Stack
operations performed on stack
stack applications
Infix to postfix conversion
Infix to prefix conversion
Postfix to infix conversion
Prefix to infix conversion
algorithm to push an element in a stack
algorithm to pop an element from a stack
We had studied about the computation of derivatives that is, how to find the derivatives of different function like composite functions, implicit functions, trigonometric functions and logarithm functions etc. Copy the link given below and paste it in new browser window to get more information on Introduction of Application of Derivatives www.askiitians.com/iit-study-material/iit-jee-mathematics/differential-calculus/introduction-of-application-of-derivatives/
1. It is unsafe for a transaction to release an intention-write lock on a file before committing, as it could allow another transaction to modify the file's records in a way that violates the first transaction's intentions.
2. The multi-granularity locking protocol requires transactions to hold intention-write locks on a data item's parents if they hold write or intention-write locks on the data item.
3. The document provides examples of transactions accessing a database table with multiversion concurrency control and discusses the state of the table and which row versions transactions would read under different scenarios.
The document discusses different notations for writing mathematical expressions: infix, prefix, and postfix. Infix notation, where the operator is between operands (a + b), is commonly used but requires parentheses. Prefix and postfix notations avoid this by placing the operator before (prefix: + a b) or after (postfix: a b +) the operands. Converting between these notations allows expressions to be evaluated without parentheses by using a stack-based algorithm.
FIWARE Wednesday Webinars - Interface With Machines and Robots: Building Inte...FIWARE
Interface With Machines and Robots: Building Interfaces to ROS Systems - 22 July 2020
Corresponding webinar recording: https://youtu.be/a0NxSS96YzY
This webinar will present how to develop FIWARE NGSI Interfaces for ROS-based robots.
Chapter: Robotics
Difficulty: 3
Audience: Technical Domain Specific
Speaker: Francisco Meléndez (Technical Expert and Evangelist, FIWARE Foundation)
This short document suggests that children often resemble their parents in character or appearance. It conveys the idea that the qualities or traits of parents are passed down to their children through the idioms "Like father, like son" and "De tal palo, tal astilla" which mean that children tend to have similar personalities or traits as their parents.
This document outlines requirements for a calculator that performs basic arithmetic operations (+, -, *, /, %) on integers using Reverse Polish Notation. The calculator will use a stack to hold operands and will have x, y, z, w stack positions. It will support 32-bit operands and hexadecimal input/output.
This document discusses stacks, including their history, definition, operations of push and pop, and applications. Stacks are linear data structures where insertion and deletion occur at the same end, known as the top. Elements can only be removed in reverse order of insertion. Common applications include reversing lists, converting infix to postfix notation, evaluating postfix expressions, and recursion.
We had studied about the computation of derivatives that is, how to find the derivatives of different function like composite functions, implicit functions, trigonometric functions and logarithm functions etc. Copy the link given below and paste it in new browser window to get more information on Introduction of Application of Derivatives www.askiitians.com/iit-study-material/iit-jee-mathematics/differential-calculus/introduction-of-application-of-derivatives/
1. It is unsafe for a transaction to release an intention-write lock on a file before committing, as it could allow another transaction to modify the file's records in a way that violates the first transaction's intentions.
2. The multi-granularity locking protocol requires transactions to hold intention-write locks on a data item's parents if they hold write or intention-write locks on the data item.
3. The document provides examples of transactions accessing a database table with multiversion concurrency control and discusses the state of the table and which row versions transactions would read under different scenarios.
The document discusses different notations for writing mathematical expressions: infix, prefix, and postfix. Infix notation, where the operator is between operands (a + b), is commonly used but requires parentheses. Prefix and postfix notations avoid this by placing the operator before (prefix: + a b) or after (postfix: a b +) the operands. Converting between these notations allows expressions to be evaluated without parentheses by using a stack-based algorithm.
FIWARE Wednesday Webinars - Interface With Machines and Robots: Building Inte...FIWARE
Interface With Machines and Robots: Building Interfaces to ROS Systems - 22 July 2020
Corresponding webinar recording: https://youtu.be/a0NxSS96YzY
This webinar will present how to develop FIWARE NGSI Interfaces for ROS-based robots.
Chapter: Robotics
Difficulty: 3
Audience: Technical Domain Specific
Speaker: Francisco Meléndez (Technical Expert and Evangelist, FIWARE Foundation)
This short document suggests that children often resemble their parents in character or appearance. It conveys the idea that the qualities or traits of parents are passed down to their children through the idioms "Like father, like son" and "De tal palo, tal astilla" which mean that children tend to have similar personalities or traits as their parents.
This document outlines requirements for a calculator that performs basic arithmetic operations (+, -, *, /, %) on integers using Reverse Polish Notation. The calculator will use a stack to hold operands and will have x, y, z, w stack positions. It will support 32-bit operands and hexadecimal input/output.
This document discusses stacks, including their history, definition, operations of push and pop, and applications. Stacks are linear data structures where insertion and deletion occur at the same end, known as the top. Elements can only be removed in reverse order of insertion. Common applications include reversing lists, converting infix to postfix notation, evaluating postfix expressions, and recursion.
The document discusses implementing a stack using a linked list as an alternative to an array. It explains that a linked list avoids size limitations of an array implementation. Elements can be inserted and removed from the start of the list in constant time, making it suitable for a stack. The four basic stack operations - push, pop, top, and isEmpty - can all be performed in constant time on this linked list implementation.
This document discusses stacks and their applications. It defines a stack as a linear list where additions and deletions are restricted to one end, called the top, resulting in Last-In First-Out (LIFO) behavior. The key applications of stacks discussed are: reversing data order, parsing data, postponing operations, and backtracking. Specific examples covered include infix to postfix notation conversion, expression evaluation, parentheses matching, goal seeking problems, and the eight queens problem.
The document discusses various applications of stacks including reversing data, parsing, postponing operations, and backtracking. It provides examples of converting infix expressions to postfix notation using a stack and evaluating postfix expressions. The key stack operations of push, pop, and accessing the stack top are defined. Implementation of a stack using an array is also mentioned.
This document discusses stack control and stack-based architectures. It describes how a stack works using push and pop operations controlled by a stack pointer. It provides examples of implementing a stack in Motorola 680X0 using a designated address register and single instructions to push and pop. Stack architectures have low hardware requirements but the stack can become a bottleneck and have little ability for parallelism. Accumulator architectures also have low requirements but the accumulator is a bottleneck and have high memory traffic.
In computer science, a stack is an abstract data type that serves as a collection of elements, with two main principal operations: push, which adds an element to the collection, and pop, which removes the most recently added element that was not yet removed.
Best Practices for Migrating Legacy Data Warehouses into Amazon RedshiftAmazon Web Services
The document summarizes best practices for migrating legacy data warehouses to Amazon Redshift. It covers architectural concepts like columnar storage and compression, data distribution styles, sort keys to optimize query performance, and materializing dimension columns in fact tables. The presentation provides an overview of these topics and their impact on storage, I/O and querying. Real-world examples are also given to illustrate key points.
The document outlines a presentation on mobile game programming and stacks. It discusses abstract data types (ADTs), data structures, and specifically focuses on stacks. It provides examples of stack implementations in C++ using classes and templates. Finally, it discusses algorithms that use stacks, including converting number systems, evaluating postfix notation, and converting infix to postfix notation.
Недавно работы комитета по стандартизации WG21 были завершены, и документ-черновик C++17 был отправлен на рассмотрение в Международную организацию по стандартизации (ISO). С этого момента технически можно считать, что стандарт C++17 у нас есть. Если вы ещё ознакомились с принятыми изменениями, то сейчас для этого самое время. В докладе будет сделан обзор нововведений. Рассмотрено текущее состояние дел у популярных компиляторов с поддержкой С++17
The document discusses Java programming and transactions. It describes reading transaction data from a CSV file, parsing the data into Transaction objects, and summarizing the transaction amounts. It covers improvements such as using generics, try-with-resources for file handling, LocalDate instead of Date, and various Java features between versions.
The document discusses stacks and their implementation using either arrays or linked lists, noting the tradeoffs of each approach. It then covers using stacks to evaluate expressions in postfix notation by pushing operands onto the stack and applying operators to the top two elements before pushing the result back on. Finally, an example is given of evaluating the postfix expression 6 2 3 + - 3 8 2 / + * to demonstrate this process.
This document discusses stacks and queues as data structures. It begins by explaining what a stack is, noting that a stack follows last-in, first-out ordering. It then provides an analogy using mail delivery to explain the stack concept. The document goes on to provide Java code examples for implementing a stack. It also gives examples of using a stack to reverse a word and check balanced parentheses. Next, the document defines queues as first-in, first-out data structures and provides Java code for implementing a queue. It concludes by explaining how stacks can be used to parse arithmetic expressions by first converting them to postfix notation.
HTAP By Accident: Getting More From PostgreSQL Using Hardware AccelerationEDB
Big Data. Data Science. AI. It's all big business.
Once upon a time we succeeded in these fields by selectively storing, processing and learning from just the right data. This, of course, requires you to know what "the right data" is. We know there are valuable insights in data, so why not store the lot? It's the 21st century equivalent of "there's gold in them thar hills!"
So having spent years stashing away terabytes of your data in PostgreSQL, you want to start learning from that data. Queries. More queries. More complex queries. Lots of real-time queries. Lots of concurrent users. It might be tempting at this point to give up on PostgreSQL and stash your data into a different solution, more suited to purpose. Don't. PostgreSQL can perform very well in HTAP environments and performs even better with a little help.
In this presentation we dive into the current state of the art with regards to PostgreSQL in HTAP environments and expose how hardware acceleration can help squeeze as much knowledge as possible out of your data.
This slides describes the basic concepts of industrial-strength compiler design. This includes basic concept of static single-assignment form (SSA) and various optimizations such as dead code elimination, global value numbering, constant propagation, etc. This is intend for a 150 minutes undergraduate compiler class.
Checking Wine with PVS-Studio and Clang Static AnalyzerAndrey Karpov
In this article, I'm going to tell you about the check of the Wine project done by the static analyzers for C/C++ code PVS-Studio and Clang Static Analyzer.
Impact Analysis FRAN PCT DATA DEFINITION CHANGEJon Fortman
This document provides an impact analysis of changing the data definition of the franchise percentage field in various records and code modules. It identifies specific code that can be updated to reference the franchise percentage at the ticket line level instead of the record level. It also notes inserting the franchise percentage field into a payment transfer table and scanning a database field for that value to produce geographic franchise reports.
The document discusses stacks, which are linear data structures that follow the LIFO (last in, first out) principle. Stacks can be implemented using arrays or linked lists. Elements are inserted and removed only from one end, called the top of the stack. Insertion is called pushing and removal is called popping. Stacks are used extensively in computer systems, for example in operating system function calls and interrupt handling. The Java programming language contains a Stack class that can be used by programmers.
The document discusses a generic programming toolkit called PADS/ML that can be used to parse, analyze, and transform semi-structured or "ad hoc" data from various domains. It describes how PADS/ML uses generated type representations and typecase analysis to write functions that can operate on any data format described by a PADS/ML type. Case studies of PADX and Harmony are presented, which use PADS/ML to build tools for querying and synchronizing different data formats.
This document discusses data structures and discrete mathematics. It provides an overview of linked lists, stacks, and queues. Key points include:
- Linked lists, stacks, and queues are common data structures that can be implemented using arrays or linked nodes.
- Common operations on data structures include adding, removing, and searching for data.
- Abstract data types (ADTs) specify functionality without defining the implementation. This allows data structures to be reused.
- Stacks follow last-in, first-out behavior using push and pop operations. Queues follow first-in, first-out behavior using enqueue and dequeue operations.
- Both stacks and queues have many applications areas like expression evaluation,
The document describes the instruction set of the 8085 microprocessor. It has 246 instructions that are 8-bit binary patterns to perform specific functions. The instructions are classified into different types like data transfer, arithmetic, logical, branching, and control instructions. Data transfer instructions move data between registers and memory. Arithmetic instructions perform operations like addition, subtraction, incrementing and decrementing registers and memory locations.
The document discusses the types of instructions in the 8085 microprocessor instruction set. It describes that the 8085 has 246 instructions that are classified into different types including data transfer instructions, arithmetic instructions, logical instructions, branching instructions, and control instructions. It provides details about common data transfer instructions like MOV, MVI, LXI, LDA, etc. and explains arithmetic instructions for addition, subtraction, increment, decrement. Logical instructions for AND, OR, XOR, rotate and compare are also covered.
The document provides an overview of different data structures and their types. It discusses linear data structures like arrays, linked lists, stacks and queues as well as non-linear structures like trees and graphs. Common operations on different data structures are also mentioned. The document further describes abstract data types and how they define the operations that can be performed on data without specifying implementation details.
Sorting
NEED FOR SORTING
Insertion Sort
Illustration of Insertion Sort
Insertion Sort algorithm
code for Insertion Sort
advantages & disadvantages of Insertion Sort
best case and worst case of Insertion Sort
Selection sort
Illustration of Selection sort
Selection sort algorithm
code for Selection sort
worst case for selection Sort
The document discusses implementing a stack using a linked list as an alternative to an array. It explains that a linked list avoids size limitations of an array implementation. Elements can be inserted and removed from the start of the list in constant time, making it suitable for a stack. The four basic stack operations - push, pop, top, and isEmpty - can all be performed in constant time on this linked list implementation.
This document discusses stacks and their applications. It defines a stack as a linear list where additions and deletions are restricted to one end, called the top, resulting in Last-In First-Out (LIFO) behavior. The key applications of stacks discussed are: reversing data order, parsing data, postponing operations, and backtracking. Specific examples covered include infix to postfix notation conversion, expression evaluation, parentheses matching, goal seeking problems, and the eight queens problem.
The document discusses various applications of stacks including reversing data, parsing, postponing operations, and backtracking. It provides examples of converting infix expressions to postfix notation using a stack and evaluating postfix expressions. The key stack operations of push, pop, and accessing the stack top are defined. Implementation of a stack using an array is also mentioned.
This document discusses stack control and stack-based architectures. It describes how a stack works using push and pop operations controlled by a stack pointer. It provides examples of implementing a stack in Motorola 680X0 using a designated address register and single instructions to push and pop. Stack architectures have low hardware requirements but the stack can become a bottleneck and have little ability for parallelism. Accumulator architectures also have low requirements but the accumulator is a bottleneck and have high memory traffic.
In computer science, a stack is an abstract data type that serves as a collection of elements, with two main principal operations: push, which adds an element to the collection, and pop, which removes the most recently added element that was not yet removed.
Best Practices for Migrating Legacy Data Warehouses into Amazon RedshiftAmazon Web Services
The document summarizes best practices for migrating legacy data warehouses to Amazon Redshift. It covers architectural concepts like columnar storage and compression, data distribution styles, sort keys to optimize query performance, and materializing dimension columns in fact tables. The presentation provides an overview of these topics and their impact on storage, I/O and querying. Real-world examples are also given to illustrate key points.
The document outlines a presentation on mobile game programming and stacks. It discusses abstract data types (ADTs), data structures, and specifically focuses on stacks. It provides examples of stack implementations in C++ using classes and templates. Finally, it discusses algorithms that use stacks, including converting number systems, evaluating postfix notation, and converting infix to postfix notation.
Недавно работы комитета по стандартизации WG21 были завершены, и документ-черновик C++17 был отправлен на рассмотрение в Международную организацию по стандартизации (ISO). С этого момента технически можно считать, что стандарт C++17 у нас есть. Если вы ещё ознакомились с принятыми изменениями, то сейчас для этого самое время. В докладе будет сделан обзор нововведений. Рассмотрено текущее состояние дел у популярных компиляторов с поддержкой С++17
The document discusses Java programming and transactions. It describes reading transaction data from a CSV file, parsing the data into Transaction objects, and summarizing the transaction amounts. It covers improvements such as using generics, try-with-resources for file handling, LocalDate instead of Date, and various Java features between versions.
The document discusses stacks and their implementation using either arrays or linked lists, noting the tradeoffs of each approach. It then covers using stacks to evaluate expressions in postfix notation by pushing operands onto the stack and applying operators to the top two elements before pushing the result back on. Finally, an example is given of evaluating the postfix expression 6 2 3 + - 3 8 2 / + * to demonstrate this process.
This document discusses stacks and queues as data structures. It begins by explaining what a stack is, noting that a stack follows last-in, first-out ordering. It then provides an analogy using mail delivery to explain the stack concept. The document goes on to provide Java code examples for implementing a stack. It also gives examples of using a stack to reverse a word and check balanced parentheses. Next, the document defines queues as first-in, first-out data structures and provides Java code for implementing a queue. It concludes by explaining how stacks can be used to parse arithmetic expressions by first converting them to postfix notation.
HTAP By Accident: Getting More From PostgreSQL Using Hardware AccelerationEDB
Big Data. Data Science. AI. It's all big business.
Once upon a time we succeeded in these fields by selectively storing, processing and learning from just the right data. This, of course, requires you to know what "the right data" is. We know there are valuable insights in data, so why not store the lot? It's the 21st century equivalent of "there's gold in them thar hills!"
So having spent years stashing away terabytes of your data in PostgreSQL, you want to start learning from that data. Queries. More queries. More complex queries. Lots of real-time queries. Lots of concurrent users. It might be tempting at this point to give up on PostgreSQL and stash your data into a different solution, more suited to purpose. Don't. PostgreSQL can perform very well in HTAP environments and performs even better with a little help.
In this presentation we dive into the current state of the art with regards to PostgreSQL in HTAP environments and expose how hardware acceleration can help squeeze as much knowledge as possible out of your data.
This slides describes the basic concepts of industrial-strength compiler design. This includes basic concept of static single-assignment form (SSA) and various optimizations such as dead code elimination, global value numbering, constant propagation, etc. This is intend for a 150 minutes undergraduate compiler class.
Checking Wine with PVS-Studio and Clang Static AnalyzerAndrey Karpov
In this article, I'm going to tell you about the check of the Wine project done by the static analyzers for C/C++ code PVS-Studio and Clang Static Analyzer.
Impact Analysis FRAN PCT DATA DEFINITION CHANGEJon Fortman
This document provides an impact analysis of changing the data definition of the franchise percentage field in various records and code modules. It identifies specific code that can be updated to reference the franchise percentage at the ticket line level instead of the record level. It also notes inserting the franchise percentage field into a payment transfer table and scanning a database field for that value to produce geographic franchise reports.
The document discusses stacks, which are linear data structures that follow the LIFO (last in, first out) principle. Stacks can be implemented using arrays or linked lists. Elements are inserted and removed only from one end, called the top of the stack. Insertion is called pushing and removal is called popping. Stacks are used extensively in computer systems, for example in operating system function calls and interrupt handling. The Java programming language contains a Stack class that can be used by programmers.
The document discusses a generic programming toolkit called PADS/ML that can be used to parse, analyze, and transform semi-structured or "ad hoc" data from various domains. It describes how PADS/ML uses generated type representations and typecase analysis to write functions that can operate on any data format described by a PADS/ML type. Case studies of PADX and Harmony are presented, which use PADS/ML to build tools for querying and synchronizing different data formats.
This document discusses data structures and discrete mathematics. It provides an overview of linked lists, stacks, and queues. Key points include:
- Linked lists, stacks, and queues are common data structures that can be implemented using arrays or linked nodes.
- Common operations on data structures include adding, removing, and searching for data.
- Abstract data types (ADTs) specify functionality without defining the implementation. This allows data structures to be reused.
- Stacks follow last-in, first-out behavior using push and pop operations. Queues follow first-in, first-out behavior using enqueue and dequeue operations.
- Both stacks and queues have many applications areas like expression evaluation,
The document describes the instruction set of the 8085 microprocessor. It has 246 instructions that are 8-bit binary patterns to perform specific functions. The instructions are classified into different types like data transfer, arithmetic, logical, branching, and control instructions. Data transfer instructions move data between registers and memory. Arithmetic instructions perform operations like addition, subtraction, incrementing and decrementing registers and memory locations.
The document discusses the types of instructions in the 8085 microprocessor instruction set. It describes that the 8085 has 246 instructions that are classified into different types including data transfer instructions, arithmetic instructions, logical instructions, branching instructions, and control instructions. It provides details about common data transfer instructions like MOV, MVI, LXI, LDA, etc. and explains arithmetic instructions for addition, subtraction, increment, decrement. Logical instructions for AND, OR, XOR, rotate and compare are also covered.
The document provides an overview of different data structures and their types. It discusses linear data structures like arrays, linked lists, stacks and queues as well as non-linear structures like trees and graphs. Common operations on different data structures are also mentioned. The document further describes abstract data types and how they define the operations that can be performed on data without specifying implementation details.
Sorting
NEED FOR SORTING
Insertion Sort
Illustration of Insertion Sort
Insertion Sort algorithm
code for Insertion Sort
advantages & disadvantages of Insertion Sort
best case and worst case of Insertion Sort
Selection sort
Illustration of Selection sort
Selection sort algorithm
code for Selection sort
worst case for selection Sort
queue
operations performed on queue
queue applications
Example to enqueue
Algorithm To enqueue() / add () An Element (ITEM )In The Queue
Example to dequeue
Algorithm To dequeue() / remove() An Element (ITEM )In The Queue
PRIORITY Queue
PRIORITY Queue Representation
linked list
singly linked list
insertion in singly linked list
DELETION IN SINGLY LINKED LIST
Searching a singly linked list
Doubly Linked List
insertion from Doubly linked list
DELETION from Doubly LINKED LIST
Searching a doubly linked list
Circular linked list
Algorithm and its Properties
Computational Complexity
TIME COMPLEXITY
SPACE COMPLEXITY
Complexity Analysis and Asymptotic notations.
Big-oh-notation (O)
Omega-notation (Ω)
Theta-notation (Θ)
The Best, Average, and Worst Case Analyses.
COMPLEXITY Analyses EXAMPLES.
Comparing GROWTH RATES
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
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
OpenID AuthZEN Interop Read Out - AuthorizationDavid Brossard
During Identiverse 2024 and EIC 2024, members of the OpenID AuthZEN WG got together and demoed their authorization endpoints conforming to the AuthZEN API
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.
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
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.
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.
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
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceIndexBug
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
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OperatiONs perfOrmed ON staCk
staCk appliCatiONs
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prefix tO iNfix CONversiON
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algOrithm tO pOp aN elemeNt frOm a
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A stack is a linear data structure that can be accessed only
at one of its ends for storing and retrieving data.
Such a stack resembles a stack of trays in a cafeteria: New
trays are put on the top of the stack and taken off the top.
The last tray put on the stack is the first tray removed from
the stack.
For this reason, a stack is called an LIFO structure last
in/first out.
4. OperatiONs perfOrmed ONOperatiONs perfOrmed ON
staCkstaCk
03/17/18 BY MS. SHAISTA QADIR 4
The operations are as follows:
◦ clear() : Clear the stack.
◦ isEmpty() : Check to see if the stack is empty.
◦ push(el) : Put the element el on the top of the
stack.
◦ pop() : Take the topmost element from the
stack.
◦ topEl() : Return the topmost element in the
stack without removing it.
5. 03/17/18 BY MS. SHAISTA QADIR 5
Stack Overflow:
If adding an element onto the top of the stack and if that
stack is full this situation is called stack overflow.
Stack Underflow:
Removing an element from the stack and if that stack is
empty this situation is called stack underflow
OperatiONs perfOrmed ON
staCk
6. staCk appliCatiONsstaCk appliCatiONs
03/17/18 BY MS. SHAISTA QADIR 6
APPLICATIONS OF STACK:
◦ Reversing Data: We can use stacks to reverse data.
(example: files, strings) Very useful for finding
palindromes.
◦ To evaluate Arithmetic expressions: (Prefix, Infix, Postfix
Notations)
◦ Arithmetic expressions have
Operands (variables or numeric constants).
Operators
i. Binary : +, -, *, / ,%
ii. Unary: - (sign for negative numbers)
7. 03/17/18 BY MS. SHAISTA QADIR 7
Example:
Prefix Notation Infix Notation Postfix Notation
+A * B C A + B * C A B C * +
* + A B C (A+B) * C A B + C *
+ – A B C A – B + C A B – C +
– A + B C A – (B+C) A B C + –
*+AB-CD (A+B)*(C-D) AB+CD-*
Priority convention(Rules):
◦ Unary minus has Highest priority
◦ *, /, % have Medium priority
◦ +, - have Lowest priority
stack applicationsstack applications
8. 03/17/18 BY MS. SHAISTA QADIR 8
stack applicationsstack applications
Infix Expression Prefix Expression Postfix Expression
A + B * C + D + + A * B C D A B C * + D +
(A + B) * (C + D) * + A B + C D A B + C D + *
A * B + C * D + * A B * C D A B * C D * +
A + B + C + D + + + A B C D A B + C + D +
9. 03/17/18 BY MS. SHAISTA QADIR 9
stack applicationsstack applications
Example:
To evaluate the expression A+B*C using Postfix notation in
a
Stack
Postfix notation for A+B*C is ABC*+
PUSH A
PUSH B
PUSH C
MULTIPLY
ADD
POP
PUSH A PUSH B PUSH C MULTIPLY ADD POP
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Postfix to Infix conversionPostfix to Infix conversion
Example: abc-+de-fg-h+/* to infix
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Postfix to Infix conversionPostfix to Infix conversion
Example: abc-+de-fg-h+/* to infix (contd)
15. 03/17/18 BY MS. SHAISTA QADIR 15
Postfix to Infix conversionPostfix to Infix conversion
Example: abc-+de-fg-h+/* to infix (contd)
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Prefix to Infix conversionPrefix to Infix conversion
Example: *+a-bc/-de+-fgh to infix
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Prefix to Infix conversionPrefix to Infix conversion
Example: *+a-bc/-de+-fgh to infix (contd)
18. algorithm to push analgorithm to push an
element in a stackelement in a stack
03/17/18 BY MS. SHAISTA QADIR 18
ALGORITHM:
1. If (TOP == MAX-1) Then
2. Print: Overflow
3. Else
4. Set TOP = TOP + 1
5. Set STACK[TOP] = ITEM
6. Print: ITEM inserted EndIf
7. Exit.
19. algorithm to push analgorithm to push an
elementelement
03/17/18 BY MS. SHAISTA QADIR 19
PROGRAM LOGIC:
public boolean isFull()
{
if(top == maxsize-1)
return true;
else
return false;
}
public void push(int a)
{
++top;
arr[top] = a;
}
20. algorithm to pop analgorithm to pop an
element From staCKelement From staCK
03/17/18 BY MS. SHAISTA QADIR 20
ALGORITHM:
1. If (TOP == -1) Then
2. Print: Underflow
3. Else
4. Set ITEM = STACK[TOP]
5. Set TOP = TOP - 1
6. Print: ITEM deleted EndIf
7. Exit
21. algorithm to pop analgorithm to pop an
element From staCKelement From staCK
03/17/18 BY MS. SHAISTA QADIR 21
PROGRAM LOGIC:
public boolean isEmpty()
{
if(top == -1)
return true;
else
return false;
}
public int pop ()
{
int e = arr[top];
top--;
return e;
}