This slide contain description about the line, circle and ellipse drawing algorithm in computer graphics. It also deals with the filled area primitive.
This slide contain description about the line, circle and ellipse drawing algorithm in computer graphics. It also deals with the filled area primitive.
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Line Drawing Algorithms - Computer Graphics - NotesOmprakash Chauhan
Straight-line drawing algorithms are based on incremental methods.
In incremental method line starts with a straight point, then some fix incrementable is added to current point to get next point on the line and the same has continued all the end of the line.
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Visit Daroko blog for real IT skills applications,androind, Computer graphics,Networking,Programming,IT jobs Types, IT news and applications,blogging,Builing a website, IT companies and how you can form yours, Technology news and very many More IT related subject.
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Line Drawing Algorithms - Computer Graphics - NotesOmprakash Chauhan
Straight-line drawing algorithms are based on incremental methods.
In incremental method line starts with a straight point, then some fix incrementable is added to current point to get next point on the line and the same has continued all the end of the line.
Digital signatures are often used to implement electronic signatures, a broader term that refers to any electronic data that carries the intent of a signature, but not all electronic signatures use digital signatures. In some countries, including the United States, India, and members of the European Union, electronic signatures have legal significance.
This Presentation Elliptical Curve Cryptography give a brief explain about this topic, it will use to enrich your knowledge on this topic. Use this ppt for your reference purpose and if you have any queries you'll ask questions.
Experience our free, in-depth three-part Tendenci Platform Corporate Membership Management workshop series! In Session 1 on May 14th, 2024, we began with an Introduction and Setup, mastering the configuration of your Corporate Membership Module settings to establish membership types, applications, and more. Then, on May 16th, 2024, in Session 2, we focused on binding individual members to a Corporate Membership and Corporate Reps, teaching you how to add individual members and assign Corporate Representatives to manage dues, renewals, and associated members. Finally, on May 28th, 2024, in Session 3, we covered questions and concerns, addressing any queries or issues you may have.
For more Tendenci AMS events, check out www.tendenci.com/events
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
We describe the deployment and use of Globus Compute for remote computation. This content is aimed at researchers who wish to compute on remote resources using a unified programming interface, as well as system administrators who will deploy and operate Globus Compute services on their research computing infrastructure.
Developing Distributed High-performance Computing Capabilities of an Open Sci...Globus
COVID-19 had an unprecedented impact on scientific collaboration. The pandemic and its broad response from the scientific community has forged new relationships among public health practitioners, mathematical modelers, and scientific computing specialists, while revealing critical gaps in exploiting advanced computing systems to support urgent decision making. Informed by our team’s work in applying high-performance computing in support of public health decision makers during the COVID-19 pandemic, we present how Globus technologies are enabling the development of an open science platform for robust epidemic analysis, with the goal of collaborative, secure, distributed, on-demand, and fast time-to-solution analyses to support public health.
Paketo Buildpacks : la meilleure façon de construire des images OCI? DevopsDa...Anthony Dahanne
Les Buildpacks existent depuis plus de 10 ans ! D’abord, ils étaient utilisés pour détecter et construire une application avant de la déployer sur certains PaaS. Ensuite, nous avons pu créer des images Docker (OCI) avec leur dernière génération, les Cloud Native Buildpacks (CNCF en incubation). Sont-ils une bonne alternative au Dockerfile ? Que sont les buildpacks Paketo ? Quelles communautés les soutiennent et comment ?
Venez le découvrir lors de cette session ignite
Prosigns: Transforming Business with Tailored Technology SolutionsProsigns
Unlocking Business Potential: Tailored Technology Solutions by Prosigns
Discover how Prosigns, a leading technology solutions provider, partners with businesses to drive innovation and success. Our presentation showcases our comprehensive range of services, including custom software development, web and mobile app development, AI & ML solutions, blockchain integration, DevOps services, and Microsoft Dynamics 365 support.
Custom Software Development: Prosigns specializes in creating bespoke software solutions that cater to your unique business needs. Our team of experts works closely with you to understand your requirements and deliver tailor-made software that enhances efficiency and drives growth.
Web and Mobile App Development: From responsive websites to intuitive mobile applications, Prosigns develops cutting-edge solutions that engage users and deliver seamless experiences across devices.
AI & ML Solutions: Harnessing the power of Artificial Intelligence and Machine Learning, Prosigns provides smart solutions that automate processes, provide valuable insights, and drive informed decision-making.
Blockchain Integration: Prosigns offers comprehensive blockchain solutions, including development, integration, and consulting services, enabling businesses to leverage blockchain technology for enhanced security, transparency, and efficiency.
DevOps Services: Prosigns' DevOps services streamline development and operations processes, ensuring faster and more reliable software delivery through automation and continuous integration.
Microsoft Dynamics 365 Support: Prosigns provides comprehensive support and maintenance services for Microsoft Dynamics 365, ensuring your system is always up-to-date, secure, and running smoothly.
Learn how our collaborative approach and dedication to excellence help businesses achieve their goals and stay ahead in today's digital landscape. From concept to deployment, Prosigns is your trusted partner for transforming ideas into reality and unlocking the full potential of your business.
Join us on a journey of innovation and growth. Let's partner for success with Prosigns.
SOCRadar Research Team: Latest Activities of IntelBrokerSOCRadar
The European Union Agency for Law Enforcement Cooperation (Europol) has suffered an alleged data breach after a notorious threat actor claimed to have exfiltrated data from its systems. Infamous data leaker IntelBroker posted on the even more infamous BreachForums hacking forum, saying that Europol suffered a data breach this month.
The alleged breach affected Europol agencies CCSE, EC3, Europol Platform for Experts, Law Enforcement Forum, and SIRIUS. Infiltration of these entities can disrupt ongoing investigations and compromise sensitive intelligence shared among international law enforcement agencies.
However, this is neither the first nor the last activity of IntekBroker. We have compiled for you what happened in the last few days. To track such hacker activities on dark web sources like hacker forums, private Telegram channels, and other hidden platforms where cyber threats often originate, you can check SOCRadar’s Dark Web News.
Stay Informed on Threat Actors’ Activity on the Dark Web with SOCRadar!
top nidhi software solution freedownloadvrstrong314
This presentation emphasizes the importance of data security and legal compliance for Nidhi companies in India. It highlights how online Nidhi software solutions, like Vector Nidhi Software, offer advanced features tailored to these needs. Key aspects include encryption, access controls, and audit trails to ensure data security. The software complies with regulatory guidelines from the MCA and RBI and adheres to Nidhi Rules, 2014. With customizable, user-friendly interfaces and real-time features, these Nidhi software solutions enhance efficiency, support growth, and provide exceptional member services. The presentation concludes with contact information for further inquiries.
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...Globus
The Earth System Grid Federation (ESGF) is a global network of data servers that archives and distributes the planet’s largest collection of Earth system model output for thousands of climate and environmental scientists worldwide. Many of these petabyte-scale data archives are located in proximity to large high-performance computing (HPC) or cloud computing resources, but the primary workflow for data users consists of transferring data, and applying computations on a different system. As a part of the ESGF 2.0 US project (funded by the United States Department of Energy Office of Science), we developed pre-defined data workflows, which can be run on-demand, capable of applying many data reduction and data analysis to the large ESGF data archives, transferring only the resultant analysis (ex. visualizations, smaller data files). In this talk, we will showcase a few of these workflows, highlighting how Globus Flows can be used for petabyte-scale climate analysis.
Enhancing Project Management Efficiency_ Leveraging AI Tools like ChatGPT.pdfJay Das
With the advent of artificial intelligence or AI tools, project management processes are undergoing a transformative shift. By using tools like ChatGPT, and Bard organizations can empower their leaders and managers to plan, execute, and monitor projects more effectively.
Understanding Globus Data Transfers with NetSageGlobus
NetSage is an open privacy-aware network measurement, analysis, and visualization service designed to help end-users visualize and reason about large data transfers. NetSage traditionally has used a combination of passive measurements, including SNMP and flow data, as well as active measurements, mainly perfSONAR, to provide longitudinal network performance data visualization. It has been deployed by dozens of networks world wide, and is supported domestically by the Engagement and Performance Operations Center (EPOC), NSF #2328479. We have recently expanded the NetSage data sources to include logs for Globus data transfers, following the same privacy-preserving approach as for Flow data. Using the logs for the Texas Advanced Computing Center (TACC) as an example, this talk will walk through several different example use cases that NetSage can answer, including: Who is using Globus to share data with my institution, and what kind of performance are they able to achieve? How many transfers has Globus supported for us? Which sites are we sharing the most data with, and how is that changing over time? How is my site using Globus to move data internally, and what kind of performance do we see for those transfers? What percentage of data transfers at my institution used Globus, and how did the overall data transfer performance compare to the Globus users?
TROUBLESHOOTING 9 TYPES OF OUTOFMEMORYERRORTier1 app
Even though at surface level ‘java.lang.OutOfMemoryError’ appears as one single error; underlyingly there are 9 types of OutOfMemoryError. Each type of OutOfMemoryError has different causes, diagnosis approaches and solutions. This session equips you with the knowledge, tools, and techniques needed to troubleshoot and conquer OutOfMemoryError in all its forms, ensuring smoother, more efficient Java applications.
Enterprise Resource Planning System includes various modules that reduce any business's workload. Additionally, it organizes the workflows, which drives towards enhancing productivity. Here are a detailed explanation of the ERP modules. Going through the points will help you understand how the software is changing the work dynamics.
To know more details here: https://blogs.nyggs.com/nyggs/enterprise-resource-planning-erp-system-modules/
Exploring Innovations in Data Repository Solutions - Insights from the U.S. G...Globus
The U.S. Geological Survey (USGS) has made substantial investments in meeting evolving scientific, technical, and policy driven demands on storing, managing, and delivering data. As these demands continue to grow in complexity and scale, the USGS must continue to explore innovative solutions to improve its management, curation, sharing, delivering, and preservation approaches for large-scale research data. Supporting these needs, the USGS has partnered with the University of Chicago-Globus to research and develop advanced repository components and workflows leveraging its current investment in Globus. The primary outcome of this partnership includes the development of a prototype enterprise repository, driven by USGS Data Release requirements, through exploration and implementation of the entire suite of the Globus platform offerings, including Globus Flow, Globus Auth, Globus Transfer, and Globus Search. This presentation will provide insights into this research partnership, introduce the unique requirements and challenges being addressed and provide relevant project progress.
Enhancing Research Orchestration Capabilities at ORNL.pdfGlobus
Cross-facility research orchestration comes with ever-changing constraints regarding the availability and suitability of various compute and data resources. In short, a flexible data and processing fabric is needed to enable the dynamic redirection of data and compute tasks throughout the lifecycle of an experiment. In this talk, we illustrate how we easily leveraged Globus services to instrument the ACE research testbed at the Oak Ridge Leadership Computing Facility with flexible data and task orchestration capabilities.
OpenFOAM solver for Helmholtz equation, helmholtzFoam / helmholtzBubbleFoamtakuyayamamoto1800
In this slide, we show the simulation example and the way to compile this solver.
In this solver, the Helmholtz equation can be solved by helmholtzFoam. Also, the Helmholtz equation with uniformly dispersed bubbles can be simulated by helmholtzBubbleFoam.
May Marketo Masterclass, London MUG May 22 2024.pdfAdele Miller
Can't make Adobe Summit in Vegas? No sweat because the EMEA Marketo Engage Champions are coming to London to share their Summit sessions, insights and more!
This is a MUG with a twist you don't want to miss.
First Steps with Globus Compute Multi-User EndpointsGlobus
In this presentation we will share our experiences around getting started with the Globus Compute multi-user endpoint. Working with the Pharmacology group at the University of Auckland, we have previously written an application using Globus Compute that can offload computationally expensive steps in the researcher's workflows, which they wish to manage from their familiar Windows environments, onto the NeSI (New Zealand eScience Infrastructure) cluster. Some of the challenges we have encountered were that each researcher had to set up and manage their own single-user globus compute endpoint and that the workloads had varying resource requirements (CPUs, memory and wall time) between different runs. We hope that the multi-user endpoint will help to address these challenges and share an update on our progress here.
3. What is a Convex Polygon?
• A polygon P is called convex if x in P and y in P implies that
the segment xy is a subset of P.
• A vertex is called reflex if its internal angle is greater than π.
• Any polygon with a reflex vertex is not convex.
3
4. Convex Hull of a Planer Set of Points
• The convex hull of a set of points is the shape taken by a
rubber band stretched around nails pounded into the plane at
each point.
4
5. Convex Layers of a Planer Set of Points
• Let S be the set of points.
• The set of convex layers is derived by applying following
procedure iteratively on S: compute the convex hull of S and
remove its vertices from S.
5
6. Research Problem
• A set of points where points may be inserted or deleted is
called a dynamic set of points.
• A practical algorithm to maintain convex layers of a dynamic
set of points is not available in literature.
6
11. Related Research Paper
K. R. Wijeweera, S. R. Kodituwakku (2018), On the Convex
Layers of a Planer Dynamic Set of Points, Ceylon Journal of
Science, Volume 47 (Issue 2), pp. 165-174.
11
12. Representation of a Layer
• Each convex layer can be represented by a convex polygon.
• The layers are numbered beginning from 0.
• The very first point which arrives should always belong to
the 0th layer.
12
13. Representation of a Layer…
• A layer is represented as a set of edges.
• Edges are also numbered beginning from 0s in each layer.
• Figure shows the representation of jth edge in ith layer.
13
14. Representation of a Layer…
• A layer or an edge can have two states: dead or alive.
• Only alive layers and alive edges are considered as the
convex layers.
• These two states are stored in array elements l_dead[i] and
e_dead[i][j].
• l_dead[i] = 1 ith layer is dead All the edges of the ith
layer are dead.
• e_dead[i][j] = 1 jth edge of the ith layer is dead.
14
16. Construction of the Primary Hull
• Each layer begins with a single point and later it may evolve
to a convex polygon.
• When a layer is a triangle then it is called “primary hull”.
• The very first point should be included to the 0th layer by
setting it as (sx[0][0], sy[0][0]).
• If next point coincides with the very first point then it should
be set as (sx[1][0], sy[1][0]).
• If next point also coincides with the very first point then it
should be set as (sx[2][0], sy[2][0]).
• In this way, coincident points are propagated to inner layers.
16
17. Construction of the Primary Hull…
• The point which is distinct to the very first point for the first
time is set as (ex[0][0], ey[0][0]).
• After insertion of the first edge to the 0th layer then the next
point can have two states: collinear with 0th edge or not.
17
18. Construction of the Primary Hull…
• The vertices of the triangle: P1 (x1, y1), P2 (x2, y2), P3 (x3, y3).
• Let txy = x1 * (y2 – y3) + x2 * (y3 – y1) + x3 * (y1 – y2).
• txy = 0 ↔ (P1, P2, P3) are collinear.
• txy > 0 ↔ (P1, P2, P3) are in anticlockwise order.
• txy < 0 ↔ (P1, P2, P3) are in clockwise order.
18
txy > 0 txy < 0
19. Collinear with the 0th Edge
• If next point is collinear with the 0th edge then there are three
possibilities as shown in the figure.
• In first two situations, the closest end point should be
replaced by the new point. The dropped end point should be
transferred to the closest inner layer.
• There is no extension for the third situation. The new point
should be transferred to the closest inner layer.
19
20. Non Collinear with the 0th Edge
• If next point is not collinear with the 0th edge then the convex
layer should be extended to a triangle.
• Let coordinates of the new point be (x, y).
• Two new edges should be added to the layer h to extend.
• 1st edge: sx[h][1] = x; sy[h][1] = y; ex[h][1] = sx[h][0];
ey[h][1] = sy[h][0];
• 2nd edge: sx[h][2] = x; sy[h][2] = y; ex[h][2] = ex[h][0];
ey[h][2] = ey[h][0];
20
21. Construction of the Secondary Hull
• The mechanism used to extend convex layer differs after the
layer became a triangle.
• Let (xc/3, yc/3) be the centroid of the primary hull.
• xc = sx[h][0] + ex[h][0] + sx[h][1]; yc = sy[h][0] + ey[h][0] +
sy[h][1];
• (xc/3, yc/3) always remains inside the layer even though the
layer is extended.
• If (xc/3, yc/3) and the new point are in opposite sides of a
given edge of the convex layer then it is said that the new
point is OUTSIDE to that edge.
21
22. Identifying INSIDE or OUTSIDE to an Edge
• The vertices of the triangle: P1 (x1, y1), P2 (x2, y2), P3 (x3, y3).
• Let txy = x1 * (y2 – y3) + x2 * (y3 – y1) + x3 * (y1 – y2).
• txy = 0 ↔ (P1, P2, P3) are collinear.
• txy > 0 ↔ (P1, P2, P3) are in anticlockwise order.
• txy < 0 ↔ (P1, P2, P3) are in clockwise order.
22
txy > 0 txy < 0
23. Identifying INSIDE or OUTSIDE to an Edge…
• Let N be the new point and G be the centroid of the primary
hull.
• Note that N is INSIDE all the edges of the layer except edge
AB.
• txy {B, A, N} * txy {B, A, G} < 0 N is OUTSIDE AB.
• txy {B, A, N} * txy {B, A, G} ≥ 0 N is INSIDE AB.
23
24. Expansion of a Layer
• When a new point appears, the outermost convex layer to
which that point is outside should be selected first.
• If the new point is not outside any of the convex layers
available then new layer should be created inside the
innermost layer.
24
25. Expansion of a Layer…
• When a layer expands then it may leave some of its existing
points.
• These points should be transferred to the adjacent inner layer
of the current layer as new points.
• This procedure should be carried out inheriting points from
outer layers to inner layers.
25
31. How to Expand a Layer
• Suppose new point appears outside a single edge of the layer.
• The edge AB should be set into dead.
• Two alive edges AN and BN should be added to the layer.
31
32. How to Expand a Layer…
• Suppose new point appears outside two edges of the layer.
• Edges MP and MQ are added as alive edges to the layer.
• Edges MQ and MR are added as alive edges to the layer.
• Note that the edge MQ appears twice in the list of edges.
32
33. How to Expand a Layer…
• If an edge appears more than once in the list of edges then it
should be set into dead.
• Therefore, the edge MQ should be set into dead.
• The point Q should be transferred to adjacent inner layer.
33
38. Analysis of the Algorithm
• Suppose that there are n points on the plane.
• The convex layers have already been found and suppose that
there are k convex layers.
• Then each layer contains (n/k) average number of points.
• Three cases:
• Insertion of a point.
• Deletion of a point.
• Working in the dynamic context.
38
39. Insertion of a Point
• The worst case occurs when the new point appears outside all
the layers.
• Suppose a point is transferred to a layer.
• It takes O (n/k) time to search and set dead the existing edges
of a layer.
• It takes O [(n/k)2] time to detect duplicate edges in the edge
list.
• Altogether, it takes O (n/k) + O [(n/k)2] = O [(n/k)2] time to
transfer a single point to a layer.
• A layer receives O (n/k) points in the worst case.
• Therefore, it takes O [(n/k)2] * O (n/k) = O [(n/k)3] time to
transfer points between two adjacent layers.
• Since there are k layers, it takes O [(n/k)3] * O (k) = O (n3/k2)
time to insert a point in the worst case. 39
40. Deletion of a Point
• The worst case occurs when a point on the outermost layer is
deleted.
• All the points except the point to be deleted should be
transferred to inner layers.
• Thus the deletion problem becomes an insertion problem.
• Therefore, it takes O (n3/k2) time to delete a point in the worst
case.
40
41. Working in the Dynamic Context
• A single point can be inserted or deleted in O (n3/k2) time.
• Therefore, the algorithm takes n * O (n3/k2) = O (n4/k2) time
to compute the convex layers in the dynamic context.
41
42. Drawbacks of Sanjib & Niraj Algorithm
• The algorithm assumes that the set of points does not contain
any collinear points.
• The authors proposed a theoretical algorithm without
providing a corresponding implementation.
• The notion of tangent is not available in higher dimensions.
42
44. Conclusions
• The proposed algorithm takes O (n3/k2) time to perform an
insertion or a deletion of a point whereas Sanjib & Niraj
algorithm takes O (n) time.
• The proposed algorithm takes O (n4/k2) time in dynamic
context whereas Sanjib and Niraj algorithm takes O (n2) time.
• The proposed algorithm can handle set of points with
coincident points and collinear points.
• The proposed algorithm was successfully implemented using
C programming language.
• The notion used in the proposed algorithm can be extended
into higher dimensions.
44