Maiya Hori

Bio: Maiya Hori is an academic researcher from Kyushu University. The author has contributed to research in topics: Facial expression & Rendering (computer graphics). The author has an hindex of 4, co-authored 35 publications receiving 81 citations. Previous affiliations of Maiya Hori include Nara Institute of Science and Technology & Tottori University.

Expression transmission using exaggerated animation for Elfoid

Abstract: We propose an expression transmission system using a cellular-phone-type teleoperated robot called Elfoid. Elfoid has a soft exterior that provides the look and feel of human skin, and is designed to transmit the speaker's presence to their communication partner using a camera and microphone. To transmit the speaker's presence, Elfoid sends not only the voice of the speaker but also the facial expression captured by the camera. In this research, facial expressions are recognized using a machine learning technique. Elfoid cannot, however, display facial expressions because of its compactness and a lack of sufficiently small actuator motors. To overcome this problem, facial expressions are displayed using Elfoid's head-mounted mobile projector. In an experiment, we built a prototype system and experimentally evaluated it's subjective usability.

Deep learning-based prediction method for people flows and their anomalies

Abstract: This paper proposes prediction methods for people flows and anomalies in people flows on a university campus. The proposed methods are based on deep learning frameworks. By predicting the statistics of people flow conditions on a university campus, it becomes possible to create applications that predict future crowded places and the time when congestion will disappear. Our prediction methods will be useful for developing applications for solving problems in cities.

Generation of facial expression for communication using elfoid with projector

Abstract: We propose a method for generating facial expressions with a mobile projector built into a cellphone-type tele-operated android, called Elfoid. Elfoid is designed to transmit the presence of a speaker to a communication partner in a remote place using a camera and microphone and a soft exterior that provides the look and feel of human skin. To transmit the presence of a speaker, Elfoid sends not only voice but also facial expressions and emotion information captured by the camera and microphone. Elfoid cannot, however, display facial motions because of its compactness and the lack of sufficiently small actuator motors. Therefore, we use a mobile projector and generate projection patterns to represent facial expressions estimated with a camera.

Energy Management of Microgrid Considering Demand Response Using Honey Badger Optimizer

Abstract: Recently, Microgrids (MGs) have received great attention for solving power system problems, due to their low environmental effects and their economic benefits. This paper proposes a new application of an effective metaheuristic optimization method, namely, Honey Badger Algorithm (HBA), to solve energy management for optimal dispatch of the gridconnected MG incorporating Demand Response programs (DRP). Honey badger algorithm is used to solve an incentive DRP, with the aim of minimizing the total cost, which includes conventional generators fuel cost and the cost of power transaction with the main grid considering the load demand. In this paper, two case studies are conducted using HBA and simulation results are compared with those obtained by other algorithms (particle swarm optimization and JAYA algorithm). First case consists of three diesel generators, a PV generator and a wind generator. To prove the scalability of the HBA, the second case, which is much larger, is tested. Simulation results for both case studies obtained by PSO, JAYA, and HBA are deeply discussed. The results show the HBA's effectiveness in solving the energy management with DR problem for MG compared with other well-known optimization techniques.

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

Abstract: 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.

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

Abstract: 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.