Published papers

Nowadays, various kinds of sensors are available due to expansion of the smartphones. Along with this, the research that records the action on a daily basis has become very popular. Distinction of transport is also a part of the studies. The major result from resent studies has been detected those transport by using the sensors such as GPS or a microphone or an acceleration sensor. However, since this is one of the biggest cause to encourage the consumption of the batteries, it is not practical to detect only with a smartphone. I suggested in this paper the system to detect transport adopting acceleration sensor and evaluated the detection accuracy by applying various kinds of method of machine learning. Moreover, I evaluated power saving of this system.

Nowadays, various kinds of sensors are available due to expansion of the smartphones. Along with this, the research that records the action on a daily basis has become very popular. Distinction of transport is also a part of the studies. The major result from resent studies has been detected those transport by using the sensors such as GPS or a microphone or an acceleration sensor. However, since this is one of the biggest cause to encourage the consumption of the batteries, it is not practical to detect only with a smartphone. I suggested in this paper the system to detect transport adopting acceleration sensor and evaluated the detection accuracy by applying various kinds of method of machine learning. Moreover, I evaluated power saving of this system.

Nowadays, various kinds of sensors are available due to expansion of the smartphones. Along with this, the research that records the action on a daily basis has become very popular. Distinction of transport is also a part of the studies. The major result from resent studies has been detected those transport by using the sensors such as GPS or a microphone or an acceleration sensor. However, since this is one of the biggest cause to encourage the consumption of the batteries, it is not practical to detect only with a smartphone. I suggested in this paper the system to detect transport adopting acceleration sensor and evaluated the detection accuracy by applying various kinds of method of machine learning. Moreover, I evaluated power saving of this system.

In,this research, we propose a software model for the dynamic distribution of software components across a wide-area network, and we provide a software environment to realize the proposed model. In the dynamic distributed software model, software modules can autonomously migrate among computers. This feature allowes dynamic distributed software to have the advantage of dynalnic load balancing, fault tolerance, scalability, optimization of computing environment, and the processing support for small-size portable devices. Moreover, we designed and implemented a dynamic distributed software toolkit named "Meta Space".

In this research, we propose a software model for the dynamic distribution of software components across a wide-area network, and we provide a software environment to realize the proposed model. In the dynamic distributed software model, software modules can autonomously migrate among computers. This feature allows dynamic distributed software to have the advantage of dynamic load balancing, fault tolerance, scalability, optimization of computing environment, and the processing support for small-size portable devices. Moreover, we designed and implemented a dynamic distributed software toolkit named "Meta Space".

This paper presents the design and implementation of information browsing support system transparent in devices and services, tranService. It translates the types of media in consideration of characteristic of devices and services. When a request for information is received from the client, it is altered to suit the format of the service. The information received from the service, in turn is altered to suit the user's request, and the information of the surrounding environment. Thus, the users can browse various information without any additional application, and service providers can provide information without consideration on users and devices.

This paper presents the design and implementation of information browsing support system transparent in devices and services, tranService. It translates the types of media in consideration of characteristic of devices and services. When a request for information is received from the client, it is altered to suit the format of the service. The information received from the service, in turn is altered to suit the user's request, and the information of the surrounding environment / Thus, the users can browse various information without any additional application, and service providers can provide information without consideration on users and devices.

© Copyright is held by the owner/author(s). In this research, we propose a system that allows one to find a hidden spot that is scenic, yet unpopulated, with the intention of improving the satisfaction of one's trip. These hidden spots are not yet noted in the existing tourism services, however can provide a new place for the tourists to discover. We developed an application as a prototype to analyze and pinpoint hidden spots by using venue data from Foursquare [1]. We acquired 19,705 data around Tokyo and calculated the relative hiding spot degree. Thus, we made it possible to provide users with hidden spot information from smartphone application.

© 2018 Elsevier B.V. Human attention has bottlenecked today's ubiquitous computing environment where users are consuming increasing amounts of information from numerous applications and services. Since the system-to-user provision of information is becoming more proactive, mainly via push notifications that often cause interruption at the users’ side, attention management is becoming very important. Despite the many existing studies concerned with detecting opportune moments to present such push information to the users (in a way that preserves the user's attention and lowers their cognitive load and frustration), there is little evaluation of such systems in the real-world production environments. Overlooked areas of study also include the examination of real users and notification contents. In this paper, we present various results from the first extensive evaluation on user's interruptibility and engagement in the real-world environment with a market-leading smartphone application that boasts a large number of users, including real notification content on the application. Following our previous mobile-sensing and machine learning-based interruptibility estimation approach, which was an effective study in its own right (Okoshi et al., 2015 [18,19]), we embedded a logic with the same approach in the “Yahoo! JAPAN” Android app (one of the most popular applications on the national market). The results from our large-scale in-the-wild user study (that included more than 680,000 users and spanned three weeks) indicate that, in most cases, delaying the notification delivery until an interruptible moment is detected is beneficial to users. The practice results in significant reduction of user response time (49.7%) when compared to delivering the notifications immediately. We observed a higher number of notifications opened in our system and constant improvement in user engagement levels throughout the entire study period. We also observed differences in click rates among different days and time among users with different attributes (e.g., age, gender, and occupation). Additional evaluation of our revised system, which can train and distribute different models for weekdays and weekends, improved the click rates during weekends. This negated the performance degradation previously observed during weekends.