Welcome to our book review site go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Game Theory for Security and Risk Management
The chapters in this volume explore how various methods from game theory can be utilized to optimize security and risk-management strategies. Emphasizing the importance of connecting theory and practice, they detail the steps involved in selecting, adapting, and analyzing game-theoretic models in security engineering and provide case studies of successful implementations in different application domains. Practitioners who are not experts in game theory and are uncertain about incorporating it into their work will benefit from this resource, as well as researchers in applied mathematics and computer science interested in current developments and future directions. The first part of the book p...
Transitioning to Affordable and Clean Energy
Transitioning to Affordable and Clean Energy is a collective volume which combines original contributions and review papers that address the question how the transition to clean and affordable energy can be governed. It will cover both general analyses of the governance of transition, including policy instruments, comparative studies of countries or policies, and papers setting out scientifically sound visions of a clean and just energy system. In particular, the following aspects are foregrounded: • Governing the supply and demand side transformation • Geographical and cultural differences and their consequences for the governance of energy transitions • Sustainability and justice rel...
Machine Learning for Embedded System Security
This book comprehensively covers the state-of-the-art security applications of machine learning techniques. The first part explains the emerging solutions for anti-tamper design, IC Counterfeits detection and hardware Trojan identification. It also explains the latest development of deep-learning-based modeling attacks on physically unclonable functions and outlines the design principles of more resilient PUF architectures. The second discusses the use of machine learning to mitigate the risks of security attacks on cyber-physical systems, with a particular focus on power plants. The third part provides an in-depth insight into the principles of malware analysis in embedded systems and describes how the usage of supervised learning techniques provides an effective approach to tackle software vulnerabilities.
Optimization of Power Flow Computation Methods
Power flow computations are a cornerstone of many simulations regarding the electric grid. This thesis evaluates the landscape of power flow computation methods with a focus on practical computational performance in large-scale simulations, as they occur in modern distribution grid planning. The investigation involves various model assumptions, different algorithms, implementation details, and unconventional computational optimization methods. As a result, the implementations devised in this thesis are up to a thousand times faster for large scale grid simulations than established solutions.
Interval Methods for Uncertain Power System Analysis
Interval Methods for Uncertain Power System Analysis In Interval Methods for Uncertain Power System Analysis, accomplished engineer Dr. Alfredo Vaccaro delivers a comprehensive discussion of the mathematical foundations of range analysis and its application to solving traditional power system operation problems in the presence of strong and correlated uncertainties. The book explores highly relevant topics in the area, from interval methods for uncertainty representation and management to a variety of application examples. The author offers readers the latest methodological breakthroughs and roadmaps to implementing the mathematics discussed within, as well as best practices commonly employe...
Data Analytics in Power Markets
This book aims to solve some key problems in the decision and optimization procedure for power market organizers and participants in data-driven approaches. It begins with an overview of the power market data and analyzes on their characteristics and importance for market clearing. Then, the first part of the book discusses the essential problem of bus load forecasting from the perspective of market organizers. The related works include load uncertainty modeling, bus load bad data correction, and monthly load forecasting. The following part of the book answers how much information can be obtained from public data in locational marginal price (LMP)-based markets. It introduces topics such as ...
Family Record of Joseph Gehman Horning, 1855-1931 and Elizabeth Bauman Good, 1852-1937
Joseph Gehman Horning was born 28 September 1855 in Pennsylvania. His parents were Moses M. Horning (1830-1906) and Lavina M. Gehman (1832-1897). He married Elizabeth Bauman Good (1852-1937), daughter of John H. Good and Lavina Bauman. They had ten children. Descendants and relatives lived mainly in Pennsylvania.
