Texture mapping is a technique that uses images to add detail and texture to 3D objects. There are several types of texture mapping including bump mapping, normal mapping, parallax mapping, and displacement mapping. Bump mapping simulates bumps and wrinkles without changing the object's surface, while normal mapping is commonly used to fake lighting of bumps and dents. Parallax mapping enhances bump mapping techniques to give the illusion of depth as the viewing angle changes. Displacement mapping uses height maps to displace the actual geometry of surface points, giving surfaces great depth but at a higher computational cost.
Mip stands for the Latin multim im parvo, meaning "many things in a small place." Mipmapping uses some clever methods to pack image data into memory. When using mipmapping, OpenGL automatically determines which texture map to use based on the size (in pixels) of the object being mapped.
Texture mapping is a graphic design process where a 2D texture map is wrapped around a 3D object to give it a surface texture. It accounts for the object's 3D position. Avatar used texture mapping extensively to create its virtual world. Textures played a key role in developing rich, varied character and environmental assets. Texture mapping techniques can also be applied to photography by layering texture photos over object photos, using layer masks and blending modes like Overlay. Warping and liquifying textures allows reshaping them to match the object. Students are assigned to take photos of textures and objects, then create texture maps by overlaying textures onto objects.
Texture mapping is a common method to add surface detail by mapping texture patterns onto object surfaces. The texture can be defined as a rectangular array or a procedure modifying surface intensity values. This approach, called texture mapping or pattern mapping, was illustrated by mapping a unit square pattern to a cylindrical surface through a series of linear transformations. Pixel positions were mapped to texture space and averaged to obtain each pixel intensity from the texture pattern.
The document discusses the key steps and concepts involved in rendering sprites for games. It explains that rendering involves describing a virtual scene and camera, defining light sources and surface properties, and solving the render equation. It also discusses triangle meshes, texture mapping, 3D projection, coordinate systems, sprite components like transformation matrices, and orthographic projection. The overall rendering process for sprites involves applying transformations, scaling, rotation and translation to the sprites.
The frame camera is used by users of digital single-lens reflex cameras (DSLRs) as a shorthand for an image sensor format which is the same size as 35mm format (36 mm × 24 mm) film.
Panoramic imagery is created either by digitally stitching together multiple images from the same position (left/right, up/down) or by rotating a camera with conventional optics, and an area or line sensor.
This document summarizes research analyzing the accuracy of 3D models reconstructed from spherical video images. The study acquired 134 spherical images of an indoor environment using a Garmin VIRB 360 camera. Images were extracted from video and reference points were collected. Aerial triangulation, dense image matching, and registration with TLS point clouds were performed. Results showed reconstruction accuracy was higher when reference points were distributed across images rather than clustered in the middle. However, the model had significant noise due to glass surfaces and stitching challenges. While geometric detail and accuracy were low, the 3D model could still enable some applications. Factors like calibration, stitching, resolution, and illumination variability affected the results.
The document discusses using a spherical camera to generate point clouds for 3D mapping of indoor and outdoor environments. It presents a methodology using a Garmin VIRB 360 spherical camera to capture images of a building. Point clouds were generated from the images and used to create 3D models of the indoor and outdoor spaces. Accuracy assessments found the outdoor point cloud and model had better geometric detail and aerial triangulation accuracy, while angle delineation was more accurate for the indoor model. Room for improvements in geometric detail and accuracy of the point clouds were identified.
Texture mapping is a technique that uses images to add detail and texture to 3D objects. There are several types of texture mapping including bump mapping, normal mapping, parallax mapping, and displacement mapping. Bump mapping simulates bumps and wrinkles without changing the object's surface, while normal mapping is commonly used to fake lighting of bumps and dents. Parallax mapping enhances bump mapping techniques to give the illusion of depth as the viewing angle changes. Displacement mapping uses height maps to displace the actual geometry of surface points, giving surfaces great depth but at a higher computational cost.
Mip stands for the Latin multim im parvo, meaning "many things in a small place." Mipmapping uses some clever methods to pack image data into memory. When using mipmapping, OpenGL automatically determines which texture map to use based on the size (in pixels) of the object being mapped.
Texture mapping is a graphic design process where a 2D texture map is wrapped around a 3D object to give it a surface texture. It accounts for the object's 3D position. Avatar used texture mapping extensively to create its virtual world. Textures played a key role in developing rich, varied character and environmental assets. Texture mapping techniques can also be applied to photography by layering texture photos over object photos, using layer masks and blending modes like Overlay. Warping and liquifying textures allows reshaping them to match the object. Students are assigned to take photos of textures and objects, then create texture maps by overlaying textures onto objects.
Texture mapping is a common method to add surface detail by mapping texture patterns onto object surfaces. The texture can be defined as a rectangular array or a procedure modifying surface intensity values. This approach, called texture mapping or pattern mapping, was illustrated by mapping a unit square pattern to a cylindrical surface through a series of linear transformations. Pixel positions were mapped to texture space and averaged to obtain each pixel intensity from the texture pattern.
The document discusses the key steps and concepts involved in rendering sprites for games. It explains that rendering involves describing a virtual scene and camera, defining light sources and surface properties, and solving the render equation. It also discusses triangle meshes, texture mapping, 3D projection, coordinate systems, sprite components like transformation matrices, and orthographic projection. The overall rendering process for sprites involves applying transformations, scaling, rotation and translation to the sprites.
The frame camera is used by users of digital single-lens reflex cameras (DSLRs) as a shorthand for an image sensor format which is the same size as 35mm format (36 mm × 24 mm) film.
Panoramic imagery is created either by digitally stitching together multiple images from the same position (left/right, up/down) or by rotating a camera with conventional optics, and an area or line sensor.
This document summarizes research analyzing the accuracy of 3D models reconstructed from spherical video images. The study acquired 134 spherical images of an indoor environment using a Garmin VIRB 360 camera. Images were extracted from video and reference points were collected. Aerial triangulation, dense image matching, and registration with TLS point clouds were performed. Results showed reconstruction accuracy was higher when reference points were distributed across images rather than clustered in the middle. However, the model had significant noise due to glass surfaces and stitching challenges. While geometric detail and accuracy were low, the 3D model could still enable some applications. Factors like calibration, stitching, resolution, and illumination variability affected the results.
The document discusses using a spherical camera to generate point clouds for 3D mapping of indoor and outdoor environments. It presents a methodology using a Garmin VIRB 360 spherical camera to capture images of a building. Point clouds were generated from the images and used to create 3D models of the indoor and outdoor spaces. Accuracy assessments found the outdoor point cloud and model had better geometric detail and aerial triangulation accuracy, while angle delineation was more accurate for the indoor model. Room for improvements in geometric detail and accuracy of the point clouds were identified.
(1) The document presents a methodology for generalizing 3D building models within CityGML for disaster and emergency management.
(2) The methodology involves 6 steps: derivation of coarse levels of detail, projection of outlier buildings, simplification of ground plans, aggregation, and reconstruction of simplified wall elements.
(3) The methodology was implemented in C++ and able to generalize 3D building models to support disaster response and recovery by providing different levels of detail for analysis and visualization.
Texture mapping involves adding graphics like photographs or designs to 3D polygon objects to make them appear more realistic. Shaders describe an object's material properties like how light is reflected. UV mapping projects a 3D model onto a 2D plane to make texture application easier. Specularity defines how surfaces reflect light to appear shiny. Normals indicate surface direction. Bump maps simulate small surface details without extra geometry. Transparency maps use black/white values to determine opacity. Normal maps store surface orientation data to mimic detail. Baking combines textures, materials, and lighting into single images to streamline rendering.
Color and appearance information in 3d modelsFrederic Kaplan
This document discusses methods for representing color and visual appearance on 3D models. It describes how color is determined by the interaction of lighting and material properties. Common representations of visual appearance include reflectance functions, BSSRDFs, SVBRDFs and BRDFs. Texture mapping and color projection from photographs are introduced as ways to encode color information onto 3D geometry. Issues with photo shooting, registration, material estimation and color projection are discussed. The document recommends resources for learning more about these topics.
Double patterning lithography is a technique used to print integrated circuit designs when feature sizes shrink below the resolution limits of a single exposure. It involves splitting the circuit layout into two masks and exposing the photo-resist layer twice to print the full design. Decomposing the circuit layout and assigning patterns to the two masks is an NP-hard graph coloring problem. The document describes techniques for decomposing the conflict graph that represents incompatible patterns, including using SPQR trees to decompose into tri-connected components and solving each independently. Experimental results show the proposed method can achieve a 3-10x speedup over other approaches.
This document discusses double patterning lithography techniques. It introduces how optical lithography is approaching its limits and double patterning is needed for smaller feature sizes. It describes the double patterning process and challenges including feature distortion and decreased yield. The document outlines techniques for polygon cutting, priority search trees, and decomposing conflict graphs into tri-connected components to solve the layout splitting problem. Experimental results on test cases including a 320k polygon design show the method achieves 3-10x speedup.
代表的なオープンソース空間データサーバの1つであるGeoServerは、多くの強力な機能を提供します。 特に、さまざまなデータソースからの空間データへの接続とパブリッシングをサポートします。 GeoServerはOpen Geospatial Consortiumによって地理空間フィーチャデータを要求するために設定された標準プロトコルであるWeb Feature Service(WFS)もサポートしています。 しかしながら、GeoServerは2次元ジオメトリのための関数しか提供しないため、3D空間データを処理する関数はほとんどありません。 GeoServerの重要なコンポーネントであるJTS Topology Suiteは3D空間操作をサポートしていないため、ソリッドジオメトリもサポートしていません。 この講演では、3D空間データを扱うために私たちが実装したGeoServerの拡張モジュールを紹介します。
GeoServer, one of the representative open source spatial data servers, provides many powerful features. In particular, it supports connecting to and publishing spatial data from a variety of data sources. GeoServer also supports Web Feature Service (WFS), which is a standard protocol established by the Open Geospatial Consortium to request geospatial feature data. However, GeoServer provides functions only for two-dimensional geometry, so it provides few functions for handling 3D spatial data. Because JTS Topology Suite, which is an important component of GeoServer, does not support 3D spatial operations, it also does not support solid geometries. In this talk, I will introduce extension modules of GeoServer that we have implemented to handle 3D spatial data.
Normal mapping is a technique used in 3D computer graphics to add detail to 3D models without increasing the number of polygons. It works by encoding normal vector information for light calculation into RGB texture maps. This allows more detailed surface shapes and lighting than would be possible with just the base polygon mesh. The technique was introduced in the late 1990s and became widely used in video games starting in the early 2000s as hardware accelerated shaders became available, enabling real-time normal mapping rendering. It provides a good quality to performance ratio for complex surface details.
This document discusses neural network architectures for image classification including VGG16, InceptionResNetv2, and a custom Deep Pneumonia Net. It compares the performance of these models on diagnosing pneumonia, finding that Deep Pneumonia Net achieves the highest test accuracy of 96.5% while using fewer parameters than VGG16 or InceptionResNetv2. Confusion matrices show Deep Pneumonia Net has a 97.3% recall rate and InceptionResNetv2 has a 94.4% recall rate for pneumonia classification.
This document discusses several topics in image enhancement and processing including:
1. Spatial filtering which involves applying a weighted mask over an image to replace pixel values.
2. Logarithmic transformation which expands darker pixel values more than brighter ones for enhancement.
3. Thresholding, logarithmic transformation, negative transformation, contrast stretching, and grey level slicing as common nonlinear image transformations.
4. Weighted average filtering which applies different coefficients to pixels to give more importance to some over others.
5. High boost filters and unsharp masking as types of high pass sharpening filters used to highlight fine image details.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
[論文紹介] DPSNet: End-to-end Deep Plane Sweep StereoSeiya Ito
DPSNet is an end-to-end deep learning model that estimates dense depth maps from stereo image pairs. It generates cost volumes from multi-scale feature maps of reference and paired images. It then refines the cost slices with dilated convolutions considering contextual information. Finally, it regresses the depth maps from the initial and refined cost volumes. Evaluation on various datasets shows DPSNet achieves state-of-the-art performance in depth map estimation, outperforming other methods in terms of accuracy metrics while maintaining full completeness of predictions.
Double patterning lithography is a technique used to overcome the limitations of optical lithography. It works by splitting the mask pattern into two separate exposures to reduce feature density. The document describes the key techniques used in their software to solve the layout splitting problem, including a novel polygon cutting algorithm, dynamic priority search trees, and representing the problem as a tri-connected graph to decompose it into independent subproblems. Experimental results showed their method achieved a 3-10x speedup over other approaches.
3D modeling involves using computer simulation software to mathematically represent real-life objects in three dimensions - width, height, and depth along the x, y, and z axes. There are two main types of 3D models: solid models, which show objects realistically for CAD, and shell boundary models, which show just the surface. 3D modeling is widely used in computer games, simulations, and other fields to create highly detailed and realistic looking 3D graphics, animations, and virtual objects.
The document discusses image segmentation techniques. It defines image segmentation as partitioning a digital image into multiple segments or regions that are similar in characteristics such as color or texture. The main goal of image segmentation is to simplify an image into meaningful parts for analysis. Common techniques discussed include thresholding, clustering, edge detection, region growing, and neural networks. Thresholding uses threshold values to separate pixels into multiple classes or objects. Clustering groups similar image pixels together while edge detection finds boundaries between objects. The document also provides an example of the split and merge segmentation method.
This is a presentation which I put together with a classmate for 3d scene visualization for one of my classes. I have many of the slides hidden for the actual presentation as the extra slides were for the final hand in product so i am not sure if they will show. I will update the pdf version with the extra information.
Marker Controlled Segmentation Technique for Medical applicationRushin Shah
Medical image segmentation is a very important field for the medical science. In medical images, edge detection is an important work for object recognition of the human organs such as brain, heart or kidney etc. and it is an essential pre-processing step in medical image segmentation.
Medical images such as CT, MRI or X-Ray visualizes the various information’s of internal organs which is very important for doctors diagnoses as well as medical teaching, learning and research.
It is a tough job to locate the internal organs if images contains noise or rough structure of human body organs.
Creating Boring Logs with EnviroInsite and EQuISBruce Jacobs
EnviroInsite's boring log design flexibility is state-of-the-art. This presentation describes how fields in the EQuIS database can be selected from to create information-rich boring logs in EnviroInsite
(1) The document presents a methodology for generalizing 3D building models within CityGML for disaster and emergency management.
(2) The methodology involves 6 steps: derivation of coarse levels of detail, projection of outlier buildings, simplification of ground plans, aggregation, and reconstruction of simplified wall elements.
(3) The methodology was implemented in C++ and able to generalize 3D building models to support disaster response and recovery by providing different levels of detail for analysis and visualization.
Texture mapping involves adding graphics like photographs or designs to 3D polygon objects to make them appear more realistic. Shaders describe an object's material properties like how light is reflected. UV mapping projects a 3D model onto a 2D plane to make texture application easier. Specularity defines how surfaces reflect light to appear shiny. Normals indicate surface direction. Bump maps simulate small surface details without extra geometry. Transparency maps use black/white values to determine opacity. Normal maps store surface orientation data to mimic detail. Baking combines textures, materials, and lighting into single images to streamline rendering.
Color and appearance information in 3d modelsFrederic Kaplan
This document discusses methods for representing color and visual appearance on 3D models. It describes how color is determined by the interaction of lighting and material properties. Common representations of visual appearance include reflectance functions, BSSRDFs, SVBRDFs and BRDFs. Texture mapping and color projection from photographs are introduced as ways to encode color information onto 3D geometry. Issues with photo shooting, registration, material estimation and color projection are discussed. The document recommends resources for learning more about these topics.
Double patterning lithography is a technique used to print integrated circuit designs when feature sizes shrink below the resolution limits of a single exposure. It involves splitting the circuit layout into two masks and exposing the photo-resist layer twice to print the full design. Decomposing the circuit layout and assigning patterns to the two masks is an NP-hard graph coloring problem. The document describes techniques for decomposing the conflict graph that represents incompatible patterns, including using SPQR trees to decompose into tri-connected components and solving each independently. Experimental results show the proposed method can achieve a 3-10x speedup over other approaches.
This document discusses double patterning lithography techniques. It introduces how optical lithography is approaching its limits and double patterning is needed for smaller feature sizes. It describes the double patterning process and challenges including feature distortion and decreased yield. The document outlines techniques for polygon cutting, priority search trees, and decomposing conflict graphs into tri-connected components to solve the layout splitting problem. Experimental results on test cases including a 320k polygon design show the method achieves 3-10x speedup.
代表的なオープンソース空間データサーバの1つであるGeoServerは、多くの強力な機能を提供します。 特に、さまざまなデータソースからの空間データへの接続とパブリッシングをサポートします。 GeoServerはOpen Geospatial Consortiumによって地理空間フィーチャデータを要求するために設定された標準プロトコルであるWeb Feature Service(WFS)もサポートしています。 しかしながら、GeoServerは2次元ジオメトリのための関数しか提供しないため、3D空間データを処理する関数はほとんどありません。 GeoServerの重要なコンポーネントであるJTS Topology Suiteは3D空間操作をサポートしていないため、ソリッドジオメトリもサポートしていません。 この講演では、3D空間データを扱うために私たちが実装したGeoServerの拡張モジュールを紹介します。
GeoServer, one of the representative open source spatial data servers, provides many powerful features. In particular, it supports connecting to and publishing spatial data from a variety of data sources. GeoServer also supports Web Feature Service (WFS), which is a standard protocol established by the Open Geospatial Consortium to request geospatial feature data. However, GeoServer provides functions only for two-dimensional geometry, so it provides few functions for handling 3D spatial data. Because JTS Topology Suite, which is an important component of GeoServer, does not support 3D spatial operations, it also does not support solid geometries. In this talk, I will introduce extension modules of GeoServer that we have implemented to handle 3D spatial data.
Normal mapping is a technique used in 3D computer graphics to add detail to 3D models without increasing the number of polygons. It works by encoding normal vector information for light calculation into RGB texture maps. This allows more detailed surface shapes and lighting than would be possible with just the base polygon mesh. The technique was introduced in the late 1990s and became widely used in video games starting in the early 2000s as hardware accelerated shaders became available, enabling real-time normal mapping rendering. It provides a good quality to performance ratio for complex surface details.
This document discusses neural network architectures for image classification including VGG16, InceptionResNetv2, and a custom Deep Pneumonia Net. It compares the performance of these models on diagnosing pneumonia, finding that Deep Pneumonia Net achieves the highest test accuracy of 96.5% while using fewer parameters than VGG16 or InceptionResNetv2. Confusion matrices show Deep Pneumonia Net has a 97.3% recall rate and InceptionResNetv2 has a 94.4% recall rate for pneumonia classification.
This document discusses several topics in image enhancement and processing including:
1. Spatial filtering which involves applying a weighted mask over an image to replace pixel values.
2. Logarithmic transformation which expands darker pixel values more than brighter ones for enhancement.
3. Thresholding, logarithmic transformation, negative transformation, contrast stretching, and grey level slicing as common nonlinear image transformations.
4. Weighted average filtering which applies different coefficients to pixels to give more importance to some over others.
5. High boost filters and unsharp masking as types of high pass sharpening filters used to highlight fine image details.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
[論文紹介] DPSNet: End-to-end Deep Plane Sweep StereoSeiya Ito
DPSNet is an end-to-end deep learning model that estimates dense depth maps from stereo image pairs. It generates cost volumes from multi-scale feature maps of reference and paired images. It then refines the cost slices with dilated convolutions considering contextual information. Finally, it regresses the depth maps from the initial and refined cost volumes. Evaluation on various datasets shows DPSNet achieves state-of-the-art performance in depth map estimation, outperforming other methods in terms of accuracy metrics while maintaining full completeness of predictions.
Double patterning lithography is a technique used to overcome the limitations of optical lithography. It works by splitting the mask pattern into two separate exposures to reduce feature density. The document describes the key techniques used in their software to solve the layout splitting problem, including a novel polygon cutting algorithm, dynamic priority search trees, and representing the problem as a tri-connected graph to decompose it into independent subproblems. Experimental results showed their method achieved a 3-10x speedup over other approaches.
3D modeling involves using computer simulation software to mathematically represent real-life objects in three dimensions - width, height, and depth along the x, y, and z axes. There are two main types of 3D models: solid models, which show objects realistically for CAD, and shell boundary models, which show just the surface. 3D modeling is widely used in computer games, simulations, and other fields to create highly detailed and realistic looking 3D graphics, animations, and virtual objects.
The document discusses image segmentation techniques. It defines image segmentation as partitioning a digital image into multiple segments or regions that are similar in characteristics such as color or texture. The main goal of image segmentation is to simplify an image into meaningful parts for analysis. Common techniques discussed include thresholding, clustering, edge detection, region growing, and neural networks. Thresholding uses threshold values to separate pixels into multiple classes or objects. Clustering groups similar image pixels together while edge detection finds boundaries between objects. The document also provides an example of the split and merge segmentation method.
This is a presentation which I put together with a classmate for 3d scene visualization for one of my classes. I have many of the slides hidden for the actual presentation as the extra slides were for the final hand in product so i am not sure if they will show. I will update the pdf version with the extra information.
Marker Controlled Segmentation Technique for Medical applicationRushin Shah
Medical image segmentation is a very important field for the medical science. In medical images, edge detection is an important work for object recognition of the human organs such as brain, heart or kidney etc. and it is an essential pre-processing step in medical image segmentation.
Medical images such as CT, MRI or X-Ray visualizes the various information’s of internal organs which is very important for doctors diagnoses as well as medical teaching, learning and research.
It is a tough job to locate the internal organs if images contains noise or rough structure of human body organs.
Creating Boring Logs with EnviroInsite and EQuISBruce Jacobs
EnviroInsite's boring log design flexibility is state-of-the-art. This presentation describes how fields in the EQuIS database can be selected from to create information-rich boring logs in EnviroInsite
EnviroInsite training workshop - Overview of EnviroInsite FeaturesBruce Jacobs
Presentation used in EnviroInsite training workshop. Includes overview of program features used in mapping, data visualization, and generation of hydrogeologic conceptual model.
EnviroInsite training workshop - Three-dimensional contoursBruce Jacobs
The document discusses 3D contouring in EnviroInsite software. It explains the 4 main steps: 1) select data, 2) create a 3D grid, 3) perform 3D interpolation, and 4) generate contour shells. It provides hints on slicing the grid into contour shells and using inverse distance interpolation for smoother contours. The document also describes how the software calculates volumes and masses within contour intervals using Monte Carlo integration. Finally, it explains how to drape an image onto either a ground surface or DEM points.
EnviroInsite training workshop - Creating cross-sectionsBruce Jacobs
This document provides an overview of cross-sections and 3D modeling in EnviroInsite. It describes how cross-sections can be defined using polylines and can include various data. It also explains how the ground and bottom surfaces of cross-sections are interpolated. The document contrasts 3D and plan views, describing how objects are rendered differently. It outlines the controls for 3D view rotation and rendering modes. Finally, it briefly introduces the lighting model used for 3D rendering.
EnviroInsite training workshop - environmental forensicsBruce Jacobs
This document discusses tools for plotting and analyzing multiple analytes, including data tables, pie charts, radial diagrams, charts, and scatter plots. It is from an EnviroInsite training workshop in March 2013 and includes hands-on exercises for using these various analysis tools.
EnviroInsite can serve as a Web Map Service client. Presentation describes procedures for selecting the coordinate system and the features from a particular web map service.
EnviroInsite w/ EQuIS K'Nect - August 2016Bruce Jacobs
EnviroInsite w/ EQuIS K'Nect is a software that integrates boring logs, contouring, GIS-style mapping, profiles, 3D visualization, fence diagrams, and other features into ESRI's ArcGIS software without requiring additional modules. It allows users to access environmental data from EQuIS directly in GIS/CAD projects. The presentation provided information on licensing models and support options for EnviroInsite. Users were given a promo code for 10% off if payment is received before September 1.
EnviroInsite training workshop - Developing a conceptual modelBruce Jacobs
The document discusses developing a hydrogeologic conceptual model. It describes taking boring logs and other subsurface data and integrating that information to create:
- Strip logs showing soil/rock types across a site
- Sections showing soil/rock types and stratigraphy in 2D
- 3D geologic models to understand the subsurface in 3 dimensions
The goal is to conceptualize the large-scale stratigraphic units and hydrogeology based on detailed boring log data and other site characterization. This conceptual model informs further hydrogeologic analysis and site investigations.
EnviroInsite w/ EQuIS K'Nect - August 2016Bruce Jacobs
EnviroInsite w/ EQuIS K'Nect is software that integrates EnviroInsite's environmental data visualization tools with the EQuIS database program. It allows users to create boring logs, contours, GIS maps, profiles, 3D visualizations, and other graphs directly from EQuIS data. The software can be used as an add-on without other modules and supports innovative workflows where GIS and database teams collaborate. It offers flexible licensing options for network or single users.
EnviroInsite training workshop - geochemistry visualization toolsBruce Jacobs
Presentation used in EnviroInsite training workshop for description of geochemistry visualization tools such as the Piper, Stiff, Durov, and Schoeller Diagrams, scatter charts, and georeferenced Stiff Diagrams
EnviroInsite training workshop - Creating boring logsBruce Jacobs
The document summarizes a boring log from a well construction and sampling project. It includes a header with project details and tables describing different aspects of well construction, including the type and depth of various materials found during drilling. Graphic logs depict soil profiles with depth, noting soil type, color, and other characteristics. The logs also indicate sampling depths and other remarks. The document provides detailed information on the stratigraphy and construction of monitoring wells.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on integration of Salesforce with Bonterra Impact Management.
Interested in deploying an integration with Salesforce for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Dandelion Hashtable: beyond billion requests per second on a commodity serverAntonios Katsarakis
This slide deck presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block request processing in three cases. First, most hashtables block while waiting for data to be retrieved from memory. Second, open-addressing designs, which represent the current state-of-the-art, either cannot free index slots on deletes or must block all requests to do so. Third, index resizes block every request until all objects are copied to the new index. Defying folklore wisdom, DLHT forgoes open-addressing and adopts a fully-featured and memory-aware closed-addressing design based on bounded cache-line-chaining. This design offers lock-free index operations and deletes that free slots instantly, (2) completes most requests with a single memory access, (3) utilizes software prefetching to hide memory latencies, and (4) employs a novel non-blocking and parallel resizing. In a commodity server and a memory-resident workload, DLHT surpasses 1.6B requests per second and provides 3.5x (12x) the throughput of the state-of-the-art closed-addressing (open-addressing) resizable hashtable on Gets (Deletes).
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
In the realm of cybersecurity, offensive security practices act as a critical shield. By simulating real-world attacks in a controlled environment, these techniques expose vulnerabilities before malicious actors can exploit them. This proactive approach allows manufacturers to identify and fix weaknesses, significantly enhancing system security.
This presentation delves into the development of a system designed to mimic Galileo's Open Service signal using software-defined radio (SDR) technology. We'll begin with a foundational overview of both Global Navigation Satellite Systems (GNSS) and the intricacies of digital signal processing.
The presentation culminates in a live demonstration. We'll showcase the manipulation of Galileo's Open Service pilot signal, simulating an attack on various software and hardware systems. This practical demonstration serves to highlight the potential consequences of unaddressed vulnerabilities, emphasizing the importance of offensive security practices in safeguarding critical infrastructure.
2. 3d Contouring
1
1.5
1. Select Data
2.1
2.7
2. Create 3d Grid
3
3.9
4
5.1
7.0
7
4.2
5.7
7.5
4.2
3. 3d Interpolation
6.5
6
8.2
4. Contour Shells
9
Similar to 2d, but no polyline bounds
3d Contouring
3. 3d Contouring Hints
• Can “slice” into
contour shells by
modifying grid extent
• Inverse distance
seems to create
smoother contours
• Z-Scale parameter in
inverse distance
reduces vertical
spreading
3d Contouring
4. Volume / Mass Calculation
• EI Evaluates volume
within each contour
interval
• Monte Carlo integration
• Mass = C x V x porosity
3d Contouring
5. Draped Image
• Image draped to
either:
Ground Surface
defined at wells
Set of X,Y,Z points
(DEM data)
3d Contouring