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1. |
Record Nr. |
UNINA9910450447703321 |
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Autore |
Thompson David |
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Titolo |
Bullying : effective strategies for long-term improvement / / David Thompson, Tiny Arora and Sonia Sharp |
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Pubbl/distr/stampa |
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London ; ; New York : , : Routledge Falmer : , : Taylor & Francis Group, , 2002 |
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ISBN |
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1-134-58020-7 |
1-280-13852-1 |
0-203-99482-5 |
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Descrizione fisica |
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1 online resource (230 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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Bullying |
Case studies |
Prevention |
Social Sciences |
Psychology |
Electronic books. |
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Lingua di pubblicazione |
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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 bibliografia |
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Includes bibliographical references (pages [195]-207) and index. |
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Nota di contenuto |
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Book Cover; Title; Contents; Tables; Preface: series introduction; Introduction: an overview; The emergence of bullying; The social basis of bullying; How much bullying? Assessment and measurement; The experiences of those who are bullied; Changing cultures; Managing the anti-bullying project in school; Preventing and responding to bullying behaviour; Researching bullying: where are we now?; Conclusions: the limits of current knowledge; Appendix: measuring bullying with the Life in School checklist; References; Index |
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Sommario/riassunto |
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Bullying: Effective Strategies for Long Term Improvement tackles the sensitive issue of bullying in schools and offers practical guidance on how to deal successfully with the issue in the long term.The authors examine how bullying begins, the impact of bullying on the victimised child, and how the extent of bullying in schools can be reliably measured and assessed. They go on to explain how to set up anti- |
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bullying initiatives which will maintain their effectiveness over the years. The complexity of the bullying process is emphasised throughout, but care is taken to outline clearly |
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2. |
Record Nr. |
UNINA9910451443303321 |
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Titolo |
Advanced automation techniques in adaptive material processing [[electronic resource] /] / Editors: XiaoQi Chen, Rajagopalan Devanathan, Aik Meng Fong |
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Pubbl/distr/stampa |
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River Edge, N.J., : World Scientific, c2002 |
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ISBN |
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Descrizione fisica |
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1 online resource (321 p.) |
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Altri autori (Persone) |
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ChenXiaoqi |
DevanathanR (Rajagopalan) |
FongAik Meng |
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Disciplina |
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Soggetti |
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Manufacturing processes - Automation |
Robotics |
Welding - Automation |
Mechatronics |
Electronic books. |
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Lingua di pubblicazione |
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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 bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Preface; Contents; Chapter 1 Overview of Material Processing Automation; 1. Constrained and Non-Constrained Material Processing; 2. Multi-Facet Mechatronic Automation; 3. Sensors for Material Processing; 3.1 Measurands in Material Processing; 3.2 Types of Sensors; 3.3 Microsensors and Soft Sensors; 4. Intelligent Control Techniques; 4.1 Conventional Computer Numerical Control; 4.2 Sensor Based Machine Tool Control; 4.3 Open Architecture and Distributed Control; 4.4 Intelligent Control and Computing Techniques; 4.5 Human-Machine Interface; References |
Chapter 2 Process Development and Approach for 3D Profile Grinding/Polishing1. Introduction; 2. Profile Grinding and Polishing of |
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Superalloys; 2.1 Superalloy Components and Manual Blending; 2.2 CNC Milling; 2.3 Wheel Grinding; 3. Force Control in Material Removal; 3.1 Robot Holding Tool; 3.2 Robot Holding Workpiece; 4. Model-Based Robotic Machining; 5. Part Variations and Process Dynamics; 6. System Concept of Adaptive Robotic Blending System; 6.1 A Mechatronic Approach; 6.2 Device and Process; 6.3 Knowledge-Based Process Control (KBPC); 6.4 Data-Driven Supervisory Control (DDSC) |
6.5 System Layout and Working Cycle7. Process Optimisation; 7.1 Grinding/Polishing Process Parameters; 7.2 Tool Path Optimisation; 7.3 Tool Wear Compensation; 8. Concluding Remarks; References; Chapter 3 Adaptive Robotic System for 3D Profile Grinding/Polishing; 1. Introduction; 2. Finishing Robot and Control Interface; 2.1 Finishing Robot; 2.2 Self-Aligned End Effector; 2.3 Control Interface; 3. In-Situ Profile Measurement; 3.1 Off-Line versus In-Situ Approach; 3.2 Sensor Techniques; 3.3 Coordinate Transform; 4. Template-Based Optimal Profile Fitting; 4.1 Template Generation |
4.2 Profile Fitting Requirements4.3 A Fast Converging Minimisation Algorithm; 4.4 Software Development; 5. Adaptive Robot Path Planner; 5.1 Definition of Tool Path; 5.2 Derivation of End-Effector Orientation; 5.3 Generation of Tool Path; 6. Implementation of SMART 3D Blending System; 7. Results; 7.1 Dimension of Finish Profile; 7.2 Surface Roughness and Finish Quality; 7.3 Wall Thickness; 8. Concluding Remarks; References; Chapter 4 Acoustic Emission Sensing and Signal Processing for Machining Monitoring and Control; 1. Introduction; 2. Sensors in Machining Process Monitoring |
2.1 Motor Current & Power2.2 Force/Torque; 2.3 Vibration/Acceleration Signals; 2.4 Optical and Vision System; 3. Acoustic Emission Sensing; 3.1 Acoustic Emission Mechanism; 3.2 Acoustic Emission in Machining; 3.3 Acoustic Emission Sensors; 4. Advanced Signal Processing Techniques; 4.1 Time Domain Analysis; 4.2 Time Series Modelling; 4.3 Frequency Domain Analysis; 4.4 Time-Frequency Domain Analysis; 4.5 Wavelet Analysis; 5. Conclusions; References; Chapter 5 Techniques of Automatic Weld Seam Tracking; 1. Introduction to Weld Seam Tracking; 1.1 The Importance of Welding; 1.2 What is Welding? |
1.3 Automated Welding |
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Sommario/riassunto |
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This volume presents the editors' research as well as related recent findings on the applications of modern technologies in electrical and electronic engineering to the automation of some of the common manufacturing processes that have traditionally been handled within the mechanical and material engineering disciplines. In particular, the book includes the latest research results achieved through applied research and development projects over the past few years at the Gintic Institute of Manufacturing Technology, Singapore. It discusses advanced automation technologies such as in-process sens |
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