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Agile processes in software engineering and extreme programming : XP 2022 workshops, Copenhagen, Denmark, June 13-17, 2022 and XP 2023 workshops, Amsterdam, the Netherlands, June 13-16, 2023 : revised selected papers
Book constitutes papers from the research workshops presented at XP 2022 and XP 2023, respectively the 23rd and 24th International Conferences on Agile Software Development, held on June 13-17, 2022 at the IT University of Copenhagen, Denmark and June 13-16, 2023 in Amsterdam, Netherlands.
Advancing Social Simulation: The First World Congress
Agent-based modeling and social simulation have emerged as both developments of and challenges to the social sciences. The developments include agent-based computational economics and investigations of theoretical sociological concepts using formal simulation techniques. Among the challenges are the development of qualitative modeling techniques, implementation of agent-based models to investigate phenomena for which conventional economic, social, and organizational models have no face validity, and the application of physical modeling techniques to social processes. Bringing together diverse approaches to social simulation and research agendas.
Advances in UAV detection, classification and tracking
Explores the latest techniques and advancements in unmanned aerial vehicle (UAV) detection, classification, and tracking. As UAV technology continues to evolve and become more accessible, there is a growing need for effective methods to detect, identify, and track these devices in various scenarios. This reprint provides a thorough overview of the state-of-the-art approaches for UAV detection, classification, and tracking, covering both theoretical and practical aspects.The reprint begins by introducing the basics of UAVs and their various applications, followed by a detailed overview of the challenges associated with UAV detection, classification, and tracking. The authors then present the latest techniques and algorithms used in the field, including machine-learning-based approaches, computer vision techniques, and sensor fusion techniques. The reprint also covers the challenges of real-world applications, such as dealing with occlusions, sensor noise, and environmental factors.
Advances in optical fiber communications
Given the increasing importance of a globally interconnected world, driven by modern digital services and the need for fast and reliable access to digital resources, communication networks are one of the key infrastructures in today’s society. In this scenario, fiber optics and optical devices play a leading role, as they allow for unprecedented growth in our capacity to cope with the ever-increasing traffic demand. Optical transmission solutions range from high-speed networks based on coherent detection and advanced modulation formats for long-haul-level communications, to networks still relying on traditional intensity modulation and direct detection receivers for short-reach communications, down to intra-data center scenarios.
Advances in Metaheuristics for Hard Optimization
The book gathers contributions related to the following topics: theoretical developments in metaheuristics; adaptation of discrete metaheuristics to continuous optimization; performance comparisons of metaheuristics; cooperative methods combining different approaches; parallel and distributed metaheuristics for multiobjective optimization; software implementations; and real-world applications.
Advances in Digital Forensics II
This book is the second volume in the anual series produced by the International Federation for Information Processing (IFIP) Working Group 11.9 on Digital Forensics, an international community of scientists, engineers and practitioners dedicated to advancing the state of the art of research and practice in digital forensics. The book contains a selection of twenty-five edited papers from the First Annual IFIP WG 11.9 Conference on Digital Forensics, held at the National Center for Forensic Science, Orlando, Florida, USA in the spring of 2006.
Advances in Computer and Information Sciences and Engineering
Advances in Computer and Information Sciences and Engineering includes a set of rigorously reviewed world-class manuscripts addressing and detailing state-of-the-art research projects in the areas of Computer Science, Software Engineering, Computer Engineering, and Systems Engineering and Sciences.
Advances in Artificial Economics : The Economy as a Complex Dynamic System
Perceiving the economy as a complex dynamic system, generates a need for new tools for its study. As a constructive simulation method, Agent-Based Computational Economics (ACE) has in recent years proven its strength and extensive applicability. Fields of study are widely spread within economics, with a cluster around financial markets. This book is based on communications given at AE’2006 (Aalborg, Denmark) – the second symposium on Artificial Economics, and covers both wellknown questions of economics, like the existence of market efficiency, as well as new questions raised by the new tools, for example questions related to networks of social interaction.
Advances and applications of DSmT for information fusion: Collected works ; Vol.3
One of the most comprehensive and flexible fusion theory based on belief functions. It can work in all fusion spaces: power set, hyper-power set, and super-power set, and has various fusion and conditioning rules that can be applied depending on each application. Some new generalized rules are introduced in this volume with codes for implementing some of them. For the qualitative fusion, the DSm Field and Linear Algebra of Refined Labels (FLARL) is proposed which can convert any numerical fusion rule to a qualitative fusion rule. When one needs to work on a refined frame of discernment, the refinement is done using Smarandache s algebraic codification. New interpretations and implementations of the fusion rules based on sampling techniques and referee functions are proposed, including the probabilistic proportional conflict redistribution rule.
Advances and applications of DSmT for information fusion ; Vol. 4
One of the most comprehensive and flexible fusion theory based on belief functions. It can work in all fusion spaces: power set, hyper-power set, and super-power set, and has various fusion and conditioning rules that can be applied depending on each application. Some new generalized rules are introduced in this volume with codes for implementing some of them. For the qualitative fusion, the DSm Field and Linear Algebra of Refined Labels (FLARL) is proposed which can convert any numerical fusion rule to a qualitative fusion rule. When one needs to work on a refined frame of discernment, the refinement is done using Smarandache s algebraic codification. New interpretations and implementations of the fusion rules based on sampling techniques and referee functions are proposed, including the probabilistic proportional conflict redistribution rule.
Advancement of Deep Learning and its Applications in Object Detection and Recognition
In just the past five years, deep learning has taken the world by surprise, driving rapid progress in fields as diverse as computer vision, natural language processing, automatic speech recognition, etc. This book presents an introduction to deep learning and various applications of deep learning such as recommendation systems, text recognition, diabetic retinopathy prediction of breast cancer, prediction of epilepsy, sentiment, fake news detection, software defect prediction and protein function prediction.
AdvancED Flash Interface Design
Flash allows users to create some amazing interactive interfaces to interact with rich Internet applications, e-learning systems, and simple web sites. In this book, two of the most talented Flash designers in the world will show you how to use them effectively to create breathtaking visuals for your Flash web sites. You'll also learn how to take advantage of Flash's powerful built-in vector-based drawing tools.
Advanced Decision Sciences Based on Deep Learning and Ensemble Learning Algorithms : A Practical Approach Using Python
Describes the deep learning models and ensemble approaches applied to decision-making problems. The authors have addressed the concepts of deep learning, convolutional neural networks, recurrent neural networks, and ensemble learning in a practical sense providing complete code and implementation for several real-world examples. The authors of this book teach the concepts of machine learning for undergraduate and graduate-level classes and have worked with Fortune 500 clients to formulate data analytics strategies and operationalise these strategies.
Advanced Autonomic Networking and Communication
This book presents a comprehensive reference of state-of-the-art efforts and early results in the area of autonomic networking and communication.
Advanced artificial intelligence models and its applications
The field of artificial intelligence (AI) has undergone enormous expansion since its inception in the mid-20th century, as demonstrated by its application across an array of engineering and scientific challenges. Particularly in the last decade, AI has witnessed a significant breakthrough with the advent of deep learning, which has facilitated the employment of various AI models across a multitude of domains. This reprint features ten papers accepted for publication in the Special Issue titled "Advanced Artificial Intelligence Models and Their Applications," published in the MDPI Mathematics journal. These papers explore numerous facets of advanced artificial intelligence models and their applications, covering areas such as cybersecurity, image classification, logistics optimization, automatic music generation, human capital investment, writer recognition, remote sensing image indexing, target tracking, and more.
Advanced .NET Remoting
Surpassing any white papers, specialist documents and other documentationthis book features in-depth coverage of the .NET Remoting Framework. The text is organized into three main parts, and this revised, second edition features 150 pages of entirely new material! Part one includes a guide to the 1.1 framework and its capabilities in real-world applications. Part two presents .NET remoting internals, and provides real-world code and development strategies. Finally, part three looks at futuristic remoting tools and their present implementation in Visual Studio .NET 2005. You will come to see how remoting procedures will change within the new IDE and revised framework.
Adobe® Acrobat® and PDF for Architecture, Engineering, and Construction
Adobe® Acrobat® and PDF for Architecture, Engineering, and Construction is designed to appeal to the engineering mind. The book is a practical guide focusing on the applications of PDF in the solution of "engineering" problems which may arise in a number of disciplines from architecture to construction. Using real-world examples, the authors follow a project from design through build and long-term maintenance. As the sample project evolves, suitable Acrobat® tools and techniques are identified and brought into play at each stage, showing readers how to personalize the context and processes to meet their own project development and management needs.
Ad-hoc Networks : Fundamental Properties and Network Topologies
This book clearly demonstrates how the Medium Access Control protocols impose a limit on the level of interference in ad-hoc networks. It has been shown that interference is upper bounded, and a new accurate method for the estimation of interference power statistics in ad-hoc and sensor networks is introduced here. Furthermore, this volume shows how multi-hop traffic affects the capacity of the network. In multi-hop and ad-hoc networks there is a trade-off between the network size and the maximum input bit rate possible per node. Large ad-hoc or sensor networks, consisting of thousands of nodes, can only support low bit-rate applications.
Adaptive Motion of Animals and Machines
Apparently, the ability of animals and robots to adapt in a real world cannot be explained or realized by one single function in a control system and mechanism. That is, adaptation in motion is induced at every level from the central nervous system to the musculoskeletal system.Thus,weorganized the International Symposium on Adaptive Motion in Animals and Machines (AMAM) forscientist sandengineersconcerned with adaptation on various level stobebrought together todiscussprinciplesateachleveland to investigate principles governing total systems.
Adaptive Learning of Polynomial Networks : Genetic Programming, Backpropagation and Bayesian Methods
This book provides theoretical and practical knowledge for develop ment of algorithms that infer linear and nonlinear models. It offers a methodology for inductive learning of polynomial neural network mod els from data. The design of such tools contributes to better statistical data modelling when addressing tasks from various areas like system identification, chaotic time-series prediction, financial forecasting and data mining. The main claim is that the model identification process involves several equally important steps: finding the model structure, estimating the model weight parameters, and tuning these weights with respect to the adopted assumptions about the underlying data distrib ution. When the learning process is organized according to these steps, performed together one after the other or separately, one may expect to discover models that generalize well.
