Published papers

Watermarking is a technology to embed digital data into a digital image. In particular, blind watermarking is expected to ensure the authenticity and/or accountability of digital images without compromising the visual impression of viewing. A re-shooting resistant blind watermarking method is proposed in this study. This method uses the features of a given image to select regions, which are modified to embed digital data. As the proposed embedding process preserves these image features, no markers are required to extract the embedded data from the watermarked image. Furthermore, based on the estimation of the watermarked image region, the method crops the re-shot image before the extraction. Therefore, the proposed method works, even if the re-shot image includes the outer area surrounding the watermarked image region. Moreover, the proposed method compensates for the geometric transformation of the re-shot image based on the definition of the coordinate system, which is based on the distribution of the image feature points. Therefore, the proposed method works when the re-shot image is taken diagonally in front of the watermarked image. Experimental results validated that the proposed method can extract the embedded digital data from re-shot images of a watermarked image under considerable conditions of re-shooting. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

This paper proposes a data augmentation method for imbalanced healthcare datasets. This method was inspired by a data augmentation method in natural language processing (NLP) that generates synthetic sentences for training by replacing some words with similar words. The proposed method generates synthetic patient records by replacing patient backgrounds with similar backgrounds. In this paper, the cosine similarity of the distributed representations was used as the similarity metric between patient backgrounds. The distributed representations of the patient backgrounds were generated by the skip-gram model. To confirm the performance improvement with the proposed data augmentation method, the prediction performance of adverse events (AEs) caused by drug administration was experimentally evaluated on a real-world medical dataset with 1,510,137 records. The combination of the proposed data augmentation method and a conventional undersampling method resulted in an 80.0% improvement in accuracy and a 40.0% improvement in the precision and F1-score. The multifaceted evaluation demonstrated that the proposed method is effective, especially for predicting AEs with positive ratios ranging from 1.0% to 2.1%, which are difficult to predict with conventional machine learning methods but should be predictable in the medical field.

The mRNA-1273 Moderna COVID-19 vaccine was introduced to combat the COVID-19 global pandemic in 2020. Although the safety of the vaccine has been investigated worldwide, real-world safety data is scarce in Japan. An online, real-time survey of adverse events following immunization (AEFIs) with mRNA-1273 was conducted in the setting of a workplace vaccination program at the School of Pharmacy, Keio University from 26 June 2021, to 11 June 2022. Participants were requested to take four surveys during a seven-day follow-up period after each of the first, second, and third booster doses. The maximum number of responses, from 301 respondents, was obtained on day 0 (vaccination date) for the first dose. 98% of respondents reported local and systemic AEFIs for the second dose on day 1. No noticeable difference in local reactions was seen among the three doses. Females reported more AEFIs than males, and the young group (18–29 years) reported a higher rate than the middle age group (≥30 years) after the first dose. Age and gender differences in rates decreased at the second and third doses. This survey confirmed that the safety profile of mRNA-1273 in a real-world setting was similar to that derived from the clinical trials, and that the agent was well-tolerated.

Recently, because of the development of industrial systems and network systems, the demands of telehaptics and telesurgery become higher. To realize these systems, a real-time communication which can guarantee deterministic delays and low jitters in a network is required. One of the real-time protocol is Synchronous-Time Division Multiple Access (S-TDMA). S-TDMA makes it possible to coexist of real-time and conventional TCP/IP communications over a multiple-hop network using Ethernet. In previous works, the schedule of real-time combinations was fixed. So this research introduces management mechanism of communication schedules by using the technology of Software Defined Networking (SDN). SDN is a notion to realize a dynamic and centralized control of network configuration by using one controller which can manage all equipments in the network. In this paper, the design and implementation of management mechanism of S-TDMA switches are discussed and performance of the implemented switches is verified. The experiment results confirm that it is possible to change time slot allocation, communication mode and paths dynamically. Results also show that the management system can control multiple switches in the network.

Visual feedback systems utilize position and velocity information estimated from frames captured by a camera. Since the velocity information is derrived through pseudo differential with two consecutive frames, the information must be delayed essentially, and the delay often limits the performance of visual feedback systems. To eliminate the delay, this paper proposed a novel technique to estimate position and velocity information from a single image. By detecting the start and end points of the motion blur of a target object in an image, the velocity information during the exposure time of the image can be estimated fundamentally. To tag such a temporal information on motion blurs, a modulated illumination was employed. This tagging method aimed to make motion blur detection robust against various background scenery. Some simulation results validated the feasibility of the proposed method.

オブザーバ理論をむだ時間補償に応用することを考案し、通信を介したバイラテラルシステムに適用し、信濃町-矢上間のキャンパスネットワーク上での実験により有効性を示している。