Yuka Kato

This paper reports the result of questionnaire surveys on the value of research papers in the field of IPSJ Special Interest Group on Distributed Processing Systems (SIG-DPS). Here, we attempt to identify the factors that lead researchers to consider research papers as "good." The subjects of the surveys are experienced researchers. First, for the primary survey, we extract the value of research papers not considered in the general peer review criteria such as novelty and usefulness, as well as the factors that researchers consider essential and important for writing papers. These papers include both their own papers and those of others. Next, we present the analysis results at a workshop of the research community and have a discussion among the participants with the aim of using the result of the survey. After that, we conduct another questionnaire survey as the secondary survey on the role of the research community in producing "good" papers. From the overall results, we show that these surveys make it possible to share values of "good" papers among the researchers in the field and, as a result, to utilize to produce "good" papers. We also show that it is important to conduct such surveys constantly.

<p>Large volumes of data are typically used during analyses. Data preprocessing, which involves detecting outliers, handling missing data, data formatting, integration, and normalization, is essential for achieving accurate results. Many tools and methods are available for reducing preprocessing time. However, most analysts face difficulties when using them. This paper proposes a method for handling outliers and missing data, called Automated PRE-Processing for Sensor Data (APREP-S). For reducing analysis resources, we combine programming by example and machine learning via Bayesian inference, inputting human knowledge to APREP-S as an example and calculating a proper proportion by machine learning via Bayesian inference. We also define k-Shape as the calculation of the rate of similarity of time-series data. In evaluation, we use sensor data of temperature and humidity and compare the sum of the square of the errors of four methods, between original data and outputs of each methods, (1) APREP-S, (2) mean of the entire data, (3) mean of the around-the-target imputation data, and (4) spline interpolation. It is verified that APREP-S is a more suitable method for humidity data than temperature data. preprocessing method. we consider the reason is that humidity data have more changing points.</p>

© 2019 IEEE. It has recently become possible to analyze integrated data obtained from sensors or wearable devices in the field of Information Technology (IT). Well-known examples include behavioral patterns of customers in a shop, the autonomous motion of robots, and fault prediction. It is known that the pre-processing of data-before it is input into the analysis model-is essential to achieve accurate results. However, this task requires 80% of the resources in the analysis process. As an improvement to the pre-processing of outliers and missing data, we had previously proposed 'APREP-S' based on Bayesian inference with Programming by Example. In this paper, we expand APREP-S and define the timing of model generation for increased interactivity between analysts and APREP-S. We calculate the accuracy of the new APREP-S and compared it to that of existing methods. Based on our results, we conclude that APREP-S is the most effective imputation method for time-series data.

The need for analyzing data is increasing at an unprecedented rate. Well-known examples include customer behavioral patterns in shops, the autonomous motion of robots, and fault prediction. Pre-processing of data is essential for achieving accurate results. This includes detecting outliers, handling missing data, and data formatting, integration, and normalization. Pre-processing is necessary for eliminating ambiguities and inconsistencies. We here propose a framework called APREP-DM (for the Automated PRE-Processing for Data Mining) applicable to data analysis, including using sensor data. We evaluate two types of perspectives: (1) considering pre-processing in a test-case scenario involving pedestrian trajectory tracking, and (2) comparing APREP-DM with the outcomes of other existing frameworks from four different perspectives. We conclude that APREP-DM is suitable for analyzing sensor data.

In recent year, there has been increasing interest in communication robots, and a variety of services including voice guidance are expected for such robots. For providing those services, state estimation of robot users is required. From the background, we have been studying a method to predict the walking direction of a pedestrian who heads toward a robot in order to provide suitable voice guidance to him/her by a communication robot installed at the reception desk of a public facility. In this paper, we verify the effectiveness of the proposed method by using actual observed data. Here, we measure pedestrian trajectories using a laser range scanner installed on a tripod and predict the branching direction using pre-trained predictor models by a machine learning algorithm. In this paper, we generated two predictor models using an open dataset of pedestrian trajectories in a shopping mall. By conducting evaluation experiments using the models, we found out that one model can predict the direction with practical accuracy but the accuracy of another one is not sufficient. The result shows that using robust and adequate predictor models are important for our target system.

In this paper, we propose a method robustly predicting the destination of a pedestrian heading toward a robot in order to provide suitable voice guidance to him/her by communication robots installed at the reception desks of public facilities. For this purpose, we measure a pedestrian trajectory with a laser range scanner attached to the robot, and predict the destination among more than three branches by cascading multiple predictor models for two branches pre-trained by a machine learning algorithm. In order to verify the effectiveness of the proposed method, we conduct experiments using a dataset of tracking pedestrians at a shopping mall, and data observed in the real environment. The result shows that our method can predict three branch destinations with an accuracy of about 80%.

It is known that there is a strong correlation between daily lifestyle and health condition. Lifestyle-related diseases are one example of them and the action of preventing them is very important topics of discussion. Recently, various devices, which are worn anytime and are able to collect vital information, are widely used. Consequently, many studies using these devices for health management have been made. From these backgrounds, this study proposes a method estimating a stress state by using the instantaneous pulse rate obtaining from wearable devices in order to identify long-term stress factors in daily life. Here, we formulate Stress and Relaxed Value (SRV) as a QOL (Quality of Life) indicator with considering both stress and relaxed state, and verify that SRV can be associated with lifestyle factors. For the method, we use LF/HF (Low Frequency/High Frequency), which is derived from the fluctuation of the peak intervals of heartbeat and is an indicator of the psychological stress state. In this study, we calculate SRV by combining LF/HF with HF, which correlates relaxed states. In addition, we verify the effectiveness of the proposed method by conducting evaluation experiments using a wearable device.

本稿では，情報処理学会におけるダイバーシティ推進の取り組みとして，2016年4月に発足したInfo-WorkPlace委員会の活動を紹介する．本委員会は，女子学生，女性技術者・研究者の活動を支援し，学会の一層の発展を図ることを目的に設立されたが，委員会名にあえて「女性」という言葉を入れていない．これは，性別・年齢などの属性を問わず，私たちのワークプレイスを新たにデザインしていくことを目指したい，という思いが込められているためである．女性支援活動は重要な取り組みといわれながらも，一部の女性だけが活発に活動していて広がりがない，女性というだけで半ば強制的に参加させられるなど，本来の意味で機能していない事例も見受けられる．我々は，参加することにメリットがあり，参加したくなる場づくりを目指した，新しい形の活動を模索している．本稿では，委員会設立までの経緯，現在の活動内容を紹介することにより，ダイバーシティ推進活動の今後の方向性について考察する．

「男性の働き方を変えないと女性の働き方も変えられない」．日本の夫婦共働きの世帯が1,100世帯を超え，多くの若い世代が育児と仕事との両立という問題に直面し，悪戦苦闘・試行錯誤しています．ダイバーシティ社会の推進において，ワークプレースはどうあるべきか？ ICTでどう支援できるか？ 2016年9月に富山大学で開催されたFIT2016において，情報処理学会Info-WorkPlace委員会とデジタルプラクティス編集委員会との共同企画イベントとして実施したパネル討論の内容をまとめました．

Recently, lifestyle-related diseases, which are caused by accumulated disordered lifestyle, have been a considerable problem. Though someone might be able to change such lifestyle by becoming aware of the style problems, it is not easy to be always conscious of health in everyday life and also to visualize their lifestyle individually. Currently, we can use various sensor devices to solve these problems. Improving of sensing technologies makes it possible to collect various kinds of vital information daily and easily. From these backgrounds, we have studied on a Quality of Life (QOL) visualization system, whose target is to improve our lifestyle on a daily basis by using vital information collected from wearable devices. In this paper, we propose a QOL indicator called SRV (Stress and Relaxed Value) as one of the functions of the QOL visualization system. That is an estimation model on stress and relaxed states by using the instantaneous pulse rate. We also verify the effectiveness of the proposed model by conducting evaluation experiments using a pulse sensor.

We have studied a dialog control method for interface robots by using location data of persons measured by a Laser Range Scanner as a human-robot interaction technology. In the method, we measured the distance between a sensor and a person with the sensor placed at human waist height as a time series data and estimated the position coordinates of the person at a time as a probability distribution. This paper extends the scheme and proposes a method estimating person attributes in addition to the location data by monitoring the movement of legs while the person is walking. As for person attributes, we focus on the age and classify persons as the elderly and the young. At that time, we construct a prediction model of age groups based on machine learning mechanisms. In this paper, we use seven feature values, these are the step length, the step width, the velocity of leg 1, the velocity of leg 2, the velocity of body, the acceleration of leg 1 and the acceleration of leg 2 for the model. By conducting experiments, we verify that classification accuracy improves particularly using acceleration and standard deviation of the data.

In this paper, we discuss the effect of network delay on remote navigation for low-cost simple robots using cloud environments. First, we conduct the experiment of remote navigation using a robot simulator and show the result which does not navigate a robot adequately under the network condition with pseudo-delay. Then, from the result, we derive the necessity of the control model in considering network delay and design the delay-conscious control model in slowing the observation and quickening the control according to the pre-defined delay model.

This paper proposes a method for estimating a stress state by using pulse sensor obtaining from wearable devices in order to identify long-term stress factors in daily life. For the method, we use LF/HF (Low Frequency / High Frequency), which is derived from the fluctuation of the peak intervals of heartbeat, and is an indicator of the psychological stress state. The proposed method estimates LF/HF by using a pulse instead of the heartbeat, and formulates Stress and Relaxed Value (SRV) as a Quality of Life (QOL) indicator on the basis of LF/HF. In addition, we conduct an experiment comparing pulse data, obtaining from pulse sensor and pulse wave obtaining from the pulse wave monitor. The experimental result shows that the same trend can be recognized on these data.

This paper proposes a remote navigation system for a simple tele-presence robot. In general, robot functions of tele-presence robots are limited, and visual angle of the camera on robots is narrow, so they are unsuitable to use navigation services. The proposed system overcomes the difficulty by adopting system architecture in which robots are controlled remotely via a server located in the Internet, by using well-designed virtual reality techniques for robot control and by implementing almost all robot navigation functions into the server. In this paper, we also implemented Remote Open Campus System (ROCS) as a prototype system, and by using that, we confirmed the effectiveness and usefulness of the proposed system.

This paper proposes a mapping method with the virtual world and the real world for robot remote controlling via the internet. Server isolates a user operation side in the virtual world and a robot working side in the real world. We use a GameEngine for creating the virtual world. The GameEngine handles user operation and user side view. This view is used for the reference for comparing matching level with the real world view which is taken by robots in the real world and current intensity level comparing with measured intensity concurrently. These comparing processes are done on the server. We validate efficiency of the method for applying to campus guidance service.

When we discuss operability and convenience of remote control robot systems, it was usual to focus on user interfaces to operate robots. In this paper, we propose to improve methods of service providing based on the different operation types, e.g. operation which requires realtime response, operation which allows delay between user operation and robot movement via networks.

Recently, there are increasing interests of integration between robot technologies and Internet services, and various cloud-based service platforms for robots are proposed. From these backgrounds, in this paper, we propose a virtual campus tour service which enables remote users to control robots in school campuses via the Internet. In implementing the service, we use Robot Service Network Protocol (RSNP), which is a common protocol specification for robot services. Therefore, users can operate various remote robots in various campuses via the proposed service. Furthermore, we conduct subjective and objective assessments on camera functions for the service, and verify the effectiveness of the proposed one.

Internet and cloud-based robot services and their platforms are becoming attractive. Many related works have been also done, such as DAvinCi, ROS on Android, and RoboEarth. However, when robot services are provided via computer networks, very reliable services are required to deal with short/long-term disconnection between services and robots due to wireless LAN disconnection, robot service problems, system error on robots, and so on. In this paper, we adopt Robot Service Network Protocol (RSNP) as a robot service platform in order to integrate robot services with Internet services. In addition, we propose a method and architecture to realize reliable cloud-based robot services for RSNP in a communication view point.

In recent years, there are great attentions to realworld data services where the Internet services, ubiquitous computing and robot services are integrated. In order to spread such services widely, standardized platforms and wide variety of applications are required. In this paper, we propose a Remote Open Campus System (ROCS) which provides a campus tour service by controlling a robot at a campus through the Internet. ROCS maps a real world campus environment to a virtual world, that is, reflecting real views captured by a robot to a virtual campus created by itself. For that, ROCS functions are created by using RSNP (Robot Service Network Protocol), which is a protocol specification for robot services. © 2013 IEEE.

Recently, there are increasing interests of integration between robot services and the Internet, and many remote control services using robots have been proposed. In order to control robots remotely, we generally use images and videos captured by robot cameras and fixed cameras, but image quality is fluctuating with a change of network condition. The fluctuation has an effect on operational accuracy of remote control robots. In this paper, we propose the method controlling quality of camera images according as network condition for a virtual campus tour service using robots.

Recently, many ICT companies as well as researchers are taking an increasing interest in robot services using cloud computing, and various service platforms for them have been proposed. From these backgrounds, we have proposed a distributed service framework using Robot Service Network Protocol (RSNP) to integrate various devices including robots with internet services. The key mechanism of the proposed framework is a robot assignment function, which discovers distributed robot resources and assign the requested tasks by end users to suitable robots. In this paper, we implement a prototype system on the proposed framework, and conduct implementation evaluation using the system.

With the rapid advance of the integration of internet and robot areas, various service platforms are proposed that assume cloud environments. For robot services, as the numbers of devices and their types increase, a mechanism that enables the entry of developers in various areas is required. However, existing platforms are insufficient to the problem. In this paper, we developed a distributed service framework that realizes the coordination of various devices, robots, and service functions based on RSNP (Robot Service Network Protocol), a protocol specification for robot services. Furthermore, we implement a pet-sitting service as a prototype system that uses a proposed framework and verify the effectiveness of the framework.

We have proposed the RSi Research Cloud (RSi-Cloud), which enables integration of robot services with internet services. Until now, we have developed a surveillance service using robot cameras on the cloud environment, and have realized internet connection from robots implemented with RSNP (Robot Service Network Protocol). This paper reports a design result of Robot Service HTML interface (RSHi), which is a mechanism to treat robot applications deployed in RSi-Cloud by the same way as RSNP robot clients. RSHi makes it possible to deploy RSNP service applications within firewall systems, and as a result, a robot service expansion can be expected. Moreover, in this paper, we show a usage example of micro-services on a service robot which uses a face detection function. © 2011 IEEE.

We propose the Network Service Platform (NSP) as a framework which enables the development of integrated services between three service fields: Internet Services, Robot Services, and Ubiquitous Computing. In this paper, we outline the development of a Home Security Service Robot System, a prototype service which integrates Internet and Robot services using the NSP framework. In this prototype system, the robot monitors the home and uploads image and motion detection data. The server on the Internet stores these images, allows human face recognition and email notification, and provides user consoles for controlling and browsing functionalities from a web browser. We also discuss the possibility of providing integrated services using the NSP framework based on the results of our implementation. © 2011 IEEE.

In this paper, we propose the Network Service Platform (NSP), which is a framework to develop network services using real-world data efficiently, and implement its application. We implemented a prototype system based on NSP using GPS data and image data obtained from cell phones. This service integrates internet services with ubiquitous services by using the Robot Service Network Protocol (RSNP), an open standard protocol for robot services. Through the implementation of the prototype system, we confirm the effectiveness of NSP to develop network services. © 2011 IEEE.

We have proposed the network service platform based on RSNP (Robot Service Network Protocol) as a service platform to develop network applications using real-world data. A feature of the platform is that the pseudo PUSH communication of RSNP makes it possible for service providers to implement and deploy secure services easily. This paper reports an implementation result of "The face detection server" that is a function of the platform and detects human face areas in a given image file. This function is implemented as a micro-service on the platform, and it can be used via the Internet using RSNP. In this paper, we discuss possibility of implementation of various service modules to the platform according to the result.

This paper proposes the RSi Research Cloud (RSi-Cloud), which enables integration of robot services with internet services and mash-up of robot services. The feature of RSi-Cloud is to use a standardized communication protocol, that is Robot Service Network Protocol (RSNP). By using the robot service specification, we can provide novel services combining various kinds of service components. In addition, since RSNP is determined based on web services, many researchers and engineers in the internet field can join robot service development. We also implement a surveillance camera service as a prototype system using the proposed platform. This paper reports the implementation result.

The service robot technology is facing the pre-dissemination phase. In this paper, we clarify that a new robot service platform requirement for that phase is the remote interrupted operation, in addition to the requirements discussed in the previous paper. And we clarify also a requirement for supporting the robot service development. To solve these requirements, we propose the command profile and a robot service execution/development environment on the internet which is consist of RSNP library, real robot services such as a disaster prevention information service and a monitor service, RSi server, and RSI robot portal site. And we show our proposals are effective.

The non-industry robot technology is becoming in pre-spread stage. In this paper, we clarify requirements of the robot service platform for pre-spread and spread stage. And we have developed RSNP 2.0 specification to resolve these requirements, by (1) a secure push-communication for robot with limited resource and/or fewer operators, (2) an efficient packaging technology for robot services used in public spaces, and (3) an integration of robot and sensors/cameras of different robot platforms. Finally, we have proved the effectiveness of our proposed RSNP 2.0 through a proof of concept implementation.