Domain Adaptation for Neural Networks by Parameter Augmentation

We propose a simple domain adaptation method for neural networks in a supervised setting. Supervised domain adaptation is a way of improving the generalization performance on the target domain by using the source domain dataset, assuming that both of the datasets are labeled. Recently, recurrent neural networks have been shown to be successful on a variety of NLP tasks such as caption generation; however, the existing domain adaptation techniques are limited to (1) tune the model parameters by the target dataset after the training by the source dataset, or (2) design the network to have dual output, one for the source domain and the other for the target domain. Reformulating the idea of the domain adaptation technique proposed by Daume (2007), we propose a simple domain adaptation method, which can be applied to neural networks trained with a cross-entropy loss. On captioning datasets, we show performance improvements over other domain adaptation methods.Comment: 9 page. To appear in the first ACL Workshop on Representation Learning for NL

Phase-resolved Spin-Wave Tomography

The propagation dynamics of spin waves are represented by their dispersion relations. Recently, we have developed a method, called spin-wave tomography (SWaT), to obtain dispersion relation of spin waves in the long wavelength regime, so-called pure magnetostatic waves. In our previous studies on SWaT, phase information of spin waves was disregarded. In this report, we demonstrate an advanced SWaT analysis, called phase-resolved spin-wave tomography (PSWaT), to realize the direct observation of the amplitude and the phase of spin waves. The PSWaT spectra are obtained by separating the real and the imaginary components of the complex Fourier transform in the SWaT analysis. We demonstrate the PSWaT spectra of spin waves excited by the photo-induced demagnetization in a Bi-doped garnet film, reflecting the characteristic features of the complex dynamical susceptibility affected by magnetostatic coupling in the film.Comment: 5 pages, 4 figure

Is Individual Environmental Consciousness One of the Determinants in Transport Mode Choice?

This paper models a transport negative impact on environment as one of attributes of the transport mode. By this modeling, we are able to examine whether individual environmental consciousness has a significant effect on his/her choice of transport mode. A survey data from Saito and Onohara Area in Northern Osaka of Japan is used to estimate the model specified by Heteroscedastic Extreme Value (HEV). Both of the estimated and simulated results imply that individual environmental consciousness does influence his/her decision on transport mode choice. Furthermore, the likelihood ratio tests suggest that both the utility and scale parameters are not equal across sub-samples of university commuters, research-facility commuters, and residents. The details of the comparison across sub-samples suggest that we may learn more from subdividing a whole sample into several sub-samples if we could select them based on their characteristics.Environmental consciousness; Transport mode choice; Stated choice experiment; Heteroscedastic Extreme Value (HEV) model; Value of time saving (VOTS)

Characteristics of vancomycin-resistant enterococci (VRE) isolated from medical fields in Japan

学位記番号：医博甲169

Frequency and wavenumber selective excitation of spin waves through coherent energy transfer from elastic waves

Using spin-wave tomography (SWaT), we have investigated the excitation and the propagation dynamics of optically-excited magnetoelastic waves, i.e. hybridized modes of spin waves and elastic waves, in a garnet film. By using time-resolved SWaT, we reveal the excitation dynamics of magnetoelastic waves through coherent-energy transfer between optically-excited pure-elastic waves and spin waves via magnetoelastic coupling. This process realizes frequency and wavenumber selective excitation of spin waves at the crossing of the dispersion relations of spin waves and elastic waves. Finally, we demonstrate that the excitation mechanism of the optically-excited pure-elastic waves, which are the source of the observed magnetoelastic waves, is dissipative in nature.Comment: 5 pages, 4 figure

Cost Benefit Analysis on Public Transport Investment by Choice Experiment Method: An Example of Osaka Monorail Saito Linefs Extension (in Japanese)

The necessity of applying Cost Benefit Analysis (CBA) in evaluating the validity of a public transport investment is well recognized by policy makers in recent days. Originating in a sense of this fact, we implement CBA in a new project called Osaka Monorail Saito Linefs extension by applying a Choice Experiment (CE) method. It is estimated that the benefit cost (B/C) ratio is 1.87 under a basic scenario. In addition, with a consideration on different kinds of uncertainty in the future, a number of sensitivity analyses are implemented. The results of sensitivity analysis indicate that the possibility of generating net benefit is extremely high for the project studied here.Cost Benefit Analysis, Choice Experiment (CE) method, Monorail, Sensitive Analysis

180-degree phase shift of magnetoelastic waves observed by phase-resolved spin-wave tomography

We have investigated optically-excited magnetoelastic waves by phase-resolved spin-wave tomography (PSWaT). PSWaT reconstructs dispersion relation of spin waves together with their phase information by using time-resolved magneto-optical imaging for spin-wave propagation followed by an analysis based on the convolution theorem and a complex Fourier transform. In PSWaT spectra for a Bi-doped garnet film, we found a 180 degree phase shift of magnetoelastic waves at around the crossing of the dispersion relations of spin and elastic waves. The result is explained by a coupling between spin waves and elastic waves through magnetoelastic interaction. We also propose an efficient way for phase manipulation of magnetoelastic waves by rotating the orientation of magnetization less than 10 degree.Comment: 5 pages, 4 figure