Caenorhabditis elegans during feeding gives good moving biological images",in which motions of several pulsing organs are superposed on its head swing. A powerful method to extract dynamic features is presented. First step is to use a variance picture VAG4 in order to pick up active pixel coordinates of concerned moving objects. Superiority of VAG4 over usual variance picture VAG2 is shown quantitatively by a model of moving particles. Pulsing areas of C. elegans, are exhibited more clearly in VAG4 than VAG2. Second step is use of a new subtraction method to extract main frequency bands. FFT spectra are averaged in active positions where VAG4 is above threshold THVR in the square with 88 pixels (ONA). The power spectra averaged in the enlarged squares (ELA) are subtracted from those in ONA, in which ELA includes ONA in its centre position. Large peak bands emerge in the subtracted power spectra. The subtraction eliminates the effect of head swing by spatial averagings in ELA. This new emphasizing method is compared to another subtraction method. The characteristic frequency of periodical moving organs coincides well with the values observed by other research groups and our visual estimation of replayed VTR images. Thus the proposed extraction method is verified to work well in double superposed motions.

An optoelectronic beam forming network (BFN) is presented for a single beam, 3-element phased array antenna that utilizes electrically controllable birefringence mode nematic liquid-crystal cells (ECB mode NLC cells) for phase shifting and amplitude control. In the circuit, a microwave signal is carried by a pair of orthogonal linearly polarized lightwaves (signal and reference lightwaves) using the optical heterodyning technique. Birefringence of liquid-crystals is utilized to selectively control the phase of the signal and reference lightwaves. Because an interferometer is formed on a single signal path, the complexity of the optical circuit is much reduced, compared to the BFNs based on arrays of Mach-Zender interferometers. A prototype circuit is built using laser sources of 1.3 µm, and its performance experimentally examined. With small deviations among the three cells, phase shifts of up to 240 degrees are achived for MW signals from 0.9 GHz to 20 GHz with good stability; attenuation of more than 18dB is achieved. An optoelectronic technique for parallel control of amplitude and phase of MW signals was developed.

This paper proposes a photonic integrated beam forming and steering network (BFN) that uses switched true-time-delay (TTD) silica-based waveguide circuits for phased array antennas. The TTD-BFN has thermooptic switches and variable time delay lines. This TTD-BFN controls four array elements, and can form and steer a beam. An RF test was carried out in the 2.5 GHz microwave frequency range. The experimental results show a peak-to-peak phase error of 6.0 degrees and peak-to-peak amplitude error of 2.0 dB. Array factors obtained from the measured results agree well with the designed ones. This silica-based beam former will be a key element in phased array antennas.

In this paper it is pointed out that although an elegant differential-like approach is developed, Coppersmith' attacking method on NIKS-TAS cannot succeed to forge a shared key of legitimate entities especially when p-1 contains highly composite divisors, as well as decomposibility-hard divisors. This is mainly due to a severe reduction of modulo size. Computer simulation results confirm this assertion. The ambiguity in the solutions to the collusion equations in the first phase can be analyzed by the elementary divisor theory. Moreover, two basis vectors, qi,ri in the second phase, are found to be inadequate to represent the space spanned by xi-yi and ui-vi(i=1,...,N), because qi,ri exist frequently over the space with small modulo size. Then, the erroneous values of αi,βi,...,εi(i=1,...,N) are derived from the inadequate basis vectors, qi,ri. Also, when the degeneracy in modulo size happens, the solutions to αi,βi,...,εi(i=1,...,N) cannot be solved even by means of the exhaustive search over the small prime divisors of p-1.

The present paper is concerned with an algorithm for the minimization of multiple-valued input, binary-valued output functions. The algorithm is an extension to muitiple-valued logic of an algorithm for the minimization of ordinary single-output Boolean functions. It is based on a local covering approach. Basically, it uses a "divide and conquer" technique, consisting of two steps called expansion and selection. The present algorithm preserves two important features of the original one. First, a lower bound on the number of prime implicants in the minimum cover of the given function is furnished as a by-product of the minimization. Second, all the essential primes of the function are identified and selected during the expansion process. That usually improves efficiency when handling functions with many essential primes. Results of a comparison of the proposed algorithm with the program ESPRESSO-IIC developed at Berkeley are presented.

In CRYPTO '94, Langford and Hellman attacked DES reduced to 8-round in the chosen plaintext scenario by their "differential-1inear cryptanalysis," which is a combination of differential cryptanalysis and linear cryptanalysis. In this paper, a historical review of differential-linear cryptanalysis, our formalization of differential-linear cryptanalysis, and the application of differential-linear cryptanalysis to FEAL-8 are presented. As a result, though the previous best method (differential cryptanalysis) required 128 chosen plaintexts, only 12 chosen plaintexts are sufficient, in computer experimentations, to attack FEAL-8.

In previous papers the building of hierarchical networks made up of components using fuzzy rules was presented. It was demonstrated that this approach could be used to construct networks to solve classification problems, and that in many cases these networks were computationally less expensive and performed at least as well as existing approaches based on feedforward neural networks. It has also been demonstrated how this approach could be extended to real-valued problems, such as function approximation and time series prediction. This paper investigates the problem of choosing the best network for real-valued approximation problems. Firstly, the nature of the network parameters, how they are interrelated, and how they affect the performance of the system are clarified. Then we address the problem of choosing the best values of these parameters. We present two model selection tools in this regard, the first using a simple statistical model of the network, and the second using structural information about the network components. The resulting network selection methods are demonstrated and their performance tested on several benchmark and applied problems. The conclusions look at future research issues for further improving the performance of the clustering network.

This paper describes the performance of a predistorter implementation to a superluminescent diode (SLD) in fiber-optic wireless systems under the optical reflection. SLD intensity noise and 3rd-order intermodulation distortion (IM3) are experimentally compared with those of DFB-and FP-LD. It is observed that the IM3 of SLD has ideal 3rd characteristics and output noise remains unchanged against the number of optical connectors. It is also found that the predistorter reduces IM3 by 8 dB. Receiver sensitivity of the system is discussed from the view point of overall design. the BER performance of an SLD with predistorter using a π/4-QPSK signal as a subcarrier is also described theoretically and experimentally.

This article considers a hybrid data backup model for a file system, which combines both conventional magnetic disk (MD) and write-once, read-many optical disk (OD). Since OD recently is a lower cost medium as well as a longer life medium than the ordinary MD, this kind of backup configuration is just recognized to be important. We mathematically formulate the hybrid data backup model and obtain the closed-form average cost rate when the system failure time and the recovery time follow exponential distributions. Numerical calculations are carried out to obtain the optimal backup policy, which is composed of two kinds of backup sizes from the main memory to MD and from MD to OD and minimizes the average cost rate. In numerical examples, the dependence of the optimal backup policy on the failure and the recovery mechanism is examined.

In 1980, Hellman presented "time-memory trade-off cryptanalysis" for block ciphers, which requires precomputation equivalent to time complexity of exhaustive search, but can drastically reduce both time complexity on intercepted ciphertexts of exhaustive search and space complexity of table lookup. This paper extends his cryptanalysis and optimizes a relation among the breaking cost, time, and success probability. The power of the optimized cryptanalytic method can be demonstrated by the estimates as of January 1995 in the following. For breaking DES in one hour with success probability of 50% or more, the estimated cost of a simple and a highly parallel machine is respectively about 0.26[million dollars] and 0.06[million dollars]. Also it takes about six and two years respectively until each machine costs for breaking FEAL-32 on the same condition decreases to 1[million dollars]. Moreover, it takes about 22.5 and 19[years] respectively until each costs for breaking Skipjack similarly decreases to 1[million dollars], but time complexity of precomputation is huge in case of the former. The cost-time product for this precomputation will decrease to 20[million dollarsyears] in about 30[years].

A voltage-mode resonant forward converter with capacitor-input filter is proposed, and its static and dynamic characteristics for both half-wave type and full-wave type are revealed by analysis and experiment. As a result, this converter has prominent features of simplicity of circuit configuration, isolation between input and output and high stability.

In this paper we analyze the reliability of a simple broadcasting scheme for hypercubes (HCCAST) with random faults. We prove that HCCAST (n) (HCCAST for the n-dimensional hypercube) can tolerate Θ(2n/n) random faulty nodes with a very high probability although it can tolerate only n - 1 faulty nodes in the worst case. By showing that most of the f-fault configurations of the n dimensional hypercube cannot make HCCAST (n) fail unless f is too large, we illustrate that hypercubes are inherently strong enough for tolerating random faults. For a realistic n, the reliability of HCCAST (n) is much better than that of the broadcasting algorithm described in [6] although the latter can asymptotically tolerate faulty links of a constant fraction of all the links. Finally, we compare the fault-tolerant performance of the two broadcasting schemes for n = 15, 16, 17, 18, 19, 20, and we find that for those practical valuse, HCCAST (n) is very reliable.

This paper presents a generalized new approach for testing interconnects (for boundary scan architectures) as well as field programmable interconnect chips (FPICs). This approach relies on a structured walking-1 test set in the sense that a structural analysis based on the layout of the interconnect system, is carried out. The proposed structural test method differs from previous approaches as it explicitly avoids aliasing and confounding and is applicable to dense as well as sparse layouts and in the presence of faults in the programmable devices of a FPIC. The proposed method is applicable to both one-step and two-step test generation and diagnosis. Two algorithms with an execution complexity of O(n2), where n is the number of nets in the interconnect, are given. New criteria for test vector compaction are proposed; a greedy condition is exploited to compact test vectors for one-step and two-step diagnosis. For a given interconnect, the two-step diagnosis algorithm requires a number of tests as a function of the number of faults present, while the one-step algorithm requires a fixed number of tests. Simulation results for benchmark and randomly generated layouts show a substantial reduction in the number of tests using the proposed approaches compared with previous approaches. The applicability of the proposed approach to FPICs as manufactured by [1] is discussed and evaluated by simulation.

This paper presents Ternary Decision Diagrams which represent sets of products. This paper also presents manipulating methods for sum-of-products forms and ringsum-of-products forms using Ternary Decision Diagrams, and gives comparison results between Ternary Decision Diagrams and Binary Decision Diagrams.

There have been many developments on neural network research, and ability of a multi-layered network for classification of multi-spectral image data has been studied. We can classify non-Gaussian distributed data using the neural network trained by a back-propagation method (BPM) because it is independent of noise conditions. The BPM is a supervised classifier, so that we can get a high classification accuracy by using the method, so long as we can choose the good training data set. However, the multi-spectral data have many kinds of category information in a pixel because of its pixel resolution of the sensor. The data should be separated in many clusters even if they belong to a same class. Therefore, it is difficult to choose the good training data set which extract the characteristics of the class. Up to now, the researchers have chosen the training data set by random sampling from the input data. To overcome the problem, a hybrid pattern classification system using BPM and Kohonens feature mapping (KFM) has been proposed recently. The system performed choosing the training data set from the result of rough classification using KFM. However, how the remotely sensed data had been influenced by the KFM has not been demonstrated quantitatively. In this paper, we propose a new approach using the competitive weight vectors as the training data set, because we consider that a competitive unit represents a small cluster of the input patterns. The approach makes the training data set choice work easier than the usual one, because the KFM can automatically self-organize a topological relation among the target image patterns on a competitive plane. We demonstrate that the representative of the competitive units by principal component analysis (PCA). We also illustrate that the approach improves the classification accuracy by applying it on the classification of the real remotely sensed data.

This paper presents a technique for disparity selection in the context of binocular pursuit. For vergence control in binocular pursuit, it is a crucial problem to find the disparity which corresponds to the target among multiple disparities generally observed in a scene. To solve the problem of the selection, we propose an approach based on histogramming the disparities obtained in the scene. Here we use an extended phase-based disparity estimation algorithm. The idea is to slice the scene using the disparity histogram so that only the target remains. The slice is chosen around a peak in the histogram using prediction of the target disparity and target location obtained by back projection. The tracking of the peak enables robustness against other, possibly dominant, objects in the scene. The approach is investigated through experiments and shown to work appropriately.

Based on a simple model for the statistical error characteristics of range sensing, a numerical scheme called renormalization is presented for optimally fitting a planar surface to data points obtained by range sensing. The renormalization method has the advantage that not only an optimal fit is computed but also its reliability is automatically evaluated in the form of the covariance matrix. Its effectiveness is demonstrated by numerical simulation. A scheme for visualizing the reliability of computation by means of the primary deviation pair is also presented.

We propose a distributed operation system platform for optical cable networks. This distributed platform is an extension of the previously proposed platform for a flexible cable network operation. The concept of the unit platform has been proposed for the distributed operation system platform. By using this concept, we discuss the system upgrade including the connection to other operation systems. We use an object-oriented software technology for designing the distributed operation system platform. The prototype system has been constructed using C++ programing language and the evaluated results are shown.

This work deals with thermal-noise modeling for silicon vertical bipolar junction transistors (BJTs) and relevant integrated circuits (ICs) operating at low currents. The two-junction BJT compact model is consistently derived from the thermal-noise generalization of the Shockley semiconductor equations developed in work which treats thermal noise as the noise associated with carrier velocity fluctuations. This model describes BJT with the Itô non-linear stochastic-differential-equation (SDE) system and is suitable for large-signal large-fluctuation analysis. It is shown that thermal noise in silicon p-n-junction diode contributes to "microplasma" noise. The above model opens way for a consistent-modeling-based design/optimization of bipolar device noise performance with the help of theory of Itô's SDEs.

In order to ensure the reliability and safety of equipment installed in process lines, it is important that maintenance and management should make efficient use of machine diagnosis techniques. Machine diagnosis by means of acoustic signals has hitherto been beset with difficulty, but there is now a strong demand that new acoustic type diagnosis equipment (utilizing acoustic signals) be developed. In response to this demand, the authors recently conducted research on diagnosis of machine faults by means of the processing of acoustic signals. In this research they were able to develop new acoustic type machine diagnosis techniques, and, using these techniques, to develop acoustic diagnosis equipment for practical use.