Computer-based learning systems can now keep detailed logs of user-system interactions, including key clicks, eye-tracking, and video data, opening up new opportunities to study how students learn with technology. Educational Data Mining (EDM; Romero, Ventura, Pechenizkiy, & Baker, 2010) is concerned with developing, researching, and applying computerized methods to detect patterns in large col...

A model for rhythm similarity in electronic dance music (EDM) is presented in this paper. Rhythm in EDM is built on the concept of a ‘loop’, a repeating sequence typically associated with a four-measure percussive pattern. The presented model calculates rhythm similarity between segments of EDM in the following steps. 1) Each segment is split in different perceptual rhythmic streams. 2) Each st...

Electrical Discharge Machining (EDM) is a non conventional machining process, where electrically conductive materials are machined by using precisely controlled sparks that occur between an electrode and a work piece in the presence of a dielectric fluid. It has been a demanding research area to model and optimize the EDM process in the present scenario. Lots of efforts have been exercised to m...

We analyze the constraints on CP-violating, flavor conserving two Higgs doublet models implied by measurements of Higgs boson properties at the Large Hadron Collider (LHC) and by the nonobservation of permanent electric dipole moments (EDMs) of molecules, atoms, and neutrons. We find that the LHC and EDM constraints are largely complementary, with the LHC studies constraining the mixing between...

Educational data mining is inherently falls into the category of the so-called secondary data analysis. It is common that data that have been collected for administrative or some other purposes at some point is considered as valuable for other (research) purpose. Collection of the student generated, student behavior and student performance related data on a massive scale in MOOCs, ITSs, LMS and...

In this paper we discuss the role of uncertainty in Knowledge Discovery in Databases (KDD) and discuss the applicability of Evidence Theory towards achieving the goal of handling the uncertainty successfully, incorporating it into the discovery process. We claim that Evidence Theory is more suitable for representing and handling uncertainty within KDD than the Bayesian Model and present a case ...

In this Research, the desktop micro forming manufacturing system has been developed. A micro forming system has been achieved in Japan and its developed micro press is limited to single forming process. To coincide with the purpose to be more practical, research and development is necessary about the press which the multi forming process is possible. Micro patterned metal components are used in...

Elman Networks is a one of the dynamic recurrent neural networks. In this research it is used for the prediction of surface roughness in Electrical Discharge Machining (EDM). Training of the models was performed with data from series of EDM experiments on SKD 11 (AISI D2) Tool steel; in the development of predictive models, machining parameters of discharge current, pulse duration and duty cycl...

The business-to–consumer is the most visible business type of electronic commerce. Online shopping allows companies to provide product information and direct sales to their consumers. In order to effectively drive consumers to accept electronic commerce and online transactions, there is an urgent need to understand the factors that influence consumer behavior towards continued use of online tra...

As an interdisciplinary discipline, data mining (DM) is popular in education area especially when examining students’ learning performances. It focuses on analyzing educational related data to develop models for improving learners’ learning experiences and enhancing institutional effectiveness. Therefore, DM does help education institutions provide highquality education for its learners. Applyi...