TL;DR: Kumar and Dillon as mentioned in this paper recently presented a conceptual, overall consistency criterion that represents a sufficient condition for consistency, and clarified the inconsistency criterion in a follow-up article, which they referred to as overall consistency.
Abstract: Kumar and Dillon recently presented a conceptual, overall consistency criterion that represents a sufficient condition for consistency. In commenting on their article, the authors (1) clarify the i...
TL;DR: The main result of the paper is a statement of the necessary and sufficient condition answering the following question: "given an arbitrary set of local checkpoints, can this set be extended to a global checkpoint that satisfies P" (where P is traditional consistency, transitlessness, or strong consistency).
Abstract: A global checkpoint is a set of local checkpoints, one per process. The traditional consistency criterion for global checkpoints states that a global checkpoint is consistent if it does not include messages received and not sent. This paper investigates other consistency criteria, transitlessness, and strong consistency. A global checkpoint is transitless if it does not exhibit messages sent and not received. Transitlessness can be seen as a dual of traditional consistency. Strong consistency is the addition of transitlessness to traditional consistency. The main result of this paper is a statement of the necessary and sufficient condition answering the following question: Given an arbitrary set of local checkpoints, can this set be extended to a global checkpoint that satisfies P (where P is traditional consistency, transitlessness, or strong consistency). From a practical point of view, this condition, when applied to transitlessness, is particularly interesting as it helps characterize which messages do not need to be recorded by checkpointing protocols.
TL;DR: A general criterion, the asymptotic consistency criterion, for these DT models to inherit the dynamical behavior of their CT counterparts is derived and detailed instances of this criterion are established for several classes of neural networks.
TL;DR: In this article, a system for admitting medical imaging data comprising image data and associated metadata comprises input means arranged to received image data from at least one source, a memory having stored therein consistency data, and processing mean arranged to analyse the imaging data to determine whether it meets the consistency criterion, and if it does not to amend the image data so that it does.
Abstract: A system for admitting medical imaging data comprising image data and associated metadata comprises input means arranged to received image data from at least one source, a memory having stored therein consistency data defining at least one consistency criterion, and processing means arranged to analyse the imaging data to determined whether it meets the consistency criterion, and if it does not to amend the imaging data so that it does
TL;DR: Control of the Type I error rate as well as power of the proposed methodology are discussed and its application to clinical trial data is considered.
Abstract: In a clinical trial with two clinically important endpoints, each of which can fully characterize a treatment benefit to support an efficacy claim by itself, a minimum degree of consistency in the findings is expected; otherwise interpretation of study findings can be problematic. Clinical trial literature contains examples where lack of consistency in the findings of clinically relevant endpoints led to difficulties in interpreting study results. The aim of this paper is to introduce this consistency concept at the study design stage and investigate the consequences of its implementation in the statistical analysis plan. The proposed methodology allows testing of hierarchically ordered endpoints to proceed as long as a pre-specified consistency criterion is met. In addition, while an initial allocation of the alpha level is specified for the ordered endpoints at the design stage, the methodology allows the alpha level allocated to the second endpoint to be adaptive to the findings of the first endpoint. In addition, the methodology takes into account the correlation between the endpoints in calculating the significance level and the power of the test for the next endpoint. The proposed Consistency-Adjusted Alpha-Adaptive Strategy (CAAAS) is very general. Several of the well-known multiplicity adjustment approaches arise as special cases of this strategy by appropriate selection of the consistency level and the form of alpha-adaptation function. We discuss control of the Type I error rate as well as power of the proposed methodology and consider its application to clinical trial data.