When people watch such motion pictures as documentaries or educational-type films, it is very natural for them to be interested in moving objects in the movies and be eager to know the detailed information related to these object. Therefore, a mechanism that enables users to directly pick up object information from motion pictures is necessary to make a movie system feasible. For this reason, we are researching techniques on using objects in motion pictures as hypermedia anchors. We call a movie system that provides the above mechanism a video hypermedia system. An object in a motion picture can generally be considered as a complex object which includes many parts. To allow users to obtain information related to each part, a system must be able to provide anchors corresponding to each part in each complex object. For this, authors cannot help defining all anchors in all frames, since the visual status of each part varies from moment to moment. This paper presents our approach for managing objects in motion pictures for video hypermedia systems. The main feature of the proposed method is to apply computer graphic techniques to the defining of anchors for a complex object.

A program slice is a set of program statements that directly or indirectly contribute to the values assumed by a set of variables at some program execution point. A few slicing algorithms have proposed to far but none of them are considered from the viewpoint of program modification. In this paper, we define a variable dependence graph (VDG) and show a new slicing algorithm on VDG. We also compare the time complexity of the algorithm with that of other existing algorithms and discuss the suitableness of our algorithm for program modification. As the result of this, we argue our algorithm is suitable for embedding debugging systems.

It is demonstrated with the Berlekamp-Massey shift-register synthesis algorithm that the linear complexity value of binary complementary sequences is at least 3/4 of the sequence length. For some sequence pairs the linear complexity value can be even 0.98 times the sequence length. In the light of these results strongly non-linear complementary sequences are considered suitable for information security applications employing the spread-spectrum (SS) technique.

Digital halftoning is a well-known technique in image processing to convert an image having several bits for brightness levels into a binary image consisting only of black and white dots. A great number of algorithms have been presented for this problem, some of which have only been evaluated just by comparison with human eyes. In this paper we formulate the digital halftoning problem as a combinatiorial problem which allows an exact solution with graph-theoretic tools. For this, we consider a d-dimensional grid of n := Nd pixels (d 1). For each pixel, we define a so-called k-neighborhood, k {0,...N - 1}, which is the set of at most (2k + 1)d pixels that can be reached from the current pixel in a distance of k. Now, in order to solve the digital halftoning problem, we are going to minimize the sum of distances of all k-neighborhoods between the original picture and the halftoned one. We show that the problem can be solved in linear time in the one-dimensional case while it looks hopeless to have a polynomial-time algorithm in higher dimension including the usual two-dimensional case. We present an exact algorithm for the one-dimensional case which runs in O(n) time if k is regarded to be a constant. For two-dimensional case we present fast approximation techniques based on space filling curves. An experimental comparison of several implementations of approximate algorithms proves that our algorithms are of practical interest.

This paper investigates some fundamental properties of alternating one-way (or two-way) pushdown automata (pda's) with sublogarithmic space. We first show that strongly (weakly) sublogarithmic space-bounded two-way alternating pda's are more powerful than one-way alternating pda's with the same space-bound. Then, we show that weakly sublogarithmic space-bounded two-way (one-way) alternating pda's are more powerful than two-way (one-way) nondeterministic pda's and alternating pda's with only universal states using the same space, and we also show that weakly sublogarithmic space-bounded one-way nondeterministic Turing machines are incomparable with one-way alternating Turing machines with only universal states using the same space. Furthermore, we investigate several fundamental closure properties, and show that the class of languages accepted by weakly sublogarithmic space-bounded one-way alternating pda's and the class of languages accepted by sublogarithmic space-bounded two-way deterministic pda's (nondeterministic pda's, alternating pda's with only universal states) are not closed under concatenation, Kleene closure, and length preserving homomorphism. Finally, we briefly investigate a relationship between 'strongly' and 'weakly'.

This paper discusses the problems of largest similar substructures (in short, LSS) in rooted and unordered trees (in short, R-trees) and those in unrooted and unordered trees (in short, trees). For two R-trees (or trees) Ta and Tb, LSS in Tb to Ta is defined, and two algorithms for finding one of the LSSs for R-trees and that for trees are proposed. The time and space complexities of both algorithms are OT (m3NaNb) and OS(mNaNb), respectively, where m is the largest degree of a vertex of Ta and Tb, and Na(Nb)is the number of vertices of Ta(Tb).

This paper proposes a method for achieving low-power control-logic modules using a combination of CMOS complex gate reorganization, transistor size optimization, and transistor layout. Complex gate reorganization minimizes transistor count and net count without changing the functionality of the circuit. Transistor sizing and layout are interdependent, the optimization of one results in the optimization of the other. The authors applied the reorganization method to a 10,846-transistor circuit, and succeeded in reducing the transistor count by 10%, and the net count by 9%. Transistor sizing and layout compaction reduced the average transistor size by one tenth, while the same delay was maintained. Total circuit capacitance, which is strongly related to power dissipation, was cut to 36%, even when wiring capacitances were dominant.

A fast and stable algorithm for locating a desired eigenvalue and its corresponding eigenvector is presented. Its effectiveness is shown through a numerical simulation. The proposed algorithm is fast and numerically accurate enough to be applied to a real application.

GDL is the language whose membership problerm is polynomial-time Turing equivalent to the discrete logarithm problem for a general finite group G. This paper gives a characterization of GDL from the viewpoint of computational complexity theory. It is shown that GDL NP co-AM, assuming that G is in NP co-NP, and that the group law operation of G can be executed in polynomial time of the element size. Furthermore, as a natural probabilistic extension, the complexity of GDL is investigated under the assumption that the group law operation is executed in an expected polynomial time of the element size. In this case, it is shown that GDL MA co-AM if G MA co-MA. As a consequence, we show that GDL is not NP-complete unless the polynomial time hierarchy collapses to the second level.

For a complex object model, a form of range restriction, called specialization constraint (SC), has been studied. On the other hand, very few models have been proposed that support selective inheritance. In this paper, the following consideration is taken into SCs for a complex object medel suppoorting selective inheritance. A polynomial-time algorithm is given for deciding if a given database schema is well-formed. A sound and complete axiomatization for SCs is presented. A polynomial-time algorithm is given that decides if an SC is a logical consequence of a set of SCs. Finally, another polynomial-time algorithm is given, which decides if there exists a database that contains a given path from a given class.

In this paper, we present for the first time two three-dimensional analytical electrostatic Green's functions for shielded and open arbitrarily multilayered medium structures. The analytical formulas for the Green's functions are simply expressed in the form of Fourier series and integrals, and are applicable to the arbitrary number of dielectric layers. In combination with the complex image charge method, we demonstrate an efficient application to analyze microstrip discontinuities in a three-layered dielectric structure. Numerical results for the capacitance associated with on open-end discontinuity show good agreement with those from a previous paper and the effectiveness of using the analytical Green's functions to analyze three-dimensional electrostatic problems.

One of the major open issues in neural network research includes a Network Designing Problem (NDP): find a polynomial-time procedure that produces minimal structures (the minimum intermediate size, thresholds and synapse weights) of multilayer threshold feed-forward networks so that they can yield outputs consistent with given sample sets of input-output data. The NDP includes as a sub-problem a Network Training Problem (NTP) where the intermediate size is given. The NTP has been studied mainly by use of iterative algorithms of network training. This paper, making use of both rate distortion theory in information theory and linear algebra, solves the NDP mathematically rigorously. On the basis of this mathematical solution, it furthermore develops a mathematical solution Procedure to the NDP that computes the minimal structure straightforwardly from the sample set. The Procedure precisely attains the minimum intermediate size, although its computational time complexity can be of non-polynomial order at worst cases. The paper also refers to a polynomial-time shortcut to the Procedure for practical use that can reach an approximately minimum intermediate size with its error measurable. The shortcut, when the intermediate size is pre-specified, reduces to a promising alternative as well to current network training algorithms to the NTP.

This paper proposes a new algorithm called the fast Projection algorithm, which reduces the computational complexity of the Projection algorithm from (p+1)L+O(p3) to 2L+20p (where L is the length of the estimation filter and p is the projection order.) This algorithm has properties that lie between those of NLMS and RLS, i.e. less computational complexity than RLS but much faster convergence than NLMS for input signals like speech. The reduction of computation consists of two parts. One concerns calculating the pre-filtering vector which originally took O(p3) operations. Our new algorithm computes the pre-filtering vector recursively with about 15p operations. The other reduction is accomplished by introducing an approximation vector of the estimation filter. Experimental results for speech input show that the convergence speed of the Projection algorithm approaches that of RLS as the projection order increases with only a slight extra calculation complexity beyond that of NLMS, which indicates the efficiency of the proposed fast Projection algorithm.

In this paper a priori estimation method is presented for calculating solution of convex optimization problems (COP) with some equality and/or inequality constraints by so-called Newton type homotopy method. The homotopy method is known as an efficient algorithm which can always calculate solution of nonlinear equations under a certain mild condition. Although, in general, it is difficult to estimate a priori computational complexity of calculating solution by the homotopy method. In the presented papers, a sufficient condition is considered for linear homotopy, under which an upper bound of the complexity can be estimated a priori. For the condition it is seen that Urabe type convergence theorem plays an important role. In this paper, by introducing the results, it is shown that under a certain condition a global minimum of COP can be always calculated, and that computational complexity of the calculation can be a priori estimated. Suitability of the estimation for analysing COP is also discussed.

A data-base for data compression is universal if in its construction no prior knowledge of the source distribution is assumed and is optimal if, when we encode the reference index of the data-base, its encoding rate achieves the optimal encoding rate for any given source: in the noiseless case the entropy rate and in the semifaithful case the rate-distortion function of the source. In the present paper, we construct a universal data-base for all stationary ergodic sources, and prove the optimality of the thus constructed data-base for two typical methods of referring to the data-base: one is a block-shift type reference and the other is a single-shift type reference.

This paper investigates the accepting powers of one-way alternatiog finite automata with counters and stack-counters (lafacs's) which operate in realtime. (The difference between counter" and stack-counter" is that the latter can be entered without the contents being changed, but the former cannot.) For each k0 and l0 ((k, l)(0, 0)), let 1AFACS(k, l, real) denote the class of sets accepted by realtime one-way alternating finite automata with k counters and l stack-counters, and let 1UFACS(k, l, real) (1NFACS(k, l, real)) denote the class of sets accepted by realtime one-way alternating finite automata with k counters and l stack-counters which have only universal (existential) states. We first investigate a relationship among the accepting powers of realtime lafacs's with only universal states, with only existential states, and with full alternation, and show, for example, that for each k0 and l0 ((k, l)(0, 0)), 1UFACS(k, l, real) 1NFACS(k, l, real) 1AFACS(k, l, real). We then investigate hierarchical properties based on the number of counters and stack-counters, and show, foe example, that for each k0 and l0 ((k, l)(0, 0)), and each X{U, N}, 1XFACS(k1, l, real)1AFACS(k, l, real)φ. We finally investigate a relationship between counters and stack-counters, and show, for example, that for each k0, l0 and m1, and each X{U, N}, 1XFACS(k, lm, real)1AFACS(k2m1, l, real)φ.

The firing squad synchronization problem is considered for defective cellular automata. A lower bound of time tf for the problem is derived. The state complexity to solve the problem is investigated and it is shown that the state set has to be arbitrary large to obtain solutions of time complexity (n). For memory-augmented defective cellular automata a tf-time solution is given.

We frequently need to calculate the Neumann function Nν(x) of complex order ν numerically in order to solve boundary problems on electromagnetic fields. This paper presents a new method for the numerical calculation of Nν(x) of complex order ν. This method can calculate Nν(x) precisely even when the order ν is close to an integer n, and the algorithm by the method is very simple.

This paper establishes a relationship among the accepting powers of deterministic, nondeterministic, and alternating one-way auxiliary pushdown automata, for any tape bound below n. Some other related results are also presented.

Various authors have proposed probabilistic extensions of Valiant's PAC (Probably Approximately Correct) learning model in which the target to be learned is a (conditional) probability distribution. In this paper, we improve upon the best known upper bounds on the sample complexity of the parameter estimation part of the learning problem for distributions and stochastic rules over a finite domain with respect to the Kullback-Leibler divergence (KL-devergence). In particular, we improve the upper bound of order O(1/ε2) due to Abe, Takeuchi, and Warmuth to a bound of order O(1/ε). In obtaining our results, we made use of the properties of a specific estimator (slightly modified maximum likelihood estimator) with respect to the KL-divergence, while previously known upper bounds were obtained using the uniform convergence technique.