Communication without words

Technological innovations to assess and include the human dimension in the building-performance loop: A review

Statistical analysis and control of dynamic systems

We show that the seismicity rate increase in the Kanto region around Tokyo following the 2011 Tohoku-Oki earthquake (M w9.0) was well correlated with the static increases in the Coulomb failure function ( ∆CFF) transferred from the Tohoku-Oki earthquake sequence. Because earthquakes in the Kanto region exhibit various focal mechanisms, the receiver faults for the ∆CFF were assumed to be reliable focal mechanism solutions of ̃3,000 earthquakes compiled from three networks (F-net, JMA network, and MeSO-net). The histograms of ∆CFF showed that more events in the postseismic period had positive ∆CFF values than those in the preseismic period (2008 April 1 2011 March 10). Among the 928 receiver faults showing the significant ∆CFF with absolute values≥ 0.1 bars in the preseismic period, 717 receiver faults (77.3 %) indicated positive ∆CFF. On the contrary, 1,334 (88.2 %) out of 1,513 receiver faults indicated positive ∆CFF in the postseismic period. We confirmed that the result is similar for the longer preseismic period, between 1997 October 1 and 2011 March 10. To test the significance of the difference in the distribution of ∆CFF between preseismic and postseismic periods, we used a Monte Carlo method with bootstrap resampling. As a result, the ratio of positive ∆CFF randomly resampled from∆CFF values in the preseismic period never exceeded 83.1%, even after 10,000 iterations. This supports the findings of Toda & Stein [2013]; however, our calculation is more reliable than theirs because we used a much larger number of focal mechanisms compiled from the three networks. It also proves that the static stress changes transferred from the Tohoku-Oki earthquake sequence are responsible for the changes in the seismicity rate in the Kanto region. Earthquakes of focal mechanisms with positive ∆CFF values drastically increased, while those with negative ∆CFFs showed no obvious changes except for immediately after the mainshock. This fault-dependent seismicity rate change strongly supports the contribution of the Coulomb stress transferred from the Tohoku-Oki sequence to the seismicity rate change in the Kanto region. Immediately following the mainshock, earthquakes of all types of focal mechanisms were activated, but the increased seismicity rate of earthquakes with negative ∆CFFs returned to the background level within a few months. This suggests that there might be other contributing factors to the seismicity rate change such as dynamic stress triggering or pore-fluid pressure changes.

Correlation between Coulomb stress imparted by the 2011 Tohoku-Oki earthquake and seismicity rate change in Kanto, Japan

Anomaly detection in home power monitoring can be categorized into two main types: detection of electrical theft, leakage, or nontechnical loss and monitoring anomalies in the daily activities of residents. Focusing on the application and practicality of anomaly detection, we propose sample efficient home power anomaly detection (SEPAD) with improved monitoring performance in terms of electricity usage as well as changes in the daily living activities of residents via provision of detailed feedback. SEPAD consists of two classifiers: an appliance pattern matching classifier (APMC) and an energy consumption habit classifier (ECHC). The APMC uses a single-source separation framework based on a semi-supervised support vector machine (semi-SVM) model. This semi-supervised learning method requires only a small amount of labeled data to achieve high accuracy in near real time and is a sample efficient detection method. The hidden Markov model (HMM)-based ECHC improves the rationality of SEPAD by providing anomaly detection functionality with respect to the daily activities of householders, especially the elderly and residents in developing areas. When SEPAD detects the appearance of an unknown pattern or known patterns contrary to the household’s electricity usage habits, it triggers an alarm. SEPAD was applied to monitor power consumption data from Mkalama, a rural area in Tanzania with 52 households containing nearly 150 occupants connected to a solar powered off-grid network. The results of the practical test demonstrate the high accuracy and practicality of the proposed method.

Sample Efficient Home Power Anomaly Detection in Real Time Using Semi-Supervised Learning

A system for providing music employing electroencephalography for music therapy is described. Music therapy for the treatment of patients suffering mental illness has been attempted over a period of 20 years. To reduce stress, it is preferable to listen to music that matches a person’s emotions. However, it is difficult to know exactly the person’s emotion. It is necessary to calibrate the proposed system employing electroencephalography to emotions. We discuss a method of calibration especially used in canonical correlation analysis. Experimental results show that it is possible to roughly estimate feelings. We consider that it is possible to use our system in practice.

/pdf/estimation-of-emotion-by-electroencephalography-for-music-1hd8aodwze.pdf

Estimation of emotion by electroencephalography for music therapy

This paper proposes a method for removing image inconsistencies which occur by an existence of moving objects or a change of illumination condition when an omnidirectional image database is generated. The database is used for archiving an outdoor scene in wide areas or generating novel view images with an image-based rendering approach. In related work, it is difficult to remove moving objects in an outdoor environment where illumination condition drastically changes, and to remove inconsistencies of color tone of images which included moving objects. The proposed method iterates the two processes which are the estimation of candidate region of moving objects and the achievement of color consistency to split regions. The color consistency is achieved by estimating linear color transformation parameters which change a histogram of an input image to that of the standard image.

http://yokoya.naist.jp/paper/datas/1185/accv2010submission.pdf

Removal of moving objects and inconsistencies in color tone for an omnidirectional image database

Emotion Transmission Using LED Embedded in Cellular-phone Type Teleoperated Communication Robot

The analysis of the movement of people in a shopping area with the aim of improving marketing is an important research topic Many conventional methods are dependent on the density of people in the area, which is easily estimated by counting the people entering or exiting the area However, a high density does not always mean an increase in activity, as certain people are simply passing the area at a given time The primary goal of this study was to introduce a set of indicators for measuring the bustle of the area, which we call “Nigiwai,” from pedestrian movement by using an analogy from classical kinematics Such indicators can be used to measure the impact of promotional events and to optimize the design of the area Our novel indicators were evaluated with simulated pedestrian scenarios and were demonstrated to distinguish shopping scenarios from those in which people move around without shopping successfully, even when the latter scenarios had much higher densities The indicators were computed solely from the pedestrian trajectory, which can easily be obtained from ordinary sensors using deep learning-based techniques As a demonstration with real data, we applied our method to a video of a street and provided a visualization of the indicators

/pdf/measuring-nigiwai-from-pedestrian-movement-3egmozg0u1.pdf

Maiya Hori

Papers

Estimation of emotion by electroencephalography for music therapy

Removal of moving objects and inconsistencies in color tone for an omnidirectional image database

Emotion Transmission Using LED Embedded in Cellular-phone Type Teleoperated Communication Robot

Measuring “Nigiwai” From Pedestrian Movement

Tracking people with active cameras using variable time-step decisions