Title: How to Write Good Research Articles
1How to Write Good Research Articles
2Presentation Outline
- Publication Requirement
- Kinds of Scientific Publications
- Where to publish your work
- Plan your writing
- Structure of a Paper
- Case studies
- Q A
3Publication Requirement
- BSc Degree (Minor)
- MPhil Degree / MS by Research / MS (Minor)
- PhD Degree
- Full time researcher / Academics
4Kinds of Scientific Publications
- Thesis
- Aspects to be Assessed for a Thesis
- background knowledge
- original contributions (amount of work)
- methodology
- presentation (writing)
- Conference Publications
- Focus on a piece of work with limited discussion
- Journal Publications
- More complete (extensive) discussion
- Book chapters / Text books
5Where to publish your work
- Journals
- Ranking of journals
- Review process of journals
- Publication cycle
- Conferences
- Ranking of conferences
- Review process of conferences
- N.B. a good journal / conference tends to have
rigorous review process and long review time
6SCI Journal Citation
7Important journals conferences
- Database
- IEEE Trans on Knowledge and Data Engineering
- ACM Trans on Database Systems
- Intl Conf on VLDB
- Software Engineering
- IEEE Trans on Software Engineering
- ACM Trans on Software Eng. and Methodology
- IEEE Intl Conf on Software Engineering
- Distributed Systems
- IEEE Trans on Parallel and Distributed Systems
- ACM Trans on Computer Systems
- IEEE Intl Conf on Distributed Computing Systems
- Computer Networks
- IEEE/ACM Trans on Networking
- IEEE INFOCOM
- ACM Mobicom, etc.
- .
8Plan your writing
- Ask two questions before starting
- What is new in your work?
- What are you going to write?
- Emphasize on the originality and significance of
your work. - Organize your thinking and decide the structure
(outlines) of your paper. - Stick on your central points throughout the whole
paper and remove all unnecessary discussions.
9Reader-oriented Writing
- Purpose of your writing disseminating your
research results. - Dont write if there is nothing to write
- Dont make a simple problem complicated to fool
people - Dont hide technical details
- Reader-oriented writing Write in a way that
would lead readers to follow your thinking, NOT
in the way of your thinking. - Well-organize your thinking
- Give enough and clear explanation (never leave
reader to guess) - Try to present your idea in an accurate way (no
ambiguous) - Always think how readers would interpret your
writing (assume youre a reader) - Use simple/ plain English
- Purpose of technical writing express your idea
correctly clearly.
10Structure of a Paper
- Title
- Abstract
- Key words
- Introduction
- Background
- Related Work
- System Model Problem Statement
- Methods / Solutions
- Simulations / Experiments
- Conclusion
- Acknowledgement
- References
- Average number of pages of a journal paper
- Average number of pages of a conference paper
11Choose a Right Title
- The title should be very specific, not too broad.
- The title should be substantially different from
others. - Topology control for multihop wireless
networks, IEEE Trans. on Comm, 93. - Topology control of multihop wireless networks
using transmit power adjustment, infocom00. - Distributed topology control for power efficient
operation in multihop wireless networks,
infocom01. - Avoid general / big titles, e.g.,
- Research on data mining,
- Some research on job assignment in cluster
computing, - A new framework for distributed computing,
12Write a concise Abstract
- The use of an abstract
- for search purpose.
- giving readers a paper-summary before getting
into details. - An abstract should tell
- the problem that the paper discusses.
- the work that has been done, or method being
used. - original findings / achievements.
- An abstract usually does NOT have
- reference numbers
- multiple paragraphs
13Choose a right set of keywords
- The use of keywords
- database search,
- categorizing your work (for editors to choose
reviewers). - The keywords must be specific and, as a whole,
represent the main topic of the paper. - Avoid using the words that are not the main
topic, such as calculus, simulations, etc.
14Examples of an abstract / keywords
15Organization of your Paper
- Top-down writing method
- Planning sections and subsections
- Sketching use a sentence to represent the points
(paragraphs) in each subsections - Writing details expand a sentence in the sketch
into a paragraph - Adjustment break / merge paragraphs, add / merge
sections - N.B. keep a logical flow from section to section,
paragraph to paragraph, and sentence to sentence.
16Introduction the most difficult part
- Purpose of introduction
- Introducing readers to your problem / work.
- An introduction usually contains
- Brief background of the topic-area
- Existing work, which would lead to the importance
/ originality of your work - Description of your problem
- Achievement / significance / brief-methodology of
work
17Related work and Reference list
- Proper selection of references
- Show your knowledge in the related area,
- Give credit to other researchers (reviewers are
usually chosen from the references), - Cite good quality work (particularly when citing
your own work) and up to date work. - Related work should
- Be organized to serve your topic,
- Emphasize on the significance / originality of
your work (Introducing your work out). - Format of references
- Consistent with the format, ordering, etc.
- Standard format of books / journal papers /
conference papers, e.g, - X. Jia, X.D. Hu and D.Z. Du, Multiwavelength
Optical Networks, Kluwer Academic, 2002. - J. Li, Yi Pan, and X. Jia, Analysis of Dynamic
Location Management for PCS Networks, IEEE Trans
on Vehicular Technology, Vol. 51, No. 5, Sep
2002, pp.1109-1119. - X. Jia, D. Li, X.Hu and D. Du, "Placement of
Read-Write Web Proxies in the Internet", Proc of
IEEE Intl. Conf. on Distributed Computing
Systems, Phoenix, USA, Apr 2001, pp.687-690. - Do NOT use non-standard abbrev.
18Examples of reference lists
19A Typical Review Form of a conference
- ACM International Conference on Image and Video
Retrieval (ACM CIVR 07) - Typical Review scenario
- Reviewer 1
- Rating
- Familiarity Please indicate your familiarity
with the paper's subject matter - This is my research area (4)
- Rating How would you rate the paper overall?
- Accept, but there are problems (4)
- Novelty How would you rate the novelty of
the paper? - New contribution (4)
- Impact Will this paper be important over
time? - Can't quite tell (3)
20A Typical Review Form of a conference
- ACM International Conference on Image and Video
Retrieval (ACM CIVR 07) - Typical Review scenario
- Reviewer 1
- Rating
- Summary Please summarize the paper briefly
This paper describes a method for recognizing the
different dynamic textures present in an image
sequence by directly comparing (without
segmentation) the statistics (i.e., motion
co-occurrence matrix) of the mixture with the
statistics of the individual dynamic textures
from a given known set of individual dynamic
textures. A mathematical (geometric)
justification of the proposed (linear) criterion
is provided. Experiments have been carried out on
synthetic mixture examples generated from samples
of natural dynamic textures. - Positives What are the most important
reasons to accept this paper, in order of
importance? Say whether the positives dominate
the negatives (1-3 sentences) This is an
interesting and difficult problem which has not
been much investigated so far. The proposed
solution is original and efficient. Satisfactory
results are reported. The positives largely
dominate the negatives. - Negatives What are the most important
reasons NOT to accept this paper, in order of
importance? (e.g., the paper has serious
technical mistakes, isn't novel, doesn't
demonstrate its point by proofs, simulations or
experiments, makes very unreasonable assumptions,
etc.) If the overall conclusions are still likely
to hold despite these flaws, please say so. Say
whether the negatives dominate the positives.
(1-3 sentences) Results on examples involving
more than two different dynamic textures and on
real videos including multiple dynamic textures
would have been appreciated.
21A Typical Review Form of a conference
- ACM International Conference on Image and Video
Retrieval (ACM CIVR 07) - Typical Review scenario
- Reviewer 1
- Rating
- Detailed Comments Please provide detailed
feedback to the author(s) Page 1 MCM should be
quoted as second-order texture measures. Page 2
A formal definition of Vi should be given. The
demonstration of Theorem 1 is not that clear to
me (last part, formulae at the bottom of Pg.2 and
top of Pg.3). The explanation should be improved.
In case of several dynamic textures (more than
two), how the number of textures could be
determined? Is a block matching technique the
best way to get reliable and accurate
displacement fields on dynamic textures (for
instance, is the brightness constancy constraint
valid? Can the motion be always considered as
nearly translational within a block?). This issue
should be further discussed. Samples of computed
displacement fields should be plotted.
Experiments on real videos depicting multiple
dynamic textures could be conducted as well. It
is not that easy to precisely evaluate how
similar the MCMs of Fig. 5 and 6 are. Differences
of the MCMs (for each pair) should be plotted, or
objective measures of the MCM differences should
be provided. How is the ratio alpha of individual
textures handled in the experiments? Is it
estimated? Then, how is the mixture class with
the true ratio selected? Or, are several
predefined (or known) alpha values tested? Then,
how the method would be applied to real cases
without a priori information on the ratio alpha ?
The reference to the work by Crivelli et al.,
ICIP2006, on multiple dynamic textures could be
added.
22A Typical Review Form of a conference
- ACM International Conference on Image and Video
Retrieval (ACM CIVR 07) - Typical Review scenario
- Reviewer 2
- Rating
- Familiarity Please indicate your familiarity
with the paper's subject matter - Passing familiarity (2)
- Rating How would you rate the paper overall?
- I can't make up my mind (3)
- Novelty How would you rate the novelty of
the paper? - Incremental improvement (3)
- Impact Will this paper be important over
time? - Probably not (2)
23A Typical Review Form of a conference
- ACM International Conference on Image and Video
Retrieval (ACM CIVR 07) - Typical Review scenario
- Reviewer 2
- Rating
- Summary Please summarize the paper briefly
This paper presents a method of characterizing
multiple temporal textures using present. Motion
Co-occurrence Matrix (MCM). Some good experiments
have been showed for the synthetic data. - Positives What are the most important
reasons to accept this paper, in order of
importance? Say whether the positives dominate
the negatives (1-3 sentences) MCM is well known
method for characterizing temporal textures.
Authors extend it for representing multiple
temporal textures. Authors have analytically and
experimentally verified the proposed method - Negatives What are the most important
reasons NOT to accept this paper, in order of
importance? (e.g., the paper has serious
technical mistakes, isn't novel, doesn't
demonstrate its point by proofs, simulations or
experiments, makes very unreasonable assumptions,
etc.) If the overall conclusions are still likely
to hold despite these flaws, please say so. Say
whether the negatives dominate the positives.
(1-3 sentences) The proposed method has only
applied to toy problems (synthetic data). Not
sure if it will work for real world problems.
24A Typical Review Form of a Journal
- IEEE Transaction on Circuits and Systems for
Video Technology - Typical Review scenario
- Reviewer 1
- Rating
- Technical Content Tutorial 7
- Advance of Theory 7
- Advance of Application 6
- Presentation Clarity 5
- Organization 5
- Conciseness 6
- English 7
- Quality of References Completeness 8
- Missing Key References
25A Typical Review Form of a Journal
- IEEE Transaction on Circuits and Systems for
Video Technology - Typical Review scenario
- Reviewer 1
- Detailed comments
- This paper describes an interesting approach to
using block-based motion measure for temporal
texture classification in video. The novelty of
this work the author claimed is to achieve
real-time performance and comparative
classification results by using block-based
motion description, compared with the
state-of-art pixel-based motion approaches. The
methodology described in this paper seems
theoretically justified, and the analysis of
experimental results is also sufficient enough.
However, the structure of this paper seems a
little unbalanced, since the author put more
words on related works and experimental analysis,
instead of approach itself (in section 3). I
suggest that the author should make the
literature review more concise and compact, thus
section 2 may be more readable. The best way of
revising section 2 is to classify the literatures
into different classes. The other comments may
include 1. It is better to numerically (e.g.
using table) prove real-time" in addition to
the comparison in section 4.3. You have mentioned
in abstract that this approach is real-time",
but did not have evidence to support this point.
2. Could you explain in the abstract what the
ratio of importance" means? And why this is
very important in this scenario? 3. The author
should simply the symbols used in section 3.1.
For example, (eta_(x), eta_(y), eta_(t)) has
appeared quite a few times in this section. It is
better to make this paper more readable using
simplified symbols. 4. In section 4.1, put a few
words to describe the dataset you used in your
experiments, i.e. the dataset in Ref. 26, e.g.
the size, the video format, duration, and so on.
5. Figure 69, please add End For" at the end
of each For" loop.
26A Typical Review Form of a Journal
- IEEE Transaction on Circuits and Systems for
Video Technology - Typical Review scenario
- Reviewer 2
- Rating
- Technical Content Tutorial 7
- Advance of Theory 5
- Advance of Application 5
- Presentation Clarity 5
- Organization 5 Conciseness 4
- English 5
- Quality of References Completeness 5
- Missing Key References
27A Typical Review Form of a Journal
- IEEE Transaction on Circuits and Systems for
Video Technology - Typical Review scenario
- Reviewer 1
- Detailed comments
- This To my understanding, this paper proposes to
characterize motion texture in terms of
block-based motion co-occurrence matrix. This
proposed approach is strongly motivated by paper
4. The strength of this paper can be summarized
in two aspects 1)Block based motion extraction
which contributes to computational efficiency.
The authors also argue that block motion can be
easily obtained due to the currently available
compression techniques such as MPEG-4 and H.26X,
which is sound. 2)Explicitly integrating spatial
and temporal information of motion texture. In
addition, the proposed method has been evaluated
with sufficient experiments and analysis.
However, the novelty of this paper is limited in
terms of quality of a regular journal paper. I am
also concerned about the following issues
1)Sections Introduction and Related work can be
more succinct. For example, do not try to attack
almost every aspect of pixel-based motion
estimation (e.g. optical flow). As to Section
Related Work, 2)Can you elaborate the claim C
the sentence after words Section 4.4 in Page
8? How does the effectiveness fade significantly?
3)Paragraphs 2 and 3 in Page 9 are redundant,
since both temporal texture analysis and texture
synthesis are not very relevant in the context of
this paper. It is fair enough to mention where it
has been surveyed for the sake of completeness.
4)Section 3.2 on separating spatial domain and
temporal domain is obscure. How does genetic
algorithm work for feature selection? Why do
those three matrice form a minimal set? 5)Authors
argue that the time-space ratio is explicitly
controlled. However, it seems that how to select
the ratio is really empirically as stated in
Section 4.4 of Page 23, which is an obstacle for
real-time applications. 6)In Figure 5 of Page 17,
why does the performance drop while k increases?
7)In Section 4.3, computational complexity is
evaluated approximately. Is the evaluation based
on the assumption that every approach uses full
search for motion estimation? Even the proposed
approach seems to be much faster than existing
ones, I wonder how fast the proposed approach is
in terms of CPU time. Is it practical to achieve
real-time performance? 8)The pseudo-codes of
STCN, SFTR, and SSTF would better appear in
Appendix. 9)As to the Table 2 of Page 24, the
authors conclude that the proposed approach is
comparable with existing ones in terms of
classification accuracy. However, it also can be
observed that the performance of the proposed
method using block motion (i.e.97.62) does not
outperform that of SFTR using Normal flow (i.e.
99.21). Is the pay-off for computational
complexity? It is also observed that block-based
motion estimation only favors the proposed
approach. Does it mean the dataset favors the
proposed approach given empirically tuned
parameters? Why should authors revert the trend
as claimed in the second sentence of the last
paragraph, Page 24? In addition, STCN is supposed
to improve the method of SFTR. However, it is
observed that it is not true at all for the given
dataset. 10)The figures (e.g. 3.37) discussed in
the last paragraph of Page 25 do not match the
figures in Table 2 (Page 24). 11)A comparison
also needs to be conducted on Dyntex database as
shown in Table 2. 12)References are very verbose
and redundant. In addition, the authors need to
pay attention to the format and spelling. For
example, there is a typo in 4 casual should be
causal.
28A Typical Review Form of a Journal
- IEEE Transaction on Circuits and Systems for
Video Technology - Typical Review scenario
- Reviewer 3
- Rating
- Technical Content Tutorial 7
- Advance of Theory 6
- Advance of Application 8
- Presentation Clarity 8
- Organization 7
- Conciseness 8
- English 8
- Quality of References Completeness 8
- Missing Key References
29A Typical Review Form of a Journal
- IEEE Transaction on Circuits and Systems for
Video Technology - Typical Review scenario
- Reviewer 1
- Detailed comments
- The authors present an approach to temporal
texture characterization. In this paper, the
block-based motion measure is used to reduce the
computational complexity while preserving the
classification accuracy. Basically, the paper is
well structured and well written, but some of the
key issues still need to be addressed, such as
1) The proposed method used the block-based
motion vectors. One of its advantage is
block-based motion vectors readily available for
MPEG and H.26x video. It is noted that
block-based motion vectors are simply estimated
for video coding and compression. So, the
block-based motion vectors are not reliable for
motion analysis. "the approximation of true
motion by the block baed motion vectors .. is
even stronger" at p4, l12 is not convincing. And
"therefore, highly likely that the true
displacement vector will also ..., the criteria
used by all video coding motion vector estimation
technique" at p4, l13 from the bottom also has
the same problem. Video coding just find the
"best-match" block for compression, it considers
little about the true displacement vector. That
makes the underlying assumption of using
block-based motion vector to character temporal
textures not obviously reasonable. 2) The
experiments are implemented on MPEG video data
and can get real time performance. If the testing
data is not MPEG video, and need to estimate the
block-based motion vectors beforehand. What will
be the processing time, it would be better if the
author could give a detailed discussion. The
authors need to give more explaination for some
technique details, such as 1) p3, l10, "One
obvious alternative for real time motion
estimation is to estimate the normal flow", this
is not "obvious" for other people. Please either
provide a reference or justify it. 2) p3, l11
from the bottom, "Any significant reduction in
the feature extraction... of normal flow vectors,
however, cannot be effective". Why they cannnot
be effective, please give the reason in a more
clearer way, not just give a statement. 3) p10,
Figure 2, what difference between (a) image frame
sequenceand (b) normal flow sequence. It would be
better if the author gives a clearer figure. 4)
p11, eq.(1). "any arbitrary image processing
element is assumed independent conditionally", it
is not obviously reasonable. Please justify such
an assumption. 5) p12, eq.(5), what do q' and q''
mean respectively? Any two adjacent frames? 6)
p13, Table 1, what is the correspondence between
temporal cliques and spatial cliques? 7) p13, l8
from the bottom. "Clearly, (0,0,-1),(1,0,0),(0,1,
0) is a minimal set fulfilling the above
requirements". Please justify it as it is not
obviously clear. 8) p14, eq.(8), what do p and q
means? It is better if the terms used in this
equation are consistent with previous ones. 9)
p14, l1 from the bottom, "that are then fused
into a single distance measure in the second
stage using weighted Euclidian distance". The
discussion on weighted Euclidian distance can not
be found throughout the paper, please add
relevant content in the revised manuscript. 10)
p15, eq.(11), v and v' means what? eq.(12) v1 and
v2 means what? If they have the same meaning, it
is better to use consistent terms. 11) p17, "All
the experiments were conducted on MATLAB 6.5.1".
How to evaluate the performance of processing
time pratically. It would be better to analyze
the computational complexity both qualitative and
quantitatively.
30A Typical Review Form of a Journal
- IEEE Transaction on Circuits and Systems for
Video Technology - Typical Review scenario
- Associate Editor Resubmit after Major Revision
for Review - Detailed comments
-
- The paper -- A temporal texture characterization
technique using block-based approximated motion
measure has been reviewed. The paper presents a
technical approach for temporal texture
classification in video using block-based motion
measure. Two major aspects from the paper include
the block based motion feature extraction with
certain computation efficiency and the
exploration of the integrating spatial and
temporal domain information explicitly. Through
the review process, some key comments from three
reviewers can be summarized as follows 1. The
level of contribution to the temporal texture
based video classification is limited which
challenges the novelty in this paper. 2. The
block based motion estimation and compensation in
video codec such as h.264 explore the statical
redundancy rather the true motion estimation.
Therefore, there is an issue to use block-based
motion vector from coded video bitstream for
motion analysis. 3. The sections of Introduction
and Related work are verbose and far from the
point of concise and compact for readers. 4.
References are very verbose and redundant. A
compact reference list will give reader a focused
area with some benefits. 5. There are some
redundant paragraphs which are not necessary to
be repeated in the paper 6. The pseudo-codes of
STCN, SFTR, and SSTF would better appear in
Appendix. 7. Section 3.2 on separating spatial
domain and temporal domain is obscure. How does
genetic algorithm work for feature selection? Why
do those three matrices form a minimal set? 8.
The methodology described in this paper seems
theoretically justified, and the analysis of
experimental results is also sufficient enough 9.
It is important to describe the advantage and
disadvantage in terms of your methodology and
performance which can let readers have their own
judgement rather make a misleading to them. Based
on the reviewers comments, I recommend the
authors to resubmit the paper after major
revision by addressing all points raised from the
reviewers. Key references that must be included
31Writing Tips carry you to a long way
- Reader-oriented writing (good organization,
logical flow, etc). - Standard and consistent formatting (professional
and neat looking). - Learning from other peoples writing.