finite difference Method, For Numerical analysis. working matlab code. numeric analysis finite difference method. MATLAB provides tools to solve math. Using linear programing techniques we can easily solve system of equations. This file provides a running code of Finite difference matlab code
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finite difference Method, For Numerical analysis. working matlab code. numeric analysis finite difference method. MATLAB provides tools to solve math. Using linear programing techniques we can easily solve system of equations. This file provides a running code of Finite difference matlab code
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
“ help.mbaassignments@gmail.com ”
or
Call us at : 08263069601
JEE Mathematics/ Lakshmikanta Satapathy/ Definite integrals part 8/ JEE question on definite integral involving integration by parts solved with complete explanation
Comuter graphics bresenhams line drawing algorithmRachana Marathe
bresenhams line drawing algorithm examples, solved examples, computer graphics, pixel calculation, hearn and baker text book on computer graphics, extra solved examples on bresenhams line drawing algorithm,
JEE Mathematics/ Lakshmikanta Satapathy/ Indefinite Integration QA part 21/ Question on Indefinite integration is solved resolving the integrand into partial fractions
DDA algorithm examples, solved examples, computer graphics, pixel calculation, line drawing algorithm, line drawing solved, 2D line drawing calculation, extra examples on DDA algorithm, Hearn and Baker book on computer graphics
LADDER AND SUBDIVISION OF LADDER GRAPHS WITH PENDANT EDGES ARE ODD GRACEFULFransiskeran
The ladder graph plays an important role in many applications as Electronics, Electrical and Wireless
communication areas. The aim of this work is to present a new class of odd graceful labeling for the ladder
graph. In particular, we show that the ladder graph Ln with m-pendant Ln mk1 is odd graceful. We also
show that the subdivision of ladder graph Ln with m-pendant S(Ln) mk1 is odd graceful. Finally, we
prove that all the subdivision of triangular snakes ( k snake ) with pendant edges
1
( ) k S snake mk are odd graceful.
JEE Mathematics/ Lakshmikanta Satapathy/ Questions on Indefinite Integration part 12 taken from previous Board papers solve by the method of substitution using standard Integrals
JEE Mathematics/ Lakshmikanta Satapathy/ Definite integrals part 8/ JEE question on definite integral involving integration by parts solved with complete explanation
Comuter graphics bresenhams line drawing algorithmRachana Marathe
bresenhams line drawing algorithm examples, solved examples, computer graphics, pixel calculation, hearn and baker text book on computer graphics, extra solved examples on bresenhams line drawing algorithm,
JEE Mathematics/ Lakshmikanta Satapathy/ Indefinite Integration QA part 21/ Question on Indefinite integration is solved resolving the integrand into partial fractions
DDA algorithm examples, solved examples, computer graphics, pixel calculation, line drawing algorithm, line drawing solved, 2D line drawing calculation, extra examples on DDA algorithm, Hearn and Baker book on computer graphics
LADDER AND SUBDIVISION OF LADDER GRAPHS WITH PENDANT EDGES ARE ODD GRACEFULFransiskeran
The ladder graph plays an important role in many applications as Electronics, Electrical and Wireless
communication areas. The aim of this work is to present a new class of odd graceful labeling for the ladder
graph. In particular, we show that the ladder graph Ln with m-pendant Ln mk1 is odd graceful. We also
show that the subdivision of ladder graph Ln with m-pendant S(Ln) mk1 is odd graceful. Finally, we
prove that all the subdivision of triangular snakes ( k snake ) with pendant edges
1
( ) k S snake mk are odd graceful.
JEE Mathematics/ Lakshmikanta Satapathy/ Questions on Indefinite Integration part 12 taken from previous Board papers solve by the method of substitution using standard Integrals
Merge sort: illustrated step-by-step walk throughYoshi Watanabe
A step-by-step illustration of Merge sort to help you walk through a series of operations. Illustration is accompanied by actual code with bold line indicating the current operation.
This file contains the contents about dynamic programming, greedy approach, graph algorithm, spanning tree concepts, backtracking and branch and bound approach.
Practical and Worst-Case Efficient ApportionmentRaphael Reitzig
Proportional apportionment is the problem of assigning seats to parties according to their relative share of votes. Divisor methods are the de-facto standard solution, used in many countries.
In recent literature, there are two algorithms that implement divisor methods: one by Cheng and Eppstein (ISAAC, 2014) has worst-case optimal running time but is complex, while the other (Pukelsheim, 2014) is relatively simple and fast in practice but does not offer worst-case guarantees.
This talk presents the ideas behind a novel algorithm that avoids the shortcomings of both. We investigate the three contenders in order to determine which is most useful in practice.
Read more over here: http://reitzig.github.io/publications/RW2015b
I am Jayson L. I am a Signals and Systems Homework Expert at matlabassignmentexperts.com. I hold a Master's in Matlab, from the University of Sheffield. I have been helping students with their homework for the past 7 years. I solve homework related to Signals and Systems.
Visit matlabassignmentexperts.com or email info@matlabassignmentexperts.com.
You can also call on +1 678 648 4277 for any assistance with Signals and Systems homework.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
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
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
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:
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
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.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
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.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
2. Divide the problems into a number of sub
problems.
Conquer the sub problems by solving
them recursively. If the sub-problem
sizes are small enough, just solve the
problems in a straight forward manner.
Combine the solutions to the sub
problems into the solution for the original
problem.
Divide and Conquer ApproachDivide and Conquer Approach
2Instructor: Sadia Arshid, DCS &SE
3. Divide-and-ConquerDivide-and-Conquer
AlgorithmsAlgorithms
An algorithm design
– merge sort
– maxmin
– quick sort
– Matrix multiplication
A larger problem is broken up into smaller
problems, the smaller problems are recursively,
and the results are merged together again
3Instructor: Sadia Arshid, DCS &SE
4. Divide-and-ConquerDivide-and-Conquer
AlgorithmsAlgorithms
More formally, we will consider only those
algorithms which:
– divide a problem into sub-problems, each
approximately of size n/b
– in all cases we have seen, the whole was
divided into b equal sub-problems
– solve those sub-problems recursively
– combine the solutions to the sub-problems to
get a solution to the overall problem
4Instructor: Sadia Arshid, DCS &SE
5. MERGE SORTMERGE SORT
Graphically, merge sort is represented as
follows:
Once we have sorted the shortest lists, then
we merge then back together again into a
sorted list
5Instructor: Sadia Arshid, DCS &SE
6. Divide the n element sequence to be
sorted into two subsequences of n/2
elements each.
Conquer: Sort the two subsequences to
produce the sorted answer.
Combine: Merge the two sorted sub
sequences to produce the sorted answer.
Merge SortMerge Sort
6Instructor: Sadia Arshid, DCS &SE
7. Merge Sort AlgorithmMerge Sort Algorithm
procedure MergeSort(n,s)
h=n/2, m=n-h
u=array[1..h], v=array[m..n]
if n>1
copy s[1] through s[h] to u
copy s[h+1] through s[n] to v
mergesort(h,u)
mergesort(m,v)
merge(h,m,u,v,s] 7Instructor: Sadia Arshid, DCS &SE
8. procedure merge(h,m,u,v,s)
i=1,j=1,k=1
while i<=h and j<=m
if u[i]<v[j]
s[k]=u[i], i=i+1
else s[k]=v[j],j=j+1
k=k+1
if i>h
copy v[j] through v[m] to s[k] through s[h+m]
else
copy u[i] through u[h] to s[k] through s[h+m]
8Instructor: Sadia Arshid, DCS &SE
10. Merge Sort AnalysisMerge Sort Analysis
T(n)=T[h]+T[m]+complexity of merge
Complexity of merge: worst case, h+m-1
Suppose n is a power of two, so that we always split
into even halves.
– h=n/2, m=n-n/2=n/2
– w(n)=w[n/2]+w[n/2]+n-1
For n = 1 the time to merge sort is1 otherwise
The time to merge sort n numbers is equal to the
time to do two recursive merge sorts of size n/2, plus
the time to merge, which is linear.
Solve this recurrence to find out running time. 10Instructor: Sadia Arshid, DCS &SE
15. at each level total number of items are n
and total recursive calls are lg n(depth of
tree)
so total space complexity is nlgn
15Instructor: Sadia Arshid, DCS &SE
16. Other version of MERGEOther version of MERGE
SORTSORT
procedure MergeSort2(low,high,n,s)
if low<high
mid=(low+high)/2
mergesort2(low,mid)
mergesort2(mid+1,high)
merge2(low,mid,high]
16Instructor: Sadia Arshid, DCS &SE
17. procedure merge2(low,mid,high)
i=low,j=mid,h=low
while h<=mid and j<=high
if s[h]<s[j]
u[i]=s[h], h=h+1
else u[i]=s[j], j=j+1
i=i+1
if i>h
copy s[h] through s[mid] to u[i] to u[high]
else
copy s[j] through s[high] to u[i] to u[high]
17Instructor: Sadia Arshid, DCS &SE