We present a throughput analysis of a multi-address call extraction server in F-NET. The extraction server splits a multi-address call into individual calls. Since the actual operation mechanisms of the server are complicated, it is difficult to directly apply the standard Markov chain technique. Restricting ourselves to the case where the server is offered by a saturated input process, we propose a simple probabilistic method to investigate the departure process of the server and its asymptotic behavior. Numerical examples evaluated by the method are compared with simulations, which demonstrate the accuracy of our modeling approach.

Privacy, voter uncoercibility, collision freedom, verifiability, and tally correctness are essential properties of modern electronic election systems. None of the single-authority election systems proposed in the literatures achieves all the above five properties. In this paper we propose a universal single-authority election system that satisfies the five properties. In particular, the privacy of each voter is protected against the authority and other voters, and no voter can coerce any other voter into changing the value of his vote in our proposed system. We also show that it is impossible for a collision-free single-authority election system to possess the voter uncoercibility and authority uncoercibility at the same time.

Fitt's law is commonly used to model target selection. But Fitts' law deals with only one kind of selection strategy. Our question is, do changes in target size, distance and direction to a target affect the differences in performance between target selection strategies? We performed the first empirical tests on a pen-based system to evaluate differences in performance between six selection strategies for selecting a target. Three target sizes, eight pen-movement-directions and three pen-movement-distances were applied to all six strategies. The results show that differences between selection strategies are affected by variations in target size but not by the other parameters (distance and direction).

The development of saturation diving in civil and defense applications has enabled man to work in the sea at great depths and for long periods of time. This advance has resulted, in part, as a consequence of the substitution of helium for nitrogen in breathing gas mixtures. However, utilization of HeO2 breathing mixture at high ambient pressures has caused problems in speech communication; in turn, helium speech enhancement systems have been developed to improve diver communication. These speech unscramblers attempt to process variously the grossly unintelligible speech resulting from the effect of breathing mixtures and ambient pressure, and to reconstruct such signals in order to provide adequate voice communication. It is known that the glottal excitation is quasi-periodic and the vocal tract filter is quasi-stationary. Hence, it is possible to use an auto regressive modelisation to restore speech intelligibility in hyperbaric conditions. Corrections are made on the vocal tract transfer function, either in the frequency domain, or directly on the autocorrelation function. A spectral subtraction or noise reduction may be added to improve speech quality. A new VAD enhanced helium speech unscrambler is proposed for use in adverse conditions or in speech recognition. This system, implementable on single chip DSP of current technology, is capable to work in real time.

The most basic cross-talk minimization problem is to assign given n intervals to n parallel tracks where the cross-talk is defined between two intervals assigned to the adjacent tracks with the amount linear to parallel running length. This paper solves the problem for the case when any pair of intervals intersects and the objective is to minimize the sum of cross-talks. We begin the discussion with the fact that twice the sum of lengths of n/2 shortest intervals is a lower bound. Then an interval set that attains this lower bound is characterized with a simple assignment algorithm. Some additional considerations provide the minimum cross-talk for the other interval sets. The main procedure is to sort the intervals twice with respect to the length of left and right halves of intervals.

This paper is concerned with the validation of simple turning points of two-point boundary value problems of nonlinear ordinary differential equations. Usually it is hard to validate approximate solutions of turning points numerically because of it's singularity. In this paper, it is pointed out that applying the infinite dimensional Krawcyzk-based interval validation method to enlarged system, the existence of simple turning points can be verified. Taking an example, the result of validation is also presented.

Related with accuracy, computational complexity and so on, quality of computing for the so-called homotopy method has been discussed recently. In this paper, we shall propose an estimation method with interval analysis of region in which unique solution path of the homotopy equation is guaranteed to exist, when it is applied to a certain class of uniquely solvable nonlinear equations. By the estimation, we can estimate the region a posteriori, and estimate a priori an upper bound of the region.

This paper describes an efficient simulation algorithm for the spatiotemporal pattern analysis of the continuous-time neural networks with the multivalued logic (multivalued continuous-time neural networks). The multivalued transfer function of neuron is approximated to the stepwise constant function which is constructed by the sum of the step functions with the different thresholds. By this approximation, the dynamics of the network can be formulated as a stepwise constant linear differential equation at each timestep and the optimal timestep for the numerical integration can be obtained analytically. Finally, it is shown that the proposed method is much faster than a variety of conventional simulators.

This article shows that a multivalued logic defined as juxtaposition of Boolean binary logics can use all of inference chain, induction and deduction that are important in realization of intelligent inference systems.

This paper describes a real-time connection admission control scheme for supporting multiple service categories. The scheme is based on a real-time cell-loss ratio evaluation algorithm for VBR based on peak/sustainable cell rates and maximum burst size. The algorithm is based on a notion of Allan variance of VP utilization. The most remarkable characteristics of the admission control scheme are that it terminates within constant time, a few milliseconds, and that its time is independent of both the number of VCs and the capacity of a cell buffer.

Recently, a trellis-based recursive maximum likelihood decoding (RMLD) algorithm has been proposed for decoding binary linear block codes. This RMLD algorithm is computationally more efficient than the Viterbi decoding algorithm. However, the computational complexity of the RMLD algorithm depends on the sectionalization of a code trellis. In general, minimization of the computational complexity results in non-uniform sectionalization of a code trellis. From implementation point of view, uniform sectionalization of a code trellis and regularity among the trellis sections are desirable. In this paper, we apply the RMLD algorithm to a class of codes which are transitive invariant. This class includes Reed-Muller (RM) codes, the extended and permuted BCH (EBCH) codes and their subcodes. For this class of codes, the binary uniform sectionalization of a code trellis results in the following regular structure. At each step of decoding recursion, the metric table construction procedure is applied uniformly to all the sections and the size and structure of each metric table are the same. This simplifies the implementation of the RMLD algorithm. Furthermore, for all RM codes of lengths 64 and 128 and EBCH codes of lengths 64 and 128 with relatively low rate, the computational complexity of the RMLD algorithm based on the binary uniform sectionalization of a code trellis is almost the same as that based on an optimum sectionalization of a code trellis.

Complex rule conditions are commonly required to describe complicated business semantics. In these cases, efficient condition evaluation is crucial for high performance of active database systems. Most previous works used the incremental evaluation techniques, whose operations are relatively expensive due to the processing based on the exact calculation of the condition expression. In this paper we propose a new filtering technique that effectively identifies false condition in an early stage of condition monitoring. Since the results of condition evaluation tend to be false in most practical cases, an efficient filtering method can highly facilitate fast condition evaluation. The proposed filtering technique is developed based on the new perspective of database state and database operations, i. e. , a vector space model. We first present vector representations of database states, database operations, and complex condition expressions. Then, we propose a filtering method based on the properties of a vector space, called the sphere containment test. Our proposed method determines the truth value of the rule conditions only with the delta vectors maintained in main memory. We compare our method with a typical incremental evaluation method and show that the proposed method can give a significant performance enhancement.

The authors have proposed a design method for two-dimensional (2-D) separable-denominator (SD) periodically time-variant digital filters (PTV DFs) and confirmed their superiority over 2-D time-invariant DFs. In that result, the periodicity matrix representing the periodicity of the varying filter coefficients is, however, restricted to two cases. This paper extends that idea so that the input-output relation of 2-D SD PTV DFs with an arbitrary periodicity matrix can be determined. This enables us to design wide range of 2-D PTV DFs.

Evaluating analytically computer architecture performance is mostly cheap and quick. However, existing analytical performance evaluation techniques usually have a difficult and time-consuming modeling process. Moreover, existing techniques do not support well the capability for finding the bottleneck and its cause of a target system being evaluated. To address the above problems and to enhance analytical performance evaluation technology, in this paper we propose a software tool that accepts system models described in a specification language, generating an executable program that performs the actual performance evaluation. The whole approach is built on a subsystem-oriented performance evaluation tool, which is, in turn, based on a formal subsystem-oriented performance evaluation technique and a subsystem specification language.

This paper proposes a new approach to recover the sign of local surface curvature of object from three shading images using neural network. The RBF (Radial Basis Function) neural network is used to learn the mapping of three image irradiances to the position on a sphere. Then, the learned neural network maps the image irradiances at the neighbor pixels of the test object taken from three illuminating directions of light sources onto the sphere images taken under the same illuminating condition. Using the property that basic six kinds of surface curvature has the different relative locations of the local five points mapped on the sphere, not only the Gaussian curvature but also the kind of curvature is directly recovered locally from the relation of the locations on the mapped points on the sphere without knowing the values of surface gradient for each point. Further, two step neural networks which combines the forward mapping and its inverse mapping one can be used to get the local confidence estimate for the obtained results. The entire approach is non-parametric, empirical in that no explicit assumptions are made about light source directions or surface reflectance. Results are demonstrated by the experiments for real images.

In this paper, we propose a new approach for describing image patterns. We integrate the concepts of multiscale image analysis, aura matrix (Gibbs random fields and cooccurrences related statistical model of texture analysis) to define image features, and to obtain the features having robustness with illumination variations and shading effects, we analyse images based on the Topographic Structure described by the Surface-Shape Operator, which describe gray-level image patterns in terms of 3D shapes instead of intensity values. Then, we illustrate usefulness of the proposed features with texture classifications. Results show that the proposed features extracted from multiscale images work much better than those from a single scale image, and confirm that the proposed features have robustness with illumination and shading variations. By comparisons with the MRSAR (Multiresolution Simultaneous Autoregressive) features using Mahalanobis distance and Euclidean distance, the proposed multiscale features give better performances for classifying the entire Brodatz textures: 112 categories, 2016 samples having various brightness in each category.

In a variety of communication systems, the multipath propagation due to various reflections is often encountered. In this paper, the directions-of-arrival (DOA) estimation of the cyclostationary coherent signals is investigated. A new approach is proposed for estimating the DOA of the coherent signals impinging on a uniform linear array (ULA) by utilizing the spatial smoothing (SS) technique. In order to improve the robustness of the DOA estimation by exploiting the cyclic statistical information sufficiently and handling the coherence effectively, we give a cyclic algorithm with multiple lag parameters and the optimal subarray size. The performance of the presented method is verified and compared with the conventional methods through numerical examples.

Macroscopic method for quantization of the evanescent fields brought about by total reflection is presented. Here, a semi-infinite space is assumed to be filled with a transparent dispersive dielectric with dielectric constant ε(ω) to the left of the plane z = 0, and be empty to the right of the plane. The wave is assumed to be incident from the left, and so the whole field is composed of the triplet of incident, reflected, and transmitted waves labeled by a continuous wave vector index. The transmitted wave in free space may be evanescent. The triplet is shown exactly without using slowly varying field approximation in dispersive medium to form orthogonal mode for different wave vectors, which provides the basis for the quantization of the triplet with taken into account of medium dispersion. The exact orthogonal relation reduces to the well known one if the dielectric is nondispersive, ε/ω = 0. By using the field expansion in terms of the orthogonal triplet modes, the total field energy is found to be the sum of the energies of independent harmonic oscillators. A discussion is also made on the wave momentum of evanescent field.

In this paper, a novel method is proposed for designing two channel biorthogonal filter banks with general IIR filters, which satisfy both the perfect reconstruction and causal stable conditions. Since the proposed filter banks are structurally perfect reconstruction implementation, the perfect reconstruction property is still preserved even when all filter coefficients are quantized. The proposed design method is based on the formulation of a generalized eigenvalue problem by using Remez multiple exchange algorithm. Then, the filter coefficients can be computed by solving the eigenvalue problem, and the optimal solution is easily obtained through a few iterations. One design example is presented to demonstrate the effectiveness of the proposed method.

The Advanced Intelligent Network (Advanced IN) is now commercialized and the Internet is becoming popular all over the world. If these two networks were connected, the potential would exist for new services. This paper surveys and analyzes the possibility of improving both the Internet and Advanced IN with an Advanced IN-the Internet connection. Service customization, which allows customers to define their own service specifications, is one of the most important service applications for the Advanced IN. However, some issues must be resolved before that service can be offered. This paper proposes a solution in which Internet technologies are applied to the IN. We review the system architecture of Service Logic Program (SLP) definition and execution in NTT's IN for service customization. Version management and cost for delivery are the major issue for service customization with the SLP(C) creation tool. We suggest an Internet version of the SLP(C) creation tool to solve these problems. Results of the prototype shows that connecting the IN and the Internet for service customization will benefit both customers and telecommunication operators.