Due to the high sensitivity of diffusion tensor imaging (DTI) to physiological motion, clinical DTI scans often suffer a significant amount of artifacts. Tensor-fitting-based, post-processing outlier rejection is often used to reduce the influence of motion artifacts. Although it is an effective approach, when there are multiple corrupted data, this method may no longer correctly identify and r...

We use an original variant of the standard trust game to study effects corruption on and trustworthiness. In this game, both trustor trustee know that part surplus they can generate may be captured by a third “corrupted” player under different expected costs audit prosecution. find slightly higher trustor’s giving in presence corruption, matched significant excess reciprocity from trustee. Both...

This paper presents a new multi-sensor data fusion method based on the combination of wavelet transform (WT) and extended Kalman filter (EKF). Input data are first filtered by a wavelet transform via Daubechies wavelet “db4” functions and the filtered data are then fused based on variance weights in terms of minimum mean square error. The fused data are finally treated by extended Kalman filter...

We apply basic statistical reasoning to signal reconstruction by machine learning — learning to map corrupted observations to clean signals — with a simple and powerful conclusion: under certain common circumstances, it is possible to learn to restore signals without ever observing clean ones, at performance close or equal to training using clean exemplars. We show applications in photographic ...

Given multiple corrupted versions of the same text, as is common with ancient manuscripts, we wish to reconstruct the original text from which the extant corrupted versions were copied (typically via latent intermediary versions). This is a challenge of cardinal importance in the humanities. We use a variant of expectation-maximization (EM), to solve this problem. We prove the efficacy of our m...