Data mining is used to extract useful information hidden in the data. Sometimes this extraction of information leads to revealing sensitive information. Privacy preservation in Data Mining is a process of sanitizing sensitive information. This research focuses on sanitizing sensitive rules discovered in quantitative data. The proposed scheme, Privacy Preserving in Fuzzy Association Rules (PPFAR...

Traditional phonology presupposes abstract underlying representations (UR) and a set of rules to explain the phonological phenomena. There are, however, a number of questions that have been raised regarding this approach : Where do URs come from? How are rules found and related to each other? In the current study, a connectionist network was trained without the benefit of any UR and explicit ru...

The constantly increasing volume and complexity of available biological data requires new methods for managing and analyzing them. An important challenge is the integration of information from different sources in order to discover possible hidden relations between already known data. In this paper we introduce a data mining approach which relates biological ontologies by mining generalized ass...

Spatial data mining is a demanding field since huge amounts of spatial data have been collected in various applications, ranging form Remote Sensing to GIS, Computer Cartography, Environmental Assessment and Planning. Although there have been efforts for spatial association rule mining, but mostly researchers discuss only the positive spatial association rules; they have not considered the spat...

The acquisition of syntactic categories is a crucial step in the process of acquiring syntax. At this stage, before a full grammar is available, only surface cues are available to the learner. Previous computational models have demonstrated that local contexts are informative for syntactic categorization. However, local contexts are affected by sentence-level structure. In this paper, we add se...

The acquisition of syntactic categories is a crucial step in the process of acquiring syntax. At this stage, before a full grammar is available, only surface cues are available to the learner. Previous computational models have demonstrated that local contexts are informative for syntactic categorization. However, local contexts are affected by sentence-level structure. In this paper, we add se...

In this article, we assume that the mesons in the πχc1 invariant mass distribution are scalar hidden charmed tetraquark states and study their masses with the QCD sum rules. The numerical result indicates that the mass is about MZ = (4.19 ± 0.17)GeV, which is consistent with the experimental data. The hidden charmed mesons Z1 and Z2 may be tetraquark states, other possibilities, such as hadro-c...

In this article, we interpolate the vector hidden charmed tetraquark state with the Cγ5 − Cγμγ5 type current, and calculate its mass with the QCD sum rules. The numerical result indicates that the mass is about MZ = (4.09 ± 0.11)GeV, while the C − Cγμ type interpolating current leads to the mass aboutMZ = (4.22±0.10)GeV; they are consistent with the experimental data on the πχc1 invariant mass ...

The rapid growing of information technology (IT) motivates and makes competitive advantages in health care industry. Nowadays, many hospitals try to build a successful customer relationship management (CRM) to recognize target and potential patients, increase patient loyalty and satisfaction and finally maximize their profitability. Many hospitals have large data warehouses containing customer ...

A multiple smooth model is proposed by smoothing technique and piecewise technique for large scale data. Mapping the training data to the hidden space with a hidden function, the proposed model divides the original data into several subclasses by Fuzzy C Means (FCM), whose initial cluster centers are selected by samples with large density indexes; derives the smooth differentiable model by util...