Genome-wide association studies have successfully identified hundreds of novel genetic variants associated with many complex human diseases. However, there is a lack of rigorous work on evaluating the statistical power for identifying these variants. In this paper, we consider sparse signal identification in genome-wide association studies and present two analytical frameworks for detailed anal...

Dynamic pattern analysis refers to analyzing the relationship of spatial patterns at different time points. Traditional spatial pattern analysis such as data clustering can find the spatial patterns extant at a geographical location at a particular time point but failing to identify spatial dynamics, or changes that occur over time in a particular place. In this paper, we present a dynamic patt...

Introducing a new device to a network or to another device is one of the most security critical phases of communication in personal networks. It is particularly challenging to make this process of associating devices easy-to-use, secure and inexpensive at the same time. A cornerstone of this process is key establishment. In this paper, we first present a taxonomy of protocols for key establishm...

Formal Concept Analysis (FCA) is a theory whose goal is to discover and to extract Knowledge from qualitative data. It provides tools for reasoning with implication basis (and association rules). In this paper we analyse how to apply FCA reasoning to increase confidence in sports betting, by means of detecting temporal regularities from data. It is applied to build a Knowledge based system for ...

Networks of thousands of sensors present a feasible and economic solution to some of our most challenging problems, such as real-time traffic modeling, military sensing and tracking. Many research projects have been conducted by different organizations regarding wireless sensor networks; however, few of them discuss how to estimate missing sensor data. In this research we present a novel data e...

In this report we present the architecture of the overall data mining system and detail the main functionalities of its visual interface. The semantics of the visual operators is formally given in terms of the language of the corresponding mining techniques, namely metarules, association rules, clustering, approximate similarity queries.

Each gas molecule has its own molecular weight, while such a microscopic characteristic is generally inaccessible, and thus, it is measured indirectly through e.g. ionization in conventional mass analysis. Here, we present a novel approach to the direct measurement of molecular weight through a nanoarchitectonic combination of aerodynamics, thermodynamics, and mechanics, transducing microscopic...

Association rule mining plays vital part in knowledge mining. The difficult task is discovering knowledge or useful rules from the large number of rules generated for reduced support. For pruning or grouping rules, several techniques are used such as rule structure cover methods, informative cover methods, rule clustering, etc. Another way of selecting association rules is based on interestingn...

The recent discovery that microRNAs (miRNAs) are present in the circulation sparked interest in their use as potential biomarkers. In this review, we will summarize the latest findings on circulating miRNAs and cardiovascular disease but also discuss analytical challenges. While research on circulating miRNAs is still in its infancy, high analytical standards in statistics and study design are ...

Association rule mining is an important problem in the data mining area. It enumerates and tests a large number of rules on a dataset and outputs rules that satisfy user-specified constraints. Due to the large number of rules being tested, rules that do not represent real systematic effect in the data can satisfy the given constraints purely by random chance. Hence association rule mining often...