In this article a multi-source system is presented as a case-study in order to show how agents can be used to build a dynamic dictionary. In this context a dictionary has a much wider sense than usual: anything that can give information about a term (whatever term may be) is a dictionary. The dictionary is composed by several information sources with different domains (knowledge area and cardin...

This study aimed to investigate the impact of web-based cooperative teaching through strategy-based instruction on EFL learners’ speaking and listening skills. Moreover, the use of cooperative teaching was hypothesized to have impact on the EFL learners’ self-efficacy. To this purpose, the study followed a mixed-methods design by implementing both qualitative and quantitative data gathering pro...

In this paper, we propose a new sampling strategy for hyperspectral signals that is based on dictionary learning and singular value decomposition (SVD). Specifically, we first learn a sparsifying dictionary from training spectral data using dictionary learning. We then perform an SVD on the dictionary and use the first few left singular vectors as the rows of the measurement matrix to obtain th...

The Bag-of-Visual-Words (BoVW) model is a popular approach for visual recognition. Used successfully in many different tasks, simplicity and good performance are the main reasons for its popularity. The central aspect of this model, the visual dictionary, is used to build mid-level representations based on low level image descriptors. Classifiers are then trained using these mid-level represent...

1: procedure CC-CMA-ES(dim, subN um, lambda, ub, lb, maxF Es) 2: pop(1 : 200, 1 : dim) ← random population 3: (best, best val) ← evaluate(pop) 4: f es ← 200 5: C ← dim × dim unit matrix 6: xw ← dim × 1 random vector 7: σ ← (ub − lb) ÷ 2 8: historyW indow ← 5 9: perf ormanceRecord ← ones(3, historyW indow) 10: while f es < maxF Es do 11: (subInf o, decomposerID) ← adaptiveDecompose(dim, subN um,...