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Published by Taylor & Francis Ltd, London, 2024
ISBN 10: 1032136146 ISBN 13: 9781032136141
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Paperback. Condition: new. Paperback. Artificial intelligence (AI), machine learning, and advanced electronic circuits involve learning from every data input and using those inputs to generate new rules for future business analytics. AI and machine learning are now giving us new opportunities to use big data that we already had, as well as unleash a whole lot of new use cases with new data types. With the increasing use of AI dealing with highly sensitive information such as healthcare, adequate security measures are required to securely store and transmit this information. This book provides a broader coverage of the basic aspects of advanced circuits design and applications.AI for Big Data-Based Engineering Applications from Security Perspectives is an integrated source that aims at understanding the basic concepts associated with the security of advanced circuits. The content includes theoretical frameworks and recent empirical findings in the field to understand the associated principles, key challenges, and recent real-time applications of advanced circuits, AI, and big data security. It illustrates the notions, models, and terminologies that are widely used in the area of Very Large Scale Integration (VLSI) circuits, security, identifies the existing security issues in the field, and evaluates the underlying factors that influence system security. This work emphasizes the idea of understanding the motivation behind advanced circuit design to establish the AI interface and to mitigate security attacks in a better way for big data. This book also outlines exciting areas of future research where already existing methodologies can be implemented. This material is suitable for students, researchers, and professionals with research interest in AI for big databased engineering applications, faculty members across universities, and software developers. This book emphasizes the idea of understanding the motivation of the advanced circuits design to establish the AI interface and to mitigate the security attacks in a better way for big data. It is for students, researchers, and professionals, faculty members and software developers who wish to carry out further research. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Published by Taylor and Francis Ltd, GB, 2024
ISBN 10: 1032136146 ISBN 13: 9781032136141
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Paperback. Condition: New. Artificial intelligence (AI), machine learning, and advanced electronic circuits involve learning from every data input and using those inputs to generate new rules for future business analytics. AI and machine learning are now giving us new opportunities to use big data that we already had, as well as unleash a whole lot of new use cases with new data types. With the increasing use of AI dealing with highly sensitive information such as healthcare, adequate security measures are required to securely store and transmit this information. This book provides a broader coverage of the basic aspects of advanced circuits design and applications.AI for Big Data-Based Engineering Applications from Security Perspectives is an integrated source that aims at understanding the basic concepts associated with the security of advanced circuits. The content includes theoretical frameworks and recent empirical findings in the field to understand the associated principles, key challenges, and recent real-time applications of advanced circuits, AI, and big data security. It illustrates the notions, models, and terminologies that are widely used in the area of Very Large Scale Integration (VLSI) circuits, security, identifies the existing security issues in the field, and evaluates the underlying factors that influence system security. This work emphasizes the idea of understanding the motivation behind advanced circuit design to establish the AI interface and to mitigate security attacks in a better way for big data. This book also outlines exciting areas of future research where already existing methodologies can be implemented. This material is suitable for students, researchers, and professionals with research interest in AI for big data-based engineering applications, faculty members across universities, and software developers.
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Published by LAP LAMBERT Academic Publishing, 2020
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Published by Taylor & Francis Ltd, 2024
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Published by LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6139455561 ISBN 13: 9786139455560
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Condition: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | The scaling of traditional planar CMOS devices is becoming difficult due to increasing gate leakage and subthreshold leakage. Multigate FETs have been proposed to overcome the limitations associated with the scaling of traditional CMOS devices below 100nm region. The multiple electrically coupled gates and the thin silicon body suppress the short-channel effects, thereby lowering the subthreshold leakage current in a multi-gate MOSFET. However, fabrication complexity increases for inversion mode (IM) FinFET devices due to ultra-steep doping profiles requirement. Junctionless transistor (JLT) overcomes the limitations associated with the creation of ultra-steep doping profiles during fabrication and short channel effects. In order to further reduce the SCEs, spacers at the both sides of gate are used that minimizes the leakage current. In this proposed work, JLT is designed with the use of spacer engineering i.e. changing the Lext, spacer¿s proportion as well as the dielectric values (¿) of spacer material and its performance are evaluated from device characteristics using TCAD software tool.
Language: English
Published by LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6139455561 ISBN 13: 9786139455560
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Condition: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | The scaling of traditional planar CMOS devices is becoming difficult due to increasing gate leakage and subthreshold leakage. Multigate FETs have been proposed to overcome the limitations associated with the scaling of traditional CMOS devices below 100nm region. The multiple electrically coupled gates and the thin silicon body suppress the short-channel effects, thereby lowering the subthreshold leakage current in a multi-gate MOSFET. However, fabrication complexity increases for inversion mode (IM) FinFET devices due to ultra-steep doping profiles requirement. Junctionless transistor (JLT) overcomes the limitations associated with the creation of ultra-steep doping profiles during fabrication and short channel effects. In order to further reduce the SCEs, spacers at the both sides of gate are used that minimizes the leakage current. In this proposed work, JLT is designed with the use of spacer engineering i.e. changing the Lext, spacer¿s proportion as well as the dielectric values (¿) of spacer material and its performance are evaluated from device characteristics using TCAD software tool.
Language: English
Published by Taylor and Francis Ltd, GB, 2024
ISBN 10: 1032136146 ISBN 13: 9781032136141
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Paperback. Condition: New. Artificial intelligence (AI), machine learning, and advanced electronic circuits involve learning from every data input and using those inputs to generate new rules for future business analytics. AI and machine learning are now giving us new opportunities to use big data that we already had, as well as unleash a whole lot of new use cases with new data types. With the increasing use of AI dealing with highly sensitive information such as healthcare, adequate security measures are required to securely store and transmit this information. This book provides a broader coverage of the basic aspects of advanced circuits design and applications.AI for Big Data-Based Engineering Applications from Security Perspectives is an integrated source that aims at understanding the basic concepts associated with the security of advanced circuits. The content includes theoretical frameworks and recent empirical findings in the field to understand the associated principles, key challenges, and recent real-time applications of advanced circuits, AI, and big data security. It illustrates the notions, models, and terminologies that are widely used in the area of Very Large Scale Integration (VLSI) circuits, security, identifies the existing security issues in the field, and evaluates the underlying factors that influence system security. This work emphasizes the idea of understanding the motivation behind advanced circuit design to establish the AI interface and to mitigate security attacks in a better way for big data. This book also outlines exciting areas of future research where already existing methodologies can be implemented. This material is suitable for students, researchers, and professionals with research interest in AI for big data-based engineering applications, faculty members across universities, and software developers.
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Taschenbuch. Condition: Neu. AI for Big Data-Based Engineering Applications from Security Perspectives | Balwinder Raj (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2024 | CRC Press | EAN 9781032136141 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
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Language: English
Published by Taylor & Francis Ltd, 2023
ISBN 10: 1032136138 ISBN 13: 9781032136134
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