ARCHAEOLOGICAL LAND USE CHARACTERIZATION USING MULTISPECTRAL REMOTE SENSING DATA
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This document summarizes a new approach for classifying remote sensing signatures extracted from multispectral imagery. It combines spectral signatures to perform accurate classification. Simulation results are provided to verify the efficiency of the proposed weighted pixel statistics approach, which uses information from multiple spectral bands. It is shown to provide more accurate and less smoothed identification of classes compared to traditional weighted order statistics methods.
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![Archaeological Land Use Characterization using Multispectral Remote Sensing Data ,[object Object],[object Object],Monitoring Hidrological Variations using Multispectral SPOT-5 Data: Regional Case of Jalisco in Mexico Dr. Iván Esteban Villalón Turrubiates, Member, IEEE UNIVERSIDAD DE GUADALAJARA CENTRO UNIVERSITARIO DE LOS VALLES](https://image.slidesharecdn.com/igarss-2011-arch3-110725160410-phpapp02/85/ARCHAEOLOGICAL-LAND-USE-CHARACTERIZATION-USING-MULTISPECTRAL-REMOTE-SENSING-DATA-1-320.jpg)
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The document summarizes the pre-launch calibration of CERES Flight Model 5 (FM5) instrument that will be onboard the NPP spacecraft. The calibration involved characterizing the instrument's response to longwave, shortwave, and total radiation. Tests were conducted in a radiometric calibration facility using internal calibration sources and external blackbody sources. The results were within the measurement accuracy requirements, with gains of 8.577 counts/Wm-2 for total radiation and 10.495 counts/Wm-2 for window channels. On-board calibration sources will provide a transfer standard to track changes after launch.
FR1.T03.1 Meeting Slides of MHS_TB over Antarctica_7_29_11.pptx
This document summarizes a study of near-nadir microwave brightness temperatures from NOAA satellites over Antarctica:
1) Measurements from NOAA-18, NOAA-19, and METOP-A showed little diurnal variability in Antarctic winter months due to 24-hour nighttime.
2) Differences between ascending and descending measurements were used to determine intersatellite/intersensor calibration biases, showing Antarctica is useful for calibration validation.
3) Long-term monitoring of instrument performance on NOAA-18 and NOAA-19 showed microwave humidity sounder and AMUS-A measurements remained stable over multiple time periods from launch.
IGARSS11_VC_ppt.pdf
The document summarizes ASTER/TIR vicarious calibration activities over the past 11 years. It describes the ASTER instrument, calibration methods, vicarious calibration sites used, experimental setup, and results of comparisons between onboard calibrator and vicarious calibration measurements. The comparisons show that the onboard calibrator has maintained an accuracy of 1K over a temperature range of 270-340K, though some sites show larger differences due to factors like straylight, low temperatures, and spatial variability.
TU1.T10.5.ppt
The document presents a new technique called C-2PO for retrieving wind speeds from cross-polarized synthetic aperture radar (SAR) data during hurricanes. C-2PO uses the cross-polarization ratio, which is insensitive to wind direction and incidence angle, making it easier to map to wind speed compared to existing techniques. Comparisons show C-2PO provides more accurate wind speed retrievals than existing methods for hurricanes, with lower biases and errors. Reasons include existing models becoming saturated at high winds and not accounting for rain and other factors that impact radar backscatter.
PlenaryAwards Presentation 2011.ppt
This document lists several award recipients from the 2011 IEEE (Institute of Electrical and Electronics Engineers). It recognizes Kamal Sarabandi for contributions to radar remote sensing, Adriano Camps for microwave remote sensing of land and sea surfaces, and Anthony Milne for leadership in remote sensing applications. Paul Rosen, Masanobu Shimada, and Eric Pottier received awards for their work in areas like radar remote sensing, radar technologies, and network theory. Thomas Jackson was recognized for advances in soil moisture remote sensing, and Richard Bamler received an education award for contributions to remote sensing education.
IGARSS2011_eguchi.ppt
The document summarizes the status and findings of version 01.xx of the GOSAT TANSO-FTS SWIR Level 2 retrieval algorithm. It finds that 93% of level 1B data is removed through quality screening. The seasonal variations of XCO2 and XCH4 seen in the retrievals are generally consistent with prior knowledge, though some regional biases exist. The data quality and accumulation over time will enable further scientific analysis of trends, seasonal cycles and variability for carbon flux estimation.
NPOESSPreparatoryProjectValidationPlansfortheOzoneMappingandProfilerSuite.ppt
This document outlines validation plans for the Ozone Mapping and Profiler Suite (OMPS) instrument on the NPOESS Preparatory Project satellite. It discusses:
1) The calibration and validation team members and their roles in characterizing instrument performance through comparisons with other satellite and ground-based instruments from launch through long-term monitoring.
2) The schedule of major validation tasks from pre-launch testing through intensive in-orbit validation in the first two years and transition to long-term monitoring.
3) Examples of early tests and comparisons that will be done with internal instrument measurements, early solar views, and single days of Earth view data to evaluate performance.
IGARSS2011-1538-Presentation-PPT-File_P.Lei.ppt
The document discusses radar micro-Doppler (mD) analysis and rotation parameter estimation for rigid targets with complicated micro-motions. It presents an inertial model to describe the attitude dynamics of free symmetric rigid bodies with a single scattering center. The mD frequency is expressed as a linear sum of four sinusoidal components related to the spin and precession rates. An estimation method using the RELAX algorithm can accurately estimate the spin and precession rates from noisy mD data when the SNR is over 13dB.
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FR1.T03.1 Meeting Slides of MHS_TB over Antarctica_7_29_11.pptx
FR1.T03.1 Meeting Slides of MHS_TB over Antarctica_7_29_11.pptx
NPOESSPreparatoryProjectValidationPlansfortheOzoneMappingandProfilerSuite.ppt
NPOESSPreparatoryProjectValidationPlansfortheOzoneMappingandProfilerSuite.ppt
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Super-Resolution of Multispectral Images
This document summarizes a proposed method for super-resolution of multispectral images using principal component analysis. It begins with background on multispectral imaging and issues with resolution. The proposed method first uses PCA to reduce the dimensionality of the multispectral data. It then learns edge details from a high-resolution database by matching blocks of the principal components. After learning, the modified principal components are inverse transformed to generate a higher resolution multispectral image. The method is tested on real multispectral data sets and shown to reconstruct higher resolution images.
Digital image classification22oct
Digital image classification is the process of sorting pixels into categories based on their spectral values. There are supervised and unsupervised classification methods. Supervised classification involves using training sites of known categories to define statistical signatures for each class. Unsupervised classification groups pixels into clusters without prior class definitions. Validation is needed to assess classification accuracy by comparing results to ground truth data. Factors like training site selection and signature separability impact classification performance.
Object Classification of Satellite Images Using Cluster Repulsion Based Kerne...
Abstract: We investigated the Classification of satellite images and multispectral remote sensing data .we
focused on uncertainty analysis in the produced land-cover maps .we proposed an efficient technique for
classifying the multispectral satellite images using Support Vector Machine (SVM) into road area, building area
and green area. We carried out classification in three modules namely (a) Preprocessing using Gaussian
filtering and conversion from conversion of RGB to Lab color space image (b) object segmentation using
proposed Cluster repulsion based kernel Fuzzy C- Means (FCM) and (c) classification using one-to-many SVM
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Keywords:-Satellite image, FCM Clustering, Classification, SVM classifier.
Fd36957962
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Digital_Image_Classification.pptx
This document discusses digital image classification and accuracy assessment. It covers topics such as spectral signatures, supervised vs. unsupervised classification, object-based image analysis, and accuracy assessment methods. The key points are:
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- Supervised classification uses training samples of known identity to classify pixels, while unsupervised classification uses computer clustering to group spectrally similar pixels without training data.
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Digital image processing
Digital image processing ,Techniques of Digital Image Processing
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remote sensing applications.
Comparison of Segmentation Algorithms and Estimation of Optimal Segmentation ...
Comparison of Segmentation Algorithms and Estimation of Optimal Segmentation ...Pinaki Ranjan Sarkar
Recent advancement in sensor technology allows very high spatial resolution along with multiple spectral bands. There are many studies, which highlight that Object Based Image Analysis(OBIA) is more accurate than pixel-based classification for high resolution(< 2m) imagery. Image segmentation is a crucial step for OBIA and it is a very formidable task to estimate optimal parameters for segmentation as it does not have any unique solution. In this paper, we have studied different segmentation algorithms (both mono-scale and multi-scale) for different terrain categories and showed how the segmented output depends on upon various parameters. Later, we have introduced a novel method to estimate optimal segmentation parameters. The main objectives of this study are to highlight the effectiveness of presently available segmentation techniques on very high-resolution satellite data and to automate segmentation process. Pre-estimation of segmentation parameter is more practical and efficient in OBIA. Assessment of segmentation algorithms and estimation of segmentation parameters are examined based on the very high-resolution multi-spectral WorldView-3(0.3m, PAN sharpened) data.Digital Image Classification.pptx
Digital image classification involves sorting pixels into discrete classes based on their spectral values. It can be performed using supervised or unsupervised approaches. Supervised classification involves using training data to define classes, while unsupervised classification uses algorithms to automatically group similar pixels. Accuracy assessment involves comparing the classification to reference data to determine accuracy through an error matrix.
COLOUR IMAGE REPRESENTION OF MULTISPECTRAL IMAGE FUSION
This document summarizes a research paper on using the Cholesky decomposition technique to fuse multispectral images and represent them as a color image. It discusses how multispectral image fusion works by combining images from different spectral bands. It then describes the VTVA (Vector valued Total Variation Algorithm) technique in detail, which uses the covariance matrix and Cholesky decomposition to control the correlation between color components in the fused image. This technique is compared to principal component analysis. The document provides background on RGB color space, color perception, and Cholesky decomposition before outlining the specific steps of the VTVA algorithm.
COLOUR IMAGE REPRESENTION OF MULTISPECTRAL IMAGE FUSION
The availability of imaging sensors operating in multiple spectral bands has led to the requirement of
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Satellite Image Classification using Decision Tree, SVM and k-Nearest Neighbor
Satellite Image Classification using Decision Tree, SVM and k-Nearest NeighborNational Cheng Kung University
This document summarizes research comparing three machine learning classification methods - Decision Tree, Support Vector Machine (SVM), and k-Nearest Neighbors (k-NN) - for classifying land use from high and low resolution satellite imagery. The researchers applied each method to classify Pleiades satellite images of Taiwan and Colorado. SVM achieved the highest overall accuracy of 78.6% for high resolution imagery and 83.3% for low resolution imagery. Decision Trees and k-NN were less accurate. The document outlines the methodology, including image preprocessing, parameter selection, accuracy assessment, and findings.P.maria sheeba 15 mco010
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International Journal of Engineering Research and Applications (IJERA) aims to cover the latest outstanding developments in the field of all Engineering Technologies & science.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
Detection of urban tree canopy from very high resolution imagery using an ob...
Tree that grows within a town, city and suburban areas, collection of these trees makes the urban forest. These urban forest and urban trees have impact on urban water, pollution and heat. Nowadays we are experiencing drastic climatic changes because of cutting of trees for our growth and increasing population which leads to expansion of roads, towers, and airports. Individual tree crown detection is necessary to map the forest along with feasible planning for urban areas. In this study, using WorldView-2imagery, trees in specific area are detected with object-based image analysis (OBAI) approach. Therefore with improvement in spatial and spectral resolution of an image, extracted from WorldView-2 carried out urban features with better accuracy. The aim of this research is to illustrate how object-based method can be applied to the available data to accurately find out vegetation, which can be further sub-classified to obtain area under tree canopy. The result thus obtained gives area under tree canopy with an accuracy of 92.43 % and a Kappa coefficient of 0.80.
IMAGE QUALITY OPTIMIZATION USING RSATV
Abstract: Primarily due to the progresses in super resolution imagery, the methods of segment-based image analysis for generating and updating geographical information are becoming more and more important. This work presents a image segmentation based on colour features with K-means clustering. The entire work is divided into two stages. First enhancement of color separation of satellite image using de correlation stretching is carried out and then the regions are grouped into a set of five classes using K-means clustering algorithm. At first, the spatial data is concentrated focused around every pixel, and at that point two separating procedures are added to smother the impact of pseudoedges. What's more, the spatial data weight is built and grouped with k-means bunching, and the regularization quality in every district is controlled by the bunching focus esteem. The exploratory results, on both reenacted and genuine datasets, demonstrate that the proposed methodology can adequately lessen the pseudoedges of the aggregate variety regularization in the level.
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International Journal of Engineering Research and Applications (IJERA) aims to cover the latest outstanding developments in the field of all Engineering Technologies & science.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
CLASSIFICATION AND COMPARISION OF REMOTE SENSING IMAGE USING SUPPORT VECTOR M...
Remote sensing is collecting information about an object without any direct physical contact with the particular object. It is widely used in many fields such as oceanography, geology, ecology. Remote sensing uses the Satellite to detect and classify the particular object or area. They also classify the object on the earth surfaces which includes Vegetation, Building, Soil, Forest and Water. The approach uses the classifiers of previous images to decrease the required number of training samples for the classifier training of an incoming image. For each incoming image, a rough classifier is predicted first based on the temporal trend of a set of previous classifiers. The predicted classifier is then fine-tuned into a more accurate manner with current training samples. This approach can be further applied as sequential image data, with only a small number of training samples, which are being required from each image. This method uses LANSAT 8 images for Training and Testing processes. First, using the Classifier Prediction technique the Signatures are being generated for the input images. The generated Signatures are used for the Training purposes. SVM Classification is used for classifying the images. The final results describes that the leverage of a priori information from previous images will provide advantageous improvement for future images in multi temporal image classification.
RADIOMETRIC RESOLUTION.pptx
Radiometric resolution refers to a sensor's ability to distinguish slight differences in energy levels and is measured in bits. More bits allows an image to store more grayscale values, enabling better discrimination between classes. For example, Landsat-8 has 12-bit resolution, allowing it to distinguish over 4,000 grayscale levels and better characterize land cover compared to Landsat-7's 8-bit resolution of 256 levels. Higher radiometric resolution improves a sensor's sensitivity to capture subtle differences in surface reflectance.
Shadow Detection and Removal Techniques A Perspective View
This document discusses techniques for shadow detection and removal in images. It provides an overview of various methods used, including those based on texture analysis, color information, Gaussian mixture models, and deterministic non-model based approaches. The document then reviews several published papers on different shadow detection and removal algorithms. These algorithms are compared based on advantages and disadvantages in terms of accuracy, computational efficiency, and applicability to different image types and conditions. The conclusion is that shadows remain a challenging problem for computer vision tasks and that the most suitable detection and removal technique depends on the specific image type and application.
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Removing Uninteresting Bytes in Software Fuzzing
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
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Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
National Security Agency - NSA mobile device best practices
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
Communications Mining Series - Zero to Hero - Session 1
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
UiPath Test Automation using UiPath Test Suite series, part 5
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
UiPath Test Automation using UiPath Test Suite series, part 6
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
20240607 QFM018 Elixir Reading List May 2024
Everything I found interesting about the Elixir programming ecosystem in May 2024
20240605 QFM017 Machine Intelligence Reading List May 2024
Everything I found interesting about machines behaving intelligently during May 2024
Climate Impact of Software Testing at Nordic Testing Days
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Pushing the limits of ePRTC: 100ns holdover for 100 days
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
How to Get CNIC Information System with Paksim Ga.pptx
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
HCL Notes and Domino License Cost Reduction in the World of DLAU
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
TrustArc Webinar - 2024 Global Privacy Survey
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
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Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
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Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
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National Security Agency - NSA mobile device best practices
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HCL Notes and Domino License Cost Reduction in the World of DLAU
ARCHAEOLOGICAL LAND USE CHARACTERIZATION USING MULTISPECTRAL REMOTE SENSING DATA
- 10. A) Illumination Source B) Radiation C) Interaction with the object D) Radiation sensing E) Transmission, reception and data processing F) Analysis and interpretation G) Application Process
- 15. Temporal Resolution Time July 1 July 12 July 23 August 3 11 days 16 days July 2 July 8 August 3
- 16. Radiometric Resolution 6-bits Range 0 63 8-bits Range 0 255 0 10-bits Range 1023
- 17. INTRODUCTION TO IMAGE CLASSIFICATION
- 24. Basic Strategy: How to do it? But in reality, that is not the case. Looking at several pixels with vegetation, you’d see variety in spectral signatures. The same would happen for other types of pixels, as well.
- 26. Think of a pixel’s brightness in a 2-Dimensional space. The pixel occupies a point in that space. The vegetation pixel and the soil pixel occupy different points in a 2-D space.
- 27. With variability, the vegetation pixels now occupy a region, not a point, of n-Dimensional space. Soil pixels occupy a different region of n-Dimensional space.
- 30. Supervised Classification The computer then creates... Supervised classification requires the analyst to select training areas where he knows what is on the ground and then digitize a polygon within that area… Mean Spectral Signatures Known Conifer Area Known Water Area Known Deciduous Area Digital Image Conifer Deciduous Water
- 31. Supervised Classification Multispectral Image Information (Classified Image) Mean Spectral Signatures Spectral Signature of Next Pixel to be Classified Conifer Deciduous Water Unknown
- 32. The Result: Image Signatures Water Conifer Deciduous Legend: Land Cover Map
- 34. Unsupervised Classification Digital Image The analyst requests the computer to examine the image and extract a number of spectrally distinct clusters… Spectrally Distinct Clusters Cluster 3 Cluster 5 Cluster 1 Cluster 6 Cluster 2 Cluster 4
- 35. Unsupervised Classification Output Classified Image Saved Clusters Cluster 3 Cluster 5 Cluster 1 Cluster 6 Cluster 2 Cluster 4 Unknown Next Pixel to be Classified
- 36. Unsupervised Classification It is a simple process to regroup (recode) the clusters into meaningful information classes (the legend). The result is essentially the same as that of the supervised classification: Conif. Hardw. Water Land Cover Map Legend Water Water Conifer Conifer Hardwood Hardwood Labels
- 37. MODEL FORMALISM
- 40. Blue Green Red Near-IR Mid-IR Mean Signature 1 Candidate Pixel Mean Signature 2 It appears that the candidate pixel is closest to Signature 1. However, when we consider the variance around the signatures… Relative Reflectance Weighted Pixel Statistics Method
- 41. Blue Green Red Near-IR Mid-IR Mean Signature 1 Candidate Pixel Mean Signature 2 The candidate pixel clearly belongs to the signature 2 group. Relative Reflectance Weighted Pixel Statistics Method
- 42. Weighted Pixel Statistics Method
- 43. Weighted Pixel Statistics Method
- 46. Results: 1 st Synthesized Scene Synthesized Scene WOS Classification WPS Classification
- 47. Quantitative Comparison 1 st Synthesized Scene
- 48. Results: 2 nd Synthesized Scene Synthesized Scene WOS Classification WPS Classification
- 49. Qualitative Comparison 2 nd Synthesized Scene Synthesized Scene WOS Classification WPS Classification
- 50. Quantitative Comparison 2 nd Synthesized Scene
- 51. Results: 3 rd Synthesized Scene Synthesized Scene WOS Classification WPS Classification
- 52. Qualitative Comparison 3 rd Synthesized Scene Synthesized Scene WOS Classification WPS Classification
- 53. Quantitative Comparison 3 rd Synthesized Scene
- 57. Archaeological Site "Guachimontones", Jalisco Mexico
- 58. Simulation Results Scene from "Guachimontones" Original Scene WPS Classification
- 60. Simulation Results Scene from "La Vega" dam, Jalisco Mexico Original Scene WPS Classification
Editor's Notes
- Information usually gathered from spacecraft or an airplane, but can be a handheld or boom-mounted device. Originally defined in 1960’s according to Jensen, to encompass photogrammertry and information gathered from nonphotometric sources.