Visualization

The present study aimed at investigating the effects of applying yoga, visualization, and Rosetta Stone software on English achievement of Iranian senior citizen EFL learners. Prior to this study, the homogeneity of the learners was checked through conducting Oxford Quick Placement Test (OQPT). Consulting the rating scale of OQPT, 30 female elementary level senior citizen EFL learners between the ages of 55 and 65 were selected to take part in the study. The participants sat for an English achievement test designed based on their textbook. They were, then, assigned to two groups of control and experimental. The members of the experimental group were taught English while practicing yoga, visualization, and applying Rosetta Stone software program, whereas their counterparts in the control group were taught via the conventional method of teaching English in the elderly day-care center. The procedure lasted for 30 sessions during the three-month treatment. Afterwards, the posttest which was similar to the pretest was administered to unravel the effect of the treatment. They were also given an attitude questionnaire to uncover their attitude towards the applied instruments. The results of the study indicated that the members of the experimental group outperformed those of the control group in terms of their English learning. The results of the attitude questionnaire demonstrated that they had positive attitudes towards the use of yoga, visualization, and Rosetta Stone software in learning English. The results of this study may offer implications for EFL teachers, curriculum designers, day-care centers of the elderly, well-fare organizations, and language schools.  

Being aware of people's attitudes and emotions about a specific person or an event can have a high impact on the decisions of individuals and organizations. With the rise of social networks, specifically Instagram, many people are sharing their attitudes on this social network. Analyzing the emotions of users of this social network can help managers make organizational decisions and predict essential events such as elections. In this research, the EAS system designed and implemented to extract emotions and visualize them. As a practical example, the Instagram users' feelings about the two main candidates for the 12th Iranian presidential election also examined. The data were Instagram Persian comments collected using a developed crawler. The result shows a more positive feeling about Rouhani in comparison with Raeisi. Also, the lexicon-based analysis of Rouhani revealed a high level of trust emotion, along with anger and disgust. The crawled and preprocessed dataset is publicly available at https://github.com/sfdk74/EAS.

The article explores approaches to assessing the quality of health care sites. The main components of evaluation are identified. The author's toolkit for health site evaluation is offered. It is based on the three branches of resource competitiveness (content, technical and marketing components). Twenty parameters of site quality calculation are defined, which have the scale and are supported by determining the weights of components. The scaling of the resulting indicator is proposed. It allows designation of the level of development of the particular site in the field of health. The practical approbation of the proposed method was carried out on the example of Ukrainian sites on the topic of rehabilitation and disease prevention. The diagram of the grouping of websites on a level of development of separate components is constructed to define the further directions of work with these sites to strengthen their competitive positions in the "Health" category. The author's typology of health sites depending on the calculated numerical combinations of the quality assessment level of components is given. It also describes the state of the "ideal" mix of components of the health site, which is formed based on the balance of individual elements.