems (DS) are an effective and powerful means of shaping high-level policies for robotics control. They provide robust and reactive control while ensuring the stability of the driving vector field. The increasing complexity of real-world scenarios necessitates DS with a higher degree of non-linearity, along with the ability to adapt to potential changes in environmental conditions, such as obstacles. Current learning strategies for DSs often involve a trade-off, sacrificing either …

Learning Dynamical Systems Encoding Non-Linearity within Space Curvature
Bernardo Fichera, Aude Billard
https://arxiv.org/abs/2403.11948 https://

Learning Dynamical Systems Encoding Non-Linearity within Space Curvature
Dynamical Systems (DS) are an effective and powerful means of shaping high-level policies for robotics control. They provide robust and reactive control while ensuring the stability of the driving vector field. The increasing complexity of real-world scenarios necessitates DS with a higher degree of non-linearity, along with the ability to adapt to potential changes in environmental conditions, such as obstacles. Current learning strategies for DSs often involve a trade-off, sacrificing either …

This https://arxiv.org/abs/2310.14667 has been replaced.
initial toot: https://mastoxiv.page/@ar…

Molecular integral equations theory in the near critical region of CO2
Environmental concerns advocate for greener yet efficient solvents. Supercritical CO2 (scCO2) is a promising candidate due to its non-toxicity and potential for reusing CO2 emissions. It also offers a versatile range of properties, finely tunable by pressure adjustments. This adaptability is exploited in chemical industry processes (separation, extraction). Developing new green processes using scCO2 requires an efficient predictive tool for the solvation properties under different conditions. E…

This https://arxiv.org/abs/2403.19179 has been replaced.
initial toot: https://mastoxiv.page/@ar…

Environmental monitoring using orbital angular momentum mode decomposition enhanced machine learning
Atmospheric interaction with light has been an area of fascination for many researchers over the last century. Environmental conditions, such as temperature and wind speed, heavily influence the complex and rapidly varying optical distortions propagating optical fields experience. The continuous random phase fluctuations commonly make deciphering the exact origins of specific optical aberrations challenging. The generation of eddies is a major contributor to atmospheric turbulence, similar in g…

This https://arxiv.org/abs/2310.12729 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Advancements in Radar Odometry
Radar odometry estimation has emerged as a critical technique in the field of autonomous navigation, providing robust and reliable motion estimation under various environmental conditions. Despite its potential, the complex nature of radar signals and the inherent challenges associated with processing these signals have limited the widespread adoption of this technology. This paper aims to address these challenges by proposing novel improvements to an existing method for radar odometry estimati…

This https://arxiv.org/abs/2310.12729 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Advancements in Radar Odometry
Radar odometry estimation has emerged as a critical technique in the field of autonomous navigation, providing robust and reliable motion estimation under various environmental conditions. Despite its potential, the complex nature of radar signals and the inherent challenges associated with processing these signals have limited the widespread adoption of this technology. This paper aims to address these challenges by proposing novel improvements to an existing method for radar odometry estimati…