In real life, our sence of social reality is supported by the institutional basis, group/interpersonal basis, and belief/schema basis. In networked life, in contrast, these natural and ordinary bases are not always warranted because of a lack of institutional backup, the fragility of the group or interpersonal environment, and the noncommonality of our common sense. In order to compensate for these incomplete bases, networkers ar seeking adaptive communication styles. In this process, there emerge three types of communication cultures. One is the name-card exchange" type. This type is realized by communicating our demographic attributes verbally, which is useful for reality construction of the institutional basis. The second is the ideographization" type. In this type, the content of customary nonverbal communication is creatively transformed into various pseudo nonverbal or para-linguistic expressions, which strengthen fragile interpersonal relationships. The last type is the verbalian" type. This type never depends on the interpersonal or institutional basis. The networked reality is constructed solely in the attempt for common sense development among members. By analyzing the content of messages exchanged in four public groups called Forums," the author found that patterns of communication are transformed in a manner adaptive to each Forum's reality. Thier adaptation modes are different and depend on the types of communication culture every Forum pursues. This is contrarty to the psychologists' tendency to assume that there must be common characteristics or rules valid throughout all of the electronic communication situations.

A programmable clock generator, based on a phase-locked loop (PLL) circuit, has been developed with 0.5 µm CMOS triple-layer Al interconnection technology for use as an on-chip clock generator in a 300-MHz video signal processor. The PLL-based clock generator generates a clock signal whose frequency ranges from 50 to 350 MHz which is an integral multiple, from 2 to 16, of an external clock frequency. In order to achieve stable operation within this wide range, a voltage controlled oscillator (VCO) with selectable low VCO gain characteristics has been developed. Experimental results show that the clock generator generates a 297-MHz clock with a 27-MHz external clock, with jitter of 180 ps and power dissipation of 120 mW at 3.3-V power supply, and it can also oscillate up to 348 MHz with a 31.7-MHz external clock.

A 3.2 GHz, 50 mW, 1 V, GaAs clock pulse generator (CG) based on a phase-locked loop (PLL) circuit has been designed for use as an on-chip clock generator in future high speed processor LSIs. 0.5 µm GaAs MESFET and DCFL circuit technologies have been used for the CG, which consists of 224 MESFETs. An "enhanced charge-up current" inverter has been specially designed for a low power and high speed voltage controlled oscillator (VCO). In this new inverter, a voltage controlled dMESFET is combined in parallel with the load dMESFET of a conventional DCFL inverter. This voltage controlled dMESFET produces an additional charge-up current resulting in the new VCO obtaining a much higher oscillation frequency than that of a ring oscillator produced with a conventional inverter. With a single 1 V power supply (Vdd), SPICE calculation results showed that the VCO tuning range was 2.25 GHz to 3.65 GHz and that the average VCO gain was approximately 1.4 GHz/V in the range of a control voltage (Vc) from 0 to 1 V. Simulation also indicated that at a Vdd of 1 V the CG locked on a 50 MHz external clock and generated a 3.2 GHz internal clock (=50 MHz64). The jitter and power dissipation of the CG at 3.2 GHz oscillation and a Vdd of 1 V were less than 8.75 psec and 50 mW, respectively. The typical lock range was 2.90 GHz to 3.59 GHz which corresponded to a pull-in range of 45.3 MHz to 56.2 MHz.

This paper discusses pulse responses of multi-conductor transmission lines terminated by linear and nonlinear subnetworks. At first step, the circuit is partitioned into a linear transmission lines and nonlinear subnetworks by the substitution voltage sources. Then, the linear subnetworks are solved by a well-known phasor technique, and the nonlinear subnetworks by a numerical integration technique. The variational value at each iteration is calculated by a frequency domain relaxation method to the associated linearized time-invariant sensitivity circuit. Although the algorithm can be efficiently applied to weakly nonlinear circuits, the convergence ratio for stiff nonlinear circuits becomes very small. Hence, we recommend to introduce a compensation element which plays very important role to weaken the nonlinearity. Thus, our algorithm is very simple and can be efficiently applied to wide classes of nonlinear circuits.

A single-chip architecture for three-dimensional (3-D) computer graphics (CG) is discussed assuming portable equipment with a 3-D CG interface. Based on a discussion of chip requirements, an architecture utilizing DRAM technology is proposed. A 31-Mbit, on-chip DRAM cell array allows a full-color, 480640-pixel frame with two 3-D frame buffers for double buffering and one 2-D frame buffer for superimposed or background images. The on-chip pixel generator produces R, G, B, and Z data in a triangular polygon with a zigzag-scan interpolation algorithm. The on-chip frame synthesizer combines data from one of the 3-D buffers with that from the 2-D buffer to produce superimposed or background 2-D images within a 3-D CG image. Parallel alpha-blending and Z-comparison circuits attached to the DRAM cell array provide a high data I/O rate. Estimation of the chip performance assuming the 0.35-µm CMOS design rule shows the chip size, the drawing speed, on-chip data I/O rate, and power dissipation would be 1413.5-mm, 0.25 million polygons/s, 1 gigabyte/s, and 590 mW at a voltage of 3.3 V, respectively. Based on circuit simulations, the chip can run on a 1.5-V dry cell with a drawing speed of 0.125 million polygons/s and a power dissipation of 61 mW. A scaled-down version of the chip which has an 1-kbit DRAM cell array with an attached alpha-blending circuit is being fabricated for evaluation.

Processing elements (PEs) with a dynamically reconfigurable pipeline architecture allow the high-speed calculation of widely used neural model which is multi-layer perceptrons with the backpropagation (BP) learning rule. Its architecture that was proposed for a single chip is extended to multiprocessors' structure. Each PE holds an element of the synaptic weight matrix and the input vector. Multi-local buses, a swapping mechanism of the weight matrix and the input vector, and transfer commands between processor elements allow the implementation of neural networks larger than the physical PE array. Estimated peak performance by the measurement of single processor element is 21.2 MCPS in the evaluation phase and 8.0 MCUPS during the learning phase at a clock frequency of 50 MHz. In the model, multi-layer perceptrons with 768 neurons and 131072 synapses are trained by a BP learning rule. It corresponds to 1357 MCPS and 512 MCUPS with 64 processor elements and 32 neurons in each PE.

This paper proposes the concept of Tool-Based Direct Deformation Method (TB-DDM) which supports networked CAD (Computer Aided Design) systems with virtual reality technologies. TB-DDM allows designers to sculpt free forms directly with tools; each tool has its deforming characteristics, such as, the area and the shape of deformation. TB-DDM's direct deformation interface is independent of form representations because the system automatically calculates appropriate deformation according to its form representation when a tool pushes" a form. The deformation with TB-DDM is concisely described by the initial shape, types of tools, and thier loci; the description enables cooperative CAD systems with narrow bandwidth network to share design process rapidly and to distribute computational load.

This letter proposes the method using a filter to suppress the very large noise obstructive to the radio pulsar surveys. This noise suppression filter is constructed from the average of the amplitude spectrum of pulsar signal for each channel. Using this method, the dispersion measure, one of the important parameters in the pulsar surveys, can easily be extracted.

With advances in the speed, bandwidth and reliability of telecommunications networks and in the performance of workstations, distributed processing has become widespread. Information sharing among distributed nodes and its mutual exclusion are of great importance for efficient distributed processing. This paper systematizes and quantitizes a shared memory called Data-Cyclic Shared Memory (DCSM) from the viewpoints of memory organization and access mode. In DCSM, the propagation delay of transmission lines and the data relaying delay in each node are used for information storage, and memory information encapsuled in the form of "memory cells" circulates infinitely in a logical ring type network. The distinctive feature of DCSM, in addition to the way data is stored, is that data and the access control are completely distributed, which contrasts with existing memory where both are centralized. Therefore, there are no performance bottlenecks caused by concentrating memory access. Distributed Shared Memory (DSM), which has a scheme similar to DCSM's, has also been proposed for distributed environments. In DSM, the data is also distributed but the control for accessing each data is centralized. From the viewpoints of memory organization and the access method, DCSM is very flexible. For instance, word length can be spatially varied by defining data size at each address, and each node can be equipped with mechanisms for special functions such as the content address specification and asynchronous report of change in contents. Because of this flexibility, it can be called a "software-defined memory." The analysis also reveals that DCSM has the disadvantages of large access delay and small memory capacity. The capacity can be enlarged by inserting FIFO type queues into the circulation network, and the delay can be shortened by circulating replicas of original memory cells. However, there is a trade off between the maximal capacity and the mean access time. DCSM has many potential applications, such as in the mutual exclusion control of distributed resources.

Numerical simulations for the (3+1)-dimensional optical-field dynamics of nonstationary pulsed beams that propagate down Kerr-like nonlinear channel waveguides are carried out for what is to our knowledge the first time. Time-resolved intrapulse switching due to spontaneous symmetry breaking of optical fields from a quasilinear symmetric field to a nonlinear asymmetric field is analyzed. A novel instability phenomenon triggered by the symmetry breakdown is found.

We have classified parenchymal echo patterns of cirrhotic liver into 3 types, according to the size of hypoechoic nodular lesions. We have been studying an ultrasonic image diagnosis system using the three–layer back–propagation neural network. In this paper, we will describe the applications of the neural network techniques for recognizing and classifying chronic liver disease, which use the nodular lesions in the Proton density and T2–weighed magnetic resonance images on the gray level of the pixels in the region of interest.

This paper describes a segmentation method of liver structure from abdominal CT images using a three–layered neural network (NN). Before the NN segmentation, preprocessing is employed to locally enhance the contrast of the region of interest. Postprocessing is also automatically applied after the NN segmentation in order to remove the unwanted spots and smooth the detected boundary. To evaluate the performance of the proposed method, the NN–determined boundaries are compared with those traced by two highly trained surgeons. Our preliminary results show that the proposed method has potential utility in automatic segmentation of liver structure and other organs in the human body.

Numerical studies of reaction–diffusion systems which consist of chaotic oscillators are carried out. The Rössler oscillators are used, which are arranged two–dimensionally and coupled by diffusion. Pacemakers where the average periods of the oscillators are artificially changed are set to produce target patterns. It is found that target patterns emerge from pacemakers and grow up as if they were in a regular oscillatory medium. The wavelength of the pattern can be varied and controlled by changing the parameters (size and frequency) of the pacemaker. The behavior of the coupled system depends on the size of the system and the strength of the pacemaker. When the system size is large, the Poincar return maps show that the behavior of the coupled system is not simple and the orbit falls into a high–dimensional attractor, while for a small system the attractor is rather simple and a one–dimensional map is obtained. Moreover, for appropriate strength of pacemakers and for certain sizes of the systems the oscillations become periodic. It is also found that the largest and local Lyapunov exponents of the system are positive and these values are uniformly distributed over the pattern. The values of the exponents are smaller than that of the uncoupled Rössler oscillator; this is due to the fact that the diffusion reduces the exponents and modifies the form of the attractor. We conclude that the large scale patterns can stably exist in the chaotic medium.

A systematic method for locating and computing branches of connecting orbits developed by the authors is outlined. The method is applied to the sine–Gordon and Hodgkin–Huxley equations.

We prove that the maximum likelihood estimator for estimating 3-D motion from noisy optical flow is not optimal", i.e., there is an unbiased estimator whose covariance matrix is smaller than that of the maximum likelihood estimator when a Gaussian noise distribution is assumed for a sufficiently large number of observed points. Since Gaussian assumption for the noise is given, the maximum likelihood estimator minimizes the mean square error of the observed optical flow. Though the maximum likehood estimator's covariance matrix usually reaches the Cramér-Rao lower bound in many statistical problems when the number of observed points is infinitely large, we show that the maximum likelihood estimator's covariance matrix does not reach the Cramér-Rao lower bound for the estimation of 3-D motion from noisy optical flow under such conditions. We formulate a superior estimator, whose covariance matrix is smaller than that of the maximum likelihood estimator, when the variance of the Gaussian noise is not very small.

Recognizable series is a model of a sequential machine. A recognizable series S is represented by a triple (λ,µ,γ), called a linear representation of S, where λ is a row vector of dimension n specifying the initial state, γ is a column vector of dimension n specifying the output at a state, and µ is a morphism from input words to nn matrices specifying the state transition. The output for an input word w is defined as λ(µw) γ, called the coefficient of w in S, and written as (S,w). We present an algorithm which constructs a reduced linear representation of an unknown recognizable series S, with coefficients in a commutative field, using coefficient queries and equivalence queries. The answer to a coefficient query, with a word w, is the coefficient (S, w) of w in S. When one asks an equivalence query with a linear representation (λ,µ,γ), if (λ,µ,γ) is a linear representation of S, yes is returned, and otherwise a word c such that λ (µc) γ(S, c) and the coefficient (S, c) are returned: Such a word c is called a counterexample for the query. For each execution step of the algorithm, the execution time consumed from the initial step to the current step is O(mN 4M), where N is the dimension of a reduced linear representation of S, M is the maximum time consumed by a single fundamental operation (addition, subtraction, multiplication or division), and m is the maximum length of counterexamples as answers to equivalence queries returned until that step.

This paper describes a noise resistant algorithm for estimating 3-D rigid motion from optical flow. We first discuss the problem of constructing the objective function to be minimized. If a Gaussian distribution is assumed for the niose, it is well-known that the least-squares minimization becomes the maximum likelihood estimation. However, the use of this objective function makes the minimization procedure more expensive because the program has to go through all the points in the image at each iteration. We therefore introduce an objective function that provides unbiased estimators. Using this function reduces computational costs. Furthermore, since good approximations can be analytically obtained for the function, using them as an initial guess we can apply an iterative minimization method to the function, which is expected to be stable. The effectiveness of this method is demonstrated by computer simulation.

Given a sorted set S of n points in the plane, the prefix convex hulls problem of S is to compute the convex hull for every prefix set of S. We present a parallel algorithm for this problem. Our algorithm runs in O(logn) time using n/logn processors in the CREW PRAM computational model. The algorithm is shown to be time and cost optimal. One of the techniques we adopt to achieve these optimal bounds is the use of a new parallel data structure Array-Tree.

The sidelobe canceler in radar systems is a highly computational demanding problem. It can be efficiently tackled by resorting to the QR decomposition mapped onto a systolic array processor. The paper reports several mapping strategies by using massive parallel computers available on the market. MIMD as well as SIMD machines have been used, specifically MEIKO Computing Surface, nCUBE2, Connection Machine CM-200, and MasPar MP-1. The achieved data throughput values have been measured for a number of operational situations of practical interest.

In this paper, we first discuss on a framework for a 3D image display system which is the combination of passive sensing and active display technologies. The passive sensing enables to capture real scenes under natural condition. The active display enables to present arbitrary views with proper motion parallax following the observer's motion. The requirements of passive sensing technology for 3D image displays are discussed in comparison with those for robot vision. Then, a new stereo algorithm, called SEA (Stereo by Eye Array), which satisfies the requirements is described in detail. The SEA uses nine images captured by a 33 camera array. It has the following features for depth estimation: 1) Pixel-based correspondence search enables to obtain a dense and high-spatial-resolution depth map. 2) Correspondence ambiguity for linear edges with the orientation parallel to a particular baseline is eliminated by using multiple baselines with different orientations. 3) Occlusion can be easily detected and an occlusion-free depth map with sharp object boundaries is generated. The feasibility of the SEA is demonstrated by experiments by using real image data.