Proceedings of the Conference on Human and Economic Resources

Knowledge and technological innovation play a crucial role in economic activities in parallel with the technological infrastructure recognized by managers, scientists, and engineers, together with the related telecommunications, information systems, environment, microelectronics machinery and computer-based transportation. As it could be easily seen, technical progress has direct effects only on production. Through process or product innovation, it is evident that to maintain a kind of feedback on education and human capital formation is the natural result of the investment inputs closely connected with the scholastic fashion. Education and technological change are major determinant of economic, cultural, political, social, demographic changes. It must be borne in mind that considering the global aspect of the economic system, one should emphasize the importance of the inclusion of information and communication technologies (ICT) in education, which naturally result in the productivity of education outputs. In parallel with the close relationship between human capital and social capital, which are closely connected with each other and at the same time trigger each other. All of them aim at the well being of economy. It related theoretical literature framework of our study would be analysed in the light of variable such as globalisation, ICT, education, human capital, social capital, and economy well being.education,knowledge, information technology, communication technology

Relating Developers’ Concepts and Artefact Vocabulary in a Financial Software Module

Developers working on unfamiliar systems are challenged to accurately identify where and how high-level concepts are implemented in the source code. Without additional help, concept location can become a tedious, time-consuming and error-prone task. In this paper we study an industrial financial application for which we had access to the user guide, the source code, and some change requests. We compared the relative importance of the domain concepts, as understood by developers, in the user manual and in the source code. We also searched the code for the concepts occurring in change requests, to see if they could point developers to code to be modified. We varied the searches (using exact and stem matching, discarding stop-words, etc.) and present the precision and recall. We discuss the implication of our results for maintenance

Neural fuzzy repair : integrating fuzzy matches into neural machine translation

We present a simple yet powerful data augmentation method for boosting Neural Machine Translation (NMT) performance by leveraging information retrieved from a Translation Memory (TM). We propose and test two methods for augmenting NMT training data with fuzzy TM matches. Tests on the DGT-TM data set for two language pairs show consistent and substantial improvements over a range of baseline systems. The results suggest that this method is promising for any translation environment in which a sizeable TM is available and a certain amount of repetition across translations is to be expected, especially considering its ease of implementation

Approximate Analytical Solutions of the Effective Mass Dirac Equation for the generalized Hulthen Potential with any kappa-Value

The Dirac equation, with position-dependent mass, is solved approximately for the generalized Hulth\'{e}n potential with any spin-orbit quantum number $\kappa$. Solutions are obtained by using an appropriate coordinate transformation, reducing the effective mass Dirac equation to a Schr\"{o}dinger-like differential equation. The Nikiforov-Uvarov method is used in the calculations to obtain energy eigenvalues and the corresponding wave functions. Numerical results are compared with those given in the literature. Analytical results are also obtained for the case of constant mass and the results are in good agreement with the literature.Comment: 13 page

Quantifying the effect of machine translation in a high-quality human translation production process

This paper studies the impact of machine translation (MT) on the translation workflow at the Directorate-General for Translation (DGT), focusing on two language pairs and two MT paradigms: English-into-French with statistical MT and English-into-Finnish with neural MT. We collected data from 20 professional translators at DGT while they carried out real translation tasks in normal working conditions. The participants enabled/disabled MT for half of the segments in each document. They filled in a survey at the end of the logging period. We measured the productivity gains (or losses) resulting from the use of MT and examined the relationship between technical effort and temporal effort. The results show that while the usage of MT leads to productivity gains on average, this is not the case for all translators. Moreover, the two technical effort indicators used in this study show weak correlations with post-editing time. The translators' perception of their speed gains was more or less in line with the actual results. Reduction of typing effort is the most frequently mentioned reason why participants preferred working with MT, but also the psychological benefits of not having to start from scratch were often mentioned

Literary machine translation under the magnifying glass : assessing the quality of an NMT-translated detective novel on document level

Several studies (covering many language pairs and translation tasks) have demonstrated that translation quality has improved enormously since the emergence of neural machine translation systems. This raises the question whether such systems are able to produce high-quality translations for more creative text types such as literature and whether they are able to generate coherent translations on document level. Our study aimed to investigate these two questions by carrying out a document-level evaluation of the raw NMT output of an entire novel. We translated Agatha Christie's novel The Mysterious Affair at Styles with Google's NMT system from English into Dutch and annotated it in two steps: first all fluency errors, then all accuracy errors. We report on the overall quality, determine the remaining issues, compare the most frequent error types to those in general-domain MT, and investigate whether any accuracy and fluency errors co-occur regularly. Additionally, we assess the inter-annotator agreement on the first chapter of the novel

Approximate Analytical Solutions of the Klein-Gordon Equation for Hulthen Potential with Position-Dependent Mass

The Klein-Gordon equation is solved approximately for the Hulth\'{e}n potential for any angular momentum quantum number $\ell$ with the position-dependent mass. Solutions are obtained reducing the Klein-Gordon equation into a Schr\"{o}dinger-like differential equation by using an appropriate coordinate transformation. The Nikiforov-Uvarov method is used in the calculations to get an energy eigenvalue and and the wave functions. It is found that the results in the case of constant mass are in good agreement with the ones obtained in the literature.Comment: 15 pages, two table

UGENT-LT3 SCATE Submission for WMT16 Shared Task on Quality Estimation

This paper describes the submission of the UGENT-LT3 SCATE system to the WMT16 Shared Task on Quality Estimation (QE), viz. English-German word and sentence-level QE. Based on the observation that the data set is homogeneous (all sentences belong to the IT domain), we performed bilingual terminology extraction and added features derived from the resulting term list to the well-performing features of the word-level QE task of last year. For sentence-level QE, we analyzed the importance of the features and based on those insights extended the feature set of last year. We also experimented with different learning methods and ensembles. We present our observations from the different experiments we conducted and our submissions for both tasks