OBJECTIVES We examined the health-related quality of life of residents in mountaintop mining counties of Appalachia using the 2006 national Behavioral Risk Factor Surveillance System. METHODS Dependent variables included self-rated health; the number of poor physical, poor mental, and activity limitation days (in the past 30 days); and the Healthy Days Index. Independent variables included me...

Cameroon has a strong geological potential for a number of mineral resources that, if well managed, could support economic growth. The country contains potentially large deposits of iron ore, gold, bauxite, diamond, limestone, nickel, and gemstones, and indices of other numerous minerals and precious metals. Despite its geological wealth, mining has never played a major role in Cameroon’s econo...

Knowledge discovery has received tremendous interests and fast developments in both text mining and social user mining. The main purpose is to search massive volumes of data for patterns as so-called knowledge. Knowledge can exist in different formats such as texts or numbers. Knowledge can be observed or hidden in different hierarchies. Knowledge can even be user-generated such as social conte...

Data Mining is the process of analyzing data from different perspectives and summarizing it into useful information. It can be defined as the activity that extracts information contained in very large database. That information can be used to increase the revenue or cut costs. Association Rule Mining (ARM) is finding out the frequent itemsets or patterns among the existing items from the given ...

due to the rapid growth of data mining technology, obtaining private data on users through this technology becomes easier. association rules mining is one of the data mining techniques to extract useful patterns in the form of association rules. one of the main problems in applying this technique on databases is the disclosure of sensitive data by endangering security and privacy. hiding the as...

In this work, we represent complex video activities as one large activity graph and propose a constraint based graph mining technique to discover a partonomy of classes of subgraphs corresponding to event classes. Events are defined as subgraphs of the activity graph that represent what we regard as interesting interactions, that is, where all objects are actively engaged and are characterized ...

Analyzing Resource Behavior Using Process Mining p. 69 Mobile Workforce Scheduling Problem with Multitask-Processes p. 81 Understanding Spaghetti Models with Sequence Clustering for ProM p. 92 Flexible Multi-dimensional Visualization of Process Enactment Data p. 104 Autonomous Optimization of Business Processes p. 116 Activity Mining by Global Trace Segmentation p. 128 A Formal Model for Proces...

Mining frequent subgraphs is a basic activity that plays an important role in mining graph data. In this paper an algorithm is proposed to find frequent subgraphs in a single large graph that has applications such as protein interactions, social networks, web interactions. One of the key operations required by any frequent subgraph discovery algorithm is to perform graph isomorphism. The propos...

Process mining techniques have proven to be a valuable tool for analyzing the execution of business processes. They rely on logs that identify events at an activity level, i.e., most process mining techniques assume that the information system explicitly supports the notion of activities/tasks. This is often not the case and only low-level events are being supported and logged. For example, use...

Current enterprises spend much effort in obtaining precise models of their software engineering processes in order to improve the process capability of their organization and to move one step forward in the CMM. The manual design of process models, however, is complicated, time-consuming, error-prone and the results are rapidly becoming out-dated; capabilities of humans in detecting discrepanci...