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1. |
Record Nr. |
UNINA9911152886703321 |
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Autore |
Hester Matthew |
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Titolo |
Automating Microsoft Windows Server 2008 R2 with Windows PowerShell 2.0 |
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Pubbl/distr/stampa |
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ISBN |
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9786613176950 |
9781283176958 |
1283176955 |
9781118103067 |
1118103068 |
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Edizione |
[1st edition] |
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Descrizione fisica |
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1 online resource (434 p.) |
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Collana |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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COMPUTERS / Operating Systems / Windows Server & NT |
Microsoft Windows server |
Operating systems (Computers) |
Windows PowerShell (Computer program language) |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di contenuto |
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Automating Microsoft® Windows Server® 2008 R2 with Windows PowerShell® 2.0; TABLE OF CONTENTS; Introduction; Chapter 1 What Is PowerShell, and Why Do You Need It?; Chapter 2 Installing and Configuring PowerShell 2.0; Chapter 3 PowerShell Grammar Lesson; Chapter 4 Aliases, Functions, and the Pipe, Oh My!; Chapter 5 Creating Your Own Scripts; Chapter 6 Remoting with PowerShell 2.0; Chapter 7 Server Essentials in PowerShell; Chapter 8 Managing Active Directory with PowerShell; Chapter 9 Managing Desktops with PowerShell; Chapter 10 Managing IIS Web Server with PowerShell |
Chapter 11 PowerShell and Deployment ServicesChapter 12 PowerShell and Virtualization; Appendix A Solutions to Exercises; Appendix B Developing at a Command Prompt; Appendix C Providing for PowerShell; Appendix D Custom Cmdlets and Advanced Functions; Appendix E Packaging PowerShell Extensions; Appendix F Building Your Own GUI with PowerShell; Index |
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Sommario/riassunto |
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Learn to automate the top server operating system, Windows Server 2008 R2 Windows PowerShell 2.0 allows you to automate nearly any task for managing Windows Server, going from dozens of clicks to a single command, and repeated tasks to automated tasks. Using screen shots and helpful exercises, this book walks you through the many benefits of automating Windows Server with PowerShell 2.0, such as allowing for scalable, flexible, and rapid deployments and changes; increasing cost effectiveness; providing a timely return on IT investment; lowering labor headcount; creating secure computi |
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2. |
Record Nr. |
UNINA9911127558403321 |
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Autore |
Blanchard Emmanuel G |
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Titolo |
Artificial Intelligence in Education : 27th International Conference, AIED 2026, Seoul, South Korea, June 27-July 3, 2026, Proceedings, Part I |
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Pubbl/distr/stampa |
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Cham : , : Springer, , 2026 |
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©2027 |
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ISBN |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (1023 pages) |
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Collana |
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Lecture Notes in Computer Science Series ; ; v.16581 |
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Formato |
Materiale a stampa |
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Nota di contenuto |
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Lecture Notes in Computer Science -- Artificial Intelligence in Education -- Preface -- Organization -- Contents -- Evidence-Decision-Feedback: Theory-Driven Adaptive Scaffolding for LLM Agents -- DrawSim-PD: Simulating Student Science Drawings to Support NGSS-Aligned Teacher Diagnostic Reasoning -- Enhancing Intelligent Tutoring Systems with Instruction-Tuned LLMs: Automated Assessment of Student Code Comprehension -- Automatically Inferring Teachers' Geometric Content Knowledge: A Skills Based Approach -- Personalized AI Practice Replicates Learning Rate Regularity at Scale -- Benchmarking Scientific Formula Vocalization in Large Speech Language Models Toward Accessible Learning -- From Untamed Black Box to Interpretable Pedagogical Orchestration: The Ensemble of |
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Specialized LLMs Architecture for Adaptive Tutoring -- Can MLLMs Read Students' Minds? Unpacking Multimodal Error Analysis in Handwritten Math -- Prompt Optimization with Verifiable Rewards for Synthetic Essay Generation -- Generating Personalized Programming Exercises via Cognitive State Graphs and ZPD-Driven Prompting -- Short, Long, or Affective: Evaluating LLM-Generated Feedback Styles for Student Learning -- Developing and Evaluating a Large Language Model-Based Tool for Qualitative Analysis of Teacher Interviews -- An Explainable AI Assistant for Introductory Programming Education: Improving Feedback Reliability with Instructor-AI Collaboration -- Hierarchical Apprenticeship Learning from Imperfect Demonstrations with Evolving Rewards -- Beyond Show and Tell: Explainable AI-Supported Feedback for Developing Data Visualization Sense-Making Skills -- A Multi-agent Approach to Validate and Refine LLM-Generated Personalized Math Problems -- Gaze to Insight: A Scalable AI Approach for Detecting Gaze Behaviours in Face-To-Face Collaborative Learning. |
When AI Meets Early Childhood Education: Large Language Models as Assessment Teammates in Chinese Preschools -- From Slides to Exams: A Multi-agent Human-AI System for Collaborative Assessment Design -- i-vip: A LLM-Driven Multi-agent System for Professional Development of Mathematics Teachers -- A Neuro-Symbolic Approach to Extracurricular Activity Recommendation Based on Cognitive Profiling -- From Problem Solving to Pedagogical Feedback: Student-Centric Tree-of-Thought Reasoning for Student Error Attribution -- ANVIL: Analogies and Videos for Lecturers -- Process-Integrated IRT: Enhancing Ability Estimation in Computer-Based Programming Assessments Through Response Process Data -- New Intent Discovery for Educational Dialogue Texts via Semantic-Aware Data Augmentation -- When Can We Trust LLM Graders? Calibrating Confidence for Automated Assessment -- REFINE: Real-World Exploration of Interactive Feedback and Student Behaviour -- The TME Framework: Multimodal Learner Modeling for Active Listening Skills in Collaborative Problem Solving -- An Item Response Theory Model for Addressing Halo Effects in Performance Assessment -- LLM-Based Virtual Standardized Patients with Response Excessiveness Suppression via Direct Preference Optimization for Medical Interview Examinations -- PSC: Personalized Sentence-Level Pronunciation Coaching Framework for Thai EFL Learners -- Building Evidence-Linked Curriculum Knowledge Graphs for Academic Pathway Planning -- Misconception Acquisition Dynamics in Large Language Models -- Beyond Next-Response Prediction: Evaluating Knowledge State Transition Consistency in Deep Learning Based Knowledge Tracing Models -- Grounding Programming Chatbot in Computational Thinking: Design and Evaluation of MazeMate -- SciEval: A Benchmark for Automatic Evaluation of K-12 Science Instructional Materials. |
Has Automated Essay Scoring Reached Sufficient Accuracy? Deriving Achievable QWK Ceilings from Classical Test Theory -- Automated Multimodal Transcription for Belonging-Centered Classroom Interaction Analysis: Opportunities and Challenges -- Single-Agent vs. Multi-agents for Automated Video Analysis of On-Screen Collaborative Learning Behaviors -- SLOW: Strategic Logical-Inference Open Workspace for Cognitive Adaptation in AI Tutoring -- From Learning Resources to Competencies: LLM-Based Tagging with Evidence and Graph Constraints -- Simulating Novice Students Using Machine Unlearning and Relearning in Large Language Models -- Author Index. |
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Sommario/riassunto |
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This six-volume set LNAI constitutes the refereed proceedings of the 27th International Conference on Artificial Intelligence in Education, |
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AIED 2026, held in Seoul, South Korea, during June 27-July 3, 2026.The 143 full papers and 165 short papers presented in this book were carefully reviewed and selected from 1241 submissions. |
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