ESP32 driven small weather station with focus on parameters usually not captured, including particle density for Air Quality and UV-Index

Python and MATLAB codes for Density-Driven Optimal Control (D2OC) using Optimal Transport and Wasserstein distance, enabling decentralized multi-agent / multi-robot non-uniform area coverage.

Graph Game Optimization-driven Instance Subgraph-density Disentanglement Clustering for Learning Explainable Topology-invariant

Data Driven Thermospheric Density Modeling with Machine Learning

A Density-driven Iterative Prototype Optimization for Transductive Few-shot Learning

The package 'data-driven density estimation x' (dddex) turns any standard point forecasting model into an estimator of the underlying conditional density

Code for "A density-driven method for the placement of biological cells over two-dimensional manifolds"

Coupled density-driven groundwater flow and solute transport model using Python

Micro X-ray Computed Tomography (microCT) image analysis provides information about micro-scale structures and properties critical to the biological and geoscientific fields. Recent advances in microCT have in part been driven by the availability of new 3D image processing techniques. These techniques, while developed for the biological/life sciences, have the potential to support other scientific fields given an appropriate application. For example, microCT analysis can provide information about the density and structure of the microfossil shells of foraminifera, which are commonly used in paleoceanography to reconstruct aspects of the ocean and climate. Information about the density and structure of foraminiferal shells is useful for characterizing changes in ocean acidification and in foraminiferal species classification and assemblage-based sea surface temperature studies. The macros presented here provide a user-friendly semi-automated workflow for applying imageJ/Fiji tools to extract microCT-derived information on many individuals scanned together in a batch. The example datasets provided are of a batch of individual foraminiferal shells. The batch is small (six individuals) for simplicity of the example, but the workflow is applicable for rapidly processing large batches (dozens to hundreds) of individuals.

The lid-driven cavity is a well-known benchmark problem for viscous incompressible fluid flow. We are dealing with a square cavity consisting of three rigid walls with no-slip conditions and a lid moving with a tangential unit velocity. The lower left corner has a reference static pressure of 0. In computational fluid dynamics (CFD), the SIMPLE algorithm is a widely used numerical procedure to solve the Navier–Stokes equations. SIMPLE is an acronym for Semi-Implicit Method for Pressure Linked Equations. The algorithm is iterative. The basic steps in the solution update are as follows: Set the boundary conditions. Compute the gradients of velocity and pressure. Solve the discretized momentum equation to compute the intermediate velocity field. Compute the uncorrected mass fluxes at faces. Solve the pressure correction equation to produce cell values of the pressure correction. Update the pressure field: where urf is the under-relaxation factor for pressure. Update the boundary pressure corrections. Correct the face mass fluxes. Correct the cell velocities by the gradient of the pressure corrections and the vector of central coefficients for the discretized linear system representing the velocity equation and Vol is the cell volume. Update density due to pressure changes.

Data Driven Deep Density Estimation

An IoT-AI framework for real-time public safety response, featuring AI-driven alert verification and proximity-aware dispatch for high-density tourist areas.

Introduction Metaverse is the next evolution of digital technologies. It includes 3D virtualization and will transform digital technologies in the next 5-10 years. Elements of a Metaverse are considered very important related to industry 4.0. Metaverse will have numerous technologies comprising the below: Digital currency Online shopping Workplace automation Social media Digital Humans Natural Language Processing Infrastructure Device independence In this article, we would understand what Metaverse is and what are its different elements? Description Metaverse is a combined virtual space. It is made by the convergence of virtually improved physical and digital reality. We can also say that it is device-free and is not owned by a single seller. Metaverse is known as an independent virtual economy. It is allowed by digital currencies and non-fungible tokens (NFTs). It characterizes a combinatorial innovation because it needs many technologies and trends to function. The following are contributing tech capabilities: Augmented reality (AR) Flexible work styles Head-mounted displays (HMDs) An AR cloud The Internet of Things (IoT) 5G Artificial intelligence (AI) Spatial technologies For better understanding, the concepts of a Metaverse, consider it as the next version of the Internet. That begins as separate bulletin boards and independent online destinations. In the long run, these destinations developed sites on a virtual shared space same as how a Metaverse would develop. Importance of the Metaverse There is a lot of exhilaration around Metaverse. Greatly of it driven by technology companies tactically claiming to be Metaverse companies. Similarly, Metaverse creates to improve or augment the digital and physical realities of people. Furthermore, deeds that now happen in siloed locations will finally occur in a single Metaverse, for example: Buying clothes and fittings for online avatars Business digital land and building virtual homes Take part in a virtual social experience Supermarkets run in virtual malls through immersive commerce With virtual classrooms to practice immersive learning Purchasing digital art, breakables, and assets (NFTs) Networking with digital humans for onboarding business connections It is likely that a Metaverse will make available determined, decentralized, joint, and interoperable opportunities. It will create the business models, which will allow organizations to extend digital business. Elements of a Metaverse Gartner is a technology research and consulting company. It described the elements of a Metaverse in the below diagram. Elements of a Metaverse Applications Virtual reality The social network company Facebook launched a social VR world named Facebook Horizon in 2019. Facebook chairman Mark Zuckerberg confirmed in 2021, a company pledged to develop a metaverse. Several VR technologies promoted by Meta Platforms remain to be developed. Microsoft developed the VR Company AltspaceVR in 2017. Microsoft has since applied metaverse features for example virtual avatars and meetings thought in virtual reality into Microsoft Teams. Future implementations for metaverse technology comprise refining work output, shared learning environments, e-commerce, real estate, and fashion. Video games Many works of metaverse technologies have by now been developed inside modern internet-enabled video games. The Second Life is combined several features of social media into a determined three-dimensional world with the user signified as an avatar. Social functions are repeatedly an integral story in many hugely multiplayer online games. Social-based gameplay of Minecraft characterizes an innovative analog of a metaverse. Hardware Technology Entrance points for metaverse comprise general-purpose computers and smartphones. Also, included augmented reality (AR), mixed reality, virtual reality (VR), and virtual world technologies. Need on VR technology has limited metaverse growth and wide-scale acceptance. Limits of moveable hardware and the requirement to balance cost and design have produced a deficiency of high-quality graphics and mobility. Lightweight wireless headsets have fought to attain the retina display pixel density required for visual immersion. Present hardware development is dedicated to choking limitations of VR headsets, sensors, and growing immersion with haptic technology. Software Technology There has been nothing for wide-scale acceptance of a uniform technical requirement for metaverse applications. Current applications depend chiefly on proprietary technology. Interoperability is the main anxiety in metaverse development. There have been a number of virtual environment standardization projects. Metaverse is known as a three-dimensional Internet that is occupied with live people. The technology company NVIDIA declared in 2021 they will accept USD for their metaverse development tools. The OpenXR is an open standard for entree into virtual and augmented reality plans and involvements. It has been accepted by Microsoft for HoloLens 2, Meta Platforms for the Oculus Quest, and Valve for SteamVR. For more details visit: https://www.technologiesinindustry4.com

My implementation of the Sow & Grow. A density-based user-driven Clustering Algorithm.

Ultra-high-density, self-healing network fabric with predictive analytics-driven machine learning integration and adaptive intelligent optimizer.

OpenFoam case file and solver for density-driven Rayleigh Taylor instability in a porous media applicable to CO2 sequestration

This is the MATLAB implementation of the haziness degree evaluator for predicting the haze density from a single image. The relevant work was published in the MDPI Sensors journal under the title "Haziness degree evaluator: a knowledge-driven approach for haze density estimation".

densityscout : This tool calculates density (like entropy) for files of any file-system-path to finally output an accordingly descending ordered list. This makes it possible to quickly find (even unknown) malware on a potentially infected Microsoft Windows driven machine

A data-driven dashboard for Bengaluru that maps BMTC bus stops, metro stations, and BBMP zones to analyze public transport accessibility. It computes key metrics like access coverage, first/last-mile gap index (FLGI), bus stop density, and nearest-metro distance—helping planners identify weak spots and prioritize investments

LiDAR360-Lite is the free version of LiDAR360 – a LiDAR point cloud processing software. Lidar360 uses a performance driven data format for 3D visualization of massive point cloud and terrain data (LiData and LiModel). It provides various display modes including elevation, intensity, classification, return number and more. This data format can be loaded almost immediately in LiDAR360, less than a second in most cases, allowing users to check the data quality very efficiently. LiDAR360 also supports common spatial formats including raster, table (.csv) and vector data (.shp) visualization. LiDAR360-Lite Features: Point cloud profile analysis, LiDAR360-Lite allows users to view the point cloud data from different angles, classify point cloud by various selection tools, and supports 2D measurement 3D visualization and editing digital terrain model, there are a variety of selection tools to support terrain smooth, flat and repair Point cloud clip tools, clip the point cloud data by polygon or rectangular Measurement tools, including area, angle, volume, height, point density measurement Essential data management tools, including: Format conversion, outliers removal, normalization, projection transformation and clip, rater tools such as band operation, raster mosaic and raster subdivision Grid statistics, statistical analysis of point cloud based on points number, density and height value User friendly window manipulation: 2D and 3D display in same window, multi-window linkage, screen rolling, layer drag, cross selection, etc Language setting

This repository contains the directories "code" and "data" to reproduce the models, calculations and figure rendering of the paper: Vidal-Cordasco, M; Ocio, D.; Hickler, T., Marín-Arroyo, A.B. (under review) "Ecosystems productivity affected the spatiotemporal disappearance of Neanderthals in Iberia". The file 1_Main_Script.R includes the functions to estimate the herbivore biomass of each herbivore species according to the bottom-up processes of the food chain regulation driven by the Net Primary Productivity (NPP), the specific herbivore guild composition in each ecosystem, and the allometric relationships between body mass and population density. This script was also used to analyse and compare the estimated NPP between the four biogeographic regions of Iberia during the Marine Isotope Stage (MIS) 3. Therefore, this code generates the main results and figures as found in the paper. The file 2_HB_Validation.R reproduces the validation process of the macroecological model to estimate herbivore abundances (used in the 1_Main_Script.R) against empirical present-day herbivore densities from a broad range of terrestrial ecosystems. The file 3_NB_NPP.R includes the analyses of the association between NPP and herbivore biomass in different ecosystems and computes a predictive model. The file 4_Clim_Validation.R was used to perform pollen-based paleoclimate reconstructions with weighted averaging (WA) regressions. These predictive functions are used to estimate temperature and precipitation from the palynological fossil record. The file 5_Rarefaction.R performs a rarefaction analysis with the local faunal assemblages in each biogeographic region of Iberia during the MIS 3. The file 6_Chronology.R was used to perform optimal linear estimation models and summed probability distribution analyses of archaeological assemblages. As the data and code in this repository are complete, it can be reproduced with only an R environment (tested for R v4.1.0) in RStudio. The necessary package dependencies are documented in each .R file. The content of this repository was made possible thanks to funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 818299) for the SUBSILIENCE project (https://www.subsilience.eu/).

Introduction Metaverse is the next evolution of digital technologies. It includes 3D virtualization and will transform digital technologies in the next 5-10 years. Elements of a Metaverse are considered very important related to industry 4.0. Metaverse will have numerous technologies comprising the below: Digital currency Online shopping Workplace automation Social media Digital Humans Natural Language Processing Infrastructure Device independence In this article, we would understand what Metaverse is and what are its different elements? Description Metaverse is a combined virtual space. It is made by the convergence of virtually improved physical and digital reality. We can also say that it is device-free and is not owned by a single seller. Metaverse is known as an independent virtual economy. It is allowed by digital currencies and non-fungible tokens (NFTs). It characterizes a combinatorial innovation because it needs many technologies and trends to function. The following are contributing tech capabilities: Augmented reality (AR) Flexible work styles Head-mounted displays (HMDs) An AR cloud The Internet of Things (IoT) 5G Artificial intelligence (AI) Spatial technologies For better understanding, the concepts of a Metaverse, consider it as the next version of the Internet. That begins as separate bulletin boards and independent online destinations. In the long run, these destinations developed sites on a virtual shared space same as how a Metaverse would develop. Importance of the Metaverse There is a lot of exhilaration around Metaverse. Greatly of it driven by technology companies tactically claiming to be Metaverse companies. Similarly, Metaverse creates to improve or augment the digital and physical realities of people. Furthermore, deeds that now happen in siloed locations will finally occur in a single Metaverse, for example: Buying clothes and fittings for online avatars Business digital land and building virtual homes Take part in a virtual social experience Supermarkets run in virtual malls through immersive commerce With virtual classrooms to practice immersive learning Purchasing digital art, breakables, and assets (NFTs) Networking with digital humans for onboarding business connections It is likely that a Metaverse will make available determined, decentralized, joint, and interoperable opportunities. It will create the business models, which will allow organizations to extend digital business. Elements of a Metaverse Gartner is a technology research and consulting company. It described the elements of a Metaverse in the below diagram. Elements of a Metaverse Applications Virtual reality The social network company Facebook launched a social VR world named Facebook Horizon in 2019. Facebook chairman Mark Zuckerberg confirmed in 2021, a company pledged to develop a metaverse. Several VR technologies promoted by Meta Platforms remain to be developed. Microsoft developed the VR Company AltspaceVR in 2017. Microsoft has since applied metaverse features for example virtual avatars and meetings thought in virtual reality into Microsoft Teams. Future implementations for metaverse technology comprise refining work output, shared learning environments, e-commerce, real estate, and fashion. Video games Many works of metaverse technologies have by now been developed inside modern internet-enabled video games. The Second Life is combined several features of social media into a determined three-dimensional world with the user signified as an avatar. Social functions are repeatedly an integral story in many hugely multiplayer online games. Social-based gameplay of Minecraft characterizes an innovative analog of a metaverse. Hardware Technology Entrance points for metaverse comprise general-purpose computers and smartphones. Also, included augmented reality (AR), mixed reality, virtual reality (VR), and virtual world technologies. Need on VR technology has limited metaverse growth and wide-scale acceptance. Limits of moveable hardware and the requirement to balance cost and design have produced a deficiency of high-quality graphics and mobility. Lightweight wireless headsets have fought to attain the retina display pixel density required for visual immersion. Present hardware development is dedicated to choking limitations of VR headsets, sensors, and growing immersion with haptic technology. Software Technology There has been nothing for wide-scale acceptance of a uniform technical requirement for metaverse applications. Current applications depend chiefly on proprietary technology. Interoperability is the main anxiety in metaverse development. There have been a number of virtual environment standardization projects. Metaverse is known as a three-dimensional Internet that is occupied with live people. The technology company NVIDIA declared in 2021 they will accept USD for their metaverse development tools. The OpenXR is an open standard for entree into virtual and augmented reality plans and involvements. It has been accepted by Microsoft for HoloLens 2, Meta Platforms for the Oculus Quest, and Valve for SteamVR.

ClusterDC is a density-based clustering algorithm tailored for identifying clusters in a two-dimensional embedding space. It is fast, robust, flexible, and data-driven.

Kernel Density Estimation (KDE) with data-driven bandwidth selection

The implementation of Visualization-driven Illuminated Density Plots (VIDP), as proposed in our 2024 IEEE TVCG paper. More information can be found in https://www.yunhaiwang.net/tvcg2024/Shaded-Density-Field/.

A hybrid **AI + physics-driven optimization framework** for CNC machining of Medium-Density Fibreboard (MDF). This project combines physics-based machining models and machine learning models to predict machining behavior, optimize cutting parameters, and automatically regenerate CNC G-code for improved machining performance.

The official Pytorch implementation of "Spatio-Temporal Joint Density Driven Learning for Skeleton-Based Action Recognition".

TimeFlow: a density-driven pseudotime method for flow cytometry data analysis.

Energy and Momentum of a Density-Driven Overflow in the Samoan Passage

Machine Learning-Driven High-Throughput Screening for High-Energy Density and Stable NASICON Cathodes