Ten colour emotional scales, namely, "Warm Cool", "Active-Passive", "Like-Dislike", "Clean-Dirty", "Fresh-Stale", "Modern-Classical", "Heavy-Light", "Hard-Soft", "Tense-Relaxed", and "Masculine-Feminine"are investigated for single-colour stimuli in CIE(Lab) colour space within a psychophysical experiment by forty observers. The relationships between Iranian colour emotional responses and CIE(Lab) colour coordinates are examined. Based on the results, colours with higher values of L*are associated to the emotional words, such as clean, light and soft. Colour with higher C* values are also associated to warm, modern, and masculine emotional words. Iranian colour emotional responses are also assayed in three existed colour emotional models, Li Chen Ou' s, Sato's and Xin-Cheng's models, for four colour emotional dimensions, "Warm-Cool", "Heavy-Light", "Active-Passive", and "Hard-Soft" scales. Results show that the Ou's model is a fairly good predictor for "Warm-Cool" scale, while the Xin-Cheng's model is a good predictor for "Heavy-Light" and "Hard-Soft" scales. In "Active-Passive" scale, none of the existed models are found to be a good predictor for Iranian colour emotional dimension.

The synthesis of six new symmetrical disazo direct dyes containing 4,4’-diaminostilbene-2,2’-disulphonic acid as middle component and N-(2-chlorophenyl)-2-hydroxybenzamide, N-(3-chlorophenyl)-2-hydroxybenzamide, N-(4-chlorophenyl)-2-hydroxybenzamide, N-(2-bromophenyl)-2-hydroxybenzamide, N-(3-bromophenyl)-2-hydroxybenzamide, N-(4-bromophenyl)-2-hydroxybenzamide as coupling components is presented. The synthesized dyes were analyzed by thin layer chromatography, electronic spectra and HPLC technique. Their structures were elucidated by FT/IR and 13C-NMR spectroscopy. The CIE(Lab) (1976) colour space was used in all the colour measurements for the six disazo stilbene dyes under the CIE recommended illuminants: D65 (natural day light), A (tungsten light), F2 (fluorescent light) and the standard 10° observer, respectively. The colour differences: DEab* and DECMC were calculated against one standard. The results reveal a good colouring power of the new azo-stilbene dyes.

People are used to exploring grayscale images in their family albums but it is difficult to grasp the reality without colours. Luckily, with advancements in Machine Learning it has been possible to solve problems previously thought impossible. The authors aim to automatically colourize grayscale images using a subset of Machine Learning called Deep Learning. The system will be trained on an image dataset and given an input grayscale image the model will be able to assign aesthetically believable colours. A grayscale photograph has been provided; our approach solves the problem of visualizing a reasonable colour version of the grayscale picture. This issue is undoubtedly under controlled; therefore earlier methods to this problem have either counted majorly on user interaction or it leads to in unsaturated colourizations. The authors put forward a completely automatic approach that will try to produce realistic and vibrant colourizations as much as possible. The proposed system has been applied as a feed-forward in a Convolutional Neural Network and has been trained on over twenty thousand colour images currently.

The present study compares the performance of two TEFL reading classes: one taking place in a regular classroom and the other held in a computer (Lab), with the learners practicing reading online. The results of an independent samples t-test showed that the difference between the learners’ scores on their reading comprehension post-tests and pretests did not differ statistically significantly from one group to the other, indicating that the two groups’ progress was similar during the one-term period of instruction. In addition to this, learner interviews and teacher observations showed that some of the challenges of practicing reading in a computer (Lab) included an over-reliance on copy/pasting; time wasted and stress induced due to Internet/technology problems, phobia, or lack of expertise; distractions created through working with technology; and occasional lack of learners’ awareness of the benefits of online reading. Yet, despite all this, reading online seems to have benefits which make it worth all the difficulties and extra effort.