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Record Nr. |
UNINA9910592989403321 |
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Titolo |
Knowledge Production and the Search for Epistemic Liberation in Africa / / edited by Dennis Masaka |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
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ISBN |
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9783031079658 |
9783031079641 |
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Edizione |
[1st ed. 2022.] |
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Descrizione fisica |
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1 online resource (233 pages) |
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Disciplina |
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Soggetti |
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Philosophy, African |
Knowledge, Theory of |
African Philosophy |
Epistemology |
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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. Introduction -- Chapter. 2. Epistemicide’ and Epistemic Emancipation in Africa – Problems and Promises -- Chapter. 3. Knowledge production and the Liberation agenda in Africa -- Chapter. 4. Decolonisation as self-recovery: the path to intellectual independence -- Chapter. 5. Colonial legacy and knowledge production in Africa: Re-echoing the need for epistemic decolonisation -- Chapter. 6. A critical exposition of ‘alternative’ site(s) of knowledge production in Africa: Decentering the African university -- Chapter. 7. African Epistemic liberation through knowledge democratisation -- Chapter. 8. How African Logic can dissipate the Question of Originality and Knowledge Production in Africa -- Chapter. 9. Africanising Institutional Culture: What Is Possible and Plausible -- Chapter. 10. 'Africa’s Knowledge and the Quest for Epistemic Liberation in a COVID-19 Crisis -- Chapter. 11. Religiosity and African Epistemology -- Chapter. 12. Ukama ethic and Covid-19 pandemic: Countervailing social distancing-induced exclusive individualism in (southern) African university -- Chapter. 13. African Indigenous Knowledge and the management of |
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COVID-19 pandemic -- Chapter. 14. African Knowledge Systems: Shona Paremiology in Promoting Morals, Peace and Human Security -- Chapter. 15. A Yòrùbá Worldview on the Compatibility of Human and Nonhuman Animal Relations (HAR) with Environmental Sustainability. |
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Sommario/riassunto |
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This book shows the importance of knowledge production using requisite terms and frameworks to the broader scheme of epistemic liberation in Africa. The text considers what this veritable direction to knowledge production would mean to other areas of concern in African philosophy such as morality, education and the environment. These contributions are important because the success of decolonising projects in African countries depend upon the methods that underpin envisioned liberative knowledge production in light of Africa’s historical and present condition. This volume appeals to students and researchers working in epistemology and African philosophy. |
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2. |
Record Nr. |
UNINA9910897974703321 |
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Titolo |
Handbook of AI and Data Sciences for Sleep Disorders / / edited by Richard B. Berry, Panos M. Pardalos, Xiaochen Xian |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
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ISBN |
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Edizione |
[1st ed. 2024.] |
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Descrizione fisica |
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1 online resource (X, 304 p. 63 illus., 54 illus. in color.) |
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Collana |
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Springer Optimization and Its Applications, , 1931-6836 ; ; 216 |
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Disciplina |
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Soggetti |
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Mathematical optimization |
Calculus of variations |
Neurology |
Machine learning |
Artificial intelligence - Data processing |
Calculus of Variations and Optimization |
Machine Learning |
Data Science |
Intel·ligència artificial en medicina |
Trastorns del son |
Neurologia |
Aprenentatge automàtic |
Llibres electrònics |
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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. |
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Nota di contenuto |
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Empowering Sleep Health: Unleashing the Potential of Artificial Intelligence and Data Science in Sleep Disorders -- Polysomnography Raw Data Extraction, Exploration, and Preprocessing -- Sleep stage probabilities derived from neurological or cardio-respiratory signals by means of artificial intelligence -- From Screening at Clinic to Diagnosis at Home: How AI/ ML/DL Algorithms are Transforming Sleep Apnea Detection -- Modeling and Analysis of Mechanical Work of Breathing -- A Probabilistic Perspective: Bayesian Neural Network for Sleep Apnea Detection -- Automatic and machine learning methods for detection and characterization of REM sleep behavior disorder -- Sleep Cyclic Alternating Pattern (CAP) as a Neurophysiological Marker of Brain Health -- Deep Learning with Electrocardiograms -- Machine learning automated analysis applied to mandibular jaw movements during sleep: a window on polysomnography -- Nightmare disorder: An Overview. |
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Sommario/riassunto |
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The rise of lifestyle changes resulting from constant connectivity, irregular work schedules, heightened stress, and disruptive sleep patterns, have contributed to increasing insomnia rates. Exacerbated by the COVID-19 pandemic, sleep disorders are more prevalent than ever. This handbook offers a comprehensive exploration of the fusion of Artificial Intelligence (AI) and data science within the realm of sleep disorders, presenting innovative approaches to diagnosis, treatment, and personalized care. The interdisciplinary nature of this handbook fosters collaboration between experts from diverse fields, including computer science, engineering, neuroscience, medicine, public health, AI, data science, and sleep medicine. Each chapter delves into specific aspects of sleep disorder analysis, innovative methodologies, novel insights, and real-world applications that showcase the transformative potential of AI and data science in sleep medicine, from analyzing sleep patterns and predicting disorder risk factors to utilizing big data analytics for large-scale epidemiological studies. This handbook hopes to offer a comprehensive resource for researchers, clinicians, and policymakers striving to address the challenges in sleep medicine. |
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