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1. |
Record Nr. |
UNINA9910457236103321 |
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Autore |
Daniel John S. <1942-, > |
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Titolo |
Mega-schools, technology, and teachers : achieving education for all / / John S. Daniel |
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Pubbl/distr/stampa |
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New York, N.Y. : , : Routledge, , 2010 |
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ISBN |
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1-135-16333-2 |
1-282-57154-0 |
9786612571541 |
0-203-85832-8 |
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Descrizione fisica |
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1 online resource (209 p.) |
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Collana |
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Open and flexible learning series |
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Disciplina |
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Soggetti |
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Education, Elementary - Developing countries |
Educational equalization - Developing countries |
Distance education - Computer-assisted instruction - Developing countries |
Electronic books. |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Book Cover; Title; Copyright; Dedication; Contents; List of Figures and Tables; Series Editor's Foreword; Acknowledgements; Glossary of Acronyms; Introduction; 1 Education for All: Unfinished Business; 2 Seeking a Silver Bullet; 3 Technology Is the Answer: What Is the Question?; 4 Open Schools and Mega-Schools; 5 Teacher Education at Scale; 6 Strategies for Success; APPENDIX 1 Profiles: Selected Open Schools and Mega-Schools; APPENDIX 2 Programmes and Mechanisms for Expanding Teacher Supply; Bibliography; Subject Index; Name Index |
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Sommario/riassunto |
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Education for All (EFA) has been a top priority for governments and intergovernmental development agencies for the last twenty years. So far the global EFA movement has placed its principal focus on providing quality universal primary education (UPE) for all children by 2015.The latest addition to The Open and Flexible Learning series, this book addresses the new challenges created by both the successes and the failures of the UPE campaign. This book advocates new approaches for |
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providing access to secondary education for today's rapidly growing population of childr |
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2. |
Record Nr. |
UNINA9910818966703321 |
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Autore |
Chebbi Chiheb |
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Titolo |
Mastering machine learning for penetration testing : develop an extensive skill set to break self-learning systems using Python / / Chiheb Chebbi |
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Pubbl/distr/stampa |
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Birmingham : , : Packt, , 2018 |
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ISBN |
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Edizione |
[1st edition] |
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Descrizione fisica |
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1 online resource (264 pages) |
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Disciplina |
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Soggetti |
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Python (Computer program language) |
Penetration testing (Computer security) |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references. |
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Sommario/riassunto |
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Become a master at penetration testing using machine learning with Python About This Book Identify ambiguities and breach intelligent security systems Perform unique cyber attacks to breach robust systems Learn to leverage machine learning algorithms Who This Book Is For This book is for pen testers and security professionals who are interested in learning techniques to break an intelligent security system. Basic knowledge of Python is needed, but no prior knowledge of machine learning is necessary. What You Will Learn Take an in-depth look at machine learning Get to know natural language processing (NLP) Understand malware feature engineering Build generative adversarial networks using Python libraries Work on threat hunting with machine learning and the ELK stack Explore the best practices for machine learning In Detail Cyber security is crucial for both businesses and individuals. As systems are getting smarter, we now see machine learning interrupting computer security. With the adoption of machine learning in upcoming security products, it's important for pentesters and security researchers to understand how these systems work, and to |
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breach them for testing purposes. This book begins with the basics of machine learning and the algorithms used to build robust systems. Once you've gained a fair understanding of how security products leverage machine learning, you'll dive into the core concepts of breaching such systems. Through practical use cases, you'll see how to find loopholes and surpass a self-learning security system. As you make your way through the chapters, you'll focus on topics such as network intrusion detection and AV and IDS evasion. We'll also cover the best practices when identifying ambiguities, and extensive techniques to breach an intelligent system. By the end of this book, you will be well-versed with identifying loopholes in a self-learning security system and will be able to efficiently breach a machine learning system. Style and approach This book takes a step-by-step approach to identify the loop holes in a self-learning security system. You will be able to efficiently breach a machine learning system with the help of best practices towards the end of the book. |
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3. |
Record Nr. |
UNINA9910155271803321 |
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Autore |
Borghetti Fabio |
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Titolo |
Tunnel Fire Testing and Modeling : The Morgex North Tunnel Experiment / / by Fabio Borghetti, Marco Derudi, Paolo Gandini, Alessio Frassoldati, Silvia Tavelli |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
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Edizione |
[1st ed. 2017.] |
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Descrizione fisica |
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1 online resource (XIII, 97 p. 96 illus., 43 illus. in color.) |
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Collana |
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PoliMI SpringerBriefs, , 2282-2577 |
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Disciplina |
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Soggetti |
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Fluid mechanics |
Thermodynamics |
Heat engineering |
Heat - Transmission |
Mass transfer |
Quality control |
Reliability |
Industrial safety |
Computer simulation |
Civil engineering |
Engineering Fluid Dynamics |
Engineering Thermodynamics, Heat and Mass Transfer |
Quality Control, Reliability, Safety and Risk |
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Simulation and Modeling |
Civil Engineering |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references at the end of each chapters. |
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Nota di contenuto |
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Safety in road tunnels -- The research project and partners involved -- The fire tests in the Morgex North tunnel -- The test results -- Evaluation of the consequences on the users safety -- Conclusions. |
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Sommario/riassunto |
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This book aims to cast light on all aspects of tunnel fires, based on experimental activities and theoretical and computational fluid dynamics (CFD) analyses. In particular, the authors describe a transient full-scale fire test (~15 MW), explaining how they designed and performed the experimental activity inside the Morgex North tunnel in Italy. The entire organization of the experiment is described, from preliminary evaluations to the solutions found for management of operational difficulties and safety issues. This fire test allowed the collection of different measurements (temperature, air velocity, smoke composition, pollutant species) useful for validating and improving CFD codes and for testing the real behavior of the tunnel and its safety systems during a diesel oil fire with a significant heat release rate. Finally, the fire dynamics are compared with empirical correlations, CFD simulations, and literature measurements obtained in other similar tunnel fire tests. This book will be of interest to all engineers and public officials who are concerned with the nature, prevention, and management of tunnel fires. |
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