A technology roadmap of assistive technologies for dementia care in Japan.

The number of elderly people in Japan is growing, which raises the issue of dementia, as the probability of becoming cognitively impaired increases with age. There is an increasing need for caregivers, who are well-trained, experienced and can pay special attention to the needs of people with dementia. Technology can play an important role in helping such people and their caregivers. A lack of mutual understanding between caregivers and researchers regarding the appropriate uses of assistive technologies is another problem. A vision of person-centred care based on the use of information and communication technology to maintain residents' autonomy and continuity in their lives is presented. Based on this vision, a roadmap and a list of challenges to realizing assistive technologies have been developed. The roadmap facilitates mutual understanding between caregivers and researchers, resulting in appropriate technologies to enhance the quality of life of people with dementia.

Locally oxidized silicon surface-plasmon Schottky detector for telecom regime.

We experimentally demonstrate an on-chip nanoscale silicon surface-plasmon Schottky photodetector based on internal photoemission process and operating at telecom wavelengths. The device is fabricated using a self-aligned approach of local-oxidation of silicon (LOCOS) on silicon on insulator substrate, which provides compatibility with standard complementary metal-oxide semiconductor technology and enables the realization of the photodetector and low-loss bus photonic waveguide at the same fabrication step. Additionally, LOCOS technique allows avoiding lateral misalignment between the silicon surface and the metal layer to form a nanoscale Schottky contact. The fabricated devices showed enhanced detection capability for shorter wavelengths that is attributed to increased probability of the internal photoemission process. We found the responsivity of the nanodetector to be 0.25 and 13.3 mA/W for incident optical wavelengths of 1.55 and 1.31 μm, respectively. The presented device can be integrated with other nanophotonic and nanoplasmonic structures for the realization of monolithic opto-electronic circuitry on-chip.

Locally oxidized silicon surface-plasmon Schottky detector for telecom regime

We experimentally demonstrate an on-chip nanoscale silicon surface-plasmon Schottky photodetector based on internal photoemission process and operating at telecom wavelengths. The device is fabricated using a self-aligned approach of local-oxidation of silicon (LOCOS) on silicon on insulator substrate, which provides compatibility with standard complementary metal-oxide semiconductor technology and enables the realization of the photodetector and low-loss bus photonic waveguide at the same fabrication step. Additionally, LOCOS technique allows avoiding lateral misalignment between the silicon surface and the metal layer to form a nanoscale Schottky contact. The fabricated devices showed enhanced detection capability for shorter wavelengths that is attributed to increased probability of the internal photoemission process. We found the responsivity of the nanodetector to be 0.25 and 13.3 mA/W for incident optical wavelengths of 1.55 and 1.31 μm, respectively. The presented device can be integrated with other nanophotonic and nanoplasmonic structures for the realization of monolithic opto-electronic circuitry on-chip. © 2011 American Chemical Society.

A role of monitoring to reduce the uncertainty in the performance of pile foundations

In typical conventional foundation design, the inherent variability of soil properties, model uncertainty and construction variability are not modeled explicitly. A main drawback of this is that the effect of each variability on the probability of an unfavorable event cannot be evaluated quantitatively. In this paper, a method to evaluate the uncertainty-reduction effect on the performance of a vertically-loaded pile foundation by monitoring the pile performance (such as pile load testing or placing sensors in piles) is proposed. The effectiveness of the proposed method is examined based on the investigation of a 120-pile foundation placed on three different ground profiles. The computed results show the capability of evaluating the uncertainty-reduction effect on the performance of a pile foundation by monitoring. © 2014 Taylor & Francis Group, London.

Single camera pose estimation using Bayesian filtering and Kinect motion priors

Traditional approaches to upper body pose estimation using monocular vision rely on complex body models and a large variety of geometric constraints. We argue that this is not ideal and somewhat inelegant as it results in large processing burdens, and instead attempt to incorporate these constraints through priors obtained directly from training data. A prior distribution covering the probability of a human pose occurring is used to incorporate likely human poses. This distribution is obtained offline, by fitting a Gaussian mixture model to a large dataset of recorded human body poses, tracked using a Kinect sensor. We combine this prior information with a random walk transition model to obtain an upper body model, suitable for use within a recursive Bayesian filtering framework. Our model can be viewed as a mixture of discrete Ornstein-Uhlenbeck processes, in that states behave as random walks, but drift towards a set of typically observed poses. This model is combined with measurements of the human head and hand positions, using recursive Bayesian estimation to incorporate temporal information. Measurements are obtained using face detection and a simple skin colour hand detector, trained using the detected face. The suggested model is designed with analytical tractability in mind and we show that the pose tracking can be Rao-Blackwellised using the mixture Kalman filter, allowing for computational efficiency while still incorporating bio-mechanical properties of the upper body. In addition, the use of the proposed upper body model allows reliable three-dimensional pose estimates to be obtained indirectly for a number of joints that are often difficult to detect using traditional object recognition strategies. Comparisons with Kinect sensor results and the state of the art in 2D pose estimation highlight the efficacy of the proposed approach.