We evaluated exposure of aquatic biota to lead (Pb), zinc (Zn), and cadmium (Cd) in streams draining a Pb-mining district in southeast Missouri. Samples of plant biomass (detritus, periphyton, and filamentous algae), invertebrates (snails, crayfish, and riffle benthos), and two taxa of fish were collected from seven sites closest to mining areas (mining sites), four sites further downstream fro...

in this study, results of noise level measurements performed in 4 different mining sites aregiven. noise level measurements performed in opencast mining site of konya ilgin lignite corporation (ilc), in konya eyak mining quarry site and in aydin cine feldspar ore dressing facility have been evaluatedtogether with worker surveys. the noise level measurements performed in manisa soma uyar mining ...

process mining includes the automated discovery of petri nets from event logs. these event logs are the starting point for various discovery and analysis techniques of the process.  in this paper process model is developed using colored petri nets (cpns) and the supporting software package cpn tools. the restaurant process model is represented for the analysis using a combination of process min...

in this study, results of noise level measurements performed in 4 different mining sites aregiven. noise level measurements performed in opencast mining site of konya ilgin lignite corporation (ilc), in konya eyak mining quarry site and in aydin cine feldspar ore dressing facility have been evaluatedtogether with worker surveys. the noise level measurements performed in manisa soma uyar mining ...

Data mining is the process of deriving knowledge from data. The data clustering is a classical activity in data mining. In this paper we propose a method to carry out data clustering using genetic algorithms. We use evolutionary characteristics to define the data clustering procedure. In addition, we present an example of application of our approach, the definition of healthcare centers for a g...

We describe an accelerometer based activity recognition system for mobile phones with a special focus on personal time management. We compare several data mining algorithms for the automatic recognition task in the case of single user and multiuser scenario, and improve accuracy with heuristics and advanced data mining methods. The results show that daily activities can be recognized with high ...

Data mining is an emerging area to discover knowledge from a tremendously large database or data warehouse. Plan mining is an extension activity of data mining. Given a set of plans, the objective is to enable user to know the interesting plans. With the proliferation of database technology, planbase are increasingly common.Efficient patterns of actions discovery, valuating the planbase, and de...

The rate at which organizations are acquiring data is getting out of proportion and managing such data so as to infer useful knowledge that can be put to use is increasingly becoming important and challenging. Data Mining (DM) is one such relatively recently technology that has emerged that is employed in inferring useful knowledge that can be put to used from a vast amount of data. This paper ...

Detecting abnormal user activity in social network websites could prevent from cyber-crime occurrence. The previous research focused on data mining while this research is based on user behavior process. In this study, the first step is defining a normal user behavioral pattern and the second step is detecting abnormal behavior. These two steps are applied on a case study that includes real and ...