Accurate prediction of protein secondary structure is an important step in understanding protein folding. Most of the knowledge of the secondary structure of proteins comes from the X-ray diiraction patterns of crystallized proteins. However, these crystallographic analyses are very expensive, laborious and time consuming. An alternative is to use the known structures to predict the secondary s...

The present study aimed to investigate the reliability and factor structure of the self-regulating capacity in vocabulary learning strategies scale (SRCvoc) in the Iranian EFL context. To this end, the original (SRCvoc) questionnaire (Tseng, Dornyei, & Schmitt, 2006) was translated into Persian, using a translation/back-translation procedure. Then, the Persian version of the SRCVOC was piloted ...

We present a robust multiple manifolds structure learning (RMMSL) scheme to robustly estimate data structures under the multiple low intrinsic dimensional manifolds assumption. In the local learning stage, RMMSL efficiently estimates local tangent space by weighted low-rank matrix factorization. In the global learning stage, we propose a robust manifold clustering method based on local structur...

The additive clustering (ADCL US) model (Shepard & Arabie, 1979) treats the similarity of two stimuli as a weighted additive measure of their common features. Inspired by recent work in unsupervised learning with multiple cause models, we propose anew, statistically well-motivated algorithm for discovering the structure of natural stimulus classes using the ADCLUS model, which promises substant...

Learning analytics means gathering a broad range of data, bringing the various sources together, and analyzing them. However, to draw educational insights from the results of the analyses, these results must be visualized and presented to the educators and learners. This task is often accomplished by using dashboards equipped with conventional and often simple visualizations such as bar charts ...

According to the transitive dynamics model, people can construct causal structures by linking together configurations of force. The predictions of the model were tested in two experiments in which participants generated new causal relationships by chaining together two (Experiment 1) or three (Experiment 2) causal relations. The predictions of the transitive dynamics model were compared against...

In Knowledge Structure Graph, each course unit represents a phase of learning activities. Both learning portfolios and Knowledge Structure Graphs contain learning information of students and let teachers know which content are difficulties and fails. The study purposes "Dual Mode On-line Learning Diagnosis System" that integrates two search methods: learning portfolio and knowledge structure. T...