Sensing technology for eyeball movement (i.e., gaze movement) has enabled various applications, e.g., hands-free input interfaces and provided information that helps us understand human beings in various fields. However, the existing method, which senses eyeball movement constantly using a wearable device has limitations that should be addressed, e.g., cost. Therefore, we propose a method to recognize eyeball movements using eyewear equipped with multiple infrared distance sensors. The proposed method recognizes eyeball movement by sensing time-series data of eyelid skin movement, which accompanies eyeball movement, using an infrared distance sensor inside the eyewear. Evaluation results of five subjects demonstrate that the proposed method can recognize five types of movement with an F-value of 1.0 and 20 types of movement with an F-value of 0.94. Our study showed the feasibility of the proposed method for gaze input interface and for inexpensive technology that constantly senses the eyeball movement.

Recently, it has become a trend to construct a thermal environment with human thermal comfort. The advantage of human thermal comfort is that we could adjust the environment through the thermal sensation of human. Since human thermal comfort is influenced by several factors such as environmental temperature, environmental humidity, airflow, mean radiant heat, and so on, it is usually difficult to be directly evaluated. This paper proposes a method of estimating subjective thermal comfort and objective thermal comfort using CNN by RGB image data, thermal image data, and sensor data. We built a pipe-type booth in a room with a small air conditioner, two heaters, a humidifier, and a dehumidifier to acquired learning data, and we trained CNN under six different learning patterns to estimate thermal comfort. We found that image data is conducive to estimate subjective thermal comfort, and sensor data is conducive to estimating objective thermal comfort.

This research aims to build a system that estimates assessment expressions to others by machine learning, collects them in real time, and feeds them back to the participants, and this study proposes two techniques that are necessary for this purpose. First, we propose a method to estimate the evaluative behavior to others, which is simplified to positive, negative, and neutral, from the facial images and head acceleration of participants in the conversation. The supervised machine learning algorithm requires ground-truth labeling. To analyze the expression of a large number of people, such as in a classroom, ground-truth labeling becomes a challenge in analysis and system construction. Second, to ease the labeling process we propose and implement a method to recommend the estimated labels on the labeling software. The accuracy of the proposed method is approximately 0.45 in F-value. Considering the time-series information, the proposed method recognizes major changes in positive evaluation behaviors. Presenting recommended labels on our labeling support system increase with time for the ground-truth labeling. However, the accuracy of labeling positive assessments improve in five out of six subjects.

Hundreds of thousands of Chinese characters are used in the Japanese and Chinese writing systems. Memorizing all the Chinese characters requires great effort because learners have to memorize not only the shape of the character but also its meaning and usage. Research to find a method to present the shape of the figures using sound has been conducted. Consequently, it is possible to generate a song for learning Chinese characters comprehensively using sounds that represent the shapes of the characters and lyrics that represent the meaning and usage. We propose a method to generate a song based on the structures, strokes, and usage of Chinese characters and a method to memorize Chinese characters using the generated song.

There have been several studies on object detection and activity recognition on a table conducted thus far. Most of these studies use image processing with cameras or a specially configured table with electrodes and an RFID reader. In private homes, methods using cameras are not preferable since cameras might invade the privacy of inhabitants and give them the impression of being monitored. In addition, it is difficult to apply the specially configured system to off-the-shelf tables. In this work, we propose a system that recognizes activities conducted on a table and identifies which user conducted the activities with load cells only. The proposed system uses four load cells installed on the four corners of the table or under the four legs of the table. User privacy is protected because only the data on actions through the load cells is obtained. Load cells are easily installed on off-the-shelf tables with four legs and installing our system does not change the appearance of the table. The results of experiments using a table we manufactured revealed that the weight error was 38 g, the position error was 6.8 cm, the average recall of recognition for four activities was 0.96, and the average recalls of user identification were 0.65 for ten users and 0.89 for four users.

This paper describes a prototype system of remote music therapy for elderly people with dementia using the latest communication technology in Japan. The system uses the latest high-speed optical network, called NGN (Next Generation Network) and the latest terminal especially for audio data communication called Hikari DUETTO NY1, which was released at the end of the last year. We did an experiment of the system using the real communication environment in this January between Tokyo and Osaka. The communication time of the system between Tokyo and Osaka was about 25.5 msec. Thus, we confirmed that the system was able to provide almost real-time audio data communication. Based on the result, the feasibility of music therapy activities, such as singing and exercises with music, using the system was examined. We confirmed that the singing activity which is the most important one in the music therapy was feasible.

In this paper, we investigate adaptive control for broadcast scheduling and base station caching in the hybrid wireless broadcast (HWB) environment. The proposed adaptive method can adapt well to different access conditions and bandwidth capabilities and adequately exploit the three data delivery modes: push-based broadcast, pull- based broadcast, and pull-based point-to-point communication. Simulation studies demonstrated that our proposed method achieves significant performance improvement in average waiting time and success rate.

In this paper, based on the Hybrid Wireless Broadcast (HWB) model, we investigate a cooperative data management strategy to provide more efficient data delivery to the mobile clients. This strategy integrates broadcast scheduling with cache management of the base station by making effective use of the HWB data dissemination, namely push- and pull- based broadcast and pull-based point-topoint wireless communication. Simulation study demonstrates that the proposed cooperation strategy can improve the system performance.

In the near future, small ubiquitous devices will be embedded into most of artifacts to support human dailylife. In such environments, we need multiple types of human-computer interfaces for enjoying ubiquitous services. This paper describes several ubiquitous gadgets; ubiquitous chip, Pin&Play, and VCC, to provide flexible ubiquitous services and user interfaces. The integrative use of these devices achieves the physical and intuitive interaction between users and ubiquitous services.

In recent years, there has been an increasing interest in broadcast database systems, where the server periodically broadcasts contents of a database to mobile clients such as PDAs. There are three query processing methods in the broadcast database system: (i) the server processes a query and then broadcasts the query result to the client; (ii) the client stores all data that are necessary in processing the query and then processes it locally; and (iii) the server and the client collaborate in processing the query. Since the performance of each method changes according to the system situation, such as query frequency, it is difficult to decide the optimal method among them statically. In this paper, we propose a new query processing method which dynamically changes the query processing method based on query frequency. This method improves not only the response time but also the success rate of query processing compared with the traditional methods.

Because of advances in information technologies, car navigation systems have come into widespread use as useful tools to guide drivers where they want to go. Conventional car navigation systems present the most suitable route according to a destination input into the system. However, since the required operation to input the destination costs so much, users do not usually use car navigation systems for daily driving. In this paper, to exploit the effective functions of car navigation systems, we propose a new system that automatically predicts user purpose and destination. The proposed car navigation system presents various information based on predicted purpose without interaction from users.

In recent years, due to the increasing popularization of various broadcast services, there has been an increasing demand for information filtering techniques. Although filtering methods that have been proposed filter data in their own ways, mathematical representation of these methods does not exist. Consequently, it is not possible to qualitatively evaluate various filtering methods, to optimize processing methods in filtering, or to design a declarative language for filtering processes. In our previous work we have defined a filtering function that represents filtering as a function, and clarified the properties of different filtering methods. In practice, current filtering methods actually consist of multiple methods. In this paper, we make it possible to qualitatively represent those filtering methods by introducing the concept of composition into the framework of filtering function. Moreover, we reveal the characteristics of those combined filtering methods by clarifying the properties of composite filtering functions.