The Double-Sided Rugged poly Si (DSR) technology has been developed for high density DRAMs. The DSR technology was achieved using transformation of rugged poly Si caused by ion implantation. The DSR can increase the surface area of the storage electrode, because it has rugged surfaces on both upper and lower sides. The 2-FINs STC (STacked Capacitor cell) with DSR was fabricated in the cell size of 0.72 µm2, and it is confirmed that the DSR can increase the surface area 1.8 times larger than that of smooth poly Si. It is expected that 25 fF/bit is obtained with a 300 nm-thick storage electrode. These effects show that sufficient capacitance for 256 Mb DRAMs is obtained with a low storage electrode. It is confirmed that there is no degradation in C-V and I-V characteristics. Moreover, the DSR needs neither complicated process steps nor special technologies. Therefore, the DSR technology is one of the most suitable methods for 256 Mb DRAMs and beyond.

We developed an eye-contact technique using a blazed half-transparent mirror (BHM), which is a micro-HM array arranged on the display surface, to make a compact eye-contact videophone. This paper describes a new BHM structure that eliminates ghosts and improves image quality. In the new BHM, the reflection and transmission areas are separated to exclude ghosts from appearing in the captured image. We evaluated the characteristics of the captured and displayed images. The results show that the contrast ratio of the captured image and the brightness of both captured and displayed images are much better than with the previous BHM.

A parallel overlapping preconditioner is applied to ICCG method and the effect of the parallel preconditioning on the convergence of the method is investigated by solving large scale block tridiagonal linear systems arising from the discretization of Poisson's equation. Compared with the original ICCG method, the parallel preconditioned ICCG method can solve the problems in high parallelism with slight increasing the number of iterations. Furthermore, the speedup and the efficiency are evaluated for the parallel preconditioned ICCG method by substituting the experimental results into formulae of complexity. For example, when a domain of simulation is discretized on a 250250 rectangular grid and the preconditioner is divided into 249 smaller ones, its speedup is 146.3 with the efficiency 0.59.

This paper investigates the problem of scheduling parallel tasks" with consideration of communication cost on an m-processor system, where processors are assumed to be identical and tasks being scheduled are independent such that they can run on more than one processor simultaneously. Once a task is processed in parallel, its finish time will be speeded up, but communication cost will also be incurred and should be taken into account. To find a schedule with minimum finish time for the parallel tasks scheduling problem is NP-hard. Therefore, in this paper, we will propose a heuristic algorithm for this kind of problem and derive its performance bounds for two different cases of applications, respectively.

Connection Admission Control (CAC) is a key part of traffic control and still leaves several challenging problems peculiar to ATM networks. One of these problems is how to assign sufficient bandwidth for any cell arrival process that satisfies the source traffic descriptor values specified by negotiation between the network and a user at the connection setup. Because the source traffic descriptor cannot describe the actual source traffic characteristics completely, it has already been studied extensively that how to estimate sufficient bandwidth under the assumption that the actual traffic parameter values in the source traffic descriptor are equal to the negotiated values. This paper extends the studies in the literature to how to estimate sufficient bandwidth only assuming that the actual values satisfy the negotiated values, that is the actual values is less than or equal to the negotiated values. We show the sufficient condition for negotiated source traffic descriptors ensuring that the cell-loss ratio calculated from the negotiated values is always the upper-bound of the actual cell-loss ratio. Using this condition, we propose a CAC that can guarantee cell-loss ratio objective so far as a user satisfies the source traffic descriptor values.

This paper presents a method for spatial and temporal segmentation of long image sequences which include multiple independently moving objects, based on the Minimum Description Length (MDL) principle. By obtaining an optimal motion description, we extract spatiotemporal (ST) segments in the image sequence, each of which consists of edge segments with similar motions. First, we construct a family of 2D motion models, each of which is completely determined by its specified set of equations. Then, based on these sets of equations we formulate the motion description length in a long sequence. The motion state of one object at one moment is determined by finding the model with shortest description length. Temporal segmentation is carried out when the motion state is found to have changed. At the same time, the spatial segmentation is globally optimized in such a way that the motion description of the entire scene reaches a minimum.

We define a new framework for rewriting graphs, called a formal graph system (FGS), which is a logic program having hypergraphs instead of terms in first-order logic. We first prove that a class of graphs is generated by a hyperedge replacement grammar if and only if it is defined by an FGS of a special form called a regular FGS. In the same way as logic programs, we can define a refutation tree for an FGS. The classes of TTSP graphs and outerplanar graphs are definable by regular FGSs. Then, we consider the problem of constructing a refutation tree of a graph for these FGSs. For the FGS defining TTSP graphs, we present a refutation tree algorithm of O(log2nlogm) time with O(nm) processors on an EREW PRAM. For the FGS defining outerplanar graphs, we show that the refutation tree problem can be solved in O(log2n) time with O(nm) processors on an EREW PRAM. Here, n and m are the numbers of vertices and edges of an input graph, respectively.

This paper describes the method of applying the integral form of Maxwell's equations to the transmission-line network used in the spatial network method for the modeling of curved conductor surfaces. The techniques of dealing with the transmission-line network near cylindrical conductor surface are explained in detail. To compare exact solutions with computed values, a cylindrical cavity resonator is analysed. The resonant frequencies and unloaded Q's for the computed three modes are obtained with the error of about 1%. Moreover, applying this treatment to the waveguide with magnetron anodeshape cross section, a cutoff-constant is computed successfully. It is found that the treatment proposed in this paper can be used as the method for modeling of curved conductor surface in the spatial network method. It is also considered that this treatment can be extend to TLM method.

Broadband antennas such as biconical antennas and log-periodic dipole antennas are generally used in automatic EMC measurements. However, these broadband antennas have not been used for accurate measurement because accurate specifications for them are lacking. Therefore, more accurate analysis is urgently required by the CISPR (International Special Committee on Radio Interference), to establish the specifications for broadband antennas for EMC measurements. In this paper, the AF of biconical antennas is calculated by using Moment Methods. The frequency characteristics and antenna height dependency of AF are presented. AF is also measured and compared to the data obtained by the calculations. Good agreement between the calculations and measurements is achieved, indicating the usefulness of our computation method. In addition, the effect of antenna separation distance and transmitting antenna height on AF is investigated. The calculated AF deviation from the reference value is nearly 0dB except for certain antenna arrangements. In these antenna arrangements, the field becomes null at the receiving antenna and widely varies in magnitude and phase around the null points. Therefore, the antenna is immersed in a non-uniform field, while the AF is defined on the assumption of a uniform field. Consequently, the erroneous AF will be derived from measurements around these null points and it will be greatly different from that obtained at other antenna heights. Thus, it is better to avoid these conditions during actual measurements. The effect of the ground plane on AF is also evaluated. AF is shown to be seriously affected by the ground plane especially at frequencies around 90MHz. It should be noted that AF deviation has crests corresponding to the null field at 300MHz. The obtained data will be useful in establishing specifications of biconical antennas for EMC measurements.

A system for measuring the low frequency amplitude and phase noises was set-up, with employing a phase sensitive detector and phase-shifter. It is noted that both noises were partly correlated. The phase noise was explained by the transit time fluctuation due to the fluctuating diffusion coefficient. The amplitude noise reduction was demonstrated by applying the inverted output of the phase noise to the amplitude noise.

Recognition of hand drawn shapes is beneficial in drawing packages and automated sketch entry in hand-held computers. Although it is possible to store and retrieve drawings through the use of electronic ink, further manipulation of these drawings require recognition to be performed. In this paper, we propose a new approach to invariant geometric shape recognition which utilizes a fuzzy function to reduce noise and a neural network for classification. Instead of recognizing segments of a drawing and then performing syntactical analysis to match with a predefined shape, which is weak in terms of generalization and dealing with noise, we examine the shape as a whole. The main concept of the recognition method is derived from the fact that internal angles are very important in the perception of the shape. Our application's aim is to recognize and correctively redraw hand drawn ellipses, circles, rectangles, squares and triangles. The neural network learns the relationships between the internal angles of a shape and its classification, therefore only a few training samples which represent the class of the shape is sufficient. The results are very successful, such that the neural network correctly classified shapes which were not included in the training set.

This paper describes an advanced rule-embedded neural network (RENN+) that has an extended framework for achieving a very tight integration of learning-based neural networks and rule-bases of existing if-then rules. The RENN+ is effective in pattern recognition with ill-posed conditions. It is basically composed of several component RENNs and an output RENN, which are three-layer back-propagation (BP) networks except for the input layer. Each RENN can be pre-organized by embedding the if-then rules through translation of the rules into logic functions in a disjunctive normal form, and can be trainded to acquire adaptive rules as required. A weight-modification-reduced learning algorithm (WMR) capable of standard regularization is used for the post-training to suppress excessive modification of the weights for the embedded rules. To estimate the effectiveness of the proposed RENN+, it was used for pattern recognition in a radar system for detection of buried pipes. This trial showed that a RENN+ with two component RENNs had good recognition capability, whereas a conventional BP network was ineffective.

An efficient algorithm is given for finding all solutions of piecewise-linear resistive circuits containing nonseparable transistor models such as the Gummel-Poon model or the Shichman-Hodges model. The proposed algorithm is simple and can be easily programmed using recursive functions.

For symmetric cryptosystems, their transformations should have nonlinear elements to be secure against various attacks. Several nonlinearity criteria have been defined and their properties have been made clear. This paper focuses on, among these criteria, the propagation criterion (PC) and the strict avalanche criterion (SAC), and makes a further investigation of them. It discusses the sets of Boolean functions satisflying the PC of higher degrees, the sets of those satisfying the SAC of higher orders and their relationships. We give a necessary and sufficient condition for an n-input Boolean function to satisfy the PC with respect to a set of all but one or two elements in {0,1}n{(0,...,0)}. From this condition, it follows that, for every even n 2, an n-input Boolean function satisfies the PC of degree n 1 if and only if it satisfies the PC of degree n. We also show a method that constructs, for any odd n 3, n-input Boolean functions that satisfy the PC with respect to a set of all but one elements in {0,1}n{(0,...,0)}. This method is a generalized version of a previous one. Concerned with the SAC of higher orders, it is shown that the previously proved upper bound of the nonlinear order of Boolean functions satisfying the criterion is tight. The relationships are discussed between the set of n-input Boolean functions satisfying the PC and the sets of those satisfying the SAC.

We propose a new compaction problem that allows layout elements to have many shape possibilities. The objective of the problem is to find not only positions but also shapes of layout elements. We present an efficient method to solve the problem--compaction with shape optimization. This method simplifies the problem by considering the optimization of shapes only for the layout elements on a critical path. The layout is compacted step by step while optimizing the shapes of layout elements. Another importance of this compaction technique is that it makes layout to be "recyclable" for other set of device parameters. The experimental examples, which attempt shape optimization and recycle of analog layout, confirms the importance and efficiency of our method.

In this letter, we demonstrate an experimental CMOS neural circuit towards an understanding of how particular computations can be performed by a T-Model neural network. The architecture and a digital hardware implementation of the learning T-Model network are presented. Our experimental results show that the T-Model allows immense collective network computations and powerful learning.

This paper presents a new microprocessing method that uses a Cl2 fast atom beam (FAB) with stainless steel (SUS304) patterned masks. This new method uses the patterned mask instead of lithographically processed patterned photoresist materials employed in the conventional FAB microprocessing method. We examined the performance of this method by etching GaAs workpieces under various conditions: (1) by setting the distance between the mask surface and flat workpiece surface, L, from 0 µm to 500 µm; (2) by setting the angle between the FAB axis and the flat workpiece surface, θ; to either 30or 50. (3) by etching a workpiece surface that had a 15-µm step and two different surface textures, smooty and undulated; and (4) by doing overlapped etching using a square-patterned mask first and then a circular-patterned mask. The experiments show that the accuracy of reproducing the mask pattern on the etched surface increases with decreasing L. Moreover, the etching rate is almost the same (L100 µm) and decreases slightly at longer distance (L100 µm). The experiments also show that the side walls of the surface are parallel to the FAB axis, even for θ0, indicating that anisotropic etching can be achieved. The experiments for the stepped surface with different surface textures show the surface texture is not affected by the FAB etching. The overlapped etching experiments show that FAB etching is capable of producing overlapped structures. These results demonstrate that this new FAB method can be used in the microproduction of multi-faced, overlapped, three-dimensional microstructures.

Effects of various joint configurations and gap sizes on the electromagnetic shielding effectiveness (SE) are evaluated to provide guidelines for best design of joints in order to increase the value of SE. Four different joint geometries are presented. A sharp decrease on SE with larger gap size for simple joints is observed. Addition of bends in the joint geometry has strong positive effect on the value of the SE. Increasing the angle of cut, which increases the effective length of the joint were also demonstrated to have increasing effect on the shielding performance.

In this paper, a new off-line handwritten word recognition method based on the explicit modeling of character junctures is presented. A handwritten word is regarded as a sequence of characters and junctures of four types. Hence both characters and junctures are explicitly modeled. A handwriting system employing hidden Markov models as the main statistical framework has been developed based on this scheme. An interconnection network of character and ligature models is constructed to model words of indefinite length. This model can ideally describe any form of hamdwritten words including discretely spaced words, pure cursive words, and unconstrained words of mixed styles. Also presented are efficient encoding and decoding schemes suitable for this model. The system has shown encouraging performance with a standard USPS database.

Wavelength-division multiplexing (WDM) optical switching networks are one of most attractive technologies in optical interconnections. By combining with time-division multiplexing (TDM) and space-division multiplexing (SDM) technologies, remarkably high-throughput interconnections may be accomplished. In this paper, we propose WDM switching networks with time-division multiplexed optical signals by using free-space optics. We also propose novel WDM interconnections, including multiple-wavelength light-sources, optical fibers and wavelength-selectable detectors. We successfully confirmed basic principles for the WDM interconnections.