Akka is a toolkit for building highly concurrent, distributed, and fault-tolerant applications on the JVM. It provides actors as the fundamental unit of concurrency. Actors receive messages asynchronously and process them one at a time by applying behaviors. Akka uses a supervision hierarchy where actors monitor child actors and handle failures through configurable strategies like restart or stop. This provides clean separation of processing and error handling compared to traditional approaches.
The Scala programming language has been gaining momentum recently as an alternative (and some might say successor) to Java on the JVM. This talk will start with an introduction to basic Scala syntax and concepts, then delve into some of Scala's more interesting and unique features. At the end we'll show a brief example of how Scala is used by the Lift web framework to simplify dynamic web apps.
Scala is an object-oriented and functional programming language that runs on the Java Virtual Machine. It was designed by Martin Odersky and developed at EPFL in Switzerland. Scala combines object-oriented and functional programming principles, including support for immutable data structures, pattern matching, and closures. It interoperates seamlessly with existing Java code and libraries.
Functional Objects & Function and ClosuresSandip Kumar
Scala functions are objects that implement traits like Function1. Functions are treated as objects with an apply method. When a function is defined as a method in a class, it is treated differently than a standalone function. Functions can take variable arguments using a * notation and have default parameter values specified.
Scala is a multi-paradigm programming language that runs on the Java Virtual Machine. It is intended to be both object-oriented and functional. Scala is compatible with Java and allows Java code to interoperate with Scala code. Some key features of Scala include type inference, lazy evaluation, treating methods as variables, and support for both object-oriented and functional programming paradigms.
I used these slides for a Scala workshop that I gave. They are based on these: http://www.scala-lang.org/node/4454. Thanks to Alf Kristian Støyle and Fredrik Vraalsen for sharing!
Scala is a multi-paradigm language that runs on the JVM and interoperates with Java code and libraries. It combines object-oriented and functional programming by allowing functions to be treated as objects and supports features like traits, pattern matching, and immutable data structures. The Scala compiler infers types and generates boilerplate code like getters/setters, making development more productive compared to Java. While Scala has a learning curve, it allows a more concise and scalable language for building applications.
Starting with Scala : Frontier Developer's Meetup December 2010Derek Chen-Becker
This document provides an overview of the Scala programming language presented at a meetup event. It discusses Scala's history and pedigree, being created by Martin Odersky. It outlines some key aspects of Scala like being object-oriented, functional, and working on the JVM. The talk covers Scala fundamentals like immutable values, mutable variables, functions, and objects. It also discusses traits, classes, case classes and more Scala concepts.
The Scala programming language has been gaining momentum recently as an alternative (and some might say successor) to Java on the JVM. This talk will start with an introduction to basic Scala syntax and concepts, then delve into some of Scala's more interesting and unique features. At the end we'll show a brief example of how Scala is used by the Lift web framework to simplify dynamic web apps.
Scala is an object-oriented and functional programming language that runs on the Java Virtual Machine. It was designed by Martin Odersky and developed at EPFL in Switzerland. Scala combines object-oriented and functional programming principles, including support for immutable data structures, pattern matching, and closures. It interoperates seamlessly with existing Java code and libraries.
Functional Objects & Function and ClosuresSandip Kumar
Scala functions are objects that implement traits like Function1. Functions are treated as objects with an apply method. When a function is defined as a method in a class, it is treated differently than a standalone function. Functions can take variable arguments using a * notation and have default parameter values specified.
Scala is a multi-paradigm programming language that runs on the Java Virtual Machine. It is intended to be both object-oriented and functional. Scala is compatible with Java and allows Java code to interoperate with Scala code. Some key features of Scala include type inference, lazy evaluation, treating methods as variables, and support for both object-oriented and functional programming paradigms.
I used these slides for a Scala workshop that I gave. They are based on these: http://www.scala-lang.org/node/4454. Thanks to Alf Kristian Støyle and Fredrik Vraalsen for sharing!
Scala is a multi-paradigm language that runs on the JVM and interoperates with Java code and libraries. It combines object-oriented and functional programming by allowing functions to be treated as objects and supports features like traits, pattern matching, and immutable data structures. The Scala compiler infers types and generates boilerplate code like getters/setters, making development more productive compared to Java. While Scala has a learning curve, it allows a more concise and scalable language for building applications.
Starting with Scala : Frontier Developer's Meetup December 2010Derek Chen-Becker
This document provides an overview of the Scala programming language presented at a meetup event. It discusses Scala's history and pedigree, being created by Martin Odersky. It outlines some key aspects of Scala like being object-oriented, functional, and working on the JVM. The talk covers Scala fundamentals like immutable values, mutable variables, functions, and objects. It also discusses traits, classes, case classes and more Scala concepts.
Scala Intro training @ Lohika, Odessa, UA.
This is a basic Scala Programming Language overview intended to evangelize the language among any-language programmers.
Some notes about programming in Scala: it covers Scala syntax and semantics, programming techniques, idioms, patterns. Many Scala features are introduced, from basic to intermediate and advanced. These are not introductory notes, but they assume a working knowledge with some other programming language (Java, C#, C++), object-oriented programming (OOP) concepts, and functional programming (FP) concepts.
This document provides an introduction to the Scala programming language. It begins with an overview of Scala's motivation and history. It then covers the basics of Scala including simple data structures, loops, objects, types and generics. More advanced topics such as traits, mixins, implicit conversions and sealed classes are also discussed. The document concludes with references for further reading.
This document provides an overview of Scala fundamentals including:
- Scala is a programming language for the JVM that supports both object-oriented and functional paradigms.
- It defines variables, values, lazy values, functions, types, classes, objects, traits, and higher-order functions.
- Classes can extend other classes and traits, allowing for multiple inheritance. Objects are used as singletons.
- Functional concepts like immutability, anonymous functions, and higher-order functions are supported.
The document summarizes the agenda and content of a Scala training workshop. The agenda includes functions and evaluations, higher order functions, data and abstraction, and exercises. Key points from the document include:
- Functions can be defined conditionally and with value definitions. Blocks allow grouping of definitions and expressions. Tail recursion optimizes recursion by reusing the call stack.
- Higher order functions allow functions to be passed as parameters or returned as results. Currying transforms functions that take multiple parameters into chains of functions that each take a single parameter.
- Classes define hierarchies and traits provide flexibility for code reuse like interfaces while abstract classes are used for base classes requiring constructor arguments.
- Exercises include implementing
Short (45 min) version of my 'Pragmatic Real-World Scala' talk. Discussing patterns and idioms discovered during 1.5 years of building a production system for finance; portfolio management and simulation.
Martin Odersky discusses the past, present, and future of Scala over the past 5 years and next 5 years. Key points include:
- Scala has grown significantly in usage and community over the past 6 years since its first release.
- Scala 2.8 will include improvements like new collections, package objects, named/default parameters, and better tool support.
- Over the next 5 years, Scala will focus on improving concurrency and parallelism through better abstractions, analyses, and static typing support.
Java 8 introduces lambda expressions and default interface methods (also known as virtual extension methods) which allow adding new functionality to existing interfaces without breaking backwards compatibility. While this helps add lambda support to existing Java collections, it has limitations compared to Scala's approach using traits, which allow true multiple inheritance of both behavior and state in a typesafe manner. Scala also introduced the "pimp my library" pattern using implicits which allows extending existing classes with new methods, providing more flexibility for library evolution than Java 8's virtual extension methods.
Scala Test allows testing of Scala and Java code. It integrates with tools like JUnit, TestNG, Ant, and Maven. Scala Test is customizable and uses traits to define different styles of testing, including Suite for defining test classes and methods, FunSuite for functional tests, Spec for behavior-driven development, and FeatureSpec for integration and acceptance tests.
The great attractiveness of purely functional languages is their ability to depart from sequential order of computation. Theoretically, it enables two important features of the compiler:
1) The ability to reorder computation flow, making the program implicitly parallelisable. Modern imperative language compilers, even using careful synchronization of concurrent code, still generate huge chunks of sequential instructions that need to be executed on a single processor core; a purely functional language compilers can dispatch very small chunks to many (hundreds and thousands) of cores, carefully eliminating as many execution path dependencies as possible.
2) As the compiler formalizes different types of side effects, it can detect a whole new class of program errors at compile time, including resource acquisition and releasing problems, concurrent access to shared resources, many types of deadlocks etc. It is not yet a full-fledged program verification, but it is a big step in that direction.
Scala is a semi-imperative language with strong support for functional programming and rich type system. One can isolate the purely functional core of the language which can be put on the firm mathematical foundation of dependent type theories. We argue that it is possible to treat Scala code as it's written by now as an implicit do-notation which can be then reduced to a purely functional core by means of recently introduced Scala macros. The formalism of arrows and applicative contexts can bring Scala to a full glory of an implicitly parallelisable programming language, while still keeping its syntax mostly unchanged.
This document provides an overview of several built-in classes in Java, including Arrays, Math, wrapper classes, and BigInteger. It discusses the key methods and functionality of each class. The Arrays class contains static methods for common array operations like sorting and searching. The Math class contains commonly used mathematical functions that operate on primitive types. Wrapper classes "wrap" the primitive types in object classes. BigInteger provides operations for very large integers.
Introduction to Functional Programming with Scalapramode_ce
The document provides an introduction to functional programming with Scala. It outlines the following topics that will be covered: learning Scala syntax and writing simple programs; important functional programming concepts like closures, higher-order functions, purity, lazy evaluation, currying, tail calls, immutability, and type inference; and understanding the functional programming paradigm through Scala. It also provides some background information on Scala and examples of Scala code demonstrating various concepts.
Category theory concepts such as objects, arrows, and composition directly map to concepts in Scala. Objects represent types, arrows represent functions between types, and composition represents function composition. Scala examples demonstrate how category theory diagrams commute, with projection functions mapping to tuple accessors. Thinking in terms of interfaces and duality enriches both category theory and programming language concepts. Learning category theory provides a uniform way to reason about programming language structures and properties of data types.
Principles of functional progrmming in scalaehsoon
a short outline on necessity of functional programming and principles of functional programming in Scala.
In the article some keyword are used but not explained (to keep the article short and simple), the interested reader can look them up in internet.
The document provides an introduction and overview of Scala concepts. In 3 sentences:
Scala is an object-oriented and functional language that runs on the Java Virtual Machine. It combines object-oriented and functional programming which allows for modularity, extensibility, and composition. The document discusses Scala concepts like expressions, types, values, classes, traits, objects, pattern matching and more to build a fundamental understanding of how Scala programs work.
The document is a slide presentation on Scala that provides an introduction to the language in 90 minutes or less. It covers Scala basics like being object oriented and functional, static typing, compilation to JVM bytecode, and interoperability with Java. It also discusses Scala tools, its use in open source projects and industry, recommended books, and jobs involving Scala. Code examples are provided to demonstrate Hello World programs, variables, methods, conditionals, sequences, and closures in Scala.
The document provides an introduction to Akka, a toolkit for building concurrent, distributed, and reactive applications on the JVM. It discusses the key principles of reactive systems - being message-driven, elastic, resilient, and responsive. Akka uses the actor model of concurrency where applications are composed of independent message-processing actors. The document then provides steps to create a new Akka application and define a simple robot actor called AkkaBot to demonstrate how actors work by responding to messages.
Akka is a toolkit for building highly concurrent, distributed, and fault-tolerant applications on the JVM. It provides actors as the core abstraction for developing such applications, with actors encapsulating state and behavior and communicating asynchronously by message passing. Akka applications are built around message-driven actors that can send and receive messages, and whose state changes are confined within the actor model. This makes Akka applications inherently scalable, fault-tolerant and self-healing.
Scala Intro training @ Lohika, Odessa, UA.
This is a basic Scala Programming Language overview intended to evangelize the language among any-language programmers.
Some notes about programming in Scala: it covers Scala syntax and semantics, programming techniques, idioms, patterns. Many Scala features are introduced, from basic to intermediate and advanced. These are not introductory notes, but they assume a working knowledge with some other programming language (Java, C#, C++), object-oriented programming (OOP) concepts, and functional programming (FP) concepts.
This document provides an introduction to the Scala programming language. It begins with an overview of Scala's motivation and history. It then covers the basics of Scala including simple data structures, loops, objects, types and generics. More advanced topics such as traits, mixins, implicit conversions and sealed classes are also discussed. The document concludes with references for further reading.
This document provides an overview of Scala fundamentals including:
- Scala is a programming language for the JVM that supports both object-oriented and functional paradigms.
- It defines variables, values, lazy values, functions, types, classes, objects, traits, and higher-order functions.
- Classes can extend other classes and traits, allowing for multiple inheritance. Objects are used as singletons.
- Functional concepts like immutability, anonymous functions, and higher-order functions are supported.
The document summarizes the agenda and content of a Scala training workshop. The agenda includes functions and evaluations, higher order functions, data and abstraction, and exercises. Key points from the document include:
- Functions can be defined conditionally and with value definitions. Blocks allow grouping of definitions and expressions. Tail recursion optimizes recursion by reusing the call stack.
- Higher order functions allow functions to be passed as parameters or returned as results. Currying transforms functions that take multiple parameters into chains of functions that each take a single parameter.
- Classes define hierarchies and traits provide flexibility for code reuse like interfaces while abstract classes are used for base classes requiring constructor arguments.
- Exercises include implementing
Short (45 min) version of my 'Pragmatic Real-World Scala' talk. Discussing patterns and idioms discovered during 1.5 years of building a production system for finance; portfolio management and simulation.
Martin Odersky discusses the past, present, and future of Scala over the past 5 years and next 5 years. Key points include:
- Scala has grown significantly in usage and community over the past 6 years since its first release.
- Scala 2.8 will include improvements like new collections, package objects, named/default parameters, and better tool support.
- Over the next 5 years, Scala will focus on improving concurrency and parallelism through better abstractions, analyses, and static typing support.
Java 8 introduces lambda expressions and default interface methods (also known as virtual extension methods) which allow adding new functionality to existing interfaces without breaking backwards compatibility. While this helps add lambda support to existing Java collections, it has limitations compared to Scala's approach using traits, which allow true multiple inheritance of both behavior and state in a typesafe manner. Scala also introduced the "pimp my library" pattern using implicits which allows extending existing classes with new methods, providing more flexibility for library evolution than Java 8's virtual extension methods.
Scala Test allows testing of Scala and Java code. It integrates with tools like JUnit, TestNG, Ant, and Maven. Scala Test is customizable and uses traits to define different styles of testing, including Suite for defining test classes and methods, FunSuite for functional tests, Spec for behavior-driven development, and FeatureSpec for integration and acceptance tests.
The great attractiveness of purely functional languages is their ability to depart from sequential order of computation. Theoretically, it enables two important features of the compiler:
1) The ability to reorder computation flow, making the program implicitly parallelisable. Modern imperative language compilers, even using careful synchronization of concurrent code, still generate huge chunks of sequential instructions that need to be executed on a single processor core; a purely functional language compilers can dispatch very small chunks to many (hundreds and thousands) of cores, carefully eliminating as many execution path dependencies as possible.
2) As the compiler formalizes different types of side effects, it can detect a whole new class of program errors at compile time, including resource acquisition and releasing problems, concurrent access to shared resources, many types of deadlocks etc. It is not yet a full-fledged program verification, but it is a big step in that direction.
Scala is a semi-imperative language with strong support for functional programming and rich type system. One can isolate the purely functional core of the language which can be put on the firm mathematical foundation of dependent type theories. We argue that it is possible to treat Scala code as it's written by now as an implicit do-notation which can be then reduced to a purely functional core by means of recently introduced Scala macros. The formalism of arrows and applicative contexts can bring Scala to a full glory of an implicitly parallelisable programming language, while still keeping its syntax mostly unchanged.
This document provides an overview of several built-in classes in Java, including Arrays, Math, wrapper classes, and BigInteger. It discusses the key methods and functionality of each class. The Arrays class contains static methods for common array operations like sorting and searching. The Math class contains commonly used mathematical functions that operate on primitive types. Wrapper classes "wrap" the primitive types in object classes. BigInteger provides operations for very large integers.
Introduction to Functional Programming with Scalapramode_ce
The document provides an introduction to functional programming with Scala. It outlines the following topics that will be covered: learning Scala syntax and writing simple programs; important functional programming concepts like closures, higher-order functions, purity, lazy evaluation, currying, tail calls, immutability, and type inference; and understanding the functional programming paradigm through Scala. It also provides some background information on Scala and examples of Scala code demonstrating various concepts.
Category theory concepts such as objects, arrows, and composition directly map to concepts in Scala. Objects represent types, arrows represent functions between types, and composition represents function composition. Scala examples demonstrate how category theory diagrams commute, with projection functions mapping to tuple accessors. Thinking in terms of interfaces and duality enriches both category theory and programming language concepts. Learning category theory provides a uniform way to reason about programming language structures and properties of data types.
Principles of functional progrmming in scalaehsoon
a short outline on necessity of functional programming and principles of functional programming in Scala.
In the article some keyword are used but not explained (to keep the article short and simple), the interested reader can look them up in internet.
The document provides an introduction and overview of Scala concepts. In 3 sentences:
Scala is an object-oriented and functional language that runs on the Java Virtual Machine. It combines object-oriented and functional programming which allows for modularity, extensibility, and composition. The document discusses Scala concepts like expressions, types, values, classes, traits, objects, pattern matching and more to build a fundamental understanding of how Scala programs work.
The document is a slide presentation on Scala that provides an introduction to the language in 90 minutes or less. It covers Scala basics like being object oriented and functional, static typing, compilation to JVM bytecode, and interoperability with Java. It also discusses Scala tools, its use in open source projects and industry, recommended books, and jobs involving Scala. Code examples are provided to demonstrate Hello World programs, variables, methods, conditionals, sequences, and closures in Scala.
The document provides an introduction to Akka, a toolkit for building concurrent, distributed, and reactive applications on the JVM. It discusses the key principles of reactive systems - being message-driven, elastic, resilient, and responsive. Akka uses the actor model of concurrency where applications are composed of independent message-processing actors. The document then provides steps to create a new Akka application and define a simple robot actor called AkkaBot to demonstrate how actors work by responding to messages.
Akka is a toolkit for building highly concurrent, distributed, and fault-tolerant applications on the JVM. It provides actors as the core abstraction for developing such applications, with actors encapsulating state and behavior and communicating asynchronously by message passing. Akka applications are built around message-driven actors that can send and receive messages, and whose state changes are confined within the actor model. This makes Akka applications inherently scalable, fault-tolerant and self-healing.
Akka 2.0 is a toolkit for building highly concurrent, distributed, and fault-tolerant applications on the JVM. It provides actors as the core abstraction for concurrency and distribution. Actors encapsulate state and behavior and communicate asynchronously by message passing. Akka provides elasticity so that new messages can be processed while an actor is busy. It also includes features for fault tolerance using a "let it crash" model and transparent distribution through routing.
New features in Akka 2.0
Akka is a right abstraction with actors for concurrent, fault-tolerant and scalable applicationsFor Fault-Tolerance uses “let it crash” model abstraction for transparent distribution for the load.
Akka provides tools for building concurrent, scalable and fault-tolerant systems using the actor model. The key tools provided by Akka include actors for concurrency, agents for shared state, dispatchers for work distribution, and supervision hierarchies for fault handling. Akka actors simplify concurrency through message passing and isolation, and provide tools for scaling and distributing actors across nodes for increased throughput and fault tolerance.
- Akka is a great fit for building scalable applications on Heroku due to its "let it crash" philosophy and ability to easily scale out by adding more dynos. Within each dyno, Akka actors can be used to build highly concurrent and resilient applications.
- While remoting and clustering between dynos is not supported due to Heroku's HTTP-only architecture, Akka actors work well within individual dynos to handle requests and background jobs.
- A simple Akka application can be deployed to Heroku with no code changes - Akka will automatically scale out by creating actor instances on each dyno. The talk
A short intro to reactive systems, Scala, Akka and the Play Framework, with a Twitter based live demonstration and performance meters. Find the sample code at https://github.com/kjozsa/reactive2
Akka is a event driven, asynchronous, distributed framework which help in doing asyc event handling. Akka is reactive which gives him power to handle faults, become responsive, elastic.
Орхан Гасимов: "Reactive Applications in Java with Akka"Anna Shymchenko
This document provides an overview of reactive applications in Java using Akka. It discusses the reactive manifesto which outlines principles of responsive, resilient, elastic and message-driven systems. The actor model and Akka framework are introduced as ways to build such reactive systems. Key concepts covered include actors, message passing, concurrency vs parallelism. Akka features for scaling systems through dispatchers, mailboxes and routers are described. Other Akka modules for futures, agents, remote communication and more are also listed.
The document provides an introduction to Akka, a toolkit for building highly concurrent, distributed, and resilient message-driven applications using the actor model on the JVM, describing how Akka implements the actor model with additional features and modules for clustering, remoting, streams, and more.
The document discusses the actor model and Akka framework for building concurrent and distributed applications. It introduces some challenges of multi-threaded programming like non-determinism and shared mutable state. The actor model addresses these issues by representing entities as isolated actors that communicate asynchronously via message passing without shared state. Akka is an implementation of the actor model on the JVM that makes building fault-tolerant distributed systems easier. Key aspects covered include defining actors, routing messages, fault tolerance, and building remote actors for distribution. A Twitter-like messaging service is presented as a case study of how to structure such an application using Akka actors.
This document discusses using reactive programming with Scala and Akka to build distributed, concurrent systems. It describes using the actor model and message passing between actors to develop scalable and resilient applications. Key points covered include using actors to build a web scraping system, handling failures through supervision strategies, and testing actor systems.
Networks and Types - the Future of Akka @ ScalaDays NYC 2018Konrad Malawski
A look into the upcoming soon-to-be-stable typed Actor APIs in Akka. Shown at Scala Days NYC 2018, while Akka 2.5.13 was out. Looking at what will become the stable Akka Typed.
This document summarizes a presentation about scaling web applications with Akka. It discusses how Akka uses an actor model of computation with message passing between lightweight processes to enable safe concurrency. Key features of Akka that help with scaling include fault tolerance through supervision, flexible dispatch strategies to leverage multiple cores, and support for NoSQL databases through pluggable storage backends. The presentation provides code examples of implementing actors in Akka and other frameworks and concludes by taking questions about Akka.
During the talk, we will build a simple web app using Lift and then introduce Akka ( http://akkasource.org) to help scale it. Specifically, we will demonstrate Remote Actors, "Let it crash" fail over, and Dispatcher. Other Scala oriented tools we will use include sbt and ENSIME mode for emacs.
Multi-threading in the modern era: Vertx Akka and QuasarGal Marder
Everybody wants scalable systems. However, writing non-blocking applications in Java is not an easy task. In this session, we'll go over 3 different frameworks for managing multi-treading and concurrency support (Akka, Vertx and Quasar).
My talk at Bangalore Java Users Group. It was meant developers who want to get them started on Scala. This talk objectives was to get started on creating a project in Scala, write some code using collections and test it using ScalaTest.
- FitNesse is an open-source automated testing framework that allows developers, testers, and customers to collaborate on software testing by writing tests in a wiki format.
- Tests in FitNesse wiki format call custom fixtures that act as a bridge between the wiki pages and the system under test. Fixtures can be written in many programming languages including Scala.
- To write a FitNesse wiki test, tables are used with inputs in even columns and method names in odd columns to call methods defined in fixtures, allowing tests to be written in a domain-specific language format.
The document discusses various data structures in Scala including queues and binary search trees. It describes functional queues in Scala as immutable data structures with head, tail, and enqueue operations. It also covers different implementations of queues and optimizations. For binary search trees, it explains the binary search tree property, provides a Tree class representation in Scala, and algorithms for in-order, pre-order, and post-order tree traversals along with their Scala implementations.
Category theory concepts such as objects, arrows, and composition map nicely to structures in Scala. Functions in Scala represent arrows between types. Composition allows combining functions. Category theory diagrams illustrate relationships between types and functions through commutative diagrams. For example, product types in category theory correspond to tuples in Scala, with projection functions representing the arrows. Learning category theory provides insights into abstraction and mathematical properties underlying programming concepts.
Scala Test allows testing of Scala and Java code. It integrates with tools like JUnit, TestNG, Ant, and Maven. Scala Test features different styles of testing like Behavior Driven Design and provides traits for organizing tests into Suites, Specs, and FeatureSpecs. Tests define expected behavior through describe and it clauses then verify results through assertions.
Scala collections provide a uniform approach to working with data structures. The core abstractions are Traversable and Iterable, which define common operations like map and foreach. Concrete implementations include lists, sets, and maps. Collections aim to be object-oriented, generic, and optionally persistent or immutable. The uniform return type principle ensures operations return collections of the same type. Key features are higher-order functions, pattern matching, and treating all data types like collections.
This presentation was presented at OSS camp in New Delhi. It deals with the basics of Scala language and how we can use it to build scalable Applications
Prediction of Electrical Energy Efficiency Using Information on Consumer's Ac...PriyankaKilaniya
Energy efficiency has been important since the latter part of the last century. The main object of this survey is to determine the energy efficiency knowledge among consumers. Two separate districts in Bangladesh are selected to conduct the survey on households and showrooms about the energy and seller also. The survey uses the data to find some regression equations from which it is easy to predict energy efficiency knowledge. The data is analyzed and calculated based on five important criteria. The initial target was to find some factors that help predict a person's energy efficiency knowledge. From the survey, it is found that the energy efficiency awareness among the people of our country is very low. Relationships between household energy use behaviors are estimated using a unique dataset of about 40 households and 20 showrooms in Bangladesh's Chapainawabganj and Bagerhat districts. Knowledge of energy consumption and energy efficiency technology options is found to be associated with household use of energy conservation practices. Household characteristics also influence household energy use behavior. Younger household cohorts are more likely to adopt energy-efficient technologies and energy conservation practices and place primary importance on energy saving for environmental reasons. Education also influences attitudes toward energy conservation in Bangladesh. Low-education households indicate they primarily save electricity for the environment while high-education households indicate they are motivated by environmental concerns.
Gas agency management system project report.pdfKamal Acharya
The project entitled "Gas Agency" is done to make the manual process easier by making it a computerized system for billing and maintaining stock. The Gas Agencies get the order request through phone calls or by personal from their customers and deliver the gas cylinders to their address based on their demand and previous delivery date. This process is made computerized and the customer's name, address and stock details are stored in a database. Based on this the billing for a customer is made simple and easier, since a customer order for gas can be accepted only after completing a certain period from the previous delivery. This can be calculated and billed easily through this. There are two types of delivery like domestic purpose use delivery and commercial purpose use delivery. The bill rate and capacity differs for both. This can be easily maintained and charged accordingly.
Software Engineering and Project Management - Introduction, Modeling Concepts...Prakhyath Rai
Introduction, Modeling Concepts and Class Modeling: What is Object orientation? What is OO development? OO Themes; Evidence for usefulness of OO development; OO modeling history. Modeling
as Design technique: Modeling, abstraction, The Three models. Class Modeling: Object and Class Concept, Link and associations concepts, Generalization and Inheritance, A sample class model, Navigation of class models, and UML diagrams
Building the Analysis Models: Requirement Analysis, Analysis Model Approaches, Data modeling Concepts, Object Oriented Analysis, Scenario-Based Modeling, Flow-Oriented Modeling, class Based Modeling, Creating a Behavioral Model.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELijaia
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
AI for Legal Research with applications, toolsmahaffeycheryld
AI applications in legal research include rapid document analysis, case law review, and statute interpretation. AI-powered tools can sift through vast legal databases to find relevant precedents and citations, enhancing research accuracy and speed. They assist in legal writing by drafting and proofreading documents. Predictive analytics help foresee case outcomes based on historical data, aiding in strategic decision-making. AI also automates routine tasks like contract review and due diligence, freeing up lawyers to focus on complex legal issues. These applications make legal research more efficient, cost-effective, and accessible.
Rainfall intensity duration frequency curve statistical analysis and modeling...bijceesjournal
Using data from 41 years in Patna’ India’ the study’s goal is to analyze the trends of how often it rains on a weekly, seasonal, and annual basis (1981−2020). First, utilizing the intensity-duration-frequency (IDF) curve and the relationship by statistically analyzing rainfall’ the historical rainfall data set for Patna’ India’ during a 41 year period (1981−2020), was evaluated for its quality. Changes in the hydrologic cycle as a result of increased greenhouse gas emissions are expected to induce variations in the intensity, length, and frequency of precipitation events. One strategy to lessen vulnerability is to quantify probable changes and adapt to them. Techniques such as log-normal, normal, and Gumbel are used (EV-I). Distributions were created with durations of 1, 2, 3, 6, and 24 h and return times of 2, 5, 10, 25, and 100 years. There were also mathematical correlations discovered between rainfall and recurrence interval.
Findings: Based on findings, the Gumbel approach produced the highest intensity values, whereas the other approaches produced values that were close to each other. The data indicates that 461.9 mm of rain fell during the monsoon season’s 301st week. However, it was found that the 29th week had the greatest average rainfall, 92.6 mm. With 952.6 mm on average, the monsoon season saw the highest rainfall. Calculations revealed that the yearly rainfall averaged 1171.1 mm. Using Weibull’s method, the study was subsequently expanded to examine rainfall distribution at different recurrence intervals of 2, 5, 10, and 25 years. Rainfall and recurrence interval mathematical correlations were also developed. Further regression analysis revealed that short wave irrigation, wind direction, wind speed, pressure, relative humidity, and temperature all had a substantial influence on rainfall.
Originality and value: The results of the rainfall IDF curves can provide useful information to policymakers in making appropriate decisions in managing and minimizing floods in the study area.
Use PyCharm for remote debugging of WSL on a Windo cf5c162d672e4e58b4dde5d797...shadow0702a
This document serves as a comprehensive step-by-step guide on how to effectively use PyCharm for remote debugging of the Windows Subsystem for Linux (WSL) on a local Windows machine. It meticulously outlines several critical steps in the process, starting with the crucial task of enabling permissions, followed by the installation and configuration of WSL.
The guide then proceeds to explain how to set up the SSH service within the WSL environment, an integral part of the process. Alongside this, it also provides detailed instructions on how to modify the inbound rules of the Windows firewall to facilitate the process, ensuring that there are no connectivity issues that could potentially hinder the debugging process.
The document further emphasizes on the importance of checking the connection between the Windows and WSL environments, providing instructions on how to ensure that the connection is optimal and ready for remote debugging.
It also offers an in-depth guide on how to configure the WSL interpreter and files within the PyCharm environment. This is essential for ensuring that the debugging process is set up correctly and that the program can be run effectively within the WSL terminal.
Additionally, the document provides guidance on how to set up breakpoints for debugging, a fundamental aspect of the debugging process which allows the developer to stop the execution of their code at certain points and inspect their program at those stages.
Finally, the document concludes by providing a link to a reference blog. This blog offers additional information and guidance on configuring the remote Python interpreter in PyCharm, providing the reader with a well-rounded understanding of the process.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
Null Bangalore | Pentesters Approach to AWS IAMDivyanshu
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
3. History
Philipp Haller worked on Actor model and released it in Scala 2.1.7 in July 2006
Jonas Boner created Akka to bring highly concurrent, event driven to JVM
Inspired by Erlang Actors, Jonas Boner began working on Akka early 2009
Jonas Boner as part of Scalable Solutions releases Akka version 0.5 in January 2010
Akka is now part of Typesafe Platform together with Play framework and Scala language
5. Scala Basics
Scala is a JVM based strongly typed language
Scala is hybrid: Functional as well as Object-Oriented
Scala is compatible with Java
Scala has support for currying, pattern matching, ADT’s, lazy evaluation, tail recursion etc
Scala is compiled to Java byte-codes and run on Java Virtual Machine
6. Scala Compared To Java
Scala adds Scala removes
pure object system static members
operator overloading primitive types
closures break and continue
mixin composition with traits special treatment of interfaces
existential types wildcards
abstract types raw types
pattern matching enums
7. Scala Cheat Sheet(1) definitions
Scala method definitions
!
def fun(x: Int) = {
result
}
!
def fun = result
!
Scala variable definitions
!
var x: Int = expression
val x: String = expression
Java method definitions
!
Int fun(int x) {
return result
}
!
(no parameterless methods)
!
java variable definitions
!
Int x = expression
final String x = expression
8. Scala Cheat Sheet(2) definitions
Scala class and object
!
class Sample(x: Int, p: Int) {
def instMeth(y: Int): Int = x + y
}
!
object Sample {
def staticMeth(x: Int, y: Int): Int = x * y
}
!
!
!
!
!
!
!
!
!
Java class
!
class Sample {
private final int x;
public final int p;
!
Sample(int x, int p) {
this.x = x;
this.p = p;
}
!
int instMeth(int y) {
return x + y;
}
!
static int staticMeth(int x, int y) {
return x *y;
}
}
9. Scala: Pattern Matching
All that is required to add a case keyword to each class that is to be pattern matchable
!
Pattern match also returns a value
!
Similar to switch except that Scala compares objects as expressions. Only one matcher
is
executed at a time.
!
case class Employee(name: String)
val employee = Employee(“john”)
employee match {
case Employee(“john”) => “Hello John!”
case _ => “Hello there!”
}
!
res0: String = Hello John
10. Akka
The name comes from a goddess in Sami mythology that
represented all wisdom and beauty in the world
It is also the name of a beautiful mountain in Laponia in north
part of Sweden
Incidentally in India it means sister in Telugu!!
11. The Problem
It is way to hard to build
=> correct highly concurrent systems
=> Truly scalable systems
=> self-healing, fault-tolerant systems
12. What is Akka?
Right abstraction with actors for concurrent, fault-tolerant and
scalable applications
For Fault-Tolerance uses “Let It Crash” model
Abstraction for transparent distribution of load
We can Scale In and Scale Out
13. Right Abstraction
Never think in terms of shared state, state visibility, threads, locks,
concurrent collections, thread notification etc
Low level concurrency becomes Simple Workflow - we only think
in terms of message flows in system
We get high CPU utilisation, low latency, high throughput and
scalability - for free as part of this model
Proven and superior model for detecting and recovering from
errors
14. Actor Model
Actor Model (1973): Carl Hewitt’s definition
!
The fundamental unit of computation that embodies:
- Processing
- Storage
- Communication
!
Three Axioms
- Create new Actors
- Send messages to Actor it knows
- Designate how it should handle the next message it receives
15. Introducing Actors
Actor is an entity encapsulating behaviour, state and a mailbox
to receive messages
For a message received by Actor a thread is allocated to it
Then behaviour is applied to the message and potentially some
state is changed or messages are passed to other Actors
16. Introducing Actors..
There is elasticity between message processing and addition of
new messages.
New messages can be added while Actor execution is
happening.
When processing of messages is completed; the thread is
deallocated from the Actor. It can again be reallocated a thread
at a later time.
21. Create Actor System
ActorSystem is a heavy-weight structure that will allocate 1…n threads. So,create one
per logical application
!
Top level actors are created from an ActorSystem
!
This is so because first Actor is the child from ActorSystem. If we create another Actor
from this first Actor: then second Actor will be child of the first Actor
!
We therefore get a tree like structure and hence get automatic supervision
!
val system = ActorSystem("myfirstApp")
22. My First Actor
import akka.actor._
!
class MyFirstActor extends Actor {
def receive = {
case msg: String => println(msg)
case _ => println("default")
}
}
you extend an Actor
!
receive method reads the message from mailbox
!
receive is a partially applied function
!
pattern match is applied on the message
23. Create Actor
package com.meetu.akka
!
import akka.actor._
!
object HelloWorldAkkaApplication extends App {
val system = ActorSystem("myfirstApp")
val myFirstActor: ActorRef = system.actorOf(Props[MyFirstActor])
……..
}
Create an Actor System
!
create actor from Actor System using actorOf method
!
the actorOf method returns an ActorRef instead of Actor class type
24. Create Actor
when actorOf is called path is reserved
!
A random UID is assigned to incarnation
!
Actor instance is created
!
preStart is called on instance
25. Send Message
package com.meetu.akka
!
import akka.actor._
!
object HelloWorldAkkaApplication extends App {
val system = ActorSystem("myfirstApp")
val myFirstActor: ActorRef = system.actorOf(Props[MyFirstActor])
myFirstActor ! "Hello World"
myFirstActor.!("Hello World")
}
Scala version has a method named “!”
!
This is asynchronous thread of execution continues after sending
!
It accepts Any as a parameter
!
In Scala we can skip a dot with a space: So it feels natural to use
26. Ask Pattern
package com.meetu.akka
!
import akka.actor._
import akka.pattern.ask
import akka.util.Timeout
import scala.concurrent.duration._
import scala.concurrent.Await
import scala.concurrent.Future
!
object AskPatternApp extends App {
implicit val timeout = Timeout(500 millis)
val system = ActorSystem("BlockingApp")
val echoActor = system.actorOf(Props[EchoActor])
!
val future: Future[Any] = echoActor ? "Hello"
val message = Await.result(future, timeout.duration).asInstanceOf[String]
!
println(message)
}
!
class EchoActor extends Actor {
def receive = {
case msg => sender ! msg
}
}
Ask pattern is blocking
!
Thread of execution waits till response is reached
27. Reply From Actor
import akka.actor.Actor
!
class LongWorkingActor extends Actor {
def receive = {
case number: Int =>
sender ! ("Hi I received the " + number)
}
}
Each Actor has been provided default sender
!
Use “!” method to send back the message
29. Round Robin Router
import akka.actor._
import akka.routing.RoundRobinPool
import akka.routing.Broadcast
!
object RouterApp extends App {
val system = ActorSystem("routerApp")
val router = system.actorOf(RoundRobinPool(5).props(Props[RouterWorkerActor]), "workers")
router ! Broadcast("Hello")
}
!
class RouterWorkerActor extends Actor {
def receive = {
case msg => println(s"Message: $msg received in ${self.path}")
}
}
A router sits on top of routees
!
When messages are sent to Router, Routees get messages in Round Robin
30. Failure: Typical Scenario
There is a single thread of control
!
If this Thread goes in failure we are doomed
!
We therefore do explicit error handling on this thread
!
Worse error do not propagate between threads. There is no way of knowing
that something failed
!
We therefore do defensive programming with:
• Error handling tangled with business logic
• Scattered all over code base
!
We can do better than this
31. Supervision
Supervise means manage another Actor failures
!
Error handling in Actors is handled by letting Actors monitor (supervise) each other
of failure
!
This means if Actor crashes a notification is sent to its supervisor (an Actor), who
can react to failure
!
This provides clean separation of processing and error handling
39. Supervise Actor
Every Actor exists in a Tree topology. Its parent provide
automatic supervision
!
Every Actor has a default Supervision strategy, which is
usually sufficient
!
supervision strategy can be overridden
!
We have either One for One strategy. Here only the
Actor that crashed is handled.
!
Other one is All For One strategy. Here all children are
restarted
40. Supervision Actor
class Supervisor extends Actor {
override val supervisorStrategy =
OneForOneStrategy(maxNrOfRetries = 10, withinTimeRange = 1 minute) {
case _: ArithmeticException => Resume
case _: NullPointerException => Restart
case _: IllegalArgumentException => Stop
case _: Exception => Escalate
}
!
def receive = {
case p: Props => sender ! context.actorOf(p)
}
}
41. Supervision: Child Actor
class Child extends Actor {
var state = 0
def receive = {
case ex: Exception => throw ex
case x: Int => state = x
case "get" => sender ! state
}
}
42. Supervision Application
object SupervisionExampleApp extends App {
implicit val timeout = Timeout(50000 milliseconds)
val system = ActorSystem("supervisionExample")
val supervisor = system.actorOf(Props[Supervisor], "supervisor")
val future = supervisor ? Props[Child]
val child = Await.result(future, timeout.duration).asInstanceOf[ActorRef]
child ! 42
println("Normal response " + Await.result(child ? "get", timeout.duration).asInstanceOf[Int])
child ! new ArithmeticException
println("Arithmetic Exception response " + Await.result(child ? "get", timeout.duration).asInstanceOf[Int])
child ! new NullPointerException
println("Null Pointer response " + Await.result(child ? "get", timeout.duration).asInstanceOf[Int])
}