This book provides a holistic picture of how Chinese turnaround schools have been remarkably improved over the years and to arouse further discussion in this regard. It contributes to the understanding of school improvement from a Chinese cultural perspective, solidifies the knowledge basis of school change theories, and expands the understanding of educational administration and policies in China.

Information security concerns the confidentiality, integrity, and availability of information processed by a computer system. With an emphasis on prevention, traditional information security research has focused little on the ability to survive successful attacks, which can seriously impair the integrity and availability of a system. Trusted Recovery And Defensive Information Warfare uses database trusted recovery, as an example, to illustrate the principles of trusted recovery in defensive information warfare. Traditional database recovery mechanisms do not address trusted recovery, except for complete rollbacks, which undo the work of benign transactions as well as malicious ones, and compensating transactions, whose utility depends on application semantics. Database trusted recovery faces a set of unique challenges. In particular, trusted database recovery is complicated mainly by (a) the presence of benign transactions that depend, directly or indirectly on malicious transactions; and (b) the requirement by many mission-critical database applications that trusted recovery should be done on-the-fly without blocking the execution of new user transactions. Trusted Recovery And Defensive Information Warfare proposes a new model and a set of innovative algorithms for database trusted recovery. Both read-write dependency based and semantics based trusted recovery algorithms are proposed. Both static and dynamic database trusted recovery algorithms are proposed. These algorithms can typically save a lot of work by innocent users and can satisfy a variety of attack recovery requirements of real world database applications. Trusted Recovery And Defensive Information Warfare is suitable as a secondary text for a graduate level course in computer science, and as a reference for researchers and practitioners in information security.

Motivation for the Book This book seeks to establish the state of the art in the cyber situational awareness area and to set the course for future research. A multidisciplinary group of leading researchers from cyber security, cognitive science, and decision science areas elab orate on the fundamental challenges facing the research community and identify promising solution paths. Today, when a security incident occurs, the top three questions security admin istrators would ask are in essence: What has happened? Why did it happen? What should I do? Answers to the ?rst two questions form the core of Cyber Situational Awareness. Whether the last question can be satisfactorily answered is greatly de pendent upon the cyber situational awareness capability of an enterprise. A variety of computer and network security research topics (especially some sys tems security topics) belong to or touch the scope of Cyber Situational Awareness. However, the Cyber Situational Awareness capability of an enterprise is still very limited for several reasons: * Inaccurate and incomplete vulnerability analysis, intrusion detection, and foren sics. * Lack of capability to monitor certain microscopic system/attack behavior. * Limited capability to transform/fuse/distill information into cyber intelligence. * Limited capability to handle uncertainty. * Existing system designs are not very "friendly" to Cyber Situational Awareness.

Providing a window on educational leadership from an Asian cultural perspective, Liu and Thien’s edited collection describes how educational leadership is linked with national culture in the context of different Asian countries. While much of the scholarship on this topic has been built on Western paradigms, this book examines the measurement of school leadership from a diverse lens by taking cultural context into account while examining educational leadership. Drawing on cross-cultural perspectives, the authors investigate the relationship between leadership for learning and societal culture, in addition to the relationship between leadership style and culture. The text provides a theoretical basis for understanding leadership in the context of Asian countries, and offers practical suggestions for identifying effective, and culturally sensitive leadership practices in similar cultural contexts. An excellent resource for graduate students, researchers in comparative education, educational practitioners looking to improve their education practices, and anyone interested in cultural leadership practices.

Geostrategic psychology is a new approach to analyze international political practice based on the intersection of geopolitics and strategic psychology Aims to respond to and understand the real needs of China's rise in today's era Gives insights into the strategy of the rise of great powers in the history

This book introduces computational advertising, and Internet monetization. It provides a macroscopic understanding of how consumer products in the Internet era push user experience and monetization to the limit. Part One of the book focuses on the basic problems and background knowledge of online advertising. Part Two targets the product, operations, and sales staff, as well as high-level decision makers of the Internet products. It explains the market structure, trading models, and the main products in computational advertising. Part Three targets systems, algorithms, and architects, and focuses on the key technical challenges of different advertising products. Features * Introduces computational advertising and Internet monetization * Covers data processing, utilization, and trading * Uses business logic as the driving force to explain online advertising products and technology advancement * Explores the products and the technologies of computational advertising, to provide insights on the realization of personalization systems, constrained optimization, data monetization and trading, and other practical industry problems * Includes case studies and code snippets

This book introduces computational advertising, and Internet monetization. It provides a macroscopic understanding of how consumer products in the Internet era push user experience and monetization to the limit. Part One of the book focuses on the basic problems and background knowledge of online advertising. Part Two targets the product, operations, and sales staff, as well as high-level decision makers of the Internet products. It explains the market structure, trading models, and the main products in computational advertising. Part Three targets systems, algorithms, and architects, and focuses on the key technical challenges of different advertising products. Features * Introduces computational advertising and Internet monetization * Covers data processing, utilization, and trading * Uses business logic as the driving force to explain online advertising products and technology advancement * Explores the products and the technologies of computational advertising, to provide insights on the realization of personalization systems, constrained optimization, data monetization and trading, and other practical industry problems * Includes case studies and code snippets

This book provides a holistic picture of how Chinese turnaround schools have been remarkably improved over the years and to arouse further discussion in this regard. It contributes to the understanding of school improvement from a Chinese cultural perspective, solidifies the knowledge basis of school change theories, and expands the understanding of educational administration and policies in China.

This book constitutes revised selected papers from the 4th International Workshop on Graphical Models for Security, GraMSec 2017, held in Santa Barbara, CA, USA, in August 2017. The 5 full and 4 short papers presented in this volume were carefully reviewed and selected from 19 submissions. The book also contains one invited paper from the WISER project. The contributions deal with the latest research and developments on graphical models for security.

Motivation for the Book This book seeks to establish the state of the art in the cyber situational awareness area and to set the course for future research. A multidisciplinary group of leading researchers from cyber security, cognitive science, and decision science areas elab orate on the fundamental challenges facing the research community and identify promising solution paths. Today, when a security incident occurs, the top three questions security admin istrators would ask are in essence: What has happened? Why did it happen? What should I do? Answers to the ?rst two questions form the core of Cyber Situational Awareness. Whether the last question can be satisfactorily answered is greatly de pendent upon the cyber situational awareness capability of an enterprise. A variety of computer and network security research topics (especially some sys tems security topics) belong to or touch the scope of Cyber Situational Awareness. However, the Cyber Situational Awareness capability of an enterprise is still very limited for several reasons: * Inaccurate and incomplete vulnerability analysis, intrusion detection, and foren sics. * Lack of capability to monitor certain microscopic system/attack behavior. * Limited capability to transform/fuse/distill information into cyber intelligence. * Limited capability to handle uncertainty. * Existing system designs are not very "friendly" to Cyber Situational Awareness.

Information security concerns the confidentiality, integrity, and availability of information processed by a computer system. With an emphasis on prevention, traditional information security research has focused little on the ability to survive successful attacks, which can seriously impair the integrity and availability of a system. Trusted Recovery And Defensive Information Warfare uses database trusted recovery, as an example, to illustrate the principles of trusted recovery in defensive information warfare. Traditional database recovery mechanisms do not address trusted recovery, except for complete rollbacks, which undo the work of benign transactions as well as malicious ones, and compensating transactions, whose utility depends on application semantics. Database trusted recovery faces a set of unique challenges. In particular, trusted database recovery is complicated mainly by (a) the presence of benign transactions that depend, directly or indirectly on malicious transactions; and (b) the requirement by many mission-critical database applications that trusted recovery should be done on-the-fly without blocking the execution of new user transactions. Trusted Recovery And Defensive Information Warfare proposes a new model and a set of innovative algorithms for database trusted recovery. Both read-write dependency based and semantics based trusted recovery algorithms are proposed. Both static and dynamic database trusted recovery algorithms are proposed. These algorithms can typically save a lot of work by innocent users and can satisfy a variety of attack recovery requirements of real world database applications. Trusted Recovery And Defensive Information Warfare is suitable as a secondary text for a graduate level course in computer science, and as a reference for researchers and practitioners in information security.

This book constitutes the thoroughly refereed post-conference proceedings of the 4th International Conference on Information Security and Cryptology, Inscrypt 2008, held in Beijing, China, in December 2008.

The 28 revised full papers presented together with 3 invited talks were carefully reviewed and selected from 183 submissions. The papers are organized in topical sections on digital signature and signcryption schemes, privacy and anonymity, message authentication code and hash function, secure protocols, symmetric cryptography, certificateless cryptography, hardware implementation and side channel attack, wireless network security, public key and identity based cryptography, access control and network security, as well as trusted computing and applications.

This book systematically introduces the competitions in the field of algorithm and machine learning. The first author of the book has won 5 championships and 5 runner-ups in domestic and international algorithm competitions.Firstly, it takes common competition scenarios as a guide by giving the main processes of using machine learning to solve real-world problems, namely problem modelling, data exploration, feature engineering, model training. And then lists the main points of difficulties, general ideas with solutions in the whole process. Moreover, this book comprehensively covers several common problems in the field of machine learning competitions such as recommendation, temporal prediction, advertising, text computing, etc. The authors, also knew as "competition professionals�, will explain the actual cases in detail and teach you various processes, routines, techniques and strategies, which is a rare treasure book for all competition enthusiasts. It is very suitable for readers who are interested in algorithm competitions and deep learning algorithms in practice, or computer-related majors.

This book constitutes the refereed proceedings of the 20th Annual Working Conference on Data and Applications Security held in Sophia Antipolis, France, in July/August 2006.

The 22 revised full papers presented were carefully reviewed and selected from 56 submissions. The papers present theory, technique, applications, and practical experience of data and application security covering a number of diverse research topics such as access control, privacy, and identity management.

Build and implement trading strategies using Python. This book will introduce you to the fundamental concepts of quantitative trading and shows how to use Python and popular libraries to build trading models and strategies from scratch. It covers practical trading strategies coupled with step-by-step implementations that touch upon a wide range of topics, including data analysis and visualization, algorithmic trading, backtesting, risk management, optimization, and machine learning, all coupled with practical examples in Python. Part one of Quantitative Trading Strategies with Python covers the fundamentals of trading strategies, including an introduction to quantitative trading, the electronic market, risk and return, and forward and futures contracts. Part two introduces common trading strategies, including trend-following, momentum trading, and evaluation process via backtesting. Part three covers more advanced topics, including statistical arbitrage using hypothesis testing, optimizing trading parameters using Bayesian optimization, and generating trading signals using a machine learning approach. Whether you're an experienced trader looking to automate your trading strategies or a beginner interested in learning quantitative trading, this book will be a valuable resource. Written in a clear and concise style that makes complex topics easy to understand, and chock full of examples and exercises to help reinforce the key concepts, you’ll come away from it with a firm understanding of core trading strategies and how to use Python to implement them. What You Will Learn Master the fundamental concepts of quantitative trading Use Python and its popular libraries to build trading models and strategies from scratch Perform data analysis and visualization, algorithmic trading, backtesting, risk management, optimization, and machine learning for trading strategies using Python Utilize common trading strategies such as trend-following, momentum trading, and pairs trading Evaluate different quantitative trading strategies by applying the relevant performance measures and statistics in a scientific manner during backtesting Who This Book Is For Aspiring quantitative traders and analysts, data scientists interested in finance, and researchers or students studying quantitative finance, financial engineering, or related fields.

This book covers the essential theory and implementation of popular Bayesian optimization techniques in an intuitive and well-illustrated manner. The techniques covered in this book will enable you to better tune the hyperparemeters of your machine learning models and learn sample-efficient approaches to global optimization. The book begins by introducing different Bayesian Optimization (BO) techniques, covering both commonly used tools and advanced topics. It follows a “develop from scratch� method using Python, and gradually builds up to more advanced libraries such as BoTorch, an open-source project introduced by Facebook recently. Along the way, you’ll see practical implementations of this important discipline along with thorough coverage and straightforward explanations of essential theories. This book intends to bridge the gap between researchers and practitioners, providing both with a comprehensive, easy-to-digest, and useful reference guide. After completing this book, you will have a firm grasp of Bayesian optimization techniques, which you’ll be able to put into practice in your own machine learning models. What You Will Learn Apply Bayesian Optimization to build better machine learning models Understand and research existing and new Bayesian Optimization techniques Leverage high-performance libraries such as BoTorch, which offer you the ability to dig into and edit the inner working Dig into the inner workings of common optimization algorithms used to guide the search process in Bayesian optimization Who This Book Is ForBeginner to intermediate level professionals in machine learning, analytics or other roles relevant in data science.

Today's cyber defenses are largely static allowing adversaries to pre-plan their attacks. In response to this situation, researchers have started to investigate various methods that make networked information systems less homogeneous and less predictable by engineering systems that have homogeneous functionalities but randomized manifestations. The 10 papers included in this State-of-the Art Survey present recent advances made by a large team of researchers working on the same US Department of Defense Multidisciplinary University Research Initiative (MURI) project during 2013-2019. This project has developed a new class of technologies called Adaptive Cyber Defense (ACD) by building on two active but heretofore separate research areas: Adaptation Techniques (AT) and Adversarial Reasoning (AR). AT methods introduce diversity and uncertainty into networks, applications, and hosts. AR combines machine learning, behavioral science, operations research, control theory, and game theory to address the goal of computing effective strategies in dynamic, adversarial environments.

Today, when a security incident happens, the top three questions a cyber operation center would ask are: What has happened? Why did it happen? What should I do? Answers to the first two questions form the core of Cyber Situation Awareness (SA). Whether the last question can be satisfactorily addressed is largely dependent upon the cyber situation awareness capability of an enterprise. The goal of this book is to present a summary of recent research advances in the development of highly desirable Cyber Situation Awareness capabilities. The 8 invited full papers presented in this volume are organized around the following topics: computer-aided human centric cyber situation awareness; computer and information science aspects of the recent advances in cyber situation awareness; learning and decision making aspects of the recent advances in cyber situation awareness; cognitive science aspects of the recent advances in cyber situation awareness

Intrusion Tolerant Database System (ITDB) is a new paradigm for secure database systems that can detect intrusions, isolate attacks, contain damage, and assess and repair damage caused by intrusions. What makes ITDB superior to conventional secure approaches is that it has an ability to reconfigure. Thus, it can yield much more stabilized levels of trustworthiness under environmental changes. However, the reconfiguration faces the problem of finding the best system configuration out of a very large number of configuration sets and under multiple conflicting criteria, which is a NPhard problem. This study focuses on two aspects of addressing adaptation problems in ITDB. First, a rule-based mechanism and neuro-fuzzy technique are proposed to apply to the adaptation model. Second, this study examines the effects of the rule-based adaptive controller and the neuro-fuzzy adaptive controller on the adaptation. The purpose of this is to evaluate which of these techniques can yield higher stabilized levels of trustworthiness, data integrity, and data availability in the face of attacks.