The document describes several sorting and selection algorithms, including insertion sort, partition, quicksort, random quicksort, counting sort, radix sort, and random select. Insertion sort works by inserting each element into the sorted portion of the array, partition divides the array around a pivot element, and quicksort uses partition to recursively sort subarrays. Counting sort counts occurrences of each value instead of comparing elements, and radix sort extends counting sort to multiple digits. Random select finds the kth smallest element by randomly partitioning the array.
Slides cover understanding heap, heap properties, representation of heap, up-heap and down heap bubbling followed by Adaptable priority queues, list and heap implementation of priority queues.
Describes Map data structure, its methods and implementation using Hash tables & linked list along with their running time. Hash table components, bucket Array and hash function. Collision handing strategies: Separate chaining, Linear probing, quadratic probing, double hashing.
Ordered Maps and corresponding binary search
Slides cover understanding heap, heap properties, representation of heap, up-heap and down heap bubbling followed by Adaptable priority queues, list and heap implementation of priority queues.
Describes Map data structure, its methods and implementation using Hash tables & linked list along with their running time. Hash table components, bucket Array and hash function. Collision handing strategies: Separate chaining, Linear probing, quadratic probing, double hashing.
Ordered Maps and corresponding binary search
Discuss seven functions, Analysis of algorithms- Experimental Studies/Primitive operations/Asymptotic notation- Big Oh/Big-Omega/Big-Theta
(Download is recommended to make the animations work)
1. Introduction to MATLAB and programming
2. Workspace, variables and arrays
3. Using operators, expressions and statements
4. Repeating and decision-making
5. Different methods for input and output
6. Common functions
7. Logical vectors
8. Matrices and string arrays
9. Introduction to graphics
10. Loops
11. Custom functions and M-files
It is a presentation on some Searching and Sorting Techniques for Computer Science.
It consists of the following techniques:
Sequential Search
Binary Search
Selection Sort
Bubble Sort
Insertion Sort
Algebraic Approach to Implementing an ATL Model Checkerinfopapers
Laura Florentina Stoica, Florian Mircea Boian, Algebraic Approach to Implementing an ATL Model Checker, STUDIA Univ. Babes Bolyai, INFORMATICA, Volume LVII, Number 2, 2012, pp. 73-82
Discuss seven functions, Analysis of algorithms- Experimental Studies/Primitive operations/Asymptotic notation- Big Oh/Big-Omega/Big-Theta
(Download is recommended to make the animations work)
1. Introduction to MATLAB and programming
2. Workspace, variables and arrays
3. Using operators, expressions and statements
4. Repeating and decision-making
5. Different methods for input and output
6. Common functions
7. Logical vectors
8. Matrices and string arrays
9. Introduction to graphics
10. Loops
11. Custom functions and M-files
It is a presentation on some Searching and Sorting Techniques for Computer Science.
It consists of the following techniques:
Sequential Search
Binary Search
Selection Sort
Bubble Sort
Insertion Sort
Algebraic Approach to Implementing an ATL Model Checkerinfopapers
Laura Florentina Stoica, Florian Mircea Boian, Algebraic Approach to Implementing an ATL Model Checker, STUDIA Univ. Babes Bolyai, INFORMATICA, Volume LVII, Number 2, 2012, pp. 73-82
Using serpentine matrices and reflections on their columns of even order we present a computer program that generates a large class of semi-magic squares and magic squares.
Other than some generic containers like list, Python in its definition can also handle containers with specified data types. Array can be handled in python by module named “array“. They can be useful when we have to manipulate only a specific data type values.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
2. Algorithm 6.1.2 Insertion Sort This algorithm sorts the array a by first inserting a [2] into the sorted array a [1]; next inserting a [3] into the sorted array a [1], a [2]; and so on; and finally inserting a [ n ] into the sorted array a [1], ... , a [ n - 1]. Input Parameters: a Output Parameters: None insertion_sort ( a ) { n = a . last for i = 2 to n { val = a [ i ] // save a [ i ] so it can be inserted j = i – 1 // into the correct place // if val < a [ j ],move a [ j ] right to make room for a [ i ] while ( j ≥ 1 && val < a [ j ]) { a [ j + 1] = a [ j ] j = j - 1 } a [ j + 1] = val // insert val } }
3. Algorithm 6.2.2 Partition This algorithm partitions the array a [ i ], ... , a [ j ] by inserting val = a [ i ] at the index h where it would be if the array was sorted. When the algorithm concludes, values at indexes less than h are less than val , and values at indexes greater than h are greater than or equal to val . The algorithm returns the index h . Input Parameters: a , i , j Output Parameters: i partition ( a , i , j ) { val = a [ i ] h = i for k = i + 1 to j if ( a [ k ] < val ) { h = h + 1 swap ( a [ h ], a [ k ]) } swap ( a [ i ], a [ h ]) return h }
4. Algorithm 6.2.4 Quicksort This algorithm sorts the array a [ i ], ... , a [ j ] by using the partition algorithm (Algorithm 6.2.2). Input Parameters: a , i , j Output Parameters: i quicksort ( a , i , j ) { if ( i < j ) { p = partition ( a , i , j ) quicksort ( a , i , p - 1) quicksort ( a , p + 1, j ) } }
5. Algorithm 6.2.6 Random Partition This algorithm partitions the array a [ i ], ... , a [ j ] by inserting val = a [ i ] at the index h where it would be if the array was sorted. The index k is chosen randomly. We assume that the function rand ( i , j ) executes in constant time and returns a random integer between i and j , inclusive. After inserting val at index h , values at indexes less than h are less than val , and values at indexes greater than h are greater than or equal to val . The algorithm returns the index h . Input Parameters: a , i , j Output Parameters: i random_partition ( a , i , j ) { k = rand [ i , j ] swap ( a [ i ], a [ k ]) return partition ( i , j ) // Algorithm 6.2.2 }
6. Algorithm 6.2.7 Random Quicksort This algorithm sorts the array a [ i ], ... , a [ j ] by using the random partition algorithm (Algorithm 6.2.6). Input Parameters: a , i , j Output Parameters: i random _ quicksort ( a , i , j ) { if ( i < j ) { p = random _ partition ( a , i , j ) random _ quicksort ( a , i , p - 1) random _ quicksort ( a , p + 1, j ) } }
7. Algorithm 6.4.2 Counting Sort This algorithm sorts the array a [1], ... , a [ n ] of integers, each in the range 0 to m , inclusive.
8. Input Parameters: a , m Output Parameters: a counting_sort ( a , m ) { // set c [ k ] = the number of occurrences of value k // in the array a . // begin by initializing c to zero. for k = 0 to m c [ k ] = 0 n = a . last for i = 1 to n c [ a [ i ]] = c [ a [ i ]] + 1 // modify c so that c [ k ] = number of elements ≤ k for k = 1 to m c [ k ] = c [ k ] + c [ k - 1] // sort a with the result in b for i = n downto 1 { b [ c [ a [ i ]]] = a [ i ] c [ a [ i ]] = c [ a [ i ]] - 1 } // copy b back to a for i = 1 to n a [ i ] = b [ i ] }
9. Algorithm 6.4.4 Radix Sort This algorithm sorts the array a [1], ... , a [ n ] of integers. Each integer has at most k digits. Input Parameters: a , k Output Parameters: a radix_sort ( a , k ) { for i = 0 to k - 1 counting_sort ( a ,10) // key is digit in 10 i ’s place }
10. Algorithm 6.5.2 Random Select Let val be the value in the array a [ i ], ... , a [ j ] that would be at index k ( i ≤ k ≤ j ) if the entire array was sorted. This algorithm rearranges the array so that val is at index k , all values at indexes less than k are less than val , and all values at indexes greater than k are greater than or equal to val . The algorithm uses the random-partition algorithm (Algorithm 6.2.6). Input Parameters: a , i , j , k Output Parameter: a random_select ( a , i , j , k ) { if ( i < j ) { p = random_partition ( a , i , j ) if ( k == p ) return if ( k < p ) random_select ( a , i , p - 1, k ) else random_select ( a , p + 1, j , k ) } }