Effect of a disparity pattern on the perception of direction: Non-retinal information masks retinal information

AbstractThe direction of an object can theoretically be determined from the binocular disparity information alone. However, there is no certain empirical evidence for this. This study examines whether the binocular disparity information alters the perceived direction. Observers make an effort to rotate their eyes beyond their movable limit for a while before observing the display. This is done to alter the reliability of the eye position signal from proprioception and efference copy. The results show that the perceived direction changes according to the amount of disparity information in the stimulus

Element Material Exposure Experiment by EFFU

The National Space Development Agency of Japan (NASDA) is planning to perform an 'Element Material Exposure Experiment' using the Exposed Facility Flyer Unit (EFFU). This paper presents an initial design of experiments proposed for this project by our company. The EFFU is installed on the Space Flyer Unit (SFU) as a partial model of the Space Station JEM exposed facility. The SFU is scheduled to be launched by H-2 rocket in January or February of 1994, then various tests will be performed for three months, on orbit of 500 km altitude, and it will be retrieved by the U.S. Space Shuttle and returned to the ground. The mission sequence is shown

A virtual work space for both hands manipulation with coherency between kinesthetic and visual sensation

This paper describes the construction of a virtual work space for tasks performed by two handed manipulation. We intend to provide a virtual environment that encourages users to accomplish tasks as they usually act in a real environment. Our approach uses a three dimensional spatial interface device that allows the user to handle virtual objects by hand and be able to feel some physical properties such as contact, weight, etc. We investigated suitable conditions for constructing our virtual work space by simulating some basic assembly work, a face and fit task. We then selected the conditions under which the subjects felt most comfortable in performing this task and set up our virtual work space. Finally, we verified the possibility of performing more complex tasks in this virtual work space by providing simple virtual models and then let the subjects create new models by assembling these components. The subjects can naturally perform assembly operations and accomplish the task. Our evaluation shows that this virtual work space has the potential to be used for performing tasks that require two-handed manipulation or cooperation between both hands in a natural manner

Pattern Classification Using A Fuzzy Immune Network Model

It is generally believed that one major function of immune system is helping to protect multicellular organisms from foreign pathogens, especially replicating pathogens such as viruses, bacteria and parasites. The relevant events in immune system are not only the molecules, but also their interactions. The immune cells can respond either positively or negatively to the recognition signal. A positive response would result in cell proliferation, activation and antibody secretion, while a negative response would lead to tolerance and suppression. Depending upon these immune mechanisms, an immune network model(here, we call it the binary model) based on biological immune response network was proposed in our previous work. However, there are some problems like input and memory in the binary model. In order to improve the binary model, in this paper we propose a fuzzy immune network model. In the proposed fuzzy immune model, we add a normalization B cell layer for normalizing the large-scale antigen information on the base of the binary model. Meanwhile, a fuzzy AND operator(.AND.) and a normalization procedure called complement coding were employed in the proposed fuzzy immune model. Compute simulations illustrate that the proposed fuzzy model not only can improve the problems existing in the binary model but also is capable of clustering arbitrary sequences of large-scale analog input patterns into stable recognition categories. (author abst.

An Engineering Immune Network Model for Pattern Recognition

The biological immune system consists of a multitude of cells and molecules that interact in a variety of ways to detect and eliminate infectious agents. It has several useful mechanisms from the viewpoint of information processing. Our overall goal for this paper is twofold: to understand the real immune system from the information processing perspective, and to use idea generated from the immune system to construct new engineering application. As one example of the latter, we propose an engineering immune network model and apply it to pattern recognition. We test the proposed model by the simulations of alphabet patter recognition. The simulation results illustrate that the proposed model is capable of clustering similar input pattern into stable categories. (author abst.