To check students’ daily language learning tasks and give students corresponding reasonable scores based on their daily behavior is hard for teachers. The existing online language learning systems are vulnerable and easy to be modified by teachers or system managers. Blockchain can provide immutable and trusted storage service and automatic calculation service. Therefore, a blockchain-based online language learning system is proposed in this paper to monitor students’ daily study and automatically evaluate their behavior so as to save teachers from tedious and complex homework verification workload and provide trusted and reliable evaluation on students’ behavior. This paper first introduces the current situation of language learning in universities and the related works on blockchain-based online language learning system. Then the system is detailed in its structure and smart contracts. At last, we implement this system and do the analysis and summary.
Image resizing becomes more and more important in content-aware image displaying. This paper proposes a patchwise scaling method to resize an image to emphasize the important areas and preserve the globally visual effect (smoothness, coherence and integrity). This method for resizing image is based on optimizing the image distance presented in this paper. The image distance is defined based on so-called local bidirectional similarity measurement and smoothness measurement to quantify the quality of resizing outputs. The original image is divided into small important patches and unimportant patches based on an important map. The important map is generated automatically using a novel combination of image edge and saliency measurement. A scaling factor is computed for each small patch. The resized image is produced by iteratively optimizing, which is based on our image distance, the scaling factor for each small patch. Experiments of different type images demonstrate that our method can be effectively used in image processing applications to locally shrink and enlarge important areas while preserving image quality. 相似文献