An Application of the Moving Frame Method to Integral Geometry in the Heisenberg Group

We show the fundamental theorems of curves and surfaces in the 3-dimensional Heisenberg group and find a complete set of invariants for curves and surfaces respectively. The proofs are based on Cartan's method of moving frames and Lie group theory. As an application of the main theorems, a Crofton-type formula is proved in terms of p-area which naturally arises from the variation of volume. The application makes a connection between CR geometry and integral geometry

Assessing the diffusion of FinTech innovation in financial industry: using the rough MCDM model

We develop a conceptual structure to explore how financial technology (FinTech) innovation is being implemented to deal with vague, inconsistent and ambiguous knowledge in actual world. The structure of this study is built upon the technology, organization, environment (TOE) context, which one uses the concept of multi-criteria estimation to measure the significance of FinTech innovation. We develop an integrated MCDM (multiple criteria decision-making) model through rough set theory help administrators obtain a strategic influence relation map for enhancing performance approaching towards the aspiration value. This model involves three steps: primary, we apply this rough number to define group views which reflect upon experts’ real experiences; second, we use the rough DEMATEL-based ANP-(RDANP) to acquire the rough influential weights and rough influential network relationship map (RINRM) based on this TOE structure and its corresponding attributes; finally, we utilize the rough modified VIKOR with the influence to analyze the gap between the performance value and the aspirated level. The empirical case was originated from financial industry in Taiwan. According to the weighting results the expected benefits, technology integration, and competitive pressure were the most important criteria. Our results also illustrate how FinTech innovation can be used for promoting financial services

Associations between blood glucose level and outcomes of adult in-hospital cardiac arrest: a retrospective cohort study

Additional file 3: Table S3. Features, interventions, and outcomes of cardiac arrest events stratified by the presence of measurement of blood glucose level after sustained return of spontaneous circulation

RVSL: Robust Vehicle Similarity Learning in Real Hazy Scenes Based on Semi-supervised Learning

Recently, vehicle similarity learning, also called re-identification (ReID), has attracted significant attention in computer vision. Several algorithms have been developed and obtained considerable success. However, most existing methods have unpleasant performance in the hazy scenario due to poor visibility. Though some strategies are possible to resolve this problem, they still have room to be improved due to the limited performance in real-world scenarios and the lack of real-world clear ground truth. Thus, to resolve this problem, inspired by CycleGAN, we construct a training paradigm called \textbf{RVSL} which integrates ReID and domain transformation techniques. The network is trained on semi-supervised fashion and does not require to employ the ID labels and the corresponding clear ground truths to learn hazy vehicle ReID mission in the real-world haze scenes. To further constrain the unsupervised learning process effectively, several losses are developed. Experimental results on synthetic and real-world datasets indicate that the proposed method can achieve state-of-the-art performance on hazy vehicle ReID problems. It is worth mentioning that although the proposed method is trained without real-world label information, it can achieve competitive performance compared to existing supervised methods trained on complete label information.Comment: Accepted by ECCV 202