Gang Li

This book provides a detailed study on sources of encrypted network traffic, methods and techniques for analyzing, classifying and detecting the encrypted traffic. The authors provide research findings and objectives in the first 5 chapters, on encrypted network traffic, protocols and applications of the encrypted network traffic. The authors also analyze the challenges and issues with encrypted network traffic. It systematically introduces the analysis and classification of encrypted traffic and methods in detecting the anomalies in encrypted traffic. The effects of traditional approaches of encrypted traffic, such as deep packet inspection and flow based approaches on various encrypted traffic applications for identifying attacks is discussed as well. This book presents intelligent techniques for analyzing the encrypted network traffic and includes case studies. The first chapter also provides fundamentals of network traffic analysis, anomalies in the network traffic, protocols for encrypted network traffic. The second chapter presents an overview of the challenges and issues with encrypted network traffic and the new threat vectors introduced by the encrypted network traffic. Chapter 3 provides details analyzing the encrypted network traffic and classification of various kinds of encrypted network traffic. Chapter 4 discusses techniques for detecting attacks against encrypted protocols and chapter 5 analyzes AI based approaches for anomaly detection. Researchers and professionals working in the related field of Encrypted Network Traffic will purchase this book as a reference. Advanced-level students majoring in computer science will also find this book to be a valuable resource.

This book initially delves into its fundamentals to initiate the exploration of online incentive mechanisms in wireless communications. Three case studies are provided to elaborate details on designing online mechanism design in practical system. For crowdsensing with random task arrivals, this book introduces a linear online incentive mechanism model with insurance of the quality of information for each incoming task. In the context of edge computing systems, the authors model a nonlinear online incentive mechanism with the consideration of mobile users’ energy budget constraints. It also explores online incentive mechanism for collaborative task offloading in mobile edge computing to achieve on-arrival instant responses. This book not only disseminates current knowledge but also sheds light on future research directions. The design of incentive mechanisms in wireless communication systems is of paramount importance as it encourages dormant terminals within networks to contribute their valuable resources. The consideration of randomness of network processes enhances the mechanism design under online settings and decision making on the fly. This book endeavours to bridge existing knowledge gaps by comprehensively presenting and developing fundamental insights into online incentive mechanisms and their design methods in the realm of wireless communications. It’s one of the first books to provide a comprehensive understanding of the fundamental principles of online incentive mechanisms and their intricately designed methods in the dynamic world of wireless communications. Future research directions include an investigation in the evolving domain of online incentive mechanism designs within wireless communications. This book strikes a balance between theoretical knowledge and practical application, making it a valuable resource for both researchers and practitioners in the field of wireless communications and network economics. Advanced-level students majoring in computer science and/or electrical engineering will want to purchase this book as a study guide.

This book introduces advanced sparsity-driven models and methods and their applications in radar tasks such as detection, imaging and classification. Compressed sensing (CS) is one of the most active topics in the signal processing area. By exploiting and promoting the sparsity of the signals of interest, CS offers a new framework for reducing data without compromising the performance of signal recovery, or for enhancing resolution without increasing measurements. An introductory chapter outlines the fundamentals of sparse signal recovery. The following topics are then systematically and comprehensively addressed: hybrid greedy pursuit algorithms for enhancing radar imaging quality; two-level block sparsity model for multi-channel radar signals; parametric sparse representation for radar imaging with model uncertainty; Poisson-disk sampling for high-resolution and wide-swath SAR imaging; when advanced sparse models meet coarsely quantized radar data; sparsity-aware micro-Doppler analysis for radar target classification; and distributed detection of sparse signals in radar networks via locally most powerful test. Finally, a concluding chapter summarises key points from the preceding chapters and offers concise perspectives. The book focuses on how to apply the CS-based models and algorithms to solve practical problems in radar, for the radar and signal processing research communities.

Connecting theory with numerical techniques using MATLAB®, this practical textbook equips students with the tools required to solve finite element problems. This hands-on guide covers a wide range of engineering problems through nine well-structured chapters including solid mechanics, heat transfer and fluid dynamics; equilibrium, steady state and transient; and 1-D, 2-D and 3-D problems. Engineering problems are discussed using case study examples, which are solved using a systematic approach, both by examining the steps manually and by implementing a complete MATLAB®code. This topical coverage is supplemented by discourse on meshing with a detailed explanation and implementation of 2-D meshing algorithms. Introducing theory and numerical techniques alongside comprehensive examples this text increases engagement and provides students with the confidence needed to implement their own computer codes to solve given problems.

Longitudinal studies often incur several problems that challenge standard statistical methods for data analysis. These problems include non-ignorable missing data in longitudinal measurements of one or more response variables, informative observation times of longitudinal data, and survival analysis with intermittently measured time-dependent covariates that are subject to measurement error and/or substantial biological variation. Joint modeling of longitudinal and time-to-event data has emerged as a novel approach to handle these issues.Joint Modeling of Longitudinal and Time-to-Event Data provides a systematic introduction and review of state-of-the-art statistical methodology in this active research field. The methods are illustrated by real data examples from a wide range of clinical research topics. A collection of data sets and software for practical implementation of the joint modeling methodologies are available through the book website.This book serves as a reference book for scientific investigators who need to analyze longitudinal and/or survival data, as well as researchers developing methodology in this field. It may also be used as a textbook for a graduate level course in biostatistics or statistics.

This book focuses on differential privacy and its application with an emphasis on technical and application aspects. This book also presents the most recent research on differential privacy with a theory perspective. It provides an approachable strategy for researchers and engineers to implement differential privacy in real world applications.Early chapters are focused on two major directions, differentially private data publishing and differentially private data analysis. Data publishing focuses on how to modify the original dataset or the queries with the guarantee of differential privacy. Privacy data analysis concentrates on how to modify the data analysis algorithm to satisfy differential privacy, while retaining a high mining accuracy. The authors also introduce several applications in real world applications, including recommender systems and location privacy Advanced level students in computer science and engineering, as well as researchers and professionals working in privacy preserving, data mining, machine learning and data analysis will find this book useful as a reference. Engineers in database, network security, social networks and web services will also find this book useful.

This book focuses on differential privacy and its application with an emphasis on technical and application aspects. This book also presents the most recent research on differential privacy with a theory perspective. It provides an approachable strategy for researchers and engineers to implement differential privacy in real world applications.Early chapters are focused on two major directions, differentially private data publishing and differentially private data analysis. Data publishing focuses on how to modify the original dataset or the queries with the guarantee of differential privacy. Privacy data analysis concentrates on how to modify the data analysis algorithm to satisfy differential privacy, while retaining a high mining accuracy. The authors also introduce several applications in real world applications, including recommender systems and location privacy Advanced level students in computer science and engineering, as well as researchers and professionals working in privacy preserving, data mining, machine learning and data analysis will find this book useful as a reference. Engineers in database, network security, social networks and web services will also find this book useful.

Longitudinal studies often incur several problems that challenge standard statistical methods for data analysis. These problems include non-ignorable missing data in longitudinal measurements of one or more response variables, informative observation times of longitudinal data, and survival analysis with intermittently measured time-dependent covariates that are subject to measurement error and/or substantial biological variation. Joint modeling of longitudinal and time-to-event data has emerged as a novel approach to handle these issues.Joint Modeling of Longitudinal and Time-to-Event Data provides a systematic introduction and review of state-of-the-art statistical methodology in this active research field. The methods are illustrated by real data examples from a wide range of clinical research topics. A collection of data sets and software for practical implementation of the joint modeling methodologies are available through the book website.This book serves as a reference book for scientific investigators who need to analyze longitudinal and/or survival data, as well as researchers developing methodology in this field. It may also be used as a textbook for a graduate level course in biostatistics or statistics.

Signals and systems enjoy wide application in industry and daily life, and understanding basic concepts of the subject area is of importance to undergraduates majoring in engineering. With rigorous mathematical deduction, this introductory text book is helpful for students who study communications engineering, electrical and electronic engineering, and control engineering. Additionally, supplementary materials are provided for self-learners.

A comprehensive book focusing on the Force Analogy Method, a novel method for nonlinear dynamic analysis and simulation This book focusses on the Force Analogy Method, a novel method for nonlinear dynamic analysis and simulation. A review of the current nonlinear analysis method for earthquake engineering will be summarized and explained. Additionally, how the force analogy method can be used in nonlinear static analysis will be discussed through several nonlinear static examples. The emphasis of this book is to extend and develop the force analogy method to performing dynamic analysis on structures under earthquake excitations, where the force analogy method is incorporated in the flexural element, axial element, shearing element and so on will be exhibited. Moreover, the geometric nonlinearity into nonlinear dynamic analysis algorithm based on the force analogy method is included. The application of the force analogy method in seismic design for buildings and structural control area is discussed and combined with practical engineering.

Tourism demand is the foundation on which all tourism-related business decisions ultimately rest. Governments and companies such as airlines, tour operators, hotels, cruise ship lines, and recreation facility providers are interested in the demand for their products by tourists. The success of many businesses depends largely or totally on the state of tourism demand, and ultimate management failure is quite often due to the failure to meet market demand. This book introduces students, researchers and practitioners to the modern developments in advanced econometric methodology within the context of tourism demand analysis, and illustrates these developments with actual tourism applications. The concepts and computations of modern advanced econometric modelling methodologies are introduced at a level that is accessible to specialists and non-specialists alike. The methodologies introduced include general-to-specific modelling, cointegration, vector autoregression, time varying parameter modelling, panel data analysis and the almost ideal demand system (AIDS). In order to help the reader understand the various methodologies, extensive tourism demand examples are provided throughout the volume.

This book is all about finite wordlength errors in digital filters, con­ trollers and estimators, and how to minimize the deleterious effects of these errors on the performance of these devices. This does by no means imply that all about finite wordlength errors in filters, controllers and estimators is to be found in this book. We first ventured into the world of finite wordlength effects in 1987 when Gang Li began his PhD thesis in this area. Our more experienced readers might well say 'This shows', but we believe that the extent of our new contributions largely offsets our relative inexperience about the subject that might surface here and there in the book. Our naive view on the subject of finite wordlength errors in 1987 could probably be summarized as follows: • numerical errors due to finite wordlength encoding and roundoff are something that one has to live with, and there is probably not much that can be done about them except to increase the wordlength by improvements on the hardware; • these errors are as old as finite arithmetic and numerical analysis and they must therefore be well understood by now; • thus, if something can be done to minimize their effects, it must have been analysed and put into practice a long time ago. It is almost fair to say that we were wrong on all counts.

Tourism demand is the foundation on which all tourism-related business decisions ultimately rest. Governments and companies such as airlines, tour operators, hotels, cruise ship lines, and recreation facility providers are interested in the demand for their products by tourists. The success of many businesses depends largely or totally on the state of tourism demand, and ultimate management failure is quite often due to the failure to meet market demand. This book introduces students, researchers and practitioners to the modern developments in advanced econometric methodology within the context of tourism demand analysis, and illustrates these developments with actual tourism applications. The concepts and computations of modern advanced econometric modelling methodologies are introduced at a level that is accessible to specialists and non-specialists alike. The methodologies introduced include general-to-specific modelling, cointegration, vector autoregression, time varying parameter modelling, panel data analysis and the almost ideal demand system (AIDS). In order to help the reader understand the various methodologies, extensive tourism demand examples are provided throughout the volume.