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In den WarenkorbTaschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Document from the year 2014 in the subject Computer Science - IT-Security, grade: 1, -, language: English, abstract: Today in the growing era of communication everyone wants to update with the new functionality so that they would survive with the best. Since the only way to access Internet is the browser, so it is vital to configure them securely. With the growing demands to ease the work in one click many engine tools, supportive plug-ins have been developed for web-browser. And the users also without knowing its causes quickly installed such extensible plug-ins in their browsers which gives the chances to intruders to get control their computer without their knowledge. Such plug-ins becomes victim for the vulnerabilities of the computer which are due to the manufacturer coding fault.
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In den WarenkorbHRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Verlag: LAP LAMBERT Academic Publishing Nov 2014, 2014
ISBN 10: 3659627828 ISBN 13: 9783659627828
Sprache: Englisch
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In den WarenkorbTaschenbuch. Zustand: Neu. Neuware -Today with the tremendous series of undocumented or poorly documented protocols how an incident responder on the network can can present the packet by capturing a binary executable file. The contents of such files can be parsed by conventional static and dynamic techniques. In many situations one can¿t detect even the binary file for analysis. So a new process of Protocol Reverse Engineering (PRE) leveraging multiple sources of information to accelerate incident response detection. It is a pseudo-formal survey of the tools, techniques, and methodologies that I've experienced or observed to be effective that is deliberately proscriptive, rather than prescriptive. It is not an exhaustive study, and only designed to cover common needs of analysts - particularly engaged in incident response.Books on Demand GmbH, Überseering 33, 22297 Hamburg 52 pp. Englisch.
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In den WarenkorbTaschenbuch. Zustand: Neu. Detecting Veracity | A New door to keep Safe from fake Posts | Hemant Kumar Saini (u. a.) | Taschenbuch | 16 S. | Englisch | 2014 | GRIN Verlag | EAN 9783656851936 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu Print on Demand.
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In den WarenkorbTaschenbuch. Zustand: Neu. Backdoor Add-ons. A new way to harbor the data | Hemant Kumar Saini | Taschenbuch | 16 S. | Englisch | 2014 | GRIN Verlag | EAN 9783656829249 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu Print on Demand.
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In den WarenkorbTaschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Document from the year 2014 in the subject Computer Science - IT-Security, grade: 1, -, language: English, abstract: Today in the growing era of communication everyone wants to update with the new functionality so that they would survive with the best. Since the only way to access Internet is the browser, so it is vital to configure them securely. With the growing demands to ease the work in one click many engine tools, supportive plug-ins have been developed for web-browser. And the users also without knowing its causes quickly installed such extensible plug-ins in their browsers which gives the chances to intruders to get control their computer without their knowledge. Such plug-ins becomes victim for the vulnerabilities of the computer which are due to the manufacturer coding fault. 16 pp. Englisch.
Verlag: LAP LAMBERT Academic Publishing, 2014
ISBN 10: 3659627828 ISBN 13: 9783659627828
Sprache: Englisch
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In den WarenkorbPaperback. Zustand: Brand New. 52 pages. 8.66x5.91x0.12 inches. In Stock.
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In den WarenkorbHardcover. Zustand: new. Hardcover. This book is intended for a technical audience with advanced learning and in-depth analysis of the latest real-world developments in the field of quantum computing. The book is focused on modeling emerging drone-based applications. The methods of developing faster drive with the new trending technology of quantum genetic heuristics, artificial intelligence, and machine-based applications are discussed. Researchers will find novel ways to secure the data and Quantum drone networks. The book examines the most promising exploratory quantum-computed drone that optimizes, secures, and dynamically analyses various sectors, including healthcare, the educational industry, finance, transportation, and manufacturing. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Verlag: H N H International Limited, 2024
ISBN 10: 1032640634 ISBN 13: 9781032640631
Sprache: Englisch
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In den WarenkorbZustand: New. pp. 310.
Verlag: LAP LAMBERT Academic Publishing, 2014
ISBN 10: 3659627828 ISBN 13: 9783659627828
Sprache: Englisch
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In den Warenkorbpaperback. Zustand: New. New. book.
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In den WarenkorbHardback. Zustand: New. New copy - Usually dispatched within 4 working days. 750.
Verlag: H N H International Limited, 2024
ISBN 10: 1032640634 ISBN 13: 9781032640631
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In den WarenkorbZustand: New. pp. 310 1st edition NO-PA16APR2015-KAP.
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In den WarenkorbZustand: New. In.
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Verlag: H N H International Limited, 2024
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In den WarenkorbZustand: New. pp. 310.
Verlag: Taylor & Francis Ltd, London, 2024
ISBN 10: 1032640634 ISBN 13: 9781032640631
Sprache: Englisch
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In den WarenkorbHardcover. Zustand: new. Hardcover. This book begins by introducing bio-inspired data-driven computation techniques, discussing bio-inspired swarm models, and highlighting the development of interactive bio-inspired energy harvesting systems to drive transportation infrastructure. It further covers important topics such as efficient control systems for distributed and hybrid renewable energy sources, and smart energy management systems for developing intelligent systems. This book:Presents data-driven intelligent heuristics for improving and advancing environmental sustainability in both eco-cities and smart cities. Discusses various efficient control systems for distributed and hybrid renewable energy sources and enhance the scope of smart energy management systems for developing even intelligent systems. Showcases how distributed energy systems improve the data-driven robots in the Internet of Medical Things. Highlights practical approaches to optimize power generation, reduce costs through efficient energy, and reduce greenhouse gas emissions to the possible minimum. Covers bio-inspired swarm models, smart data-driven sensing to combat environmental issues, and futuristic data-driven enabled schemes in blockchain-fog-cloud assisted medical eny ecosystem.The text is primarily written for graduate students, and academic researchers in diverse fiergelds including electrical engineering, electronics and communications engineering, computer science and engineering, and environmental engineering. This book begins by introducing bio-inspired data-driven computation techniques, discussing bio-inspired swarm models, and highlighting the development of interactive bio-inspired energy harvesting systems to drive transportation infrastructure. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Verlag: Taylor & Francis Ltd, London, 2024
ISBN 10: 1032640634 ISBN 13: 9781032640631
Sprache: Englisch
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In den WarenkorbHardcover. Zustand: new. Hardcover. This book begins by introducing bio-inspired data-driven computation techniques, discussing bio-inspired swarm models, and highlighting the development of interactive bio-inspired energy harvesting systems to drive transportation infrastructure. It further covers important topics such as efficient control systems for distributed and hybrid renewable energy sources, and smart energy management systems for developing intelligent systems. This book:Presents data-driven intelligent heuristics for improving and advancing environmental sustainability in both eco-cities and smart cities. Discusses various efficient control systems for distributed and hybrid renewable energy sources and enhance the scope of smart energy management systems for developing even intelligent systems. Showcases how distributed energy systems improve the data-driven robots in the Internet of Medical Things. Highlights practical approaches to optimize power generation, reduce costs through efficient energy, and reduce greenhouse gas emissions to the possible minimum. Covers bio-inspired swarm models, smart data-driven sensing to combat environmental issues, and futuristic data-driven enabled schemes in blockchain-fog-cloud assisted medical eny ecosystem.The text is primarily written for graduate students, and academic researchers in diverse fiergelds including electrical engineering, electronics and communications engineering, computer science and engineering, and environmental engineering. This book begins by introducing bio-inspired data-driven computation techniques, discussing bio-inspired swarm models, and highlighting the development of interactive bio-inspired energy harvesting systems to drive transportation infrastructure. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Verlag: Springer Nature Switzerland, Springer Nature Switzerland, 2025
ISBN 10: 3031911466 ISBN 13: 9783031911460
Sprache: Englisch
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In den WarenkorbBuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book explores a pioneering exploration of how deep generative models, including generative adversarial networks (GANs) and variational autoencoders (VAEs), renovating early neurological disorder detection. This book is a bridge between computational neuroscience and clinical neurology gaps, providing novel AI-driven methodologies for diagnosing conditions such as Alzheimer s, Parkinson s, epilepsy, and neurodevelopmental disorders. With a strong focus on neuroimaging, genomic data analysis, and biomedical informatics, the book equips researchers and practitioners with the tools to improve diagnostic accuracy and decision-making. It includes practical case studies, visual illustrations, and structured methodologies for training and validating deep learning models. Designed for neurologists, radiologists, data scientists, and AI researchers, this book is an essential resource for advancing precision medicine and next-generation healthcare innovation.
Verlag: Taylor & Francis Ltd, London, 2024
ISBN 10: 1032640634 ISBN 13: 9781032640631
Sprache: Englisch
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In den WarenkorbHardcover. Zustand: new. Hardcover. This book begins by introducing bio-inspired data-driven computation techniques, discussing bio-inspired swarm models, and highlighting the development of interactive bio-inspired energy harvesting systems to drive transportation infrastructure. It further covers important topics such as efficient control systems for distributed and hybrid renewable energy sources, and smart energy management systems for developing intelligent systems. This book:Presents data-driven intelligent heuristics for improving and advancing environmental sustainability in both eco-cities and smart cities. Discusses various efficient control systems for distributed and hybrid renewable energy sources and enhance the scope of smart energy management systems for developing even intelligent systems. Showcases how distributed energy systems improve the data-driven robots in the Internet of Medical Things. Highlights practical approaches to optimize power generation, reduce costs through efficient energy, and reduce greenhouse gas emissions to the possible minimum. Covers bio-inspired swarm models, smart data-driven sensing to combat environmental issues, and futuristic data-driven enabled schemes in blockchain-fog-cloud assisted medical eny ecosystem.The text is primarily written for graduate students, and academic researchers in diverse fiergelds including electrical engineering, electronics and communications engineering, computer science and engineering, and environmental engineering. This book begins by introducing bio-inspired data-driven computation techniques, discussing bio-inspired swarm models, and highlighting the development of interactive bio-inspired energy harvesting systems to drive transportation infrastructure. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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In den WarenkorbHardcover. Zustand: Brand New. 336 pages. 9.18x6.12x9.21 inches. In Stock.
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In den WarenkorbZustand: As New. Unread book in perfect condition.
Verlag: Springer International Publishing AG, Cham, 2025
ISBN 10: 3031911466 ISBN 13: 9783031911460
Sprache: Englisch
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In den WarenkorbHardcover. Zustand: new. Hardcover. This book explores a pioneering exploration of how deep generative models, including generative adversarial networks (GANs) and variational autoencoders (VAEs), renovating early neurological disorder detection. This book is a bridge between computational neuroscience and clinical neurology gaps, providing novel AI-driven methodologies for diagnosing conditions such as Alzheimers, Parkinsons, epilepsy, and neurodevelopmental disorders. With a strong focus on neuroimaging, genomic data analysis, and biomedical informatics, the book equips researchers and practitioners with the tools to improve diagnostic accuracy and decision-making. It includes practical case studies, visual illustrations, and structured methodologies for training and validating deep learning models. Designed for neurologists, radiologists, data scientists, and AI researchers, this book is an essential resource for advancing precision medicine and next-generation healthcare innovation. mso-bidi-language: AR-SA;">This book explores a pioneering exploration of how deep generative models, including generative adversarial networks (GANs) and variational autoencoders (VAEs), renovating early neurological disorder detection. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Verlag: Springer International Publishing AG, Cham, 2025
ISBN 10: 3031911466 ISBN 13: 9783031911460
Sprache: Englisch
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In den WarenkorbHardcover. Zustand: new. Hardcover. This book explores a pioneering exploration of how deep generative models, including generative adversarial networks (GANs) and variational autoencoders (VAEs), renovating early neurological disorder detection. This book is a bridge between computational neuroscience and clinical neurology gaps, providing novel AI-driven methodologies for diagnosing conditions such as Alzheimers, Parkinsons, epilepsy, and neurodevelopmental disorders. With a strong focus on neuroimaging, genomic data analysis, and biomedical informatics, the book equips researchers and practitioners with the tools to improve diagnostic accuracy and decision-making. It includes practical case studies, visual illustrations, and structured methodologies for training and validating deep learning models. Designed for neurologists, radiologists, data scientists, and AI researchers, this book is an essential resource for advancing precision medicine and next-generation healthcare innovation. mso-bidi-language: AR-SA;">This book explores a pioneering exploration of how deep generative models, including generative adversarial networks (GANs) and variational autoencoders (VAEs), renovating early neurological disorder detection. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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In den WarenkorbHardcover. Zustand: Brand New. 476 pages. 9.44x6.69x9.61 inches. In Stock.
Verlag: Springer International Publishing AG, Cham, 2025
ISBN 10: 3031911466 ISBN 13: 9783031911460
Sprache: Englisch
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In den WarenkorbHardcover. Zustand: new. Hardcover. This book explores a pioneering exploration of how deep generative models, including generative adversarial networks (GANs) and variational autoencoders (VAEs), renovating early neurological disorder detection. This book is a bridge between computational neuroscience and clinical neurology gaps, providing novel AI-driven methodologies for diagnosing conditions such as Alzheimers, Parkinsons, epilepsy, and neurodevelopmental disorders. With a strong focus on neuroimaging, genomic data analysis, and biomedical informatics, the book equips researchers and practitioners with the tools to improve diagnostic accuracy and decision-making. It includes practical case studies, visual illustrations, and structured methodologies for training and validating deep learning models. Designed for neurologists, radiologists, data scientists, and AI researchers, this book is an essential resource for advancing precision medicine and next-generation healthcare innovation. mso-bidi-language: AR-SA;">This book explores a pioneering exploration of how deep generative models, including generative adversarial networks (GANs) and variational autoencoders (VAEs), renovating early neurological disorder detection. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.