The new notion of "multiuser interface", an interface for groups working together in a shared workspace, originated from the expansion of CSCW research and the spread of the groupware concept. This paper introduces a new multiuser interface design approach based on the translucent video overlay technique. This approach was realized in the multimedia desktop conference system Team WorkStation. Team WorkStation demonstrates that this translucent video overlay technique can achieve two different goals: (1) fused overlay for realizing the open shared workspace, and (2) selective overlay for effectively using limited screen space. This paper first describes the concept of open shared workspace and its implementation based on the fused overlay technique. The shared work window of Team-WorkStation is created by overlaying translucent individual workspace images. Each video layer is originally physically separated. However, because of the spatial relationships among marks on each layer, the set of overlaid layers provides users with sufficient semantics to fuse them into one image. The usefulness of this cognitive fusion was demonstrated through actual usage in design sessions. Second, the problem of screen space limitation is described. To solve this problem, the idea of ClearFace based on selective overlay is introduced. The ClearFace idea is to lay translucent live face video windows over a shared work window. Through the informal observations of experimental use in design sessions, little difficulty was experienced in switching the focus of attention between the face images and the drawing objects. The theory of selective looking accounts for this flexible perception mechanism. Although users can see drawn objects behind a face without difficulty, we found that users hesitate to draw figures or write text over face images. Because of this behavior, we devised the "movable" face window strategy.

Transmittance distribution along a horizontal line in LCDs addressed by amorphous silicon TFTs was investigated using measurements and calculations. Nonuniformity of the distribution, in which the transmittance increased with increasing distance from the left edge of the LCD, was observed in a 10 inch diagonal TFT-LCD. The cause of the nonuniformity was attributed to the decrease in voltage drop due to the gate source parasitic capacitance and the increase in gate voltage fall time due to large line resistance, based on the measurements of voltage drops in TFT test elements and calculations considering the decrease in voltage drop. The distribution could be improved by reducing the line resistance and parasitic capacitance in the actual LCD.

This paper presents a new connected associative memory neural network. In this network, a threshold function which has two dynamical parameters is introduced. After analyzing the dynamical behaviors and giving an upper bound of the memory capacity of the conventional connected associative memory neural network, it is demonstrated that these parameters play an important role in the recalling processes of the connected neural network. An approximate method of evaluationg their optimum values is given. Further, the optimum feedback stopping time of this network is discussed. Therefore, in our network, the recalling processes are ended at the optimum feedback stopping time whether a state energy has been local minimum or not. The simulations on computer show that the dynamical behaviors of our network are greatly improved. Even though the number of learned patterns is so large as the number of neurons, the statistical properties of the dynamical behaviors of our network are that the output series of recalling processes approach to the expected patterns on their initial inputs.

This paper investigates the performance of the line spectrum pair (LSP) frequency parameter representation for speech recognition. Transitional parameters of LSP frequencies are defined using first-order regression coefficients. The transitional and the instantaneous frequency parameters are linearly combined to generate a single feature vector used for recognition. The performance of the single vector is compared with that of the cepstral coefficients (CC) representation using a minimumdistance classifier in speaker-independent isolated word recognition experiments. In the speech recognition experiments, the transitional and the instantaneous coefficients are also combined in the distance domain. Also, inverse variance weighted Euclidean measures are defined using LSP frequencies to achieve Mel-scale-like warping and the new warped-frequencies are used in recognition experiments. The performance of the single feature vector defined with transitional and instantaneous LSP frequencies is found to be the best among the measures used in the experiments.

It is known that the problem of finding a largest common subgraph is NP-hard for general graphs even if the number of input graphs is two. It is also known that the problem can be solved in polynomial time if the input is restricted to two trees. In this paper, a randomized parallel (an RNC) algorithm for finding a largest common subtree of two trees is presented. The dynamic tree contraction technique and the RNC minimum weight perfect matching algorithm are used to obtain the RNC algorithm. Moreover, an efficient NC algorithm is presented in the case where input trees are of bounded vertex degree. It works in O(log(n1)log(n2)) time using O(n1n2) processors on a CREW PRAM, where n1 and n2 denote the numbers of vertices of input trees. It is also proved that the problem is NP-hard if the number of input trees is more than two. The three dimensional matching problem, a well known NP-complete problem, is reduced to the problem of finding a largest common subtree of three trees.

By adding some functions to memories, highly parallel computation may be realized. We have proposed memory-based parallel computation models, which uses a new functional memory as a SIMD type parallel computation engine. In this paper, we consider models with communication between the words of the functional memory. The memory-based parallel computation model consists of a random access machine and a functional memory. On the functional memory, it is possible to access multiple words in parallel according to the partial match with their memory addresses. The cube-FRAM model, which we propose in this paper, has a hypercube network on the functional memory. We prove that PSPACE is accelerated to polynomial time on the model. We think that the operations on each word of the functional memory are, in a sense, the essential ones for SIMD type parallel computation to realize the computational power.

A maximal l-diameter tree cover of a graph G(V,E) is a spanning subgraph C(V,EC) of G such that each connected component of C is a tree, C contains no path with more than l edges, and adding any edge in EEC to C yields either a path of length l1 or a cycle. For every function f from positive integers to positive integers, the maximal f-diameter tree cover prolem (MDTC(f) problem for short) is to find a maximal f(n)-diameter tree cover of G, given an n-node graph G. In this paper, we give two parallel algorithms for the MDTC(f) problem. The first algorithm can be implemented in time O(TMSP(n,f(n))log2n) using polynomial number of processors on an EREW PRAM, where TMSP(n,f(n) is the time needed to find a maximal set of vertex disjoint paths of length f(n) in a given n-node graph using polynomial number of processors on an EREW PRAM. We then show that if suitable restrictions are imposed on the input graph and/or on the magnitude of f, then TMSP(n,f(n))O(logkn) for some constant k and thus, for such cases, we obtain an NC algorithm for the MDTC(f) problem. The second algorithm runs in time O(n log2n/{f(n)1}) using polynomial number of processors on an EREW PRAM. Thus if f(n)Ω(n/logkn) for some kO, we obtain an NC algorithm for the MDTC(f) problem.

A method is presented for analyzing the scalar wave scattering from a conducting target of arbitrary shape in random media for both the Dirichlet and Neumann problems. The current generators on the target are introduced and expressed generally by the Yasuura method. When using the current generators, the scattering problem is reduced to the wave propagation problem in random media.

We study the depth of planar Boolean circuits. We show that planar Boolean circuits of depth D(n) are simulated by on-line Turing machines in space O(D(n)). From this relationship, it is shown that any planar circuit for computing integer multiplication requires linear depth. It is also shown that a planar analogue to the NC-hierarchy is properly separated.