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The pressure of publication pushes back the frontiers of laziness. Here, a sole change in a paper title allows the paper to pass through reviews (if there are any reviews in this case, look at Nuit Blanche on peer review).
If you steal from one author it's plagiarism; if you steal from many it's research. (attributed to Wilson Mizner)
The most interesting example i had seen so far was a paper i reviewed on nonsubsampled contourlets (a kind of discretized, directional wavelet). It was entitled "A New Image Denoising Scheme using the Nonsubsampled Contourlet Transform", and submitted in 2008 to Signal Processing by three authors from one of the two most populated countries in the world. Its content had about 60% overlap with a more standard and authoritative paper on the topic. A big difference resided in the typeset: the text was written with word (instead of LaTeX), the figures were drawn in Word too (instead of Xfig, InkScape). I hereby provide a little excerpt, so you can check the subtle differences:
Original paper: 2) Nonsubsampled Directional Filter Bank (NSDFB): The directional filter bank of Bamberger and Smith [18] is constructed by combining critically-sampled two-channel fan filter banks and resampling operations. The result is a tree-structured filter bank that splits the 2-D frequency plane into directional wedges. A shift-invariant directional expansion is obtained with a nonsubsampled DFB (NSDFB). The NSDFB is constructed by eliminating the downsamplers and upsamplers in the DFB (see also [20]). This is done by switching off the downsamplers/upsamplers in each two-channel filter bank in the DFB tree structure and upsampling the filters accordingly. This results in a tree composed of two-channel NSFBs. Fig. 3 illustrates a four channel decomposition.
Submitted paper: b: Nonsubsampled Directional Filter Bank (NSDFB) The directional filter bank of Bamberger and Smith [14] is constructed by combining critically-sampled two-channel fan filter banks and resampling operations. The result is a tree-structured filter bank that splits the 2-D frequency plane into directional wedges. A shift-invariant directional expansion is obtained with a nonsubsampled DFB (NSDFB). The NSDFB is constructed by eliminating the downsamplers and upsamplers in the DFB. This is done by switching off the downsamplers/upsamplers in each two-channel filter bank in the DFB tree structure and upsampling the filters accordingly. This results in a tree composed of two-channel Nonsubsampled Filter Banks (NSFB). Fig. 3 illustrates a four channel decomposition.
But i am very unfair: the reference list was quite different. Interestingly, to the genuine honesty of the (submitting) authors, the partly copied paper EVEN cited the original paper: Arthur L. Cunha, Jianping Zhou, Minh N. Do. The nonsubsampled contourlet transform: Theory, design, and applications. IEEE Trans. on Image processing, 2006, 15(10): 3089-3101. The paper was subsequently rejected. But (i just discovered it today, 2014/12/29), that in 2011, a paper intitled "Performance Analysis of Modified Nonsubsampled Contourlet Transform for Image Denoising" was published in the Research Journal of Applied Science, Engineering and Technology. It was written by two authors from the other of the two most populated countries in the world.
It was received: March 16, 2011, accepted: May 18, 2011 and published: July 25, 2011. That's a fast track. And it possesses many cut-caste-plagiarized parts taken from A. L. da Cunha 2006 paper, as i show below, only from the introduction:
- original: Another important feature of a transform is its stability with respect to shifts of the input signal.
- pasted: Another important feature of a transform is its stability with respect to shifts of the input signal.
- original: Thus, most state-of-the-art wavelet denoising algorithms (see for example [6]–[8]) use an expansion with less shift sensitivity than the standard maximally decimated wavelet decomposition—the most common being the nonsubsampled wavelet transform (NSWT) computed with the à trous algorithm [9].
- pasted: Thus, most state-of-the-art wavelet denoising algorithms (Chang, 2000) use an expansion with less shift sensitivity than the standard maximally decimated wavelet decomposition the most common being the nonsubsampled wavelet transform (NSWT) computed with a trous algorithm (Shensa, 1992) now it is implemented using Mat lab software
- original: In addition to shift-invariance, it has been recognized that an efficient image representation has to account for the geometrical structure pervasive in natural scenes. In this direction, several representation schemes have recently been proposed [10]–[15].
- pasted: In addition to shift-invariance, it has been recognized that an efficient image representation has to account for the geometrical structure pervasive in natural scenes. In this direction, several representation schemes have recently been proposed (Donoho, 1999).
- original: In this paper, we propose an overcomplete transform that we call the nonsubsampled contourlet transform (NSCT). Our main motivation is to construct a flexible and efficient transform targeting applications where redundancy is not a major issue (e.g., denoising). The NSCT is a fully shift-invariant, multiscale, and multidirection expansion that has a fast implementation. The proposed construction leads to a filter-design problem that to the best of our knowledge has not been addressed elsewhere. The design problem is much less constrained than that of contourlets. This enables us to design filters with better frequency selectivity thereby achieving better subband decomposition. Using the mapping approach we provide a framework for filter design that ensures good frequency localization in addition to having a fast implementation through ladders steps. The NSCT has proven to be very efficient in image denoising and image enhancement as we show in this paper.
- pasted: So In this study, we propose an over complete transform that we call the modified Nonsubsampled Contourlet Transform (NSCT). Our main motivation is to construct a flexible and efficient transform targeting applications where redundancy is not a major issue (e.g., denoising). The NSCT is a fully shift-invariant, multiscale, and multidirectional expansion that has a fast implementation. The proposed construction leads to a filter-design problem that to the best of our knowledge has not been addressed elsewhere. The design problem is much less constrained than that of contourlets.This enables us to design filters with better frequency selectivity thereby achieving better subband decomposition. So the NSCT has proven to be very efficient in image denoising.So first let us see the contourlet transform and its construction.
The new authors have mostly subsampled the reference list, so to say.
I am not sure this recent "copy-paste-publish" trend deserves as much praise as Jorge Luis Borges short story: Pierre Menard, autor del Quijote. The story narrates 20th century writer Pierre Ménard's efforts to truly re-create Cervantes' Don Quixote, beyond a mere translation, in the 17th century Spanish, sparking thoughts on authorship, imitation and appropriation (well, 60% of my words are similar here to the Wikipedia page ;) There are worse artifacts than copy indeed: "Mirrors and fatherhood are abominable because they multiply it [human kind] and extend it.(Les miroirs et la copulation sont abominables car ils multiplient le nombre des hommes)" (J. L. Borges).
The recent example did some genuine editing: the title is partly new (SOA is mainly expanded), acknowledgments have been deleted, and the references cut to item 21. That's a Catch 22.
- Interacting with the SOA-Based Internet of Things: Discovery, Query, Selection, and On-Demand Provisioning of Web Services, IEEE TRANSACTIONS ON SERVICES COMPUTING, 2010: http://www.vs.inf.ethz.ch/res/papers/dguinard-intera-2010.pdf
- Service Oriented Architecture-Based Internet of Things: Discovery, Query, Selection, and On-Demand Provisioning of Web Services, International Journal of Computer Science and Telecommunications, 2012 http://www.ijcst.org/Volume3/Issue1/p7_3_1.pdf ([EDIT] funnily, the paper does not seem to be accessible anymore since the publication of this post. Still there is a Google Trace, and i have saved it on my drive, in case i'd like to publish a paper on SOA-based Internet of Things in a near future ;)
Click on images for a larger view. I just discover there is a Wikipedia page in Scientific plagiarism in India.