GENERALIZED ANXIETY DISORDER AND ITS ASSOCIATED FACTORS AMONG FEMALE STUDENTS

Background and Aim: To determine the Generalized Anxiety Disorder and its association with factors like hormonal changes, chronic illness among female students of university. Methodology: Perceptions and preferences of Female Students were determined in well-organized Institute (Superior University) with ages between 16-28 years old of all disciplines. Electronic self-administrated questionnaires consisting of two parts; demographics factors (Age, Gender, Designation, education Discipline, socioeconomic status and medical history) and Generalized Anxiety Disorder GAD-7, were then filled by the participated female students with sample size of 231. Then the perceptions and preferences were evaluated using a pre validated questionnaire (GAD-7) from previous research article. Results: A total of 231 responses were returned. All respondents were females. About (62.7%) of total respondents reported feeling nervous, anxious, or on edge to some degree; 10% of respondents said that they experience this feeling nearly every day. A significant proportion of respondents reported mild to moderate anxiety levels. The mean score of anxiety scale was 3.87±3.32 with minimum and maximum score of 0 and 19. The study findings give us a better considerate that Traumatic disorders (39.4 %), hormone issues (45.2%), were the main causes of anxiety. 39.8% indicated that they had a family history of anxiety. Overall, moderate to high levels of anxiety among the participants were observed. Conclusion: These results illustrate the need to devise treatment strategies to alleviate symptoms of generalized anxiety and reduce the prevalence of Generalized Anxiety Disorder among students. It is suggested that to decrease the level of anxiety among university students, regular counseling sessions should be implemented.

A Study of Plagiarism Detection Using Natural Language Processing Technique

Now a day?s plagiarism became very common in many fields of life such as research and education. It is an illegal deed used to make others work as own property without any proper references. Plagiarism is defined as showing other?s work as your own or using/stealing other?s ideas without any permission. Due to advancement in plagiarism techniques adopted by plagiarist, it is very difficult to detect plagiarism accurately by existing techniques. Different features are observed to determine the presence of plagiarism in documents such as syntactic, lexical, semantic and structural features. Today lots of techniques are introduced to detect plagiarism i.e. string matching, a bag of words, fingerprinting, citation analysis and stylometry . Advance detectors mostly work with source code or natural language text. To detect similarity in natural language texts, detectors commonly explore the Internet. In text analysis, detectors use very easy and simple comparison procedures based on broad coverage and processing speed. This research explores new and modern plagiarism detection tasks especially text-based plagiarism detection includes monolingual plagiarism detection. The main idea behind this research is that rewritten and original text does not have similar text and differences among these documents can be explored with the help of linguistic and statistical indicators. To investigate above statement, the main research objectives are formulated as follow; a four stage novel framework for plagiarism detection is proposed. Natural Language Processing (NLP) is used by this framework instead of focusing on traditional string-matching approaches. The objective of this model is to use text pre-processing and statistical, shallow and deep linguistic techniques using a corpus-based approach. Proposed framework is tested by comparing its working theoretically with other techniques.