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41 results for “point process”
Processing of 3-D Polygon Mesh Model and Radio Propagation Simulations in a Cave: Surface Reconstruction from Point Cloud, Simplification of the Mesh, and Ray Tracing
<p><strong>ABOUT</strong></p><p>This repository includes mesh data from cave geometry scanning and processing, and radio propagation data from ray tracing simulations.</p><p>The geometry data is obtained with laser scanning in a cave in Slovenija. </p><p>The geometry processing includes (i) 3-D shape reconstruction - surface reconstruction from point cloud data and (ii) simplification - reduction of the geometric complexity of the 3-D mesh model. </p><p>The radio propagation data is obtained using CloudRT [1] ray-tracing simulator. </p><p>The obtained propagation-related quantities include information about the propagation mechanism, interactions with the geometry, received power, delay, azimuth and elevation angles of arrival and departure, and path loss. </p><p> </p><p><strong>AUTHORS</strong></p><p>Teodora Kocevska, Andrej Hrovat, Tomaž Javornik</p><p>Department of Communication Systems</p><p>Jožef Stefan Institute, SI-1000 Ljubljana, Slovenia</p><p>teodora.kocevska@ijs.si</p><p> </p><p><strong>GEOMETRY PROCESSING</strong></p><p>The cave segment used for the propagation calculations is selected from a point cloud obtained in a cave in Litia, Slovenia. The point cloud is obtained with 3-D laser scanning of the environment. The selected segment is approx. 58 m long. Several parameter configurations were considered for 3-D shape reconstruction, including Poisson surface reconstruction with octree depths of 8, 10, and 12. Geometries that represent the cave shape and have different levels of complexity were created and studied. In the simplification process, one and two-stage simplification was explored using the Quadric Edge Collapse Decimation approach. </p><p> </p><p><strong>RADIO SETUP</strong></p><p>The transmitter (Tx) is fixed at the entrance of the cave and the receiver (Rx) is moved along the cave in 40 positions with a step of 1 m.</p><p>Omnidirectional antennas at the Tx and Rx sites and vertical polarization are considered. The antenna is mounted 1.5 m above the ground.</p><p>The start frequency is 3.5 GHz, the end frequency is 3.6 GHz and the step is 10 MHz. Direct propagation and first-order reflection are considered. </p><p>The cave geometry is represented by a triangular mesh, and the material of the cave is wet earth. The material electromagnetic properties are selected according to the specifications presented in [2].</p><p> </p><p><strong>FOLDER STRUCTURE</strong></p><p>The folder structure is:</p><p> - Polygon_Mesh_Models</p><p> <i># 3-D environment models with varying </i>levels<i> of geometry complexity</i></p><p> - Reconstruction_Segmen1_Poisson_Surface_Reconstruction</p><p> - Simplification_Segment1_Quadric_Edge_Collapse_Decimation</p><p> - Propagation_Data</p><p> <i># Propagation quantities of all rays between a transmitter and receiver</i></p><p> - AllRay_PropData</p><p> - PathLoss</p><p> - readme.txt</p><p> - RayTracing_EnvironmentModel</p><p> <i> # Final environment model used for ray tracing simulations</i></p><p> - Cave_MeshModel.json</p><p> - Cave_MeshModel.skb</p><p> - Cave_MeshModel.skp</p><p> - RayTracing_MaterialProperties</p><p> <i># Properties of the materials in the environment</i></p><p> - materials.json</p><p> - materials.mtl</p><p> - readme.txt</p><p> - Cave_Length.txt</p><p> <i># Length between selected locations in the environment</i></p><p> - Cave_Segment1_visual.png</p><p> <i> # Visualization of the environment segment used for propagation calculation</i></p><p> - readme.txt</p><p> <i># Overall description </i></p><p><strong>REFERENCES</strong></p><p>[1] D. He, B. Ai, K. Guan, L. Wang, Z. Zhong, and T. Kürner, "The Design and Applications of High-Performance Ray-Tracing Simulation Platform for 5G and Beyond Wireless Communications: A Tutorial," in IEEE Communications Surveys & Tutorials, vol. 21, no. 1, pp. 10-27, First quarter 2019, doi: 10.1109/COMST.2018.2865724.</p><p>[2] R. sector of International Telecommunication Union (ITU-R), "Effects of building materials and structures on radio wave propagation above about 100 MHz," International Telecommunication Union, ITU-R Recommendation P.2040-2, 2021.</p><p> </p><p><strong>ACKNOWLEDGEMENT</strong></p><p>This work was supported by the Slovenian Research Agency under grant <strong>J2-3048</strong>.</p><p> </p>
IG. 6. — A, Trunk vertebra of Alsophis sp. 2 from Pointe du Helleux archaeological site (Square 2 – crab layer) located on Grande-Terre Island; B, trunk vertebra of Erythrolamprus juliae cf. copeae (Parker, 1936) from Sainte-Rose La Ramée archaeological site (US 2058) located on Basse-Terre Island. Abbreviations: cd., condyle; ct., cotyle; di., diapophysis; h. k., hemal keel; m. c., medial constriction; n. a., neural arch; n. s., neural spine; p. c., precondylar constriction; p. d., paracotylar depression; p. n., postero-medial notch of the zygantrum; pa., parapophysis; pz. f., prezygapophyseal facet; pz. p., prezygapophyseal process; s. d., subcentral depression; s. r., subcentral ridge; s. t., sub-cotylar tubercle; zs., zygosphene. Scale bars: 4 mm in Fossil dipsadid snakes from the Guadeloupe Islands (French West-Indies) and their interactions with past human populations
IG. 6. — A, Trunk vertebra of Alsophis sp. 2 from Pointe du Helleux archaeological site (Square 2 – crab layer) located on Grande-Terre Island; B, trunk vertebra of Erythrolamprus juliae cf. copeae (Parker, 1936) from Sainte-Rose La Ramée archaeological site (US 2058) located on Basse-Terre Island. Abbreviations: cd., condyle; ct., cotyle; di., diapophysis; h. k., hemal keel; m. c., medial constriction; n. a., neural arch; n. s., neural spine; p. c., precondylar constriction; p. d., paracotylar depression; p. n., postero-medial notch of the zygantrum; pa., parapophysis; pz. f., prezygapophyseal facet; pz. p., prezygapophyseal process; s. d., subcentral depression; s. r., subcentral ridge; s. t., sub-cotylar tubercle; zs., zygosphene. Scale bars: 4 mm
Figure 4. - Brightfield image showing the posterior mesosoma and anterior metasoma of Pteroceraphronmirabilipennis Dessart 1981. Arrows point to bifurcated anteromedian process of the propodeum-metanotum complex.
Figure 4. - Brightfield image showing the posterior mesosoma and anterior metasoma of Pteroceraphronmirabilipennis Dessart 1981. Arrows point to bifurcated anteromedian process of the propodeum-metanotum complex.
Understanding complex spatial dynamics from mechanistic models through spatio-temporal point processes
<p>Landscape heterogeneity affects population dynamics, which determine species persistence, diversity and interactions. These relationships can be accurately represented by advanced spatially-explicit models (SEMs) allowing for high levels of detail and precision. However, such approaches are characterised by high computational complexity, high amount of data and memory requirements, and spatio-temporal outputs may be difficult to analyse. A possibility to deal with this complexity is to aggregate outputs over time or space, but then interesting information may be masked and lost, such as local spatio-temporal relationships or patterns. An alternative solution is given by meta-models and meta-analysis, where simplified mathematical relationships are used to structure and summarise the complex transformations from inputs to outputs. Here, we propose an original approach to analyse SEM outputs. By developing a meta-modelling approach based on spatio-temporal point processes (STPPs), we characterise spatio-temporal population dynamics and landscape heterogeneity relationships in agricultural contexts. A landscape generator and a spatially-explicit population model simulate hierarchically the pest-predator dynamics of codling moth and ground beetles in apple orchards over heterogeneous agricultural landscapes. Spatio-temporally explicit outputs are simplified to marked point patterns of key events, such as local proliferation or introduction events. Then, we construct and estimate regression equations for multi-type STPPs composed of event occurrence intensity and magnitudes. Results provide local insights into spatio-temporal dynamics of pest-predator systems. We are able to differentiate the contributions of different driver categories ( i.e., spatio-temporal, spatial, population dynamics). We highlight changes in the effects on occurrence intensity and magnitude when considering drivers at global or local scale. This approach leads to novel findings in agroecology where, for example, we show that the organisation of cultivated patches and semi-natural elements play different roles for pest regulation depending on the scale considered. It aids to formulate guidelines for biological control strategies at global and local scale.</p>
Understanding complex spatial dynamics from mechanistic models through spatio-temporal point processes
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Dataset for A Modified Approach for Process-Integrated Reference Point Determination
<p>The Global Geodetic Observing System (GGOS) calls for continues and automated determination of the geometric reference points of space-geodetic techniques such as DORIS, GNSS, SLR and VLBI. Whereas the reference points of DORIS beacons and GNSS antennas can simply be measured by observing well-defined reference markers, the determination of SLR and VLBI reference points are a metrological challenge, because these reference points are inaccessible and non-materialized. Indirect methods are needed to estimate the reference points in a rigorous way, which fulfil the requirements on an automated and continues reference point determination of the Global Geodetic Observing System. In this investigation, a modified approach for reference point determination of SLR and VLBI telescopes is presented. The results of the new approach are compared to proven reference point models. The numerical deviations of the estimated reference point coordinates and the axis-offset are <<50 μm and demonstrate the equivalence of the new approach.</p>
Data from: Point process models for presence-only analysis
1. Presence-only data are widely used for species distribution modelling, and point process regression models are a exible tool that has considerable potential for this problem, when data arise as point events. 2. In this paper we review point process models, some of their advantages, and some common methods of fitting them to presence-only data. 3. Advantages include (and are not limited to): clarification of what the response variable is that is modelled; a framework for choosing the number and location of quadrature points (commonly referred to as pseudoabsences or \background points") objectively; clarity of model assumptions and tools for checking them; models to handle spatial dependence between points when it is present; ways forward regarding difficult issues such as accounting for sampling bias. 4. Point process models are related to some common approaches to presenceonly species distribution modelling, which means that a variety of different software tools can be used to fit these models, including MAXENT or generalised linear modelling software.
Code and processed data - Control points for design of taxonomic composition in synthetic human gut consortia
<p>Code, optical density data, and sequencing tally files (relative abundance from 16S sequencing of defined communities) for <strong>Control points for design of taxonomic composition in synthetic human gut consortia. </strong>Files are organized by experiment with a readme file contained within the .zip file. "Setup" folders have information about expeirmental design, "rawData" folders have optical density and tallyfiles, "analysis" folders have scripts used to analyze data and generate models. </p>
Processed data from Repair-seq screens of prime editing of point mutations
<p>Processed data from Repair-seq screens of prime editing of point mutations.</p>
Kinematic Process and Characteristic of Root-Induced Water Flow Using a Visualizing Point Source Infiltration Experiment
<p><span>The video is the temporal results of the 2-D point source infiltration experiment in this paper. ‘G-’ represents the granular experimental group, and ’RG-’ represents the root-granular experimental group. The injection rate of G-1 and RG-1 is 0.25 mm/min, corresponding to the boundary flow rate of 0.03 ml/min. </span></p> <p><span>In this experiment, the glass beads have a particle diameter ranging from 0.6-0.8 mm. The selected root has diameters ranging from 1.3-1.5 mm.</span></p>
Datasets for "Detecting rhythmic spiking through the power spectra of point process model residuals"
<p>This repository contains synthetic and empirical datasets that were analyzed in the preprint "Detecting rhythmic spiking through the power spectra of point process model residuals."</p> <p>Relative to the previous version (1.0.0), this new version (1.0.1) only entails changes in the naming of some folders, and the text of an explanatory text file. The changes reflect the reordering of the figures in the newest version of the manuscript.</p>
Dataset from 'Hesse, C., Koroknai, L., & Billino, J. (2018). Individual differences in processing resources modulate bimanual interference in pointing. Psychological Research. doi: 10.1007/s00426-018-1050-3
<p>--------------------------------------------------------------</p> <p>The folder contains 8 data files and 1 readme file describing the content of the data files.</p> <p>-------------------------------------------------------------</p> <p>For further questions, please contact:<br> c.hesse[at]abdn.ac.uk</p> <p> </p>
Points clouds of the best Somma-Vesuvius gravitative deformation process analog model
<p>Dense points clouds of the best Somma-Vesuvius gravitative deformation process analog model, realized with the Agisoft Photoscan software using a dataset of photos taken with four different cameras.</p>
Dataset of the paper: "Creating Common Ground: Formalizing and Designing an Employee-driven Innovation Process with Decision Points"
<p>All practical artifacts of the submitted PACIS2023 paper with the title "Creating Common Ground: Formalizing and Designing an Employee-driven Innovation Process with Decision Points"</p>
How Point-of-Care Ultrasound Affects the Diagnostic Process in General Practice.
ClinicalTrials.gov study NCT03375333. IPD Sharing: UNDECIDED. Countries: 1. Publications: 2.
Mid-point Transverse Process to Pleura Block Versus Thoracic Paravertebral Block in Posterolateral Thoracotomy
ClinicalTrials.gov study NCT06361121. IPD Sharing: NO. Countries: 1. Publications: 4.
Ultrasound-guided Paravertebral Block Versus Mid-point Transverse Process Pleura Block in Mastectomy Surgery
ClinicalTrials.gov study NCT05332028. IPD Sharing: NO. Countries: 1. Publications: 8.
Data from: Point process models for presence-only analysis
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Harmony Point Chinstrap penguin GPS and Time-Depth-Recorder processed data
<p>Tracking data from Chinstrap Penguins (<em>Pygoscelis antarcticus</em>) tracked with axy-trek marine loggers in Harmony Point (Nelson Island, Maritime Antarctic Peninsula) in the breeding seasons of 2019/20 and 2021/22.</p> <p>The zip file is composed of two folders containing outputs from the R script named "GPS_TDR_processing.R", which process raw data from Axy-trek marine loggers producing 3 outputs that are within each of the folders. The outputs are: (1) 5-min resampled foraging trips (with trip ID identified), (2) dive statistics and (3) foraging trip summaries.</p> <p> </p> <p>Each file is named as the TagID, type of data (GPS or TDR), period (IB for late incubation / brooding - from late december to early january; CR for Chick-Rearing, from early to mid January) and season (2019/20 as 19 and 2021/22 as 21).</p> <p> </p> <p>GPS data is composed of the fields: Date (YYYY-mm-dd HH:MM:SS), distances, trip number and geographical coordinates in "+proj=longlat +datum=WGS84 +no_defs".</p> <p>TDR data is composed of outputs from dive statistics summarized using the "diveMove" R package. </p>
Kinematic Process and Characteristic of Root-Induced Water Flow Using a Visualizing Point Source Infiltration Experiment
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