A Homogeneous Set-Theoretical Frame for Clustering Fuzzy Relational Data

Our purpose is to provide a set-theoretical frame to clustering fuzzy relational data basically based on cardinality of the fuzzy subsets that represent objects and their complementaries, without applying any crisp property. From this perspective we define a family of fuzzy similarity indexes which includes a set of fuzzy indexes introduced by Tolias et al, and we analyze under which conditions it is defined a fuzzy proximity relation. Following an original idea due to S. Miyamoto we evaluate the similarity between objects and features by means the same mathematical procedure. Joining these concepts and methods we establish an algorithm to clustering fuzzy relational data. Finally, we present an example to make clear all the process

An automatic correction tool for relational database schemas

A Web-based tool developed to automatically correct relational database schemas is presented. This tool has been integrated into a more general e-learning platform and is used to reinforce teaching and learning on database courses. This platform assigns to each student a set of database problems selected from a common repository. The student has to design a relational database schema and enter it into the system through a user friendly interface specifically designed for it. The correction tool corrects the design and shows detected errors. The student has the chance to correct them and send a new solution. These steps can be repeated as many times as required until a correct solution is obtained. Currently, this system is being used in different introductory database courses at the University of Girona with very promising results

Determinants of acquisition completion: a relational perspective

The strategic literature on relatedness in the context of mergers and acquisitions (M&As) is extensive, yet we know little about whether or how relatedness has an influence on the announcement to completion stage of the M&A process. Drawing on research on intra-industry competition and relational capabilities, we seek to shed light on the relatedness debate by examining the strategic forces that affect the completion of an announced related M&A, accounting for financial and organizational factors. We also explore additional strategic forces that might amplify or attenuate the negative effect of relatedness on deal completion. We test and find support for our hypotheses using longitudinal data from a sample of the largest M&A announcements in the world from 1991 to 2001.

Debt enforcement and relational contracting

We examine how third-party debt enforcement affects the emergence and performance ofrelational contracts in credit markets. We implement an experiment with finitely repeatedcredit relationships in which borrowers can default. In the weak enforcement treatmentdefaulting borrowers can keep their funds invested. In the strong enforcement treatmentdefaulting borrowers have to liquidate their investment. Under weak enforcement fewerrelationships emerge in which loans are extended and repaid. When such relationships doemerge they exhibit a lower credit volume than under strong enforcement. These findingssuggest that relational contracting in credit markets requires a minimum standard of thirdpartydebt enforcement.

ValTer2 and ForesTer : From a relational term bank to hypertext on the Web

Abstract

Soil infiltration based on bp neural network and grey relational analysis

Soil infiltration is a key link of the natural water cycle process. Studies on soil permeability are conducive for water resources assessment and estimation, runoff regulation and management, soil erosion modeling, nonpoint and point source pollution of farmland, among other aspects. The unequal influence of rainfall duration, rainfall intensity, antecedent soil moisture, vegetation cover, vegetation type, and slope gradient on soil cumulative infiltration was studied under simulated rainfall and different underlying surfaces. We established a six factor-model of soil cumulative infiltration by the improved back propagation (BP)-based artificial neural network algorithm with a momentum term and self-adjusting learning rate. Compared to the multiple nonlinear regression method, the stability and accuracy of the improved BP algorithm was better. Based on the improved BP model, the sensitive index of these six factors on soil cumulative infiltration was investigated. Secondly, the grey relational analysis method was used to individually study grey correlations among these six factors and soil cumulative infiltration. The results of the two methods were very similar. Rainfall duration was the most influential factor, followed by vegetation cover, vegetation type, rainfall intensity and antecedent soil moisture. The effect of slope gradient on soil cumulative infiltration was not significant.

Spatial relational learning and memory abilities do not differ between men and women in a real-world, open-field environment

This study assesses gender differences in spatial and non-spatial relational learning and memory in adult humans behaving freely in a real-world, open-field environment. In Experiment 1, we tested the use of proximal landmarks as conditional cues allowing subjects to predict the location of rewards hidden in one of two sets of three distinct locations. Subjects were tested in two different conditions: (1) when local visual cues marked the potentially-rewarded locations, and (2) when no local visual cues marked the potentially-rewarded locations. We found that only 17 of 20 adults (8 males, 9 females) used the proximal landmarks to predict the locations of the rewards. Although females exhibited higher exploratory behavior at the beginning of testing, males and females discriminated the potentially-rewarded locations similarly when local visual cues were present. Interestingly, when the spatial and local information conflicted in predicting the reward locations, males considered both spatial and local information, whereas females ignored the spatial information. However, in the absence of local visual cues females discriminated the potentially-rewarded locations as well as males. In Experiment 2, subjects (9 males, 9 females) were tested with three asymmetrically-arranged rewarded locations, which were marked by local cues on alternate trials. Again, females discriminated the rewarded locations as well as males in the presence or absence of local cues. In sum, although particular aspects of task performance might differ between genders, we found no evidence that women have poorer allocentric spatial relational learning and memory abilities than men in a real-world, open-field environment.