New methods are needed for accessing very large information services. This paper proposes the use of a user model neural network to allow better access to a news service. The network is constructed on the basis of articles read, and articles marked as rejected. It adapts over time to better represent the user's interests and rank the articles supplied by the news service. Using an augmented keyword search we can also search for articles using keywords in conjunction with the user model neural network. Trials of the system in a USENET news environment show promising results for the use of this approach in information retrieval.

The subject of the paper is to propose a simple O(|V|+|E|) algorithm for finding all 3-edge-components of a given undirected multigraph G=(V, E). An 3-edge-connected component of G is defined as a maximal set of vertices such that G has at least three edge-disjoint paths between every pair of vertices in the set. The algorithm is based on the depth-first search (DFS) technique. For any fixed DFS-tree T of G, cutpairs of G are partitioned into two types: a type 1 pair consists of an edge of T and a back edge; a type 2 pair consists of two edges of T. All type 1 pairs can easily be determined in O(|V|+|E|) time. The point is that an edge set KE(T) in which any type 2 pair is included can be found in O(|V|+|E|) time. All 3-edge-components of G appear as connected components if we delete from G all edges contained in type 1 pairs or in the edge set KE(T).

This paper presents an automatic creation method of 3D facial models which are needed for facial image generation by 3D computer graphics. A 3D facial model of a specific person is obtained from just the front and side view images without any human operation. The method has two parts; feature extraction and generic model modification. In the feature extraction part, the regions or edges which express the facial features such as eyes, nose, mouth or chin outline are extracted from the front and side view images. A generic head model is then modified based on the position and shape of the extracted facial features in the generic model modification part. As a result, a 3D model for persons is obtained. By using the specific model and the front and side view images, texture-mapped facial images can be generated easily.

We have developed an efficient general-purpose two-dimensional device simulation system which consists of a solver, and pre- and post-processors. This system can easily handle any complicated device having a non-rectangular shape. It can also be applied to compound semiconductor devices with heterojunctions, including optical devices such as laser diodes. In order to handle any device, a new program for construction of device geometry is developed as a preprocessor. It has an efficient graphic interface to reduce the time required to input data for simulations, which is a very time consuming task for complicated devices. A new efficient data structure representing device geometry is introduced in the program. During postprocessing, any physical quantity can be displayed on the multi-window screen. In addition, a general-purpose solver for basic semiconductor equations is implemented in the system. Using this system, any device can be successfully analyzed in a unified manner and the turn-around time for the simulation is significantly reduced.

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.

We describe two information disseminating schemes, t-disseminate and t-Rdisseminate in a computer network with N processors, where each processor can send a message to t-directions at each round. If no processors have failed, these schemes are time optimal. When at most t processors have failed, for t1 and t2 any of these schemes can broadcast information within any consecutive logt+1N2 rounds, and for an arbitrary t they can broadcast information within any consecutive logt+1N3 rounds.