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POSTGRADUATE
HANDBOOK
The guidelines for the format by published papers are as follows:
(a) The theses may comprise published papers and/or manuscripts
accepted for publication by high impact journals (e.g. ISI journals). The
papers should be published or accepted for publication during the
period of candidature.
(b) The minimum number of papers and/or manuscripts is normally three
(3). However, in some disciplines a larger number of papers is required
to meet the expectations of scope and quality in accordance with PhD-
level research. For Doctor of Philosophy by Prior Publication mode, the
minimum number of published works is at least five (5) and these
works must be those published within a period not exceeding 10 years
prior to the date of submission of thesis.
(c) Where the papers have more than one writer, the candidate must be the
main writer of at least two (2) out of three (3) papers. For Doctor of
Philosophy by Prior Publication mode, the candidate should be the
primary author of four (4) of the published works submitted.
(d) Normally, the theses shall include the following in addition to the
components required of a standard thesis:
list of publications and/or manuscripts;
acknowledgments of joint writers and evidence of permissions; and
published papers and accepted manuscripts.
(e) Each published paper or accepted manuscript must include a clear
statement of the contribution made by each author of any jointly
written paper. For example, a statement of contribution from a 3-
author academic research publication is as follows:
Tang, M.Y., Adli, D.S.H., & Belabut, D. (2011). Histological
development of selected neural structures of Dark-sided
Chor=frd5t6s Frog, Microhyla heymonsi (Amphibia:
Anura). Malaysian Journal of Science, 29(1), 11-18.
Tang, M.Y. participated in all experiments, coordinated the data
analysis and contributed to the writing of the manuscript. Adli,
D.S.H. supervised the development of work and edited the
manuscript. Belabut, D. gave technical support and conceptual
advice, and helped in data interpretation.
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