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Format: 1 online resource (625 p.)

ISBN: 1-282-29016-9 , 9786612290169 , 0-08-095875-3

Series Statement: Mathematics in science and engineering ; 189

Content: Scientific computing with automatic result verification

Note: "The bulk of the papers collected in this book represent selected material taken from doctoral or diploma theses which were written at the Institute for Applied Mathematics at the University of Karlsruhe"--P. ix. , Front Cover; Scientific Computing With Automatic Result Verification; Copyright Page; Contents; Contributors; Preface; Acknowledgements; Introduction; Part I. Language and Progmmmmg Support for Verified Scientific Computation; Chapter 1. PASCAL-XSC, New Concepts for Scientific Computation and Numerical Data Processing; Chapter 2. ACRITH-XSC, A Fortran-like Language for Verified Scientific Computing; Chapter 3. C-XSC, A Programming Environment for Verified Scientific Computing and Numerical Data Processing; Chapter 4. Proposal for Accurate Floating-Point Vector Arithmetic , Part II. Enclosure Methods and Algorithms with Automatic Result VerificationChapter 5. Automatic Differentiation and Applications; Chapter 6. Numerical Quadrature by Extrapolation with Automatic Result Verification; Chapter 7. Numerical Integration in Two Dimensions with Automatic Result Verification; Chapter 8. Verified Solution of Integral Equations with Applications; Chapter 9. Enclosure Methods for Linear and Nonlinear Systems of Fredholm Integral Equations of the Second Kind , Chapter 10. A Step Size Control for Lohner's Enclosure Algorithm for Ordinary Differential Equations with Initial ConditionsChapter 11. Interval Arithmetic in Staggered Correction Format; Part III. Applications in the Engineering Sciences; Chapter 12. Multiple Precision Computations with Result Verification; Chapter 13. Verification of Asymptotic Stability for Interval Matrices and Applications in Control Theory; Chapter 14. Numerical Reliability of MHD Flow Calculations; Chapter 15. The Reliability Question for Discretizations of Evolution Problems , Part I: Theoretical Consideration on FailuresPart II: Practical Failures; Chapter 16. KKR Bandstructure Calculations, A Challenge to Numerical Accuracy; Chapter 17. A Hardware Kernel for Scientific/Engineering Computations; Chapter 18. Bibliography on Enclosure Methods and Related Topics; Index , English

Additional Edition: ISBN 0-12-044210-8

Language: English

Subjects: Computer Science

Keywords: Aufsatzsammlung ; Aufsatzsammlung

URL: https://www.sciencedirect.com/bookseries/mathematics-in-science-and-engineering/vol/189/suppl/C

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Format: 1 online resource (311 pages)

Edition: 1st ed.

ISBN: 9789819707799

Note: Intro -- Preface -- Contents -- Contributors -- Service Composition for Smart Cities -- Consistent and Quality-Aware Service Composition in Smart Cities -- 1 Introduction -- 2 Service Composition in Cyber Space -- 2.1 Background Around 2010 -- 2.2 Different Quality Aspects in Service Selection -- 2.3 Self-Adaptive Network-Aware Service Selection -- 2.4 Consistency in Service Selection -- 2.5 Service Selection in Cloud Computing -- 3 Service Composition in Physical Space -- 3.1 Background Around 2015 -- 3.2 EU-Japan Smart City Projects -- 3.3 Consistency in Physical Service Composition -- 3.4 Verification Framework -- 3.5 Runtime Adaptation -- 4 Retrospective Discussion -- 4.1 Services Computing -- 4.2 Impact on the Author -- 5 Concluding Remarks -- References -- Designing and Analyzing Human-in-the-Loop Service Compositions -- 1 Introduction -- 1.1 Background -- 1.2 Approach -- 1.3 Structure of This Chapter -- 2 Human-in-the-Loop Service Composition -- 2.1 A Language Service Composition Example -- 2.2 Composition of Web Services and Human Activities -- 3 Empirical Study on Human-in-the-Loop Translation Services -- 3.1 Experiment Design -- 3.2 Experiment Results -- 3.3 Discussion -- 4 Human-in-the-Loop Service Design for Supporting Real-World Multilingual Activities -- 4.1 Designing Composite Services for Real-World Applications -- 4.2 Service Design Process -- 4.3 Experiment, Result and Analysis -- 5 Analyzing Crowdsourcing Workflow Models -- 5.1 Crowdsourcing Workflows -- 5.2 Modeling Iterative and Parallel Processes -- 5.3 Workflow Optimization -- 5.4 Implementing Crowdsourcing Workflow Models -- 6 Related Work -- 6.1 Human Activities in Service Composition -- 6.2 User-Centered Composite Service Design -- 6.3 Crowdsourcing Workflow Models -- 7 Conclusion -- References -- Human-Machine Collaboration for a Multilingual Service Platform. , 1 Introduction -- 1.1 Background -- 1.2 Approach -- 1.3 Structure of This Chapter -- 2 Multilingual Service Platform for Smart Cities -- 3 Human-Machine Service Composition -- 3.1 Collaborative Creation Workflow -- 3.2 Crowdsourcing System for Language Resource Creation -- 4 Reliable Crowdsourced Services for Creating Language Resources -- 4.1 Introduction -- 4.2 Issues in Crowdsourcing -- 4.3 Crowdsourced Workflow -- 4.4 Evaluation Aggregation with Hyper-Questions -- 4.5 Task Assignment Based on Workers' Reliability -- 4.6 Evaluation -- 5 AI Services for Augmenting Language Resources -- 5.1 Introduction -- 5.2 Pivot-Based Approach -- 5.3 Experiment for Pivot-Based Approach -- 5.4 Neural Network Approach -- 5.5 Experiment for Neural-Based Approach -- 6 Markov-Based Composite Service for Human-Machine Collaboration -- 6.1 Formalizing Plan Optimization -- 6.2 Experiment -- 6.3 Discussion -- 7 Conclusion -- References -- Data Analysis for Smart Cities -- Automatic Big Data Analysis Using AI-Based Service Composition for Smart City -- 1 Concept of Automatic Service Composition -- 1.1 Introduction -- 1.2 Preliminaries for Service Composition -- 1.3 Workflow Orchestration in a Nested Composition for Scalability -- 1.4 Architecture for Scalable ASC -- 2 Better Service Composition Using Service Graph -- 2.1 Introduction -- 2.2 Background and Related Work -- 2.3 Motivating Example -- 2.4 Connecting Isolated Services into GSSN -- 2.5 Workflow as a Service -- 3 Better Service Discovery Using Attention of Service Invocation -- 3.1 Related Work -- 3.2 Service Embedding -- 3.3 Service Embedding with Deep Neural Language Networks -- 3.4 Semantic Service Clustering Based on Service Embedding -- 3.5 Data Preparation -- 3.6 Experiment and Discussion -- 4 Intelligent Big Data Analysis with ASC for Virtual World -- 4.1 Related Work. , 4.2 Preliminaries for Big Data Analytics -- 4.3 Architecture for Intelligent BDA -- 4.4 Evaluation -- 5 A Scenario of Smart City Simulation on Virtual Space and Conclusion -- 5.1 Motivation Scenario -- 5.2 Conclusion -- References -- Privacy-Preserving Data Collection and Analysis for Smart Cities -- 1 Introduction -- 1.1 Purpose of This Research -- 1.2 Structure of This Chapter -- 2 Background -- 2.1 Motivating Examples -- 2.2 Attack Model -- 2.3 Local Differential Privacy (LDP) -- 3 Measurement Noise Under LDP -- 3.1 Introduction -- 3.2 Models -- 3.3 True-Value-Based Differential Privacy (TDP) -- 3.4 Analysis -- 3.5 Evaluation -- 3.6 Related Research Work -- 4 Missing Values Under LDP -- 4.1 Introduction -- 4.2 Proposed Method -- 4.3 Evaluation -- 5 Human-to-Human Interactions Under LDP -- 5.1 Introduction -- 5.2 Related Work and Real Applications -- 5.3 Problem Definition -- 5.4 Proposed Method -- 5.5 Evaluation -- 6 Conclusion -- References -- Human-Centered Service Integration for Smart Cities -- Automated Negotiations Protocols for Complex Utility Function as Social System -- 1 Introduction -- 1.1 Main Flow of Automated Negotiations -- 1.2 Complex Multi-issue Negotiation with Highly Nonlinear Utility Functions -- 1.3 Main Contributions of This Chapter -- 2 Multi-issue Negotiation with Highly Nonlinear Utility Functions -- 2.1 Basic Model of Multi-issue Negotiation -- 2.2 Basic Bidding Protocol -- 3 Threshold Adjustment Mechanism for Keeping Agents' Privacy -- 3.1 Threshold Adjustment Mechanism -- 3.2 Experiments -- 4 Secure and Efficient Negotiation Protocols -- 4.1 Secure Negotiation Protocol -- 4.2 Hybrid Secure Negotiation Protocol (HSP) -- 4.3 Experiments -- 5 Secure and Fair Protocol that Addresses Weaknesses in Nash Bargaining Solution -- 5.1 Weaknesses of the Nash Bargaining Solution in Nonlinear Negotiation. , 5.2 Secure and Fair Mediator Protocol with Approximated Fairness -- 5.3 Experiments -- 6 Decomposing the Contract Space Based on Issue Interdependencies -- 6.1 Strength of Issue Interdependency -- 6.2 Decomposing the Contract Space -- 6.3 Experiments -- 7 Conclusion and Future Work -- 7.1 Conclusion -- 7.2 Future Work -- References -- Exploiting Smart Systems for Monitoring and Assisting Elderly People at Home -- 1 Introduction -- 1.1 Background -- 1.2 Research Goal and Approach -- 1.3 Scope of Chapter -- 2 Monitoring Elderly Living by Environmental Sensors -- 2.1 Autonomous Sensor Box -- 2.2 Service Platform for In-Home Environment Sensing -- 2.3 Implementation -- 2.4 Deploying Autonomous Sensor Box in Actual Elderly Home -- 3 Recognizing Daily Activities from Environmental Sensor Data -- 3.1 Can System Recognize Activities from Environmental Data? -- 3.2 Proposed Activity Recognition Method -- 3.3 Collecting Data for Activity Recognition -- 3.4 Constructing Machine Learning Recognition Model -- 3.5 Experimental Evaluation -- 3.6 Introducing BLE Beacons to Improve Accuracy -- 3.7 Additional Experiment with BLE Beacon Data -- 4 Monitoring Elderly Mind by Agents -- 4.1 Understanding Internal States -- 4.2 Agent Technologies Developed for Mind Sensing -- 4.3 Mind Sensing Service: Rule-Based Service for Systematic Mind Sensing -- 4.4 Case Study -- 5 Design and Evaluation of Mind Monitoring Service -- 5.1 Monitoring Internal State for Long Term -- 5.2 Concept of Mind Monitoring Service -- 5.3 System Architecture -- 5.4 M1: Interaction with LINE Mei-Chan Using Mind Sensing Service -- 5.5 M2: Inquiry Method Specialized for Acquisition of Mental State -- 5.6 M3: Self-Care Assistance and Feedback by Monitoring Mental State -- 5.7 Operating Mind Monitoring Service in Actual Households -- 6 Conclusion -- References.

Additional Edition: Print version: Murakami, Yohei Human-Centered Services Computing for Smart Cities Singapore : Springer,c2024 ISBN 9789819707782

Language: English

Keywords: Electronic books.

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Format: 1 online resource (249 pages)

Edition: 1st ed.

ISBN: 9783031548277

Note: Intro -- Foreword by Florian Schütz -- Foreword by Jan Kleijssen -- Preface -- Acknowledgments -- Contents -- List of Contributors -- Reviewers -- Acronyms -- Part I Introduction -- 1 From Deep Neural Language Models to LLMs -- 1.1 What LLMs Are and What LLMs Are Not -- 1.2 Principles of LLMs -- 1.2.1 Deep Neural Language Models -- 1.2.2 Generative Deep Neural Language Models -- 1.2.3 Generating Text -- 1.2.4 Memorization vs Generalization -- 1.2.5 Effect of the Model and Training Dataset Size -- References -- 2 Adapting LLMs to Downstream Applications -- 2.1 Prompt Optimization -- 2.2 Pre-Prompting and Implicit Prompting -- 2.3 Model Coordination: Actor-Agents -- 2.4 Integration with Tools -- 2.5 Parameter-Efficient Fine-Tuning -- 2.6 Fine-Tuning -- 2.7 Further Pretraining -- 2.8 From-Scratch Re-Training -- 2.9 Domain-Specific Distillation -- References -- 3 Overview of Existing LLM Families -- 3.1 Introduction -- 3.2 Pre-Transformer LLMs -- 3.3 BERT and Friends -- 3.4 GPT Family Proper -- 3.5 Generative Autoregressors (GPT Alternatives) -- 3.6 Compute-Optimal Models -- 3.6.1 LLaMA Family -- 3.7 Full-Transformer/Sequence-to-Sequence Models -- 3.8 Multimodal and Mixture-of-Experts Models -- 3.8.1 Multimodal Visual LLMs -- 3.8.2 Pathways Language Model, PaLM -- 3.8.3 GPT-4 and BingChat -- References -- 4 Conversational Agents -- 4.1 Introduction -- 4.2 GPT Related Conversational Agents -- 4.3 Alternative Conversational Agent LLMs -- 4.3.1 Conversational Agents Without Auxiliary Capabilities -- 4.3.2 Conversational Agents With Auxiliary Capabilities -- 4.3.2.1 Models With Non-Knowledge Auxiliary Capabilities -- 4.4 Conclusion -- References -- 5 Fundamental Limitations of Generative LLMs -- 5.1 Introduction -- 5.2 Generative LLMs Cannot Be Factual -- 5.3 Generative LLMs With Auxiliary Tools Still Struggle To Be Factual. , 5.4 Generative LLMs Will Leak Private Information -- 5.5 Generative LLMs Have Trouble With Reasoning -- 5.6 Generative LLMs Forget Fast and Have a Short Attention Span -- 5.7 Generative LLMs Are Only Aware of What They Saw at Training -- 5.8 Generative LLMs Can Generate Highly Inappropriate Texts -- 5.9 Generative LLMs Learn and Perpetrate Societal Bias -- References -- 6 Tasks for LLMs and Their Evaluation -- 6.1 Introduction -- 6.2 Natural Language Tasks -- 6.2.1 Reading Comprehension -- 6.2.2 Question Answering -- 6.2.3 Common Sense Reasoning -- 6.2.4 Natural Language Generation -- 6.3 Conclusion -- References -- Part II LLMs in Cybersecurity -- 7 Private Information Leakage in LLMs -- 7.1 Introduction -- 7.2 Information Leakage -- 7.3 Extraction -- 7.4 Jailbreaking -- 7.5 Conclusions -- References -- 8 Phishing and Social Engineering in the Age of LLMs -- 8.1 LLMs in Phishing and Social Engineering -- 8.2 Case Study: Orchestrating Large-Scale Scam Campaigns -- 8.3 Case Study: Shā Zhū Pán Attacks -- References -- 9 Vulnerabilities Introduced by LLMs Through Code Suggestions -- 9.1 Introduction -- 9.2 Relationship Between LLMs and Code Security -- 9.2.1 Vulnerabilities and Risks Introduced by LLM-Generated Code -- 9.3 Mitigating Security Concerns With LLM-Generated Code -- 9.4 Conclusion and The Path Forward -- References -- 10 LLM Controls Execution Flow Hijacking -- 10.1 Faulting Controls: The Genesis of Execution Flow Hijacking -- 10.2 Unpacking Execution Flow: LLMs' Sensitivity to User-Provided Text -- 10.3 Examples of LLMs Execution Flow Attacks -- 10.4 Securing Uncertainty: Security Challenges in LLMs -- 10.5 Security by Design: Shielding Probabilistic Execution Flows -- References -- 11 LLM-Aided Social Media Influence Operations -- 11.1 Introduction -- 11.2 Salience of LLMs -- 11.3 Potential Impact -- 11.4 Mitigation -- References. , 12 Deep(er) Web Indexing with LLMs -- 12.1 Introduction -- 12.2 Innovation Through Integration of LLMs -- 12.3 Navigating Complexities: Challenges and Mitigation Strategies -- 12.3.1 Desired Behavior of LLM-Based Search Query Creation Tools -- 12.3.2 Engineering Challenges and Mitigations -- 12.3.2.1 Ethical and Security Concerns -- 12.3.2.2 Fidelity of Query Responses and Model Accuracy -- 12.3.2.3 Linguistic and Regulatory Variations -- 12.3.2.4 Handling Ambiguous Queries -- 12.4 Key Takeaways -- 12.5 Conclusion and Reflections -- References -- Part III Tracking and Forecasting Exposure -- 13 LLM Adoption Trends and Associated Risks -- 13.1 Introduction -- 13.2 In-Context Learning vs Fine-Tuning -- 13.3 Adoption Trends -- 13.3.1 LLM Agents -- 13.4 Potential Risks -- References -- 14 The Flow of Investments in the LLM Space -- 14.1 General Context: Investments in the Sectors of AI, ML, and Text Analytics -- 14.2 Discretionary Evidence -- 14.3 Future Work with Methods Already Applied to AI and ML -- References -- 15 Insurance Outlook for LLM-Induced Risk -- 15.1 General Context of Cyber Insurance -- 15.1.1 Cyber-Risk Insurance -- 15.1.2 Cybersecurity and Breaches Costs -- 15.2 Outlook for Estimating the Insurance Premia of LLMs Cyber Insurance -- References -- 16 Copyright-Related Risks in the Creation and Useof ML/AI Systems -- 16.1 Introduction -- 16.2 Concerns of Owners of Copyrighted Works -- 16.3 Concerns of Users Who Incorporate Content Generated by ML/AI Systems Into Their Creations -- 16.4 Mitigating the Risks -- References -- 17 Monitoring Emerging Trends in LLM Research -- 17.1 Introduction -- 17.2 Background -- 17.3 Data and Methods: Noun Extraction -- 17.4 Results -- 17.4.1 Domain Experts Validation and Interpretations -- 17.5 Discussion, Limitations and Further Research -- 17.6 Conclusion -- References -- Part IV Mitigation. , 18 Enhancing Security Awareness and Education for LLMs -- 18.1 Introduction -- 18.2 Security Landscape of LLMs -- 18.3 Foundations of LLM Security Education -- 18.4 The Role of Education in Sub-Areas of LLM Deployment and Development -- 18.5 Empowering Users Against Security Breaches and Risks -- 18.6 Advanced Security Training for LLM Users -- 18.7 Conclusion and the Path Forward -- References -- 19 Towards Privacy Preserving LLMs Training -- 19.1 Introduction -- 19.2 Dataset Pre-processing with Anonymization and De-duplication -- 19.3 Differential Privacy for Fine-Tuning Models -- 19.4 Differential Privacy for Deployed Models -- 19.5 Conclusions -- References -- 20 Adversarial Evasion on LLMs -- 20.1 Introduction -- 20.2 Evasion Attacks in Image Classification -- 20.3 Impact of Evasion Attacks on the Theory of Deep Learning -- 20.4 Evasion Attacks for Language Processing and Applicability to Large Language Models -- References -- 21 Robust and Private Federated Learning on LLMs -- 21.1 Introduction -- 21.1.1 Peculiar Challenges of LLMs -- 21.2 Robustness to Malicious Clients -- 21.3 Privacy Protection of Clients' Data -- 21.4 Synthesis of Robustness and Privacy -- 21.5 Concluding Remarks -- References -- 22 LLM Detectors -- 22.1 Introduction -- 22.2 LLMs' Salience -- 22.2.1 General Detectors -- 22.2.2 Specific Detectors -- 22.3 Potential Mitigation -- 22.3.1 Watermarking -- 22.3.2 DetectGPT -- 22.3.3 Retrieval Based -- 22.4 Mitigation -- References -- 23 On-Site Deployment of LLMs -- 23.1 Introduction -- 23.2 Open-Source Development -- 23.3 Technical Solution -- 23.3.1 Serving -- 23.3.2 Quantization -- 23.3.3 Energy Costs -- 23.4 Risk Assessment -- References -- 24 LLMs Red Teaming -- 24.1 History and Evolution of Red-Teaming Large Language Models -- 24.2 Making LLMs Misbehave -- 24.3 Attacks -- 24.3.1 Classes of Attacks on Large Language Models. , 24.3.1.1 Prompt-Level Attacks -- 24.3.1.2 Contextual Limitations: A Fundamental Weakness -- 24.3.1.3 Mechanisms of Distractor and Formatting Attacks -- 24.3.1.4 The Role of Social Engineering -- 24.3.1.5 Integration of Fuzzing and Automated Machine Learning Techniques for Scalability -- 24.4 Datasets -- 24.5 Defensive Mechanisms Against Manual and Automated Attacks on LLMs -- 24.6 The Future -- Appendix -- References -- 25 Standards for LLM Security -- 25.1 Introduction -- 25.2 The Cybersecurity Landscape -- 25.2.1 MITRE CVEs -- 25.2.2 CWE -- 25.2.3 MITRE ATT& -- CK and Cyber Kill Chain -- 25.3 Existing Standards -- 25.3.1 AI RMF Playbook -- 25.3.2 OWASP Top 10 for LLMs -- 25.3.3 AI Vulnerability Database -- 25.3.4 MITRE ATLAS -- 25.4 Looking Ahead -- References -- Part V Conclusion -- 26 Exploring the Dual Role of LLMs in Cybersecurity: Threats and Defenses -- 26.1 Introduction -- 26.2 LLM Vulnerabilities -- 26.2.1 Security Concerns -- 26.2.1.1 Data Leakage -- 26.2.1.2 Toxic Content -- 26.2.1.3 Disinformation -- 26.2.2 Attack Vectors -- 26.2.2.1 Backdoor Attacks -- 26.2.2.2 Prompt Injection Attacks -- 26.2.3 Testing LLMs -- 26.3 Code Creation Using LLMs -- 26.3.1 How Secure is LLM-Generated Code? -- 26.3.2 Generating Malware -- 26.4 Shielding with LLMs -- 26.5 Conclusion -- References -- 27 Towards Safe LLMs Integration -- 27.1 Introduction -- 27.2 The Attack Surface -- 27.3 Impact -- 27.4 Mitigation -- References.

Additional Edition: Print version: Kucharavy, Andrei Large Language Models in Cybersecurity Cham : Springer International Publishing AG,c2024 ISBN 9783031548260

Language: English

Keywords: Electronic books. ; Electronic books.

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Format: 1 online resource (289 pages)

Edition: 1st ed. 2024.

ISBN: 9783031603136

Series Statement: Progress in IS,

Content: This book presents up-to-date descriptions of Smart Services Innovations in industry, supported by new scientific approaches. It summarizes the outcomes of the fifth Smart Services Summit, held in Zurich in October 2023, which primarily focused on the ability of Smart Service Systems to support resilience and build sustainability. As the evolution of Smart Services accelerates, new technologies can be leveraged to create new value propositions and business models that deliver tangible sustainability outcomes. This book addresses social, economic, and environmental aspects of sustainability in connection with new technologies and includes papers on how these technologies can help achieve resilience and sustainability. In this context, topics such as sustainability and resilience in supply chains, X-as-a-Service, large language models for service automation, and location-based systems are discussed. Given its scope, the book represents an indispensable guide for practitioners and advanced students alike.

Note: Intro -- Foreword -- Preface -- About the Summit -- Contents -- Editors and Contributors -- Smart Services and Resilience -- Using Synthetic Data for Improving Robustness and Resilience in ML-Based Smart Services -- 1 Introduction -- 2 Synthetic Data -- 3 An Architecture for Robustness in Smart Services -- 4 Experiments -- 5 Conclusion -- References -- Sustainable Smart Services for Financial Institutions: Evaluation of ESG Service Creation Framework Applicability for Practitioners -- 1 Introduction -- 2 ESG Service Creation Framework -- 3 Methodology -- 4 Results of the Interviews -- 5 Insights and Reflections -- 6 Demonstration: ESG Readiness Assessment for SMEs -- 7 Conclusion and Outlook -- References -- Quantitative Models for Sustainable Smart Services in the Building Industry -- 1 Introduction -- 2 Methodology -- 3 Literature -- 3.1 Potential of Smart Services -- 3.2 Smart Building -- 3.3 B2B Platforms -- 3.4 Quantification of Economic and Environmental Value -- 4 Results -- 4.1 User Analysis -- 4.2 Quantitative Assessment of the Economic and Environmental Service Value Creation -- 4.3 Calculation Example -- 4.4 Environmental Dimension -- 5 Discussion -- 6 Conclusion, Limitations and Future Research -- References -- Interrelation Between Resilience and Sustainability in Smart Service Systems -- 1 Introduction -- 2 Literature Review -- 2.1 Measuring Sustainability in Manufacturing Systems -- 2.2 Measuring Resilience in Manufacturing Systems -- 2.3 Relationship Between Resilience and Sustainability -- 2.4 Case Studies of Smart Services -- 3 Research Design -- 3.1 Research Methods -- 4 Discussions -- 4.1 Assessment of Case Study Companies Based on Sustainability Aspects and Resilience Factors -- 4.2 Analysis and Recommendations of the Case Study Companies -- 4.3 Relationship Between Sustainability and Resilience. , 5 Conclusion, Limitations and Scope for Future Research -- 5.1 Conclusion -- 5.2 Limitations -- 5.3 Scope for Future Research -- References -- Building Supply Chain Resilience Using Artificial Intelligence in Risk Management Systems -- 1 Introduction -- 2 Literature Review -- 2.1 Risk Definition -- 2.2 Supply Chain Risk Management (SCRM) -- 2.3 Bow Tie Risk Framework -- 2.4 Introduction to Artificial Intelligence in SCRM -- 3 Research Methodology -- 4 Results -- 4.1 Gaps in Bow-Tie Risk Framework -- 4.2 Need for Artificial Intelligence Based on Risk Type -- 4.3 Relevance of AI in the Risk Management Systems -- 5 Discussions -- 5.1 Building Risk Management System Using Enhanced Bow-Tie Risk Framework -- 5.2 Guidance to Businesses -- 6 Conclusions, Limitations, and Future Research -- 6.1 Conclusions -- 6.2 Limitations -- 6.3 Future Research -- References -- Discovering Dynamic Resiliency in Organizations -- 1 Introduction and Motivation -- 2 State of Art and Next Steps -- 2.1 Resiliency in Organizations as a Multi-disciplinary Concept -- 2.2 Nudges from Contingency Theories for a 'System View' -- 3 Re-interpreting Resilience: A Personal and Contextual View of 'Resiliency' -- 3.1 The Contribute of Systems Thinking -- 4 Resiliency in Organizations -- 4.1 Is It De Facto Dynamic?! -- 4.2 The Role of Structural Pre-conditions and Systems Determinants -- 5 Findings, Implications and First Conclusions -- References -- Resilient and Value Creating Wine Ecosystem: An NFT-Driven Agricultural Digital Twin Case Study with #NFGrapevine -- 1 Introduction -- 1.1 Research Questions -- 2 Background -- 2.1 Web3 -- 2.2 Internet of Things -- 2.3 Digital Twin -- 3 Methodology -- 3.1 Analysis of Current State -- 4 Results -- 4.1 The #NFG Ecosystem -- 4.2 Data to Value Stream -- 4.3 Recommended Actions -- 5 Discussion -- 6 Conclusion, Limitations, and Future Research. , 6.1 Academic Implications -- 6.2 Managerial Considerations -- References -- Contribution Model Ecosystem for Resiliency and Sustainability -- 1 Introduction -- 2 Literature Review -- 2.1 Contribution Model Framework and Ecosystem -- 2.2 Contribution Model Ecosystem -- 3 Methodology -- 4 Results -- 4.1 Case Study 1: Sustainable Building Practices -- 4.2 Case Study 2: Sustainable Food Supply Chain -- 4.3 Case Study 3: Long-Life Electrical Assets -- 4.4 Case Study 4: Sustainable Urban Mobility -- 5 Discussion -- 5.1 Contribution Model to Support Sustainability -- 5.2 Managerial Implications -- 5.3 Theoretical Implications -- 6 Conclusions, Limitations, and Future Research -- References -- Innovative Business Models and Systems -- Towards a Taxonomy of Large Language Model Based Business Model Transformations -- 1 Introduction -- 2 Theoretical Background -- 2.1 Business Model Transformation -- 2.2 The Economic Value of Large Language Models -- 3 Research Methodology -- 4 Results -- 4.1 New Customer Benefits -- 4.2 New Sales and Communication Channels -- 4.3 Increased Business Process Automation -- 4.4 Improved Use of Information Resource -- 4.5 Business Model Viability -- 5 Discussion -- 5.1 Contribution to Theory -- 5.2 Contribution to Practice -- 6 Conclusion -- References -- Four Scenarios for Future of Outcome-Based Contracts -- 1 Introduction -- 2 Uncertainty in OBC Futures -- 3 Methodology -- 4 Four Scenarios for Future of OBCs -- 5 Discussion -- 6 Conclusions, Limitations, and Future Research -- Appendix 1: Participants of the Disaggregate Delphi -- Appendix 2: Futures Table for Industrial Equipment OBCs in 2033 -- References -- The Role of Strategic and Learning Orientation in Creating Competitive Advantage Through Digital Service Innovation -- 1 Introduction -- 2 Theoretical Background. , 2.1 Strategic and Learning Orientation to Drive Innovation Capabilities -- 2.2 Digital Service Innovation to Drive Manufacturer Performance -- 3 Conceptual Framework Development and Results -- 3.1 Cultural Antecedents of Digital Service Innovation -- 3.2 Consequences of Digital Service Innovation -- 4 Contributions and Research Opportunities -- 4.1 Theoretical Contributions -- 4.2 Managerial Contributions -- 4.3 Research Opportunities -- References -- Reflections for Innovation Management from the Design of a Service Platform Offer in Rail Freight -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results -- 4.1 Initial Innovation Process -- 4.2 Actual Innovation Process -- 5 Discussion -- 5.1 Key Lessons from the Case -- 5.2 Development Process -- 5.3 Managerial Relevance -- 5.4 Academic Implications -- 6 Conclusions and Future Research -- References -- Monetization Roadmap for Digital Services in Product-Service Systems: Insights and Challenges from a Case Study -- 1 Introduction -- 2 Literature Review -- 2.1 Advanced Services in PSS -- 2.2 Revenue Models in PSS -- 3 Methodology -- 4 Results and Discussion -- 4.1 Service Scoping -- 4.2 Testing -- 4.3 Service and Product Distinction -- 4.4 Individuality in the Service Offers -- 4.5 Monetization Roadmap -- 4.6 Academic Implications -- 5 Conclusion -- References -- Digital Twins and System Integration -- How Teams Use Tangible Prototypes to Move from Future Speculation to Decisions When Developing Resilient Product-Service Systems -- 1 Introduction -- 2 Theoretical Background -- 3 Research Methodology -- 4 Results -- 4.1 Rapid Embodiment of Complex Scenarios -- 4.2 Bounding Complexity into Simple Objects -- 4.3 Rapid Iteration and Concept Exchange -- 4.4 Defining Boundaries of Opportunity and Invention Space -- 5 Discussion and Implications -- 6 Conclusions -- References. , Moving Towards Smart Visualization for Smart City Services: A Systematic Literature Review in Earthquake Engineering -- 1 Introduction -- 1.1 Motivation -- 1.2 Approach -- 2 Research Methodology -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- The Smart Factory as an Operational Asset-Use of Visual Twins to Improve Factory Operational Performance -- 1 Introduction -- 2 Literature Review -- 2.1 Operational Improvement -- 2.2 The Digital Twin -- 2.3 Augmented Reality and Gamification for Better Decision-Making -- 3 Methodology -- 4 Results -- 4.1 Inventory Reduction in Engineered-To-Order Production -- 4.2 Factory Footprint Optimization for Manufacture-To-Order Production -- 5 Discussion -- 5.1 Academic Implications -- 5.2 Managerial Implications -- 6 Conclusion -- References -- Enhancing Energy Flexibility via Product-Service Systems: An Analysis of Dishwasher Usage with Renewable Integration at HSB Living Lab+ -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Overall Methodology -- 3.2 HSB Living Lab+ Case Study -- 3.3 Three Scenarios of PSS -- 3.4 PSS Sustainability Multi Criteria Assessment -- 4 Results -- 4.1 Scenario 1: Product as Usual (PAU) -- 4.2 Scenario 2: PSS 1-Product with Screen-Based Interface -- 4.3 Scenario 3: PSS 2-Product with QR Code-Based Web Interface -- 4.4 PSS Sustainability Assessment -- 5 Discussion -- 6 Conclusion -- References -- Leveraging User-Centricity for OEMs Through Product, Software, and Service Development -- 1 Introduction -- 2 Services in the Realm of OEMs of Complex Hardware -- 3 Relevant Questions for Product and Software Development from a Digital Servitization Perspective -- 4 Interdependencies Between Product, Service, and Software -- 5 Service Design in Digital Servitization -- 6 Conclusion -- References -- Extended Abstracts and Posters. , Automatic Transcription of the Basic MTM-2 Motions in Virtual Reality.

Additional Edition: Print version: West, Shaun Smart Services Summit Cham : Springer,c2024 ISBN 9783031603129

Language: English

DOI: 10.1007/978-3-031-60313-6

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Format: 1 online resource (167 pages)

Edition: 1st ed.

ISBN: 9783030342586

Series Statement: Springer Texts in Education Series

Note: Intro -- Acknowledgements -- Introduction -- Reference -- Contents -- 1 Background and Earlier Research -- Abstract -- References -- 2 Contemporary Perspectives on Teaching -- Abstract -- 2.1 The Need to Adapt Teaching to Student Characteristics -- 2.2 Didactic Design -- References -- Bibliographic Recommendations -- 3 Basic Concepts in Information Literacy -- Abstract -- 3.1 Information Literacy Concept -- 3.2 Equivalence of the Concept in Various Languages -- 3.3 Objectives of Information Literacy -- 3.4 International Concerns on Information Literacy -- 3.5 Competencies in Information Literacy -- 3.6 Standards of Information Literacy -- 3.6.1 Structure of Standards -- 3.6.2 International Standards of Information Literacy -- 3.7 Models of Information Literacy -- 3.7.1 SCONUL Model -- 3.7.2 CILIP Information Literacy Model -- 3.7.3 Seven Faces of Information Literacy in Higher Education -- References -- Webography -- Bibliographic Recommendations: Definitions and Models-Information Literacy Website -- 4 Accessing Information -- Abstract -- 4.1 Defining the Need of Information -- 4.1.1 Expressing and Defining the Need of Information -- 4.2 Research Question -- 4.3 Research Strategies -- 4.4 Keywords -- 4.5 Using a Thesaurus -- 4.6 Boolean Logic Operators -- 4.7 Search of Phrases -- 4.8 Truncation -- Webography -- Bibliographic Recommendations -- How Do I Search for Information? -- Finding Information for Your Research Paper -- 5 Locating and Retrieving Information -- Abstract -- 5.1 Traditional Information Sources-Libraries -- 5.2 Cataloguing -- 5.2.1 Bibliographic Description -- 5.2.2 Descriptive Features -- 5.2.3 Classification -- 5.2.4 Indexing -- 5.2.5 Thesaurus -- References -- Webography -- Bibliographic Recommendations -- 6 Information Search Strategies -- Abstract -- 6.1 Traditional Library Catalogues. , 6.1.1 Search Information on Internet -- 6.1.2 MetaSearch Tools -- Webography -- Bibliographic Recommendations -- 7 Information Evaluation -- Abstract -- 7.1 Evaluation of Scientific Series Publications (Journals) -- 7.2 Peer Review Process -- 7.3 Bibliometric Databases -- 7.4 Clarivate Analitycs-WoS -- 7.4.1 Impact Factor -- 7.4.2 LibGuides: Journal Impact Factors: Home -- 7.4.3 H-index, HIRSH Index -- 7.5 Conclusion -- 7.6 Web Resources Evaluation -- Webography -- 8 Information Management -- Abstract -- 8.1 Using Information in the Research Process -- 8.1.1 Role of Citation Process -- 8.1.2 Principles of Describing Information Sources -- 8.1.3 Citation Methods -- 8.1.3.1 Numerical Citation Method (Vancouver Style) -- 8.1.3.2 Citation of the First Element and Publishing Date Method (Havard Style) -- 8.2 Citation Styles -- 8.2.1 "Author-Date" System (Harvard System) -- 8.2.2 "Author-Title"/"Author-Page" Style -- 8.2.3 Sequential Number System or "Author-Number" (Vancouver System) -- 8.2.4 References in a Notes System -- 8.2.5 Citation "Anatomy" -- 8.2.5.1 Printed Information Sources -- 8.2.5.2 Electronic Information Sources -- 8.2.5.3 Other Information Sources -- 8.2.5.4 Unpublished Information Sources -- 8.3 Using Microsoft Office Word-References -- 8.3.1 Steps for Automatic Bibliography Generation -- 8.4 Other Publications Identification Elements: International Codes for Publications -- 8.4.1 International Standard Book Number -- 8.4.2 International Standard Serial Number -- 8.4.3 International Standard Music Number -- 8.4.4 Digital Object Identifier -- References -- Bibliographic Recommendations -- 9 Information Communication -- Abstract -- 9.1 Ethical Use of Information -- 9.1.1 Plagiarism -- 9.1.2 Citation -- 9.1.3 Plagiarism Detection -- 9.1.3.1 Plagiarism Detection for Text Documents -- 9.1.3.2 Operation of Plagiarism Detection Systems. , 9.2 Intellectual Property. Copyright. Legislation -- 9.3 Information Communication -- 9.3.1 Creating and Presenting Academic Works -- 9.3.2 Presentation of Scientific Results -- 9.3.2.1 Form of Scientific Communication -- 9.3.2.2 Information Presentation -- References -- Webography -- Bibliographical Recommendations -- 10 Teaching Learning Methods -- Abstract -- 10.1 Teaching Strategies -- 10.2 Methods and Training Procedures -- 10.2.1 The Relationship Between the Method and Procedure -- 10.3 Classifications of Teaching-Learning Methods -- 10.4 Descriptions of the Methods Used in the Examples in Previous Chapters -- Bibliographic Recommendations -- Webography for the Whole Book.

Additional Edition: Print version: Landøy, Ane Collaboration in Designing a Pedagogical Approach in Information Literacy Cham : Springer International Publishing AG,c2019 ISBN 9783030342579

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Format: 1 online resource (XV, 309 p. 50 illus.)

Edition: 1st ed. 2018.

ISBN: 9783319916026 , 3319916025

Series Statement: Lecture Notes in Business Information Processing, 314

Content: This open access book constitutes the proceedings of the 19th International Conference on Agile Software Development, XP 2018, held in Porto, Portugal, in May 2018. XP is the premier agile software development conference combining research and practice, and XP 2018 provided a playful and informal environment to learn and trigger discussions around its main theme – make, inspect, adapt. The 21 papers presented in this volume were carefully reviewed and selected from 62 submissions. They were organized in topical sections named: agile requirements; agile testing; agile transformation; scaling agile; human-centric agile; and continuous experimentation. .

Note: Agile requirements -- COSMIC User Story Standard -- Improving Mockup-based Requirement Specification with End-User Annotations -- Agile testing -- Combining STPA and BDD for Safety Analysis and Verification in Agile Development: A Controlled Experiment -- Software tester, we want to hire you! An analysis of the demand for soft skills -- Developers' initial perceptions on TDD practice: A thematic analysis with distinct domains and languages -- Myths and Facts about Static Application Security Testing Tools: An Action Research at Telenor Digital -- Automated Acceptance Tests as Software Requirements: An Experiment to Compare the Applicability of Fit tables and Gherkin Language -- Agile transformation -- Interface Problems of Agile in a Non-Agile Environment -- Enterprise agility: Why is transformation so hard? -- Technical and Organizational Agile Practices: A Latin-American Survey -- Agile Software Development { Adoption & Maturity: An Activity Theory Perspective -- Scaling agile -- Do Agile Methods Work for Large Software Projects? -- Learning in the Large - An Exploratory Study of Retrospectives in Large-Scale Agile Development -- Reporting in Agile Portfolio Management: Routines, Metrics and Artefacts to Maintain an Effective Oversight -- Inter-team Coordination in Large-Scale Agile Development: A Case Study of Three Enabling Mechanisms -- Supporting Large-Scale Agile Development with Domain-driven Design -- Towards Agile Scalability Engineering -- Human-centric agile -- Stress in Agile Software Development: Practices and Outcomes -- Teamwork quality and team performance: Exploring differences between small and large agile projects -- Continuous experimentation -- Challenges and Strategies for Undertaking Continuous Experimentation to Embedded Systems: Industry and Research Perspectives -- ICOs overview: should investors choose an ICO developed with the Lean Startup methodology?. , English

Additional Edition: ISBN 9783319916019

Additional Edition: ISBN 3319916017

Language: English

Keywords: Konferenzschrift

DOI: 10.1007/978-3-319-91602-6

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Format: VIII, 271 p. 64 illus., 48 illus. in color. , online resource.

Edition: 1st ed. 2025.

ISBN: 9783031783227

Series Statement: Future of Business and Finance,

Content: This edited book discusses the new technologies and innovations on the horizon. Transformation in healthcare is often focused on technology and digitalization, but it's always a combination of technology and humans, akin to a team play. How can digitalization in healthcare propel us forward, and what types of interactions with teams and patients are possible in the future? The transformative nature of new technologies, products, services, procedures, and organizations will shape the future of healthcare and business models. The book also explains why management skills must be developed to meet the needs of customers and patients in the upcoming decade.

Note: Chapter 1. Quantum Computing: Foundations, Opportunities, Challenges and Applications in Healthcare -- Chapter 2. Transforming Healthcare With AI: Practical Insights Into Leveraging Large Language Models -- Chapter 3. Staff Retention and Development in German Hospitals - Particularly in Early Rehabilitation (Neurological, Neurosurgical and Interdisciplinary) -- Chapter 4. Transformation in the Healthcare Sector - More Than Digitalisation and Technology -- Chapter 5. Unlocking the Potential of Automation and AI for Medical Practices -- Chapter 6. Human-computer Interaction: Paths to Understanding Trust in Artificial Intelligence -- Chapter 7. Renal Denervation - a New Chapter in Curing Drug Resistance in Hypertension -- Chapter 8. Strategic Challenges in Hospital Management: A German and European Perspective for the Future -- Chapter 9. Digital and AI Applications From Pre-visit to Post-visit Services in Outpatient Care -- Chapter 10. Revolutionizing Personalised Medicine Using Cutting Edge It -- Chapter 11. Open Innovation Platforms as a Sustainable Future Concept for Innovations in the Healthcare Sector (Follow-up Study) -- Chapter 12. Beyond the Couch: Harnessing Creativity With Smartphone Apps to Revolutionize Mental Health Care -- Chapter 13. Interoperability in Hospitals - Improving Work Processes in Care and Treatment With Fhir and a CDR Clinical Data Repository -- Chapter 14. Transforming the Pharmaceutical Field Force: the Future of Sales Representatives -- Chapter 15. How Tech Foster Longevity Medicine -- Chapter 16. Legal Implications of Transformation in Health Care -- Chapter 17. Empowering Patients and Healthcare Professionals: Medtech Meets Digital Learning -- Chapter 18. AI in Remote Patient Monitoring -- Chapter 19. Skill and Grade Mix in Nursing.

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DOI: 10.1007/978-3-031-78322-7

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Format: XXI, 485 p. 141 illus., 107 illus. in color. , online resource.

Edition: 1st ed. 2024.

ISBN: 9789819998364

Series Statement: Frontiers of Artificial Intelligence, Ethics and Multidisciplinary Applications,

Content: This groundbreaking proceedings volume explores the integration of Artificial Intelligence (AI) across key domains-healthcare, finance, education, robotics, industrial and other engineering applications -unveiling its transformative potential and practical implications. With a multidisciplinary lens, it transcends technical aspects, fostering a comprehensive understanding while bridging theory and practice. Approaching the subject matter with depth, the book combines theoretical foundations with real-world case studies, empowering researchers, professionals, and enthusiasts with the knowledge and tools to effectively harness AI. Encompassing diverse AI topics-machine learning, natural language processing, computer vision, data analytics and supervisory control - the volume showcases state-of-the-art techniques propelling AI advancements. Structured into four parts: Part 1: Artificial Intelligence (AI), explores evolving deep neural networks, reinforcement learning, and explainable AI, providing a deep dive into the technical foundations of AI advancements. Part 2: Robotics and Control Systems, delves into the integration of AI in robotics and automatic control, addressing supervisory control, automated robotic movement coordination, anomaly detection, dynamic programming, and fault tolerance, offering insights into the evolving landscape of intelligent automation. Part 3: AI and Society, examines the societal impact of AI through chapters on ethical considerations, economic growth, environmental engagements, and hazard management, providing a holistic perspective on AI's role in shaping society. Part 4: PhD Symposium, presents the future of AI through cutting-edge research, covering legal and ethical dimensions, privacy considerations, and computationally efficient solutions, offering a glimpse into the next generation of AI advancements. Catering to a diverse audience-from industry leaders to students-the volume consolidates the expertise of renowned professionals, serving as a comprehensive resource for navigating the ever-evolving AI landscape. An essential reference for those staying at the forefront of AI developments. .

Note: Advances in AI - NLP, Vision, Voice, and Self-taught AI Systems -- Soft Computing and Evolutionary Computing -- Neuro Evolutionary Techniques -- Innovations in AI methods, techniques, and algorithms -- Explainable AI -- AI and Robotics -- AI and Automatic Control -- AI and Cloud -- AI and IoT -- Intelligent Engineering Systems, Expert Systems -- Knowledge-Based Systems.

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Additional Edition: Printed edition: ISBN 9789819998357

Additional Edition: Printed edition: ISBN 9789819998371

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DOI: 10.1007/978-981-99-9836-4

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Format: XXXIV, 385 p. 125 illus., 103 illus. in color. , online resource.

Edition: 1st ed. 2025.

ISBN: 9789819660087

Series Statement: Lecture Notes in Artificial Intelligence, 15683

Content: This two-volume proceedings, LNAI 15683 and LNAI 15684, constitutes the proceedings of the 17th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2025, held in Kitakyushu, Japan, during April 23-25, 2025. The 56 full papers and presented in these two volumes were carefully reviewed and selected from 301 submissions. The papers are organized in the following topical sections: Part I: Data Mining, Processing and Integration; Deep Learning Methods and Applications; Generative Models Applications; Intelligent Information Systems and Problem-Solving Algorithms. Part II: Games and Decision Theories; Image Processing and Computer Vision; Intelligent Techniques in Optimization; Machine Learning Techniques and Applications.

Note: -- Data Mining, Processing and Integration. -- Physics-informed Discovery of State Variables in Second-Order and Hamiltonian Systems. -- A Hybrid Discovery Framework for USV Voyage Route Generation Using AIS Data. -- Proactive approach to personnel assignment in University Course Timetabling Problem. -- Improving Traffic Sign Detection Using Synthetic Data and Automatic Labeling. -- Unraveling Research Patterns in Quantum Computing Through Topic Modeling and Network Analysis. -- Mining Erasable Patterns Using the Bitmap Method in Quantitative Component Databases. -- Privacy Preserving Based on SHA Encryption and Cluster Analysis in Federated Frequent Itemset Mining. -- An Optimization Algorithm for Finding Extractive Summary from Multiple Source Documents Based on Association and Clustering. -- Improving Stress Detection with Synthetic Datasets: GPT-4o-mini and Transformer Model Evaluation. -- On Translating Association-Oriented Structures of Unified Process Metamodel into OWL. -- A Method for Evaluating Expressive Power and Semantic Capacity of Metamodel in Conceptual Data Modeling. -- Optimizing Task Estimation Accuracy in Agile Projects: A Data-Driven Study. -- Low Computational Aggregation Method for Time Series Forecasting. -- Information graphs in process analysis. -- Deep Learning Methods and Applications. -- ESM-VAE: Bias Reduction in EEG Models via Synthetic Data Generation with Variational Autoencoders. -- Chromatic Aberration Detection Using Fully Convolutional Networks. -- Contextual Statistical Evaluation of Selected CRISPR-Cas9 Recurrent Deep Learning Models Predicting Off-target Activities for K562 and Hek293 Cell Lines. -- CerMixer: An Efficient Model for Cervical Cancer Classification Based on Patching and Multi-Scale Depthwise Convolutional Fusion. -- Generative Models Applications. -- Prompts De-Biasing Augmentation to Mitigate Gender Stereotypes in Large Language Models. -- Automatic Creation of Multilingual Knowledge Graph with Large Language Models. -- Simulating Oxford-Style Debates with LLM-based Multi-Agent Systems. -- An empirical review of the effectiveness of different language processing approaches in Software Code Vulnerability Detection. -- Intelligent Information Systems and Problem-Solving Algorithms. -- Analysis of Artificial Intelligence Solutions in Offensive Cybersecurity Domains. -- Research on the Application of Large Language Models (LLM) for Improving Recruitment Efficiency and Accuracy. -- A Trading Strategy Portfolio Optimization Approach Based on Fuzzy Mean-semivariance Model Using Memetic Algorithm. -- Brain-Computer Interface Framework for Real-Time Application Adaptation. -- Jaccard Distance under Incompleteness.

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Additional Edition: Printed edition: ISBN 9789819660070

Additional Edition: Printed edition: ISBN 9789819660094

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DOI: 10.1007/978-981-96-6008-7

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Format: 1 online resource (261 pages)

Edition: 1 ed.

ISBN: 9781003278658 , 1003278655 , 9781000904161 , 1000904164

Content: "Advancing Natural Language Processing in Educational Assessment examines the use of natural language technology in educational testing, measurement, and assessment. Recent developments in natural language processing (NLP) have enabled large-scale educational applications, though scholars and professionals may lack a shared understanding of the strengths and limitations of NLP in assessment as well as the challenges that testing organizations face in implementation. This first-of-its-kind book provides evidence-based practices for the use of NLP-based approaches to automated text and speech scoring, language proficiency assessment, technology-assisted item generation, gamification, learner feedback, and beyond. Spanning historical context, validity and fairness issues, emerging technologies, and implications for feedback and personalization, these chapters represent the most robust treatment yet about NLP for education measurement researchers, psychometricians, testing professionals, and policymakers"--

Note: The role of robust software in automated scoring / Nitin Madnani, Aoife Cahill, and Anastassia Loukina -- Psychometric considerations when using deep learning for automated scoring / Susan Lottridge, Chris Ormerod, and Amir Jafari -- Speech analysis in assessment / Jared C. Bernstein and Jian Cheng -- Assessment of clinical skills : a case study in constructing an NLP-based scoring system for patient notes / Polina Harik, Janet Mee, Christopher Runyon, and Brian E. Clauser -- Automatic generation of multiple-choice test items from paragraphs using deep nural networks / Ruslan Mitkov, Le An Ha, Halyna Maslak, Tharindu Ranasinghe, and Vilelmini Sosoni -- Training Optimus Prime, M.D. : a case study of automated item generation using artificial intelligence : from fine-tuned GPT2 to GPT3 and beyond / Matthias von Davier -- Computational psychometrics for digital-first assessments : a blend of ML and psychometrics for item generation and scoring / Geoff LaFlair, Kevin Yancey, Burr Settles, Alina A von Davier -- Validity, fairness, and technology-based assessment / Suzanne Lane -- Evaluating fairness of automated scoring in educational measurement / Matthew S. Johnson and Daniel F. McCaffrey -- Extracting linguistic signal from item text and its application to modeling item characteristics / Victoria Yaneva, Peter Baldwin, Le An Ha, and Christopher Runyon -- Stealth literacy assessment : leveraging games and NLP in iSTART / Ying Fang, Laura K. Allen, Rod D. Roscoe, and Danielle S. McNamara -- Measuring scientific understanding across international samples : the promise of machine translation and NLP-based machine learning technologies / Minsu Ha and Ross H. Nehm -- Making sense of college students' writing achievement and retention with automated writing evaluation / Jill Burstein, Daniel McCaffrey, Steven Holtzman & Beata Beigman Klebanov.

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