Plagiarism means taking another person’s work and not giving any credit to them for it. Plagiarism is one of the most serious problems in academia and among researchers. Even though there are multiple tools available to detect plagiarism in a document but most of them are domain-specific and designed to work in English texts, but plagiarism is not limited to a single language only. Bengali is the most widely spoken language of Bangladesh and the second most spoken language in India with 300 million native speakers and 37 million second-language speakers. Plagiarism detection requires a large corpus for comparison. Bengali Literature has a history of 1300 years. Hence most Bengali Literature books are not yet digitalized properly. As there was no such corpus present for our purpose so we have collected Bengali Literature books from the National Digital Library of India and with a comprehensive methodology extracted texts from it and constructed our corpus. Our experimental results find out average accuracy between 72.10 % - 79.89 % in text extraction using OCR. Levenshtein Distance algorithm is used for determining Plagiarism. We have built a web application for end-user and successfully tested it for Plagiarism detection in Bengali texts. In future, we aim to construct a corpus with more books for more accurate detection.

Cheating is a kind of fraud or attempts to get dishonest advantages in an academic institution, it has been increasing dramatically for the last 50 years with the growth of technology. In some countries, this phenomenon has changed to a problematic factor in schools. Plagiarism is also considered as a type of cheating if it occurs intentionally. More efforts are made to mitigate the severity of cheating in an academic institution using technological-based devices. Besides, technology has an effective role in the detection of plagiarism by several detection platforms, however, still, there are some types of plagiarism which cannot be detected by these platforms efficiently, that authors should treat honestly during his/her scientific writing. This work aims to conceptualize and characterize cheating and plagiarism in an academic institution, also it is tried to indicate the relationship of cheating and plagiarism that in which cases, plagiarism becomes cheating. To achieve the purposes, relevant literature including scientific papers, monographs, reports, and authorized website were reviewed, and the literature output are integrated with the observation and experience of author during the teaching and learning in academic institutions.The findings and direct observation from close contact of classrooms show that cheating is felt mostly in classes with large numbers of students, that institution policy, instructor control, and using of technology have the most effect on the controlling cheating. Plagiarism as academic dishonesty is a widespread phenomenon among the students and even the authors. In some cases, the poor understanding of students and authors in scientific writing rules causes plagiarism and is measurable by some available detection platforms.

The concept of Research Integrity and research ethics are linked to the scientific research process and its communication. Presenting the results objectively is essential. It turns out that few scientists use manipulation of results and consequently other types of misconduct such as data Fabrication, Falsification, and Plagiarism (FFP). In this article, we show the definitions of these and different aspects of behavior that should be avoided, which affect principles of research reliability. We present, through a brief literature review, the concept of Research Integrity, FFP, and its relations with Publish or Perish. Editorial disputes are linked to the power that scientists have to remain in the field of research, governed by clear rules to increase their intellectual capital. We discussed that scientists tend to want their papers published in journals with better impact and well-evaluated, seeking prominence in the publishing sector. We have seen that both scientists and journals can have sequelae and problems in the face of the Publish or Perish movement, which can call into question the quality of the editorial process, peer review, and the journal itself.

The recent advancement of Artificial Intelligence (AI) and Machine Learning (ML) tools has had a pervasive effect on every sphere of human existence. Libraries and information centres are not immune to these technological advances. These disruptive technologies have transformed the traditional face of libraries and their operations. There are many available AI tools, for example, chatbots, literature review tools, plagiarism detection tools, and several other developments in the field that have perhaps made the functioning of libraries easier. However, there is growing concern and uncertainty among both traditional library and modern professionals regarding the possible job loss and security issues related to these new technologies, which the professionals must deal with. Librarians and information professionals must be ready to handle the unforeseen situation. However, it is to be observed how libraries cope with these uncertainties, and threats to the integrity, availability of data, and normal library housekeeping functions.