sanitization of data in computer network



Hyunjoung Lee Fundamentals of Big Data Network Analysis for Research and Industry Hyunjoung Lee Fundamentals of Big Data Network Analysis for Research and Industry Новинка

Hyunjoung Lee Fundamentals of Big Data Network Analysis for Research and Industry

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Fundamentals of Big Data Network Analysis for Research and Industry Hyunjoung Lee, Institute of Green Technology, Yonsei University, Republic of Korea Il Sohn, Material Science and Engineering, Yonsei University, Republic of Korea Presents the methodology of big data analysis using examples from research and industry There are large amounts of data everywhere, and the ability to pick out crucial information is increasingly important. Contrary to popular belief, not all information is useful; big data network analysis assumes that data is not only large, but also meaningful, and this book focuses on the fundamental techniques required to extract essential information from vast datasets. Featuring case studies drawn largely from the iron and steel industries, this book offers practical guidance which will enable readers to easily understand big data network analysis. Particular attention is paid to the methodology of network analysis, offering information on the method of data collection, on research design and analysis, and on the interpretation of results. A variety of programs including UCINET, NetMiner, R, NodeXL, and Gephi for network analysis are covered in detail. Fundamentals of Big Data Network Analysis for Research and Industry looks at big data from a fresh perspective, and provides a new approach to data analysis. This book: Explains the basic concepts in understanding big data and filtering meaningful data Presents big data analysis within the networking perspective Features methodology applicable to research and industry Describes in detail the social relationship between big data and its implications Provides insight into identifying patterns and relationships between seemingly unrelated big data Fundamentals of Big Data Network Analysis for Research and Industry will prove a valuable resource for analysts, research engineers, industrial engineers, marketing professionals, and any individuals dealing with accumulated large data whose interest is to analyze and identify potential relationships among data sets.
Moazzam Hossain Intrusion Detection with Artificial Neural Networks Moazzam Hossain Intrusion Detection with Artificial Neural Networks Новинка

Moazzam Hossain Intrusion Detection with Artificial Neural Networks

Intrusion detection system is a detection mechanism that detects unauthorized, malicious presents in the computer systems. The purpose of this book is to design, implement and evaluate an anomaly based network intrusion detection system. The System learns about the normal users' behavior and finds the anomalies by matching with this normal behavior. A special type of neural network called backpropagation neural network is used for learning normal users' behavior. The network traffic that only contains information of normal users is presented with the neural network for learning about the normal users' behavior. The system performance has been tested by using a simulated computer network. The neural network is trained with huge,not so huge and small amount of data. The detection capability of the system has been tested with huge and small amount of data. It is seen from the performance analysis that the system performs well when trained with small amount of data. An overall detection rate of 98% has been achieved for both known and unknown attacks. Moreover, the system can detect 100% normal user.
Dehmer Matthias Statistical and Machine Learning Approaches for Network Analysis Dehmer Matthias Statistical and Machine Learning Approaches for Network Analysis Новинка

Dehmer Matthias Statistical and Machine Learning Approaches for Network Analysis

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Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks. Comprised of chapters written by internationally renowned researchers in the field of interdisciplinary network theory, the book presents current and classical methods to analyze networks statistically. Methods from machine learning, data mining, and information theory are strongly emphasized throughout. Real data sets are used to showcase the discussed methods and topics, which include: A survey of computational approaches to reconstruct and partition biological networks An introduction to complex networks—measures, statistical properties, and models Modeling for evolving biological networks The structure of an evolving random bipartite graph Density-based enumeration in structured data Hyponym extraction employing a weighted graph kernel Statistical and Machine Learning Approaches for Network Analysis is an excellent supplemental text for graduate-level, cross-disciplinary courses in applied discrete mathematics, bioinformatics, pattern recognition, and computer science. The book is also a valuable reference for researchers and practitioners in the fields of applied discrete mathematics, machine learning, data mining, and biostatistics.
Andre Perez Network Security Andre Perez Network Security Новинка

Andre Perez Network Security

10570.86 руб. или Купить в рассрочку!
This book introduces the security mechanisms deployed in Ethernet, Wireless-Fidelity (Wi-Fi), Internet Protocol (IP) and MultiProtocol Label Switching (MPLS) networks. These mechanisms are grouped throughout the book according to the following four functions: data protection, access control, network isolation, and data monitoring. Data protection is supplied by data confidentiality and integrity control services. Access control is provided by a third-party authentication service. Network isolation is supplied by the Virtual Private Network (VPN) service. Data monitoring consists of applying rules to data in order to authorize its transfer or detect attacks. The chapters of the book cover cryptography, 802.1x mechanism, WPA mechanisms, IPSec mechanism, SSL/TLS/DTLS protocols, network management, MPLS technology, Ethernet VPN, firewalls and intrusion detection.
T. Brüggemann, P. Hedström, M. Josefsson Data mining and data based direct marketing activities T. Brüggemann, P. Hedström, M. Josefsson Data mining and data based direct marketing activities Новинка

T. Brüggemann, P. Hedström, M. Josefsson Data mining and data based direct marketing activities

Master's Thesis from the year 2004 in the subject Business economics - Marketing, Corporate Communication, CRM, Market Research, Social Media, grade: 1,7 (A-), Växjö University (School of Management and Economics), course: International Business Environment, 40 entries in the bibliography, language: English, abstract: Widespread changes within business environments in recent years has demanded acquisitions of new tools that are more skilled to cope with new challenges and demands in business. Advances in computer technologies, higher accessibility of computer associated tools and decreased prices of general computer-related products are reasons enough for at least considerations about higher usage of new technologies. Particularly in direct marketing activities discussed technology is called Data Mining.Companies are faced with hosts of data collected in their data repositories. Of course, companies want to make use of their data and aim to discover interesting patterns of knowledge within their data repositories. Direct marketers which can be involved in catalogue marketing, telemarketing or widely known direct-mail marketing are intensive users of Data Mining Technologies. Because of that, the authors strive to do research concerning reasons for and advantages and disadvantages with using Data Mining as support for direct marketing activities.Chapter 1 deals with general information for the reader as support for delving into the topic. The included problem discussion fi...
Dileep Keshava Narayana IT Application Security and Control Dileep Keshava Narayana IT Application Security and Control Новинка

Dileep Keshava Narayana IT Application Security and Control

Document from the year 2012 in the subject Computer Science - IT-Security, grade: 98, University of Greenwich (University of Greenwich), course: Network & Computer systems security, language: English, abstract: This work features the following topics: Steganography exercise, Digital Watermarking exercise, Churchill secondary school data protection report, Database Authentication, Database Authorization: Privileges and role based security, Database Authorization and data integrity (Views, Constraints), Implementing Virtual private database, Churchill secondary school database security policy, Database Security Policy and Database Security policy implementation.
Enrico Seib Data Mining - Methoden in der Simulation Enrico Seib Data Mining - Methoden in der Simulation Новинка

Enrico Seib Data Mining - Methoden in der Simulation

Bachelorarbeit aus dem Jahr 2008 im Fachbereich Informatik - Wirtschaftsinformatik, Note: 1,0, Universität Rostock (Institut für Informatik, Lehrstuhl für Modellierung und Simulation), 100 Quellen im Literaturverzeichnis, Sprache: Deutsch, Abstract: Principles and methods of data mining are a widespread area, i.e. retail dealer use data mining tools to analyze the behavior of customers, computer hardware supplier use data mining to optimize their inventory. There are multiple possibilities of using data mining techniques, even in technical and scientific areas of applications. In regard of manyfold fields of application, there are no less than the number of techniques and methods for Data Mining in existence. Another field to apply Data Mining technique is the domain of simulation. Simulation is the computer-based approach of executing and experimenting of and with models. One aim of this thesis is to analyze data mining tools to see how capable they are solving data mining duties with respect to data calculated by simulation. Different data mining tools are analyzed, commercial tools like SPSS and SPSS Clementine as well as established and freely available tools like WEKA and the R-Project. These tools are analyzed in matters of their data mining functionalities, options to access different data sources, and their complexity of different data mining algorithms. Beyond the analysis of data mining tools with respect to functionality and simulation, envi-ronments for modeling a...
Oliver Ibe C. Fundamentals of Data Communication Networks Oliver Ibe C. Fundamentals of Data Communication Networks Новинка

Oliver Ibe C. Fundamentals of Data Communication Networks

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What every electrical engineering student and technical professional needs to know about data exchange across networks While most electrical engineering students learn how the individual components that make up data communication technologies work, they rarely learn how the parts work together in complete data communication networks. In part, this is due to the fact that until now there have been no texts on data communication networking written for undergraduate electrical engineering students. Based on the author’s years of classroom experience, Fundamentals of Data Communication Networks fills that gap in the pedagogical literature, providing readers with a much-needed overview of all relevant aspects of data communication networking, addressed from the perspective of the various technologies involved. The demand for information exchange in networks continues to grow at a staggering rate, and that demand will continue to mount exponentially as the number of interconnected IoT-enabled devices grows to an expected twenty-six billion by the year 2020. Never has it been more urgent for engineering students to understand the fundamental science and technology behind data communication, and this book, the first of its kind, gives them that understanding. To achieve this goal, the book: Combines signal theory, data protocols, and wireless networking concepts into one text Explores the full range of issues that affect common processes such as media downloads and online games Addresses services for the network layer, the transport layer, and the application layer Investigates multiple access schemes and local area networks with coverage of services for the physical layer and the data link layer Describes mobile communication networks and critical issues in network security Includes problem sets in each chapter to test and fine-tune readers’ understanding Fundamentals of Data Communication Networks is a must-read for advanced undergraduates and graduate students in electrical and computer engineering. It is also a valuable working resource for researchers, electrical engineers, and technical professionals.
N N SAKHARE, A V DHUMANE COMPUTER NETWORK N N SAKHARE, A V DHUMANE COMPUTER NETWORK Новинка

N N SAKHARE, A V DHUMANE COMPUTER NETWORK

1 TCP/IP Protocol Suit 2 Data Link Lyer 3 Ethernet 4 Logical Addressing 5 Internet PRotocol 6 Internet Protocol 7 Network Layer 8 transport Layer 9 Transmission Control Protocol 10 Introduction to Wireless Network 11 Network Security
Mung Chiang Smart Data Pricing Mung Chiang Smart Data Pricing Новинка

Mung Chiang Smart Data Pricing

10570.86 руб. или Купить в рассрочку!
A comprehensive text addressing the high demand for network, cloud, and content services through cutting-edge research on data pricing and business strategies Smart Data Pricing tackles the timely issue of surging demand for network, cloud, and content services and corresponding innovations in pricing these services to benefit consumers, operators, and content providers. The pricing of data traffic and other services is central to the core challenges of network monetization, growth sustainability, and bridging the digital divide. In this book, experts from both academia and industry discuss all aspects of smart data pricing research and development, including economic analyses, system development, user behavior evaluation, and business strategies. Smart Data Pricing: • Presents the analysis of leading researchers from industry and academia surrounding the pricing of network services and content. • Discusses current trends in mobile and wired data usage and their economic implications for content providers, network operators, end users, government regulators, and other players in the Internet ecosystem. • Includes new concepts and background technical knowledge that will help researchers and managers effectively monetize their networks and improve user quality-of-experience. • Provides cutting-edge research on business strategies and initiatives through a diverse collection of perspectives. • Combines academic and industry expertise from multiple disciplines and business organizations. The ideas and background of the technologies and economic principles discussed within these chapters are of real value to practitioners, researchers, and managers in identifying trends and deploying new pricing and network management technologies, and will help support managers in identifying new business directions and innovating solutions to challenging business problems.
Doug Lowe Networking For Dummies Doug Lowe Networking For Dummies Новинка

Doug Lowe Networking For Dummies

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The #1 bestselling beginner's guide to computer networking—now in a new edition Need networking know-how, but don't know where to turn? Run—don't walk—to the no-nonsense networking guidance offered in this friendly guide! Whether you're a networking administrator or an everyday computer user looking to set up a network in your home or office, Networking For Dummies seamlessly gets you connected with the basics and gives you the knowledge to work out whatever kinks may come your way—in no time. A network can make everything in your home or office run more smoothly and easily, but setting one up can be challenging for even the most computer-savvy people. Well, relax—this bestselling guide has you covered! Inside, you'll find step-by-step instructions on setting up and maintaining a network, working with broadband and wireless technologies, ensuring you're following best practices with storage and back-up procedures, building a wired or wireless network, and much more. Set up a network for all major operating systems Secure, optimize, and troubleshoot your network Create an intranet and use the Cloud safely Make sense of the latest updates to Windows 10 Don't let a thorny networking issue get the best of you! Heed the simple guidance in this friendly guide and effectively network your way to more effective shared data and resources.
Sören Weber Data portability and relation management in social web applications Sören Weber Data portability and relation management in social web applications Новинка

Sören Weber Data portability and relation management in social web applications

Bachelor Thesis from the year 2008 in the subject Computer Science - Internet, New Technologies, grade: 1,3, University of Bremen, course: Mediainformatics, 35 entries in the bibliography, language: English, abstract: This Bachelor-Thesis deals with the synchronisation of social network services. This type of internet application enjoys great popularity which results in new challenges for identity and relation management. On one side the user has to manage different identities and on the other side a friendslist per social network service. From this effort arose to make data portable and reusable for example in order to avoid re-declaring friends to every site. To accomplish this goal numerous projects and technologies have been developed, which already provide partial solutions for this problem. The basic conceptual question however how to deal with the problem generally is still open. Moreover some of the techniques are only suitable for special use cases or else not ready für a professional use. In this thesis some of the existing standards shall be used to tie them together to one total system. This system consists out of a central identity provider, which functions as a central storage for the users contact data. By utilising interfaces this contact data can be exchanged with the social network service and by that improves the relation management for the users.
Tapan Gondaliya Intrusion Detection System in mobile ad hoc network in MAC layer Tapan Gondaliya Intrusion Detection System in mobile ad hoc network in MAC layer Новинка

Tapan Gondaliya Intrusion Detection System in mobile ad hoc network in MAC layer

Master's Thesis from the year 2013 in the subject Computer Science - IT-Security, grade: C, Lovely Professional University, Punjab (School Of Computer Science and Engineering), course: M.Tech(CSE), language: English, abstract: The rapid proliferation of Mobile ad hoc network has changed the landscape of network security. The recent DOS attacks on major Internet sites have shown us, no open computer network is immune from intrusions. The ad-hoc network is particularly vulnerable due to its features of open medium, dynamic changing topology and cooperative algorithms, lack of centralized monitoring and management point and lack of a clear line of defense. The traditional way of protecting networks with firewalls and encryption software is no longer sufficient and effective. There are many intrusion detection techniques have been developed on Ad hoc network but have been turned to be inapplicable in this new environment. Here we need to search for new architecture and mechanisms to protect Mobile Ad hoc network. In the above all technique of intrusion detection is applied on the only one layer and that is probably on routing layer. But here we apply this intrusion detection system in the MAC layer for the more security, efficiency and high speed compare to other technique those whose apply in the network layer.
Franz-Josef Auernigg Detection of mental blocks in humans based on physiological measures Franz-Josef Auernigg Detection of mental blocks in humans based on physiological measures Новинка

Franz-Josef Auernigg Detection of mental blocks in humans based on physiological measures

Diploma Thesis from the year 2006 in the subject Computer Science - Applied, grade: 2.0, University of Salzburg (Department of Computer Sciences), course: Natural Computation, 36 entries in the bibliography, language: English, abstract: This thesis presents techniques to detect mental blocks in humans based on the physiological parameters skin potential and skin resistance. We examine physiological measures from the Musico Cause and Effect study of the Science Network for Man and Music at the University of Music and Dramatic Arts, Mozarteum Salzburg. The existing digital signal analysis tool AIDA used to process the physiological data has been replaced by the Dynalyzer developed by the author with considerable improvements in accuracy and performance. We present fundamentals of digital signal processing, outline the measurement of physiological data, and discuss characteristics of mental blocks. We suggest several criteria for the detection of mental blocks based on characteristic features of the physiological time series in the time and/or frequency domain. In first experiments the potential of these criteria is evaluated by applying them to actual physiological data of a test subject. As no ground truth on the occurrence of mental blocks is available, the experimental results can only be an indicator for the quality of the detection of mental blocks. Further experiments are conducted with data from the Vienna determination test assessing the reactive stress tolerance and at...
Amar Sahay Data Visualization, Volume I. Recent Trends and Applications Using Conventional and Big Data Amar Sahay Data Visualization, Volume I. Recent Trends and Applications Using Conventional and Big Data Новинка

Amar Sahay Data Visualization, Volume I. Recent Trends and Applications Using Conventional and Big Data

Data visualization involves graphical and visual tools used in data analysis and decision making. The emphasis in this book is on recent trends and applications of visualization tools using conventional and big data. These tools are widely used in data visualization and quality improvement to analyze, enhance, and improve the quality of products and services. Data visualization is an easy way to obtain a first look at the data visually. The book provides a collection of visual and graphical tools widely used to gain an insight into the data before applying more complex analysis. The focus is on the key application areas of these tools including business process improvement, business data analysis, health care, finance, manufacturing, engineering, process improvement, and Lean Six Sigma. The key areas of application include data and data analysis concepts, recent trends in data visualization and ÒBig Data,Ó widely used charts and graphs and their applications, analysis of the relationships between two or more variables graphically using scatterplots, bubble graphs, matrix plots, etc., data visualization with big data, computer applications and implementation of widely used graphical and visual tools, and computer instructions to create the graphics presented along with the data files.
Saurabh Pal Data Mining Applications. A Comparative Study for Predicting Student.s Performance Saurabh Pal Data Mining Applications. A Comparative Study for Predicting Student.s Performance Новинка

Saurabh Pal Data Mining Applications. A Comparative Study for Predicting Student.s Performance

Doctoral Thesis / Dissertation from the year 2014 in the subject Computer Science - General, , course: DOCTOR OF PHILOSOPHY, language: English, abstract: The primary objective of this research is to develop a process to accurately predict useful data from the huge amount of available data using data mining techniques. Data Mining is the process of finding treads, patterns and correlations between fields in large RDBMS. It permits users to analyse and study data from multiple dimensions and approaches, classify it, and summarize identified data relationships. Our focus in this thesis is to use education data mining procedures to understand higher education system data better which can help in improving efficiency and effectiveness of education. In order to achieve a decisional database, many steps need to be taken which are explained in this thesis. This work investigates the efficiency, scalability, maintenance and interoperability of data mining techniques. In this research work, data-results obtained through different data mining techniques have been compiled and analysed using variety of business intelligence tools to predict useful data. An effort has also been made to identify ways to implement this useful data efficiently in daily decision process in the field of higher education in India.Mining in educational environment is called Educational Data Mining. Han and Kamber describes data mining software that allow the users to analyze data from different dimensions, categ...
Pablo Mariño Pavón Optimization of Computer Networks. Modeling and Algorithms: A Hands-On Approach Pablo Mariño Pavón Optimization of Computer Networks. Modeling and Algorithms: A Hands-On Approach Новинка

Pablo Mariño Pavón Optimization of Computer Networks. Modeling and Algorithms: A Hands-On Approach

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This book covers the design and optimization of computer networks applying a rigorous optimization methodology, applicable to any network technology. It is organized into two parts. In Part 1 the reader will learn how to model network problems appearing in computer networks as optimization programs, and use optimization theory to give insights on them. Four problem types are addressed systematically – traffic routing, capacity dimensioning, congestion control and topology design. Part 2 targets the design of algorithms that solve network problems like the ones modeled in Part 1. Two main approaches are addressed – gradient-like algorithms inspiring distributed network protocols that dynamically adapt to the network, or cross-layer schemes that coordinate the cooperation among protocols; and those focusing on the design of heuristic algorithms for long term static network design and planning problems. Following a hands-on approach, the reader will have access to a large set of examples in real-life technologies like IP, wireless and optical networks. Implementations of models and algorithms will be available in the open-source Net2Plan tool from which the user will be able to see how the lessons learned take real form in algorithms, and reuse or execute them to obtain numerical solutions. An accompanying link to the author’s own Net2plan software enables readers to produce numerical solutions to a multitude of real-life problems in computer networks (www.net2plan.com).
Mohamed Rahama Data Structures and Algorithms Mohamed Rahama Data Structures and Algorithms Новинка

Mohamed Rahama Data Structures and Algorithms

Research Paper (undergraduate) from the year 2012 in the subject Computer Science - Applied, grade: A, Atlantic International University (School of Science and Engineering), course: Data Structures and Algorithms, language: English, abstract: This paper reviews the different ways of building data in computer systems, or aspiring to the data structure, as well as the searching methods in this data, which is known as algorithms. Data Structures and algorithms are integrated to form computer programs and in broader terms, explains what is generally known as programming abstraction.Data structures discuss the ways and mechanisms that we use to organize data in an integrated form in computers systems and exploitation of memory locations in an easy and structured ways such as arrays, stacks, queues, lists, linked lists and other. Algorithms, on the other hand, are the ways in which the instructions and operations are carried out to handle information and data on the different types of data structure.
Mourad Elloumi Biological Knowledge Discovery Handbook. Preprocessing, Mining and Postprocessing of Biological Data Mourad Elloumi Biological Knowledge Discovery Handbook. Preprocessing, Mining and Postprocessing of Biological Data Новинка

Mourad Elloumi Biological Knowledge Discovery Handbook. Preprocessing, Mining and Postprocessing of Biological Data

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The first comprehensive overview of preprocessing, mining, and postprocessing of biological data Molecular biology is undergoing exponential growth in both the volume and complexity of biological data—and knowledge discovery offers the capacity to automate complex search and data analysis tasks. This book presents a vast overview of the most recent developments on techniques and approaches in the field of biological knowledge discovery and data mining (KDD)—providing in-depth fundamental and technical field information on the most important topics encountered. Written by top experts, Biological Knowledge Discovery Handbook: Preprocessing, Mining, and Postprocessing of Biological Data covers the three main phases of knowledge discovery (data preprocessing, data processing—also known as data mining—and data postprocessing) and analyzes both verification systems and discovery systems. BIOLOGICAL DATA PREPROCESSING Part A: Biological Data Management Part B: Biological Data Modeling Part C: Biological Feature Extraction Part D Biological Feature Selection BIOLOGICAL DATA MINING Part E: Regression Analysis of Biological Data Part F Biological Data Clustering Part G: Biological Data Classification Part H: Association Rules Learning from Biological Data Part I: Text Mining and Application to Biological Data Part J: High-Performance Computing for Biological Data Mining Combining sound theory with practical applications in molecular biology, Biological Knowledge Discovery Handbook is ideal for courses in bioinformatics and biological KDD as well as for practitioners and professional researchers in computer science, life science, and mathematics.
Matthias Leeb Process Mining and Network Protocols Matthias Leeb Process Mining and Network Protocols Новинка

Matthias Leeb Process Mining and Network Protocols

Diploma Thesis from the year 2015 in the subject Computer Science - IT-Security, grade: 1, St. Pölten University of Applied Sciences (Informatik & Security), language: English, abstract: Process mining is the binding link between computational intelligence, data mining, process modeling and analysis. The thesis shows how this research discipline can be applied to network protocols and what the awards will be. Process mining is based on event data, logged by almost every information system. This event data is extracted, transformed and loaded into the process mining tool to discover, check conformance or enhance the underlying process based on observed behavior. Determining the significance of process mining in the field of network protocols and their control flow, finding the best possible algorithms and notation systems, clarifying the prerequisites and providing a proof of concept are the main achievements. Additionally other reasonable and beneficial applications, like mining an alternative protocol, dealing with a large amount of event data and estimations due to size of necessary event data, are investigated.
Daniel Larose T. Discovering Knowledge in Data. An Introduction to Data Mining Daniel Larose T. Discovering Knowledge in Data. An Introduction to Data Mining Новинка

Daniel Larose T. Discovering Knowledge in Data. An Introduction to Data Mining

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The field of data mining lies at the confluence of predictive analytics, statistical analysis, and business intelligence. Due to the ever-increasing complexity and size of data sets and the wide range of applications in computer science, business, and health care, the process of discovering knowledge in data is more relevant than ever before. This book provides the tools needed to thrive in today’s big data world. The author demonstrates how to leverage a company’s existing databases to increase profits and market share, and carefully explains the most current data science methods and techniques. The reader will “learn data mining by doing data mining”. By adding chapters on data modelling preparation, imputation of missing data, and multivariate statistical analysis, Discovering Knowledge in Data, Second Edition remains the eminent reference on data mining. The second edition of a highly praised, successful reference on data mining, with thorough coverage of big data applications, predictive analytics, and statistical analysis. Includes new chapters on Multivariate Statistics, Preparing to Model the Data, and Imputation of Missing Data, and an Appendix on Data Summarization and Visualization Offers extensive coverage of the R statistical programming language Contains 280 end-of-chapter exercises Includes a companion website for university instructors who adopt the book
Linoy A Tharakan Certain Power Management Algorithms for Wireless Sensor Networks by Energy Efficient Data Transmission, Security and Node Deployment Linoy A Tharakan Certain Power Management Algorithms for Wireless Sensor Networks by Energy Efficient Data Transmission, Security and Node Deployment Новинка

Linoy A Tharakan Certain Power Management Algorithms for Wireless Sensor Networks by Energy Efficient Data Transmission, Security and Node Deployment

Doctoral Thesis / Dissertation from the year 2017 in the subject Electrotechnology, grade: PhD, , course: Doctor of Philosophy, language: English, abstract: Wireless Sensor Networks (WSNs) is fast emerging as prominent study area that attracting considerable research attention globally. The field has seen tremendous development in design and development of application related interfaces with sensor networks. Sensor network finds applications in several domains such as medical, military, home networks, space and so on. Many researchers strongly believe that WSNs can become as important as the internet in the near future. Just as the internet allows access to digital information anywhere, WSNs could easily provide remote interaction with the physical world. It is going to be the backbone of Ubiquitous Computing (UBICOMP).Through local collaboration among sensors, elimination of duplicate data, participation of relevant nodes in the given task etc. can produce a significant difference in energy conservation, thereby increasing the life time of the sensor network.As the number of nodes increases, data security becomes the most challenging part of the network. The intruders can hack the data any time during processing, transmission or at the receiver end. So, as a popular approach data encryption is the most commendable approach in today's network. Asymmetric key encryption consumes more energy in processing and so not recommended for WSNs. Symmetric key encryption gives bette...
Chunlei Tang The Data Industry. The Business and Economics of Information and Big Data Chunlei Tang The Data Industry. The Business and Economics of Information and Big Data Новинка

Chunlei Tang The Data Industry. The Business and Economics of Information and Big Data

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Provides an introduction of the data industry to the field of economics This book bridges the gap between economics and data science to help data scientists understand the economics of big data, and enable economists to analyze the data industry. It begins by explaining data resources and introduces the data asset. This book defines a data industry chain, enumerates data enterprises’ business models versus operating models, and proposes a mode of industrial development for the data industry. The author describes five types of enterprise agglomerations, and multiple industrial cluster effects. A discussion on the establishment and development of data industry related laws and regulations is provided. In addition, this book discusses several scenarios on how to convert data driving forces into productivity that can then serve society. This book is designed to serve as a reference and training guide for ata scientists, data-oriented managers and executives, entrepreneurs, scholars, and government employees. Defines and develops the concept of a “Data Industry,” and explains the economics of data to data scientists and statisticians Includes numerous case studies and examples from a variety of industries and disciplines Serves as a useful guide for practitioners and entrepreneurs in the business of data technology The Data Industry: The Business and Economics of Information and Big Data is a resource for practitioners in the data science industry, government, and students in economics, business, and statistics. CHUNLEI TANG, Ph.D., is a research fellow at Harvard University. She is the co-founder of Fudan’s Institute for Data Industry and proposed the concept of the “data industry”. She received a Ph.D. in Computer and Software Theory in 2012 and a Master of Software Engineering in 2006 from Fudan University, Shanghai, China.
Abid Afsar Comparitive Performance Study Of Routing Protocols in Wireless Sensor Network Abid Afsar Comparitive Performance Study Of Routing Protocols in Wireless Sensor Network Новинка

Abid Afsar Comparitive Performance Study Of Routing Protocols in Wireless Sensor Network

Master's Thesis from the year 2012 in the subject Computer Science - Technical Computer Science, grade: 70%, Griffith College Dublin (Faculty of Computing ), course: MSC Computing , language: English, abstract: Modern wireless sensor network can be expanded into large geographical areas via cheap sensor devices which can sustain themselves itself with very a low power usage. The networking capability enables these sensor nodes to incorporate, collaborates, and coordinates with among each other , and this is a fundamental shift in the field of networks which differentiates sensor network nodes form other networks such as IP-datagram, Ad-Hoc and so on.Currently, routing in the wireless sensor network faces multiple challenges, such as new scalability, coverage, packet loss, interference, real-time audio and video real time streaming, harsh weather environments, energy constraints and so forth. Network routing can be called an amalgamation of routing protocol and routing algorithm. The job of the routing protocols is to provide a cohesive view of network nodes topology while routing algorithm provides the intelligence in terms of optimal path calculation.We set out to conduct a detailed study of routing protocols in a IP-datagram, wireless ad-hoc and sensor network, and also accomplished routing protocols comparison against the chosen network performance factor dropped packet ratio.Routing protocols play an important role in modern wireless communication networks.Routing pro...
Andre Perez Mobile Networks Architecture Andre Perez Mobile Networks Architecture Новинка

Andre Perez Mobile Networks Architecture

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This book explains the evolutions of architecture for mobiles and summarizes the different technologies: – 2G: the GSM (Global System for Mobile) network, the GPRS (General Packet Radio Service) network and the EDGE (Enhanced Data for Global Evolution) evolution; – 3G: the UMTS (Universal Mobile Telecommunications System) network and the HSPA (High Speed Packet Access) evolutions: – HSDPA (High Speed Downlink Packet Access), – HSUPA (High Speed Uplink Packet Access), – HSPA+; – 4G: the EPS (Evolved Packet System) network. The telephone service and data transmission are the two main services provided by these networks. The evolutions are fundamentally dictated by the increase in the rate of data transmission across the radio interface between the network and mobiles. This book is intended as a readily understandable support to help students and professionals wishing to quickly acquire the main concepts of networks for mobiles understand the technologies deployed.
Andre Carvalho A General Introduction to Data Analytics Andre Carvalho A General Introduction to Data Analytics Новинка

Andre Carvalho A General Introduction to Data Analytics

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A guide to the principles and methods of data analysis that does not require knowledge of statistics or programming A General Introduction to Data Analytics is an essential guide to understand and use data analytics. This book is written using easy-to-understand terms and does not require familiarity with statistics or programming. The authors—noted experts in the field—highlight an explanation of the intuition behind the basic data analytics techniques. The text also contains exercises and illustrative examples. Thought to be easily accessible to non-experts, the book provides motivation to the necessity of analyzing data. It explains how to visualize and summarize data, and how to find natural groups and frequent patterns in a dataset. The book also explores predictive tasks, be them classification or regression. Finally, the book discusses popular data analytic applications, like mining the web, information retrieval, social network analysis, working with text, and recommender systems. The learning resources offer: A guide to the reasoning behind data mining techniques A unique illustrative example that extends throughout all the chapters Exercises at the end of each chapter and larger projects at the end of each of the text’s two main parts Together with these learning resources, the book can be used in a 13-week course guide, one chapter per course topic. The book was written in a format that allows the understanding of the main data analytics concepts by non-mathematicians, non-statisticians and non-computer scientists interested in getting an introduction to data science. A General Introduction to Data Analytics is a basic guide to data analytics written in highly accessible terms.
He You Radar Data Processing With Applications He You Radar Data Processing With Applications Новинка

He You Radar Data Processing With Applications

12081.7 руб. или Купить в рассрочку!
A systematic introduction to the theory, development and latest research results of radar data processing technology • Presents both classical theory and development methods of radar data processing • Provides state-of-the-art research results, including data processing for modern style radars, and tracking performance evaluation theory • Includes coverage of performance evaluation, registration algorithm for Radar network, data processing of passive radar, pulse Doppler radar, and phased array radar • Has applications for those engaged in information engineering, radar engineering, electronic countermeasures, infrared techniques, sonar techniques, and military command
Dzenan Hamzic AAL Data Cluster Analysis. Theory and Implementation Dzenan Hamzic AAL Data Cluster Analysis. Theory and Implementation Новинка

Dzenan Hamzic AAL Data Cluster Analysis. Theory and Implementation

Bachelor Thesis from the year 2016 in the subject Computer Science - Applied, grade: 1, Vienna University of Technology, language: English, abstract: The e-Home project from the Vienna University of Technology is an R&D project with goals of providing assistive technologies for private households of older people with the idea to give them possibilities for longer and independent living in their homes. The e-Home system consists of an adaptive intelligent network of wireless sensors for activity monitoring with a central context-aware embedded system. The primary goal of this thesis is to investigate unsupervised prediction and clustering possibilities of user behaviour based on collected time-series data from infrared temperature sensors in the e-Home enviroment. Three different prediction approaches are described. Hourly Based Event Binning approach is compared to two clustering algorithms, Hierarchical Clustering and Dirichlet Process GMM. Prediction rates are measured on data from three different test persons. This thesis first examines two different approaches for event detection from infrared signal data. In a second stage three different methods for unsupervised prediction analytics are discussed and tested on selected data-sets. Clustering algorithms parameter settings for time-series data have also been discussed and tested in detail. Finally the prediction performance results are compared and each method's advantages and disadvantages have been discussed. The...
Ledley Robert S. Computer Architecture and Security. Fundamentals of Designing Secure Computer Systems Ledley Robert S. Computer Architecture and Security. Fundamentals of Designing Secure Computer Systems Новинка

Ledley Robert S. Computer Architecture and Security. Fundamentals of Designing Secure Computer Systems

9520.13 руб. или Купить в рассрочку!
The first book to introduce computer architecture for security and provide the tools to implement secure computer systems This book provides the fundamentals of computer architecture for security. It covers a wide range of computer hardware, system software and data concepts from a security perspective. It is essential for computer science and security professionals to understand both hardware and software security solutions to survive in the workplace. Examination of memory, CPU architecture and system implementation Discussion of computer buses and a dual-port bus interface Examples cover a board spectrum of hardware and software systems Design and implementation of a patent-pending secure computer system Includes the latest patent-pending technologies in architecture security Placement of computers in a security fulfilled network environment Co-authored by the inventor of the modern Computed Tomography (CT) scanner Provides website for lecture notes, security tools and latest updates
Hengqing Tong Developing Econometrics Hengqing Tong Developing Econometrics Новинка

Hengqing Tong Developing Econometrics

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Statistical Theories and Methods with Applications to Economics and Business highlights recent advances in statistical theory and methods that benefit econometric practice. It deals with exploratory data analysis, a prerequisite to statistical modelling and part of data mining. It provides recently developed computational tools useful for data mining, analysing the reasons to do data mining and the best techniques to use in a given situation. Provides a detailed description of computer algorithms. Provides recently developed computational tools useful for data mining Highlights recent advances in statistical theory and methods that benefit econometric practice. Features examples with real life data. Accompanying software featuring DASC (Data Analysis and Statistical Computing). Essential reading for practitioners in any area of econometrics; business analysts involved in economics and management; and Graduate students and researchers in economics and statistics.
Mahfudzah Othman, Mohammad Hafiz Ismail, Alif Faisal Ibrahim Computing Research . Innovation (CRINN), Vol.1, November 2016 Mahfudzah Othman, Mohammad Hafiz Ismail, Alif Faisal Ibrahim Computing Research . Innovation (CRINN), Vol.1, November 2016 Новинка

Mahfudzah Othman, Mohammad Hafiz Ismail, Alif Faisal Ibrahim Computing Research . Innovation (CRINN), Vol.1, November 2016

The publication of this book, CRINN (Computing Research and Innovation), Volume 1, November 2016, is a compilation of peer-reviewed research papers, technical and concept papers and innovations among the academicians from Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Perlis Branch, and other universities from all over Malaysia. This volume comprises 14 scholarly articles from Computer Sciences, Mathematical Sciences, Computer Network and Data Communications and Information Technology and System Sciences fields.
Richard Brath Graph Analysis and Visualization. Discovering Business Opportunity in Linked Data Richard Brath Graph Analysis and Visualization. Discovering Business Opportunity in Linked Data Новинка

Richard Brath Graph Analysis and Visualization. Discovering Business Opportunity in Linked Data

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Wring more out of the data with a scientific approach to analysis Graph Analysis and Visualization brings graph theory out of the lab and into the real world. Using sophisticated methods and tools that span analysis functions, this guide shows you how to exploit graph and network analytic techniques to enable the discovery of new business insights and opportunities. Published in full color, the book describes the process of creating powerful visualizations using a rich and engaging set of examples from sports, finance, marketing, security, social media, and more. You will find practical guidance toward pattern identification and using various data sources, including Big Data, plus clear instruction on the use of software and programming. The companion website offers data sets, full code examples in Python, and links to all the tools covered in the book. Science has already reaped the benefit of network and graph theory, which has powered breakthroughs in physics, economics, genetics, and more. This book brings those proven techniques into the world of business, finance, strategy, and design, helping extract more information from data and better communicate the results to decision-makers. Study graphical examples of networks using clear and insightful visualizations Analyze specifically-curated, easy-to-use data sets from various industries Learn the software tools and programming languages that extract insights from data Code examples using the popular Python programming language There is a tremendous body of scientific work on network and graph theory, but very little of it directly applies to analyst functions outside of the core sciences – until now. Written for those seeking empirically based, systematic analysis methods and powerful tools that apply outside the lab, Graph Analysis and Visualization is a thorough, authoritative resource.
Ashwin Dhivakar To Implement a Multi-Level Security in Cloud Computing Using Cryptography Novel Approach Ashwin Dhivakar To Implement a Multi-Level Security in Cloud Computing Using Cryptography Novel Approach Новинка

Ashwin Dhivakar To Implement a Multi-Level Security in Cloud Computing Using Cryptography Novel Approach

Master's Thesis from the year 2014 in the subject Computer Science - IT-Security, Lovely Professional University, course: M.Tech (Computer Science and Engineering), language: English, comment: Thank you everyone for helping me throughout this phase of my life..!! , abstract: Currently cloud computing environments have come up with a serious problem known as security which is in terms of Confidentiality of Data, Integrity of the Message and Authenticity of the users (CIA). Since user's personal data is being stored in an unencrypted format on a remote machine operated by third party vendors who provide various services, the impact of user's identity and unauthorized access or disclosure of files are very high. Though we have various techniques and algorithms to protect our data from hackers and intruders still cloud environments are prone to other attacks. In this paper, a novel approach is implemented to protect user's confidential data from third party service providers, and also to make sure that the data is not disclosed to any unauthentic user or the service provider even, in any cloud environments. This approach provides a multi-level security in three aspects: 1) User authentication for "authorization" to enter the network, 2) Image Sequencing password for "authentication" wherein it is proved that the identity is original user, and 3) RSA algorithm to encrypt the data further for providing "data integrity". Thus this approach pro...
Malekmohammadi Najmeh, Farid Mahboubeh The Application of Data Envelopment Analysis to Queuing System Malekmohammadi Najmeh, Farid Mahboubeh The Application of Data Envelopment Analysis to Queuing System Новинка

Malekmohammadi Najmeh, Farid Mahboubeh The Application of Data Envelopment Analysis to Queuing System

In this work, the relations between data envelopment analysis and queuing models are proposed. Via our new approach, some drawbacks of the previously methods for large scale computer networks are rectified. Meanwhile the proposed method is also defined for fuzzy queuing models. The major goal of our new aspect is the relation between DEA and queuing system which has been rarely noticed by researchers. Also, we want to show that how DEA can increase the overall efficiency in any system. Our main aim is the capability and the usage of DEA even in queuing system. The objectives of the work are to: Defining a technique for evaluating the operational efficiency of large-scale computer networks via data envelopment analysis and queuing models. Determining an approach for evaluation of efficiency in fuzzy queuing models with publicity and renouncement.
Gregory Bassett A. Multimedia Networks. Protocols, Design and Applications Gregory Bassett A. Multimedia Networks. Protocols, Design and Applications Новинка

Gregory Bassett A. Multimedia Networks. Protocols, Design and Applications

7736.87 руб. или Купить в рассрочку!
The transportation of multimedia over the network requires timely and errorless transmission much more strictly than other data. This had led to special protocols and to special treatment in multimedia applications (telephony, IP-TV, streaming) to overcome network issues. This book begins with an overview of the vast market combined with the user’s expectations. The base mechanisms of the audio/video coding (H.26x etc.) are explained to understand characteristics of the generated network traffic. Further chapters treat common specialized underlying IP network functions which cope with multimedia data in conjunction which special time adaption measures. Based on those standard functions these chapters can treat uniformly SIP, H.248, High-End IP-TV, Webcast, Signage etc. A special section is devoted to home networks which challenge high-end service delivery due to possibly unreliable management. The whole book treats concepts described in accessible IP-based standards and which are implemented broadly. The book is aimed at graduate students/practitioners with good basic knowledge in computer networking. It provides the reader with all concepts of currently used IP technologies of how to deliver multimedia efficiently to the end user.
Indra Gunawan Fundamentals of Reliability Engineering. Applications in Multistage Interconnection Networks Indra Gunawan Fundamentals of Reliability Engineering. Applications in Multistage Interconnection Networks Новинка

Indra Gunawan Fundamentals of Reliability Engineering. Applications in Multistage Interconnection Networks

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This book presents fundamentals of reliability engineering with its applications in evaluating reliability of multistage interconnection networks. In the first part of the book, it introduces the concept of reliability engineering, elements of probability theory, probability distributions, availability and data analysis. The second part of the book provides an overview of parallel/distributed computing, network design considerations, and more. The book covers a comprehensive reliability engineering methods and its practical aspects in the interconnection network systems. Students, engineers, researchers, managers will find this book as a valuable reference source.
Smirnov Aleksandr, Shtreker Evgeniy, Pavel Nabrodov Projekt Von Aleksandr Smirnov Aleksandr, Shtreker Evgeniy, Pavel Nabrodov Projekt Von Aleksandr Новинка

Smirnov Aleksandr, Shtreker Evgeniy, Pavel Nabrodov Projekt Von Aleksandr

The monograph will be interesting for young scientists in the field of telecommunications In the work are the main principles of parallel telecommunication systems. In the basis of these principles lies parallel processing of data and development of telecommunication devices on a parallel basis. For the following theoretical base was used system of residual classes. Data in this system can be processed in parallel without transfer digits. Elements of telecommunications proposed to implement in the neural network which has parallelism and the ability to learn or setting up an obstacle. In the basis of the book lies the theory of transfer and processing of parallel data by parallel elements of telecommunications. The book offered some of neural networks and put some outstanding issues, such as training of neural networks in the mirror mathematics.
John Chirillo Hack Attacks Revealed. A Complete Reference with Custom Security Hacking Toolkit John Chirillo Hack Attacks Revealed. A Complete Reference with Custom Security Hacking Toolkit Новинка

John Chirillo Hack Attacks Revealed. A Complete Reference with Custom Security Hacking Toolkit

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The #1 menace for computer systems worldwide, network hacking can result in mysterious server crashes, data loss, and other problems that are not only costly to fix but difficult to recognize. Author John Chirillo knows how these can be prevented, and in this book he brings to the table the perspective of someone who has been invited to break into the networks of many Fortune 1000 companies in order to evaluate their security policies and conduct security audits. He gets inside every detail of the hacker's world, including how hackers exploit security holes in private and public networks and how network hacking tools work. As a huge value-add, the author is including the first release of a powerful software hack attack tool that can be configured to meet individual customer needs.
Nadeem Akhtar, Faraz Khan, Faridul Haque Siddiqui Statistical Analysis of Continuous Data Streams Using DSMS Nadeem Akhtar, Faraz Khan, Faridul Haque Siddiqui Statistical Analysis of Continuous Data Streams Using DSMS Новинка

Nadeem Akhtar, Faraz Khan, Faridul Haque Siddiqui Statistical Analysis of Continuous Data Streams Using DSMS

Several applications involve a transient stream of data which has to be modeled and analyzed continuously. Their continuous arrival in multiple, rapid, time-varying and possibly unpredictable and unbounded way make the analysis difficult and opens fundamentally new research problems. Examples of such data intensive applications include stock market, road traffic analysis, whether forecasting systems etc. Data Stream Management Systems are specifically designed for handling continuous data streams. They can handle multiple, time-varying, unpredictable and unbounded streams which cannot be handled using traditional tools. In this work, we have used a Data Stream Management System- Stanford STREAM in three different application domain namely Road Traffic analysis, Habitat Monitoring analysis and Network Packet analysis. We have also used another DSMS, telegraphCQ, coupled with jamdroid, an open source road traffic analysis system, for mining road traffic data.
Contemporary Perspectives in Data Mining, Volume 2 Contemporary Perspectives in Data Mining, Volume 2 Новинка

Contemporary Perspectives in Data Mining, Volume 2

A volume in Contemporary Perspectives in Data MiningSeries Editors Kenneth D. Lawrence, New Jersey Institute of Technologyand Ronald K. Klimberg, Saint Joseph's UniversityThe series, Contemporary Perspectives on Data Mining, is composed of blind refereed scholarlyresearch methods and applications of data mining. This series will be targeted both at theacademic community, as well as the business practitioner.Data mining seeks to discover knowledge from vast amounts of data with the use of statisticaland mathematical techniques. The knowledge is extracted from this data by examining thepatterns of the data, whether they be associations of groups or things, predictions, sequentialrelationships between time order events or natural groups.Data mining applications are in marketing (customer loyalty, identifying profitable customers, instorepromotions, e-commerce populations); in business (teaching data mining, efficiency of the Chinese automobile industry, moderateasset allocation funds); and techniques (veterinary predictive models, data integrity in the cloud, irregular pattern detection in amobility network and road safety modeling.)
Johnson Wayne P. Making Sense of Data I. A Practical Guide to Exploratory Data Analysis and Data Mining Johnson Wayne P. Making Sense of Data I. A Practical Guide to Exploratory Data Analysis and Data Mining Новинка

Johnson Wayne P. Making Sense of Data I. A Practical Guide to Exploratory Data Analysis and Data Mining

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Praise for the First Edition “…a well-written book on data analysis and data mining that provides an excellent foundation…” —CHOICE “This is a must-read book for learning practical statistics and data analysis…” —Computing Reviews.com A proven go-to guide for data analysis, Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining, Second Edition focuses on basic data analysis approaches that are necessary to make timely and accurate decisions in a diverse range of projects. Based on the authors’ practical experience in implementing data analysis and data mining, the new edition provides clear explanations that guide readers from almost every field of study. In order to facilitate the needed steps when handling a data analysis or data mining project, a step-by-step approach aids professionals in carefully analyzing data and implementing results, leading to the development of smarter business decisions. The tools to summarize and interpret data in order to master data analysis are integrated throughout, and the Second Edition also features: Updated exercises for both manual and computer-aided implementation with accompanying worked examples New appendices with coverage on the freely available Traceis™ software, including tutorials using data from a variety of disciplines such as the social sciences, engineering, and finance New topical coverage on multiple linear regression and logistic regression to provide a range of widely used and transparent approaches Additional real-world examples of data preparation to establish a practical background for making decisions from data Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining, Second Edition is an excellent reference for researchers and professionals who need to achieve effective decision making from data. The Second Edition is also an ideal textbook for undergraduate and graduate-level courses in data analysis and data mining and is appropriate for cross-disciplinary courses found within computer science and engineering departments.
Leslie Jones, Eugene Kennedy A Guide to Data-Driven Leadership in Modern Schools Leslie Jones, Eugene Kennedy A Guide to Data-Driven Leadership in Modern Schools Новинка

Leslie Jones, Eugene Kennedy A Guide to Data-Driven Leadership in Modern Schools

The purpose of this publication is to provide school leaders and other educatorswith insight into practical uses of data and how to create school culturesconducive to effective data use. Practicing school leaders can benefit from thispublication as well as teachers who use data in their classrooms to driveinstruction. Another use of this book is for graduate schools that prepare K-12school leaders.Because of accountability and the importance of data use in schools, data drivendecisions and the effective use of data are critical. In A Guide to Data-DrivenLeadership in Modern Schools, the use of data as aligned to educational reform isdiscussed. Accountability and standardized testing are vital elements of reform.The culture must be created in schools to address multi- facets of data use which is presented in Chapter 2 of thepublication.The use of data should guide/inform decisions linked to both management and instruction in schools. In Chapter3, the use of data to inform management is discussed; and the use of data to inform instruction is presented inChapter 4. Practices of effective management and instructional leadership are obsolete without effectivepersonnel in schools. The use of data in personnel evaluations is explored in Chapter 5.
Galit Shmueli Data Mining for Business Analytics. Concepts, Techniques, and Applications with XLMiner Galit Shmueli Data Mining for Business Analytics. Concepts, Techniques, and Applications with XLMiner Новинка

Galit Shmueli Data Mining for Business Analytics. Concepts, Techniques, and Applications with XLMiner

10194.04 руб. или Купить в рассрочку!
Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner®, Third Edition presents an applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies. Readers will work with all of the standard data mining methods using the Microsoft® Office Excel® add-in XLMiner® to develop predictive models and learn how to obtain business value from Big Data. Featuring updated topical coverage on text mining, social network analysis, collaborative filtering, ensemble methods, uplift modeling and more, the Third Edition also includes: Real-world examples to build a theoretical and practical understanding of key data mining methods End-of-chapter exercises that help readers better understand the presented material Data-rich case studies to illustrate various applications of data mining techniques Completely new chapters on social network analysis and text mining A companion site with additional data sets, instructors material that include solutions to exercises and case studies, and Microsoft PowerPoint® slides Free 140-day license to use XLMiner for Education software Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner®, Third Edition is an ideal textbook for upper-undergraduate and graduate-level courses as well as professional programs on data mining, predictive modeling, and Big Data analytics. The new edition is also a unique reference for analysts, researchers, and practitioners working with predictive analytics in the fields of business, finance, marketing, computer science, and information technology. Praise for the Second Edition «…full of vivid and thought-provoking anecdotes… needs to be read by anyone with a serious interest in research and marketing.»– Research Magazine «Shmueli et al. have done a wonderful job in presenting the field of data mining – a welcome addition to the literature.» – ComputingReviews.com «Excellent choice for business analysts…The book is a perfect fit for its intended audience.» – Keith McCormick, Consultant and Author of SPSS Statistics For Dummies, Third Edition and SPSS Statistics for Data Analysis and Visualization Galit Shmueli, PhD, is Distinguished Professor at National Tsing Hua University’s Institute of Service Science. She has designed and instructed data mining courses since 2004 at University of Maryland, Statistics.com, The Indian School of Business, and National Tsing Hua University, Taiwan. Professor Shmueli is known for her research and teaching in business analytics, with a focus on statistical and data mining methods in information systems and healthcare. She has authored over 70 journal articles, books, textbooks and book chapters. Peter C. Bruce is President and Founder of the Institute for Statistics Education at www.statistics.com. He has written multiple journal articles and is the developer of Resampling Stats software. He is the author of Introductory Statistics and Analytics: A Resampling Perspective, also published by Wiley. Nitin R. Patel, PhD, is Chairman and cofounder of Cytel, Inc., based in Cambridge, Massachusetts. A Fellow of the American Statistical Association, Dr. Patel has also served as a Visiting Professor at the Massachusetts Institute of Technology and at Harvard University. He is a Fellow of the Computer Society of India and was a professor at the Indian Institute of Management, Ahmedabad for 15 years.
Vikas Rajole Causes of Data Breaches and Preventive Measures. Data Loss Prevention Vikas Rajole Causes of Data Breaches and Preventive Measures. Data Loss Prevention Новинка

Vikas Rajole Causes of Data Breaches and Preventive Measures. Data Loss Prevention

Technical Report from the year 2012 in the subject Computer Science - Applied, grade: none, Royal Holloway, University of London, course: M.Sc. Information Security, language: English, abstract: As technology evolves, the threat landscape evolves. The threat landscape has changed frommere script kiddies for fun to organised cyber crime to steal data for identity theft andmonetary gains.It is very important to protect the business data from all kind of data breach attacks in orderto maintain the brand reputation and customer faith. New laws and governance policiesmake it mandatory for organisations to protect customer data. This project talks about thedifferent effect of data breaches and preventive measures. This project targets mostly on the'confidentiality' trait of the information security's CIA triad.
Giudici Paolo Applied Data Mining for Business and Industry Giudici Paolo Applied Data Mining for Business and Industry Новинка

Giudici Paolo Applied Data Mining for Business and Industry

14203.43 руб. или Купить в рассрочку!
The increasing availability of data in our current, information overloaded society has led to the need for valid tools for its modelling and analysis. Data mining and applied statistical methods are the appropriate tools to extract knowledge from such data. This book provides an accessible introduction to data mining methods in a consistent and application oriented statistical framework, using case studies drawn from real industry projects and highlighting the use of data mining methods in a variety of business applications. Introduces data mining methods and applications. Covers classical and Bayesian multivariate statistical methodology as well as machine learning and computational data mining methods. Includes many recent developments such as association and sequence rules, graphical Markov models, lifetime value modelling, credit risk, operational risk and web mining. Features detailed case studies based on applied projects within industry. Incorporates discussion of data mining software, with case studies analysed using R. Is accessible to anyone with a basic knowledge of statistics or data analysis. Includes an extensive bibliography and pointers to further reading within the text. Applied Data Mining for Business and Industry, 2nd edition is aimed at advanced undergraduate and graduate students of data mining, applied statistics, database management, computer science and economics. The case studies will provide guidance to professionals working in industry on projects involving large volumes of data, such as customer relationship management, web design, risk management, marketing, economics and finance.
Matthew Monte Network Attacks and Exploitation. A Framework Matthew Monte Network Attacks and Exploitation. A Framework Новинка

Matthew Monte Network Attacks and Exploitation. A Framework

3398.49 руб. или Купить в рассрочку!
Incorporate offense and defense for a more effective network security strategy Network Attacks and Exploitation provides a clear, comprehensive roadmap for developing a complete offensive and defensive strategy to engage in or thwart hacking and computer espionage. Written by an expert in both government and corporate vulnerability and security operations, this guide helps you understand the principles of the space and look beyond the individual technologies of the moment to develop durable comprehensive solutions. Numerous real-world examples illustrate the offensive and defensive concepts at work, including Conficker, Stuxnet, the Target compromise, and more. You will find clear guidance toward strategy, tools, and implementation, with practical advice on blocking systematic computer espionage and the theft of information from governments, companies, and individuals. Assaults and manipulation of computer networks are rampant around the world. One of the biggest challenges is fitting the ever-increasing amount of information into a whole plan or framework to develop the right strategies to thwart these attacks. This book clears the confusion by outlining the approaches that work, the tools that work, and resources needed to apply them. Understand the fundamental concepts of computer network exploitation Learn the nature and tools of systematic attacks Examine offensive strategy and how attackers will seek to maintain their advantage Understand defensive strategy, and how current approaches fail to change the strategic balance Governments, criminals, companies, and individuals are all operating in a world without boundaries, where the laws, customs, and norms previously established over centuries are only beginning to take shape. Meanwhile computer espionage continues to grow in both frequency and impact. This book will help you mount a robust offense or a strategically sound defense against attacks and exploitation. For a clear roadmap to better network security, Network Attacks and Exploitation is your complete and practical guide.
Matthias Dehmer Applied Statistics for Network Biology. Methods in Systems Biology Matthias Dehmer Applied Statistics for Network Biology. Methods in Systems Biology Новинка

Matthias Dehmer Applied Statistics for Network Biology. Methods in Systems Biology

14192.14 руб. или Купить в рассрочку!
The book introduces to the reader a number of cutting edge statistical methods which can e used for the analysis of genomic, proteomic and metabolomic data sets. In particular in the field of systems biology, researchers are trying to analyze as many data as possible in a given biological system (such as a cell or an organ). The appropriate statistical evaluation of these large scale data is critical for the correct interpretation and different experimental approaches require different approaches for the statistical analysis of these data. This book is written by biostatisticians and mathematicians but aimed as a valuable guide for the experimental researcher as well computational biologists who often lack an appropriate background in statistical analysis.
Peter Andres Untracked activities. How users of fitness trackers value their generated data Peter Andres Untracked activities. How users of fitness trackers value their generated data Новинка

Peter Andres Untracked activities. How users of fitness trackers value their generated data

Bachelor Thesis from the year 2017 in the subject Computer Science - Commercial Information Technology, grade: 1,3, University of Frankfurt (Main), language: English, abstract: Nowadays, people do not only pursue an activity in order to stay healthy, they track this activity to gain a rational judgement about their activity. Through this data, the user gains insights into intangible metrics of everyday life in order to simplify daily activities due to the transparency of the generated data.Is this data more than just the simplification of everyday life? How do the users value their generated data? This thesis focuses on the question of how users value their data generated through tracking. Furthermore, it will be investigated what emphasizes the feeling of loss if an activity remains inadvertently untracked.This bachelor thesis solely focuses on the subjective valuation of data generated through tracking physical activities. To evaluate the subjective value, this work differentiates between activities that the users tracks and activities that accidentally remain unmonitored. This work assumes that this difference between these activities is the added value of tracking data. To evaluate possible factors that emphasize the value of perceived value of data an empirical study is conducted. This study examines the influence of personality traits on the value of data. Furthermore, the users' level of engagement in social comparison to evaluate his or her abilities and levels of...
Tai Doan Convolutional Neural Network in classifying scanned documents Tai Doan Convolutional Neural Network in classifying scanned documents Новинка

Tai Doan Convolutional Neural Network in classifying scanned documents

Internship Report from the year 2016 in the subject Computer Science - Applied, University of Science and Technology of Hanoi, course: Internship, language: English, abstract: In this project, I created and augmented a dataset from a number of given images to train and test convolutional neural network which is used to classify five classes of images of scanned documents. In order to generate the dataset, some image processing techniques were applied such as sliding-window, rotating, flipping and pyramid-sizing. The result of this phase is a set of images having same size 244x224x3. These images after being labeled were divided into three dataset for training, validating and testing the network. The network is a simple convolution neural network which is also called LeNet. It has three convolutional layers and one fully connected layer. After being trained and validated, the best state of the network was pointed out and tested on the testing dataset and some real images. The result showed that the LeNet was able to classify images of documents in a pretty high accuracy. At the end of the project, I modified the network and discussed the affect that those changes had on the network with the purpose of creating another similar network which can perform better than the original one. The result proved that it worked a little better than its original version.
Martin Fink Crossings, Curves, and Constraints in Graph Drawing Martin Fink Crossings, Curves, and Constraints in Graph Drawing Новинка

Martin Fink Crossings, Curves, and Constraints in Graph Drawing

The visualization of data is an important topic in computer science; with an increasing amount of data available, making data sets well-readable for users is a frequent task. A lot of data that contains connections between persons or objects can be represented as a graph. Hence, graph drawing, that is, the visualization of graphs, is a specialized research area.This book covers research results in different areas of graph drawing. Its focus is on drawing metro maps and on labeling maps with external labels that are connected to the points of interest by lines. In both areas, the use of curves and the effects of crossings are investigated.
Tasneem A. Rizvi Latest Curve Approximation Techniques Tasneem A. Rizvi Latest Curve Approximation Techniques Новинка

Tasneem A. Rizvi Latest Curve Approximation Techniques

Digital representation of curves and surface involves geometric modeling techniques that are used for efficient acquisition, reconstruction and analysis of 2D and 3D objects. Curve approximation techniques are used for modeling the digital representation of object. In computing the approximated curves, efficient data point's approximation is a challenge mostly found in many applications of Computer Aided Geometric Design (CAGD), as the available techniques mostly uses data parametrization for curve approximation. Data parametrization involves complex computations which lead to processing overhead.
Bangjun Lei Classification, Parameter Estimation and State Estimation. An Engineering Approach Using MATLAB Bangjun Lei Classification, Parameter Estimation and State Estimation. An Engineering Approach Using MATLAB Новинка

Bangjun Lei Classification, Parameter Estimation and State Estimation. An Engineering Approach Using MATLAB

9816.51 руб. или Купить в рассрочку!
A practical introduction to intelligent computer vision theory, design, implementation, and technology The past decade has witnessed epic growth in image processing and intelligent computer vision technology. Advancements in machine learning methods—especially among adaboost varieties and particle filtering methods—have made machine learning in intelligent computer vision more accurate and reliable than ever before. The need for expert coverage of the state of the art in this burgeoning field has never been greater, and this book satisfies that need. Fully updated and extensively revised, this 2nd Edition of the popular guide provides designers, data analysts, researchers and advanced post-graduates with a fundamental yet wholly practical introduction to intelligent computer vision. The authors walk you through the basics of computer vision, past and present, and they explore the more subtle intricacies of intelligent computer vision, with an emphasis on intelligent measurement systems. Using many timely, real-world examples, they explain and vividly demonstrate the latest developments in image and video processing techniques and technologies for machine learning in computer vision systems, including: PRTools5 software for MATLAB—especially the latest representation and generalization software toolbox for PRTools5 Machine learning applications for computer vision, with detailed discussions of contemporary state estimation techniques vs older content of particle filter methods The latest techniques for classification and supervised learning, with an emphasis on Neural Network, Genetic State Estimation and other particle filter and AI state estimation methods All new coverage of the Adaboost and its implementation in PRTools5. A valuable working resource for professionals and an excellent introduction for advanced-level students, this 2nd Edition features a wealth of illustrative examples, ranging from basic techniques to advanced intelligent computer vision system implementations. Additional examples and tutorials, as well as a question and solution forum, can be found on a companion website.
Galit Shmueli Data Mining for Business Analytics. Concepts, Techniques, and Applications in R Galit Shmueli Data Mining for Business Analytics. Concepts, Techniques, and Applications in R Новинка

Galit Shmueli Data Mining for Business Analytics. Concepts, Techniques, and Applications in R

10194.04 руб. или Купить в рассрочку!
Data Mining for Business Analytics: Concepts, Techniques, and Applications in R presents an applied approach to data mining concepts and methods, using R software for illustration Readers will learn how to implement a variety of popular data mining algorithms in R (a free and open-source software) to tackle business problems and opportunities. This is the fifth version of this successful text, and the first using R. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes: • Two new co-authors, Inbal Yahav and Casey Lichtendahl, who bring both expertise teaching business analytics courses using R, and data mining consulting experience in business and government • Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students • More than a dozen case studies demonstrating applications for the data mining techniques described • End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented • A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions Data Mining for Business Analytics: Concepts, Techniques, and Applications in R is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology. “ This book has by far the most comprehensive review of business analytics methods that I have ever seen, covering everything from classical approaches such as linear and logistic regression, through to modern methods like neural networks, bagging and boosting, and even much more business specific procedures such as social network analysis and text mining. If not the bible, it is at the least a definitive manual on the subject.” Gareth M. James, University of Southern California and co-author (with Witten, Hastie and Tibshirani) of the best-selling book An Introduction to Statistical Learning, with Applications in R Galit Shmueli, PhD, is Distinguished Professor at National Tsing Hua University’s Institute of Service Science. She has designed and instructed data mining courses since 2004 at University of Maryland, Statistics.com, Indian School of Business, and National Tsing Hua University, Taiwan. Professor Shmueli is known for her research and teaching in business analytics, with a focus on statistical and data mining methods in information systems and healthcare. She has authored over 70 publications including books. Peter C. Bruce is President and Founder of the Institute for Statistics Education at Statistics.com. He has written multiple journal articles and is the developer of Resampling Stats software. He is the author of Introductory Statistics and Analytics: A Resampling Perspective (Wiley) and co-author of Practical Statistics for Data Scientists: 50 Essential Concepts (O’Reilly). Inbal Yahav, PhD, is Professor at the Graduate School of Business Administration at Bar-Ilan University, Israel. She teaches courses in social network analysis, advanced research methods, and software quality assurance. Dr. Yahav received her PhD in Operations Research and Data Mining from the University of Maryland, College Park. Nitin R. Patel, PhD, is Chairman and cofounder of Cytel, Inc., based in Cambridge, Massachusetts. A Fellow of the American St
Helen Armstrong Social Network Analysis with Applications Helen Armstrong Social Network Analysis with Applications Новинка

Helen Armstrong Social Network Analysis with Applications

8075.72 руб. или Купить в рассрочку!
A comprehensive introduction to social network analysis that hones in on basic centrality measures, social links, subgroup analysis, data sources, and more Written by military, industry, and business professionals, this book introduces readers to social network analysis, the new and emerging topic that has recently become of significant use for industry, management, law enforcement, and military practitioners for identifying both vulnerabilities and opportunities in collaborative networked organizations. Focusing on models and methods for the analysis of organizational risk, Social Network Analysis with Applications provides easily accessible, yet comprehensive coverage of network basics, centrality measures, social link theory, subgroup analysis, relational algebra, data sources, and more. Examples of mathematical calculations and formulas for social network measures are also included. Along with practice problems and exercises, this easily accessible book covers: The basic concepts of networks, nodes, links, adjacency matrices, and graphs Mathematical calculations and exercises for centrality, the basic measures of degree, betweenness, closeness, and eigenvector centralities Graph-level measures, with a special focus on both the visual and numerical analysis of networks Matrix algebra, outlining basic concepts such as matrix addition, subtraction, multiplication, and transpose and inverse calculations in linear algebra that are useful for developing networks from relational data Meta-networks and relational algebra, social links, diffusion through networks, subgroup analysis, and more An excellent resource for practitioners in industry, management, law enforcement, and military intelligence who wish to learn and apply social network analysis to their respective fields, Social Network Analysis with Applications is also an ideal text for upper-level undergraduate and graduate level courses and workshops on the subject.
Rajesh Prasad Optimizing the Performance of a WMN using Network Coding Rajesh Prasad Optimizing the Performance of a WMN using Network Coding Новинка

Rajesh Prasad Optimizing the Performance of a WMN using Network Coding

This book presents the design, testbed implementation and evaluation of XOR-Top, a protocol that uses local topology information for network coding for unicast transmission in wireless mesh networks. One of the main constraints in a wireless mesh network is limited bandwidth. Network coding has shown great potential to improve the overall throughput of wireless networks with broadcast nature. In this book, we have harnessed the benefits of network coding to improve the network throughput of a wireless mesh network which uses a omnidirectional broadcast. In this work, we implement and evaluate a new encoding strategy, XOR-Top, which relies on local topology information, and uses bitwise XOR for packet coding. In essence, we can say that in this book we have studied local topology assisted network coding, designed a new protocol (XOR-Top), verified the correctness of the new coding schemes by simulation as well as experimental testbed and completed the performance analysis of data collected by simulation and experiments.
Bojan Milicevic Principles of Interface Design and the Representation of Semantic Data Bojan Milicevic Principles of Interface Design and the Representation of Semantic Data Новинка

Bojan Milicevic Principles of Interface Design and the Representation of Semantic Data

The semantic approach to data storage, management and extraction is a promising concept that has constantly been gaining importance during the past years. However, the visualization of semantic data systems as well as the functionalities of their interfaces still contain some obstacles for both, the interaction designer and the interacting user. In order to accommodate to those obstacles, the interaction designer has to come up with an intuitive and efficient user interface design, introducing inexperienced users to data representation and extraction in a semantic environment. The intention of this work is to provide an overview over the disciplines of Human Computer Interaction and Interaction Design, with the intention to mediate the essential human-based and technical processes influencing the design of interaction, with a focus on the organisation and representation of unstructured, semantically rich data.
Norman Schneidewind F. Computer, Network, Software, and Hardware Engineering with Applications Norman Schneidewind F. Computer, Network, Software, and Hardware Engineering with Applications Новинка

Norman Schneidewind F. Computer, Network, Software, and Hardware Engineering with Applications

11976.94 руб. или Купить в рассрочку!
There are many books on computers, networks, and software engineering but none that integrate the three with applications. Integration is important because, increasingly, software dominates the performance, reliability, maintainability, and availability of complex computer and systems. Books on software engineering typically portray software as if it exists in a vacuum with no relationship to the wider system. This is wrong because a system is more than software. It is comprised of people, organizations, processes, hardware, and software. All of these components must be considered in an integrative fashion when designing systems. On the other hand, books on computers and networks do not demonstrate a deep understanding of the intricacies of developing software. In this book you will learn, for example, how to quantitatively analyze the performance, reliability, maintainability, and availability of computers, networks, and software in relation to the total system. Furthermore, you will learn how to evaluate and mitigate the risk of deploying integrated systems. You will learn how to apply many models dealing with the optimization of systems. Numerous quantitative examples are provided to help you understand and interpret model results. This book can be used as a first year graduate course in computer, network, and software engineering; as an on-the-job reference for computer, network, and software engineers; and as a reference for these disciplines.
Marcelo Mendonça Teixeira, Tiago Alessandro Espínola Ferreira The Communication Model of Virtual Universe Marcelo Mendonça Teixeira, Tiago Alessandro Espínola Ferreira The Communication Model of Virtual Universe Новинка

Marcelo Mendonça Teixeira, Tiago Alessandro Espínola Ferreira The Communication Model of Virtual Universe

Research Paper (postgraduate) from the year 2013 in the subject Communications - Theories, Models, Terms and Definitions, grade: College and University, Federal Rural University of Pernambuco (Statistics and Informatics Departament), course: Computer Science, language: English, abstract: The virtual environments can be considered as one of the factors driving the transformation of mass media, associating new forms in network communication and making the information more accessible to any person that has access to the worldwide network of computers, promoting the production and dissemination of information in science and technology for teaching and research in all areas of knowledge and different sectors of society. In this sense, our book plans to explore the communication in cyber universe, as well, the influence of ICT and cyberculture to network society.
Leonhard Korowajczuk LTE, WiMAX and WLAN Network Design, Optimization and Performance Analysis Leonhard Korowajczuk LTE, WiMAX and WLAN Network Design, Optimization and Performance Analysis Новинка

Leonhard Korowajczuk LTE, WiMAX and WLAN Network Design, Optimization and Performance Analysis

13512.45 руб. или Купить в рассрочку!
A technological overview of LTE and WiMAX LTE, WiMAX and WLAN Network Design, Optimization and Performance Analysis provides a practical guide to LTE and WiMAX technologies introducing various tools and concepts used within. In addition, topics such as traffic modelling of IP-centric networks, RF propagation, fading, mobility, and indoor coverage are explored; new techniques which increase throughput such as MIMO and AAS technology are highlighted; and simulation, network design and performance analysis are also examined. Finally, in the latter part of the book Korowajczuk gives a step-by-step guide to network design, providing readers with the capability to build reliable and robust data networks. By focusing on LTE and WiMAX this book extends current network planning approaches to next generation wireless systems based on OFDMA, providing an essential resource for engineers and operators of fixed and wireless broadband data access networks. With information presented in a sequential format, LTE, WiMAX and WLAN Network Design, Optimization and Performance Analysis aids a progressive development of knowledge, complementing latter graduate and postgraduate courses while also providing a valuable resource to network designers, equipment vendors, reference material, operators, consultants, and regulators. Key Features: One of the first books to comprehensively explain and evaluate LTE Provides an unique explanation of the basic concepts involved in wireless broadband technologies and their applications in LTE, WiMAX, and WLAN before progressing to the network design Demonstrates the application of network planning for LTE and WiMAX with theoretical and practical approaches Includes all aspects of system design and optimization, such as dynamic traffic simulations, multi-layered traffic analysis, statistical interference analysis, and performance estimations
Harvey Goldstein Methodological Developments in Data Linkage Harvey Goldstein Methodological Developments in Data Linkage Новинка

Harvey Goldstein Methodological Developments in Data Linkage

6705.29 руб. или Купить в рассрочку!
A comprehensive compilation of new developments in data linkage methodology The increasing availability of large administrative databases has led to a dramatic rise in the use of data linkage, yet the standard texts on linkage are still those which describe the seminal work from the 1950-60s, with some updates. Linkage and analysis of data across sources remains problematic due to lack of discriminatory and accurate identifiers, missing data and regulatory issues. Recent developments in data linkage methodology have concentrated on bias and analysis of linked data, novel approaches to organising relationships between databases and privacy-preserving linkage. Methodological Developments in Data Linkage brings together a collection of contributions from members of the international data linkage community, covering cutting edge methodology in this field. It presents opportunities and challenges provided by linkage of large and often complex datasets, including analysis problems, legal and security aspects, models for data access and the development of novel research areas. New methods for handling uncertainty in analysis of linked data, solutions for anonymised linkage and alternative models for data collection are also discussed. Key Features: Presents cutting edge methods for a topic of increasing importance to a wide range of research areas, with applications to data linkage systems internationally Covers the essential issues associated with data linkage today Includes examples based on real data linkage systems, highlighting the opportunities, successes and challenges that the increasing availability of linkage data provides Novel approach incorporates technical aspects of both linkage, management and analysis of linked data This book will be of core interest to academics, government employees, data holders, data managers, analysts and statisticians who use administrative data. It will also appeal to researchers in a variety of areas, including epidemiology, biostatistics, social statistics, informatics, policy and public health.

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Data Mining for Business Analytics: Concepts, Techniques, and Applications in R presents an applied approach to data mining concepts and methods, using R software for illustration Readers will learn how to implement a variety of popular data mining algorithms in R (a free and open-source software) to tackle business problems and opportunities. This is the fifth version of this successful text, and the first using R. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes: • Two new co-authors, Inbal Yahav and Casey Lichtendahl, who bring both expertise teaching business analytics courses using R, and data mining consulting experience in business and government • Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students • More than a dozen case studies demonstrating applications for the data mining techniques described • End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented • A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions Data Mining for Business Analytics: Concepts, Techniques, and Applications in R is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology. “ This book has by far the most comprehensive review of business analytics methods that I have ever seen, covering everything from classical approaches such as linear and logistic regression, through to modern methods like neural networks, bagging and boosting, and even much more business specific procedures such as social network analysis and text mining. If not the bible, it is at the least a definitive manual on the subject.” Gareth M. James, University of Southern California and co-author (with Witten, Hastie and Tibshirani) of the best-selling book An Introduction to Statistical Learning, with Applications in R Galit Shmueli, PhD, is Distinguished Professor at National Tsing Hua University’s Institute of Service Science. She has designed and instructed data mining courses since 2004 at University of Maryland, Statistics.com, Indian School of Business, and National Tsing Hua University, Taiwan. Professor Shmueli is known for her research and teaching in business analytics, with a focus on statistical and data mining methods in information systems and healthcare. She has authored over 70 publications including books. Peter C. Bruce is President and Founder of the Institute for Statistics Education at Statistics.com. He has written multiple journal articles and is the developer of Resampling Stats software. He is the author of Introductory Statistics and Analytics: A Resampling Perspective (Wiley) and co-author of Practical Statistics for Data Scientists: 50 Essential Concepts (O’Reilly). Inbal Yahav, PhD, is Professor at the Graduate School of Business Administration at Bar-Ilan University, Israel. She teaches courses in social network analysis, advanced research methods, and software quality assurance. Dr. Yahav received her PhD in Operations Research and Data Mining from the University of Maryland, College Park. Nitin R. Patel, PhD, is Chairman and cofounder of Cytel, Inc., based in Cambridge, Massachusetts. A Fellow of the American St
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