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Designing machine learning systems : An iterative process for production-ready applications
Machine learning systems are both complex and unique. Each design decision--such as how to process and create training data, which features to use, how often to retrain models, and what to monitor--in the context of how it can help your system as a whole achieve its objectives. The iterative framework in this book uses actual case studies backed by ample references. The book will help you tackle scenarios such as: Engineering data and choosing the right metrics to solve a business problem Automating the process for continually developing, evaluating, deploying, and updating models Developing a monitoring system to quickly detect and address issues your models might encounter in production Architecting an ML platform that serves across use cases Developing responsible ML systems
Deep neural networks and data for automated driving : robustness, uncertainty quantification, and insights towards safety
Environment perception for highly automated driving heavily employs deep neural networks, facing many challenges. How much data do we need for training and testing? How to use synthetic data to save labeling costs for training? How do we increase robustness and decrease memory usage? For inevitably poor conditions: How do we know that the network is uncertain about its decisions? Can we understand a bit more about what actually happens inside neural networks? This leads to a very practical problem particularly for DNNs employed in automated driving: What are useful validation techniques and how about safety? This book unites the views from both academia and industry, where computer vision and machine learning meet environment perception for highly automated driving. Naturally, aspects of data, robustness, uncertainty quantification, and, last but not least, safety are at the core of it. This book is unique: In its first part, an extended survey of all the relevant aspects is provided. The second part contains the detailed technical elaboration of the various questions mentioned above.
Cyber Security : Critical Infrastructure Protection
Focus on critical infrastructure protection. The chapters present detailed analysis of the issues and challenges in cyberspace and provide novel solutions in various aspects. The first part of the book focus on digital society, addressing critical infrastructure and different forms of the digitalization, strategic focus on cyber security, legal aspects on cyber security, citizen in digital society, and cyber security training. The second part focus on the critical infrastructure protection in different areas of the critical infrastructure. The chapters cover the cybersecurity situation awareness, aviation and air traffic control, cyber security in smart societies and cities, cyber security in smart buildings, maritime cyber security, cyber security in energy systems, and cyber security in healthcare. The third part presents the impact of new technologies upon cyber capability building as well as new challenges brought about by new technologies. These new technologies are among others are quantum technology, firmware and wireless technologies, malware analysis, virtualization.
Coordination, organizations, institutions, and norms in agent systems II ; AAMAS 2006 and ECAI 2006 International Workshops, COIN 2006 Hakodate, Japan, May 9, 2006 Riva del Garda, Italy, August 28, 2006, Revised Selected Papers
In recent years, social and organizational aspects of agency have become major research topics in MAS. Recent applications of MAS on Web services, grid c- puting and ubiquitous computing highlight the need for using these aspects in order to ensure social order within such environments. Openness, heterogeneity, and scalability of MAS, in turn, pose new demands on traditional MAS int- action models and bring forward the need to look into the environment where agents interact and at di?erent ways of constraining or regulating interactions.it provide theoretically demanding and interdisciplinary research questions at d- ferent levels of abstraction.
Concise Guide to Quantum Computing : Algorithms, Exercises, and Implementations
This textbook is intended for practical, laboratory sessions associated with the course of quantum computing and quantum algorithms, as well as for self-study. It contains basic theoretical concepts and methods for solving basic types of problems and gives an overview of basic qubit operations, entangled states, quantum circuits, implementing functions, quantum Fourier transform, phase estimation, etc. The book serves as a basis for the application of new information technologies in education and corporate technical training: theoretical material and examples of practical problems, as well as exercises with, in most cases, detailed solutions, have relation to information technologies. A large number of detailed examples serve to better develop professional competencies in computer science.
Computer Graphics for Artists : An Introduction
Far too often artists, even professionals, lack a basic understanding of the principles of computer graphics resulting in inefficiency and a lower quality of work. This book addresses these issues by providing fundamental information in a university course format, with theoretical material, detailed illustrations, and projects to test the reader’s understanding of the concepts covered.
Learning Design : A Handbook on Modelling and Delivering Networked Education and Training
Put together contributions from members of the "Valkenburg Group", consisting of 33 experts deeply involved in e-learning and more specifically learning design. The result is a rich and lasting source of information for both e-learning course and tool developers, providing information about the specification itself, how to implement it in practice, what tools to use, and what pitfalls to avoid. The book not only reports first experiences, but also goes beyond the current state of the art by looking at future prospects and emerging applications.
Layce (Image data poisoning) = لايس (تسميم بيانات الصور )
The ongoing growth of image generative artificial intelligence models was paved with existing drawings and art pieces by great artists both past and present, and while generative models are very useful and helpful, there is the issue of the origin of the datasets trained on, and the morality of usage regarding copyrights and artistic identity. A novel line of defense that helps artists and visual content creators actively protect their pieces emerged, dubbed Data Poisoning and it works by misleading Artificial Intelligence models that attempt to use a Poisoned Image for training, or as a reference, as the Poisoned Image will appear to the human eye identical to the original art piece, while the Artificial Intelligence model will be seeing a remarkably different image, causing generative models to generate false positive results when given a prompt poisoned by the author or when trained on data poisoned by the original owner. This study aims to study image data poisoning methods and technologies, and build an application containing multiple image models, and poisoning models as well, accompanied by a Community for artists to share art and interact with each other.
Beyond the Worst-Case Analysis of Algorithms
There are no silver bullets in algorithm design, and no single algorithmic idea is powerful and flexible enough to solve every computational problem. Nor are there silver bullets in algorithm analysis, as the most enlightening method for analyzing an algorithm often depends on the problem and the application. However, typical algorithms courses rely almost entirely on a single analysis framework, that of worst-case analysis, wherein an algorithm is assessed by its worst performance on any input of a given size. The purpose of this book is to popularize several alternatives to worst-case analysis and their most notable algorithmic applications, from clustering to linear programming to neural network training. Forty leading researchers have contributed introductions to different facets of this field, emphasizing the most important models and results, many of which can be taught in lectures to beginning graduate students in theoretical computer science and machine learning.
Berufliche passagen im lebenslauf : berufsbildungs- und transitionsforschung in der Schweiz = Vocational passages in the CV : Vocational training and transition research in Switzerland
During the transition from school to work, important groundwork is laid that prepares the further course of a person's life. In addition, this volume presents new results from diverse transition research from all over Switzerland, which are based on various disciplines such as psychology, sociology, educational sciences or educational economics. For this purpose, theoretical foundations and empirical evidence for the analysis and control of significant passages in the life course are developed.
Artificial neural network-based optimized design of reinforced concrete structures
Introduces AI-based Lagrange optimization techniques that can enable more rational engineering decisions for concrete structures while conforming to codes of practice. It shows how objective functions including cost, CO2 emissions, and structural weight of concrete structures are optimized either separately or simultaneously while satisfying constraining design conditions using an ANN-based Lagrange algorithm. Any design target can be adopted as an objective function. Many optimized design examples are verified by both conventional structural calculations and big datasets. Uniquely applies the new powerful tools of AI to concrete structural design and optimization Multi-objective functions of concrete structures optimized either separately or simultaneously Design requirements imposed by codes are automatically satisfied by constraining conditions Heavily illustrated in color with practical design examples
Agile processes in software engineering and extreme programming ; XP 2020 Workshops, Copenhagen, Denmark, June 8–12, 2020, Revised Selected Papers
This book constitutes the 6 research workshops, the Agile Education and Training Track, the Doctoral Symposium, as well as a panel presented at XP 2020, the 21st International Conference on Agile Software Development, which was held during June 8-12, 2020.
A healthcare professionals training system
The Objective Structured Clinical Examination (OSCE) is a type of examination often used in health sciences. It is designed to test clinical skill performance and competence in a range of skills. It is a practical, real-world approach to learning and assessment. Comprises a circuit of short (5-10 minutes) stations, in which each candidate is examined on a one-to-one basis with one or two impartial examiner(s) and patients who are either real or simulated (actors or electronic patient simulators). Each station has a different examiner; in comparison, the traditional method of clinical examination is when a candidate is assigned to an examiner for the entire examination.
