We propose a semantics filter aimed at filtering unnecessary data for a user. In the Geographic Information Systems (GIS), the transfer of spatial data for each user is one of the important problems. We design a system that filters spatial data by using user's information adoptively. Our system derives the degree of geographical knowledge by the fuzzy reasoning and decides the priority of buildings by the C4.5 using user's information. Furthermore, in the process of the priority of buildings, we determine also the priority from geometrical and topological information. This paper describes a method for determining the priority of buildings.

Scheduling in a constrained environment is a complex and difficult process. Genetic algorithm (GA) approach has been increasingly used to solve various combinatorial optimization type problems. In this paper, we carry out experiments to investigate a GA based approach to the job shop scheduling problem (JSSP). We propose genetic heuristics to be used in our GA. We evaluate the performance of the proposed approach using well known benchmark instances for the JSSP.

In this paper we consider a sex-fair matching in the stable marriage problem. The sex-fair stable matching defined in this paper has a property that the sum of the partner's rank of each man in his preference list is as close as possible to the sum of the partner's rank of each woman in her preference list. We transform the sex-fair marriage problem into a graph problem which is suitable for a genetic algorithm. We propose a genetic algorithm for the sex-fair stable matching. The transformation into the graph problem makes application of the GA easier and effective. Computer experiments show the effectiveness of the proposed genetic algorithm.

The authors discuss the design of distributed and autonomous algorithms for producing social matching such as dancing pairs from groups of boys and girls, roommates for a boy dormitory, and job placement in the employment market in message-exchange network environments. The matching process must preserve personal privacy, stability of matching, preference-based autonomous behavior, and conformability of the whole model to social norms. Such constraints are shown to give rise to quite interesting design problems and algorithms, which are contrasted with imperative computer algorithms.>

In previous work, we designed architecture of FEM-TORUS, torus array of processing elements PE that are supposed to be conventional VLSI microprocessors operating in the data-driven mode with message-passing communication, and described wavefront-driven hardware algorithms on it for solving band-limited linear systems Ax=b often encountered in the finite-element-method analysis of partial differential equations. FEM-TORUS is a paper machine without hardware implementation but with a simulator that accepts application programs to execute.

This paper proposes a design of matrix machines for solving large-scale band-limited matrix equations. The design provides a guide-line for specifying functionality of each processing element PE, array arrangements of PEs, communication structures and parallel algorithms. The basic feature of the design is (1) a rotary array arrangement of data-flow type PEs with the slant width 2B-1 and circumference Z, on which the diagonal strip of a band-limited matrix data is wound around, and (2) wavefront-sequential executions of tasks, each of which is consisted of a group of pipelined wavefronts and circulates around the rotary array. The wavefront algorithm first produces the Gaussian solution via LU decomposition and then its accuracy is improved by applying the incomplete LU (conjugate) residual iteration.