Recent multilingual pre-trained models, like XLM-RoBERTa (XLM-R), have been demonstrated effective in many cross-lingual tasks. However, there are still gaps between the contextualized representations of similar words in different languages. To solve
this problem, we propose a novel framework named Multi-View Mixed Language Training (MVMLT), which leverages code-switched data with multi-view learning to fine-tune XLM-R. MVMLT uses gradient-based saliency to extract keywords which are the most relevant to downstream tasks and replaces them with the corresponding words in the target language dynamically. Furthermore, MVMLT utilizes multi-view learning to encourage contextualized embeddings to align into a more refined language-invariant space. Extensive experiments with four languages show that our model achieves state-of-the-art results on zero-shot cross-lingual sentiment classification and dialogue state tracking tasks, demonstrating the effectiveness of our proposed model.
Background& Objective: Onychomycosis is a frequent nail disease caused by dermatophytes, yeasts, and
non-dermatophyte molds. Far more than being a simple cosmetic problem, infected nail serves as a
chronic reservoir, which can give rise to repeated
mycotic infections.
This study aim to identify the common fungal species which are responsible for onychomycosis in
clinically suspected patients of onychomycosis in Dermatology and Venereal Diseases Hospital in
Damascus between October 2010 and July 2011.
Materials & Methods: Both direct microscopy and culture of the nail material were performed to identify
the causative fungi of onychomycosis.
Results: Culture positivity was obtained in 65 of the 76 clinically suspected samples, etiological fungal
agents were (%61.5) dermatophytes, (24.6%) yeasts, and (13.9 %) non-dermatophyte molds . The isolated
fungal species were (43.1%) Trichophyton Rubrum and (16.9%) T. Interdigitale (1.5%) T.Verrucosum
Aspergillus Versicolor which was the most frequent non dermatophyte molds. Females were affected in
fingernails more frequently than males, while males were affected in toenails more frequently than
females, and in both sexes those most infected were between 20-40 years of age.
Conclusion: Dermatophytes, in particular T. rubrum, but also T. Interdigitale, are the most frequently
isolated causative agents in onychomycosis in patients seen in Dermatology and Venereal Diseases
Hospital in Damascus . In addition, yeasts may be isolated relatively frequently, while molds are
uncommon.
The researcher study the color concept in modern age, and clarify the
theories of harmony and contrast of colors. Also he talked about the color
philosophy, which include a study of the relation between color and shape,
form, space…, and a study o
f the psychological' colors effects on number of
interiors, Residential, Educational, Cultural, Commercial, Health care…
Finally, the research end to give the most important considerations and
steps that should be followed in the study to any color scheme of an interior
space, in a way that achieve the functional aspect as first, and aesthetic
aspect as second.
The topic of this research aims at minimizing carpet image color number
(acquired by a scanner) from 16 million colors to 5 colors, in order to restore
the shapes of the original image automatically without distortions.
For this purpose an algorit
hm was developed for the application called CDS
(Carpet Design System)- which is an application developed locally for use in
sewing carpets in General Institution of Texture Factory in Syria-, but the
results are still not acceptable, because the resulting images have a lot of
distortions, and they need some processing using an image processing
application (ex. Photoshop). This task needs more than tow weeks.
In this research work, we study the CDS algorithm, and other color
quantification algorithms, developed in research laboratories specialized in
image processing. We apply this algorithms on carpet images, after doing the
necessary modifications for tuning and adapting to our special problem. Finally
we compare the results, and suggest the best solution for the problem.
