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Titlebook: Husserl’s Phenomenology; From Pure Logic to E James Richard Mensch Book 2023 The Editor(s) (if applicable) and The Author(s), under exclusi

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發(fā)表于 2025-3-21 19:48:39 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Husserl’s Phenomenology
副標(biāo)題From Pure Logic to E
編輯James Richard Mensch
視頻videohttp://file.papertrans.cn/431/430034/430034.mp4
概述Addresses the fundamental issues of the consistency of Husserl’s descriptions of subjectivity.Covers the entire span of Husserl’s career in a compact format.Includes multiple citations and examples
叢書名稱Phaenomenologica
圖書封面Titlebook: Husserl’s Phenomenology; From Pure Logic to E James Richard Mensch Book 2023 The Editor(s) (if applicable) and The Author(s), under exclusi
描述.This text examines the many transformations in Husserl’s phenomenology that his discoveries of the nature of appearing lead to. It offers a comprehensive look at the Logical Investigations’ delimitation of the phenomenological field, and continues with Husserl’s account of our consciousness of time. This volume examines Husserl’s turn to transcendental idealism and the problems this raises for our recognition of other subjects.?I details Husserl’s account of embodiment and examines his theory of the instincts. Drawing from his published and unpublished manuscripts, it outlines his treatment of our mortality and the teleological character of our existence. ?This book appeals to students and researchers and presents a genetic account of our selfhood, one that unifies Husserl’s different claims about who and what we are..
出版日期Book 2023
關(guān)鍵詞Husserl’s Phenomenology; Refutation of Psychologism; Phenomenology of Embodiment; Transcendental Ideali
版次1
doihttps://doi.org/10.1007/978-3-031-26147-3
isbn_softcover978-3-031-26149-7
isbn_ebook978-3-031-26147-3Series ISSN 0079-1350 Series E-ISSN 2215-0331
issn_series 0079-1350
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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James Richard Menschtion its connectivity with its neighborhood as well as its importance within a transaction. The measure is especially useful in problem domains utilizing network or interaction characteristics amongst items such as in a social network or web click-stream data. We compared our technique against state
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James Richard Menschabout diseases such as the coronavirus disease 2019 (COVID-19). This knowledge helps users to get a better understanding of the disease, and thus to take parts in preventing, controlling and/or combating the disease. However, many existing data science models often require lots of historical data fo
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d. The experimental results show that the image interpolation method and sift algorithm can improve the brightness continuity and visual effect of the sequence images, so the information in the images can be obtained better when observing the images in the experiment. The computer three-dimensional
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