HYCEDIS: HYbrid Confidence Engine for Deep Document Intelligence System

Measuring the confidence of AI models is critical for safely deploying AI in real-world industrial systems. One important application of confidence measurement is information extraction from scanned documents. However, there exists no solution to provide reliable confidence score for current state-of-the-art deep-learning-based information extractors. In this paper, we propose a complete and novel architecture to measure confidence of current deep learning models in document information extraction task. Our architecture consists of a Multi-modal Conformal Predictor and a Variational Cluster-oriented Anomaly Detector, trained to faithfully estimate its confidence on its outputs without the need of host models modification. We evaluate our architecture on real-wold datasets, not only outperforming competing confidence estimators by a huge margin but also demonstrating generalization ability to out-of-distribution data.Comment: Document Intelligence @ KDD 2021 Worksho

Preparation of cross-linked magnetic chitosan particles from steel slag and shrimp shells for removal of heavy metals

<p>In this study, a new method for preparation of cross-linked magnetic chitosan particles (MCPs) from steel slag and shrimp shells using green tea extract as crosslinking reagent has been presented. The MCPs obtained were characterized by means of X-ray diffraction analysis, Fourier-transform infrared spectroscopy, scanning electron microscopy and magnetic properties, and then were used to investigate the adsorption properties of Cu(II) and Ni(II) ions in aqueous solutions. The influence of experimental conditions such as contact time, pH value, adsorbent dose and initial metal concentration, and the possibility of regeneration were studied systematically. The Cu(II) and Ni(II) adsorption isotherms, kinetics and thermodynamics have been measured and discussed. The results show that the synthesized MCPs have high adsorption capacity for both metal ions (126.58 mg/g for Cu(II) and 66.23 mg/g for Ni(II)), and have excellent regeneration stability with efficiency of greater than 83% after five cycles of the adsorption–regeneration process. The adsorption process of Ni(II) and Cu(II) on MCPs was feasible, spontaneous and exothermic, and better described by the Langmuir model and pseudo-second-order kinetic equation. The MCPs can be applied as a low cost and highly efficient adsorbent for removal of heavy metals from wastewater due to its high adsorption capacity, easy recovery and good reusability.</p