Genre-specific Error Detection with Multimodal Feedback

A purpose-built online error detection tool was developed to provide genre-specific corpus-based feedback on errors occurring in draft research articles and graduation theses. The primary envisaged users were computer science majors studying at a public university in Japan. This article discusses the development and evaluation of this interactive, multimodal tool. An in-house learner corpus of graduation theses was annotated for errors that affect the accuracy, brevity, clarity, objectivity and formality of scientific research writing. Software was developed to identify the errors discovered and provide learners with actionable advice and multimodal explanations in both English and Japanese. Qualitative evaluation received in usability studies and focus groups from both teachers and students was extremely positive. Preliminary quantitative evaluation of the effectiveness of the error detector was conducted. Through this pedagogic tool, learners can receive immediate actionable feedback on potential errors, and their teachers no longer feel obliged to check for common genre-specific errors.

A fully automated pipeline for mining abdominal aortic aneurysm using image segmentation

Imaging software have become critical tools in the diagnosis and the treatment of abdominal aortic aneurysms (AAA). The aim of this study was to develop a fully automated software system to enable a fast and robust detection of the vascular system and the AAA. The software was designed from a dataset of injected CT-scans images obtained from 40 patients with AAA. Pre-processing steps were performed to reduce the noise of the images using image filters. The border propagation based method was used to localize the aortic lumen. An online error detection was implemented to correct errors due to the propagation in anatomic structures with similar pixel value located close to the aorta. A morphological snake was used to segment 2D or 3D regions. The software allowed an automatic detection of the aortic lumen and the AAA characteristics including the presence of thrombus and calcifications. 2D and 3D reconstructions visualization were available to ease evaluation of both algorithm precision and AAA properties. By enabling a fast and automated detailed analysis of the anatomic characteristics of the AAA, this software could be useful in clinical practice and research and be applied in a large dataset of patients.

An Efficient Hardware-Based Fault-Tolerant Method for SMS4

The SMS4 cryptosystem has been used in the Wireless LAN Authentication and Privacy Infrastructure (WAPI) standard for providing data confidentiality in China. So far, reliability has not been considered a primary objective in original version. However, a single fault in the encryption/decryption process can completely change the result of the cryptosystem no matter the natural or malicious injected faults. In this paper, we proposed low-cost structure-independent fault detection scheme for SMS4 cryptosystem which is capable of performing online error detection and can detect a single bit fault or odd multiple bit faults in coverage of 100 percent. Finally, the proposed techniques have been validated on Virtex-7 families FPGA platform to analyze its power consumption, overhead and time delay. It only needs 85 occupied Slices and 8.72mW to run a fault-tolerant scheme of SMS4 cryptosystem with 0.735ns of detection delay. Our new scheme increases in minimum redundancy to enhance cryptosystem’s reliability and achieve a better performance compared with the previous scheme.