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A reconstruction of Aristotle's modal syllogistic

History and Philosophy of Logic, 2006
Ever since Łukasiewicz, it has been opinio communis that Aristotle's modal syllogistic is incomprehensible due to its many faults and inconsistencies, and that there is no hope of finding a single consistent formal model for it. The aim of this paper is to disprove these claims by giving such a model.
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Unified reconstruction framework for multi-modal medical imaging

Journal of X-Ray Science and Technology: Clinical Applications of Diagnosis and Therapeutics, 2011
Various types of advanced imaging technologies have significantly improved the quality of medical care available to patients. Corresponding medical image reconstruction algorithms, especially 3D reconstruction, play an important role in disease diagnosis and treatment assessment. However, these increasing reconstruction methods are not implemented in a
Di, Dong   +5 more
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Federated Pseudo Modality Generation for Incomplete Multi-Modal MRI Reconstruction

IEEE Journal of Biomedical and Health Informatics
While multi-modal learning has been widely used for MRI reconstruction, it relies on paired multi-modal data, which is difficult to acquire in real clinical scenarios. Especially in the federated setting, there is a common issue that several medical institutions suffer from missing modalities or even only have single-modal data.
Yunlu Yan   +8 more
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H. B. Smith on modality: A logical reconstruction

Journal of Philosophical Logic, 1987
This paper offers a reconstruction of some ideas of H. B. Smith on the logic of (alethic) modalities developed in the mid-30's. Smith's main assumptions are (A) that any two positive modalities \(\Gamma\), \(\Delta\) (i.e. any strings of modal operators \(\square\), \(\diamond)\) are comparable in the sense that either \(\Gamma\) p entails \(\Delta\) p
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Modalities as Indicators in Argumentative Reconstruction

2009
This paper addresses the role of modal expressions as argumentative indicators and the importance of considering the semantics of modality in the reconstruction of argumentation. Modal expressions include modal verbs, such as the English may, can, must, should, will and many other lexical and grammatical devices.
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Errors in Zernike Transformations and Non-modal Reconstruction Methods

Journal of Refractive Surgery, 2005
ABSTRACT PURPOSE: Wavefront aberrometers often represent the wavefront in terms of Zernike polynomials. The fit coefficients for these polynomials are pupil-size dependent; hence it is desirable to be able to calculate polynomial coefficients at a different pupil size from the initial measurement.
Daniel R, Neal   +2 more
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Same Modality nerve Reconstruction for Accessory nerve Injuries

Otolaryngology–Head and Neck Surgery, 2008
The standard repair of a nerve gap under tension is to use a sensory autograft, such as the medial antebrachial cutaneous or the sural nerve. The practice of using sensory grafts to repair motor nerve defects is challenged by the discovery of preferential motor reinnervation and modality specific nerve regeneration.
Christina K, Magill   +2 more
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Evidence Reconstruction of Epistemic Modal Logic S5

2006
We introduce the logic of proofs whose modal counterpart is the modal logic S5. The language of Logic of Proofs LP is extended by a new unary operation of negative checker “?”. We define Kripke-style models for the resulting logic in the style of Fitting models and prove the corresponding Completeness theorem. The main result is the Realization theorem
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Mode Reconstruction for Source Coding and Multi-modal Control

2003
In this paper we take the point of view that control procedures have an information theoretic content that can be more or less effectively coded. Of particular interest are control procedures for navigation and obstacle avoidance for mobile robots, and we show how tokenized instructions can be used for understanding how computer generated inputs to ...
Adam Austin, Magnus Egerstedt
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Work Together: Correlation-Identity Reconstruction Hashing for Unsupervised Cross-Modal Retrieval

IEEE Transactions on Knowledge and Data Engineering, 2023
Lei Zhu, Jingjing Li, Zheng Zhang
exaly  

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