Digital and IT general topics Books

Book SynopsisThis text provides an in-depth overview of the ever-evolving field of cybersecurity. It covers a range of topics, including information security, network security, cryptography, and ethical hacking. The book is designed to help individuals and organizations understand the threats and vulnerabilities that exist in the digital world, and to develop strategies to protect themselves from cyber-attacks. Whether you are an IT professional, a business owner, or just someone interested in the topic, this book is an essential resource for anyone looking to enhance their understanding of cybersecurity.Table of Contents Chapter 1 Cyber Security and Cyber Crime Chapter 2 Cyber Security Threats with New Perspectives Chapter 3 Fundamentals of Cyber Security Chapter 4 Attacker Techniques and Motivations Chapter 5 Cyber-Risk Management Chapter 6 Cyber World Today Chapter 7 Cyber Security Concerns for Emergency Management Chapter 8 Software Security and Trusted Systems

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Book SynopsisThis book provides a comprehensive overview of the core principles and functionality of computer operating systems. The book covers various topics, including process management, memory management, file systems, device management, and security. It is written to provide readers with a deeper understanding of how operating systems work and how they can be used to optimize computer performance. This book is an essential resource for understanding the intricacies of operating systems.Table of Contents Chapter 1 Fundamentals of Operating System Chapter 2 History of Operating Systems Chapter 3 Structure of Operating Systems Chapter 4 Processes in Operating Systems Chapter 5 Memory Management Chapter 6 File Systems Chapter 7 Mobile Operating Systems Chapter 8 Distributed Operating Systems

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Book SynopsisThis text introduces readers to the basic principles of programming for the internet. It covers essential topics such as web development, client-server architecture, database management, and security. The book is written for beginners who have little to no experience in programming and want to learn how to develop websites and web applications. With clear explanations and practical examples, this book is an excellent starting point for anyone interested in internet programming.Table of Contents Chapter 1 Introduction to Internet Programming Chapter 2 World Wide Web and Website Development Chapter 3 HTML and CSS: Building Blocks of the Web Chapter 4 JavaScript: The Language of the Web Chapter 5 Object-Oriented Programming Chapter 6 Database Integration: SQL and NoSQL Chapter 7 Web Application Security Chapter 8 Performance Methodologies of Internet Programming

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Book SynopsisThis book introduces readers to the world of digital art and design. It explores the principles, techniques, and tools used to create images and animations on a computer. The book covers topics such as 2D and 3D graphics, rendering, shading, and lighting. It is an essential resource for students, artists, and designers looking to expand their knowledge and skills in the field of computer graphics. With the growing demand for digital media, this book is a valuable asset for anyone interested in creating visually stunning graphics and animations.Table of Contents Chapter 1 Introduction to Computer Graphics Chapter 2 Principles of Modeling Chapter 3 Transformation Matrices Chapter 4 Ray and Path Tracing Chapter 5 Standard Approximations and Representations Chapter 6 Color and Blending Chapter 7 Computer Animations Chapter 8 Computer Graphics in Games

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Book SynopsisThis book provides a comprehensive overview of the fundamental principles, concepts, and technologies of distributed computing. It covers various topics including the architecture of distributed systems, communication protocols, distributed file systems, distributed databases, and distributed algorithms. The book is written to help readers understand the complexities of distributed systems and how to design and develop distributed applications that are reliable, scalable, and efficient. This book is an essential text for understanding the concepts and principles of distributed systems.Table of Contents Chapter 1 Introduction to Distributed System Chapter 2 Design Patterns of Distributed Systems Chapter 3 Data Communication and Computer Networks Chapter 4 Consistency and Replication Chapter 5 Distributed File System Chapter 6 Data Storage in Distributed System Chapter 7 Scalability and Performance in Distributed System Chapter 8 Distributed System Security

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Book SynopsisThe Cyber Certified Professional (CCP) scheme certifies your ability to enforce cyber security knowledge and expertise in real-world situations. The book is designed to help information security professionals understand the CC scheme and how it can be used to evaluate and certify the security of IT products. Whether you are involved in information security management or product development, this book is an essential resource for understanding the CCP scheme and its role in information security.Table of Contents Chapter 1 Introduction to Information Security Chapter 2 The Human Resources of IT Project Management Chapter 3 Budget Management in IT Projects Chapter 4 Stakeholders in IT Project Management Chapter 5 Change Management in IT Project Chapter 6 Methods and Tools in IT Project Management Chapter 7 Challenges in IT Project Management Chapter 8 Prospects in IT Project Management

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Book SynopsisInformation Systems is a comprehensive text to the design, development, and management of information systems. The book covers topics such as system analysis and design, database management, computer networks, security, and decision support systems. The book also explores emerging trends in information systems, such as cloud computing, big data, and artificial intelligence. It is written to help students and professionals understand how information systems can be used to support business operations and achieve strategic objectives.Table of Contents Chapter 1 Basic Concepts of Information Systems Chapter 2 Hardware and Software Used in Information Systems Chapter 3 Modeling and Development of Information Systems Chapter 4 Database Management System Chapter 5 Role of Telecommunication and Networks in Information Systems Chapter 6 Information Systems in Business and Society Chapter 7 Ethical and Security Issues of Informative System Chapter 8 Emerging Trends in Information System

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Book SynopsisThis book deals with the basic principles, concepts, and protocols that underpin the Internet. It provides an overview of the technologies used to build the Internet and how they work together to create a global network. The book covers topics such as web technologies, network protocols, security, and mobile computing. It is a valuable resource for anyone interested in understanding the technology behind the Internet and how it has evolved to become an essential part of modern life.Table of Contents Chapter 1 Basics of Internet Technologies Chapter 2 Networking Protocols and Standards of Internet Technologies Chapter 3 Hardware and Software in Internet Technologies Chapter 4 World Wide Web and Website Development Chapter 5 Performance Methodologies of Internet Technologies Chapter 6 Cyber Security Threats and Challenges Chapter 7 Variety of Internet and Its Applications Chapter 8 Opportunities and Future of Internet Technologies

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Book SynopsisData centers consume roughly 1% of the total electricity demand, while ICT as a whole consumes around 10%. Demand is growing exponentially and, left unchecked, will grow to an estimated increase of 20% or more by 2030. This book covers the energy consumption and minimization of the different data center components when running real workloads, taking into account the types of instructions executed by the servers. It presents the different air- and liquid-cooled technologies for servers and data centers with some real examples, including waste heat reuse through adsorption chillers, as well as the hardware and software used to measure, model and control energy. It computes and compares the Power Usage Effectiveness and the Total Cost of Ownership of new and existing data centers with different cooling designs, including free cooling and waste heat reuse leading to the Energy Reuse Effectiveness. The book concludes by demonstrating how a well-designed data center reusing waste heat to produce chilled water can reduce energy consumption by roughly 50%, and how renewable energy can be used to create net-zero energy data centers.Table of ContentsIntroduction ix Chapter 1. Systems in Data Centers 1 1.1. Servers 1 1.2. Storage arrays 3 1.3. Data center networking 4 1.4. Components 5 1.4.1. Central processing unit 5 1.4.2. Graphics processing unit 7 1.4.3. Volatile memory 8 1.4.4. Non-volatile memory 10 1.4.5. Non-volatile storage 10 1.4.6. Spinning disks and tape storage 13 1.4.7. Motherboard 15 1.4.8. PCIe I/O cards 16 1.4.9. Power supplies 17 1.4.10. Fans 18 Chapter 2. Cooling Servers 19 2.1. Evolution of cooling for mainframe, midrange and distributed computers from the 1960s to 1990s 19 2.2. Emergence of cooling for scale out computers from 1990s to 2010s 20 2.3. Chassis and rack cooling methods 23 2.4. Metrics considered for cooling 27 2.4.1. Efficiency 27 2.4.2. Reliability cost 28 2.4.3. Thermal performance 29 2.5. Material used for cooling 31 2.6. System layout and cooling air flow optimization 32 Chapter 3. Cooling the Data Center 37 3.1. System cooling technologies used 37 3.2. Air-cooled data center 38 3.2.1. Conventional air-cooled data center 38 3.3. ASHRAE data center cooling standards 40 3.3.1. Operation and temperature classes 40 3.3.2. Liquid cooling classes 41 3.3.3. Server and rack power trend 42 3.4. Liquid-cooled racks 43 3.5. Liquid-cooled servers 46 3.5.1. Water heat capacity 46 3.5.2. Thermal conduction module 47 3.5.3. Full node heat removal with cold plates 48 3.5.4. Modular heat removal with cold plates 50 3.5.5. Immersion cooling 50 3.5.6. Recent DWC servers 51 3.6. Free cooling 54 3.7. Waste heat reuse 54 3.7.1. Reusing heat as heat 54 3.7.2. Transforming heat with adsorption chillers 55 Chapter 4. Power Consumption of Servers and Workloads 65 4.1. Trends in power consumption for processors 65 4.1.1. Moore’s and Dennard’s laws 68 4.1.2. Floating point instructions on Xeon processors 72 4.1.3. CPU frequency of instructions on Intel Xeon processors 73 4.2. Trends in power consumption for GPUs 74 4.2.1. Moore’s and Dennard’s laws 77 4.3. ACPI states 78 4.4. The power equation 83 Chapter 5. Power and Performance of Workloads 87 5.1. Power and performance of workloads 87 5.1.1. SKU power and performance variations 87 5.1.2. System parameters 89 5.1.3. Workloads used 92 5.1.4. CPU-bound and memory-bound workloads 92 5.1.5. DC node power versus components power 93 5.2. Power, thermal and performance on air-cooled servers with Intel Xeon 94 5.2.1. Frequency, power and performance of simple SIMD instructions 95 5.2.2. Power, thermal and performance behavior of HPL 98 5.2.3. Power, thermal and performance behavior of STREAM 103 5.2.4. Power, thermal and performance behavior of real workloads 107 5.2.5. Power, thermal and frequency differences between CPUs 115 5.3. Power, thermal and performance on water-cooled servers with Intel Xeon 124 5.3.1. Impact on CPU temperature 124 5.3.2. Impact on voltage and frequency 125 5.3.3. Impact on power consumption and performance 127 5.4. Conclusions on the impact of cooling on power and performance 131 Chapter 6. Monitoring and Controlling Power and Performance of Servers and Data Centers 133 6.1. Monitoring power and performance of servers 133 6.1.1. Sensors and APIs for power and thermal monitoring on servers 134 6.1.2. Monitoring performance on servers 140 6.2. Modeling power and performance of servers 142 6.2.1. Cycle-accurate performance models 142 6.2.2. Descriptive models 142 6.2.3. Predictive models 144 6.3. Software to optimize power and energy of servers 149 6.3.1. LoadLeveler job scheduler with energy aware feature 150 6.3.2. Energy Aware Runtime (EAR) 151 6.3.3. Other run time systems to manage power 153 6.4. Monitoring, controlling and optimizing the data center 154 6.4.1. Monitoring the data center 154 6.4.2. Integration of the data center infrastructure with the IT devices 156 Chapter 7. PUE, ERE and TCO of Various Cooling Solutions 159 7.1. Power usage effectiveness, energy reuse effectiveness and total cost of ownership 159 7.1.1. Power usage effectiveness and energy reuse effectiveness 159 7.1.2. PUE and free cooling 162 7.1.3. ERE and waste heat reuse 163 7.2. Examples of data centers PUE and EREs 164 7.2.1. NREL Research Support Facility, CO 164 7.2.2. Leibnitz Supercomputing data center in Germany 166 7.3. Impact of cooling on TCO with no waste heat reuse 173 7.3.1. Impact of electricity price on TCO 177 7.3.2. Impact of node power on TCO 178 7.3.3. Impact of free cooling on TCO 181 7.4. Emerging technologies and their impact on TCO 183 7.4.1. Waste heat reuse 184 7.4.2. Renewable electricity generation 189 7.4.3. Storing excess energy for later reuse 192 7.4.4. Toward a net-zero energy data center 193 Conclusion 195 References 199 Index 209

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Book SynopsisThe different forms of telepresence in education, in distance learning, in student support, in the use of learning environments or even at the heart of robot systems, are developed in universities and higher education facilities specializing in professional training. They constitute opportunities to reform arguments and give rise to important questions: how should we think about the hierarchy of presence and absence in these techniques in order to make possible “the presence of the absent”? What is the effect on mediation processes? On the perception of the body and on identity? How does it transform collaborative work? Telepresence in Training brings together research that attempts to answer these questions by using studies and practical supports from higher education, with regards to teacher training and telepresence robots in France, Belgium, Switzerland and Quebec. Table of ContentsIntroduction xi Jean-Luc RINAUDO List of Abbreviations xix Part 1. Telepresence and Student Support 1 Chapter 1. Feelings of Telepresence and Proximity: the Perspectives of E-tutors on a Hybrid Learning Environment 3 Brigitte DENIS 1.1. Introduction 3 1.2. Telepresence and proximities in remote interactions 4 1.2.1. Overcoming absence with telepresence 4 1.2.2. Experiencing the feeling of proximity at a distance 6 1.3. Research question 7 1.4. Presentation of the system 7 1.4.1. Targeted competencies and target audience 7 1.4.2. Organization: a hybrid techno-pedagogical system 8 1.5. Learning system agents 10 1.5.1. Creator-directors 11 1.5.2. The supervising team 12 1.5.3. Types of recurring artifacts 14 1.6. Methodology 15 1.6.1. Data collection 15 1.6.2. Limitations 16 1.7. Results 16 1.7.1. Interaction modalities and media 17 1.7.2. Conditions and types of exchanges between e-tutors and students 17 1.7.3. How do e-tutors provide the feeling of telepresence from a distance? 20 1.7.4. Impact of the eT’s interventions/interactions 21 1.8. Discussion 24 1.9. Conclusion and perspectives 27 1.10. Appendix: e-tutor interview guide 28 1.11. References 30 Chapter 2. Reinforcing Telepresence in Research Training with Learning Communities: Remote Collaboration between Student-Researchers 33 Gustavo ANGULO and Cathia PAPI 2.1. Introduction 33 2.2. Multidimensional approach to distance learning 35 2.3. Modulating pedagogical distance: what presence should be created? 37 2.4. Increasing presence in the research learning process through distance learning: how to problematize collaboration between student-researchers at a distance? 41 2.5. Further questions 46 2.6. Conclusion 47 2.7. References 48 Chapter 3. Facilitating Problem-Based Learning: A Reflective Analysis 59 Ann-Louise DAVIDSON and Nadia NAFFI 3.1. Introduction 59 3.2. Context 60 3.3. Problem-based learning and problem-based learning objects 61 3.4. The use of technologies and underlying competencies 63 3.5. Description for an online course designed and developed with a problem-based approach 64 3.6. Methodological framework for our reflection 67 3.7. Reflection on student support 68 3.8. Conclusion 71 3.9. Appendix: perception matrix 73 3.10. References 73 Part 2. Telepresence in Teacher Training 77 Chapter 4. Contribution of Virtual Classes to the Construction of Professional Knowledge for Teachers 79 Romaine CARRUPT 4.1. Professional knowledge and virtual classes 79 4.2. Hybridization of part-time training 80 4.3. Construction of professional knowledge in virtual classes 80 4.3.1. A system for hybrid professional training 80 4.3.2. Synchronous communication in a virtual class 81 4.3.3. Training and support for learning in virtual classes 82 4.3.4. Professional knowledge 82 4.4. Hypotheses and research questions 83 4.5. Methodology 84 4.6. Results and analysis 87 4.6.1. Interactions in virtual classes/in person 87 4.6.2. Measurement of incorporated knowledge 89 4.7. Discussion of interactions in virtual classes and in person 91 4.7.1. Progressive interpenetration of theoretical knowledge in virtual classes 91 4.7.2. Scientific knowledge inoperative in person 94 4.7.3. Mediatized/non-mediatized interactions 97 4.7.4. An orchestration of instruments 99 4.8. Conclusion 99 4.9. References 101 Chapter 5. Support for Work through Telepresence: Teachers’ Feelings of Self-Efficacy and Strategies for Self-Management 107 Stéphanie BOÉCHAT-HEER 5.1. Introduction 107 5.2. Conceptual framework 108 5.2.1. Social interactions in telepresence and the feeling of presence 108 5.2.2. The pedagogical system and the organization of interaction between participants 109 5.2.3. The feeling of self-efficacy in the implementation of pedagogical design 110 5.3. Methodological approach 111 5.3.1. Objectives and research questions 111 5.3.2. Research type and method 112 5.3.3. Overview of research, participants and instruments 112 5.3.4. Data analysis. 113 5.4. Analysis of the results and discussion 113 5.4.1. Contrasting opinions depending on the level of the teachers’ practice in telepresence 113 5.4.2. Teachers’ feelings of self-efficacy and their self-management strategies 114 5.5. Conclusion 122 5.6. References 123 Part 3. Telepresence Robots 127 Chapter 6. Effect of a Telepresence Robot on Remote Students’ Bodily Impressions: Extended or Mended Body 129 Françoise POYET 6.1. Introduction 129 6.2. A new ontophany engendered by the telepresence robot 130 6.3. Sensory motor and bodily schema: towards an augmented body? 131 6.4. Methodology 133 6.5. Discussion 135 6.5.1. Technical appropriation of the robot facilitated by the transfer of old sensory-motor schemes 135 6.5.2. Modified perceptions, a new way to perceive and understand ubiquity as an ordinary phenomenon 136 6.5.3. Constructing a new representation of one’s body and adapting one’s bodily schema 138 6.5.4. An open window to the class: from an extended to a mended body? 139 6.5.5. A location, an interpersonal distance and redefined social behaviors 140 6.5.6. Repercussions on learning styles: a focus on attention and a change in strategy 141 6.6. Conclusion 141 6.7. Acknowledgments 142 6.8. References 143 Chapter 7. Co-construction of Tangible, Dispersed and Multi-semiotic Spaces through the Use of a Telepresence Robot 145 Dorothée FURNON 7.1. A new phenomenological experience 145 7.2. Understanding physical experience from a systemic perspective 147 7.3. Intersubjective negotiation for the construction of tangible spaces 150 7.4. Field study and data collection methods 151 7.5. Illustrations of perceptual adjustments during mediatized interactions 152 7.5.1. Transformation of a cursor into an instrument of vocal proprioception 153 7.5.2. Perceptual adjustment in the co-construction of a statement within the pedagogical relationship 155 7.6. Creation of multiple spaces for the appearance of the self and the other through an expansion of physical spaces 156 7.7. The biases and limits of provoked absence in a study based on a systemic approach. 158 7.8. Conclusion and recommendations 159 7.9. References 161 Chapter 8. The Telepresence Robot in Universities: Between Subjectification and Unlinking 163 Jean-Luc RINAUDO 8.1. Introduction 163 8.2. A telepresence system 164 8.3. The psychoanalytical clinical approach 165 8.4. Psychoanalytical approach to robots 167 8.5. Methodology 169 8.6. A surprising opportunity 169 8.7. Other considerations 172 8.8. The psycho(patho)logy of the virtual everyday: a presence in the absence 173 8.9. References 175 Chapter 9. A Telepresence Research Set-up in a Doctoral Seminar: the “Digital Presences” Workshop 179 Christine DEVELOTTE 9.1. Introduction 179 9.2. Context: reflexive research 180 9.3. Technical-physical system 184 9.4. Theoretical framework 186 9.5. Techno-methodological choices 188 9.6. Technical work on video data 189 9.7. Discussion 190 9.8. Conclusion 193 9.9. Appendices 194 9.9.1. Appendix 1. Explanatory interview 194 9.9.2. Appendix 2. Questionnaire 197 9.10. References 198 Conclusion 201 Jean-Luc RINAUDO Postface 205 Jacques WALLET List of Authors 213 Index 215

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Book SynopsisThe digital transformation of companies is both a competitive challenge and a complex step for large groups and industries, and at the same time a tremendous opportunity. This transformation is entering a new dimension with the development of immersive technologies such as virtual reality, mixed reality and augmented reality, which are revolutionizing the way we generate content as well as visualize and interact with models and data.The challenges of innovation and digital transformation within companies are now converging. Research shows the potential that immersive technologies have to accelerate the first steps of the innovation process.The objective of this book is to provide a clear vision of the state of research on immersive technologies for design and to deliver practical recommendations for companies wishing to improve their innovation process.Table of ContentsForeword ix Acknowledgments xi Preface xiii Introduction xv Chapter 1. Innovation Management: Issues and Key Points for a Vital and Strategic Process 1 1.1. A question of survival 1 1.1.1. The example of Blockbuster Video 2 1.1.2. A regime of intensive innovation 2 1.1.3. From creativity to innovation 3 1.1.4. Equipping ourselves to innovate better 4 1.1.5. Modeling innovation at the company level 6 1.2. The blue ocean strategy 6 1.3. Open innovation 8 1.3.1. The two types of open innovation 9 1.3.2. The example of the MayAM challenge 10 1.3.3. Collaborative innovation 10 1.3.4. Crowdsourcing 11 1.3.5. The lead user 11 1.4. Technical and human issues from ideation to design 13 1.4.1. The sketch as a reflective process 13 1.4.2. Types of representation 14 1.4.3. Conditions for the effectiveness of sketches 15 1.4.4. The phases of ideation 16 1.4.5. The right tools at the right time 17 1.4.6. A growing variety of tools 19 Chapter 2. Creativity and Cognition: Factors and Biases of Mental Processes Involved in Creative Activities 21 2.1. The creativity process 21 2.1.1. The Wallas model (1926) 21 2.1.2. The GENEPLORE 22 2.1.3. Analogies 24 2.2. The factors of individual creativity 26 2.2.1. The individual creativity model 26 2.2.2. Investment theory 27 2.3. Creativity and personality 28 2.3.1. The Myers Briggs Type Indicator 29 2.3.2. The Big Five 30 2.3.3. Constituting a group for ideation 31 2.4. The factors of organizational creativity 32 2.5. Cognitive biases and creativity 35 Chapter 3. Physical and Virtual Environments and their Influence on Creativity 43 3.1. Physical environment of creation 43 3.1.1. Interference and stimulation 45 3.1.2. Layout 47 3.1.3. Natural elements 50 3.1.4. Colors, sounds, light and temperature 53 3.1.5. Creativity, posture and movement 55 3.2. Virtual creation environment 59 3.2.1. Avatars 60 3.2.2. Inspiring environments 64 Chapter 4. User-Centered Innovation Methods: Design Thinking, Double Diamond, Lean UX and Time to Concept 67 4.1. Design Thinking 67 4.2. The Double Diamond 70 4.3. Lean UX 71 4.3.1. Uncertainty linked to innovation 71 4.3.2. Definition 72 4.3.3. The Lean UX loop 72 4.4. The Time to Concept method 74 4.4.1. An example of the application of Time to Concept method 74 4.4.2. Managing innovation projects in Time to Concept 76 4.4.3. The six principles of the Time to Concept method 78 Chapter 5. Some Creative Problem-Solving Methods: TRIZ, C-K, CPS, Design Sprint 83 5.1. The TRIZ method 83 5.2. The C-K theory 85 5.3. Creative Problem Solving 86 5.4. Design Sprint 87 5.5. Lateral thinking 89 5.6. Synectics 91 5.7. Detour techniques 92 5.8. Discovery matrices 93 Chapter 6. All-Terrain Ideation Techniques: Brainstorming, Brainwriting, Brainsketching, Bodystorming and Immersive-Storming 95 6.1. Brainstorming 95 6.2. Brainwriting 97 6.3. Brainsketching 98 6.4. Bodystorming 99 6.5. Immersive-storming 101 Chapter 7. Immersive Tools for Every Innovative Situation 103 7.1. Design in virtual reality 103 7.1.1. The natural gesture 103 7.1.2. Links with CAD 105 7.1.3. Comparison of sketching tools 106 7.2. Co-design in virtual reality 108 7.2.1. Information capture in virtual reality 109 7.2.2. Asymmetrical collaboration 110 7.2.3. Affordances and constraints for immersive-storming 112 7.3. Types of immersive applications for creativity 114 7.4. Choosing the right creativity tools 118 7.5. Immersive tools for innovation project stages 120 7.5.1. Immersive technologies and Design Thinking 121 7.5.2. Immersive technologies and Lean Startup 123 7.5.3. Immersive technologies and Time to Concept 124 7.5.4. Immersive technologies and the creative process 126 Chapter 8. A Successful Immersive Experience for More Creativity 129 8.1. The experience of immersed users 129 8.1.1. Drawing inspiration from reality 130 8.1.2. A future standardization 130 8.1.3. User support 131 8.1.4. Physical space planning 133 8.1.5. The psychological dimensions of the user experience 134 8.2. The creative’s user experience 135 8.2.1. The Creative Support Index 135 8.2.2. The design of tools for ideation 136 Conclusion 139 References 141 Index 159

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Book SynopsisMeticulously crafted to align with the ACM/IEEE-CS/AAAI Computer Science CS2023 curricular guidelines, Fundamentals in Computer Programming Workbook: An Active and Guide Inquiry Learning Approach to Enhance Computational Thinking empowers students to master the art of programming.Structured to facilitate both individual and collaborative learning, this workbook guides students through the intricacies of Java programming, decision structures, loops, methods, and beyond. It delves into the realms of object-oriented programming, exception handling, recursion, and algorithmic complexities before advancing into the sophisticated territories of arrays, linked lists, stacks, queues, trees, heaps, and hash tables.With a focus on active learning, the workbook employs Bloom's for Computing revised taxonomy to ensure a robust development of computational thinking skills. Each chapter is a step-by-step journey through problem-solving, supported by digital content accessible via QR codes for a seamless blend of traditional and modern learning experiences.Designed for a diverse range of learners--from community colleges to technical schools to four-year institutions--Fundamentals in Computer Programming Workbook is the perfect companion for undergraduate computer science courses and programs.

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Book SynopsisCyberspace is one of the major bases of the economic development of industrialized societies and developing. The dependence of modern society in this technological area is also one of its vulnerabilities. Cyberspace allows new power policy and strategy, broadens the scope of the actors of the conflict by offering to both state and non-state new weapons, new ways of offensive and defensive operations. This book deals with the concept of "information war", covering its development over the last two decades and seeks to answer the following questions: is the control of the information space really possible remains or she a utopia? What power would confer such control, what are the benefits? Table of ContentsIntroduction ix Chapter 1. The United States 1 1.1. Information warfare in the 1990s 1 1.1.1. Points of view from security experts 1 1.1.2. US Air Force Doctrine: AFDD 2-5 (1998) 7 1.1.3. The doctrine of the Joint Chiefs of Staff committee: JP 3-13 (1998) 10 1.1.4. Components of information warfare 14 1.2. Information warfare in the 2000s 23 1.2.1. Dictionary of the Department of Defense 23 1.2.2. US Air Force: AFDD 2-5 (2005) and AFPD 10-7 (2006) 24 1.2.3. The doctrine of the Joint Chiefs of Staff committee: JP 3-13 (2006) 26 1.3. Information warfare in the 2010s 28 1.4. Important concepts and reflections 43 1.4.1. Information operations 44 1.4.2. Information superiority 51 1.4.3. The “value” of information 62 1.4.4. Information system 65 1.4.5. Command and control warfare: C2W 66 1.4.6. Effect-based operations (EBOs) 68 1.4.7. The OODA loop 69 1.4.8. RMA 70 1.4.9. C4ISR 72 1.4.10. Network centric warfare (NCW) 73 1.4.11. ISR: intelligence, surveillance, reconnaissance 74 1.4.12. Cyberwar 75 1.4.13. Netwar 89 Chapter 2. China 91 2.1. Significant publications 91 2.2. Strategic and doctrinal thinking about information warfare. Genesis 96 2.2.1. General Wang Pufeng: one of the pioneers 97 2.2.2. Wang Baocun and Li Fei 100 2.2.3. Wei Jincheng 104 2.2.4. Colonels Qiao Liang and Wang Xiangsui: unrestricted warfare 105 2.2.5. General Dai Qingmin and Wang Baocun 111 2.2.6. General Niu Li, Colonel Li Jiangzhou and Major Xu Dehui 114 2.2.7. 2004 White Paper on national defense 115 2.3. Recent policies and strategies on information and cyber security 117 2.3.1. The Science of Military Strategy 2013 118 2.3.2. Defense White Paper 2013 118 2.3.3 Sino-Russian cybersecurity agreement 2015 119 2.3.4. PLA Daily editorial on 20 May 2015 121 2.3.5. Defense White Paper of 26 May 2015 122 2.3.6. The national cybersecurity bill of July 2015 125 2.4. Reflections 125 2.4.1. The American perspective on Chinese information warfare, modernization and informatization of the PLA 125 2.4.2. Evolution of analyses and discourse about Chinese strategy 163 2.4.3. China as a “victim” 172 2.4.4. The strategy of active defense 173 Chapter 3. Russia 177 3.1. Military doctrines and national security strategies 180 3.2. Information warfare in practice 185 3.2.1. Cyber attacks against Estonia. Who is the culprit? 186 3.2.2. The Russia–Georgia conflict 194 3.2.3. Ukraine 214 3.3. Comments 220 3.3.1. Characteristics of the Russian idea of information warfare 220 3.3.2. Aggressiveness 222 3.3.3. Type of Cold War 223 3.3.4. Challenges, objectives and targets 224 3.3.5. Psychological information warfare 229 3.3.6. Players of information warfare 233 3.3.7. Hybrid warfare and information warfare 236 3.3.8. Information warfare: what is new… 240 Chapter 4. Concepts and Theories: Discussions 247 4.1. Doctrines 247 4.2. Information warfare: definitions, models 256 4.2.1. The information environment 257 4.2.2. Definitions and models for information warfare 261 4.3. Information warfare or data warfare? 281 4.3.1. Defining data 284 4.3.2. Some theories about data 289 4.3.3. Visualization 296 4.3.4. Data warfare? 306 Conclusion 325 Index 329

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Book SynopsisThere is a great transformation of the production of knowledge and intelligibility. The "digital fold of the world" (with the convergence of NBIC) affects the collective assemblages of “thought”, of research. The aims of these assemblages are also controversial issues. From a general standpoint, these debates concern “performative science and performative society”. But one emerges and strengthens that has several names: transhumanism, post-humanism, speculative post-humanism. It appears as a great narration, a large story about the future of our existence, facing our entry into the Anthropocene. It is also presented as a concrete utopia with an anthropological and technical change. In this book, we proposed to show how collective intelligences stand in the middle of the coupling of ontological horizons and of the “process of bio-technical maturation”.Table of ContentsIntroduction ix Chapter 1. Elements of the General Configuration and Adaptive Landscape of Collective Intelligences 1 1.1. The intertwined narratives of tangible utopias and brilliant futures 1 1.2. Intelligence is “always already collective and machined” 5 1.3. Collective intelligences in the weaving of data 9 1.4. Semiotics and statistics 13 1.5. Data cities and human becomings: the new milieus of intelligence 17 1.5.1. Open Data (OD): a heterogeneous movement, the contribution to novel forms of knowledge in question 22 1.6. Coupling OD/big data/data mining 32 1.7. The semantic web as intellectual technology 34 1.8. Toward understanding onto-ethologies 42 1.9. Marketing intelligences: data and graphs in the heat of passions 50 1.10. Personal data: private property as an open and unstable process 59 1.11. The figures of the network 64 1.12. Machinic interfaces: social subjection and enslavement 67 1.13. Collective intelligences and anthropological concerns 70 1.14. Toward a new encyclopedic state: first overview 74 1.15. Controversies and boundaries 78 1.16. The milieus of intelligence and knowledge 84 1.17. Which criteria for writings? 86 1.18. Collective intelligences of usage and doxic collective intelligences: the status of short forms 90 1.19. Collective intelligences, self-organization, “swarm” intelligences 92 1.20. Short forms, relinkage, relaunching 99 1.21. Insomniac commentary as a catastrophic correction of short forms 100 1.22. Twitter as a Markovian Territory: a few remarks 103 Chapter 2. Post- and Transhumanist Horizons 107 2.1. Some bioanthropotechnical transformations 107 2.2. What to do with our brain? 113 2.3. About transhumanism and speculative posthumanism 122 2.4. Epigenetic and epiphylogenetic plasticity 125 2.5. Speculative uncertainties 127 2.6. Trans- and posthumanism as they present themselves 152 Chapter 3. Fragmented Encyclopedism 169 3.1. Collective intelligences and the encyclopedic problem 169 3.2. The political utopia in store 170 3.3. Encyclopedism and digital publishing modes 174 3.4. A new documentary process 176 3.5. Fragmented encyclopedism: education/interfaces 190 3.6. Encyclopedism and correlations 192 3.6.1. “Correlation is enough”: the Anderson controversy, and the J. Gray paradigm and their limits 192 3.7. “Perplication” in knowledge 198 3.7.1. Doxic tension in fragmented encyclopedism and format accordingly 198 3.8. Networks of the digital environment 199 3.8.1. Variations of speed and slowness at the center of encyclopedic pragmatics 200 3.9. Knowledge and thought in fragmented encyclopedism 201 3.10. What criteriology for encyclopedic writings? 202 3.11. Borders in fragmented encyclopedism: autoimmune disorders and disagreement 205 3.12. Fragmented encyclopedism: a habitat for controversies? 207 3.13. Encyclopedism according to the semantic and sociosemantic web (ontologies and web): mapping(s) and semantic levels 209 3.14. From ontologies to “onto-ethologies” and assemblages 212 3.15. Fragmented encyclopedism in the digital age: metalanguage and combinatorial 214 3.15.1. Encyclopedism and doxic immanence field: the proliferation of short forms 216 3.16. From fragmented encyclopedism to gaseous encyclopedism 217 Bibliography 219 Index 233Conclusion

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Book SynopsisInformation and communication technologies have increased their share of services in contemporary economic exchanges. We are witnessing a transformation of modern economies characterized by a predominant role of information and knowledge in the production of wealth. In order to make this intangible resource bear fruit, organizations are looking for ways, methods, procedures, processes and technical solutions to efficiently manage knowledge Within a framework of research into synergies and resource interdependence, organizations also rely on strategic alliances (joint venture), mergers or other legal forms of association that have an impact on knowledge management. This book explores the range of knowledge management techniques.Table of ContentsIntroduction ix Part 1 A Systemic Approach to the Organization Based on Knowledge Management and its Tools 1 Chapter 1 Theoretical Anchoring of Knowledge 3 1.1 Individual knowledge and skills 4 1.2 From individual learning to organizational learning 9 1.3 Knowledge management 16 1.4 Knowledge management systems 23 1.5 Communities, teams and knowledge management 26 1.6 Knowledge management and cultures 31 Chapter 2 The Design of the Learning Organization 37 2.1 From the systemic approach to the organizational design 37 2.2 Proposal of an organizational design for knowledge management: "learning organization design" 44 Part 2 Emergence of a New Design: that of the Learning Organization 61 Chapter 3 Real-World Access Methodology 63 3.1 Methodological choices 64 3.2 The field of research 67 3.3 Data collection 85 3.4 Processing of the collected data 92 Chapter 4 Case Study 99 4.1 Design of the learning organization SCCC (before the merger) 99 4.2 Design of the learning organization SCCC (period of merger with N) 108 4.3 Design of the learning organization NSN (post-merger) 114 4.4 Overview of the three phases 122 Chapter 5 Emergence of a New Organizational Design 127 5.1 Emergence of a design of the learning organization 127 5.2 Emergence of a new organizational design in view of the impact of culture 130 5.3 Emergence of a new organizational design when faced with knowledge boundaries 131 Conclusion 139 Bibliography 147 Index 171

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Book SynopsisAlan Sondheim's Writing Under explores and examines what happens to writing as it takes place on and through the networked computer. Sondheim began experimenting with artistic and philosophical writing using computers in the early 1970s. Since 1994, he has explored the possibilities of writing on the Internet, whether using blogs, web pages, emails, virtual worlds, or other tools. The sum total of Sondheim's writing online is entitled ""The Internet Text."" Writing Under selects from this work to provide insight into how writing takes place today and into the unique practices of a writer. The selections range from philosophical musings, to technical explorations of writing practice, to poetic meditations on the writer online. This work expands our understanding of writing today and charts a path for writing's future.Trade Review“Alan Sondheim is one of the precious few who joyfully-and in abject misery-risks these terrors of writing for us, for our pleasure and our undoing. What happens? Language disposes of us. As if that were not all that is required of any writer, Alan Sondheim is also the poet, the artist, the maker who has most profoundly immersed himself and his work in the life-changing code-forms-of networked computation-that have the world and its ‘genesis redux’ in their grip.”John Cayley, Literary Arts, Brown University

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Book Synopsis"You can print from an iPhone(R). It's the dumbest thing." - Bo Fahs, writer and host of Tele-Friends From the moment we began to digitise our world, we created machines that worked tirelessly to pull all that information zooming around back to the physical world. Enter: the home printer. Perhaps as payback for forming a nonsensical dichotomy, these printers couldn't just work. Not without a fight, at least. No. They insisted on screeching at plane-like decibels, plopping out pages at an excruciatingly slow pace, streaking only the most important documents and running out of ink when you know you JUST refilled the cartridge. From the first consumer inkjet to more modern monstrosities, Sh*tty Printers breaks down the worst offenders of our home offices. Featuring popular and exasperating home staples such as: - The HP Thinkjet 2225A - The Lexmark Z22 - The long forgotten Canon BJC-85 - and many more Each printer is beautifully photographed and ruthlessly torn to shreds as their individual strengths, weaknesses and charisma are scored on sliding scales born from relatable frustration.Trade Review"The author of this book, photographer and humorist J.P. Garrigues, has a weird, uncanny knack for zeroing in on exactly what’s bothering you, before you’ve even noticed it." - Bo Fahs, Foreword Contributor

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Book SynopsisThis book celebrates Michael Stonebraker's accomplishments that led to his 2014 ACM A.M. Turing Award "for fundamental contributions to the concepts and practices underlying modern database systems."The book describes, for the broad computing community, the unique nature, significance, and impact of Mike's achievements in advancing modern database systems over more than forty years. Today, data is considered the world's most valuable resource, whether it is in the tens of millions of databases used to manage the world's businesses and governments, in the billions of databases in our smartphones and watches, or residing elsewhere, as yet unmanaged, awaiting the elusive next generation of database systems. Every one of the millions or billions of databases includes features that are celebrated by the 2014 Turing Award and are described in this book.Why should I care about databases? What is a database? What is data management? What is a database management system (DBMS)? These are just some of the questions that this book answers, in describing the development of data management through the achievements of Mike Stonebraker and his over 200 collaborators. In reading the stories in this book, you will discover core data management concepts that were developed over the two greatest eras (so far) of data management technology.The book is a collection of 36 stories written by Mike and 38 of his collaborators: 23 world-leading database researchers, 11 world-class systems engineers, and 4 business partners. If you are an aspiring researcher, engineer, or entrepreneur you might read these stories to find these turning points as practice to tilt at your own computer-science windmills, to spur yourself to your next step of innovation and achievement.Table of Contents Data Management Technology Kairometer: The Historical Context Foreword Preface Introduction PART I 2014 ACM A.M. TURING AWARD PAPER AND LECTURE The Land Sharks Are on the Squawk Box PART II MIKE STONEBRAKER'S CAREER 1. Make it Happen: The Life of Michael Stonebraker PART III MIKE STONEBRAKER SPEAKS OUT: AN INTERVIEW WITH MARIANNE WINSLETT 2. Mike Stonebraker Speaks Out: An Interview PART IV THE BIG PICTURE 3. Leadership and Advocacy 4. Perspectives: The 2014 ACM Turing Award 5. Birth of an Industry: Path to the Turing Award 6. A Perspective of Mike from a 50-Year Vantage Point PART V STARTUPS 7. How to Start a Company in Five (Not So) Easy Steps 8. How to Create and Run a Stonebraker Startup-- The Real Story 9. Getting Grownups in the Room: A VC Perspective PART VI DATABASE SYSTEMS RESEARCH 10. Where Good Ideas Come From and How to Exploit Them 11. Where We Have Failed 12. Stonebraker and Open Source 13. The Relational Database Management Systems Genealogy PART VII CONTRIBUTIONS BY SYSTEM 14. Research Contributions of Mike Stonebraker: An Overview PART VII.A RESEARCH CONTRIBUTIONS BY SYSTEM 15. The Later Ingres Years 16. Looking Back at Postgres 17. Databases Meet the Stream Processing Era 18. C-Store: Through the Eyes of a Ph.D. Student 19. In-Memory, Horizontal, and Transactional: The H-Store OLTP DBMS Project 20. Scaling Mountains: SciDB and Scientific Data Management 21. Data Unification at Scale: Data Tamer 22. The BigDAWG Polystore System 23. Data Civilizer: End-to-End Support for Data Discovery, Integration, and Cleaning PART VII.B CONTRIBUTIONS FROM BUILDING SYSTEMS 24. The Commercial Ingres Codeline 25. The Postgres and Illustra Codelines 26. The Aurora/Borealis/SteamBase Codelines: A Tale of Three Systems 27. The Vertica Codeline 28. The VoltDB Codeline 29. The SciDB Codeline: Crossing the Chasm 30. The Tamr Codeline 31. The BigDAWG Codeline PART VIII PERSPECTIVES 32. IBM Relational Database Code Bases 33. Aurum: A Story about Research Taste 34. Nice: Or What It Was Like to Be Mike's Student 35. Michael Stonebraker: Competitor, Collaborator, Friend 36. The Changing of the Database Guard PART IX SEMINAL WORKS OF MICHAEL STONEBRAKER AND HIS COLLABORATORS OTLP Through the Looking Glass, and What We Found There ""One Size Fits All"": An Idea Whose Time Has Come and Gone The End of an Architectural Era (It's Time for a Complete Rewrite) C-Store: A Column-Oriented DBMS The Implementation of POSTGRES The Design and Implementation of INGRES The Collected Works of Michael Stonebraker References Index Biographies

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Book SynopsisThis book celebrates Michael Stonebraker's accomplishments that led to his 2014 ACM A.M. Turing Award "for fundamental contributions to the concepts and practices underlying modern database systems."The book describes, for the broad computing community, the unique nature, significance, and impact of Mike's achievements in advancing modern database systems over more than forty years. Today, data is considered the world's most valuable resource, whether it is in the tens of millions of databases used to manage the world's businesses and governments, in the billions of databases in our smartphones and watches, or residing elsewhere, as yet unmanaged, awaiting the elusive next generation of database systems. Every one of the millions or billions of databases includes features that are celebrated by the 2014 Turing Award and are described in this book.Why should I care about databases? What is a database? What is data management? What is a database management system (DBMS)? These are just some of the questions that this book answers, in describing the development of data management through the achievements of Mike Stonebraker and his over 200 collaborators. In reading the stories in this book, you will discover core data management concepts that were developed over the two greatest eras (so far) of data management technology.The book is a collection of 36 stories written by Mike and 38 of his collaborators: 23 world-leading database researchers, 11 world-class systems engineers, and 4 business partners. If you are an aspiring researcher, engineer, or entrepreneur you might read these stories to find these turning points as practice to tilt at your own computer-science windmills, to spur yourself to your next step of innovation and achievement.Table of Contents Data Management Technology Kairometer: The Historical Context Foreword Preface Introduction PART I 2014 ACM A.M. TURING AWARD PAPER AND LECTURE The Land Sharks Are on the Squawk Box PART II MIKE STONEBRAKER'S CAREER 1. Make it Happen: The Life of Michael Stonebraker PART III MIKE STONEBRAKER SPEAKS OUT: AN INTERVIEW WITH MARIANNE WINSLETT 2. Mike Stonebraker Speaks Out: An Interview PART IV THE BIG PICTURE 3. Leadership and Advocacy 4. Perspectives: The 2014 ACM Turing Award 5. Birth of an Industry: Path to the Turing Award 6. A Perspective of Mike from a 50-Year Vantage Point PART V STARTUPS 7. How to Start a Company in Five (Not So) Easy Steps 8. How to Create and Run a Stonebraker Startup-- The Real Story 9. Getting Grownups in the Room: A VC Perspective PART VI DATABASE SYSTEMS RESEARCH 10. Where Good Ideas Come From and How to Exploit Them 11. Where We Have Failed 12. Stonebraker and Open Source 13. The Relational Database Management Systems Genealogy PART VII CONTRIBUTIONS BY SYSTEM 14. Research Contributions of Mike Stonebraker: An Overview PART VII.A RESEARCH CONTRIBUTIONS BY SYSTEM 15. The Later Ingres Years 16. Looking Back at Postgres 17. Databases Meet the Stream Processing Era 18. C-Store: Through the Eyes of a Ph.D. Student 19. In-Memory, Horizontal, and Transactional: The H-Store OLTP DBMS Project 20. Scaling Mountains: SciDB and Scientific Data Management 21. Data Unification at Scale: Data Tamer 22. The BigDAWG Polystore System 23. Data Civilizer: End-to-End Support for Data Discovery, Integration, and Cleaning PART VII.B CONTRIBUTIONS FROM BUILDING SYSTEMS 24. The Commercial Ingres Codeline 25. The Postgres and Illustra Codelines 26. The Aurora/Borealis/SteamBase Codelines: A Tale of Three Systems 27. The Vertica Codeline 28. The VoltDB Codeline 29. The SciDB Codeline: Crossing the Chasm 30. The Tamr Codeline 31. The BigDAWG Codeline PART VIII PERSPECTIVES 32. IBM Relational Database Code Bases 33. Aurum: A Story about Research Taste 34. Nice: Or What It Was Like to Be Mike's Student 35. Michael Stonebraker: Competitor, Collaborator, Friend 36. The Changing of the Database Guard PART IX SEMINAL WORKS OF MICHAEL STONEBRAKER AND HIS COLLABORATORS OTLP Through the Looking Glass, and What We Found There ""One Size Fits All"": An Idea Whose Time Has Come and Gone The End of an Architectural Era (It's Time for a Complete Rewrite) C-Store: A Column-Oriented DBMS The Implementation of POSTGRES The Design and Implementation of INGRES The Collected Works of Michael Stonebraker References Index Biographies

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Book SynopsisThis book is an introduction to computers covering relevant topics that include: computers and society, the Internet, social media, Microsoft Office 2019, and high-level programming. The main goals are to help students to define computers and information processing and describe the main concepts related to hardware, software, and their use. The author prepares students to identify how the Internet has changed people’s lives and develops critical thinking about the role of computers in society, recognize the impact of technology in the personal and professional base, to mention a few. Emphasis is placed on developing skills in Word processing, spreadsheets, presentations, and programming algorithms.

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Book SynopsisThe field of multimedia is unique in offering a rich and dynamic forum for researchers from “traditional” fields to collaborate and develop new solutions and knowledge that transcend the boundaries of individual disciplines. Despite the prolific research activities and outcomes, however, few efforts have been made to develop books that serve as an introduction to the rich spectrum of topics covered by this broad field. A few books are available that either focus on specific subfields or basic background in multimedia. Tutorial-style materials covering the active topics being pursued by the leading researchers at frontiers of the field are currently lacking.In 2015, ACM SIGMM, the special interest group on multimedia, launched a new initiative to address this void by selecting and inviting 12 rising-star speakers from different subfields of multimedia research to deliver plenary tutorial-style talks at the ACM Multimedia conference for 2015. Each speaker discussed the challenges and state-of-the-art developments of their prospective research areas in a general manner to the broad community. The covered topics were comprehensive, including multimedia content understanding, multimodal human-human and human-computer interaction, multimedia social media, and multimedia system architecture and deployment.Following the very positive responses to these talks, the speakers were invited to expand the content covered in their talks into chapters that can be used as reference material for researchers, students, and practitioners. Each chapter discusses the problems, technical challenges, state-of-the-art approaches and performances, open issues, and promising direction for future work. Collectively, the chapters provide an excellent sampling of major topics addressed by the community as a whole. This book, capturing some of the outcomes of such efforts, is well positioned to fill the aforementioned needs in providing tutorial-style reference materials for frontier topics in multimedia.At the same time, the speed and sophistication required of data processing have grown. In addition to simple queries, complex algorithms like machine learning and graph analysis are becoming common. And in addition to batch processing, streaming analysis of real-time data is required to let organizations take timely action. Future computing platforms will need to not only scale out traditional workloads, but support these new applications too.This book, a revised version of the 2014 ACM Dissertation Award winning dissertation, proposes an architecture for cluster computing systems that can tackle emerging data processing workloads at scale. Whereas early cluster computing systems, like MapReduce, handled batch processing, our architecture also enables streaming and interactive queries, while keeping MapReduce's scalability and fault tolerance. And whereas most deployed systems only support simple one-pass computations (e.g., SQL queries), ours also extends to the multi-pass algorithms required for complex analytics like machine learning. Finally, unlike the specialized systems proposed for some of these workloads, our architecture allows these computations to be combined, enabling rich new applications that intermix, for example, streaming and batch processing.We achieve these results through a simple extension to MapReduce that adds primitives for data sharing, called Resilient Distributed Datasets (RDDs). We show that this is enough to capture a wide range of workloads. We implement RDDs in the open source Spark system, which we evaluate using synthetic and real workloads. Spark matches or exceeds the performance of specialized systems in many domains, while offering stronger fault tolerance properties and allowing these workloads to be combined. Finally, we examine the generality of RDDs from both a theoretical modeling perspective and a systems perspective.This version of the dissertation makes corrections throughout the text and adds a new section on the evolution of Apache Spark in industry since 2014. In addition, editing, formatting, and links for the references have been added.Table of Contents Preface PART I: MULTIMEDIA CONTENT ANALYSIS 1. Deep Learning for Video Classification and Captioning 2. Audition for Multimedia Computing 3. Multimodal Analysis of Free-standing Conversational Groups 4. Encrypted Domain Multimedia Content Analysis 5. Efficient Similarity Search PART II: HUMAN-CENTERED MULTIMEDIA COMPUTING 6. Social-Sensed Multimedia Computing 7. Situation Recognition Using Multimodal Data 8. Hawkes Processes for Events in Social Media 9. Utilizing Implicit User Cues for Multimedia Analytics PART III: MULTIMEDIA COMMUNICATION AND SYSTEMS 10. Multimedia Fog Computing: Minions in the Cloud and Crowd 11. Cloud Gaming Bibliography Index Editor Biography

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Book SynopsisThe field of multimedia is unique in offering a rich and dynamic forum for researchers from “traditional” fields to collaborate and develop new solutions and knowledge that transcend the boundaries of individual disciplines. Despite the prolific research activities and outcomes, however, few efforts have been made to develop books that serve as an introduction to the rich spectrum of topics covered by this broad field. A few books are available that either focus on specific subfields or basic background in multimedia. Tutorial-style materials covering the active topics being pursued by the leading researchers at frontiers of the field are currently lacking.In 2015, ACM SIGMM, the special interest group on multimedia, launched a new initiative to address this void by selecting and inviting 12 rising-star speakers from different subfields of multimedia research to deliver plenary tutorial-style talks at the ACM Multimedia conference for 2015. Each speaker discussed the challenges and state-of-the-art developments of their prospective research areas in a general manner to the broad community. The covered topics were comprehensive, including multimedia content understanding, multimodal human-human and human-computer interaction, multimedia social media, and multimedia system architecture and deployment.Following the very positive responses to these talks, the speakers were invited to expand the content covered in their talks into chapters that can be used as reference material for researchers, students, and practitioners. Each chapter discusses the problems, technical challenges, state-of-the-art approaches and performances, open issues, and promising direction for future work. Collectively, the chapters provide an excellent sampling of major topics addressed by the community as a whole. This book, capturing some of the outcomes of such efforts, is well positioned to fill the aforementioned needs in providing tutorial-style reference materials for frontier topics in multimedia.At the same time, the speed and sophistication required of data processing have grown. In addition to simple queries, complex algorithms like machine learning and graph analysis are becoming common. And in addition to batch processing, streaming analysis of real-time data is required to let organizations take timely action. Future computing platforms will need to not only scale out traditional workloads, but support these new applications too.This book, a revised version of the 2014 ACM Dissertation Award winning dissertation, proposes an architecture for cluster computing systems that can tackle emerging data processing workloads at scale. Whereas early cluster computing systems, like MapReduce, handled batch processing, our architecture also enables streaming and interactive queries, while keeping MapReduce's scalability and fault tolerance. And whereas most deployed systems only support simple one-pass computations (e.g., SQL queries), ours also extends to the multi-pass algorithms required for complex analytics like machine learning. Finally, unlike the specialized systems proposed for some of these workloads, our architecture allows these computations to be combined, enabling rich new applications that intermix, for example, streaming and batch processing.We achieve these results through a simple extension to MapReduce that adds primitives for data sharing, called Resilient Distributed Datasets (RDDs). We show that this is enough to capture a wide range of workloads. We implement RDDs in the open source Spark system, which we evaluate using synthetic and real workloads. Spark matches or exceeds the performance of specialized systems in many domains, while offering stronger fault tolerance properties and allowing these workloads to be combined. Finally, we examine the generality of RDDs from both a theoretical modeling perspective and a systems perspective.This version of the dissertation makes corrections throughout the text and adds a new section on the evolution of Apache Spark in industry since 2014. In addition, editing, formatting, and links for the references have been added.Table of Contents Preface PART I: MULTIMEDIA CONTENT ANALYSIS 1. Deep Learning for Video Classification and Captioning 2. Audition for Multimedia Computing 3. Multimodal Analysis of Free-standing Conversational Groups 4. Encrypted Domain Multimedia Content Analysis 5. Efficient Similarity Search PART II: HUMAN-CENTERED MULTIMEDIA COMPUTING 6. Social-Sensed Multimedia Computing 7. Situation Recognition Using Multimodal Data 8. Hawkes Processes for Events in Social Media 9. Utilizing Implicit User Cues for Multimedia Analytics PART III: MULTIMEDIA COMMUNICATION AND SYSTEMS 10. Multimedia Fog Computing: Minions in the Cloud and Crowd 11. Cloud Gaming Bibliography Index Editor Biography

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Book SynopsisRecent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. This has led to an increasing demand for powerful software tools to help people analyze and manage vast amounts of text data effectively and efficiently. Unlike data generated by a computer system or sensors, text data are usually generated directly by humans, and are accompanied by semantically rich content. As such, text data are especially valuable for discovering knowledge about human opinions and preferences, in addition to many other kinds of knowledge that we encode in text. In contrast to structured data, which conform to well-defined schemas (thus are relatively easy for computers to handle), text has less explicit structure, requiring computer processing toward understanding of the content encoded in text. The current technology of natural language processing has not yet reached a point to enable a computer to precisely understand natural language text, but a wide range of statistical and heuristic approaches to analysis and management of text data have been developed over the past few decades. They are usually very robust and can be applied to analyze and manage text data in any natural language, and about any topic.This book provides a systematic introduction to all these approaches, with an emphasis on covering the most useful knowledge and skills required to build a variety of practically useful text information systems. The focus is on text mining applications that can help users analyze patterns in text data to extract and reveal useful knowledge. Information retrieval systems, including search engines and recommender systems, are also covered as supporting technology for text mining applications. The book covers the major concepts, techniques, and ideas in text data mining and information retrieval from a practical viewpoint, and includes many hands-on exercises designed with a companion software toolkit (i.e., MeTA) to help readers learn how to apply techniques of text mining and information retrieval to real-world text data and how to experiment with and improve some of the algorithms for interesting application tasks. The book can be used as a textbook for a computer science undergraduate course or a reference book for practitioners working on relevant problems in analyzing and managing text data.Table of Contents PART I. OVERVIEW AND BACKGROUND Introduction Background Text Data Understanding MeTA: A Unified Toolkit for Text Data Management and Analysis PART II. TEXT DATA ACCESS Overview of Text Data Access Retrieval Models Feedback Search Engine Implementation Search Engine Evaluation Web Search Recommender Systems PART III. TEXT DATA ANALYSIS Overview of Text Data Analysis Word Association Mining Text Clustering Text Categorization Text Summarization Topic Analysis Opinion Mining and Sentiment Analysis PART IV. UNIFIED TEXT DATA MANAGEMENT ANALYSIS SYSTEM Toward a Unified System for Text Management and Analysis Appendix A. Bayesian Statistics Appendix B. Expectation-Maximization Appendix C. KL-divergence and Dirichlet Prior Smoothing References Index Authors Biographies

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Book SynopsisRecent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. This has led to an increasing demand for powerful software tools to help people analyze and manage vast amounts of text data effectively and efficiently. Unlike data generated by a computer system or sensors, text data are usually generated directly by humans, and are accompanied by semantically rich content. As such, text data are especially valuable for discovering knowledge about human opinions and preferences, in addition to many other kinds of knowledge that we encode in text. In contrast to structured data, which conform to well-defined schemas (thus are relatively easy for computers to handle), text has less explicit structure, requiring computer processing toward understanding of the content encoded in text. The current technology of natural language processing has not yet reached a point to enable a computer to precisely understand natural language text, but a wide range of statistical and heuristic approaches to analysis and management of text data have been developed over the past few decades. They are usually very robust and can be applied to analyze and manage text data in any natural language, and about any topic.This book provides a systematic introduction to all these approaches, with an emphasis on covering the most useful knowledge and skills required to build a variety of practically useful text information systems. The focus is on text mining applications that can help users analyze patterns in text data to extract and reveal useful knowledge. Information retrieval systems, including search engines and recommender systems, are also covered as supporting technology for text mining applications. The book covers the major concepts, techniques, and ideas in text data mining and information retrieval from a practical viewpoint, and includes many hands-on exercises designed with a companion software toolkit (i.e., MeTA) to help readers learn how to apply techniques of text mining and information retrieval to real-world text data and how to experiment with and improve some of the algorithms for interesting application tasks. The book can be used as a textbook for a computer science undergraduate course or a reference book for practitioners working on relevant problems in analyzing and managing text data.Table of Contents PART I. OVERVIEW AND BACKGROUND Introduction Background Text Data Understanding MeTA: A Unified Toolkit for Text Data Management and Analysis PART II. TEXT DATA ACCESS Overview of Text Data Access Retrieval Models Feedback Search Engine Implementation Search Engine Evaluation Web Search Recommender Systems PART III. TEXT DATA ANALYSIS Overview of Text Data Analysis Word Association Mining Text Clustering Text Categorization Text Summarization Topic Analysis Opinion Mining and Sentiment Analysis PART IV. UNIFIED TEXT DATA MANAGEMENT ANALYSIS SYSTEM Toward a Unified System for Text Management and Analysis App. A. Bayesian Statistics App. B. Expectation-Maximization App. C. KL-divergence and Dirichlet Prior Smoothing References Index Authors Biographies

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Book SynopsisThe Handbook of Multimodal-Multisensor Interfaces provides the first authoritative resource on what has become the dominant paradigm for new computer interfaces— user input involving new media (speech, multi-touch, gestures, writing) embedded in multimodal-multisensor interfaces. These interfaces support smart phones, wearables, in-vehicle and robotic applications, and many other areas that are now highly competitive commercially. This edited collection is written by international experts and pioneers in the field. It provides a textbook, reference, and technology roadmap for professionals working in this and related areas. This first volume of the handbook presents relevant theory and neuroscience foundations for guiding the development of high-performance systems. Additional chapters discuss approaches to user modeling and interface designs that support user choice, that synergistically combine modalities with sensors, and that blend multimodal input and output. This volume also highlights an in-depth look at the most common multimodal-multisensor combinations—for example, touch and pen input, haptic and non-speech audio output, and speech-centric systems that co-process either gestures, pen input, gaze, or visible lip movements. A common theme throughout these chapters is supporting mobility and individual differences among users. These handbook chapters provide walk-through examples of system design and processing, information on tools and practical resources for developing and evaluating new systems, and terminology and tutorial support for mastering this emerging field. In the final section of this volume, experts exchange views on a timely and controversial challenge topic, and how they believe multimodal-multisensor interfaces should be designed in the future to most effectively advance human performance.Table of Contents Introduction Theory and Neuroscience Foundations Theoretical Foundations of Multimodal Interfaces and Systems The Impact of Multimodal-Multisensory Learning on Human Performance and Brain Activation Patterns Approaches to Design and User Modeling Multisensory Haptic Interactions: Understanding the Sense and Designing for It A Background Perspective on Touch as a Multimodal Understanding and Supporting Modality Choices Using Cognitive Models to Understand Multimodal Processes: The Case for Speech and Gesture Production Multimodal Feedback in HCI: Haptics, Non-Speech Audio, and Their Applications Multimodal Technologies for Seniors: Challenges and Opportunities Common Modality Combinations Gaze Informed Multimodal Interaction Multimodal Speech and Pen Interfaces Multimodal Gesture Recognition Audio and Visual Modality Combination in Speech Processing Applications Multidisciplinary Challenge Topic: Perspectives on Learning with Multimodal Technology Contributors’ Brief Biographies: Editors, Authors and Challenge Discussants Index

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Book SynopsisThe Handbook of Multimodal-Multisensor Interfaces provides the first authoritative resource on what has become the dominant paradigm for new computer interfaces— user input involving new media (speech, multi-touch, gestures, writing) embedded in multimodal-multisensor interfaces. These interfaces support smart phones, wearables, in-vehicle and robotic applications, and many other areas that are now highly competitive commercially. This edited collection is written by international experts and pioneers in the field. It provides a textbook, reference, and technology roadmap for professionals working in this and related areas. This first volume of the handbook presents relevant theory and neuroscience foundations for guiding the development of high-performance systems. Additional chapters discuss approaches to user modeling and interface designs that support user choice, that synergistically combine modalities with sensors, and that blend multimodal input and output. This volume also highlights an in-depth look at the most common multimodal-multisensor combinations—for example, touch and pen input, haptic and non-speech audio output, and speech-centric systems that co-process either gestures, pen input, gaze, or visible lip movements. A common theme throughout these chapters is supporting mobility and individual differences among users. These handbook chapters provide walk-through examples of system design and processing, information on tools and practical resources for developing and evaluating new systems, and terminology and tutorial support for mastering this emerging field. In the final section of this volume, experts exchange views on a timely and controversial challenge topic, and how they believe multimodal-multisensor interfaces should be designed in the future to most effectively advance human performance.Table of Contents Introduction Theory and Neuroscience Foundations Theoretical Foundations of Multimodal Interfaces and Systems The Impact of Multimodal-Multisensory Learning on Human Performance and Brain Activation Patterns Approaches to Design and User Modeling Multisensory Haptic Interactions: Understanding the Sense and Designing for It A Background Perspective on Touch as a Multimodal Understanding and Supporting Modality Choices Using Cognitive Models to Understand Multimodal Processes: The Case for Speech and Gesture Production Multimodal Feedback in HCI: Haptics, Non-Speech Audio, and Their Applications Multimodal Technologies for Seniors: Challenges and Opportunities Common Modality Combinations Gaze Informed Multimodal Interaction Multimodal Speech and Pen Interfaces Multimodal Gesture Recognition Audio and Visual Modality Combination in Speech Processing Applications Multidisciplinary Challenge Topic: Perspectives on Learning with Multimodal Technology Contributors’ Brief Biographies: Editors, Authors and Challenge Discussants Index

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Book SynopsisThe Handbook of Multimodal-Multisensor Interfaces provides the first authoritative resource on what has become the dominant paradigm for new computer interfaces: user input involving new media (speech, multi-touch, hand and body gestures, facial expressions, writing) embedded in multimodal-multisensor interfaces that often include biosignals. This edited collection is written by international experts and pioneers in the field. It provides a textbook, reference, and technology roadmap for professionals working in this and related areas. This second volume of the handbook begins with multimodal signal processing, architectures, and machine learning. It includes recent deep learning approaches for processing multisensorial and multimodal user data and interaction, as well as context-sensitivity. A further highlight is processing of information about users' states and traits, an exciting emerging capability in next-generation user interfaces. These chapters discuss real-time multimodal analysis of emotion and social signals from various modalities, and perception of affective expression by users. Further chapters discuss multimodal processing of cognitive state using behavioral and physiological signals to detect cognitive load, domain expertise, deception, and depression. This collection of chapters provides walk-through examples of system design and processing, information on tools and practical resources for developing and evaluating new systems, and terminology and tutorial support for mastering this rapidly expanding field. In the final section of this volume, experts exchange views on the timely and controversial challenge topic of multimodal deep learning. The discussion focuses on how multimodal-multisensor interfaces are most likely to advance human performance during the next decade.Table of Contents 1. Multimodal Machine Learning 2. Classifying Multimodal Data 3. Learning for Multimodal and Context-sensitive Interfaces 4. Deep Learning for Multisensorial and Multimodal Interaction 5. Multimodal User State and Trait Recognition 6. Multimodal-Multisensor Affect Detection 7. Multimodal Analysis of Social Signals 8. Real-time Sensing of Affect and Social Signals in a Multimodal Framwork 9. How do Users Perceive Multimodal Expressions of Affects? 10. Multimodal Behavior and Physiological Signals as Indicators of Cognitive Load 11. Multimodal Learning Analytics 12. Multimodal Assessment of Depression and Related Disorders Based on Behavioral Signals 13. Multimodal Deception Detection 14. Perspectives on Strategic Fusion 15. Perspectives on Predictive Power of Multimodal Deep Learning

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Book SynopsisThe Handbook of Multimodal-Multisensor Interfaces provides the first authoritative resource on what has become the dominant paradigm for new computer interfaces: user input involving new media (speech, multi-touch, hand and body gestures, facial expressions, writing) embedded in multimodal-multisensor interfaces that often include biosignals. This edited collection is written by international experts and pioneers in the field. It provides a textbook, reference, and technology roadmap for professionals working in this and related areas. This second volume of the handbook begins with multimodal signal processing, architectures, and machine learning. It includes recent deep learning approaches for processing multisensorial and multimodal user data and interaction, as well as context-sensitivity. A further highlight is processing of information about users' states and traits, an exciting emerging capability in next-generation user interfaces. These chapters discuss real-time multimodal analysis of emotion and social signals from various modalities, and perception of affective expression by users. Further chapters discuss multimodal processing of cognitive state using behavioral and physiological signals to detect cognitive load, domain expertise, deception, and depression. This collection of chapters provides walk-through examples of system design and processing, information on tools and practical resources for developing and evaluating new systems, and terminology and tutorial support for mastering this rapidly expanding field. In the final section of this volume, experts exchange views on the timely and controversial challenge topic of multimodal deep learning. The discussion focuses on how multimodal-multisensor interfaces are most likely to advance human performance during the next decade.Table of Contents 1. Multimodal Machine Learning 2. Classifying Multimodal Data 3. Learning for Multimodal and Context-sensitive Interfaces 4. Deep Learning for Multisensorial and Multimodal Interaction 5. Multimodal User State and Trait Recognition 6. Multimodal-Multisensor Affect Detection 7. Multimodal Analysis of Social Signals 8. Real-time Sensing of Affect and Social Signals in a Multimodal Framwork 9. How do Users Perceive Multimodal Expressions of Affects? 10. Multimodal Behavior and Physiological Signals as Indicators of Cognitive Load 11. Multimodal Learning Analytics 12. Multimodal Assessment of Depression and Related Disorders Based on Behavioral Signals 13. Multimodal Deception Detection 14. Perspectives on Strategic Fusion 15. Perspectives on Predictive Power of Multimodal Deep Learning

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Book SynopsisThis textbook presents the elementary aspects of quantum computing in a mathematical form. It is intended as core or supplementary reading for physicists, mathematicians, and computer scientists taking a first course on quantum computing. It starts by introducing the basic mathematics required for quantum mechanics, and then goes on to present, in detail, the notions of quantum mechanics, entanglement, quantum gates, and quantum algorithms, of which Shor's factorisation and Grover's search algorithm are discussed extensively. In addition, the algorithms for the Abelian Hidden Subgroup and Discrete Logarithm problems are presented and the latter is used to show how the Bitcoin digital signature may be compromised. It also addresses the problem of error correction as well as giving a detailed exposition of adiabatic quantum computing. The book contains around 140 exercises for the student, covering all of the topics treated, together with an appendix of solutions.Table of ContentsIntroduction.- Basic Notions of Quantum Mechanics.- Tensor Products and Composite Systems.- Entanglement.- Quantum Gates and Circuits for Elementary Calculations.- On the Use of Entanglement.- Error Correction.- Adiabatic Quantum Computing.- Epilogue Appendices: A Elementary Probability Theory.- B Elementary Arithmetic Operations.- C LANDAU Symbols.- D Modular Arithmetic.- E Continued Fractions.- F Some Group Theory.- G Proof of a Quantum Adiabatic Theorem.- Solutions to Exercises.

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Book SynopsisThis book presents the proceedings of the NeuroIS Retreat 2021, June 1-3, virtual conference, reporting on topics at the intersection of information systems (IS) research, neurophysiology and the brain sciences. Readers will discover the latest findings from top scholars in the field of NeuroIS, which offer detailed insights on the neurobiology underlying IS behavior, essential methods and tools and their applications for IS, as well as the application of neuroscience and neurophysiological theories to advance IS theory.Table of ContentsWhere NeuroIS Helps to Understand Human Processing of Text: A Taxonomy for Research Questions Based on Textual Data.- Towards a Psychophysiological Investigation of Perceived Trustworthiness and Risk in Online Pharmacies: Results of a Pre-Study.- Exploring the Influence of Personality Traits on Affective Customer Experiences in Retailing: Combination of Heart Rate Variability (HRV) and Self-Report Measures.- Motor dysfunction simulation in able-bodied participants for usability evaluation of assistive technology:A research proposal.- Exploring the Potential of NeuroIS in the Wild: Opportunities and Challenges of Home Environments.- Exploring the Recognition of Facial Activities Through Around-the-Ear Electrode Arrays (cEEGrids).

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Book SynopsisThis book constitutes the refereed proceedings of the 23rd International Conference on Asia-Pacific Digital Libraries, ICADL 2021, which was held in December 2021. Due to COVID-19 pandemic the conference was held virtually.The 17 full, 14 short, and 5 practice papers presented in this volume were carefully reviewed and selected from 87 submissions. The papers were organized in topical sections named: Knowledge Discovery from Digital Collections; Search for Better User Experience; Information Extraction; Multimedia; Text Classification and Matching; Data Infrastructure for Digital Libraries; Data Modeling; Neural-based Learning.

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Book SynopsisThis open access book describes the development of Innopolis, a young Russian university established in 2012 to focus on teaching excellence in computer science, engineering, and robotics. It reports on the problems that were faced in the first decade of its development, and the adopted solutions. It shows how the key aspects for the development of the faculty, the curricula, the university structure, and the challenge of internationalization have been successfully addressed by the university management and professors, and how the solutions are scalable for other newly founded research organizations.The book is divided in five parts: “The Beginning” describes the very early days in general, from the foundation and start-up of the university with the related processes. “The People” reports on the initial hiring of the faculty members, the selection of students, and the curriculum development. “The Activities” provide information about the creation of the single research institutions and labs, and their relation to industry. “The Future” gives an outlook on the planned internationalization and faculty strategy. Eventually, “A Visual Journey” shows a selection of photographs illustrating highlights of the whole process and the current achievements. The processes and the components described built the basis for the development of Innopolis, and many of them still have a big impact on its present and its future. The fewer mistakes are made at the beginning, the higher the probability to fully achieve the initial goals.Table of ContentsPart I: The Beginning.- 1. The Arcadia of Innopolis.- 2. Early Days and Further Development.- Part II: The People.- 3. Hiring and Developing an International Faculty.- 4. Curricula and Language of Instruction.- 5. Attracting the Best Students.- 6. The Research Environment and Our Values.- Part III: The Activities.- 7. Faculty, Institutes, and Labs.- 8. Cooperation with Industry.- Part IV: The Future.- 9. Internationalization of the University.- 10. Online and Blended Education: After COVID-19.- 11. Faculty Strategy for the Future.- 12. Conclusion.- Part V: A Visual Journey.- 13. Photobook.

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Book SynopsisThis book constitutes the refereed proceedings of the 36th Annual IFIP WG 11.3 Conference on Data and Applications Security and Privacy, DBSec 2022, held in Newark, NJ, USA, in July 2022.The 12 full papers and 6 short papers presented were carefully reviewed and selected from 33 submissions. The conference covers research in data and applications security and privacy.Table of ContentsData Privacy.- Distributed Systems.- IoT Security.- Privacy-Preserving Access and Computation.- Quantum Security.- Security Operations and Policies.

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Book SynopsisThis two-volume set of LNCS 13393 and LNCS 13394 constitutes - in conjunction with the volume LNAI 13395 - the refereed proceedings of the 18th International Conference on Intelligent Computing, ICIC 2022, held in Xi'an, China, in August 2022. The 209 full papers of the three proceedings volumes were carefully reviewed and selected from 449 submissions.This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was “Advanced Intelligent Computing Technology and Applications”. Papers focused on this theme were solicited, addressing theories, methodologies, and applications in science and technology.Table of ContentsEvolutionary Computing and Learning. Neural Networks.- Pattern Recognition.- Image Processing.- Information Security.- Biomedical Informatics Theory and Methods.- Biomedical Data Modeling and Mining.- Intelligent Computing in Computational Biology.- Computational Genomics and Biomarker Discovery.- Intelligent Computing in Drug Design.- Theoretical Computational Intelligence and Applications.- Fuzzy Theory and Algorithms.- Machine Learning and Data Mining.- Intelligent Computing in Computer Vision.- Intelligent Control and Automation.- Intelligent Data Analysis and Prediction.- Intelligent Computing and Optimization.

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Book SynopsisThis book constitutes the proceedings of the 5th International Workshop on Predictive Intelligence in Medicine, PRIME 2022, held in conjunction with MICCAI 2022 as a hybrid event in Singapore, in September 2022.The 19 papers presented in this volume were carefully reviewed and selected for inclusion in this book. The contributions describe new cutting-edge predictive models and methods that solve challenging problems in the medical field for a high-precision predictive medicine.Table of ContentsFederated Time-dependent GNN Learning from Brain Connectivity Data with Missing Timepoints.- Bridging the Gap between Deep Learning and Hypothesis-Driven Analysis via Permutation Testing.- Multi-Tracer PET Imaging Using Deep Learning: Applications in Patients with High-Grade Gliomas.- Multiple Instance Neuroimage Transformer.- Intervertebral Disc Labeling With Learning Shape Information, A Look Once Approach.- Mixup augmentation improves age prediction from T1-weighted brain MRI scans.- Diagnosing Knee Injuries from MRI with Transformer Based Deep Learning.- MISS-Net: Multi-view contrastive transformer network for MCI stages prediction using brain 18F-FDG PET imaging.- TransDeepLab: Convolution-Free Transformer-based DeepLab v3+ for Medical Image Segmentation.- Opportunistic hip fracture risk prediction in Men from X-ray: Findings from the Osteoporosis in Men (MrOS) Study.- Weakly-Supervised TILs Segmentation based on Point Annotations using Transfer Learning with Point Detector and Projected-Boundary Regressor.- Discriminative Deep Neural Network for Predicting Knee OsteoArthritis in Early Stage.- Long-Term Cognitive Outcome Prediction in Stroke Patients Using Multi-Task Learning on Imaging and Tabular Data.- Quantifying the Predictive Uncertainty of Regression GNN Models Under Target Domain Shifts.- Investigating the Predictive Reproducibility of Federated Graph Neural Networks using Medical Datasets.- Learning subject-specific functional parcellations from cortical surface measures.- A Triplet Contrast Learning of Global and Local Representations for Unannotated Medical Images.- Predicting Brain Multigraph Population From a Single Graph Template for Boosting One-Shot Classification.- Meta-RegGNN: Predicting Verbal and Full-Scale Intelligence Scores using Graph Neural Networks and Meta-Learning

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Book SynopsisThe 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23–27, 2022. The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.Table of ContentsA Simple Approach and Benchmark for 21,000-Category Object Detection.- Knowledge Condensation Distillation.- Reducing Information Loss for Spiking Neural Networks.- Masked Generative Distillation.- Fine-Grained Data Distribution Alignment for Post-Training Quantization.- Learning with Recoverable Forgetting.- Efficient One Pass Self-Distillation with Zipf’s Label Smoothing.- Prune Your Model before Distill It.- Deep Partial Updating: Towards Communication Efficient Updating for On-Device Inference.- Patch Similarity Aware Data-Free Quantization for Vision Transformers.- L3: Accelerator-Friendly Lossless Image Format for High-Resolution, High-Throughput DNN Training.- Streaming Multiscale Deep Equilibrium Models.- Symmetry Regularization and Saturating Nonlinearity for Robust Quantization.- SP-Net: Slowly Progressing Dynamic Inference Networks.- Equivariance and Invariance Inductive Bias for Learning from Insufficient Data.- Mixed-Precision Neural Network Quantization via Learned Layer-Wise Importance.- Event Neural Networks.- EdgeViTs: Competing Light-Weight CNNs on Mobile Devices with Vision Transformers.- PalQuant: Accelerating High-Precision Networks on Low-Precision Accelerators.- Disentangled Differentiable Network Pruning.- IDa-Det: An Information Discrepancy-Aware Distillation for 1-Bit Detectors.- Learning to Weight Samples for Dynamic Early-Exiting Networks.- AdaBin: Improving Binary Neural Networks with Adaptive Binary Sets.- Adaptive Token Sampling for Efficient Vision Transformers.- Weight Fixing Networks.- Self-Slimmed Vision Transformer.- Switchable Online Knowledge Distillation.- ℓ∞-Robustness and Beyond: Unleashing Efficient Adversarial Training.- Multi-Granularity Pruning for Model Acceleration on Mobile Devices.- Deep Ensemble Learning by Diverse Knowledge Distillation for Fine-Grained Object Classification.- Helpful or Harmful: Inter-Task Association in Continual Learning.- Towards Accurate Binary Neural Networks via Modeling Contextual Dependencies.- SPIN: An Empirical Evaluation on Sharing Parameters of Isotropic Networks.- Ensemble Knowledge Guided Sub-network Search and Fine-Tuning for Filter Pruning.- Network Binarization via Contrastive Learning.- Lipschitz Continuity Retained Binary Neural Network.- SPViT: Enabling Faster Vision Transformers via Latency-Aware Soft Token Pruning.- Soft Masking for Cost-Constrained Channel Pruning.- Non-uniform Step Size Quantization for Accurate Post-Training Quantization.- SuperTickets: Drawing Task-Agnostic Lottery Tickets from Supernets via Jointly Architecture Searching and Parameter Pruning.- Meta-GF: Training Dynamic-Depth Neural Networks Harmoniously.- Towards Ultra Low Latency Spiking Neural Networks for Vision and Sequential Tasks Using Temporal Pruning.- Towards Accurate Network Quantization with Equivalent Smooth Regularizer.

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Book SynopsisThis three-volume set, LNAI 13629, LNAI 13630, and LNAI 13631 constitutes the thoroughly refereed proceedings of the 19th Pacific Rim Conference on Artificial Intelligence, PRICAI 2022, held in Shangai, China, in November 10–13, 2022.The 91 full papers and 39 short papers presented in these volumes were carefully reviewed and selected from 432 submissions. PRICAI covers a wide range of topics in the areas of social and economic importance for countries in the Pacific Rim: artificial intelligence, machine learning, natural language processing, knowledge representation and reasoning, planning and scheduling, computer vision, distributed artificial intelligence, search methodologies, etc.Table of ContentsRecommender System.- Mixture of Graph Enhanced Expert Networks for Multi-task Recommendation.- MF-TagRec: Multi-feature fused tag recommendation for GitHub.- Co-contrastive Learning for Multi-behavior Recommendation.- Pattern Matching and Information-aware between Reviews and Ratings for Recommendation.- Cross-view Contrastive Learning for Knowledge-aware Session-based Recommendation.- Reinforcement Learning.- HiSA: Facilitating Efficient Multi-Agent Coordination and Cooperation by Hierarchical Policy with Shared Attention.- DDMA: Discrepancy-Driven Multi-Agent Reinforcement Learning.- PRAG: Periodic Regularized Action Gradient for Efficient Continuous Control.- Identifying Multiple Influential Nodes for Complex Networks based on Multi-Agent Deep Reinforcement Learning.- Online Learning in Iterated Prisoner’s Dilemma to Mimic Human Behavior.- Optimizing Exploration-Exploitation Trade-off in Continuous Action Spaces via Q-ensemble.- Hidden Information General Game Playing With Deep Learning and Search.- Sequential Decision Making with “Sequential Information” in Deep Reinforcement Learning.- Two-Stream Communication-Efficient Federated Pruning Network.- Strong General AI.- Multi-scale Lightweight Neural Network for Real-time Object Detection.- Hyperspectral Image Classification Based On Transformer and Generative Adversarial Network.- Deliberation Selector for Knowledge-grounded Conversation Generation.- Training a Lightweight ViT Network for Image Retrieval.- Vision and Perception.- Segmented–original Image Pairs to Facilitate Feature Extraction in Deep Learning Models.- FusionSeg: Motion Segmentation by Jointly Exploiting Frames and Events.- Weakly-supervised Temporal Action Localization with Multi-head Cross-modal Attention.- CrGAN: Continuous Rendering of Image Style.- DPCN: Dual Path Convolutional Network for Single Image Deraining.- All Up to You: Controllable Video Captioning With a Masked Scene Graph.- A Multi-Head Convolutional Neural Network With Multi-path Attention improves Image Denoising.- Learning Spatial Fusion and Matching for Visual Object Tracking.- Lightweight Wavelet-based Transformer for Image Super-resolution.- Efficient high-resolution human pose estimation.- The Geometry Enhanced Deep Implicit Function based 3D Reconstruction for objects in a real-scene image.- Multi-View Stereo Network with Attention Thin Volume.- 3D Point Cloud Segmentation Leveraging Global 2D-view Features.- Self-Supervised Indoor 360-Degree Depth Estimation via Structural Regularization.- Global Boundary Refinement for Semantic Segmentation via Optimal Transport.- Optimization-based Predictive Approach for On-Demand Transportation.- Joint Contrast: Skeleton-based Mutual Action Recognition with Contrastive Learning.- Nested Multi-Axis Learning Network for Single Image Super Resolution.- Efficient Scale Divide and Conquer Network for Object Detection.- Video-Based Emotion Recognition in the Wild for Online Education Systems.- Real-world Underwater Image Enhancement via Degradation-aware Dynamic Network.- Self-Supervised Vision Transformer based Nearest Neighbor Classification for Multi-Source Open-Set Domain Adaptation.- Lightweight image dehazing neural network model based on estimating medium transmission map by intensity.- CMNet: Cross-aggregation Multi-branch Network for Salient Object Detection.- More than Accuracy: an Empirical Study of Consistency between Performance and Interpretability.- Object-scale Adaptive Optical Flow Estimation Network.- A Task-aware Dual Similarity Network for Fine-grained Few-shot Learning.- Rotating Target Detection Based On Lightweight Network.- Corner Detection Based on a Dynamic Measure of Cornerity.

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Book SynopsisThis volume set constitutes the refereed proceedings of the 16th International Conference on Knowledge Science, Engineering and Management, KSEM 2023, which was held in Guangzhou, China, during August 16–18, 2023. The 114 full papers and 30 short papers included in this book were carefully reviewed and selected from 395 submissions. They were organized in topical sections as follows: knowledge science with learning and AI; knowledge engineering research and applications; knowledge management systems; and emerging technologies for knowledge science, engineering and management. Table of ContentsKnowledge Science with Learning and AI.- ​Joint Feature Selection and Classifier Parameter Optimization: A Bio-inspired Approach.- Automatic Gaussian Bandwidth Selection for Kernel Principal Component Analysis.- Boosting LightWeight Depth Estimation Via Knowledge Distillation.- Graph Neural Network with Neighborhood Reconnection.- Critical Node Privacy Protection Based on Random Pruning of Critical Trees.- DSEAformer: Forecasting by De-stationary Autocorrelation with Edgebound.- Multitask-based Cluster Transmission for Few-Shot Text Classification.- Hyperplane Knowledge Graph Embedding with Path Neighborhoods and Mapping Properties.- RTAD-TP: Real- Time Anomaly Detection Algorithm for Univariate Time Series Data Based on Two- Parameter Estimation.- Multi-Sampling Item Response Ranking Neural Cognitive Diagnosis with Bilinear Feature Interaction.- A Sparse Matrix Optimization Method for Graph Neural Networks Training.- Dual-dimensional Refinement of Knowledge Graph Embedding Representation.- Contextual Information Augmented Few-Shot Relation Extraction.- Dynamic and Static Feature-aware Microservices Decomposition via Graph Neural Networks.- An Enhanced Fitness-distance Balance Slime Mould Algorithm and Its Application in Feature Selection.- Low Redundancy Learning for Unsupervised Multi-view Feature Selection.- Dynamic Feed-Forward LSTM.- Black-box Adversarial Attack on Graph Neural Networks Based on Node Domain Knowledge.- Role and Relationship-Aware Representation Learning for Complex Coupled Dynamic Heterogeneous Networks.- Twin Graph Attention Network with Evolution Pattern Learner for Few-Shot Temporal Knowledge Graph Completion.- Subspace Clustering with Feature Grouping for Categorical Data.- Learning Graph Neural Networks on Feature-Missing Graphs.- Dealing with Over-reliance on Background Graph for Few-shot Knowledge Graph Completion.- Kernel-based feature extraction for time series clustering.- Cluster Robust Inference for embedding-based Knowledge Graph Completion.- Community-enhanced Contrastive Siamese networks for Graph Representation Learning.- Distant Supervision Relation Extraction with Improved PCNN and Multi-level Attention.- Enhancing Adversarial Robustness via Anomaly-aware Adversarial Training.- An Improved Cross-Validated Adversarial Validation Method.- EACCNet: Enhanced Auto-Cross Correlation Network for Few-Shot Classification.- Joint Label-Structure Estimation from Multifaceted Graph Data.- Dual Channel Knowledge Graph Embedding with Ontology Guided Data Augmentation.- Multi-Dimensional Graph Rule Learner.- MixUNet: A Hybrid Retinal Vessels Segmentation Model Combining The Latest CNN and MLPs.- Robust Few-shot Graph Anomaly Detection via Graph Coarsening.- An Evaluation Metric for Prediction Stability with Imprecise Data.- Reducing The Teacher-Student Gap Via Elastic Student.

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Book SynopsisThe multi-volume set LNAI 14169 until 14175 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, in September 2023.The 196 papers were selected from the 829 submissions for the Research Track, and 58 papers were selected from the 239 submissions for the Applied Data Science Track. The volumes are organized in topical sections as follows:Part I: Active Learning; Adversarial Machine Learning; Anomaly Detection; Applications; Bayesian Methods; Causality; Clustering.Part II: ​Computer Vision; Deep Learning; Fairness; Federated Learning; Few-shot learning; Generative Models; Graph Contrastive Learning.Part III: ​Graph Neural Networks; Graphs; Interpretability; Knowledge Graphs; Large-scale Learning.Part IV: ​Natural Language Processing; Neuro/Symbolic Learning; Optimization; Recommender Systems; Reinforcement Learning; Representation Learning.Part V: ​Robustness; Time Series; Transfer and Multitask Learning.Part VI: ​Applied Machine Learning; Computational Social Sciences; Finance; Hardware and Systems; Healthcare & Bioinformatics; Human-Computer Interaction; Recommendation and Information Retrieval.​Part VII: Sustainability, Climate, and Environment.- Transportation & Urban Planning.- Demo.Table of ContentsRobustness.- Time Series.- Transfer and Multitask Learning.

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Book SynopsisThe 10-volume set LNCS 14254-14263 constitutes the proceedings of the 32nd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2023, which took place in Heraklion, Crete, Greece, during September 26–29, 2023.The 426 full papers, 9 short papers and 9 abstract papers included in these proceedings were carefully reviewed and selected from 947 submissions. ICANN is a dual-track conference, featuring tracks in brain inspired computing on the one hand, and machine learning on the other, with strong cross-disciplinary interactions and applications. Table of ContentsA Shallow Information Enhanced Efficient Small Object Detector based on YOLOv5.- Adaptive Dehazing YOLO for Object Detection.- Adaptive Training Strategies for Small Object Detection using Anchor-based Detectors.- Automatic Driving Scenarios: A Cross-Domain Approach for Object Detection.- Dual Attention Feature Fusion for Visible-Infrared Object Detection.- Feature Sniffer: A Stealthy Inference Attacks Framework on Split Learning.- Few-Shot Object Detection via Transfer Learning and Contrastive Reweighting.- GaitFusion: Exploring the fusion of silhouettes and optical flow for gait recognition.- Gradient Adjusted and Weight Rectified Mean Teacher for Source-free Object Detection.- IMAM: Incorporating multiple attention mechanisms for 3D Object Detection from Point Cloud.- LGF2: Local and Global Feature Fusion for Text-guided Object Detection.- MLF-DET: Multi-Level Fusion for Cross-Modal 3D Object Detection.- Object Detection in Foggy Images with Transmission Map Guidance.- PE-YOLO: Pyramid Enhancement Network for Dark Object Detection.- Region Feature Disentanglement for Domain Adaptive Object Detection.- ROFusion: Efficient Object Detection using Hybrid Point-wise Radar-Optical Fusion.- SDGC-YOLOv5: A more accurate model for small object detection.- The Statistical Characteristics of P3a and P3b Subcomponents in Electroencephalography Signals.- Transforming Limitations into Advantages: Improving Small Object Detection Accuracy with SC-AttentionIoU Loss Function.- Visual-Haptic-Kinesthetic Object Recognition with Multimodal Transformer.- X-shape Feature Expansion Network for Salient Object Detection in Optical Remote Sensing Images.- Aggregate Distillation For Top-K Recommender System.- Candidate-Aware Dynamic Representation for News Recommendation.- Category Enhanced Dual View Contrastive Learning for Session-based Recommendation.- Electronic Medical Record Recommendation System Based on Deep Embedding Learning with Named Entity Recognition.- Incremental Recommendation Algorithm based on the Influence Propagation Model.- Scenic Spot Recommendation Method Integrating Knowledge Graph And Distance Cost.- A Unified Video Semantics Extraction and Noise Object Suppression Network for Video Saliency Detection.- Adaptive Token Excitation With Negative Selection For Video-Text Retrieval.- Boosting Video Super Resolution with Patch-Based Temporal Redundancy Optimization.- Bring the Noise: Introducing Noise Robustness to Pretrained Automatic Speech Recognition.- Correction while Recognition: Combining Pretrained Language Model for Taiwan-accented Speech Recognition.- Cross-Camera Prototype Learning for Intra-Camera Supervised Person Re-Identification.- ECDet: A Real-time Vehicle Detection Network for CPU-only Devices.- Gated Multi-Modal Fusion with Cross-Modal Contrastive Learning for Video Question Answering.- Learning Video Localization on Segment-Level Video Copy Detection with Transformer.- Linear Transformer-GAN: A Novel Architecture to Symbolic Music Generation.- MBMS-GAN: Multi-Band Multi-Scale Adversarial Learning for Enhancement of Coded Speech at Very Low Rate.- OWS-Seg: online weakly supervised video instance segmentation via contrastive learning.- Replay to Remember: Continual Layer-Specific Fine-tuning for German Speech Recognition.- Self-Supervised Video Object Segmentation Using Motion Feature Compensation.- Space-Time Video Super-Resolution Based on Long-Term Time Dependence.

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Book SynopsisThe 10-volume set LNCS 14254-14263 constitutes the proceedings of the 32nd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2023, which took place in Heraklion, Crete, Greece, during September 26–29, 2023.The 426 full papers, 9 short papers and 9 abstract papers included in these proceedings were carefully reviewed and selected from 947 submissions. ICANN is a dual-track conference, featuring tracks in brain inspired computing on the one hand, and machine learning on the other, with strong cross-disciplinary interactions and applications. Table of Contents2RDA: Representation and Relation Distillation with Data Augmentation.- A Document-Level Relation Extraction Framework with Dynamic Pruning.- A Global Feature Fusion Network for Lettuce Growth Trait Detection.- Adaptive Embedding and Distribution Re-Margin for Long-tail Recognition.- Adaptive Propagation Network Based on Multi-Scale Information Fusion.- An Efficient Approach for Improving the Recall of Rough Abstract Retrieval in Scientific Claim Verification.- An Explainable Feature Selection Approach for Fair Machine Learning.- Anchor link prediction based on trusted anchor re-identification.- Application of Data Encryption in Chinese Named Entity Recognition.- Attractor dynamics drive flexible timing in birdsong.- Boost Predominant Instrument Recognition Performance with MagiaSearch and MagiaClassifier.- Can Machine Learning Support Improvement in Effective Nutrition of patients in Critical Care Units?.- Cross-Domain Transformer with Adaptive Thresholding for Domain Adaptive Semantic Segmentation.- Delineation of prostate boundary from medical images via a mathematical formula-based hybrid algorithm.- Diversifying non-dissipative Reservoir Computing dynamics.- Efficient Reinforcement Learning using State-Action Uncertainty with Multiple Heads.- Exploring the role of feedback inhibition for the robustness against corruptions on event-based data.- Extracting feature space for synchronizing behavior in an interaction scene using unannotated data.- F-E Fusion:A Fast Detection Method of Moving UAV Based on Frame and Event Flow.- Few-shot Relational Triple Extraction based on Evaluation of Token-Level Semantic Similarity.- GII: a Unified Approach to Representation Learning in Open Set Recognition with Novel Category Discovery.- Glancing text and vision regularized training to enhance machine translation.- Global-Temporal Enhancement for Sign Language Recognition.- Global-to-contextual Shared Semantic Learning for Fine-grained Vision-language Alignment.- Gradient-based Learning of Finite Automata.- Hierarchical Contrastive Learning for CSI-based Fingerprint Localization.- Higher Education Programming Competencies: A Novel Dataset.- Higher Target Relevance Parallel Machine Translation with Low-Frequency Word Enhancement.- I^2KD-SLU: An Intra-Inter Knowledge Distillation Framework for Zero-Shot Cross-Lingual Spoken Language Understanding.- Imbalanced Few-shot Learning based on Meta-transfer Learning.- Impact Analysis of Climate Change on Floods in an Indian Region using Machine Learning.- Improving Limited Resource Speech Recognition Performance with Latent Regression Bayesian Network.- Input Layer Binarization with Bit-Plane Encoding.- Investigation of Information Processing Mechanisms in the Human Brain during Reading Tanka Poetry.- Joint Demosaicing and Denoising with Frequency Domain Features.- Knowledge Distillation with Feature Enhancement Mask.- Label-description Enhanced Network for Few-shot Named Entity Recognition.- Landslide Surface Displacement Prediction Based on VSXC-LSTM Algorithm.- LaneMP: Robust Lane Attention Detection based on Mutual Perception of Keypoints.- LE-MVSNet: Lightweight Efficient Multi-view Stereo Network.- Lightweight Reference-Less Summary Quality Evaluation via Key Feature Extraction.- Limited Information Opponent Modeling.

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Book SynopsisThe 10-volume set LNCS 14254-14263 constitutes the proceedings of the 32nd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2023, which took place in Heraklion, Crete, Greece, during September 26–29, 2023.The 426 full papers and 9 short papers included in these proceedings were carefully reviewed and selected from 947 submissions. ICANN is a dual-track conference, featuring tracks in brain inspired computing on the one hand, and machine learning on the other, with strong cross-disciplinary interactions and applications.Table of ContentsMEA-TransUNet: a Multiple External Attention Network for Multi-Organ Segmentation.- Membership-Grade Based Prototype Rectification for Fine-Grained Few-Shot Classification.- Multi-grained Aspect Fusion for Review Response Generation.- Multiple Object Tracking based on Variable GIoU-Embedding Matrix and Kalman Filter Compensation.- Multi-relation Identification for Few-shot Document-level Relation Extraction.- Multi-Task Learning for Mongolian Morphological Analysis.- Multi-task Pre-training for Lhasa-Tibetan Speech Recognition.- Mutual Information Dropout: Mutual Information Can Be All You Need.- Non-Outlier Pseudo-Labeling for Short Text Clustering.- Optimal Node Embedding Dimension Selection Using Overall Entropy.- PairEE: A Novel Pairing-Scoring Approach for Better Overlapping Event Extraction.- PCB Component Rotation Detection Based on Polarity Identifier Attention.- PCDialogEval: Persona and Context Aware Emotional Dialogue Evaluation.- PlantDet: A benchmark for Plant Detection in the Three-Rivers-Source Region.- PO-DARTS: Post-Optimizing the Architectures Searched by Differentiable Architecture Search Algorithms.- Predicting high vs low mother-baby synchrony with GRU-based ensemble models.- Properties of the weighted and robust implicitly weighted correlation coefficients.- PSML: Prototype-Based OSSL Framework for Multi-Information Mining.- Pure Physics-Informed Echo State Network of ODE Solution Replicator.- RegionRel:A Framework for Jointly Extracting Relational Triplets by Performing Sub-tasks by Region.- Robustness to Variability and Asymmetry of In-memory On-chip Training.- Selecting Distinctive-Variant Training Samples Base on Intra-class Similarity.- Semantic Information Mining and Fusion Method for Bot Detection.- Semilayer-Wise Partial Quantization without Accuracy Degradation or Back Propagation.- ShadowGAN for Line Drawings Shadow Generation.- Ship Attitude Prediction Based on Dynamic Sliding Window and EEMD-SSA-BiLSTM.- Solving Math Word Problem with External Knowledge and Entailment Loss.- Spatially Invariant and Frequency-Aware CycleGAN for Unsupervised MR-to-CT Synthesis.- Spatio-temporal Attention Model with Prior Knowledge for Solar Wind Speed Prediction.- Spatiotemporal model with attention mechanism for ENSO Predictions.- SPM-Diffusion for Temperature Prediction.- S-SOLVER: Numerically stable adaptive step size solver for neural ODEs.- TableSF: A Structural Bias Framework for Table-to-Text Generation.- TCS-LipNet:Temporal & Channel & Spatial Attention-based Lip Reading Network.- The Dynamic Selection of Combination Methods in Classifier Ensembles by Region of Competence.- The progressive detectors and discriminative feature descriptors combining global and local information.- Towards Better Dialogue Utterance Rewriting via a Gated Span-Copy Mechanism.- TSP Combination Optimization with Semi-local Attention Mechanism.- UDCGN: Uncertainty-Driven Cross-Guided Network for Depth Completion of Transparent Objects.- Use of Machine Learning Algorithms to Analyze the Digit Recognizer Problem in an Effective Manner.- Vulnerability Analysis of Continuous Prompts for Pre-trained Language Models.

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Book SynopsisThe 10-volume set LNCS 14254-14263 constitutes the proceedings of the 32nd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2023, which took place in Heraklion, Crete, Greece, during September 26–29, 2023.The 426 full papers, 9 short papers and 9 abstract papers included in these proceedings were carefully reviewed and selected from 947 submissions. ICANN is a dual-track conference, featuring tracks in brain inspired computing on the one hand, and machine learning on the other, with strong cross-disciplinary interactions and applications. Table of ContentsA Data Augmentation based ViT for Fine-Grained Visual Classification.- A Detail Geometry Learning Network for High-Fidelity Face Reconstruction.- A Lightweight Multi-Scale Large Kernel Attention Hierarchical Network for Single Image Deraining.- A Multi-Scale Method for Cell Segmentation in Fluorescence Microscopy Images.- Adaptive interaction-based multi-view 3D object reconstruction.- An auxiliary modality based Text-Image matching methodology for fake news detection.- An Improved Lightweight YOLOv5 for Remote Sensing Images.- An Improved YOLOv5 with Structural Reparameterization for Surface Defect Detection.- ASP Loss: Adaptive Sample-Level Prioritizing Loss for Mass Segmentation on Whole Mammography Images.- Cascaded Network-based Single-View Bird 3D Reconstruction.- CLASPPNet: A Cross-Layer Multi-Class Lane Semantic Segmentation Model Fused with Lane Detection Module.- Classification-based and Lightweight Networks For Fast Image Super Resolution.- CLN: Complementary Learning Network For 3D Face Reconstruction And Alignment.- Combining Edge-guided Attention and Sparse-connected U-Net for Detection of Image Splicing.- Contour-augmented Concept Prediction Network for image captioning.- Contrastive Knowledge Amalgamation for Unsupervised Image Classification.- Cross Classroom Domain Adaptive Object Detector for Student's Heads.- Diffusion-Adapter: Text Guided Image Manipulation with Frozen Diffusion Models.- DWA: Differential Wavelet Amplifier for Image Super-Resolution.- Dynamic Facial Expression Recognition in Unconstrained Real-World Scenarios Leveraging Dempster-Shafer Evidence Theory.- End-to-end Remote Sensing Change Detection of Unregistered Bi-temporal Images for Natural Disasters.- E-Patcher: A Patch-based Efficient Network for Fast Whole Slide Images Segmentation.- Exploiting Multi-modal Fusion for Robust Face Representation Learning with Missing Modality.- Extraction Method of Rotated Objects from High-resolution Remote Sensing Images.- Few-shot NeRF-based View Synthesis for Viewpoint-biased Camera Pose Estimation.- Ga-RFR: Recurrent Feature Reasoning with gated convolution for Chinese Inscriptions Image Inpainting.- Generalisation Approach for Banknote Authentication by Mobile Devices Trained on Incomplete Samples.- Image Caption with Prior Knowledge Graph and Heterogeneous Attention.- Image Captioning for Nantong Blue Calico Through Stacked Local-Global Channel Attention Network.- Improving Image Captioning with Feature Filtering and Injection.- In silico study of single synapse dynamics using a three-state kinetic model.- Interpretable Image Recognition by Screening Class-specific and Class-shared Prototypes.- Joint Edge-guided and Spectral Transformation Network for Self-Supervised X-ray Image Restoration.- Lightweight Human Pose Estimation Based On Densely Guided Self-Knowledge Distillation.- MCAPR: Multi-Modality Cross Attention for Camera Absolute Pose Regression.- MC-MLP: A Multiple Coordinate Frames MLP-Like Architecture for Vision.- Medical Image Segmentation and Saliency Detection through a Novel Color Contextual Extractor.- MedNet: A Dual-Copy Mechanism for Medical Report Generation from Images.- Ms-AMPool: Down-Sampling Method for Dense Prediction Tasks.- Multi-frame Tilt-angle Face Recognition Using Fusion Re-ranking.- Multi-scale field distillation for multi-task semantic segmentation.- Neural Field Conditioning Strategies for 2D Semantic Segmentation.- Neurodynamical Model of the Visual Recognition of Dynamic Bodily Actions from Silhouettes.- PACE: Point Annotation-Based Cell Segmentation for Efficient Microscopic Image Analysis.- Pie-UNet: A novel Parallel Interaction Encoder for Medical Image Segmentation.- Prior-SSL: A Thickness Distribution Prior and Uncertainty Guided Semi-supervised Learning Method for Choroidal Segmentation in OCT Images.- PSR-Net A Dual-Branch Pyramid Semantic Reasoning Network for Segmentation of Remote Sensing Images.

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Book SynopsisThe 10-volume set LNCS 14254-14263 constitutes the proceedings of the 32nd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2023, which took place in Heraklion, Crete, Greece, during September 26–29, 2023.The 426 full papers, 9 short papers and 9 abstract papers included in these proceedings were carefully reviewed and selected from 947 submissions. ICANN is a dual-track conference, featuring tracks in brain inspired computing on the one hand, and machine learning on the other, with strong cross-disciplinary interactions and applications. Table of ContentsA Further Exploration of Deep Multi-Agent Reinforcement Learning with Hybrid Action Space.- Air-to-Ground Active Object Tracking via Reinforcement Learning.- Enhancing P300 Detection in Brain-Computer Interfaces with Interpretable Post-Processing of Recurrent Neural Networks.- Group-Agent Reinforcement Learning.- Improving Generalization of Multi-agent Reinforcement Learning through Domain-Invariant Feature Extraction.- Latent-Conditioned Policy Gradient for Multi-Objective Deep Reinforcement Learning.- LIIVSR: A Unidirectional Recurrent Video Super-Resolution Framework with Gaussian Detail Enhancement and Local Information Interaction Modules.- Masked Scale-Recurrent Network for Incomplete Blurred Image Restoration.- Multi-fusion Recurrent Network for Argument Pair Extraction.- Pacesetter Learning For Large Scale Cooperative Multi-Agent Reinforcement Learning.- Stable Learning Algorithm Using Reducibility for Recurrent Neural Networks.- t-ConvESN: Temporal Convolution-Readout for Random Recurrent Neural Networks.- Adaptive Reservoir Neural Gas: An Effective Clustering Algorithm for Addressing Concept Drift in Real-Time Data Streams.- An Intelligent Dynamic Selection System Based on Nearest Temporal Windows for Time Series Forecasting.- Generating Sparse Counterfactual Explanations For Multivariate Time Series.- Graph Neural Network-Based Representation Learning for Medical Time Series.- Knowledge Forcing: Fusing Knowledge-Driven Approaches with LSTM for Time Series Forecasting.- MAGNet: Muti-scale Attention and Evolutionary Graph Structure for Long Sequence Time-Series Forecasting.- MIPCE: Generating Multiple Patches Counterfactual-changing Explanations for Time Series Classification.- Multi-Timestep-Ahead Prediction with Mixture of Experts for Embodied Question Answering.- Rethink the Top-u Attention in Sparse Self-attention for Long Sequence Time-Series Forecasting.- Temporal Attention Signatures for Interpretable Time-Series Prediction.- Time-Series Prediction of Calcium Carbonate Concentration in Flue Gas Desulfurization Equipment by Optimized Echo State Network.- WAG-NAT: Window Attention and Generator Based Non-Autoregressive Transformer for Time Series Forecasting.- A Novel Encoder and Label Assignment for Instance Segmentation.- A Transformer-based Framework for Biomedical Information Retrieval Systems.- A Transformer-Based Method for UAV-View Geo-Localization.- Cross-graph Transformer Network for Temporal Sentence Grounding.- EGCN: A Node Classification Model based on Transformer and Spatial Feature Attention GCN for Dynamic Graph.- Enhance Representational Differentiation Step By Step: A Two-Stage Encoder-Decoder Network for Implicit Discourse Relation Classification.- GenTC: Generative Transformer via Contrastive Learning for Receipt Information Extraction.- Hierarchical Classification for Symmetrized VI Trajectory Based on Lightweight Swin Transformer.- Hierarchical Vision and Language Transformer for Efficient Visual Dialog.- ICDT: Maintaining Interaction Consistency for Deformable Transformer with Multi-scale Features in HOI Detection.- Imbalanced Conditional Conv-Transformer For Mathematical Expression Recognition.- Knowledge Graph Transformer for Sequential Recommendation.- LorenTzE: Temporal Knowledge Graph Embedding based on Lorentz Transformation.- MFT: Multi-scale Fusion Transformer for Infrared and Visible Image Fusion.- NeuralODE-based Latent Trajectories into AutoEncoder Architecture for Surrogate Modelling of Parametrized High-dimensional Dynamical Systems.- RRecT: Chinese Text Recognition with Radical-enhanced Recognition Transformer.- S2R: Exploring a Double-Win Transformer-Based Framework for Ideal and Blind Super-Resolution.- Self-adapted Positional Encoding in the Transformer Encoder for Named Entity Recognition.- SHGAE: Social Hypergraph AutoEncoder for Friendship Inference.- Temporal Deformable Transformer For Action Localization.- Trans-Cycle: Unpaired Image-to-Image Translation Network by Transformer.

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Book SynopsisThis book constitutes the refereed proceedings of the 5th Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2023, held in conjunction with MICCAI 2023 in Vancouver, Canada, in October 2023. For this workshop, 21 papers from 32 submissions were accepted for publication. The accepted papers cover the fields of uncertainty estimation and modeling, as well as out of distribution management, domain shift robustness, Bayesian deep learning and uncertainty calibration.Table of ContentsUncertainty estimation and modelling.- Out of Distribution management and domain shift robustness.- Bayesian deep learning and uncertainty calibration.

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