Is machine translation a dim technology for its users? An eye tracking study.

State-of-the-art research shows that the impact of language technologies on public awareness and attitudes toward using machine translation has been changing. As machine translation acceptability is considered to be a multilayered concept, this paper employs criteria of usability, satisfaction and quality as components of acceptability measurement. The study seeks to determine whether there are any differences in the machine-translation acceptability between professional users, i.e., translators and language editors, and non-professional users, i.e., ordinary users of machine translation who use it for non-professional everyday purposes. The main research questions whether non-professional users process raw machine translation output in the same way as professional users and whether there is a difference in the processing of raw machine-translated output between users with different levels of machine-translated text acceptability are analyzed. The results of an eye tracking experiment, measuring fixation time, dwell time and glance count, indicate a difference between professional and non-professional users' cognitive processing and acceptability of machine translation output: translators and language editors spend more time overall reading the machine-translated texts, possibly because of their deeper critical awareness as well as professional attitude toward the text. In terms of acceptability overall, professional translators critically assess machine translation on all components of which confirms the findings of previous similar research. However, the study draws attention to non-professional users' lower awareness regarding machine translation quality. The study was conducted within a research project that received funding from the Research Council of Lithuania (LMTLT, agreement No S-MOD-21-2), seeking to explore and evaluate the impact on society of machine translation technological solutions.

Integrating global data into local health data base.

Data analysis traditionally belong to scientist's field of interest. Usually scientists gatherer and analyze their own data. Challenges of 21st century require more global point view in decision making process from each worker in local workplace. Local public health sector is strongly related with global world. So, right managerial decision-making in local workplaces depends on changes in global environment. The speed of changes is very high. Therefore, it is necessary to encourage workers of public health sector to make daily managerial decisions evaluating both global and local data. Information technologies (IT) supports decision making process. It is easier to analyze homogeneous data. Analysis of global data has shown that data formats were often incompatible. Limited IT competencies of public health workers make analysis of data from different sources difficult. This article describes a method for integration of global heterogeneous data in local databases.