Software Engineering, Artificial Intelligence, Net…

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Author : Meir Kalech
Genre : Computers

Summary : Software is an integral part of our lives today. Modern software systems are highly complex and often pose new challenges in different aspects of Software Engineering (SE).Artificial Intelligence (AI) is a growing field in computer science that has been proven effective in applying and developing AI techniques to address various SE challenges.This unique compendium covers applications of state-of-the-art AI techniques to the key areas of SE (design, development, debugging, testing, etc).All the materials presented are up-to-date. This reference text will benefit researchers, academics, professionals, and postgraduate students in AI, machine learning and software engineering.Related Link(s)

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Author : Roger Lee
Genre : Mathematics

Summary : The purpose of the 10th ACIS International Conference on Software Engineering Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD rd 2009), held in Daegu, Korea on May 27–29, 2009, the 3 International Workshop st on e-Activity (IWEA 2009) and the 1 International Workshop on Enterprise Architecture Challenges and Responses (WEACR 2009) is to aim at bringing together researchers and scientist, businessmen and entrepreneurs, teachers and students to discuss the numerous fields of computer science, and to share ideas and information in a meaningful way. Our conference officers selected the best 24 papers from those papers accepted for presentation at the conference in order to publish them in this volume. The papers were chosen based on review scores submitted by members of the program committee, and underwent further rounds of rigorous review. In chapter 1, Igor Crk and Chris Gniady propose a network-aware energy m- agement mechanism that provides a low-cost solution that can significantly reduce energy consumption in the entire system while maintaining responsiveness of local interactive workloads. Their dynamic mechanisms reduce the decision delay before the disk is spun-up, reduce the number of erroneous spin-ups in local wo- stations, decrease the network bandwidth, and reduce the energy consumption of individual drives. In chapter 2, Yoshihito Saito and Tokuro Matsuo describe a task allocation mechanism and its performance concerning with software developing. They run simulations and discuss the results in terms of effective strategies of task allocation.

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Author : Roger Lee
Genre : Technology & Engineering

Summary : The series "Studies in Computational Intelligence" (SCI) publishes new developments and advances in the various areas of computational intelligence – quickly and with a high quality. The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life science, as well as the methodologies behind them. The series contains monographs, lecture notes and edited volumes in computational intelligence spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automata, self-organizing systems, soft computing, fuzzy systems, and hybrid intelligent systems. Critical to both contributors and readers are the short publication time and world-wide distribution - this permits a rapid and broad dissemination of research results. The purpose of the first ACIS International Symposium on Software and Network Engineering held on December 19-20, 2012 on the Seoul National University campus, Seoul, Korea is to bring together scientist, engineers, computer users, students to share their experiences and exchange new ideas, and research results about all aspects (theory, applications and tools) of software & network engineering, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them The symposium organizers selected the best 12 papers from those papers accepted for presentation at the symposium in order to publish them in this volume. The papers were chosen based on review scores submitted by members of the program committee, and underwent further rigorous rounds of review. The symposium organizers selected the best 12 papers from those papers accepted for presentation at the symposium in order to publish them in this volume. The papers were chosen based on review scores submitted by members of the program committee, and underwent further rigorous rounds of review.

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Author : Roger Lee
Genre : Technology & Engineering

Summary : This edited book presents scientific results of the 24th ACIS International Winter Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD2022-Summer) which was held on December 7–9, 2022, at Taichung, Taiwan. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. The conference organizers selected the best papers from those papers accepted for presentation at the workshop. The papers were chosen based on review scores submitted by members of the program committee and underwent further rigorous rounds of review. From this second round of review, 15 of the most promising papers are then published in this Springer (SCI) book and not the conference proceedings.

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Author : Radek Silhavy
Genre :

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Author : Meziane, Farid
Genre : Computers

Summary : "This book provides an overview of useful techniques in artificial intelligence for future software development along with critical assessment for further advancement"--Provided by publisher.

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Author : Taghi M. Khoshgoftaar
Genre : Computers

Summary : The constantly evolving technological infrastructure of the modem world presents a great challenge of developing software systems with increasing size, complexity, and functionality. The software engineering field has seen changes and innovations to meet these and other continuously growing challenges by developing and implementing useful software engineering methodologies. Among the more recent advances are those made in the context of software portability, formal verification· techniques, software measurement, and software reuse. However, despite the introduction of some important and useful paradigms in the software engineering discipline, their technological transfer on a larger scale has been extremely gradual and limited. For example, many software development organizations may not have a well-defined software assurance team, which can be considered as a key ingredient in the development of a high-quality and dependable software product. Recently, the software engineering field has observed an increased integration or fusion with the computational intelligence (Cl) field, which is comprised of primarily the mature technologies of fuzzy logic, neural networks, genetic algorithms, genetic programming, and rough sets. Hybrid systems that combine two or more of these individual technologies are also categorized under the Cl umbrella. Software engineering is unlike the other well-founded engineering disciplines, primarily due to its human component (designers, developers, testers, etc. ) factor. The highly non-mechanical and intuitive nature of the human factor characterizes many of the problems associated with software engineering, including those observed in development effort estimation, software quality and reliability prediction, software design, and software testing.

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Author : Jarred Capellman
Genre : Computers

Summary : Create, train, and evaluate various machine learning models such as regression, classification, and clustering using ML.NET, Entity Framework, and ASP.NET Core Key FeaturesGet well-versed with the ML.NET framework and its components and APIs using practical examplesLearn how to build, train, and evaluate popular machine learning algorithms with ML.NET offeringsExtend your existing machine learning models by integrating with TensorFlow and other librariesBook Description Machine learning (ML) is widely used in many industries such as science, healthcare, and research and its popularity is only growing. In March 2018, Microsoft introduced ML.NET to help .NET enthusiasts in working with ML. With this book, you’ll explore how to build ML.NET applications with the various ML models available using C# code. The book starts by giving you an overview of ML and the types of ML algorithms used, along with covering what ML.NET is and why you need it to build ML apps. You’ll then explore the ML.NET framework, its components, and APIs. The book will serve as a practical guide to helping you build smart apps using the ML.NET library. You’ll gradually become well versed in how to implement ML algorithms such as regression, classification, and clustering with real-world examples and datasets. Each chapter will cover the practical implementation, showing you how to implement ML within .NET applications. You’ll also learn to integrate TensorFlow in ML.NET applications. Later you’ll discover how to store the regression model housing price prediction result to the database and display the real-time predicted results from the database on your web application using ASP.NET Core Blazor and SignalR. By the end of this book, you’ll have learned how to confidently perform basic to advanced-level machine learning tasks in ML.NET. What you will learnUnderstand the framework, components, and APIs of ML.NET using C#Develop regression models using ML.NET for employee attrition and file classificationEvaluate classification models for sentiment prediction of restaurant reviewsWork with clustering models for file type classificationsUse anomaly detection to find anomalies in both network traffic and login historyWork with ASP.NET Core Blazor to create an ML.NET enabled web applicationIntegrate pre-trained TensorFlow and ONNX models in a WPF ML.NET application for image classification and object detectionWho this book is for If you are a .NET developer who wants to implement machine learning models using ML.NET, then this book is for you. This book will also be beneficial for data scientists and machine learning developers who are looking for effective tools to implement various machine learning algorithms. A basic understanding of C# or .NET is mandatory to grasp the concepts covered in this book effectively.

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Author : Quang A. Dang
Genre : Technology & Engineering

Summary : This book includes the extended and revised versions of a set of selected papers from the First NAFOSTED Conference on Information and Computer Science (NICS’2014), held at Le Quy Don Technical Academy, Hanoi, Vietnam from 13/Mar./2014 to 14/Mar./2014. The conference was co-organized by The National Foundation for Science and Technology Development (NAFOSTED) and Le Quy Don Technical Academy. The purpose of the NICS conference series is to promote scientific publications in the country and to provide a platform for high quality academic exchange among scientists in the fields of computer science, information and communication. The conference includes five tracks, namely “Computer Science”, “Artificial Intelligence”, “Network Systems”, “Software Engineering”, and “Information Systems”. The papers in this book are among the best contributions at NICS’2014 taken into account the quality of their presentation at the conference and the recommendation of the two experts in the extra round of independent review.

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Author : Derek Partridge
Genre : Computers

Summary :