There are many interactive design tools: Adobe Photoshop, GIMP, and so on. The interactive design tools often provide their users many visual effects. The users need to look for design parameter values appropriate to their desired visual effect. Interactive design can be dealt as a sort of optimal solution search problems. In optimal solution search, initial value setting plays an important role. Onomatopoeia can solve the initial value setting of the interactive design because onomatopoeia can easily describe the visual effect. We proposed a method that allows the users to input their own arbitrary onomatopoeia to design and obtain their desired visual effect. The method hires an onomatopoeia thesaurus map that can convert the arbitrary onomatopoeia to the initial values. We adopted Japanese brush font design system as an experimental example of the interactive design tool in order to evaluate our proposed method. Human subjects used the system and set the initial values of design parameters to design bold and scratched look of target fonts. As a result, the method was able to set more appropriate initial values closer to the optimal values to design the target in comparison with other conventional methods. The proposed method can be useful to solve the initial value setting of the interactive design.

Onomatopoeias are useful expression to communicate intuitive image of some designs. There are some approaches adopt onomatopoeias to design computer graphics, robot motion or Japanese calligraphic fonts. Murata et al. [11] introduced onomatopoeias to their system to design Japanese calligraphic fonts, however, it wasn't easy task to achieve suitable design using only onomatopoeias. On the other hand, Nakamura et al. [12] suggested that achieving an optimal design on an interactive design system corresponds to solving a search problem. To solve the search problem, selection of initial values plays an important role. Nakamura et al. proposed introducing onomatopoeias to set proper initial values of Murata's design system. Nakamura's experimental result showed that the proposed method is useful to achieve an suitable design of the calligraphic font. But the experiment was conducted for the fonts whose appearances were easily described by using onomatopoeias. Our study aims to reevaluate Nakamura's method. We adopted the fonts whose appearances were difficult to describe by onomatopoeias, and conducted an experiment to evaluate the cost to achieve the suitable design. As the experimental result, onomatopoeias can be a useful tool to achieve an suitable design without considering easiness or difficulty to describe by onomatopoeias.

Adobe Illustrator provides many tools for a user to create art works. The tools also provide many parameters or options that the user can tune up or select. This study focuses on black-and-white drawings (“Sumi-e” or “Suiboku-ga” in Japanese) on Adobe Illustrator. In order to create black-and-white drawings, the user usually has to select a proper brush from preset brushes Adobe Illustrator provides. But the selection is difficult for the user, especially beginners. This paper proposes a supporting plug-in tool for the user to decide and apply the proper brush. The plug-in can accept an onomatopoeic utterance input which expresses the user's own imagination or impression of the brush. Onomatopoeia is well known as a useful figurative expression for Japanese people to describe their own imagination or impression for something. This paper reports the configuration of the plug-in and illustrated some examples of black-and-white drawings created by using the plug-in. The architecture of the plug-in consists of CNN(convolution neural network), database of brush samples, brush image interpolation, fuzzy-based image expansion and contraction, and so on. CNN allows input of arbitrary onomatopoeias. The brush image interpolation generates a new brush from brush samples in the database. The fuzzy-based image expansion and contraction transforms the new brush into a natural-looked brush form with less jaggy.

Onomatopoeias are useful tool to communicate intuitively and conveniently among people. This paper focused on the utility of onomatopoeias and proposed a design supporting system of Japanese Kanji-calligraphic “Shodo” font using onomatopoeia utterance. The system can generate a variety of scratched- and blurred-look design of “Shodo”. In order to realize the design, the system utilized the correspondence between onomatopoeias and the scratched- and blurred-look. This paper reported the concept and the architecture of the proposed system. And we demonstrated some output examples generated by the system.

A proposed robot provides functionality inspired by the behavior of hearing dogs, which assist hearing-impaired people by alerting them to important sounds such as fire and smoke alarms. Hearing dogs use body contact for communication with hearing-impaired people, a process heavily depending on haptic communication. The proposed robot also uses physical contact for urgent notification, like a hearing dog's touching behavior. The robot can move using its wheels and then approach and bump people. To be explicit our proposal, our bumping behavior model was simplified and an experiment was conducted with hearing-impaired participants and a prototype robot. This paper reports the experimental results and discusses effectiveness of the robot's bumping behavior.

Our emotion estimation refers to estimation of a reader's sentiments and feelings after they read a narrative (i.e., post-reading emotion types). The emotion types manifest in a reader's feelings combine to form diverse and various patterns. To elicit this phenomenon, we here attempt to estimate readers' emotional patterns based on their cognitive appraisals of the work. This paper describes our cognitive appraisal methodology, variation in readers' emotion types due to differences in their cognitive appraisals, and report and discuss the results of emotion estimation experiments in which a reader performs a cognitive appraisal of the text of a narrative.

Research on physical human-robot interaction has been attracting attention recently, focusing on robot embodiment. The work reported here proposes Active Touch Communication Robot (AcToR), a robot that is modeled on the hearing dog. A hearing dog is a type of dog assist people who are deaf or hard of hearing by alerting their handler to important sounds. AcToR uses the sense of touch to notify a human of the intention to transfer information. For example, when AcToR detects that a cell phone that is in another location has received a call, AcToR moves to the user's location and makes contact with the user's body to notify the user of the incoming call. The AcToR robot is based on the Roomba®and uses the Roomba's bumper and contact sensors to detect contact. This paper reports the results of psychological experiments using the AcToR robot that indicate the feasibility of using touch to transfer information from a robot to a person.

Embodied expertise, which expresses skills of experts, is a kind of tacit knowledge that is difficult to transfer to another person by means of writing it down or verbalizing it. The aim of our study is to translate embodied expertise into explicit knowledge, i.e. onomatopoeias. We call the onomatopoeias "embodied expertise onomatopoeias" which could facilitate people to intuitively and easily understand the skills. Acquiring "embodied expertise onomatopoeias" is considered as a problem of pattern recognition. Our study adopted a skill of Japanese penmanship "Pen Shodo" which is Japanese calligraphy using pen to be translated to onomatopoeias, and investigated a possibility to construct a classification system for the skill.

The consultation algorithm for computer shogi determines each move by voting of multiple computer shogi players. In this research, we discuss some methods that optimize weights of player vote during a shogi game. To change the weight of player's vote, we use two kinds of criterion. One is the adoption times of each player vote and the other is evaluation value of the board position. Experimental results suggest the validity of our proposed method.

Tagging has emerged as a powerful mechanism that enables users to find and understand entities. However, there are three types of issues in traditional tagging systems. In this paper, we explore and seek a tag-algorithm that predicts tags of users and contents with a degree of relevance, which we called the tag ratio. We described our algorithm and evaluated them by the Naive Bayes classifier. Experiment results showed that all rating's precision of sought continuous number content's tag were better than raw binary valued content's tag's.

Given the remarkable recent progress in robotics research, we can envision the day when robots and humans coexist and robots become closely integrated into our daily lives. This means endowing robots with the ability to communicate so they perceive human emotion, adapt their behavior to humans, and sense situations even without explicit instructions. Meanwhile, affective computing, that interprets emotion or other affective phenomena from human biosignals, has emerged as an area of great interest. In addition to biosignals-brain waves, heart rate, pulse, electrical activity, and the like-affective computing is concerned with facial expressions, gestures, and a wide range of other indicators of emotion. Here we explore the latest insights of affective computing in relation to human-robot interaction (HRI). There is good reason to believe robots will soon have the ability to read human emotions, so here we investigate the feasibility of inferring human psychological states from biosensor signals. Obviously, non-invasive biosensors that don't interfere with normal everyday activities would be preferable. A number of inexpensive user-friendly brain-wave sensors have been brought to market recently, and we employ one of these devices, the NeuroSky Mindset EEG neuroheadset, in assessment trials to explore the feasibility of inferring subjective assessments. Using our experimental setup, we find that it is indeed possible to infer subjective assessments from biosignals, and this capability could prove immensely useful for future HRI applications.

Given a remarkable recent progress in robotics research, we can envision the day when robots and humans coexist and robots become closely integrated into our daily lives. This means endowing robots with the ability to communicate so they perceive human emotion, adapt their behavior to humans, and sense situations even without explicit instructions. Meanwhile, affective computing, that interprets emotion or other affective phenomena from human biosignals, has emerged as an area of great interest. In addition to biosignals-brain waves, heart rate, pulse, electrical activity, and the like-affective computing is concerned with facial expressions, gestures, and a wide range of other indicators of emotion. Here we explore the latest insights of affective computing in relation to human-robot interaction (HRI). There is good reason to believe robots will soon have the ability to read human emotions, so here we investigate the feasibility of inferring human psychological states from biosensor signals. Obviously, non-invasive biosensors that don't interfere with normal everyday activities would be preferable. A number of inexpensive user-friendly brain-wave sensors have been brought to market recently, and we employ one of these devices, the Neuro Sky Mindset EEG neuroheadset, in assessment trials to explore the feasibility of inferring subjective assessments. Using our experimental setup, we find that it is indeed possible to infer subjective assessments from biosignals, and this capability could prove immensely useful for future HRI applications.

We describe a cost-effective and low-power-consumption approach for on-chip optical interconnection. This approach includes an investigation into architectures, devices, and materials. We have proposed and fabricated a bonded structure of an Si-based optical layer on a large-scale integration (LSI) chip. The fabricated optical layer contains Si nanophotodiodes for optical detectors, which are coupled with SiON waveguides using surface-plasmon antennas. Optical signals were introduced to the optical layer and distributed to the Si nanophotodiodes. The output signals from the photodiodes were sent electrically to the transimpedance-amplifier circuitries in the LSI. The signals from the photodiodes triggered of the circuitries at 5 GHz. Since electrooptical modulators consume the most power in on-chip optical interconnect systems and require a large footprint, they are critical to establish on-chip optical interconnection. Two approaches are investigated: 1) an architecture using a fewer number of modulators and 2) high electrooptical coefficient materials.

Recently, there has been significant research interest in homogeneous modular robots that can transform (i.e. reconfigure their overall shape). However, many of the proposed transformation mechanisms are too expensive and complex to be practical. The transformation process is also normally slow, and therefore the mechanisms are not suitable for situations where frequent, quick reconfiguration is required. To solve these problems, we have studied a transformable mobile robot composed of multiple homogeneous gear-type units. Each unit has only one actuator and cannot move independently. But when engaged in a swarm configuration, units are able to move rapidly by rotating around one another. The most important problem encountered when developing our multi-module robot was determining how units should join together. We designed a passive attachment mechanism that employs a single, six-pole magnet carried by each unit. Motion principles for the swarm were confirmed in simulation, and based on these results we constructed a series of hardware prototypes. In our teleoperation experiments we verified that a powered unit can easily transfer from one stationary unit to another, and that the swarm can move quickly in any direction while transforming.

This paper describes the compiler that we have developed in this study for high-speed simulation of cellular automata (CA). CA is a powerful method to understand and simulate the behavior of complex systems. CA is temporal and spatial discrete system. Updating many cells' state valves at high speed is needed for a high precision simulation. SIMD instructions can accelerate CA simulations because each cell can be updated simultaneously in CA theory. The compiler generates a high speed simulator using MMX technology. MMX technology is one of SIMD technologies and enables to process many operations by a single instruction. The compiler generates a simulator from the description of local rules in DORA language. We designed DORA language for cording local rules with simple description naturally. We ran the performance test of the simulator generated by our compiler. The results showed that the simulators generated by our compiler runs about 3 to 11 times faster than ones with C compiler.

The objective is to propose an immune distributed competitive problem solver using MHC and an immune network and to verify its validity by means of computer simulations. Our algorithm solves the division-of-labor issues and problems for each agent work domain in a multi-agent system (MPS) by two immune functions. First, the Major Histocompatibility Complex (MHC) distinguishes "self" from "nonself", used in the process of eliminating states of competition. Second, the immune network that produces specific antibodies by modification of immune cells is used to produce adaptive behaviors for agents. Then, to investigate the validity of the proposed method, this algorithm is applied to the "N-th agent travelling salesmen problem (n-TSP)" as a typical case problem for multi-agent systems. The effectiveness of solving multi-agent system problems in this way is clarified through some simulations.

As the neural networks or genetic algorithms, adaptive algorithms become popular and these techniques are applied to many kinds of optimization problems. The immune system is one of the adaptive biological system whose functions are to identify and to eliminate foreign material. In this paper, we propose an optimization algorithm based on immune model and applied to the n-th agents' travelling salesman problem called n-TSP. Some computer simulations are designed to investigate the performance of the immune algorithm. The results of simulations represent that the immune algorithm shows good performance for the combinatorial optimization problems.

Recently, a disturbance observer based controller has been widely used in the industrial world because of its simplicity. However, this method depends on the intuitive approach in determining the disturbance estimation filter, and therefore, more systematic approach is desired. In this paper, we first combine the generalized compensator and the disturbance observer based controller by clarifying the internal structure of the generalized 2-degree-of-freedom (DOF) compensator. Secondly, based on the clarified structure, we derive a robust stability condition, and propose the design algorithm of a free parameter taking into account the condition. The proposed design algorithm is easy to implement and, as a result, we obtain a lower order free parameter than that of the conventional design algorithm. Thirdly, we show by adopting an appropriate coprime factorization that the clarified structure can also be regarded as an extended version of the conventional PD compensator. Finally, we apply the proposed algorithm to a positioning control of a 3-DOF direct drive robot, and show some experimental results to verify the effectiveness of the proposed algorithm.

This paper proposes an alternative control scheme for a teleoperation system which consists of a master arm, a slave arm and a virtual environment. For a given task, the operator manipulates a virtual environment and executes the task, a skill for the task is extracted through the manipulation, and the skill is transferred to the remote site to execute the task in real. First, the authors consider the design of a control algorithm for a master arm manipulating the virtual environment so that the system has a given dynamics for the operator and the environment. Then the authors consider the design of a control algorithm for the master-slave system manipulating the real environment so that the system has the same dynamics given to the manipulator of the virtual environment. By designing a control scheme, with which the master arm with a real environment and the master arm with a virtual environment have the same dynamics, the skill extracted from the operation of the virtual environment would be applied to the real task using the slave arm. The proposed control system is applied to an experimental master-slave manipulator and experimental results illustrate the effectiveness of the system.>

The transitional motion when a robotic manipulator and a workpiece first make contact is fundamental and occurs frequently. The authors propose a learning controller to improve the contact motion. The learning controller has two features. It observes input and output signals at different periods to improve the transient response of the system; and it can modify an initial state of the system, which includes an approaching velocity of the manipulator. By modifying the approach velocity, a fine contact motion can be achieved, because the magnitude of the impact force depends on the approach velocity. Simulation results verify the effectiveness of the proposed method.>

Image binarization is a task to convert gray-level images into bi-level ones. Its underlying notion can be simply thought of as threshold selection. However, the result of binarization will cause significant influence on the process of image recognition or understanding. In this paper we discuss a new binarization method, named CMB (connectionist model binarization), which uses the connectionist model. In the method a gray-level histogram is input to a multilayer network trained with the back-propagation algorithm to obtain a threshold which gives a visually suitable binarized image. From the experimental results, it was verified that CMB is an effective binarization method in comparison with other methods.

The application of a connectionist model to an image binarization method called connectionist model binarization (CMB) is discussed. CMB employs a multilayer network of a connectionist model whose input and output are a histogram and a desirable threshold for binarization, respectively. This network is trained with a back-propagation algorithm to output a threshold which gives a visually suitable binarised image against any histogram. The details of CMB are described, and its learning strategy and binarization performance are discussed.>

The authors present the visiting card understanding system, whose output is suitable for the input of a visiting-card database. The system consists of two modules. One is a document model which represents the hierarchical knowledge about the layout structure of visiting cards. The other is an understanding module which interprets the document model to general and test hierarchical hypotheses about the contents of a visiting card. Since the understanding module is fundamentally independent of document type, the system is applicable to many kinds of documents.>