Materials for a new reinforcement method using an internal heating technique have been developed experimentally for fusion splices. The method employs a protective package of a carbon-fiber composite and a hot-melt adhesive in a heat-shrinkable tube. The most appropriate heating current and heating time were determined from a consideration of the decomposition temperature of the adhesive (300) and the complete shrinking temperature (115) and the minimum welding temperature of Nylon 12 (about 180). The protective package can be installed in less than 30 seconds at a power of 10 W. Air bubbles which might cause microbending were completely eliminated by using Nylon 12 as the hot-melt adhesive, irradiated polyethylene as the heat-shrinkable tube and a carbon-fiber-composite electrical heating rod which also acted a tension member. The key for preparing the carbon-fiber composite was to remove its impurities. Under the condition of temperature difference larger than 40 deg. between the shrinking temperature of the heat-shrinkable tube and the melting temperature of the hot-melt adhesive. Nylon 12 and irradiated polyethylene were needed for the complete elimination of residual bubbles. By using Nylon 12 as the hot-melt adhesive, a reliable protective package could be achieved for a fusion spliced optical fiber with a low excess loss of less than 0.06 dB/splice between -60 and +70 and a high tensile strength of 3.9 kg.

In the field of speech recognition, many researchers have proposed speech recognition methods using auditory information like acoustic signal or visual information like shape and motion of lips. Auditory information has valid features for speech recognition, but it is difficult to accomplish speech recognition in noisy environment. On the other side, visual information has advantage to accomplish speech recognition in noisy environment, but it is difficult to extract effective features for speech recognition. Thus, in case of using either auditory information or visual information, it is difficult to accomplish speech recognition perfectly. In this paper, we propose a method to fuse auditory information and visual information in order to realize more accurate speech recognition. The proposed method consists of two processes: (1) two probabilities for auditory information and visual information are calculated by HMM, (2) these probabilities are fused by using linear combination. We have performed speech recognition experiments of isolated words, whose auditory information (22.05kHz sampling, 8-bit quantization) and visual information (30-frame/s sampling, 24-bit quantization) are captured with multi-media personal computer, and have confirmed the validity of the proposed method.

In this article, a new type of diffusion template and an analogic CNN algorithm using this diffusion template for detecting some lung cancer symptoms in X-ray films are proposed. The performance of the diffusion template is investigated and our CNN algorithm is verified to detect some key lung cancer symptoms, successfully.

In this paper, we propose a method to construct structure models of articulated objects from multiple local observations of their motion using state transition analysis of local geometric constraints. The object model is constructed by a bottom-up approach with three levels. Each level groups sensor data with a constraint among local features observed by the sensor, and constructs the local model. If the sensor data in current model conflict, the model is reconstructed. In each level, the first level estimates a local geometric feature from the local sensor data (eg. edge, feature point) The second level estimates a rigid body from the local geometric feature. The third level estimates an object from the rigid bodies. In the third level, the constraint between rigid bodies is estimated by transition states, which are motions between rigid bodies. This approach is implemented on a blackboard system.

This work presents a further development of the approach to modelling thermal (i.e. carrier-velocity-fluctuation) noise in semiconductor devices proposed in papers by the present authors. The basic idea of the approach is to apply classical theory of Ito's stochastic differential equations (SDEs) and stochastic diffusion processes to describe noise in devices and circuits. This innovative combination enables to form consistent mathematical basis of the noise research and involve a great variety of results and methods of the well-known mathematical theory in device/circuit design. The above combination also makes our approach completely different, on the one hand, from standard engineering formulae which are not associated with any consistent mathematical modelling and, on the other hand, from the treatments in theoretical physics which are not aimed at device/circuit models and design. (Both these directions are discussed in more detail in Sect. 1). The present work considers the bipolar transistor compact model derived in Ref. [2] according to theory of Ito's SDEs and stochastic diffusion processes (including celebrated Kolmogorov's equations). It is shown that the compact model is transformed into the Ito SDE system. An iterative method to determine noisy currents as entries of the stationary stochastic process corresponding to the above Ito system is proposed.

A novel technique is proposed to fabricate a chirped fiber Bragg grating utilizing thermal diffusion of core dopant. The chirped grating is written with a uniform period by using UV exposure technique in the fiber whose effective index of the guided mode varies along its length. Thermal diffusion of the core dopant it employed to realize this change of the effective index. Through the thermal diffusion process, the effective index of the fiber decreases from its initial value. When the grating is written in the diffused core region, its reflection wavelength becomes shorter than that in the non-diffused region. The continuous change of effective index is required for making a chirped grating. The fiber is heated by a non-uniform heat source. When the uniform grating is written in this region, the reflection wavelength smoothly changes along the fiber length although the grating period is constant. By optimizing the fiber parameters to realize a highly chirped grating, we have obtained a typical one whose bandwidth is 14.1 nm at half maximum and maximum rejection in transmission is 29 dB. Additionally, the proposed method has an advantage to control the chirp profile with high mechanical reliability.

We developed a 1200 dots-per-inch light emitting diode array (1200 dpi LED array) chip using a GaAs0.8 P0.2 epitaxial substrate for the first time. One LED array chip consists of 256 LEDs. In general, LED arrays are fabricated by vapor-phase zinc diffusion. From the viewpoint that shallow junctions should be formed to fabricate a very high-density LED array, solid-phase diffusion seems to be more suitable. We fabricated the LED array using selectively-masked solid-phase zinc diffusion, and the diffusion depth was controlled at 1 µm. The diffusion depth was uniform under the diffusion window. The ratio of the length of lateral diffusion to the diffusion depth was about 1.7. These features imply that Zn diffusion was well controlled. In the Zn diffusion, the carrier concentration in the Zn diffusion region was high enough and the sheet resistance of the diffusion region with a diffusion depth of 1 µm was low enough to obtain a sufficient level of emitted light power. The results of performance tests showed that the characteristics of the LED array chip are satisfactory for application in optical printer print heads, because of the array's highly-resolved near-field pattern characteristic, ample emitted light power, low emitted-light-power deviation, and long life.

Petri net is a graphical and mathematical tool for modelling, analysis, verification, and evaluation of discrete event systems. Liveness is one of the most important problems of Petri net analysis. This is concerned with a capability for firing of transitions and can be interpreted as a problem to decide whether the system under consideration is always able to reach a stationary behavior, or to decide whether the system is free from any redundant elements. An asymmetric choice (AC) net is a superclass of useful subclasses such as EFCs, FCs, SMs, and MGs, where SMs admit no synchronization, MGs admit no conflicts, FCs as well as EFCs admit no confusion, and ACs allow asymmetric confusion but disallow symmetric confusion. It is known that an AC net N is live iff it is place-live, but this is not the "initial-marking-based" condition and place-liveness is in general hard to test. For the initial-marking-based liveness for AC nets, it is only known that an AC net N is live if (but not only if) every deadlock in N contains a marked structural trap.

We propose a method to fuse auditory information and visual information for accurate speech recognition. This method fuses two kinds of information by using Iinear combination after calculating two kinds of probabilities by HMM for each word. In addition, we use full-frame color image as visual information in order to improve the accuracy of the proposed speech recognition system. We have performed experiments comparing the proposed method with the method using either auditory information or visual information, and confirmed the validity of the proposed method.

In this article, a new analogic CNN algorithm to extract features of postage stamps in gray-scale images Is introduced. The Gradient Controlled Diffusion method plays an important role in the approach. In our algorithm, it is used for smoothing and separating Arabic figures drawn with a color which is similar to the background color. We extract Arabic figures in postage stamps by combining Gradient Controlled Diffusion with nearest neighbor linear CNN template and logic operations. Applying the feature extraction algorithm to different test images it has been verified that it is also effective in complex segmentation problems

We propose a speech recognition method using fusion of auditory and visual information for accurate speech recognition. Since we use both auditory information and visual information, we can perform speech recognition more accurately in comparison with the case of either auditory information or visual information. After processing each information by HMM, they are fused by linear combination with weight coefficient. We performed experiments and confirmed the validity of the proposed method.

We have developed a neutron imaging system based on the penumbral imaging technique. The system consists of a penumbral aperture and a sensitive neutron detector. The aperture was made from a thick (6 cm) tungsten block with a toroidal taper. It can effectively block 14-MeV neutrons and provide a satisfactory sharp, isoplanatic (space-invariant) point spread function (PSF). A two-dimensional scintillator array, which is coupled with a gated two-stage image intensifier system and a CCD camera, was used as a sensitive neutron detector. It can record the neutron image with high sensitivity and high signal-to-noise ratio. The reconstruction was performed with a Wiener filter. The spatial resolution of the reconstructed neutron image was estimated to be 31 µm by computer simulation. Experimental demonstration has been achieved by imaging 14-MeV deuterium-tritium neutrons emitted from a laser-imploded target.

Recently, some speech recognition methods using fusion of visual and auditory information have been researched. In this paper, a study on the mouth shape image suitable for fusion of visual and auditory information has been described. Features of mouth shape which are extracted from gray level image and binary image are adopted, and speech recognition using linear combination method has been performed. From results of speech recognition, the studies on the mouth shape features which are effective in fusion of visual and auditory information have been performed. And the effectiveness of using two kinds of mouth shape features also has been confirmed.

This letter presents SAM, a multiplexer for ATM's circuit emulation services that can precisely control the cell clumping at the connection-level. Compared with a FIFO (First In First Out) multiplexer, it also improves the connection-level diffusion and CDV (Cell Delay Variation) performance. SAM can therefore significantly increase the number of connections accepted by CAC (Call Admission Control) procedures in the subsequent multiplexer.

This paper discusses crystal-growth and device-design issues associated with the development of high-performance InP/InGaAs heretostructure bipolar transistors (HBTs). It is shown that a highly Si-doped n+-subcollector in the HBT structure causes anomalous Zn redistribution during metalorganic vapor phase epitaxial (MOVPE) growth. A thermodynamical model of and a useful solution to this big problem are presented. A novel hybrid structure consisting of an abrupt emitter-base heterojunction and a compositionally-graded base is shown to enhance nonequilibrium base transport and thereby increase current gain and cutoff frequency fT. A double-heterostructure bipolar transistor (DHBT) with a step-graded InGaAsP collector can improve collector breakdown behavior without any speed penalty. We also elucidate the effect of emitter size shrinkage on high-frequency performance. Maximum oscillation frequency fmax in excess of 250 GHz is reported.

This paper investigates a different method of speaker adaptation for Mandarin syllable recognition. Based on the minimum classification error (MCE) criterion, we use the generalized probabilistic decent (GPD) algorithm to adjust interatively the parameters of the hidden Markov models (HMM). The experiments on the multi-speaker Mandarin syllable database of Telecommunication Laboratories (T.L.) yield the following results: 1) Efficient speaker adaptation can be achieved through discriminative training using the MCE criterion and the GPD algorithm. 2) The computations required can be reduced through the use of the confusion sets in Mandarin base syllables. 3) For the discriminative training, the adjustment on the mean values of the Gaussian mixtures has the most prominent effect on speaker adaptation. 4) The discriminative training approach can be used to enhance the speaker adaptation capability of the maximum a posteriori (MAP) approach.

We propose a nonlocal impact ionization model applicable for the drain region where electric field increases exponentially. It is expressed as a function of an electric field and a characteristic length which is determined by a thickness of gate oxide and a source/drain junction depth. An analytical substrate current model for n-MOSFET is also derived from the new nonlocal impact ionization model. The model well explains the reason why the theoretical characteristic length differs from empirical expressions used in a pseudo two-dimensional model for MOSFET's. The nonlocal impact ionization model implemented in a device simulator demonstrates that the new model can predict substrate current correctly in the framework of drift-diffusion model.

This paper describes that a neural network, which consists of neurons with piecewise–linear sigmoid characteristics, is able to approximate any piecewise–linear map with origin symmetry. The neural network can generate "deterministic diffusion" originating from its diffusive trajectory.

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.

We propose two methods to fuse auditory information and visual information for accurate sppech recognition. The first method fuses two kinds of information by using linear combination after calculating two kinds of probabilities by HMM for each word. The second method fuses two kinds of information by using the histogram which expresses the correlation of them. We have performed experiments comparing the proposed methods with the conventional method and confirmed the validity of the proposed methods.