The document discusses the ABA problem that can occur in non-blocking concurrent queue algorithms. It shows an example of how the ABA problem can allow a thread to incorrectly retrieve another thread's data from the queue. It then describes two common solutions to the ABA problem - adding version numbers to data structures or using load-linked/store-conditional instructions. Finally, it shows pseudocode for an enqueue operation of a non-blocking concurrent queue that avoids the ABA problem by using a double-compare-and-swap with version numbers.
This document summarizes a client-server chat application. It discusses networking basics like TCP, ports, and sockets. TCP ensures data is received in the same order sent using acknowledgements. Ports identify services/processes, and sockets connect two programs. The server runs each client on a separate thread. The client requests a connection to the server at a given port/IP. Classes like Swing, IO, and Net are used. Potential uses include private LAN chat, file transfer, broadcasting notices, and serving as a backup connection.
This document is a project report submitted by four students for their Bachelor of Engineering degree in Computer Engineering. It outlines their development of an Android application called "Spread the Smile - An Food Donating App" which aims to connect donors, NGOs, and those in need by facilitating food donations. The report includes sections on introduction and problem definition, requirements analysis, system design, and conclusions. Diagrams are provided to illustrate the system architecture, classes, use cases, activities, sequences, and database design.
This document outlines the requirements and design specifications for a chat application. It aims to develop an easy-to-use instant messaging solution that allows users to communicate seamlessly. The specification covers functional and non-functional requirements, use case diagrams for authentication, chat, contacts, monitoring and maintenance functions, and sequence diagrams depicting key processes like registration, login, messaging and friend management. Data flow diagrams and class diagrams are also included.
Scheduling Definition, objectives and types Maitree Patel
Scheduling is the process of determining which process will use the CPU when multiple processes are ready to execute. The objectives of scheduling are to maximize CPU utilization, throughput, and fairness while minimizing response time, turnaround time, and waiting time. There are three main types of schedulers: long-term schedulers manage process admission to the system; short-term or CPU schedulers select the next process to run on the CPU; and medium-term schedulers handle process suspension during I/O waits.
1) A semaphore consists of a counter, a waiting list, and wait() and signal() methods. Wait() decrements the counter and blocks if it becomes negative, while signal() increments the counter and resumes a blocked process if the counter becomes positive.
2) The dining philosophers problem is solved using semaphores to lock access to shared chopsticks, with one philosopher designated as a "weirdo" to avoid deadlock by acquiring locks in a different order.
3) The producer-consumer problem uses three semaphores - one to limit buffer size, one for empty slots, and one for locks - to coordinate producers adding to a bounded buffer
This document discusses software bugs including their history, causes, impact, and classification. It begins with definitions of common terms used to describe bugs and errors. Key events that resulted from software bugs like the Mariner 1 space probe failure and radiation therapy machine bugs that killed patients are summarized. The document also outlines common reasons why bugs are introduced during development including lack of testing and unrealistic timelines. It concludes with classifications of bugs and contact information for the author.
An insight into what role news agencies and various media houses play in India as a part of democracy in country. Its impact as a medium of communication in various situations - both good and bad. Also, the history of Indian media and its role in Indian electoral system.
Our application aims to bring about transparency, clarity and swiftness in the process of donation thus aiming to mitigate prevailing issues in whatever zone it is possible for us to do so. This is a project report for the same.
This document summarizes a client-server chat application. It discusses networking basics like TCP, ports, and sockets. TCP ensures data is received in the same order sent using acknowledgements. Ports identify services/processes, and sockets connect two programs. The server runs each client on a separate thread. The client requests a connection to the server at a given port/IP. Classes like Swing, IO, and Net are used. Potential uses include private LAN chat, file transfer, broadcasting notices, and serving as a backup connection.
This document is a project report submitted by four students for their Bachelor of Engineering degree in Computer Engineering. It outlines their development of an Android application called "Spread the Smile - An Food Donating App" which aims to connect donors, NGOs, and those in need by facilitating food donations. The report includes sections on introduction and problem definition, requirements analysis, system design, and conclusions. Diagrams are provided to illustrate the system architecture, classes, use cases, activities, sequences, and database design.
This document outlines the requirements and design specifications for a chat application. It aims to develop an easy-to-use instant messaging solution that allows users to communicate seamlessly. The specification covers functional and non-functional requirements, use case diagrams for authentication, chat, contacts, monitoring and maintenance functions, and sequence diagrams depicting key processes like registration, login, messaging and friend management. Data flow diagrams and class diagrams are also included.
Scheduling Definition, objectives and types Maitree Patel
Scheduling is the process of determining which process will use the CPU when multiple processes are ready to execute. The objectives of scheduling are to maximize CPU utilization, throughput, and fairness while minimizing response time, turnaround time, and waiting time. There are three main types of schedulers: long-term schedulers manage process admission to the system; short-term or CPU schedulers select the next process to run on the CPU; and medium-term schedulers handle process suspension during I/O waits.
1) A semaphore consists of a counter, a waiting list, and wait() and signal() methods. Wait() decrements the counter and blocks if it becomes negative, while signal() increments the counter and resumes a blocked process if the counter becomes positive.
2) The dining philosophers problem is solved using semaphores to lock access to shared chopsticks, with one philosopher designated as a "weirdo" to avoid deadlock by acquiring locks in a different order.
3) The producer-consumer problem uses three semaphores - one to limit buffer size, one for empty slots, and one for locks - to coordinate producers adding to a bounded buffer
This document discusses software bugs including their history, causes, impact, and classification. It begins with definitions of common terms used to describe bugs and errors. Key events that resulted from software bugs like the Mariner 1 space probe failure and radiation therapy machine bugs that killed patients are summarized. The document also outlines common reasons why bugs are introduced during development including lack of testing and unrealistic timelines. It concludes with classifications of bugs and contact information for the author.
An insight into what role news agencies and various media houses play in India as a part of democracy in country. Its impact as a medium of communication in various situations - both good and bad. Also, the history of Indian media and its role in Indian electoral system.
Our application aims to bring about transparency, clarity and swiftness in the process of donation thus aiming to mitigate prevailing issues in whatever zone it is possible for us to do so. This is a project report for the same.
This document discusses various techniques for process synchronization. It begins by defining process synchronization as coordinating access to shared resources between processes to maintain data consistency. It then discusses critical sections, where shared data is accessed, and solutions like Peterson's algorithm and semaphores to ensure only one process accesses the critical section at a time. Semaphores use wait and signal operations on a shared integer variable to synchronize processes. The document covers binary and counting semaphores and provides an example of their use.
The Java Mail Server project allows clients to connect to a mail server to send and receive emails and attachments. The project is divided into three modules: a server module that uses server sockets to accept client connections, a client module that uses sockets to connect to the server, and an email inbox module that handles mail functions like forwarding, viewing attachments, and saving emails. The server stores details of client connections, mail sending and receiving. Clients can connect when the server is active to exchange emails with other clients. Usernames and passwords are stored in data files rather than a SQL server. The project provides automatic threading to handle socket connections and includes features for reliable TCP communication between clients.
This document discusses semaphores, which are integer variables that coordinate access to shared resources. It describes counting semaphores, which allow multiple processes to access a critical section simultaneously up to a set limit, and binary semaphores, which only permit one process at a time. Key differences are that counting semaphores can have any integer value while binary semaphores are limited to 0 or 1, and counting semaphores allow multiple slots while binary semaphores provide strict mutual exclusion. Limitations of semaphores include potential priority inversion issues and deadlocks if not used properly.
Al Qur’an as A Media of Journalism for Da’wahiosrjce
IOSR Journal of Humanities and Social Science is a double blind peer reviewed International Journal edited by International Organization of Scientific Research (IOSR).The Journal provides a common forum where all aspects of humanities and social sciences are presented. IOSR-JHSS publishes original papers, review papers, conceptual framework, analytical and simulation models, case studies, empirical research, technical notes etc.
We have designed this website with the purpose of allowing the students to give exams and view their results. This site is an attempt to remove the existing flaws in the manual system of conducting exams.
Students are provided the flexibility to choose among different types of aptitude and programming language tests.
The document describes the waterfall model of software development. It begins by listing the presenters and defining sequential and incremental software development models. It then discusses the waterfall model in more detail, describing it as a linear sequential process where each phase must be completed before the next begins. The document outlines the history, use cases, diagram, phases and advantages/disadvantages of the waterfall model.
The document describes a chat server application built using Java sockets. It includes a client and server component that allow users to login and send messages to each other. The server uses multithreading to handle multiple client connections concurrently by passing accepted socket connections to separate thread objects. The chat server provides group and private messaging capabilities and could be expanded in the future to include additional features like offline messaging, file sharing, and a user profile database.
SDLC is the acronym of Software Development Life Cycle. It is also called as Software development process. The software development life cycle (SDLC) is a framework defining tasks performed at each step in the software development process.
Review on Whatsapp's End to End encryption and Facebook integrationGovindarrajan NV
The presentation deals with the latest updates of whatsapp with the end to end encryption and Facebook integration explained in a very detailed manner from the basics with advantages and disadvantages.
The document provides project documentation for a Court Case Management System (CCMS) being developed for Ceylinco Insurance PLC. Key details include:
- The CCMS will manage case registration, courts, counsels, fees, payments and provide reporting capabilities.
- It will be a web-based system using PHP and MySQL to simplify complex case management processes and improve communication.
- The system aims to enhance productivity, communication, planning/monitoring and accessibility for Ceylinco Insurance staff.
Railway management system, database mini projectshashank reddy
This document describes a database project for a railway reservation system. It includes entities like users, passengers, trains, stations, tickets. It provides the entity relationship diagram and normalized database schema. It also includes sample SQL commands to create the tables and insert sample data into the tables. The tables created are for users, trains, stations, train status, tickets, passengers and relationship tables for starts, reaches, stops_at and books.
The document discusses solutions to the critical section problem where multiple processes need exclusive access to shared resources. It defines the critical section problem and requirements for a solution. It then presents three algorithms using shared variables to coordinate access between two processes in a way that satisfies mutual exclusion, progress, and bounded waiting.
The document discusses different types of early computer processing methods. Serial processing required users to restart the entire setup sequence if an error occurred, wasting significant time. To improve efficiency, simple batch processing was developed where multiple jobs were submitted in batches to maximize processor utilization and reduce wasted time from scheduling and setup between individual jobs. This represented an early form of multiprogramming to better use the expensive computer resources.
1. Process management is an integral part of operating systems for allocating resources, enabling information sharing, and protecting processes. The OS maintains data structures describing each process's state and resource ownership.
2. Processes go through discrete states and events can cause state changes. Scheduling selects processes to run from ready, device, and job queues using algorithms like round robin, shortest job first, and priority scheduling.
3. CPU scheduling aims to maximize utilization and throughput while minimizing waiting times using criteria like response time, turnaround time, and fairness between processes.
The document discusses how to rewrite Java code in Scala by taking advantage of Scala's functional programming features like case classes, pattern matching, filters, maps, folds, and generators to make the code more concise and readable. It provides examples of rewriting common Java constructs like filtering lists, mapping over lists, and reducing lists using these Scala features.
Queue data structures allow for first-in, first-out access to elements. They have two ends - a head for removing elements and a tail for adding elements. Common implementations include arrays, linked lists, and stacks. Priority queues order elements by priority when removing them. Double-ended queues allow adding/removing from either end.
This document discusses various techniques for process synchronization. It begins by defining process synchronization as coordinating access to shared resources between processes to maintain data consistency. It then discusses critical sections, where shared data is accessed, and solutions like Peterson's algorithm and semaphores to ensure only one process accesses the critical section at a time. Semaphores use wait and signal operations on a shared integer variable to synchronize processes. The document covers binary and counting semaphores and provides an example of their use.
The Java Mail Server project allows clients to connect to a mail server to send and receive emails and attachments. The project is divided into three modules: a server module that uses server sockets to accept client connections, a client module that uses sockets to connect to the server, and an email inbox module that handles mail functions like forwarding, viewing attachments, and saving emails. The server stores details of client connections, mail sending and receiving. Clients can connect when the server is active to exchange emails with other clients. Usernames and passwords are stored in data files rather than a SQL server. The project provides automatic threading to handle socket connections and includes features for reliable TCP communication between clients.
This document discusses semaphores, which are integer variables that coordinate access to shared resources. It describes counting semaphores, which allow multiple processes to access a critical section simultaneously up to a set limit, and binary semaphores, which only permit one process at a time. Key differences are that counting semaphores can have any integer value while binary semaphores are limited to 0 or 1, and counting semaphores allow multiple slots while binary semaphores provide strict mutual exclusion. Limitations of semaphores include potential priority inversion issues and deadlocks if not used properly.
Al Qur’an as A Media of Journalism for Da’wahiosrjce
IOSR Journal of Humanities and Social Science is a double blind peer reviewed International Journal edited by International Organization of Scientific Research (IOSR).The Journal provides a common forum where all aspects of humanities and social sciences are presented. IOSR-JHSS publishes original papers, review papers, conceptual framework, analytical and simulation models, case studies, empirical research, technical notes etc.
We have designed this website with the purpose of allowing the students to give exams and view their results. This site is an attempt to remove the existing flaws in the manual system of conducting exams.
Students are provided the flexibility to choose among different types of aptitude and programming language tests.
The document describes the waterfall model of software development. It begins by listing the presenters and defining sequential and incremental software development models. It then discusses the waterfall model in more detail, describing it as a linear sequential process where each phase must be completed before the next begins. The document outlines the history, use cases, diagram, phases and advantages/disadvantages of the waterfall model.
The document describes a chat server application built using Java sockets. It includes a client and server component that allow users to login and send messages to each other. The server uses multithreading to handle multiple client connections concurrently by passing accepted socket connections to separate thread objects. The chat server provides group and private messaging capabilities and could be expanded in the future to include additional features like offline messaging, file sharing, and a user profile database.
SDLC is the acronym of Software Development Life Cycle. It is also called as Software development process. The software development life cycle (SDLC) is a framework defining tasks performed at each step in the software development process.
Review on Whatsapp's End to End encryption and Facebook integrationGovindarrajan NV
The presentation deals with the latest updates of whatsapp with the end to end encryption and Facebook integration explained in a very detailed manner from the basics with advantages and disadvantages.
The document provides project documentation for a Court Case Management System (CCMS) being developed for Ceylinco Insurance PLC. Key details include:
- The CCMS will manage case registration, courts, counsels, fees, payments and provide reporting capabilities.
- It will be a web-based system using PHP and MySQL to simplify complex case management processes and improve communication.
- The system aims to enhance productivity, communication, planning/monitoring and accessibility for Ceylinco Insurance staff.
Railway management system, database mini projectshashank reddy
This document describes a database project for a railway reservation system. It includes entities like users, passengers, trains, stations, tickets. It provides the entity relationship diagram and normalized database schema. It also includes sample SQL commands to create the tables and insert sample data into the tables. The tables created are for users, trains, stations, train status, tickets, passengers and relationship tables for starts, reaches, stops_at and books.
The document discusses solutions to the critical section problem where multiple processes need exclusive access to shared resources. It defines the critical section problem and requirements for a solution. It then presents three algorithms using shared variables to coordinate access between two processes in a way that satisfies mutual exclusion, progress, and bounded waiting.
The document discusses different types of early computer processing methods. Serial processing required users to restart the entire setup sequence if an error occurred, wasting significant time. To improve efficiency, simple batch processing was developed where multiple jobs were submitted in batches to maximize processor utilization and reduce wasted time from scheduling and setup between individual jobs. This represented an early form of multiprogramming to better use the expensive computer resources.
1. Process management is an integral part of operating systems for allocating resources, enabling information sharing, and protecting processes. The OS maintains data structures describing each process's state and resource ownership.
2. Processes go through discrete states and events can cause state changes. Scheduling selects processes to run from ready, device, and job queues using algorithms like round robin, shortest job first, and priority scheduling.
3. CPU scheduling aims to maximize utilization and throughput while minimizing waiting times using criteria like response time, turnaround time, and fairness between processes.
The document discusses how to rewrite Java code in Scala by taking advantage of Scala's functional programming features like case classes, pattern matching, filters, maps, folds, and generators to make the code more concise and readable. It provides examples of rewriting common Java constructs like filtering lists, mapping over lists, and reducing lists using these Scala features.
Queue data structures allow for first-in, first-out access to elements. They have two ends - a head for removing elements and a tail for adding elements. Common implementations include arrays, linked lists, and stacks. Priority queues order elements by priority when removing them. Double-ended queues allow adding/removing from either end.
Выступление в рамках спецкурса "Немейнстримовые технологии разработки", читаемого в НГУ. http://bit.ly/mainstreamless
Аудио дорожка работает, но нужно иметь некоторое терпение, так как грузится она не моментально.
This document discusses monads and continuations in functional programming. It provides examples of using monads like Option and List to handle failure in sequences of operations. It also discusses delimited continuations as a low-level control flow primitive that can implement exceptions, concurrency, and suspensions. The document proposes using monads to pass implicit state through programs by wrapping computations in a state transformer (ST) monad.
An Introduction to Higher Order Functions in Spark SQL with Herman van HovellDatabricks
Nested data types offer Apache Spark users powerful ways to manipulate structured data. In particular, they allow you to put complex objects like arrays, maps and structures inside of columns. This can help you model your data in a more natural way.
While this feature is certainly useful, it can quite bit cumbersome to manipulate data inside of complex objects because SQL (and Spark) do not have primitives for working with such data. In addition, it is time-consuming, non-performant, and non-trivial. During this talk we will discuss some of the commonly used techniques for working with complex objects, and we will introduce new ones based on Higher-order functions. Higher-order functions will be part of Spark 2.4 and are a simple and performant extension to SQL that allow a user to manipulate complex data such as arrays.
Michal Malohlava presents: Open Source H2O and Scala Sri Ambati
Michal Malohlava discusses the magic behind the math - exposing the way that open source big data analysis H2O uses Scala to get work done, and demos how users can interact with Scala to get the most out of data analysis.
Crystal Ball Event Prediction and Log Analysis with Hadoop MapReduce and SparkJivan Nepali
This document summarizes a student's Big Data project using MapReduce (Hadoop) and Spark that analyzes log data. It describes implementations of three approaches (pair, stripe, hybrid) to predict event co-occurrence relationships. It also describes using Spark and Scala to analyze web server log files to find top products, categories, and client IPs. Pseudocode and results are shown for each technique.
This document provides an agenda and overview for a Spark workshop covering Spark basics and streaming. The agenda includes sections on Scala, Spark, Spark SQL, and Spark Streaming. It discusses Scala concepts like vals, vars, defs, classes, objects, and pattern matching. It also covers Spark RDDs, transformations, actions, sources, and the spark-shell. Finally, it briefly introduces Spark concepts like broadcast variables, accumulators, and spark-submit.
The document provides an introduction to machine learning. It discusses the author's path to becoming a data scientist and some key machine learning concepts, including:
- Required skills at different experience levels for machine learning roles
- Popular machine learning approaches like deep learning and reinforcement learning
- Common machine learning problems like one shot learning and imbalanced datasets
- How machine learning works by using tricks on data through parametric models and free parameters
- Key questions in machine learning like what to teach, how to teach, and to what entity
- Popular machine learning frameworks like TensorFlow that automate tasks
Perl6 is a powerful programming language that incorporates many programming paradigms including functional, object oriented, reactive, and event based programming. It aims to provide programmers with a toolbox of features to build applications in many different styles. The language includes features like junctions, promises, channels, supplies, sets, roles, and strong support for Unicode. It also allows calling external native libraries and has built-in support for rational numbers, sequences, and lazy evaluation. Perl6 code examples are provided to demonstrate various features like List utilities, junctions, promises, channels/supplies, roles, and native calls. Further reading resources are also referenced.
Perl6 is a powerful programming language that incorporates many programming paradigms including functional, object-oriented, and reactive programming. It has built-in support for concepts like promises to handle asynchronous code, channels for communicating between asynchronous processes, and sets/bags for storing unique values. The language also has features for rational numbers, lazy evaluation, roles for composition, and easy integration with native libraries. Perl6 aims to provide programmers a flexible toolbox to build applications in many different styles.
The document discusses maximum flow computation and algorithms for finding the maximum flow in a flow network. It describes flow networks as directed graphs where each edge has a capacity and explains the maximum flow problem as finding the most flow that can be pushed from a source node to a sink node respecting the edge capacities. The Ford-Fulkerson algorithm and its implementation using breadth-first search (Edmonds-Karp algorithm) are presented for finding augmenting paths and incrementally increasing the flow until no more is possible.
(How) can we benefit from adopting scala?Tomasz Wrobel
Scala offers benefits from adopting it such as increased productivity through concise and expressive code, static typing with type inference, support for both object-oriented and functional programming paradigms, and interoperability with Java. Switching from Java to Scala involves some changes like using val for immutable variables and var for mutable, but overall the syntax is quite similar which eases the transition.
Scala is a programming language that runs on the Java Virtual Machine (JVM) and is designed to express common programming patterns in a concise, elegant, and type-safe way. Some key points about Scala include that it is functional and object-oriented, statically typed, and allows seamless integration with Java. Scala code is often more concise than equivalent Java code through features like pattern matching and immutable data structures. Functional programming principles like pure functions, recursion, and avoiding side effects are emphasized in Scala.
Data Structures and Algorithm AnalysisSpring 2020 Post Midterm Ejeniihykdevara
Data Structures and Algorithm Analysis
Spring 2020 Post Midterm Exam – 100 points + 10 bonus
NAME:
1. How much memory will the following structures take up? Hint: int takes 4 bytes, float takes 4 bytes, char takes 1 byte. – 9 points
a. struct Structure1 {int a,b,c,d,e[10]; float f;};
b. struct Structure2 {int a[12]; float b[5];};
c. struct Structure3 {char a[10][12][4], b[5][5], c[10];};
2. Show the steps when sorting (smallest to largest) the following arrays of numbers using selection sort i.e. every time a swap occurs, show what the current state of the array looks like, including the final sorted array. – 12 points
a. [10, 2, 5, 8, 9, 1, 4, 7]
b. [7, 1, 3, 2, 5, 4, 8, 12, 9]
c. [8, 7, 6, 5, 4, 3, 2, 1]
d. [5, 3, 8, 1, 9, 4, 2, 6]
3. Big-O: What is meant by f(n) = O(g(n))? Give the definition and then explain what it means in your own terms. – 5 points
4. Big-Omega: What is meant by f(n) = Ω(g(n))? Give the definition and then explain what it means in your own terms. – 5 points
5. Show that , make sure you use the definition and justify the inequalities and constants used. - 4 points
6. Show that , make sure you use the definition and justify the inequalities and constants used. - 4 points
7. Show that , make sure you use the definition and justify the inequalities and constants used. - 4 points
8. Show that , make sure you use the definition and justify the inequalities and constants used. - 4 points
9. Show that , make sure you use the definition and justify the inequalities and constants used. - 4 points
10. What principle governs how you add/remove elements in a stack? Spell it out and briefly explain. - 4 points
11. Briefly describe an application of a stack. - 4 points
12. What principle governs how you add/remove elements in a queue? Spell it out and briefly explain. - 4 points
13. Briefly describe an application of a queue. - 4 points
Consider the following graph (pseudocode for BFS and DFS given on page 9):
14. Write the order in which the nodes would be visited in when doing a breadth first search (BFS) traversal starting at node 4. Also, write the distances from 4 to every other node. - 6 points
15. Write the order in which the nodes would be visited in when doing a breadth first search (BFS) traversal starting at node 5. Also, write the distances from 5 to every other node. - 6 points
Same graph (for your convenience):
16. Write the order in which the nodes would be visited in when doing a depth first search (DFS) traversal starting at node 4 (order discovered or order off the stack). - 6 points
17. Write the order in which the nodes would be visited in when doing a depth first search (DFS) traversal starting at node 5 (order discovered or order off the stack). - 6 points
18. Give the definition of a graph. - 5 points
19. Give the definition of a tree (from graph theory). - 4 ...
This document outlines the agenda and content for a Scala training workshop. The agenda includes an introduction, sections on types and pattern matching, lists, collections, lazy evaluation, exercises, and sharing. The types and pattern matching section covers functions as objects, subtyping and generics, pattern matching, and examples. It also discusses blocks, tail recursion, higher-order functions, currying, and data abstraction through class hierarchies and traits vs abstract classes. The document provides examples for many of these concepts. Exercises at the end include implementing Pascal's triangle through recursion.
This document introduces higher order functions (HOFs) in Scala. It provides examples of how HOFs such as map and filter can transform collections in more idiomatic and functional ways compared to imperative approaches using loops. Key benefits of HOFs include producing immutable and thread-safe results without needing to manually manage intermediate data structures. The document also briefly outlines some other powerful HOFs like reduce, partition, min, max and parallel collections.
The document discusses the Pi-calculus, a formal system for describing processes that communicate via channels. It provides an overview of the history and motivation for Pi-calculus, its basic elements like variables, channels, and processes, examples of how it can model processes and lambda calculus, and rules for reducing Pi-calculus expressions. Pi-calculus is used to describe concurrent and distributed systems formally and can describe processes that change over time through communication.
This presentation discusses the following topics:
Basic features of R
Exploring R GUI
Data Frames & Lists
Handling Data in R Workspace
Reading Data Sets & Exporting Data from R
Manipulating & Processing Data in R
Association rule mining is used to find relationships between items in transaction data. It identifies rules that can predict the occurrence of an item based on other items purchased together frequently. Some key metrics used to evaluate rules include support, which measures how frequently an itemset occurs; confidence, which measures how often items in the predicted set occur given items in the predictor set; and lift, which compares the confidence to expected confidence if items were independent. An example association rule evaluated is {Milk, Diaper} -> {Beer} with support of 0.4, confidence of 0.67, and lift of 1.11.
This document discusses clustering, which is the task of grouping data points into clusters so that points within the same cluster are more similar to each other than points in other clusters. It describes different types of clustering methods, including density-based, hierarchical, partitioning, and grid-based methods. It provides examples of specific clustering algorithms like K-means, DBSCAN, and discusses applications of clustering in fields like marketing, biology, libraries, insurance, city planning, and earthquake studies.
Classification is a data analysis technique used to predict class membership for new observations based on a training set of previously labeled examples. It involves building a classification model during a training phase using an algorithm, then testing the model on new data to estimate accuracy. Some common classification algorithms include decision trees, Bayesian networks, neural networks, and support vector machines. Classification has applications in domains like medicine, retail, and entertainment.
The document discusses the assumptions and properties of ordinary least squares (OLS) estimators in linear regression analysis. It notes that OLS estimators are best linear unbiased estimators (BLUE) if the assumptions of the linear regression model are met. Specifically, it assumes errors have zero mean and constant variance, are uncorrelated, and are normally distributed. Violation of the assumption of constant variance is known as heteroscedasticity. The document outlines how heteroscedasticity impacts the properties of OLS estimators and their use in applications like econometrics.
This document provides an introduction to regression analysis. It discusses that regression analysis investigates the relationship between dependent and independent variables to model and analyze data. The document outlines different types of regressions including linear, polynomial, stepwise, ridge, lasso, and elastic net regressions. It explains that regression analysis is used for predictive modeling, forecasting, and determining the impact of variables. The benefits of regression analysis are that it indicates significant relationships and the strength of impact between variables.
MYCIN was an early expert system developed at Stanford University in 1972 to assist physicians in diagnosing and selecting treatment for bacterial and blood infections. It used over 600 production rules encoding the clinical decision criteria of infectious disease experts to diagnose patients based on reported symptoms and test results. While it could not replace human diagnosis due to computing limitations at the time, MYCIN demonstrated that expert knowledge could be represented computationally and established a foundation for more advanced machine learning and knowledge base systems.
The document discusses expert systems, which are computer applications that solve complex problems at a human expert level. It describes the characteristics and capabilities of expert systems, why they are useful, and their key components - knowledge base, inference engine, and user interface. The document also outlines common applications of expert systems and the general development process.
The Dempster-Shafer Theory was developed by Arthur Dempster in 1967 and Glenn Shafer in 1976 as an alternative to Bayesian probability. It allows one to combine evidence from different sources and obtain a degree of belief (or probability) for some event. The theory uses belief functions and plausibility functions to represent degrees of belief for various hypotheses given certain evidence. It was developed to describe ignorance and consider all possible outcomes, unlike Bayesian probability which only considers single evidence. An example is given of using the theory to determine the murderer in a room with 4 people where the lights went out.
A Bayesian network is a probabilistic graphical model that represents conditional dependencies among random variables using a directed acyclic graph. It consists of nodes representing variables and directed edges representing causal relationships. Each node contains a conditional probability table that quantifies the effect of its parent nodes on that variable. Bayesian networks can be used to calculate the probability of events occurring based on the network structure and conditional probability tables, such as computing the probability of an alarm sounding given that no burglary or earthquake occurred but two neighbors called.
This document discusses knowledge-based agents in artificial intelligence. It defines knowledge-based agents as agents that maintain an internal state of knowledge, reason over that knowledge, update their knowledge based on observations, and take actions. Knowledge-based agents have two main components: a knowledge base that stores facts about the world, and an inference system that applies logical rules to deduce new information from the knowledge base. The document also describes the architecture of knowledge-based agents and different approaches to designing them.
A rule-based system uses predefined rules to make logical deductions and choices to perform automated actions. It consists of a database of rules representing knowledge, a database of facts as inputs, and an inference engine that controls the process of deriving conclusions by applying rules to facts. A rule-based system mimics human decision making by applying rules in an "if-then" format to incoming data to perform actions, but unlike AI it does not learn or adapt on its own.
This document discusses formal logic and its applications in AI and machine learning. It begins by explaining why logic is useful in complex domains or with little data. It then describes logic-based approaches to AI that use symbolic reasoning as an alternative to machine learning. The document proceeds to explain propositional logic and first-order logic, noting how first-order logic improves on propositional logic by allowing variables. It also mentions other logics and their applications in areas like automated discovery, inductive programming, and verification of computer systems and machine learning models.
The document discusses production systems, which are rule-based systems used in artificial intelligence to model intelligent behavior. A production system consists of a global database, set of production rules, and control system. The rules fire to modify the database based on conditions. Different control strategies are used to determine which rules fire. Production systems are modular and allow knowledge representation as condition-action rules. Examples of applications in problem solving are provided.
The document discusses game playing in artificial intelligence. It describes how general game playing (GGP) involves designing AI that can play multiple games by learning the rules, rather than being programmed for a specific game. The document outlines how the minimax algorithm is commonly used for game playing, involving move generation and static evaluation functions to search game trees and determine the best move by maximizing or minimizing values at each level.
A study on “Diagnosis Test of Diabetics and Hypertension by AI”, Presentation slides for International Conference on "Life Sciences: Acceptance of the New Normal", St. Aloysius' College, Jabalpur, Madhya Pradesh, India, 27-28 August, 2021
A study on “impact of artificial intelligence in covid19 diagnosis”Dr. C.V. Suresh Babu
A study on “Impact of Artificial Intelligence in COVID-19 Diagnosis”, Presentation slides for International Conference on "Life Sciences: Acceptance of the New Normal", St. Aloysius' College, Jabalpur, Madhya Pradesh, India, 27-28 August, 2021
A study on “impact of artificial intelligence in covid19 diagnosis”Dr. C.V. Suresh Babu
Although the lungs are one of the most vital organs in the body, they are vulnerable to infection and injury. COVID-19 has put the entire world in an unprecedented difficult situation, bringing life to a halt and claiming thousands of lives all across the world. Medical imaging, such as X-rays and computed tomography (CT), is essential in the global fight against COVID-19, and newly emerging artificial intelligence (AI) technologies are boosting the power of imaging tools and assisting medical specialists. AI can improve job efficiency by precisely identifying infections in X-ray and CT images and allowing further measurement. We focus on the integration of AI with X-ray and CT, both of which are routinely used in frontline hospitals, to reflect the most recent progress in medical imaging and radiology combating COVID-19.
Leveraging Generative AI to Drive Nonprofit InnovationTechSoup
In this webinar, participants learned how to utilize Generative AI to streamline operations and elevate member engagement. Amazon Web Service experts provided a customer specific use cases and dived into low/no-code tools that are quick and easy to deploy through Amazon Web Service (AWS.)
How to Make a Field Mandatory in Odoo 17Celine George
In Odoo, making a field required can be done through both Python code and XML views. When you set the required attribute to True in Python code, it makes the field required across all views where it's used. Conversely, when you set the required attribute in XML views, it makes the field required only in the context of that particular view.
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
Level 3 NCEA - NZ: A Nation In the Making 1872 - 1900 SML.pptHenry Hollis
The History of NZ 1870-1900.
Making of a Nation.
From the NZ Wars to Liberals,
Richard Seddon, George Grey,
Social Laboratory, New Zealand,
Confiscations, Kotahitanga, Kingitanga, Parliament, Suffrage, Repudiation, Economic Change, Agriculture, Gold Mining, Timber, Flax, Sheep, Dairying,
Chapter wise All Notes of First year Basic Civil Engineering.pptxDenish Jangid
Chapter wise All Notes of First year Basic Civil Engineering
Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
Gender and Mental Health - Counselling and Family Therapy Applications and In...PsychoTech Services
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2. Introduction
• Queues are everywhere in parallel applications
and operating systems
• Many researchers have proposed queues
–
–
–
–
Hwang and Briggs
Gottlieb
Massalin
Et al. etc…
• Queue performance can be critical to operating
system performance
– Scheduling Queues
– Free memory lists
– Many other critical kernel operations
3. Concurrent FIFO Queue algorithms
• Blocking algorithms risk performance
degradation
– A process can be delayed or halted at inopportune
moments
• Scheduling preemption
• Page faults
• Cache misses
– Slow processes can prevent faster ones from
completing indefinitely
• Non-Blocking algorithms must solve the ABA
problem
– During contention, some process will complete
within a given number of operations
4. ABA problem
Pop () {
loop
value = SM
newVal = value -1
THREAD1
THREAD2
data = Stack Data
CAS(&SM, value, newVal)
v1=Pop()
value = 5
Push (d) {
loop
value = SM
newVal = value +1
Stack Data = d
CAS(&SM, value, newVal)
break
Stack
SM
5
…
x
time
newVal = 4
data=X
return data
value = 5
newVal = 4
break
v2=Pop()
data=X
5. ABA problem
Pop () {
loop
value = SM
newVal = value -1
THREAD1
THREAD2
data = Stack Data
CAS(&SM, value, newVal)
v1=Pop()
value = 5
Push (d) {
loop
newVal = 4
data=X
return data
value = 5
newVal = 4
break
v2=Pop()
data=X
CAS(&SM,value,newVal)
value = SM
newVal = value +1
Stack Data = d
CAS(&SM, value, newVal)
break
Stack
SM
4
…
x
time
6. ABA problem
Pop () {
loop
value = SM
newVal = value -1
THREAD1
THREAD2
data = Stack Data
CAS(&SM, value, newVal)
v1=Pop()
value = 5
Push (d) {
loop
newVal = 4
data=X
return data
value = 5
newVal = 4
break
v2=Pop()
data=X
CAS(&SM,value,newVal)
value = SM
v2 = x
newVal = value +1
Stack Data = d
CAS(&SM, value, newVal)
break
Stack
SM
4
…
x
time
7. ABA problem
Pop () {
loop
value = SM
newVal = value -1
THREAD1
THREAD2
data = Stack Data
CAS(&SM, value, newVal)
v1=Pop()
value = 5
Push (d) {
loop
newVal = 4
data=X
return data
value = 5
newVal = 4
break
v2=Pop()
data=X
CAS(&SM,value,newVal)
value = SM
v2 = x
newVal = value +1
Push(z)
Stack Data = d
CAS(&SM, value, newVal)
break
Stack
SM
4
…
x
time
8. ABA problem
Pop () {
loop
value = SM
newVal = value -1
THREAD1
THREAD2
data = Stack Data
CAS(&SM, value, newVal)
v1=Pop()
value = 5
Push (d) {
loop
newVal = 4
data=X
return data
value = 5
newVal = 4
break
v2=Pop()
data=X
CAS(&SM,value,newVal)
value = SM
v2 = x
newVal = value +1
Stack Data = d
Push(z)
CAS(&SM, value, newVal)
value = 4
break
Stack
SM
4
…
x
time
9. ABA problem
Pop () {
loop
value = SM
newVal = value -1
THREAD1
THREAD2
data = Stack Data
CAS(&SM, value, newVal)
v1=Pop()
value = 5
Push (d) {
loop
newVal = 4
data=X
return data
value = 5
newVal = 4
break
v2=Pop()
data=X
CAS(&SM,value,newVal)
value = SM
v2 = x
newVal = value +1
Stack Data = d
Push(z)
CAS(&SM, value, newVal)
value = 4
break
newVal=5
Stack
SM
4
…
x
time
10. ABA problem
Pop () {
loop
value = SM
newVal = value -1
THREAD1
THREAD2
data = Stack Data
CAS(&SM, value, newVal)
v1=Pop()
value = 5
Push (d) {
loop
newVal = 4
data=X
return data
value = 5
newVal = 4
break
v2=Pop()
data=X
CAS(&SM,value,newVal)
value = SM
v2 = x
newVal = value +1
Stack Data = d
Push(z)
CAS(&SM, value, newVal)
value = 4
break
newVal=5
Stack
CAS(&SM,value,newVal)
SM
5
…
z
time
11. ABA problem
Pop () {
loop
value = SM
newVal = value -1
THREAD1
THREAD2
data = Stack Data
CAS(&SM, value, newVal)
v1=Pop()
value = 5
Push (d) {
newVal = 4
data=X
return data
value = 5
newVal = 4
break
v2=Pop()
data=X
loop
CAS(&SM,value,newVal)
value = SM
v2 = x
newVal = value +1
Stack Data = d
Push(z)
CAS(&SM, value, newVal)
value = 4
break
newVal=5
Stack
CAS(&SM,value,newVal)
CAS(&SM,value,newVal)
SM
5
…
z
time
12. ABA problem
Pop () {
loop
value = SM
newVal = value -1
THREAD1
THREAD2
data = Stack Data
CAS(&SM, value, newVal)
v1=Pop()
value = 5
Push (d) {
newVal = 4
data=X
return data
value = 5
newVal = 4
break
v2=Pop()
data=X
loop
CAS(&SM,value,newVal)
value = SM
v2 = x
newVal = value +1
Stack Data = d
Push(z)
CAS(&SM, value, newVal)
value = 4
break
newVal=5
Stack
CAS(&SM,value,newVal)
CAS(&SM,value,newVal)
v1=x
SM
4
…
z
time
13. ABA problem
Pop () {
loop
value = SM
newVal = value -1
THREAD1
THREAD2
data = Stack Data
CAS(&SM, value, newVal)
v1=Pop()
value = 5
Push (d) {
newVal = 4
data=X
return data
value = 5
newVal = 4
break
v2=Pop()
data=X
loop
CAS(&SM,value,newVal)
value = SM
v2 = x
newVal = value +1
Stack Data = d
Push(z)
CAS(&SM, value, newVal)
value = 4
break
newVal=5
Stack
CAS(&SM,value,newVal)
CAS(&SM,value,newVal)
v1=x
SM
4
…
z
CAS should fail but it succeeds
time
Thread1 has Thread2’s data
14. Solutions for ABA problem
Cache Kernel
• Add version # to data structures
• Increment # during every CAS instruction
LL/SC
• Fail if Cache Line has been written to
15. Solution for ABA problem
Pop () {
loop
value = SM
newVal = value -1
THREAD1
THREAD2
data = Stack Data
DCAS(&SM, value,
v1=Pop()
value = 5
return data
Push (d) {
newVal = 4
data=X
break
value = 5
newVal = 4
<ver++,newVal>)
v2=Pop()
data=X
loop
DCAS(&SM,value,ver,newVal)
value = SM
v2 = x
newVal = value +1
Stack Data = d
Push(z)
DCAS(&SM, value,
value = 4
<ver++,newVal>)
newVal=5
Stack
break
DCAS(&SM,value,ver,newVal)
DCAS(&SM,value,ver,newVal)
Will not incorrectly succeed
SM
5
…
z
(ver != ver+2)
time
16. Solution for ABA problem
Pop () {
loop
value = SM
newVal = value -1
THREAD1
THREAD2
data = Stack Data
DCAS(&SM, value,
v1=Pop()
value = 5
return data
Push (d) {
newVal = 4
data=Z
break
value = 5
newVal = 4
<ver++,newVal>)
v2=Pop()
data=X
loop
DCAS(&SM,value,ver,newVal)
value = SM
v2 = x
newVal = value +1
Stack Data = d
Push(z)
DCAS(&SM, value,
value = 4
<ver++,newVal>)
newVal=5
Stack
break
DCAS(&SM,value,ver,newVal)
DCAS(&SM,value,ver,newVal)
Will not incorrectly succeed
SM
4
(ver != ver+2)
…
time
V1 = Z
17. Correctness Properties
1.
2.
3.
4.
5.
The linked list is always connected
Nodes only inserted after the last node
Nodes only deleted from beginning
Head always points to the first node
Tail always points to a node in the list
52. struct node_t {
data_type value
node_t * next
}
struct queue_t {
pointer_t Head
pointer_t Tail
lock_type H_lock
lock_type T_lock
}
initialize(Q: pointer to queue t)
node = new node()
node–>next.ptr = NULL
Q–>Head = Q–>Tail = node
Q–>H lock = Q–>T lock = FREE
dequeue(Q: pointer to queue t, pvalue: pointer to data type): boolean
lock(&Q–>H lock)
node = Q–>Head
new head = node–>next
if new head == NULL
enqueue(Q: pointer to queue t, value: data type)
unlock(&Q–>H lock)
node = new node()
return FALSE
node–>value = value
endif
node–>next.ptr = NULL
*pvalue = new head–>value
lock(&Q–>T lock)
Q–>Head = new head
Q–>Tail–>next = node
unlock(&Q–>H lock)
Q–>Tail = node
free(node)
unlock(&Q–>T lock)
return TRUE
• Algorithms have same general structure only different
data types
• No loops, ‘busy waiting’ instead
• Only dequeues access Head Lock
• Only enqueues access Tail Lock
53. Performance Parameters
• Net execution time for one million
enqueue/dequeue pairs
• 12-processor Silicon Graphics Challenge
multiprocessor
• Algorithms compiled with using highest
optimization level
• Including many hand optimizations
55. Conclusion
• NBS clear winner for multiprocessor
multiprogrammed systems
• Above 5 processors, use the new nonblocking queue
• If hardware only supports test-and-set use
two lock queue
• For two or less processors use a single
lock algorithm for queues