Extrapolation of fuzzy values from incomplete data bases

This paper presents different approaches which enable a data base management system to obtain a plausible fuzzy estimate for an attribute value of an item for which the information is not explicitly stored in the data base. This can be made either by a kind of analogical reasoning from information about particular items or by means of expert rules which specify the (fuzzy) sets of possible values of the attribute under consideration, for various classes of items. Another kind of expert rules enables the system to compute an estimate from the attribute value of another item provided that, in other respects, this latter item sufficiently resembles the item, the value of which we are interested in; then these expert rules are used either for controlling the analogical reasoning process or for enlarging the scope of application of the first kind of expert rules. The different approaches are discussed in the framework of possibility theory.     

A prolog based expert system for the allocation of quality assurance program resources

The worldwide proliferation of fraudulent materials has brought about the need for a new approach to the control of purchased material quality. Nuclear power, defense, aerospace and many other industries are affected by the supply of poor quality clones that presume to be original replacement parts. Safety considerations abound as these highly defective materials are used in systems that are critical to the preservation of human lives. Commonly utilized quality assurance programs have not effectively stopped the influx of fraudulent materials. These programs fail to concentrate inspection efforts on materials and inspection attributes that would effectively prevent the acceptance of fraudulent materials. herein a solution is presented to this problem in the form of an expert system application. Information commonly available in industry is formulated into a knowledge based system wherein advisories are given to the user regarding key purchased material receipt inspection strategies.     

Intelligent SQL

Intelligent SQL is an intelligent database engine interface language which incorporates object-oriented, inferencing, and multi-media constructs. It is intended to be a powerful extension of existing SQL dialects. It also provides querying capabilities for object-oriented databases. Intelligent SQL was prototyped at Ashton-Tate. This paper discusses the main features of Intelligent SQL.     

Effect of Negative Emotional Content on Working Memory and Long-Term Memory.

In long-term memory, negative information is better remembered than neutral information. Differences in processes important to working memory may contribute to this emotional memory enhancement. To examine the effect that the emotional content of stimuli has on working memory performance, the authors asked participants to perform working memory tasks with negative and neutral stimuli. Task accuracy was unaffected by the emotional content of the stimuli. Reaction times also did not differ for negative relative to neutral words, but on an n-back task using faces, participants were slower to respond to fearful faces than to neutral faces. These results suggest that although emotional content does not have a robust effect on working memory, in some instances emotional salience can impede working memory performance. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Elimination of fictitious penetrating rays from PO and hybridization with AFIM

Physical optics (PO) is an approximation method for high‐frequency scattering and diffraction problems. But PO fields are inaccurate in the shadow region where the source is screened by the scatter. Two key factors of the error for PO are (i) edge diffraction coefficients and (ii) existence of fictitious penetrating rays. The correction with respect to the former has been extensively investigated by many authors using various ray techniques such as GTD, UTD, and UAT. On the other hand, the latter was identified recently by the authors. This paper proposes novel PO‐based calculation procedures termed PO‐AF and PTD‐AF, where PO and Aperture Field Integration Method (AFIM) are merged with the help of special elementary diffraction coefficients. These can uniformly cover the whole angular region and only the error factor (ii) is removed in PO‐AF while both (i) and (ii) are removed in PTD‐AF. The theoretical backgrounds of PO currents are discussed in terms of field equivalence theorem and visualization of EM waves. Next, new methods are proposed and their validity is numerically demonstrated for 2D scattering problems of a strip, a corner reflector, and a cylinder of circular arc. © 2004 Wiley Periodicals, Inc. Electr Eng Jpn, 150(2): 1–10, 2005; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20037     

Photostabilisation of colour formers for heat-sensitive recording systems: Effect of counter-ions on the photofading of fluoran dyes

Fluorans are given considerable attention as functional dyes for heat-and/or pressure-sensitive recording media. Numerous potential metal complexes were synthesised to prolong the life of coloured species. The protecting effect of these compounds against the photofading was examined on cellulose. It was found that the zinc or nickel salts of 3,5-dihydroxy-2-naphthoic acid and its derivatives can be applied as effective stabilisers against the fading of fluoran dyes.     

房地产开发企业会计核算问题探讨

本文就房地产开发企业会计核算的现状及特点进行了分析,并提出了完善房地产开发企业会计核算规范的对策。     

EXTENSION OF THE RELATIONAL DATABASE AND ITS ALGEBRA WITH ROUGH SET TECHNIQUES

This paper describes a database model based on the original rough sets theory. Its rough relations permit the representation of a rough set of tuples not definable in terms of the elementary classes, except through use of lower and upper approximations. The rough relational database model also incorporates indiscernibility in the representation and in all the operators of the rough relational algebra. This indiscernibility is based strictly on equivalence classes which must be defined for every attribute domain. There are several obvious applications for which the rough relational database model can more accurately model an enterprise than does the standard relational model. These include systems involving ambiguous, imprecise, or uncertain data. Retrieval over mismatched domains caused by the merging of one or more applications can be facilitated by the use of indiscernibility, and naive system users can achieve greater recall with the rough relational database. In addition, applications inherently “rough” could be more easily implemented and maintained in the rough relational database.