The purpose of this study is to provide a new approach for detection using bio-impedance. This impedance is measured by the four-electrode method. As the impedance changes resulting from ankle, knee, and hip movements depended heavily on electrode placement, we determined the optimal electrode configurations for those movements by searching for high correlation coefficients, large impedance changes, and minimum interferences in ten subjects (Age: 204). Our optimal electrode configurations showed very strong relationships between the ankle joint angle and ankle impedance (γ = -0.9130.03), between the knee joint angle and knee impedance (γ = 0.9440.02), and between the hip joint angle and hip impedance (γ = 0.8230.08). This study showed the possibility that lower leg movement could be easily measured by impedance measurement system with two pairs of skin-electrodes.

In this paper, we introduce a new technology to extract the unique features from an iris image, which uses scale-space filtering. Resulting iris code can be used to develop a system for rapid and automatic human identification with high reliability and confidence levels. First, an iris part is separated from the whole image and the radius and center of the iris are evaluated. Next, the regions that have a high possibility of being noise are discriminated and the features presented in the highly detailed pattern are then extracted. In order to conserve the original signal while minimizing the effect of noise, scale-space filtering is applied. Experiments are performed using a set of 272 iris images taken from 18 persons. Test results show that the iris feature patterns of different persons are clearly discriminated from those of the same person.

This paper considers a motion planning method for humanoid robots. First, we review a modular state net which is a state net representing behavior of a part of the humanoid robots. Each whole body motion of the humanoid robots is represented by a combination of modular state nets for those parts. In order to obtain a feasible path of the whole body, a timed Petri net is used as an abstracted model of a set of all modular state nets. Next, we show an algorithm for constructing nonlinear dynamics which describes a periodic motion. Finally, we extend the state net in order to represent primitive periodic motions and their transition relation so that we can generate a sequence of primitive periodic motions satisfying a specified task.

In this paper, we propose a formal method for detection of three automation surprises in human-machine interaction; a mode confusion, a refusal state, and a blocking state. The mode confusion arises when a machine is in a different mode from that anticipated by the user, and is the most famous automation surprise. The refusal state is a situation that the machine does not respond to a command the user executes. The blocking state is a situation where an internal event occurs, leading to change of an interface the user does not know. In order to detect these phenomena, we propose a composite model in which a machine and a user model evolve concurrently. We show that the detection of these phenomena in human-machine interaction can be reduced to a reachability problem in the composite model.

In many cryptosystems incorporating human beings, the users' limited memories and their indifference to keeping the systems secure may cause some severe vulnerability of the whole systems. Thus we need more studies on personal entropy, from an information theoretical point of view, to capture the characteristics of human beings as special information sources for cryptosystems. In this paper, we discuss and analyze the use of personal entropy for generating cryptographic keys. In such a case, it is crucially important to precisely evaluate the amount of personal entropy that indicates the actual key length. We propose an advanced key generation scheme based on the conventional graphical passwords proposed in [12]. We improve them to make the most of the secret information extracted in one drawing, i.e., we incorporate the on-line pen pressure and pen inclination information in addition to utilize more secret information. We call the scheme dynamic graphical passwords, and propose a practical construction of them. We also show a precise way of quantifying their entropy, and finally, as an experimental result, we can generate a key of over 110-bit long, using the data of a single drawing. When quantifying their entropy, we need to precisely evaluate the entropy of graphical passwords as well as that of the on-line information of pen movements. We need to precisely evaluate the entropy of graphical passwords by considering the users' biased choices of their graphical passwords. It is expected that they tend to choose their passwords that are memorable as easily as possible, thus we quantify the burden of memorizing each graphical password by the length of its description using a special language based on [12]. We improve the approach in [12] by more directly reflecting how easily each graphical password can be memorized.

Much of the work on faces in computer vision has been focused on face recognition or facial expression analysis, but has not been directly related with face direction detection. In this paper, we propose a vision-based approach to detect a face direction from a single monocular view of a face by using a facial feature called facial triangle, which is formed by two eyebrows and the lower lip. Specifically, the proposed method introduces simple formulas to detect face rotation, horizontally and vertically, using the facial triangle. It makes no assumption about the structure of the face and produces an accurate estimate of face direction.

In this study, a CG animation tool was designed that allows interpolation and extrapolation of two types of repeated motions including finger actions, for quantitative analyses of the relationship between features of human motions and subjective impressions. Three-dimensional human motions are measured with a magnetic motion capture and a pair of data gloves, and then relatively accurate time-series joint data are generated utilizing statistical characteristics. Based on the data thus obtained, time-series angular data of each joint for two dancing motions is transformed into frequency domain by Fourier transform, and spectral shape of each dancing action is interpolated. The interpolation and extrapolation of two motions can be synthesized with simple manner by changing an weight parameter while keeping good harmony of actions. Using this CG animation tool as a motion synthesizer, repeated human motions such as a dancing action that gives particular impressions on the observers can be quantitatively measured and analyzed by the synthesis of actions.

Performance of three binding schemes for memory local to a node is evaluated. Since a large number of cache misses can occur in a large (relative to the cache size) working set, binding at a page fault time alone cannot efficiently utilize locality of reference at the local memory. In a small working set, the address bound to the local memory at a node miss time is not effective due to low cache miss rates. Our simulation shows that binding at a cache miss time achieves up to 3.1 times and 2.4 times performance of the schemes of binding at a page fault time and at a node miss time respectively.

In CC-NUMA multiprocessor systems, it is important to reduce the remote memory access time. Based upon the fact that increasing the size of the LRU second-level (L2) cache more than a certain value does not reduce the cache miss rate significantly, in this paper, we propose two split L2 caches to utilize the surplus of the L2 cache. The split L2 caches are composed of a traditional LRU cache and another cache to reduce the remote memory access time. Both work together to reduce total L2 cache miss time by keeping remote (or long-distance) blocks as well as recently used blocks. For another cache, we propose two alternatives: an L2-RVC (Level 2 - Remote Victim Cache) and an L2-DAVC (Level 2 - Distance-Aware Victim Cache). The proposed split L2 caches reduce total execution time by up to 27%. It is also found that the proposed split L2 caches outperform the traditional single LRU cache of double size.

The number of customers of a service for Internet access from cellular phones in Japan has been explosively increasing for some time. We analyze the relation between the number of customers and the volume of traffic, with a view to finding clues to the structure of human relations among the very large set of potential customers of the service. The traffic data reveals that this structure is a scale-free network, and we calculate the exponent that governs the distribution of node degree in this network. The data also indicates that people who have many friends tend to subscribe to the service at an earlier stage. These results are useful for investigating various fields, including marketing strategies, the propagation of rumors, the spread of computer viruses, and so on.

We have been developing new cycling environments by using knowledge sharing and speech communication. We have offered multimodal knowledge contents to share knowledge on safe and exciting cycling. We accumulated 140 contents, focused on issues such as riding techniques, trouble shootings, and preparations on cycling. We have also offered a new way of speech communication using an ad-hoc wireless LAN technology for safe cycling. Group cycling requires frequent communication to lead the group safely. Speech communication achieves spontaneous communication between group members without looking around or speaking loudly. Experimental result through actual cycling has shown the effectiveness of sharing multimodal knowledge contents and speech communication. Our new developed environment has an advantage of increasing multimodal knowledge through the accumulation of personal experiences of actual cycling.

In 1960, the famous computer pioneer J.C.R. Licklider described a vision for human-computer interaction that he called "man-computer symbiosis. " Licklider predicted the development of computer software that would allow people "to think in interaction with a computer in the same way that you think with a colleague whose competence supplements your own. " More than 40 years later, one rarely encounters any computer application that comes close to capturing Licklider's notion of human-like communication and collaboration. We echo Licklider by arguing that true symbiotic interaction requires at least the following three elements: a complementary and effective division of labor between human and machine; an explicit representation in the computer of the user's abilities, intentions, and beliefs; and the utilization of nonverbal communication modalities. We illustrate this argument with various research prototypes currently under development at Mitsubishi Electric Research Laboratories (USA).

There has recently been considerable interest in research on wearable non-grounded force display. However, there have been no developments for the communication of nonverbal information (ex. tennis and golf swing). We propose a small and lightweight wearable force display to present motion timing and direction. The display outputs a torque using rotational moment and mechanical brakes. We explain the principle of this device, and describe an actual measurement of the torque and torque sensitivity experiments.

The purpose of this study is to design a humanoid robotic hand system that is capable of conveying feelings and sensitivities by finger movement for the non-verbal communication between men and robots in the near future. In this paper, studies have been made in four steps. First, a small-sized and light-weight robotic hand was developed to be used as the humanoid according to the concept of extracting required minimum motor functions and implementing them to the robot. Second, basic characteristics of the movement were checked by experiments, simple feedforward control mechanism was designed based on velocity control, and a system capable of tracking joint time-series change command with arbitrary pattern input was realized. Third, tracking performances with regard to sinusoidal input with different frequencies were studied for evaluation of the system thus realized, and space- and time-related accuracy were investigated. Fourth, the sign language motions were generated as examples of information transmission by finger movement. A series of results thus obtained indicated that this robotic hand is capable of transmitting information promptly with comparatively high accuracy through the movement.

This paper studies the propagation and crossing of signals in cellular automata whose cells are updated at random times. The signals considered consist of a core part, surrounded by an insulating sheath that is missing at the side of the core that corresponds to the direction into which the signal moves. We study two types of signals: (1) signals by which the sheath at the left and right sides of the core advance first in a propagation step, followed by the core, and (2) signals by which the core advances first, followed by the sheath at its left and right sides. These types naturally arise in, respectively, Moore neighborhood cellular automata with semi-totalistic rules and von Neumann neighborhood cellular automata with symmetric transition rules. The type of a signal has a profound impact on the way signals cross each other, as we show by the construction of one signal of each type. The results we obtained should be of assistance in constructing asynchronous circuits on asynchronous cellular automata.

In this paper, a process is described for analysing the motion of a human target in a video stream. Moving targets are detected and their boundaries extracted. From these, a "star" skeleton is produced. Two motion cues are determined from this skeletonization: body posture, and cyclic motion of skeleton segments. These cues are used to determine human activities such as walking or running, and even potentially, the target's gait. Unlike other methods, this does not require an a priori human model, or a large number of "pixels on target". Furthermore, it is computationally inexpensive, and thus ideal for real-world video applications such as outdoor video surveillance.

Faces of a person performing freely in front of the camera can be captured in a sufficient resolution for facial parts recognition by the proposed camera system enhanced with a special PTZ camera. Head region, facial parts regions such as eyes and mouth and the borders of facial parts are extracted hierarchically by being guided by the irises and nostrils preliminarily extracted from the images of PTZ camera. In order to show the effectivity of this system, we proposed a possibility to generate the borders of facial parts of the face for the facial caricaturing and to introduce eye-contacting facial images which can eye-contact bilaterally with each other on the TV conference environment.

A good watermark is known to be perceptually invisible, undetectable without key and robust to spatial/temporal data modification. In this paper, we utilize the characteristics of the human visual system (HVS) for watermarking. In HVS, the response of visual cortex decomposes the image spectra into perceptual channels that are octave bands in spatial frequency. Based on the octave-bands division, same numbers of bits of the watermark are inserted into each channel. Experimental results show that the proposed method based on HVS method gives strong robustness to the attacks compared with conventional DCT, wavelet and DFT watermarking methods.

The instruction set architecture of MBP-light, a dedicated processor for the DSM (Distributed Shared Memory) management of JUMP-1 is analyzed with a real prototype. The Buffer-Register Architecture proposed for MBP-core improves performance with 5.64% in the home cluster and 6.27% in a remote cluster. Only a special instruction for hashing cluster address is efficient and improves the performance with 2.80%, but other special instructions are almost useless. It appears that the dominant operations in the DSM management program were handling packet queues assigned into the local cluster. Thus, common RISC instructions, especially load/store instructions, are frequently used. Separating instruction and data memory improves performance with 33%. The results suggest that another alternative which provides separate on-chip cache and instructions dedicated for packet queue management is advantageous.

Recent years have witnessed a growing interest in employing animated agents for tasks that are typically performed by humans. They serve as communicative partners in a variety of applications, such as tutoring systems, sales, or entertainment. This paper first discusses design principles for animated agents to enhance their effectiveness as tutors, sales persons, or actors, among other roles. It is argued that agents should support their perception as social actors by displaying human-like social cues such as affect and gestures. An architecture for emotion-based agents will be described and a simplified version of the model will be illustrated by two interaction scenarios that feature cartoon-style characters and can be run in a web browser. The second focus of this paper is an empirical evaluation of the effect of an affective agent on users' emotional state which is derived from physiological signals of the user. Our findings suggest that an agent with affective behavior may significantly decrease user frustration.