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1. |
Record Nr. |
UNINA9910765541303321 |
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Autore |
Waller Lee |
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Titolo |
Higher Education . Volume 3 : Reflections From the Field / / Lee Waller, Sharon Waller |
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Pubbl/distr/stampa |
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London, England : , : IntechOpen, , 2023 |
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ISBN |
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Descrizione fisica |
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1 online resource (358 pages) : illustrations |
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Collana |
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IntechOpen book series. Educational and human development ; ; volume 5 |
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Disciplina |
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Soggetti |
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Higher education and state |
Public health |
COVID-19 (Disease) |
Pandemic |
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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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Nota di contenuto |
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Table of Contents -- 1. Perspective Chapter: Changing the Educational Metaphors -- 2. A Study on the Writing Educational Needs by Learner Type: Based on the Basic Class of H University -- 3. Perspective Chapter: Developing a Semiotic Awareness of Argumentation in Academic Writing for Studies in Higher Education -- 4. Perspective Chapter: The Metaverse for Education -- 5. Perspective Chapter: Communication as an Essential Strategy in the Success of the Teaching-Learning Process -- 6. Institutional Policies and Initiatives for the Internationalization of HE: A Case of Southeast Asia and Pakistan -- 7. Pandemic Pivot: A Faculty Development Program for Enhanced Remote Teaching -- 8. Synchronous Learning in Institutions of Higher Learning during COVID-19: Lessons from Developing Countries -- 9. Higher Education: What does the Neurocognitive Evidence Say for Decision-Making and Complex Problem Solving? -- 10. Experience-Based Reflections on the Blended Learning Pedagogical Approach in Higher Education -- 11. Flipped Classroom Approach of Teaching Chemistry in Higher Education -- 12. The Use of Metacognitive Strategies in EFL Academic Writing -- 13. Teaching Professional Ethical Knowledge and Teaching Digital Skills in Higher Education -- 14. Perspective Chapter: A Phenomenological Study of an International |
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Class Program at an Indonesian University -- 15. Perspective Chapter: African Higher Education Centers of Excellence - A Critical Reflection -- 16. Perspective Chapter: Sustaining University Education for and National Development in Nigeria -- 17. Perspective Chapter: Artifact Remains in Indonesia as an Object of Field Study of Learning Media for the History of Indonesian Fine Arts Course -- 18. Perspective Chapter: Academia as a Culture - The 'Academy' for Women Academics -- 19. Perspective Chapter: Alumni Engagement in Higher Education Institutions - Perspectives from India -- 20. Perspective Chapter: Teacher Education in a Multicultural Globalizing World - Field-Based Reflections -- 21. Perspective Chapter: Reflections on the Future of Higher Education in the United Kingdom -- 2. Perspective Chapter: A Systematic Study for Model Management Education toward Problem Based Learning in West Africa -- 23. Perspective Chapter: Toxic Leadership in Higher Education - What We Know, How It Is Handled. |
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Sommario/riassunto |
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COVID wrought havoc on the world's economic systems. Higher education did not escape the ravages brought on by the pandemic as institutions of higher education around the world faced major upheavals in their educational delivery systems. Some institutions were prepared for the required transition to online learning. Most were not. Whether prepared or not, educators rose to the challenge. The innovativeness of educators met the challenges as digital learning replaced the face-to-face environment. In fact, some of the distance models proved so engaging that many students no longer desire a return to the face-to-face model. As with all transitions, some things were lost while others were gained. This book examines practice in the field as institutions struggled to face the worst global pandemic in the last century. The book is organized into four sections on "Changing Education", "Education in the Pandemic", "Sustaining University Education", and "Embracing the Future in a Global World". It presents various perspectives from educators around the world to illustrate the struggles and triumphs of those facing new challenges and implementing new ideas to empower the educational process. These discussions shed light on the impact of the pandemic and the future of higher education post-COVID. Higher education has been forever changed, and higher education as it once was may never return. While many questions arise, the achievements in meeting and overcoming the pandemic illustrate the creativity and innovativeness of educators around the world who inspired future generations of learners to reach new heights of accomplishment even in the face of the pandemic. |
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2. |
Record Nr. |
UNINA9911004846903321 |
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Autore |
Glaser Andrew |
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Titolo |
Industrial Robotics : practical applications for implementing robotic automation / / Andrew Glaser |
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Pubbl/distr/stampa |
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[Place of publication not identified], : Industrial Press Incorporated, 2008 |
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ISBN |
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0-8311-9207-0 |
1-60119-936-8 |
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Classificazione |
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Disciplina |
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Soggetti |
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Robots, Industrial |
Mechanical Engineering |
Engineering & Applied Sciences |
Industrial & Management Engineering |
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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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Bibliographic Level Mode of Issuance: Monograph |
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3. |
Record Nr. |
UNINA9910734093703321 |
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Titolo |
Deep Neural Evolution : Deep Learning with Evolutionary Computation / / edited by Hitoshi Iba, Nasimul Noman |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2020 |
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ISBN |
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Edizione |
[1st ed. 2020.] |
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Descrizione fisica |
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1 online resource (437 pages) |
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Collana |
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Natural Computing Series, , 2627-6461 |
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Disciplina |
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Soggetti |
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Machine learning |
Neural networks (Computer science) |
Machine Learning |
Mathematical Models of Cognitive Processes and Neural Networks |
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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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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Chapter 1: Evolutionary Computation and meta-heuristics -- Chapter 2: A Shallow Introduction to Deep Neural Networks -- Chapter 3: On the Assessment of Nature-Inspired Meta-Heuristic Optimization Techniques to Fine-Tune Deep Belief Networks -- Chapter 4: Automated development of DNN based spoken language systems using evolutionary algorithms -- Chapter 5: Search heuristics for the optimization of DBN for Time Series Forecasting -- Chapter 6: Particle Swarm Optimisation for Evolving Deep Convolutional Neural Networks for Image Classification: Single- and Multi-objective Approaches -- Chapter 7: Designing Convolutional Neural Network Architectures Using Cartesian Genetic Programming -- Chapter 8: Fast Evolution of CNN Architecture for Image Classificaiton -- Chapter 9: Discovering Gated Recurrent Neural Network Architectures -- Chapter 10: Investigating Deep Recurrent Connections and Recurrent Memory Cells Using Neuro-Evolution -- Chapter 11: Neuroevolution of Generative Adversarial Networks -- Chapter 12: Evolving deep neural networks for X-ray based detection of dangerous objects -- Chapter 13: Evolving the architecture and hyperparameters of DNNs for malware detection -- Chapter 14: Data Dieting in GAN Training -- Chapter 15: One-Pixel Attack: Understanding and Improving Deep Neural Networks with Evolutionary Computation. |
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Sommario/riassunto |
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This book delivers the state of the art in deep learning (DL) methods hybridized with evolutionary computation (EC). Over the last decade, DL has dramatically reformed many domains: computer vision, speech recognition, healthcare, and automatic game playing, to mention only a few. All DL models, using different architectures and algorithms, utilize multiple processing layers for extracting a hierarchy of abstractions of data. Their remarkable successes notwithstanding, these powerful models are facing many challenges, and this book presents the collaborative efforts by researchers in EC to solve some of the problems in DL. EC comprises optimization techniques that are useful when problems are complex or poorly understood, or insufficient information about the problem domain is available. This family of algorithms has proven effective in solving problems with challenging characteristics such as non-convexity, non-linearity, noise, and irregularity, which dampen the performance of most classic optimization schemes. Furthermore, EC has been extensively and successfully applied in artificial neural network (ANN) research —from parameter estimation to structure optimization. Consequently, EC researchers are enthusiastic about applying their arsenal for the design and optimization of deep neural networks (DNN). This book brings together the recent progress in DL research where the focus is particularly on three sub-domains that integrate EC with DL: (1) EC for hyper-parameter optimization in DNN; (2) EC for DNN architecture design; and (3) Deep neuroevolution. The book also presents interesting applications of DL with EC in real-world problems, e.g., malware classification and object detection. Additionally, it covers recent applications of EC in DL, e.g. generative adversarial networks (GAN) training and adversarial attacks. The book aims to prompt and facilitate the research in DL with EC both in theory and in practice. |
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