Robust Activity Recognition for Aging Society

Human activity recognition (HAR) is widely applied to many industrial applications. In the context of Industry 4.0, driven by the same demand of machines\u27 self-organizing ability, HAR can also be adopted in elderly healthcare. However, HAR should be adaptive to the application scenarios in elderly healthcare. In this paper, we propose a nonintrusive activity recognition method that can be applied to long-term and unobtrusive monitoring for elderlies. The method is robust to obstruction and nontarget object interference. Skeleton sequence is estimated from RGB images. Based on two activity continuity metrics, an interframe matching algorithm is proposed to filter nontarget objects. In order to make full use of spatial-temporal information, we propose a novel activity encoding method based on the interframe joints distances. A convolutional neural network is used to learn the distinguishing features automatically. A specific data augmentation method is designed to avoid the overfitting problem on small-scale datasets. The experiments are performed on two public activity datasets and a newly released noisy activity dataset (NAD). The NAD contains obstruction, nontarget object interference. The experimental results show that the proposed method achieves the state-of-the-art performance while only using one ordinary camera. The proposed method is robust to a realistic environment

Missing one-loop contributions in secondary gravitational waves

We find several missing one-loop-order contributions in previous considerations about secondary gravitational waves induced at nonlinear order in cosmological perturbations. We consider a consistent perturbative expansion to third-order in cosmological perturbations, including higher-order interactions and iterative solutions ignored in the previous literature. Tensor fluctuations induced by the source with two scalar and one tensor perturbations are correlated with the first-order tensor fluctuation and thus give a one-loop-order correction to the tensor power spectrum. The missing loop correction is \textit{scale-invariant} and \textit{negative} in the superhorion region, which secondarily reduces the initial primordial tensor power spectrum prior to the horizon re-entry. Such an IR behavior is very different from the auto-spectrum of second-order induced tensor modes discussed in the previous literature and can be important for the actual gravitational wave measurements. For a sharp peak of scalar fluctuations with $A_\zeta=10^{-2}$ at $k_*=10^{5}h/{\rm Mpc}$ motivated by the LIGO/Virgo events, we show that the tensor power spectrum at the cosmic microwave background scale reduces by at most 35%. Hence, the polarization B-mode might not be seen because of the reduction of the original tensor spectrum due to the secondary effect of primordial black hole formation.Comment: 13 pages, 6 figure

Predicting Transportation Carbon Emission with Urban Big Data

Transportation carbon emission is a significant contributor to the increase of greenhouse gases, which directly threatens the change of climate and human health. Under the pressure of the environment, it is very important to master the information of transportation carbon emission in real time. In the traditional way, we get the information of the transportation carbon emission by calculating the combustion of fossil fuel in the transportation sector. However, it is very difficult to obtain the real-time and accurate fossil fuel combustion in the transportation field. In this paper, we predict the real-time and fine-grained transportation carbon emission information in the whole city, based on the spatio-temporal datasets we observed in the city, that is taxi GPS data, transportation carbon emission data, road networks, points of interests (POIs), and meteorological data. We propose a three-layer perceptron neural network (3-layerPNN) to learn the characteristics of collected data and infer the transportation carbon emission. We evaluate our method with extensive experiments based on five real data sources obtained in Zhuhai, China. The results show that our method has advantages over the well-known three machine learning methods (Gaussian Naive Bayes, Linear Regression, and Logistic Regression) and two deep learning methods (Stacked Denoising Autoencoder and Deep Belief Networks)

Tactile-Filter: Interactive Tactile Perception for Part Mating

Humans rely on touch and tactile sensing for a lot of dexterous manipulation tasks. Our tactile sensing provides us with a lot of information regarding contact formations as well as geometric information about objects during any interaction. With this motivation, vision-based tactile sensors are being widely used for various robotic perception and control tasks. In this paper, we present a method for interactive perception using vision-based tactile sensors for a part mating task, where a robot can use tactile sensors and a feedback mechanism using a particle filter to incrementally improve its estimate of objects (pegs and holes) that fit together. To do this, we first train a deep neural network that makes use of tactile images to predict the probabilistic correspondence between arbitrarily shaped objects that fit together. The trained model is used to design a particle filter which is used twofold. First, given one partial (or non-unique) observation of the hole, it incrementally improves the estimate of the correct peg by sampling more tactile observations. Second, it selects the next action for the robot to sample the next touch (and thus image) which results in maximum uncertainty reduction to minimize the number of interactions during the perception task. We evaluate our method on several part-mating tasks with novel objects using a robot equipped with a vision-based tactile sensor. We also show the efficiency of the proposed action selection method against a naive method. See supplementary video at https://www.youtube.com/watch?v=jMVBg_e3gLw .Comment: Accepted at RSS202

Search for the warm-hot intergalactic medium around A 2744 using Suzaku

We present the results from Suzaku satellite observations of the surrounding region of a galaxy cluster, A 2744, at z = 0.3. To search for oxygen emission lines from the warm-hot intergalactic medium (WHIM), we analyzed X-ray spectra from two northeastern regions 2.2-3.3 and 3.3-4.4 Mpc from the center of the cluster, which offers the first test on the presence of a WHIM near the typical accretion shock radius (similar to 2 r(200)) predicted by hydrodynamical simulations. For the 2.2-3.3 Mpc region, the spectral fit significantly (99.2% significance) improved when we included O-VII and O-VIII lines in the spectralmodel. A comparable WHIM surface brightness was obtained in the 3.3-4.4 Mpc region and the redshift of the O-VIII line is consistent with z=0.3 with in errors. The present results support that the observed soft X-ray emission originated from the WHIM. However, considering both statistical and systematic uncertainties, OVIII detection in the northeast regions was marginal. The surface brightnesses of the O-VIII line in 10(-7) photons cm(-2) s(-1) arcmin(-2) for the 2.2-3.3 and 3.3-4.4 Mpc regions were measured to be 2.7 +/- 1.0 and 2.1 +/- 1.2, giving upper limits on the baryon overdensity of delta = 319(<442) and 284(<446), respectively. This is comparable with previous observations of cluster outskirts and their theoretical predictions. The future prospect for WHIM detection using the Athena X-IFU micro-calorimeter is briefly discussed here. In addition, we also derived the intracluster medium temperature distribution of A 2744 to detect a clear discontinuity at the location of the radio relic. This suggests that the cluster has undergone strong shock heating by mass accretion along the filament.Peer reviewe

Slip rates on the Chelungpu and Chushiang thrust faults inferred from a deformed strath terrace along the Dungpuna river, west central Taiwan

The Chelungpu fault produced the September 1999 M_w = 7.6 Chi-Chi earthquake, central Taiwan. The shortening rate accommodated by this structure, integrated over several seismic cycles, and its contribution to crustal shortening across the Taiwanese range have remained unresolved. To address the issues, we focus our study on the Chelungpu and Chushiang thrust faults within the southernmost portion of the Chi-Chi rupture area. Structural measurements and available seismic profiles are used to infer the subsurface geometry of structures. The Chushiang and Chelungpu faults appear as two splay faults branching onto a common ramp that further north connects only to the Chelungpu surface trace. We survey a deformed strath terrace along the Dungpuna river, buried under a 11,540 ± 309 years old fill deposit. Given this age, the dip angles of the faults, and the vertical throw determined from the offset of the strath terrace across the surface fault traces, we estimate slip rates of 12.9 ± 4.8 and 2.9 ± 1.6 mm/yr on the Chelungpu and Chushiang faults, respectively. These yield a total shortening rate of 15.8 ± 5.1 mm/yr to be absorbed on their common decollement at depth. This total value is an upper bound for the slip rate on the Chelungpu fault further north, where the Chushiang fault disappears and transfers shortening to adjacent faults. Combining these results with the recently constrained shortening rate on the Changhua blind thrust reveals that all these frontal faults presently absorb most of the long-term horizontal shortening across the Taiwanese range. They thus stand as the major sources of seismic hazards in this heavily populated area. The return period of earthquakes similar to the Chi-Chi event over a ∼80 km long stretch of the Western Foothills is estimated to be ~64 years. This value is an underestimate because it assumes that all the faults locked during the interseismic period slip only during such large events. Comparison with historical seismicity suggests that episodic aseismic deformation might also play a major role in accommodating shortening

ロジウム触媒を用いるアレン-アルキンの新規環構築反応

13301甲第4188号博士（創薬科学）金沢大学博士論文要旨Abstrac

ロジウム触媒を用いるアレン-アルキンの新規環構築反応

13301甲第4188号博士（創薬科学）金沢大学博士論文本文Ful

Ground state of a polydisperse electrorheological solid: Beyond the dipole approximation

The ground state of an electrorheological (ER) fluid has been studied based on our recently proposed dipole-induced dipole (DID) model. We obtained an analytic expression of the interaction between chains of particles which are of the same or different dielectric constants. The effects of dielectric constants on the structure formation in monodisperse and polydisperse electrorheological fluids are studied in a wide range of dielectric contrasts between the particles and the base fluid. Our results showed that the established body-centered tetragonal ground state in monodisperse ER fluids may become unstable due to a polydispersity in the particle dielectric constants. While our results agree with that of the fully multipole theory, the DID model is much simpler, which offers a basis for computer simulations in polydisperse ER fluids.Comment: Accepted for publications by Phys. Rev.