In this work, we take all the color-antitriplet diquarks, such as scalar, pseudoscalar, vector, axialvector and tensor basic constituents to construct local pseudoscalar four-quark currents without importing explicit P-waves implement negative-parity, investigate mass spectroscopy of hidden-charm tetraquark states strange, with strange hidden-strange in framework QCD sum rules a consistent comp...

Rule-extraction from trained neural networks has previously been used to generate propositional rule-sets. The extraction of "generic" rules or objects from trained feedforward networks is clearly desirable and sufficient for many applications. We present several approaches to generate a knowledge base that includes rules, facts and a is-a hierarchy that enables the greater explanatory capabili...

Socialisation theories have traditionally focused on how children are socialised in a rather unidirectional manner, according to a transmission model. However, more recent research and theories show that children are not just passive recipients, but active agents in their socialisation process. At the same time, children are subordinated to adult control. In school, they are regimented and invo...

Text mining is a specific method to extract knowledge from structured and unstructured data. This extracted knowledge from text mining process can be used for further usage and discovery. This paper presents the method for extraction information from unstructured text data and the importance of Association Rules Mining, specifically for of Korean language (text) and also, NLP (Natural Language ...

Privacy preserving data mining is a novel research direction in data mining and statistical databases, which has recently been proposed in response to the concerns of preserving personal or sensible information derived from data mining algorithms. There have been two types of privacy proposed concerning data mining. The first type of privacy, called output privacy, is that the data is altered s...

Association rule mining typically focuses on discovering global rules valid across the entire dataset. Yet local rules valid for subsets of the dataset, while significantly different from global rules, are often also of tremendous importance to analysts. In this work, we tackle this overlooked problem of online mining of localized association rules. We provide support for analysts to interactiv...

The information age has enabled organizations to gather large volumes of data. However, the usefulness of this data is negligible if “meaningful information” cannot be extracted from it. Data mining answers this need. The problem of privacy-preserving data mining has become important recently because of the increasing ability to store personal data and the sophistication of data mining algorith...