Author: Qi Liu
Publisher: Springer Nature
ISBN: 9811969019
Category : Technology & Engineering
Languages : en
Pages : 1506
Book Description
This conference proceeding is a collection of the papers accepted by the CENet2022 – the 12th International Conference on Computer Engineering and Networks held on November 4-7, 2022 in Haikou, China. The topics focus but are not limited to Internet of Things and Smart Systems, Artificial Intelligence and Applications, Communication System Detection, Analysis and Application, and Medical Engineering and Information Systems. Each part can be used as an excellent reference by industry practitioners, university faculties, research fellows and undergraduates as well as graduate students who need to build a knowledge base of the most current advances and state-of-practice in the topics covered by this conference proceedings. This will enable them to produce, maintain, and manage systems with high levels of trustworthiness and complexity.
Proceedings of the 12th International Conference on Computer Engineering and Networks
Author: Qi Liu
Publisher: Springer Nature
ISBN: 9811969019
Category : Technology & Engineering
Languages : en
Pages : 1506
Book Description
This conference proceeding is a collection of the papers accepted by the CENet2022 – the 12th International Conference on Computer Engineering and Networks held on November 4-7, 2022 in Haikou, China. The topics focus but are not limited to Internet of Things and Smart Systems, Artificial Intelligence and Applications, Communication System Detection, Analysis and Application, and Medical Engineering and Information Systems. Each part can be used as an excellent reference by industry practitioners, university faculties, research fellows and undergraduates as well as graduate students who need to build a knowledge base of the most current advances and state-of-practice in the topics covered by this conference proceedings. This will enable them to produce, maintain, and manage systems with high levels of trustworthiness and complexity.
Publisher: Springer Nature
ISBN: 9811969019
Category : Technology & Engineering
Languages : en
Pages : 1506
Book Description
This conference proceeding is a collection of the papers accepted by the CENet2022 – the 12th International Conference on Computer Engineering and Networks held on November 4-7, 2022 in Haikou, China. The topics focus but are not limited to Internet of Things and Smart Systems, Artificial Intelligence and Applications, Communication System Detection, Analysis and Application, and Medical Engineering and Information Systems. Each part can be used as an excellent reference by industry practitioners, university faculties, research fellows and undergraduates as well as graduate students who need to build a knowledge base of the most current advances and state-of-practice in the topics covered by this conference proceedings. This will enable them to produce, maintain, and manage systems with high levels of trustworthiness and complexity.
Artificial Intelligence for Edge Computing
Author: Mudhakar Srivatsa
Publisher: Springer Nature
ISBN: 3031407873
Category : Technology & Engineering
Languages : en
Pages : 373
Book Description
It is undeniable that the recent revival of artificial intelligence (AI) has significantly changed the landscape of science in many application domains, ranging from health to defense and from conversational interfaces to autonomous cars. With terms such as “Google Home”, “Alexa”, and “ChatGPT” becoming household names, the pervasive societal impact of AI is clear. Advances in AI promise a revolution in our interaction with the physical world, a domain where computational intelligence has always been envisioned as a transformative force toward a better tomorrow. Depending on the application family, this domain is often referred to as Ubiquitous Computing, Cyber-Physical Computing, or the Internet of Things. The underlying vision is driven by the proliferation of cheap embedded computing hardware that can be integrated easily into myriads of everyday devices from consumer electronics, such as personal wearables and smart household appliances, to city infrastructure and industrial process control systems. One common trait across these applications is that the data that the application operates on come directly (typically via sensors) from the physical world. Thus, from the perspective of communication network infrastructure, the data originate at the network edge. From a performance standpoint, there is an argument to be made that such data should be processed at the point of collection. Hence, a need arises for Edge AI -- a genre of AI where the inference, and sometimes even the training, are performed at the point of need, meaning at the edge where the data originate. The book is broken down into three parts: core problems, distributed problems, and other cross-cutting issues. It explores the challenges arising in Edge AI contexts. Some of these challenges (such as neural network model reduction to fit resource-constrained hardware) are unique to the edge environment. They need a novel category of solutions that do not parallel more typical concerns in mainstream AI. Others are adaptations of mainstream AI challenges to the edge space. An example is overcoming the cost of data labeling. The labeling problem is pervasive, but its solution in the IoT application context is different from other contexts. This book is not a survey of the state of the art. With thousands of publications appearing in AI every year, such a survey is doomed to be incomplete on arrival. It is also not a comprehensive coverage of all the problems in the space of Edge AI. Different applications pose different challenges, and a more comprehensive coverage should be more application specific. Instead, this book covers some of the more endemic challenges across the range of IoT/CPS applications. To offer coverage in some depth, we opt to cover mainly one or a few representative solutions for each of these endemic challenges in sufficient detail, rather that broadly touching on all relevant prior work. The underlying philosophy is one of illustrating by example. The solutions are curated to offer insight into a way of thinking that characterizes Edge AI research and distinguishes its solutions from their more mainstream counterparts.
Publisher: Springer Nature
ISBN: 3031407873
Category : Technology & Engineering
Languages : en
Pages : 373
Book Description
It is undeniable that the recent revival of artificial intelligence (AI) has significantly changed the landscape of science in many application domains, ranging from health to defense and from conversational interfaces to autonomous cars. With terms such as “Google Home”, “Alexa”, and “ChatGPT” becoming household names, the pervasive societal impact of AI is clear. Advances in AI promise a revolution in our interaction with the physical world, a domain where computational intelligence has always been envisioned as a transformative force toward a better tomorrow. Depending on the application family, this domain is often referred to as Ubiquitous Computing, Cyber-Physical Computing, or the Internet of Things. The underlying vision is driven by the proliferation of cheap embedded computing hardware that can be integrated easily into myriads of everyday devices from consumer electronics, such as personal wearables and smart household appliances, to city infrastructure and industrial process control systems. One common trait across these applications is that the data that the application operates on come directly (typically via sensors) from the physical world. Thus, from the perspective of communication network infrastructure, the data originate at the network edge. From a performance standpoint, there is an argument to be made that such data should be processed at the point of collection. Hence, a need arises for Edge AI -- a genre of AI where the inference, and sometimes even the training, are performed at the point of need, meaning at the edge where the data originate. The book is broken down into three parts: core problems, distributed problems, and other cross-cutting issues. It explores the challenges arising in Edge AI contexts. Some of these challenges (such as neural network model reduction to fit resource-constrained hardware) are unique to the edge environment. They need a novel category of solutions that do not parallel more typical concerns in mainstream AI. Others are adaptations of mainstream AI challenges to the edge space. An example is overcoming the cost of data labeling. The labeling problem is pervasive, but its solution in the IoT application context is different from other contexts. This book is not a survey of the state of the art. With thousands of publications appearing in AI every year, such a survey is doomed to be incomplete on arrival. It is also not a comprehensive coverage of all the problems in the space of Edge AI. Different applications pose different challenges, and a more comprehensive coverage should be more application specific. Instead, this book covers some of the more endemic challenges across the range of IoT/CPS applications. To offer coverage in some depth, we opt to cover mainly one or a few representative solutions for each of these endemic challenges in sufficient detail, rather that broadly touching on all relevant prior work. The underlying philosophy is one of illustrating by example. The solutions are curated to offer insight into a way of thinking that characterizes Edge AI research and distinguishes its solutions from their more mainstream counterparts.
Putting AI in the Critical Loop
Author: Prithviraj Dasgupta
Publisher: Elsevier
ISBN: 0443159874
Category : Computers
Languages : en
Pages : 306
Book Description
Providing a high level of autonomy for a human-machine team requires assumptions that address behavior and mutual trust. The performance of a human-machine team is maximized when the partnership provides mutual benefits that satisfy design rationales, balance of control, and the nature of autonomy. The distinctively different characteristics and features of humans and machines are likely why they have the potential to work well together, overcoming each other's weaknesses through cooperation, synergy, and interdependence which forms a "collective intelligence. Trust is bidirectional and two-sided; humans need to trust AI technology, but future AI technology may also need to trust humans.Putting AI in the Critical Loop: Assured Trust and Autonomy in Human-Machine Teams focuses on human-machine trust and "assured performance and operation in order to realize the potential of autonomy. This book aims to take on the primary challenges of bidirectional trust and performance of autonomous systems, providing readers with a review of the latest literature, the science of autonomy, and a clear path towards the autonomy of human-machine teams and systems. Throughout this book, the intersecting themes of collective intelligence, bidirectional trust, and continual assurance form the challenging and extraordinarily interesting themes which will help lay the groundwork for the audience to not only bridge the knowledge gaps, but also to advance this science to develop better solutions. - Assesses the latest research advances, engineering challenges, and the theoretical gaps surrounding the question of autonomy - Reviews the challenges of autonomy (e.g., trust, ethics, legalities, etc.), including gaps in the knowledge of the science - Offers a path forward to solutions - Investigates the value of trust by humans of HMTs, as well as the bidirectionality of trust, understanding how machines learn to trust their human teammates
Publisher: Elsevier
ISBN: 0443159874
Category : Computers
Languages : en
Pages : 306
Book Description
Providing a high level of autonomy for a human-machine team requires assumptions that address behavior and mutual trust. The performance of a human-machine team is maximized when the partnership provides mutual benefits that satisfy design rationales, balance of control, and the nature of autonomy. The distinctively different characteristics and features of humans and machines are likely why they have the potential to work well together, overcoming each other's weaknesses through cooperation, synergy, and interdependence which forms a "collective intelligence. Trust is bidirectional and two-sided; humans need to trust AI technology, but future AI technology may also need to trust humans.Putting AI in the Critical Loop: Assured Trust and Autonomy in Human-Machine Teams focuses on human-machine trust and "assured performance and operation in order to realize the potential of autonomy. This book aims to take on the primary challenges of bidirectional trust and performance of autonomous systems, providing readers with a review of the latest literature, the science of autonomy, and a clear path towards the autonomy of human-machine teams and systems. Throughout this book, the intersecting themes of collective intelligence, bidirectional trust, and continual assurance form the challenging and extraordinarily interesting themes which will help lay the groundwork for the audience to not only bridge the knowledge gaps, but also to advance this science to develop better solutions. - Assesses the latest research advances, engineering challenges, and the theoretical gaps surrounding the question of autonomy - Reviews the challenges of autonomy (e.g., trust, ethics, legalities, etc.), including gaps in the knowledge of the science - Offers a path forward to solutions - Investigates the value of trust by humans of HMTs, as well as the bidirectionality of trust, understanding how machines learn to trust their human teammates
Euro-Par 2024: Parallel Processing
Author: Jesus Carretero
Publisher: Springer Nature
ISBN: 3031695771
Category :
Languages : en
Pages : 430
Book Description
Publisher: Springer Nature
ISBN: 3031695771
Category :
Languages : en
Pages : 430
Book Description
IoT for Defense and National Security
Author: Robert Douglass
Publisher: John Wiley & Sons
ISBN: 1119892201
Category : Political Science
Languages : en
Pages : 532
Book Description
IoT for Defense and National Security Practical case-based guide illustrating the challenges and solutions of adopting IoT in both secure and hostile environments IoT for Defense and National Security covers topics on IoT security, architecture, robotics, sensing, policy, operations, and more, including the latest results from the premier IoT research initiative of the U.S. Defense Department, the Internet of Battle Things. The text also discusses challenges in converting defense industrial operations to IoT and summarizes policy recommendations for regulating government use of IoT in free societies. As a modern reference, this book covers multiple technologies in IoT including survivable tactical IoT using content-based routing, mobile ad-hoc networks, and electronically formed beams. Examples of IoT architectures include using KepServerEX for edge connectivity and AWS IoT Core and Amazon S3 for IoT data. To aid in reader comprehension, the text uses case studies illustrating the challenges and solutions for using robotic devices in defense applications, plus case studies on using IoT for a defense industrial base. Written by leading researchers and practitioners of IoT technology for defense and national security, IoT for Defense and National Security also includes information on: Changes in warfare driven by IoT weapons, logistics, and systems IoT resource allocation (monitoring existing resources and reallocating them in response to adversarial actions) Principles of AI-enabled processing for Internet of Battlefield Things, including machine learning and inference Vulnerabilities in tactical IoT communications, networks, servers and architectures, and strategies for securing them Adapting rapidly expanding commercial IoT to power IoT for defense For application engineers from defense-related companies as well as managers, policy makers, and academics, IoT for Defense and National Security is a one-of-a-kind resource, providing expansive coverage of an important yet sensitive topic that is often shielded from the public due to classified or restricted distributions.
Publisher: John Wiley & Sons
ISBN: 1119892201
Category : Political Science
Languages : en
Pages : 532
Book Description
IoT for Defense and National Security Practical case-based guide illustrating the challenges and solutions of adopting IoT in both secure and hostile environments IoT for Defense and National Security covers topics on IoT security, architecture, robotics, sensing, policy, operations, and more, including the latest results from the premier IoT research initiative of the U.S. Defense Department, the Internet of Battle Things. The text also discusses challenges in converting defense industrial operations to IoT and summarizes policy recommendations for regulating government use of IoT in free societies. As a modern reference, this book covers multiple technologies in IoT including survivable tactical IoT using content-based routing, mobile ad-hoc networks, and electronically formed beams. Examples of IoT architectures include using KepServerEX for edge connectivity and AWS IoT Core and Amazon S3 for IoT data. To aid in reader comprehension, the text uses case studies illustrating the challenges and solutions for using robotic devices in defense applications, plus case studies on using IoT for a defense industrial base. Written by leading researchers and practitioners of IoT technology for defense and national security, IoT for Defense and National Security also includes information on: Changes in warfare driven by IoT weapons, logistics, and systems IoT resource allocation (monitoring existing resources and reallocating them in response to adversarial actions) Principles of AI-enabled processing for Internet of Battlefield Things, including machine learning and inference Vulnerabilities in tactical IoT communications, networks, servers and architectures, and strategies for securing them Adapting rapidly expanding commercial IoT to power IoT for defense For application engineers from defense-related companies as well as managers, policy makers, and academics, IoT for Defense and National Security is a one-of-a-kind resource, providing expansive coverage of an important yet sensitive topic that is often shielded from the public due to classified or restricted distributions.
Verification and Evaluation of Computer and Communication Systems
Author: Belgacem Ben Hedia
Publisher: Springer Nature
ISBN: 3030659550
Category : Computers
Languages : en
Pages : 289
Book Description
This book constitutes the proceedings of the 14th International Conference on Verification and Evaluation of Computer and Communication Systems, VECoS 2020, which was supposed to be held in Xi’an, China, in October 2020, but was held virtually instead. The 19 full papers and 1 short paper presented in this volume were carefully reviewed and selected from 60 submissions. The aim of the VECoS conference is to bring together researchers and practitioners in the areas of verification, control, performance, and dependability evaluation in order to discuss state of the art and challenges in modern computer and communication systems in which functional and extra-functional properties are strongly interrelated. Thus, the main motivation for VECoS is to encourage the cross-fertilization between various formal verification and evaluation approaches, methods and techniques, and especially those developed for concurrent and distributed hardware/software systems. The papers are organized in the following topical sections: petri-net, simulation, and scheduling; formal modeling and verification, testing; and artificial intelligence and machine learning.
Publisher: Springer Nature
ISBN: 3030659550
Category : Computers
Languages : en
Pages : 289
Book Description
This book constitutes the proceedings of the 14th International Conference on Verification and Evaluation of Computer and Communication Systems, VECoS 2020, which was supposed to be held in Xi’an, China, in October 2020, but was held virtually instead. The 19 full papers and 1 short paper presented in this volume were carefully reviewed and selected from 60 submissions. The aim of the VECoS conference is to bring together researchers and practitioners in the areas of verification, control, performance, and dependability evaluation in order to discuss state of the art and challenges in modern computer and communication systems in which functional and extra-functional properties are strongly interrelated. Thus, the main motivation for VECoS is to encourage the cross-fertilization between various formal verification and evaluation approaches, methods and techniques, and especially those developed for concurrent and distributed hardware/software systems. The papers are organized in the following topical sections: petri-net, simulation, and scheduling; formal modeling and verification, testing; and artificial intelligence and machine learning.
Automated Technology for Verification and Analysis
Author: Étienne André
Publisher: Springer Nature
ISBN: 3031453298
Category : Computers
Languages : en
Pages : 453
Book Description
This book constitutes the refereed proceedings of the 21st International Symposium on Automated Technology for Verification and Analysis, ATVA 2023, held in Singapore, in October 2023. The symposium intends to promote research in theoretical and practical aspects of automated analysis, verification and synthesis by providing a forum for interaction between regional and international research communities and industry in related areas. The 30 regular papers presented together with 7 tool papers were carefully reviewed and selected from 150 submissions.The papers are divided into the following topical sub-headings: Temporal logics, Data structures and heuristics, Verification of programs and hardware.
Publisher: Springer Nature
ISBN: 3031453298
Category : Computers
Languages : en
Pages : 453
Book Description
This book constitutes the refereed proceedings of the 21st International Symposium on Automated Technology for Verification and Analysis, ATVA 2023, held in Singapore, in October 2023. The symposium intends to promote research in theoretical and practical aspects of automated analysis, verification and synthesis by providing a forum for interaction between regional and international research communities and industry in related areas. The 30 regular papers presented together with 7 tool papers were carefully reviewed and selected from 150 submissions.The papers are divided into the following topical sub-headings: Temporal logics, Data structures and heuristics, Verification of programs and hardware.
Role of Data-Intensive Distributed Computing Systems in Designing Data Solutions
Author: Sarvesh Pandey
Publisher: Springer Nature
ISBN: 3031155424
Category : Technology & Engineering
Languages : en
Pages : 339
Book Description
This book discusses the application of data systems and data-driven infrastructure in existing industrial systems in order to optimize workflow, utilize hidden potential, and make existing systems free from vulnerabilities. The book discusses application of data in the health sector, public transportation, the financial institutions, and in battling natural disasters, among others. Topics include real-time applications in the current big data perspective; improving security in IoT devices; data backup techniques for systems; artificial intelligence-based outlier prediction; machine learning in OpenFlow Network; and application of deep learning in blockchain enabled applications. This book is intended for a variety of readers from professional industries, organizations, and students.
Publisher: Springer Nature
ISBN: 3031155424
Category : Technology & Engineering
Languages : en
Pages : 339
Book Description
This book discusses the application of data systems and data-driven infrastructure in existing industrial systems in order to optimize workflow, utilize hidden potential, and make existing systems free from vulnerabilities. The book discusses application of data in the health sector, public transportation, the financial institutions, and in battling natural disasters, among others. Topics include real-time applications in the current big data perspective; improving security in IoT devices; data backup techniques for systems; artificial intelligence-based outlier prediction; machine learning in OpenFlow Network; and application of deep learning in blockchain enabled applications. This book is intended for a variety of readers from professional industries, organizations, and students.
Science of Cyber Security
Author: Chunhua Su
Publisher: Springer Nature
ISBN: 3031175514
Category : Computers
Languages : en
Pages : 575
Book Description
This book constitutes the proceedings of the 4th International Conference on Science of Cyber Security, SciSec 2022, held in Matsu, Japan in August 2022. The 36 full papers presented in this volume were carefully reviewed and selected from 88 submissions. The papers are organized in the following topical sections: blockchain and applications; cryptography and applications; network security; cyber-physical system; malware; mobile system security; system and web security; security in financial industry; social engineering and personalized security; privacy and anonymity.
Publisher: Springer Nature
ISBN: 3031175514
Category : Computers
Languages : en
Pages : 575
Book Description
This book constitutes the proceedings of the 4th International Conference on Science of Cyber Security, SciSec 2022, held in Matsu, Japan in August 2022. The 36 full papers presented in this volume were carefully reviewed and selected from 88 submissions. The papers are organized in the following topical sections: blockchain and applications; cryptography and applications; network security; cyber-physical system; malware; mobile system security; system and web security; security in financial industry; social engineering and personalized security; privacy and anonymity.
Deep Learning and Its Applications for Vehicle Networks
Author: Fei Hu
Publisher: CRC Press
ISBN: 100087723X
Category : Computers
Languages : en
Pages : 357
Book Description
Deep Learning (DL) is an effective approach for AI-based vehicular networks and can deliver a powerful set of tools for such vehicular network dynamics. In various domains of vehicular networks, DL can be used for learning-based channel estimation, traffic flow prediction, vehicle trajectory prediction, location-prediction-based scheduling and routing, intelligent network congestion control mechanism, smart load balancing and vertical handoff control, intelligent network security strategies, virtual smart and efficient resource allocation and intelligent distributed resource allocation methods. This book is based on the work from world-famous experts on the application of DL for vehicle networks. It consists of the following five parts: (I) DL for vehicle safety and security: This part covers the use of DL algorithms for vehicle safety or security. (II) DL for effective vehicle communications: Vehicle networks consist of vehicle-to-vehicle and vehicle-to-roadside communications. This part covers how Intelligent vehicle networks require a flexible selection of the best path across all vehicles, adaptive sending rate control based on bandwidth availability and timely data downloads from a roadside base-station. (III) DL for vehicle control: The myriad operations that require intelligent control for each individual vehicle are discussed in this part. This also includes emission control, which is based on the road traffic situation, the charging pile load is predicted through DL andvehicle speed adjustments based on the camera-captured image analysis. (IV) DL for information management: This part covers some intelligent information collection and understanding. We can use DL for energy-saving vehicle trajectory control based on the road traffic situation and given destination information; we can also natural language processing based on DL algorithm for automatic internet of things (IoT) search during driving. (V) Other applications. This part introduces the use of DL models for other vehicle controls. Autonomous vehicles are becoming more and more popular in society. The DL and its variants will play greater roles in cognitive vehicle communications and control. Other machine learning models such as deep reinforcement learning will also facilitate intelligent vehicle behavior understanding and adjustment. This book will become a valuable reference to your understanding of this critical field.
Publisher: CRC Press
ISBN: 100087723X
Category : Computers
Languages : en
Pages : 357
Book Description
Deep Learning (DL) is an effective approach for AI-based vehicular networks and can deliver a powerful set of tools for such vehicular network dynamics. In various domains of vehicular networks, DL can be used for learning-based channel estimation, traffic flow prediction, vehicle trajectory prediction, location-prediction-based scheduling and routing, intelligent network congestion control mechanism, smart load balancing and vertical handoff control, intelligent network security strategies, virtual smart and efficient resource allocation and intelligent distributed resource allocation methods. This book is based on the work from world-famous experts on the application of DL for vehicle networks. It consists of the following five parts: (I) DL for vehicle safety and security: This part covers the use of DL algorithms for vehicle safety or security. (II) DL for effective vehicle communications: Vehicle networks consist of vehicle-to-vehicle and vehicle-to-roadside communications. This part covers how Intelligent vehicle networks require a flexible selection of the best path across all vehicles, adaptive sending rate control based on bandwidth availability and timely data downloads from a roadside base-station. (III) DL for vehicle control: The myriad operations that require intelligent control for each individual vehicle are discussed in this part. This also includes emission control, which is based on the road traffic situation, the charging pile load is predicted through DL andvehicle speed adjustments based on the camera-captured image analysis. (IV) DL for information management: This part covers some intelligent information collection and understanding. We can use DL for energy-saving vehicle trajectory control based on the road traffic situation and given destination information; we can also natural language processing based on DL algorithm for automatic internet of things (IoT) search during driving. (V) Other applications. This part introduces the use of DL models for other vehicle controls. Autonomous vehicles are becoming more and more popular in society. The DL and its variants will play greater roles in cognitive vehicle communications and control. Other machine learning models such as deep reinforcement learning will also facilitate intelligent vehicle behavior understanding and adjustment. This book will become a valuable reference to your understanding of this critical field.