Written communication is of utmost importance to the progress of scientific research. The speed of such development, however, may be affected by the scarcity of reviewers to referee the quality of research articles. In this context, automatic approac
hes that are able to query linguistic segments in written contributions by detecting the presence or absence of common rhetorical patterns have become a necessity. This paper aims to compare supervised machine learning techniques tested to accomplish genre analysis in Introduction sections of software engineering articles. A semi-supervised approach was carried out to augment the number of annotated sentences in SciSents (Avaliable on: ANONYMOUS). Two supervised approaches using SVM and logistic regression were undertaken to assess the F-score for genre analysis in the corpus. A technique based on logistic regression and BERT has been found to perform genre analysis highly satisfactorily with an average of 88.25 on F-score when retrieving patterns at an overall level.
This research aims to identify the reality of librarian service in two
schools from the first cycle of basic education schools, and to
determine the degree of teacher usage for learning techniques
available in schools libraries, and to achieve the
se objects a
observation card and three questionnaires were prepared and they
were given to librarians, teachers, and a sample of students, and it
has been applied on two schools from the first cycle schools in
Damascus: Ibrahim Hanano and Al-Amal schools, and the number
of sample members were (156) member distributors as the
following: the librarian at both schools, (14) teachers and (140)
students.
The results showed that the reality of the school library is
inadequate in terms of physical environment and the available
collectibles, As for the librarian he is not a specialist in the field of
libraries but he practiced the required role requested from him to the
fullest.
