Tomomi Takashina

Individual Level Analysis Using Decision Making Features in Multiagent Based Simulation

We introduce a set of evaluation tools in the framework of individual level analysis for multiagent based simulations. These tools are intended to overcome the weak points of multiagent systems: that it is difficult to avoid mistakes in description and arbitrary modeling; and to find reliable explanations of causal relationships between the model and its result. We analyze some artificial market models using an evaluation process that consists of the evaluation of initial learning maturity, discrimination between models, and the visualization of attention tendency in a group. We conclude that these analytical methods are useful for the evaluation of multiagent based simulations in terms of validation and finding causal relations.

Toward practical implementation of emotion driven digital camera using EEG

Photography is closely tied with peoples emotion. Therefore, the concept of emotion driven camera is a natural consequence of future photography. As for EEG emotion detection in research laboratories, there have been many works but it is considered difficult to apply such methodologies in generic environments. For measuring ERP (event related potential), some kinds of cues are typically used for knowing the exact time in which a stimulus given, but it is difficult to know such cues in real world. Therefore, we propose a cue detection mechanism based on the architecture of digital single lens reflex camera. It enables to reproduce an environment similar to research laboratories and is still a natural configuration for ordinary digital cameras.

Evaluation of Feeling of the Like in Watching Pictures by Physiological Signals

We usually use the word ‘like’ when we see good pictures, e.g. in social networks. When we choose a picture that evokes the feeling of ‘like’ out of many pictures, we evaluate each picture based on our subjective and intuitive preference. We hypothesized that physiological responses arise when participants watch pictures that evokes the feeling of ‘like’. In this study, we examined whether we can measure physiological responses when participants feel ‘to like’ a picture they choose among many pictures. We measured electroencephalogram, electrooculogram, electrocardiogram, and respiration of the participants while these are choosing the best picture from a set of pictures which had different setting of depth of field. We found that EEG responses appears when the participant watched the best pictures which evokes the feeling of ‘like’.

Toward a Compact Device to Interact with a Capacitive Touch Screen

Capacitive touch screens are widely used in various products. Touch screens have an advantage that an input system and output system can be integrated into a single module. We consider this advantage could make it possible to realize a new universal interface for both human-to-machine (H2M) and machine-to-machine (M2M). For a M2M interface, some sort of method to simulate finger touching is needed. Therefore, we propose an alternative method to interact with a touch screen using two electrical approaches. Our proposal is effective in automating touch screen operations, modality conversion device for people with disabilities, and so on. We assembled a prototype to confirm the principle to control a touch screen with the electrical methods. We believe that our proposal will complement the weakness of touch screens and expand their possibility.

Sushi Train Interface: Passive and Interactive Information Sharing

We proposed sushi train interface as a novel information sharing method to have users notice everyday information in a natural manner. In the interface, information rails are projected on ceilings or walls, and information dishes go around on the rails. Users interact with the information rails using remote pointing devices. We constructed a prototype as a proof-of-concept and implemented pointing methods by a camera device and a smart laser pointer. The both methods are expected to be used for interacting information rails.

Tangible Microscope with Intuitive Stage Control Interface

Control interfaces of microscope stage have been conservative because they historically precede compact mechanisms which can be used in dark rooms with the sense of fingertips. However, there is a trend of expanding frontier in microscope interaction. New kinds of interactions for microscope are proposed and the freedom of stage control increases by hexapod micropositioning. We propose a tangible microscope which has an intuitive stage control interface. The interface combines a tablet device and a hexapod stage. Because a stage is a plane, we virtually assume a stage is on one’s palm. It is very intuitive that the stage moves in the same manner of palm’s move. As a proof-of-concept, we constructed a prototype by regarding a tablet as a palm. We haven’t any quantitative evaluation yet, but it is expected that the concept of tangible microscope brings a new sense of stage control to users.

Wide area interaction using telephoto imaging

Conventional interaction researches deal with relatively small spaces with physical proximity or completely distant spaces without physical proximity. However, there is an intermediate range of them. The distance to a target for interaction is longer than physical proximity but the target can be seen in a view. Such situations occur in sport stadiums, construction sites, cities, and so on. We call interaction in such a range as wide area interaction. As for wide area interaction, there are some researches on the infrastructure aspect [Blackstock et al. 2006], but there are few on the practical interaction method. Our approach is to utilize telephoto lens. With telephoto lens, a user can address a distant object and point the exact coordinate on the surface of the object from a distant place.

MASSE: environment supporting for simulation and analysis of multiagent systems

In multiagent system research, the work in building simulation model and the effort in developing analysis methods are closely related because building multiagent models relies heavily on new effective analysis methods while justifying new analysis methods needs the simulation results of multiagent models. MASSE (Multiagent Simulation Systematic Explorer) was proposed as an integrated environment which is aimed at (a) to conduct efficient simulation by intelligent scheduling, (b) to conduct intelligent data analysis and knowledge discovery on simulation data, and (c) to develop such analysis methods themselves. Current implementation of MASSE is described in this manuscript, and its usefulness is shown in three aspects: simple accommodation of existing simulators, satisfactory performance for adopting grid computing technique, and systematic data analysis tool. Collaboration among simulation developers and analysts can be strongly supported by using MASSE to incorporate various simulators and unified method for data analysis. We conclude that the current implementation of MASSE is satisfactory