-Enormous numbers of intelligent data mining techniques are in usage to discover hidden patterns. Especially Association rule mining has a high impact on business improvement. However mining association rules at multiplelevel may lead to discovery of more specific and concrete knowledge from data. Privacy is needed in order to withstand the business competence. Now-a-days privacy preserving dat...

In this paper we present an idea of trusted communication platform for Multi-Agent Systems (MAS) called TrustMAS. Based on analysis of routing protocols suitable for MAS we have designed a new proactive hidden routing. Proposed steg-agents discovery procedure, as well as further routes updates and hidden communication, are cryptographically independent. Steganographic exchange can cover heterog...

Motivated by the analogous properties of $Z_c(3900/3885)$ and $Z_{cs}(3985/4000)$, we tentatively assign $Z_c(4020/4025)$ as $A\bar{A}$-type hidden-charm tetraquark state with $J^{PC}=1^{+-}$, where $A$ denotes axialvector diquark states, explore states without strange, strange hidden-strange via QCD sum rules in a consistent way. Then hadronic coupling constants two-body strong decays based on...

Selection rules arising from accidental or broken symmetries may be sufficiently obscure that their agency is hidden, leading to the appearance of "magic zeroes" -- quantities are suppressed without apparent recourse a symmetry explanation. Magic zeroes and corresponding hidden shed new light on parametric hierarchies in Standard Model beyond. We identify responsible for recently-discovered mag...

This paper discusses the possible introduction of hidden reliability defects during CMOS foundry fabrication processes that may lead to accelerated wearout of the devices. These hidden defects or hardware Trojans can be created by deviation from foundry design rules and processing parameters. The Trojans are produced by exploiting time-based wearing mechanisms (HCI, NBTI, TDDB and EM) and/or co...

Reservoir Computing (RC) is a relatively recent architecture for using recurrent neural networks. It has shown interesting performance in a wide range of tasks despite the simple training rules. We use it here in a logistic regression (LogR) framework. Considering non-Markovian time series with a hidden variable, we show that RC can be used to estimate the transition probabilities at each time ...

The chemical name extraction has a great importance in the biomedical field. Named Entity Recognition is the subtask of information extraction that is used to identify named entities in the given data. There are various dictionary-based, rule-based and machine learning approaches available for Named Entity Recognition. Rule based techniques include hand written rules. In this paper an extensive...

This paper focuses on the application of Spatial Data mining Techniques to efficiently manage the challenges faced by peripheral rural areas in analyzing and predicting market scenario and better manage their economy. Spatial data mining is the task of unfolding the implicit knowledge hidden in the spatial databases. The spatial Databases contain both spatial and non-spatial attributes of the a...

In the recent past, many organizations have produced a large amount of machinereadable data in the form of files and databases. The explosive growth in data has generated an urgent need for techniques and tools for extracting useful hidden information from the data, in terms, e.g., of patterns or rules. Information from the data is used to analyze the user behaviour, to improve the services pro...

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 ...