The use of mobile devices for informal learning has gained attention over recent years. Museum learning is also regarded as an important research topic in the field of informal learning. This study explored a blended mobile museum learning environment (BMMLE). Moreover, this study applied three blended museum learning modes: (a) the traditional museum visit accompanied by a learning website, (b...

Increasing attention has been paid of late to the problem of detecting and explaining “deviant” process instances, i.e. instances diverging from normal/desired outcomes (e.g., frauds, faults, SLA violations), based on log data. Current solutions allow to discriminate between deviant and normal instances, by combining the extraction of (sequence-based) behavioral patterns with standard classifie...

One of the most significant aspects of current sport psychology research is the trend toward developing the relationship between theoretical concepts and practical applications. There have been many recent calls for the development of specific experimental paradigms closely linked to critical features of movement control and social interaction within specific frames of reference such as competi...

We investigated the thermoelectric properties of the ternary half-Heusler compound, TiNiSn, when introducing C and N. The addition of C or N to TiNiSn leads to an enhanced power factor and a decreasing lattice thermal conductivity by point defect phonon scattering. The thermoelectric performances of TiNiSn alloys are significantly improved by adding 1 at. % TiN, TiC, and figure of merit (ZT) va...

previous evidence has shown that the number of l and m cones in retina varies significantly between subjects. however, it is not clear how the variation of l/m ratio changes the behavioral performance of the subject. a model of transformation of data from retina to visual cortex for evaluation of various l/m cones ratios is presented. while l/m cone ratios close to 1 brings the best performance...

In this work, we aim at building a bridge from poor behavioral data to an effective, quick-response, and robust behavior model for online identity theft detection. We concentrate on this issue in online social networks (OSNs) where users usually have composite behavioral records, consisting of multi-dimensional low-quality data, e.g., offline check-ins and online user generated content (UGC). A...