Reviewerly/exHarmony huggingface dataset:
Gesture Recognition Using IMU Sensor Attached to Hand and Deep Learning

A program was developed to recognize the movement of a hand using IMU (Inertial Measurement Unit) sensor, which is also used by smartphones. A sensor module was made by connecting the IMU sensor with a pressure sensor. Then, in order to obtain an accurate recognition rate with CNN (Convolutional Neural Network), a signal image was made from the gesture signal data collected using the IMU sensor attached to the hand. The neural network model was trained with multiple gestures including handwaving, beckon, circular motions. The optimization process resulted a high test-accuracy of 97%. Furthermore, the program was also tested to recognize gestures in real-time by utilizing the pressure sensor as a switch. The experimental results confirmed that hand gestures can be recognized with excellent accuracy.
Visual Imitation with Reinforcement Learning using Recurrent Siamese Networks

It would be desirable for a reinforcement learning (RL) based agent to learn behaviour by merely watching a demonstration. However, defining rewards that facilitate this goal within the RL paradigm remains a challenge. Here we address this problem with Siamese networks, trained to compute distances between observed behaviours and an agent's behaviours. We use an RNN-based comparator model to learn such distances in space and time between motion clips while training an RL policy to minimize this distance. Through experimentation, we have also found that the inclusion of multi-task data and an additional image encoding loss helps enforce temporal consistency and improve policy learning. These two components appear to balance reward for matching a specific instance of a behaviour versus that behaviour in general. Furthermore, we focus here on a particularly challenging form of this problem where only a single demonstration is provided for a given task -- the one-shot learning setting. We demonstrate our approach on humanoid, dog and raptor agents in 2D and a 3D quadruped and humanoid. In these environments, we show that our method outperforms the state-of-the-art, GAIfO (i.e. GAIL without access to actions) and TCNs.
Self-weighted locality discriminative feature selection

Linear discriminant analysis (LDA) is one of the most popular methods for dimensionality reduction, and there have many different variants based on LDA. However, conventional LDA have some drawbacks: 1) The projection matrix offers the disadvantage of interpretability; 2) LDA assumes that every class data are drawn from Gaussian distribution which may not be applicable to many real-world data. Aiming to solve these problems, we propose a robust feature selection method, namely <i>Self-weighted Locality Discriminative Feature Selection</i> (SLD-FS), by combining row sparsity<i> l</i><sub>2,1</sub>-norm regularization and self-weighted locality discriminant analysis strategy. Additionally, an effective iterative algorithm is developed to optimise this objective function, and the algorithm is proved to convergence. Extensive experiments conducted on various data sets demonstrate the effectiveness of SLD-FS when compared with some state-of-the-art supervised feature selection methods.
Development of Violin-playing Robot

We are developing a violin-playing robot which can communicate with human through playing the violin expressively. In this paper, we focus on “vibrato”, which is one of the most popular technique for playing the violin. In order to reveal the sound characteristics of vibrato, we conducted experiments with three trained violinists, in which, we asked them to play the sound of D5 with vibrato and analyzed the sound with FFT. Also, we recorded the sound of a short famous musical piece in three conditions. As a result of the sound analysis, we found that the values of the frequency fluctuation in vibrato vary from 2 Hz to 6 Hz. Then we analyzed their playing based on a questionnaire, and we found 5 patterns on musical notes to which the vibrato should be applied.
Efficient job scheduling algorithm based on weighted average priority in cloud computing

In cloud computing, the issue of the scheduling of job is the greatest and testing issue. There are numerous algorithms for scheduling available that are utilized in the environment of cloud computing for better resource scheduling. Scheduling is assigning fundamentally number of resources to the tasks in a manner that there will be maximum utilization of resource, minimum time for total processing and minimum time of waiting. The basic aim of this paper is to study and analyze the various scheduling algorithms in cloud computing, to develop an improved task scheduling using QoS parameters of Virtual machines and priorities of the task based on the deadline, to compare the results of the proposed scheduling technique with the existing multi-objective task Scheduling technique. The proposed methodology is implemented with the help of Cloudsim and NetbeansIDE8.0. CloudSim is the library that provides the simulation environment of cloud computing and also provides primary classes describing virtual machines, data centers, users and applications.
Update of Human Frequency Map by Networked Multiple Mobile Robots

Currently, many of mobile robots are stand-alone. The robots acquire and utilize sensor data and map information by themselves. Sharing of sensor data and map information by networked multiple robots will be efficient for recognition and decision making in large scale environments. This paper introduces a map sharing system based on block chain for mobile robots. In the proposed system, multiple robots share Human Frequency Maps which include human existence frequency in each grid of the maps human. Especially, this paper focuses on updating Human Frequency Maps based by multiple mobile robots. We developed a simulator for map sharing and updating. As a result of simulation, map sharing and updating can be achieved, based on evaluating observation number and distance to each grid.
Development of novel robot mechanisms to realize exaggerated motions abstracted from a Japanese Bunraku puppet

Japanese “Bunraku” puppets have attracted people by showing their impressive and emotional action, even though the structures and motions are different from human beings. The exaggerating and omission of motions, which include expansion and contraction, and high frequency shakings of the body, are effectively utilized to express humanistic emotions. This paper proposes novel robot mechanisms to reproduce functions and motions of Bunraku puppets by extracting the mechanism of a Bunraku puppet. The proposed configuration of the robot has capability of expanding and contracting of its neck and chest. The shoulders, arms and hands are mounted on the both sides of the waist, which mimics the Bunraku puppeteers to realize expansion and contraction of both arms, and at the same time it contributes to drastically reduce the weight of upper body to realize high frequency shaking. Translate motion of the shoulder, which independently moves from the neck, realizes much emotional action.
Development of image processing system to learn by deep learning

Deep learning has been widely used and studied on natural language explanation generation, question and answer, image recognition, and the like are currently undertaken. Therefore, we will develop a system using deep learning so that students can easily handle image recognition.
A Study on Optimal Path Planning for Autonomous Driving Vehicle with Speed Change

There are many path planning methods using geometric curves as a reference path. It is important to construct smooth reference path because the efficiency and ride comfort of the vehicle depend on the smoothness of the reference path. Moreover, in the case where the vehicle speed is changed, we should consider the fact that the faster the vehicle speed is, the more effort is required to follow the reference path. Hence we use the kinematic model of vehicle to construct the path for considering speed change of vehicle. We propose the method to generate the optimal path minimizing the square sum of the vehicle lateral acceleration. The optimal paths can be easily obtained because the optimal control problem is reduced by the change of the independent variable and normalization. Additionally, the optimal paths can be summarized in some figures or so called field of extremals.
TEI Models for the Publication of Social Sciences and Humanities Journals: Opportunities, Challenges, and First Steps Toward a Standardized Workflow

The TEI Guidelines are developed and curated by a community whose main purpose is to standardize the encoding of primary sources relevant for humanities research and teaching. But other communities are also working with TEI-based publication formats. The first goal of this paper is to raise awareness of the importance of TEI-based scholarly publishing as we know it today. The second goal is to contribute to a reflection on the development of a TEI customization that would cover the whole authoring-reviewing-publishing workflow and guarantee archiving options that are as solid for journal publications as what we now have for primary sources published in TEI.
Human Assistance Method by Connecting Two-Dimensionally Walking Condition Map to Emotion Map

This paper aims to explore the relationship between walking and emotion. We employed the two-dimension walking condition map and two-dimension emotion map to confirm their tendency and relation. According to the individual differences, we propose the personal walking ideal-line on the walking condition map. Then, we conduct the experiment by shifting the position on the personal walking ideal-line on walking condition map to stimulate the subject’s emotion. We thus can confirm the tendency and relation for connecting the walking and emotion. To valid use this tendency, we proposed to use it in the assistive engineering. As the results, we recommend patient should walk on their own personal walking-ideal-line, they can freely control the emotion by changing walking pattern. In conclusion, this method can be applied for various assistance devices to keep the motivation until they recover.
Verification of collision avoidance method for multiple quadrotors using buffered Voronoi cells

In this paper, we assume a situation that multiple quadrotors are flying autonomously in the same space for the purpose of aerial photographing, surveillance, or home delivery and so on. In such a situation, an algorithm to avoid mutual collision is needed. D. Zhou et al. proposed an algorithm based on the Buffered Voronoi Cells (BVC) to reach each target position without mutual collision when the multiple quadrotors fly and confirmed its operation by some simulations. In this research, we applied the method based on BVC to the different number of quadrotors from the verification by D. Zhou et al. and verified the performance of it by numerical simulations using MATLAB. In addition, we confirmed the algorithm by a dynamic simulation with four quadrotors using the dynamic simulator V-REP.
Systematic mapping study of economic and business models of cloud services

&lt;p&gt;&lt;span&gt;Cloud computing is a business paradigm wherein computers and computing related services are provided by Cloud Service Providers to consumers either as software, development platform, or infrastructure. From an economic and business perspective, Cloud services involve cost, ownership quality of service and service level agreements. There are studies on economic and business models of cloud services on the cloud landscape especially in the area of pricing. Despite this, there is still a dearth of papers in this area of study. The objective of this study is to conduct a systematic mapping study to collect all relevant research on economic and business models of Cloud services. A systematic map provides a structured overview in a particular research area. The representation of the mapping process offers unique course-grained overview of the results. The results are presented in terms of research such as evaluation and solution, and contribution such as tools and method utilized. The results showed that there are more publications on pricing models in relation to tools with 6.87% and model with 14.5%, more publications on economic and business implications in terms of method with 11.45%, more publications on Cloud market in term of processes with 6.87%, more papers on security in the area of evaluation with 8.55% and validation research with 6.58%, and more papers on Cloud markets with respect to experience with 4.61% and validation with 5.92%. The research gaps identified in this study should motivate researchers to carry out more mapping studies in the field.&lt;/span&gt;&lt;/p&gt;
Anomalous Ozone Measurements Detection Using Unsupervised Machine Learning Methods

Air Quality has become a major area of concern in today's world due to the industries and heavy traffic in urban environments. It is also important to analyze the reason behind the degradation of Air quality to curb further damage and provide appropriate remedial measures. In this context, this paper studies different Machine learning methods to detect Anomalous Ozone Measurements in Air Quality data. The comparative study done using unsupervised Machine learning approaches-One Class Support Vector Machine and Isolation Forests showed that Isolation Forests performed better than One- Class Support Vector Machine. Also, these predicted anomalies were tested for a faulty sensor using Z-Score. Isolation Forest was the most effective in finding anomalies in Ozone measurements from Air Quality sensor data, as compared to One Class Support Vector Machine with an accuracy of 92.7%.
RRT Path Planning Method with Spatial Recognition of 3D Camera to Manipulator

The problem of the manipulator avoiding interference with obstacles in the work environment and planning a safe route is one of the big problems in robotics automation. As one of route planning with obstacle avoidance, RRT aims at speeding up the calculation by using random sampling. RRT has the advantage of high obstacle avoidance capability. In recent years, researches on a robot vision system combining robot and vision progressed. In the obstacle avoidance route plan, information on the obstacle position from a camera has advantages such as easy calculation. The purpose of this research is to calculate the position of an obstacle necessary for route planning using a 3D camera and propose a method in which the manipulator moves to the target position while avoiding the obstacle by the improved RRT route planning method.
Semantic 3D gaze mapping toward comprehending attention of multiple people

Gaze information conveys what the people are interested in, and it is expected that the analysis of the point-of-gaze can be used for marketing research. However, the point-of-gaze is computed on a screen, and it is difficult to estimate the 3D point-of-gaze in the world-coordinate system for gaze data of multiple people. Therefore, we propose a method for estimating the 3D point-of-gaze using structure from motion. The semantic 3D map is reconstructed using a semantic segmentation and keyframes selected from scene images. Additionally, the 3D point-of-gaze can be also estimated on the 3D map without prior information.
Soundness Visualization System for Equipment of Nuclear Power Plant

For the safety enhancement of the nuclear power plant, the safety equipment is constructing additionally under the new regulatory requirements. With the increase of safety equipment, the amount of inspection during the outage may increase. Accordingly, increase of the outage lead to prolong maintenance schedule period. To perform the outage efficiently, we developed health visualization system for the equipment while operations. The health visualization system consists of database, health diagnosis engine and visualization engine. In this health diagnosis engine, the diagnosis technique that integrated a statistical model, which can detect the change of the process value early, with a physical model, which can identify equipment, the parts and phenomenon, was applied. With a constant monitoring of the process value, it is possible to estimate the phenomenon and equipment immediately when the process value shows different behavior than usual. Besides, by understanding that the equipment is healthy while operations, it is possible to optimize the amount of inspected equipment in the outage.
Cross-ratio based gaze estimation using display light reflections on cornea detected by polarization camera system

Cross-ratio method can estimate point-of-gaze on a screen without performing a hardware calibration, and it has a tolerance of the head movement. However, this method requires the display, which near-infrared light-emitting-diodes are attached on, to detect screen corners. Therefore, we developed a polarization camera system to detect screen reflection on cornea without near-infrared-light emission. Most of the liquid crystal display has an internal polarizing filter, and thus, the transmitted light can be controlled by the external polarizing filter. We performed the evaluation experiment of cross-ratio based gaze estimation using display corner detection from polarized images.
Study of wheelchair platooning using robot with two independent driving wheels

In Japan, the burden on wheelchair users and carers is getting bigger due to the lack of manpower of medical and welfare services accompanying the declining birthrate and aging population. Also, people who can not move the wheelchair by themselves will have a greater stress due to being unable to go out alone. This research aims to solve the burden on people who move wheelchairs and to eliminate manual labor shortage in nursing care facilities, research on wheelchair autopilot and row running. Report on the results of automatic follow-up experiment using a two-wheel independently driven robot, which is the foundation.
Mobile Robot Localization Considering Attributes of Objects to Prevent Robot Kidnapped Problem

To prevent occurring robot kidnapped problem, it is important to evaluate likelihood of each particle considering an environmental change. Moving objects are one of the main causes of environmental change and each objects has each own movability. For example, chair has high movability because it is designed to move and interacts often with humans. On the other hand, walls or shelves have low movability because they are designed not to move and interact less often with humans. So, in this study, we define classes of objects and movability of them. We propose a localization approach that focuses on the association between sensor information obtained from objects whose movability is low and prior map by considering classes and movability in order to prevent occurring robot kidnapped problem.
Development of Test Methods for Robots for Nuclear Disaster Response

This paper proposed test methods for the robots for nuclear emergency response. Our motivation is to enhance the development of the robots and the improvement of the operator proficiency for decommissioning of Fukushima Daiichi Nuclear Power Station. We describe some proposals of developed test method for nuclear disaster response ground robots. Subject of the robots’ performance to be evaluated and required conditions are described. Practical example courses and testing procedure utilizing the mockup facility and developed test field are also introduced.
Validation of MR technology for medical engineering applications

In recent years, AR / VR related technology has been spreading and utilized. HoloLens using MR (Mixed Reality) technology is expected to operate in various environments. In this research, we are investigating the operation in the medical and nursing care fields that uses this as a new input interface. In this report, results of verification of various functions will be introduced.
Autonomous Traveling Manual Wheelchair (1st report)

In a nursing home care facility, it is one of the factors that the burden of a caregiver is increasing by guiding many cared persons on a wheelchair before and after a meal. Although many autonomous electric wheelchairs have been researched and developed, it is not reasonable to introduce them for the entire care receivers in a nursing home from the viewpoint of cost, time and trouble of maintenance. We are developing a detachable robot which makes a manual wheelchair run autonomously. This report describes the experimental machines were prototyped by defining the basic concept, target specifications and design conditions, and the results of basic experiments such as straight running stability experiment, speed experiment, measurement experiment of obstacle sensor. In future, we will proceed with implementation of straight follow-up control function and autonomous driving function.
Editorial for Special Issue “IberSPEECH2018: Speech and Language Technologies for Iberian Languages”

The main goal of this Special Issue is to present the latest advances in research and novel applications of speech and language technologies based on the works presented at the IberSPEECH edition held in Barcelona in 2018, paying special attention to those focused on Iberian languages. IberSPEECH is the international conference of the Special Interest Group on Iberian Languages (SIG-IL) of the International Speech Communication Association (ISCA) and of the Spanish Thematic Network on Speech Technologies (Red Temática en Tecnologías del Habla, or RTTH for short). Several researchers were invited to extend their contributions presented at IberSPEECH2018 due to their interest and quality. As a result, this Special Issue is composed of 13 papers that cover different topics of investigation related to perception, speech analysis and enhancement, speaker verification and identification, speech production and synthesis, natural language processing, together with several applications and evaluation challenges.
Change in the walking speed induced by sound intervention using real-time gait event detection

In recent years, people who lack exercise have been increasing. However, it is reported that a lack of exercise leads to chronic diseases. Therefore, if not having a habit of exercising, getting rid of the lack of exercise is hopeful by increasing the exercise intensity of daily behavior. As one of the fundamental daily behavior, walking is considered. It is desired to promote this exercise strength at walking in everyday life by natural intervention. This study focused on the change in walking speed induced by the sound intervention using real-time gait event detection. Experiments were conducted on three healthy males. The following methods were employed for the sound interventions: generating a beep sound in constant tempo (Constant Tempo) and generating a sound in adapted tempo based on the initial contact (Adapted Tempo). Among two interventions, the significant increase in walking speed by entrainment was observed in the latter method which generated the beep sound synchronously with the gait event by detecting the initial contact.
Stair Climbing Algorithm with Seat Sliding Motion for Four-Wheel Type Vehicle

This paper proposes an algorithm which enables a four-wheel robot to climb stairs that are higher than the radius of the wheel. In the proposed stair climbing algorithm, the two wheels on left (right) side climb a step using the pressing force that is generated by a torque of steering axis. In addition, this algorithm uses the static effect and the dynamic effect which are generated by a movement of the center of gravity with seat sliding. When seat sliding decelerates, a moment which raises the wheel is generated. This moment is used when lifting the wheel in this algorithm. The effectiveness of the proposed algorithm is verified by simulation.