There are several reasons an academic might want to establish an online presence. The first is good old-fashioned self-promotion: this is especially important for early-career academics. No-one else is going to promote your work, so you have to do it yourself. Carefully building an online presence that connects your name with your area of expertise is one way to build your profile and to get your name known.
I have quite a common name ("Michael" and "John" are something like the second or
third most common given names for males in my generation, and "Watts" is
the second or third most common surname for people of English ancestry)
but if you Google for "Michael Watts computational intelligence" 45 of the first 50 hits are either my pages or pages that specifically mention me, such as committees I serve on. So, as far as Google is concerned, my name is linked pretty strongly with computational intelligence (certainly more strongly than it is with ecological modelling - 29/50 - which is what I get paid to do).
Secondly, communicating your work to other scientists and to the public is at the heart of what scientists do: idealistically, our work is done to benefit humanity, but it cannot do that if no-one knows about what you do. Of course, the primary means of communicating with other scientists is via papers and conferences, but papers are not very accessible to the general public: they are written for other scientists, that is, they can be quite abstract and hard to read, and papers can be hard to find, that is, locked behind pay-walls. An online presence, however, can be made much more accessible. It does not need to be written in the strict "scientific style", it can include links to supporting material to assist reader comprehension, and it is freely available.
Having a website is a good start, and is a good place to put things like software and teaching materials that you want to make available for others to use. If you have something to say though (and every scientist should have something to say) then a blog is an excellent way of saying it. I started this blog because I was inspired to do so by two of the people I work with, both of whom run popular blogs, on climate change and conservation biology respectively. After studying their blogs and realising that there was nothing equivalent for computational intelligence, I started this blog. It takes me an hour or two per week to produce new content for the blog, which I personally think is time well spent.
There are many social media and networking sites out there, and it is worth your time to establish profiles in as many of them as you can. The obvious ones are Facebook*, LinkedIn, Twitter and Google+ but there are also a number of networking sites specifically for academics. The big ones appear to be Academia.edu and ResearchGate, but others are network.nature.com, Epernicus, KES International, Research pages, the Research Cooperative, scholarz.net, biomedexperts.com, scispace.com, mynetresearch.com, labroots.com, researchiscool.com, iamresearcher.com, researchr.org and hypertope.com. There are also publication trackers like Google Scholar Citations and Researcher ID. Most networking and social media sites allow you to specify a research interest and a home page, so I always list computational intelligence and point them all to my own web site. This has the effect of creating a lot of points on the web that, firstly, associate my name with computational intelligence, and secondly, associate my name with my website. This has the effect of boosting my name in the search engine results. It can be a lot of work to set these profiles up, especially if you have a lot of publications, but maintenance after that is limited to updating sites when you publish new papers.
Having a website isn't that expensive (I pay about AU$110 per year for the website and domain name). Blogs are free (unless you want to associate it with a domain name, which is still pretty cheap), as are the social media and networking sites I use. The best thing is, many of these can be linked together so that an update on one site is propagated to others (see the report I wrote here about linking this blog to other sites).
There are several articles about scientists and social media that are well worth a read: here, here, here, here, and here. These cover things like using Twitter to communicate more effectively. So, why not invest some time and a bit of money, and start establishing your own online presence?
*You may notice that I haven't linked to my Facebook profile: this is because I mostly use Facebook to keep in touch with old friends and family members, who aren't particularly interested in Computational Intelligence.
Edited 17 April to add link to researchr.org
Edited 11 April to add link to iamresearcher.com
Tuesday, April 10, 2012
Monday, April 9, 2012
Conference paper deadline: ICIIC 2012
The paper submission deadline for the International Conference on Information and Intelligent Computing 2012 is 20 July 2012. This conference will be held in Chengdu, China, 8-9 December, 2012.
Sunday, April 8, 2012
Website on Evolving Connectionist Systems updated
I've updated my website on Evolving Connectionist Systems at ecos.watts.net.nz. The major change is that the equations are all rendered using MathML, which makes them much neater and easier to read.
Friday, April 6, 2012
Call for papers: IEEE ICACI 2012
The deadline for submitting papers to the IEEE International Conference on Advanced Computational Intelligence 2012 is 15 May 2012. This conference will be held in Nanjing, China, 18-20 October, 2012.
Thursday, April 5, 2012
Conference paper deadline: MLSP 2012
The deadline for submitting papers to the IEEE International Workshop on Machine Learning for Signal Processing (MLSP) 2012 is 7 May 2012. This workshop will be held in Santanda, Spain, 23-26 September 2012.
Wednesday, April 4, 2012
Deadline extended: Special Issue: Applications of ECoS
The deadline for submitting papers to the special issue of Evolving Systems on Applications of Evolving Connectionist Systems has been extended to 14 May 2012.
Reminder: paper submission deadline for UKCI 2012
A reminder that the paper submission deadline for the 12th UK Annual Workshop on Computational Intelligence (UKCI) 2012 is May 1, 2012. This workshop will be held in Edinburgh, Scotland, UK, 5-7 September, 2012.
Tuesday, April 3, 2012
Open source textbooks
The principle of Open Source Software (OSS) has been established for a long time. The Linux OS (or GNU/Linux, for the purists out there) made the idea of freely giving away software and source code respectable. Concerns about the quality of the software, and whether or not companies could make money from open source, have all been washed away over the years. OSS tends to be more stable, has bugs fixed faster, and evolves faster than commercial software. Also, companies have been making money from OSS for years: Red Hat being just one example.
In this pod cast transcript Steven Cherry from IEEE Spectrum talks with Richard Baraniuk of Rice University about Open Source Textbooks (OST). Baraniuk has founded the Connexions platform, a platform for developing open source textbooks.
I can think of several objections to the idea of OST, but I believe that, in common with OSS, these objections are not insurmountable problems:
Firstly, there is the issue of quality control. When an author submits a book proposal to a publisher, the publisher will send the outline and a sample chapter to reviewers. But, the reviewers tend to be people the author knows, as unlike anonymous peer review of journal articles, a textbook author can often nominate the reviewers of their proposal.
Secondly, there is the issue of formatting the book. If you use an authoring system like LaTeX, formatting a book isn't really that hard (certainly easier than formatting a book in Word). Publishers tend to only provide an author with a template, anyway.
Thirdly, advertising the book. This seems to vary fairly widely between different publishers, with some putting a lot of effort into it, and others doing much less. With the reach that the Internet provides people now, I don't see advertising as a large issue. If you have a blog, website, or networking profile (and I think that a serious academic should have all of these), you can advertise your book there. If you can afford it, you can buy some ads through Google or one of the other advertising services. It takes a bit of work, but not as much as writing the book in the first place.
Fourthly, producing the book. If you are going entirely for a soft-copy, open-source approach, that's not a problem: just whack the book up on a website, and let people download it. If you want to sell hard copies, then you can go with a publishing-on-demand (POD) service like lulu.com. Using POD has the advantage that you don't need to pay for inventory before you can start selling copies. That is, while most traditional publishers like to produce the hard copies themselves, they also like to print several thousand copies, and then sell them. With POD, copies are printed as they are sold. No inventory, so no big pile of books (money!) sitting in a warehouse where they might get sold later on. If the publisher doesn't decide to kill the book, or sell the lot off at a loss, or just pulp them.
Finally, money! Traditional publishers take a big chunk of the sale price of a book for themselves: around 90%, or more. Combined with the relatively small number of copies that most textbooks sell, an author isn't going to make a lot of money from the exercise (there are exceptions, but it's a pretty long tail: most textbook authors will make very little money, and just a few will make a lot). If you publish open-source, then there are other ways of making money from the book - advertising on the website you host it on, soliciting donations, and selling hard copies via POD services, which tend to give larger shares to the authors. For an early-career author like myself, the biggest problem I face isn't missing out on a royalty cheque, it's obscurity.
I've come to realise that, in common with the problems with academic journal publishers, textbook publishers really don't add that much value. Sure, there is the cachet associated with publishing with certain publishers, just as there is with publishing with certain journals, but is that enough of a reason to put up with their disadvantages?
An OST system like Connexions also solve most of the objections I listed above: material that is submitted to Connexions is subject to peer review, it is becoming well-established as a place to go to for OST, and they sell hard copies. I really do think that, just as open access journals are the future for publishing papers, open source textbooks are the future of textbooks, and that within a generation (certainly within my working lifetime) we will see traditional text book publishers diminish in importance.
Is Connexions to OST as Source Forge is to OSS? Would you spend money to buy a hard-copy of an OST textbook? Would you contribute money in other ways to support the work of an OST author? Would you assign an OST as a class textbook?
In this pod cast transcript Steven Cherry from IEEE Spectrum talks with Richard Baraniuk of Rice University about Open Source Textbooks (OST). Baraniuk has founded the Connexions platform, a platform for developing open source textbooks.
I can think of several objections to the idea of OST, but I believe that, in common with OSS, these objections are not insurmountable problems:
Firstly, there is the issue of quality control. When an author submits a book proposal to a publisher, the publisher will send the outline and a sample chapter to reviewers. But, the reviewers tend to be people the author knows, as unlike anonymous peer review of journal articles, a textbook author can often nominate the reviewers of their proposal.
Secondly, there is the issue of formatting the book. If you use an authoring system like LaTeX, formatting a book isn't really that hard (certainly easier than formatting a book in Word). Publishers tend to only provide an author with a template, anyway.
Thirdly, advertising the book. This seems to vary fairly widely between different publishers, with some putting a lot of effort into it, and others doing much less. With the reach that the Internet provides people now, I don't see advertising as a large issue. If you have a blog, website, or networking profile (and I think that a serious academic should have all of these), you can advertise your book there. If you can afford it, you can buy some ads through Google or one of the other advertising services. It takes a bit of work, but not as much as writing the book in the first place.
Fourthly, producing the book. If you are going entirely for a soft-copy, open-source approach, that's not a problem: just whack the book up on a website, and let people download it. If you want to sell hard copies, then you can go with a publishing-on-demand (POD) service like lulu.com. Using POD has the advantage that you don't need to pay for inventory before you can start selling copies. That is, while most traditional publishers like to produce the hard copies themselves, they also like to print several thousand copies, and then sell them. With POD, copies are printed as they are sold. No inventory, so no big pile of books (money!) sitting in a warehouse where they might get sold later on. If the publisher doesn't decide to kill the book, or sell the lot off at a loss, or just pulp them.
Finally, money! Traditional publishers take a big chunk of the sale price of a book for themselves: around 90%, or more. Combined with the relatively small number of copies that most textbooks sell, an author isn't going to make a lot of money from the exercise (there are exceptions, but it's a pretty long tail: most textbook authors will make very little money, and just a few will make a lot). If you publish open-source, then there are other ways of making money from the book - advertising on the website you host it on, soliciting donations, and selling hard copies via POD services, which tend to give larger shares to the authors. For an early-career author like myself, the biggest problem I face isn't missing out on a royalty cheque, it's obscurity.
I've come to realise that, in common with the problems with academic journal publishers, textbook publishers really don't add that much value. Sure, there is the cachet associated with publishing with certain publishers, just as there is with publishing with certain journals, but is that enough of a reason to put up with their disadvantages?
An OST system like Connexions also solve most of the objections I listed above: material that is submitted to Connexions is subject to peer review, it is becoming well-established as a place to go to for OST, and they sell hard copies. I really do think that, just as open access journals are the future for publishing papers, open source textbooks are the future of textbooks, and that within a generation (certainly within my working lifetime) we will see traditional text book publishers diminish in importance.
Is Connexions to OST as Source Forge is to OSS? Would you spend money to buy a hard-copy of an OST textbook? Would you contribute money in other ways to support the work of an OST author? Would you assign an OST as a class textbook?
Monday, April 2, 2012
Reminder: paper submission deadline SEAL 2012
A reminder that the deadline for submitting papers to the 9th International Conference on Evolution and Learning (SEAL) 2012 is 1 May 2012. This conference will be held in Hanoi, Vietnam, 16-19 December, 2012.
Thursday, March 29, 2012
Reminder: paper submission deadline for AI'12
A reminder that the deadline for submitting papers to the 25th Australasian Joint Conference on Artificial Intelligence (AI) 2012 is 29 June, 2012. This conference will be held in Sydney, Australia, 4-7 December, 2012.
Squirrel detection with SVM
Below is an entertaining video explaining how to automatically squirt squirrels with a water gun. What's interesting about this is that the presenter used a Support Vector Machine (SVM) to classify the images from the camera as either a squirrel or not a squirrel. I haven't talked about SVM on this blog much, but they are very powerful, learning algorithms that often outperform neural networks in classification applications.
He starts talking about the details of squirrel detection about the 7:30 mark - before that he describes the image processing toolkit he used to segment the images from the camera into blobs, where each blob needed to be classified as either a squirrel or not a squirrel. I was particularly interested in how he used three different kinds of features as inputs to the SVM: size of the blob segmented from the image; the colour histogram of the blob; and the entropy of the blob, where entropy is used as a measure of the "fuzziness" of the blob - squirrels have fuzzy, furry tails, while birds do not. This shows that careful thought is always required when selecting the inputs to a classifier or a learning algorithm. You can't just throw everything in and hope to get something useful out!
He starts talking about the details of squirrel detection about the 7:30 mark - before that he describes the image processing toolkit he used to segment the images from the camera into blobs, where each blob needed to be classified as either a squirrel or not a squirrel. I was particularly interested in how he used three different kinds of features as inputs to the SVM: size of the blob segmented from the image; the colour histogram of the blob; and the entropy of the blob, where entropy is used as a measure of the "fuzziness" of the blob - squirrels have fuzzy, furry tails, while birds do not. This shows that careful thought is always required when selecting the inputs to a classifier or a learning algorithm. You can't just throw everything in and hope to get something useful out!
Wednesday, March 28, 2012
Scientific Writing
Adam Ruben has a written a rather tongue-in-cheek essay on How to Write Like a Scientist. He asks why can't we scientists write the way other people write? Why are scientific papers written the way they are?
Scientific papers are written the way the are because of their purpose. The whole point of a paper is to describe what the authors did and what they found, and to communicate this as widely as possible, to readers who may not have English as a first language, or who may be approaching the paper from a different field. If papers are going to do this effectively, they have to be unambiguous. The problem with being unambiguous in English is that there are so many words that have the same, or nearly the same, meaning - only, lone, sole, and so on.
Papers use the past tense because you are describing what you have done, not what you are doing or what you will do. Papers have used the passive voice for a long time, but I've noticed a change to active voice recently, and I'm trying to move to active voice in my own writing (my current supervisor once admonished me with "No-one in my lab uses the passive voice!"). The same thing applies to using "we" or "the author" instead of "I" - it's been the fashion to not use "I", but that's changing. If the work was done by more than one person, then it's entirely appropriate to use "we".
I especially liked his comments about the use of "obviously" and I'll admit I've used it a few times myself. Not to demonstrate my intellectual superiority, but to forestall comments from reviewers: the times when I've not inserted a phrase like "obviously, ovens can be hot"*, at least one reviewer has pointed it out.
The use of idioms should be avoided. Idioms can be highly specific to a certain culture. For example, Australians and New Zealanders both speak English. Also, the New Zealand accent is close enough to the Australian accent that most of the time, when I speak, I can pass for a local. The one thing that gives me away as a New Zealander in Australia is the idioms I use: I use New Zealand idioms that just aren't used in Australia. Now, imagine I used those idioms in a paper read by people all over the world: how many people would understand it?**
I've touched on this issues in a previous post, as well as common grammatical errors to avoid and ten rules for good writing. I think papers can be made more accessible without losing clarity, but it's going to take time, and a lot more work from authors.
*This refers to a sign on the oven in the tea room shared by the IT staff at Lincoln University: "Warning: Oven may be hot". Other signs in the area read "Warning: fridge may be cold" and "Warning: floor".
**That said, I have recently used the term "munted" in a paper - look it up if you want to know what it means!
Scientific papers are written the way the are because of their purpose. The whole point of a paper is to describe what the authors did and what they found, and to communicate this as widely as possible, to readers who may not have English as a first language, or who may be approaching the paper from a different field. If papers are going to do this effectively, they have to be unambiguous. The problem with being unambiguous in English is that there are so many words that have the same, or nearly the same, meaning - only, lone, sole, and so on.
Papers use the past tense because you are describing what you have done, not what you are doing or what you will do. Papers have used the passive voice for a long time, but I've noticed a change to active voice recently, and I'm trying to move to active voice in my own writing (my current supervisor once admonished me with "No-one in my lab uses the passive voice!"). The same thing applies to using "we" or "the author" instead of "I" - it's been the fashion to not use "I", but that's changing. If the work was done by more than one person, then it's entirely appropriate to use "we".
I especially liked his comments about the use of "obviously" and I'll admit I've used it a few times myself. Not to demonstrate my intellectual superiority, but to forestall comments from reviewers: the times when I've not inserted a phrase like "obviously, ovens can be hot"*, at least one reviewer has pointed it out.
The use of idioms should be avoided. Idioms can be highly specific to a certain culture. For example, Australians and New Zealanders both speak English. Also, the New Zealand accent is close enough to the Australian accent that most of the time, when I speak, I can pass for a local. The one thing that gives me away as a New Zealander in Australia is the idioms I use: I use New Zealand idioms that just aren't used in Australia. Now, imagine I used those idioms in a paper read by people all over the world: how many people would understand it?**
I've touched on this issues in a previous post, as well as common grammatical errors to avoid and ten rules for good writing. I think papers can be made more accessible without losing clarity, but it's going to take time, and a lot more work from authors.
*This refers to a sign on the oven in the tea room shared by the IT staff at Lincoln University: "Warning: Oven may be hot". Other signs in the area read "Warning: fridge may be cold" and "Warning: floor".
**That said, I have recently used the term "munted" in a paper - look it up if you want to know what it means!
Thursday, March 22, 2012
Reminder: paper submission deadline for AIAA 2012
A reminder that the deadline for submitting papers to the 7th International Symposium Advances in Artificial Intelligence and Applications (AIAA) 2012 is 22 April 2012. This conference will be held in Wroclaw, Poland, 9-12 September, 2012.
Wednesday, March 21, 2012
Reminder: paper submission deadline for iCAST 2012
A reminder that the deadline for submitting papers to the 4th International Conference on Awareness Science and Technology (iCAST) 2012 is 15 April 2012. The conference will be held in Seoul, Korea, 21-24 August, 2012.
Tuesday, March 20, 2012
Call for papers: Applications of ECoS
Special issue of Evolving Systems on
Applications of Evolving Connectionist Systems
Guest Editor
Scope
The topic of this special issue is “Applications of Kasabov’s Evolving Connectionist Systems”.
In modern society, the volume and rate of data production are huge and set to increase. To process and utilise this avalanche of data, methods are needed that can rapidly and accurately model it as it becomes available. These models must be able to learn throughout their lifetimes, without forgetting what they have previously learned, and be able to explain themselves.
Kasabov’s Evolving Connectionist Systems (ECoS) are able to fulfil each of these requirements. They are a class of constructive neural networks that learn via structural growth and adaptation. They have a fast, one-pass learning algorithm, where all that can be learnt from the data is learned in the first training pass. Because of their open structure, they exhibit continuous, life-long learning whereby the structure expands as necessary to accommodate new data. Finally, they have a strong resistance to catastrophic forgetting following additional training on new data.
Examples of ECoS networks include the Evolving Fuzzy Neural Network (EFuNN), which was the first ECoS network published and is characterised by embedded fuzzy logic elements. There is also the Simple Evolving Connectionist System (SECoS), which is essentially an EFuNN with the fuzzy elements removed, and the Dynamic Evolving Fuzzy Inference System (DENFIS) for discovering Takagi-Sugeno style fuzzy rules. Many ECoS networks use fuzzy rule extraction algorithms that allow for the explanation of what the networks have learned, in a comprehensible manner.
ECoS networks are well suited to applications that are dealing with new data continuously and that have dynamic, time-critical aspects. Previous applications of ECoS include:
- Stock market prediction and macroeconomic modelling
- Speech recognition, especially multi-speaker speech recognition
- Bioinformatics and medical modelling
- Image and video parsing
- Robot control
- Information system security
The special issue is concerned with all aspects of the application of ECoS networks to real-life problems and data sets. Topics of interest include, but are not limited to:
- Applications of ECoS to real-world problems
- Data mining of complex data sets using ECoS
- Comparisons of ECoS with other algorithms over real-world data sets
- Modifications of ECoS algorithms to fit them to real-world problems
Proposed Schedule
- Submission due date: 16 April, 2012
- Preliminary notification of acceptance: 4 June, 2012
- Revised manuscripts due: 9 July, 2012
- Final acceptance notification: 6 August, 2012
- Final version due: 3 September, 2012
- Intended publication date: January, 2013
Submission
The special issue invites original contributions within the specified scope. Manuscripts must not be under review elsewhere, nor can they have been previously published. Extended conference papers must contain at least 30% new material. Please format all manuscripts according to the Instructions for Authors:
Please submit all papers via the online submission system:
Monday, March 19, 2012
Reminder: conference paper deadline for IJCCI 2012
A reminder that the deadline for submitting papers to the International Joint Conference on Computational Intelligence (IJCCI) 2012 is 19 April 2012. This conference will be held in Barcelona, Spain, 5-7 October, 2012.
Friday, March 16, 2012
Reminder: paper submission deadline for ISICA 2012
A reminder that the deadline for papers submitted to the International Symposium on Intelligence Computing and Applications (ISICA) 2012 is 15 April 2012. This conference will be held in Wuhan, China, 27-28 October, 2012.
Thursday, March 15, 2012
Reminder: paper deadline for ICCCI 2012
A reminder that the deadline for papers submitted to the 4th International Conference on Computational Collective Intelligence (ICCCI) 2012 is 15 April 2012. This conference will be held in Ho Chi Minh City, Vietnam, 28-30 November, 2012.
Wednesday, March 14, 2012
Reminder: paper submission deadline: IEEE CIG 2012
A reminder that the deadline for submitting papers to the IEEE Conference on Computational Intelligence in Games (IEEE CIG) 2012 is 15 April 2012. This conference will be held in Granada, Spain, 12-15 September, 2012.
Tuesday, March 13, 2012
Reminder: paper submission deadline for CBR-MD 2012
A reminder that the deadline for submitting papers to the International Workshop Case-Based Reasoning (CBR-MD) 2012 is 13 April 2012. This workshop will be held in Berlin, Germany, 20 July 2012.
Friday, March 9, 2012
Publishing or perishing 3
Following this previous post, I've found a few more articles about the dismissal of staff from the University of Sydney, for not publishing at least four papers in three years. This article is scathing of the university management, while Alex Burns, in this post, is in a similar vein to what I wrote: that four papers in three years is not an excessive number and that most academics should be able to meet it.
The most interesting post I found was this one, from David McGloin at the University of Dundee, where he lists a number of reasons someone might not reach the target number of publications. This is useful, as it informs as to what strategies academics could follow to avoid finding themselves in this sort of situation. Below, I reproduce each of his points, along with my responses:
It could be that you’re on the brink of some big breakthrough and the focus of this has taken many years to complete.
It is very dangerous for any academic to focus on one project to the exclusion of all others. Also, any project can be broken up into small, publishable chunks. That is, rather than writing up a single magnum opus of a paper at the end of the project, one should publish several smaller papers during the course of the work. This is more likely to make funding agencies happy as well, as it shows them that you are being consistently productive.
It may be that you’ve had bad luck with papers getting accepted, or have been doing good work, but maybe aiming to high up the journal league table.
Reformatting a rejected paper for another journal doesn't take very long. Waiting for reviews takes a long time (six months or more for some of my papers) but again, no academic should be working on just one project at a time. Everyone gets a period of bad luck with getting papers accepted (I had a long string of rejections throughout 2010 - I made up for it in 2011). The important thing is to have more than one project on the go at any one time, and to have a fast turn-around on rejected papers. If you follow a journal article submission strategy similar to the one I suggest, you should already have a good idea of other journals you could submit to.
It could be that you have had a run of poor luck on grant funding, and have not had the support to do your work and write up results, in terms of PhD students, postdocs, or simply a lack of equipment.
I do tend to agree with this point, especially for fields that need a lot of equipment to get results. I will point out, though, that having a good publication record will help with getting research grants.
Maybe a series of experiments didn’t work, but the next one will (and it will win a Nobel Prize).
Again, it is very important to pursue more than one research project at a time. That way, if one set of experiments doesn't work out, you can still publish the results from another.
Maybe your research output is highly subjective (think works by artists) and the critics didn’t like your last show.
This is more of a problem for researchers in the humanities. As a scientist I can't really comment on this, other than to point again to my responses above.
Maybe your research rivals knew about your employment conditions and decided to reject your last paper (to make it to the magic four) to get you sacked.
This is the most frightening point. Not only is such behavior completely unethical, it undermines the entire peer-review process. Anyone engaging in such behavior - rejecting papers just because the author is a rival - should be sacked immediately. If this does happen, it is also a failure on the part of the journal editors. Most journal submission systems allow the authors to list reviewers they are opposed to. Any editor who sends a paper to a reviewer who they have reasonable suspicion is a rival of the author, is failing to do their job.
Or maybe, just maybe you didn’t feel the need to publish every last little bit of work to avoid saturating the journals and keep the overall quality of published work high enough to make it bearable to read them.
This is a non sequitor. Submitting a lot of papers does not mean a lack of quality in the papers. As I mentioned above, you can break your project up into smaller, publishable chunks and submit a paper on each. Planning your research program is an essential skill for the professional researcher. Also, if the quality of the paper is so low that it's unreadable, how would it get published to begin with?
Maybe you published one Nature paper a year over the last three years and nothing else, and they each got 500 citations
This is one of those situations that could occur, but is really unlikely. The people I know who do publish in Nature, are the people who publish 20+ papers (journal articles) per year! I really can't see how anyone could be good enough to publish three papers in a row in Nature yet not be good enough to get one more paper published in another journal.
Publish or perish is the rule of academia, and has been for a long time. Sensible and positive ways you can publish without perishing are:
The most interesting post I found was this one, from David McGloin at the University of Dundee, where he lists a number of reasons someone might not reach the target number of publications. This is useful, as it informs as to what strategies academics could follow to avoid finding themselves in this sort of situation. Below, I reproduce each of his points, along with my responses:
It could be that you’re on the brink of some big breakthrough and the focus of this has taken many years to complete.
It is very dangerous for any academic to focus on one project to the exclusion of all others. Also, any project can be broken up into small, publishable chunks. That is, rather than writing up a single magnum opus of a paper at the end of the project, one should publish several smaller papers during the course of the work. This is more likely to make funding agencies happy as well, as it shows them that you are being consistently productive.
It may be that you’ve had bad luck with papers getting accepted, or have been doing good work, but maybe aiming to high up the journal league table.
Reformatting a rejected paper for another journal doesn't take very long. Waiting for reviews takes a long time (six months or more for some of my papers) but again, no academic should be working on just one project at a time. Everyone gets a period of bad luck with getting papers accepted (I had a long string of rejections throughout 2010 - I made up for it in 2011). The important thing is to have more than one project on the go at any one time, and to have a fast turn-around on rejected papers. If you follow a journal article submission strategy similar to the one I suggest, you should already have a good idea of other journals you could submit to.
It could be that you have had a run of poor luck on grant funding, and have not had the support to do your work and write up results, in terms of PhD students, postdocs, or simply a lack of equipment.
I do tend to agree with this point, especially for fields that need a lot of equipment to get results. I will point out, though, that having a good publication record will help with getting research grants.
Maybe a series of experiments didn’t work, but the next one will (and it will win a Nobel Prize).
Again, it is very important to pursue more than one research project at a time. That way, if one set of experiments doesn't work out, you can still publish the results from another.
Maybe your research output is highly subjective (think works by artists) and the critics didn’t like your last show.
This is more of a problem for researchers in the humanities. As a scientist I can't really comment on this, other than to point again to my responses above.
Maybe your research rivals knew about your employment conditions and decided to reject your last paper (to make it to the magic four) to get you sacked.
This is the most frightening point. Not only is such behavior completely unethical, it undermines the entire peer-review process. Anyone engaging in such behavior - rejecting papers just because the author is a rival - should be sacked immediately. If this does happen, it is also a failure on the part of the journal editors. Most journal submission systems allow the authors to list reviewers they are opposed to. Any editor who sends a paper to a reviewer who they have reasonable suspicion is a rival of the author, is failing to do their job.
Or maybe, just maybe you didn’t feel the need to publish every last little bit of work to avoid saturating the journals and keep the overall quality of published work high enough to make it bearable to read them.
This is a non sequitor. Submitting a lot of papers does not mean a lack of quality in the papers. As I mentioned above, you can break your project up into smaller, publishable chunks and submit a paper on each. Planning your research program is an essential skill for the professional researcher. Also, if the quality of the paper is so low that it's unreadable, how would it get published to begin with?
Maybe you published one Nature paper a year over the last three years and nothing else, and they each got 500 citations
This is one of those situations that could occur, but is really unlikely. The people I know who do publish in Nature, are the people who publish 20+ papers (journal articles) per year! I really can't see how anyone could be good enough to publish three papers in a row in Nature yet not be good enough to get one more paper published in another journal.
Publish or perish is the rule of academia, and has been for a long time. Sensible and positive ways you can publish without perishing are:
- pursuing more than one research project at a time
- collaborating widely (this is pretty easy to do in computational intelligence, as our algorithms are so widely applicable
- breaking your research into small, publishable chunks
- rapid turn-around on rejected papers
Thursday, March 8, 2012
Reminder: paper submission deadline for CISE 2012
A reminder that the deadline for papers submitted to the 4th International Conference on Computational Intelligence and Software Engineering (CISE) 2012 is 11 June 2012. This conference will be held in Wuhan, China, December 14-16, 2012.
Wednesday, March 7, 2012
Conference paper deadline: IDA 2012
The deadline for submitting papers to the Eleventh International Symposium on Intelligence Data Analysis (IDA) 2012 is 12 May 2012. This symposium will be held in Helsinki, Finland, 27-27 October, 2012.
Tuesday, March 6, 2012
Call for papers: ELM 2012
The deadline for submitting papers to the International Symposium on Extreme Learning Machines (ELM) 2012 is 1 June, 2012. This symposium will be held in Singapore 11-13 December, 2012.
Monday, March 5, 2012
Conference paper deadline: ICANN 2012
The deadline for submitting papers to the 22nd International Conference on Artificial Neural Networks (ICANN) 2012 is 19 March 2012. This conference will be held in Lausanne, Switzerland, 11-14 September, 2012.
Friday, March 2, 2012
Conference paper deadline: CISIS 2012
The deadline for submitting papers to the 5th International Conference on Computational Intelligence in Security for Information Systems (CISIS) 2012 is 20 March 2012. This conference will be held in Ostrava, Czech Republic, 5-8 September, 2012.
Wednesday, February 29, 2012
Reminder: conference paper deadline for EANN
A reminder that the deadline for submitting papers to the 13th International Conference on Engineering Applications of Neural Networks (EANN 2012) is 31 March 2012. This conference will be held in London, UK, 20-23 September, 2012.
Tuesday, February 28, 2012
Publishing or perishing 2
Or, big trouble in little USyd.
In a previous post, I discussed the principle of "Publish or perish". This phrase is a succinct way of saying that the most important metric by which an academic is judged, is their publication record: those who do not publish enough will not be valued as highly as those who publish more. Recent developments in Australian academia have made this literally true.
The University of Sydney is dismissing 100 academics who have not published at least four times in the last three years. Early career researchers are apparently exempt from this threshold, so it is only senior academics (presumably permanent staff members) who are at risk. In other words, they are in senior positions, yet they have not published, so they are perishing.
To put that number (four papers is three years) in perspective, I'm not a permanent staff member, yet in the last three years I've published fifteen times, and have more than a dozen publications in the pipeline (I expect to publish them this year). While I am currently full-time research, I have taught full-time in the past, yet I still managed to publish research. During my final year teaching, I published papers, was finishing my PhD, and taught / administered two undergrad courses. I got married that year, too.
The only thing that garners any sympathy from me is that claims are being made that late last year academic staff were told that an average publication rate of 0.8 per year (four papers in five years) would be satisfactory. If that is true, then management have moved the goal-posts, which strikes me as rather unfair. However, even when I was working as a post-doc at the University of Sydney, I was expected to produce at least two papers per year. In my current position, my target output is at least six per year (I got ten last year, and I'm on track to get twelve this year - the best way to meet a target, is to aim to exceed it). Did senior lecturers really think they could get away with less? "Publish or perish" is a very old saying.
Now, the University of Sydney is taking this action to make up for a massive short-fall in income (the exact reasons for this sudden short-fall are rather murky) but what would the effect be if this hard form of publish or perish were enforced more often at universities? It might have the effect of sweeping out those academics who have become complacent in their positions, or who are approaching the end of their academic careers (that is, they are no longer capable of performing research at the level required). This would in turn free up positions for younger staff, who are capable of producing publications, yet can't find permanent positions because they're being held by unproductive senior staff. Are there any other professions where those who do not perform, get to keep their jobs? Of course not. A major part of being an academic is publishing: if you're not publishing, you're not doing your job. If you're not doing your job, do you deserve to keep it?
On a humane level, I'm sorry for the people who are losing their jobs. But honestly, I wish this standard were applied at more universities.
In a previous post, I discussed the principle of "Publish or perish". This phrase is a succinct way of saying that the most important metric by which an academic is judged, is their publication record: those who do not publish enough will not be valued as highly as those who publish more. Recent developments in Australian academia have made this literally true.
The University of Sydney is dismissing 100 academics who have not published at least four times in the last three years. Early career researchers are apparently exempt from this threshold, so it is only senior academics (presumably permanent staff members) who are at risk. In other words, they are in senior positions, yet they have not published, so they are perishing.
To put that number (four papers is three years) in perspective, I'm not a permanent staff member, yet in the last three years I've published fifteen times, and have more than a dozen publications in the pipeline (I expect to publish them this year). While I am currently full-time research, I have taught full-time in the past, yet I still managed to publish research. During my final year teaching, I published papers, was finishing my PhD, and taught / administered two undergrad courses. I got married that year, too.
The only thing that garners any sympathy from me is that claims are being made that late last year academic staff were told that an average publication rate of 0.8 per year (four papers in five years) would be satisfactory. If that is true, then management have moved the goal-posts, which strikes me as rather unfair. However, even when I was working as a post-doc at the University of Sydney, I was expected to produce at least two papers per year. In my current position, my target output is at least six per year (I got ten last year, and I'm on track to get twelve this year - the best way to meet a target, is to aim to exceed it). Did senior lecturers really think they could get away with less? "Publish or perish" is a very old saying.
Now, the University of Sydney is taking this action to make up for a massive short-fall in income (the exact reasons for this sudden short-fall are rather murky) but what would the effect be if this hard form of publish or perish were enforced more often at universities? It might have the effect of sweeping out those academics who have become complacent in their positions, or who are approaching the end of their academic careers (that is, they are no longer capable of performing research at the level required). This would in turn free up positions for younger staff, who are capable of producing publications, yet can't find permanent positions because they're being held by unproductive senior staff. Are there any other professions where those who do not perform, get to keep their jobs? Of course not. A major part of being an academic is publishing: if you're not publishing, you're not doing your job. If you're not doing your job, do you deserve to keep it?
On a humane level, I'm sorry for the people who are losing their jobs. But honestly, I wish this standard were applied at more universities.
Monday, February 27, 2012
Conference paper deadline: FCTA 2012
The deadline for submitting papers to the International Conference on Fuzzy Computation Theory and Applications (FCTA) 2012 is 19 April 2012. This conference will be held in Barcelona, Spain, 5-7 October, 2012.
Friday, February 24, 2012
Reminder: paper submission deadline for UCNC 2012
A reminder that the deadline for submitting papers to the 11th Conference on Unconventional Computation and Natural Computation (UCNC) 2012 is 26 March 2012. This conference will be held in Orleans, France, 3-6 September, 2012.
Thursday, February 23, 2012
Reminder: paper submission deadline for CIDM 2012
A reminder that the deadline for submitting papers to the Third International Workshop on Computational Intelligence for Disaster Management (CIDM) 2012 is March 25 2012. This workshop will be held in Bucharest, Romania, 19-21 September 2012.
Wednesday, February 22, 2012
Using MLP to model the distribution of bacterial crop diseases
A new paper I co-authored with Sue Worner at Lincoln University is now available and describes how we used MLP to model the global distribution of bacterial crop diseases.
We had data on the presence or absence of certain species of bacterial crop disease (that is, bacteria that infect and cause diseases in plants we use as crops) in 459 geo-political regions throughout the world. We also had data on the climate in these regions and the presence of host plant species. We created MLP that predicted the presence or absence of the bacteria species from climate (abiotic factors). We also created MLP that predicted the presence or absence of the bacteria species from the host plant species assemblages (biotic factors). While both of these approaches worked, we got much better accuracies by combining the outputs into ensembles, and by using a cascaded or tandem ANN approach.
Ensembles are a way of combining the outputs of several ANN. An input vector is propagated through each of the ANN, and the output values combined either statistically (the final output value is the max, mean or median of the uncombined outputs) or algorithmically (output is determined as a majority vote of the uncombined outputs - that is, if the majority of the values is above a threshold, the output of the ensemble is a presence, otherwise, absence). We looked at three different kinds of ensemble: firstly, ensembles of the best ten MLP trained on abiotic inputs; secondly, ensembles of the best ten MLP trained on biotic inputs; and finally, ensembles that combined the best ten MLP trained on abiotic input as well as the best ten MLP trained on biotic inputs. These last ensembles were particularly interesting, as it allowed us to make predictions of species distributions using both biotic and abiotic factors simultaneously. The rationale behind ensembles is that different MLP learn different parts of the problem space: by combining the outputs of several MLP, it is possible to cover a larger part of the problem space, and therefore to boost prediction accuracy. Combining abiotic and biotic factors is the same idea. We know that an organism is affected by both of these factors, so combining both of them allows us to make more accurate predictions.
While the ensemble approach boosted the prediction accuracies, we thought we could do better, so we created MLP that took as inputs the outputs of the very best MLP trained on abiotic and biotic factors. In other words, the outputs of the climate and host networks were used as the input values for a second-level of MLP, which were then trained on the presence and absence of the bacteria species. The idea behind tandem ANN is that, if a first-level network makes a mistake - that is, if a climate or host MLP makes an incorrect prediction - then the tandem network can learn to correct it. Again, we were combining abiotic and biotic factors to make predictions.
The results of all these techniques were that while the single-level MLP were able to predict the distributions of the crop diseases fairly well, combining abiotic and biotic factors gave much better accuracy, whether the combination was achieved by a simple ensemble approach, or by using a tandem MLP approach.
This paper is published in Computational Ecology and Software, an open-access journal. Given my previous posts extolling the virtues of open access journals (see here, here, here and here) I'm putting my academic money where my mouth is, and submitting to open-access journals.
We had data on the presence or absence of certain species of bacterial crop disease (that is, bacteria that infect and cause diseases in plants we use as crops) in 459 geo-political regions throughout the world. We also had data on the climate in these regions and the presence of host plant species. We created MLP that predicted the presence or absence of the bacteria species from climate (abiotic factors). We also created MLP that predicted the presence or absence of the bacteria species from the host plant species assemblages (biotic factors). While both of these approaches worked, we got much better accuracies by combining the outputs into ensembles, and by using a cascaded or tandem ANN approach.
Ensembles are a way of combining the outputs of several ANN. An input vector is propagated through each of the ANN, and the output values combined either statistically (the final output value is the max, mean or median of the uncombined outputs) or algorithmically (output is determined as a majority vote of the uncombined outputs - that is, if the majority of the values is above a threshold, the output of the ensemble is a presence, otherwise, absence). We looked at three different kinds of ensemble: firstly, ensembles of the best ten MLP trained on abiotic inputs; secondly, ensembles of the best ten MLP trained on biotic inputs; and finally, ensembles that combined the best ten MLP trained on abiotic input as well as the best ten MLP trained on biotic inputs. These last ensembles were particularly interesting, as it allowed us to make predictions of species distributions using both biotic and abiotic factors simultaneously. The rationale behind ensembles is that different MLP learn different parts of the problem space: by combining the outputs of several MLP, it is possible to cover a larger part of the problem space, and therefore to boost prediction accuracy. Combining abiotic and biotic factors is the same idea. We know that an organism is affected by both of these factors, so combining both of them allows us to make more accurate predictions.
While the ensemble approach boosted the prediction accuracies, we thought we could do better, so we created MLP that took as inputs the outputs of the very best MLP trained on abiotic and biotic factors. In other words, the outputs of the climate and host networks were used as the input values for a second-level of MLP, which were then trained on the presence and absence of the bacteria species. The idea behind tandem ANN is that, if a first-level network makes a mistake - that is, if a climate or host MLP makes an incorrect prediction - then the tandem network can learn to correct it. Again, we were combining abiotic and biotic factors to make predictions.
The results of all these techniques were that while the single-level MLP were able to predict the distributions of the crop diseases fairly well, combining abiotic and biotic factors gave much better accuracy, whether the combination was achieved by a simple ensemble approach, or by using a tandem MLP approach.
This paper is published in Computational Ecology and Software, an open-access journal. Given my previous posts extolling the virtues of open access journals (see here, here, here and here) I'm putting my academic money where my mouth is, and submitting to open-access journals.
Tuesday, February 21, 2012
Conference paper deadline: NIPS 2012
The deadline for submitting papers to Neural Information Processing Systems (NIPS) 2012 is 2 June 2012. This conference will be held at Lake Tahoe, Nevada, 3-6 December, 2012.
Monday, February 20, 2012
Call for papers: Applications of ECoS
Special issue of Evolving Systems on
Applications of Evolving Connectionist Systems
Guest Editor
Scope
The topic of this special issue is “Applications of Kasabov’s Evolving Connectionist Systems”.
In modern society, the volume and rate of data production are huge and set to increase. To process and utilise this avalanche of data, methods are needed that can rapidly and accurately model it as it becomes available. These models must be able to learn throughout their lifetimes, without forgetting what they have previously learned, and be able to explain themselves.
Kasabov’s Evolving Connectionist Systems (ECoS) are able to fulfil each of these requirements. They are a class of constructive neural networks that learn via structural growth and adaptation. They have a fast, one-pass learning algorithm, where all that can be learnt from the data is learned in the first training pass. Because of their open structure, they exhibit continuous, life-long learning whereby the structure expands as necessary to accommodate new data. Finally, they have a strong resistance to catastrophic forgetting following additional training on new data.
Examples of ECoS networks include the Evolving Fuzzy Neural Network (EFuNN), which was the first ECoS network published and is characterised by embedded fuzzy logic elements. There is also the Simple Evolving Connectionist System (SECoS), which is essentially an EFuNN with the fuzzy elements removed, and the Dynamic Evolving Fuzzy Inference System (DENFIS) for discovering Takagi-Sugeno style fuzzy rules. Many ECoS networks use fuzzy rule extraction algorithms that allow for the explanation of what the networks have learned, in a comprehensible manner.
ECoS networks are well suited to applications that are dealing with new data continuously and that have dynamic, time-critical aspects. Previous applications of ECoS include:
- Stock market prediction and macroeconomic modelling
- Speech recognition, especially multi-speaker speech recognition
- Bioinformatics and medical modelling
- Image and video parsing
- Robot control
- Information system security
The special issue is concerned with all aspects of the application of ECoS networks to real-life problems and data sets. Topics of interest include, but are not limited to:
- Applications of ECoS to real-world problems
- Data mining of complex data sets using ECoS
- Comparisons of ECoS with other algorithms over real-world data sets
- Modifications of ECoS algorithms to fit them to real-world problems
Proposed Schedule
- Submission due date: 16 April, 2012
- Preliminary notification of acceptance: 4 June, 2012
- Revised manuscripts due: 9 July, 2012
- Final acceptance notification: 6 August, 2012
- Final version due: 3 September, 2012
- Intended publication date: January, 2013
Submission
The special issue invites original contributions within the specified scope. Manuscripts must not be under review elsewhere, nor can they have been previously published. Extended conference papers must contain at least 30% new material. Please format all manuscripts according to the Instructions for Authors:
Please submit all papers via the online submission system:
Friday, February 17, 2012
Reminder: paper submission deadline for IEEE CISDA 2012
A reminder that the deadline for papers submitted to the IEEE Workshop on Computational Intelligence for Security and Defence Applications (IEEE CISDA) 2012 is 19 March 2012. This workshop will be held in Ottawa, Canada, 11-13 July 2012.
Thursday, February 16, 2012
Call for papers: CIDU 2012
The deadline for submitting papers to the 2012 Conference on Intelligent Data Understanding (CIDU) 2012 is 18 May 2012. This conference will be held in Boulder, Colorado, 24-26 October, 2012.
Wednesday, February 15, 2012
Reminder: paper submission deadline ICONIP 2012
A reminder that the paper submission deadline for the International Conference on Neural Information Processing (ICONIP) 2012 is May 15, 2012. This conference will be held in Doha, Qatar, November 26-29, 2012.
Tuesday, February 14, 2012
Reminder: paper submission deadline for IEEE CIMSA 2012
A reminder that the deadline for submitting papers to the IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (IEEE CIMSA) 2012 is 15 March 2012. This conference will be held in Tianjin, China, 2-4 July 2012.
Monday, February 13, 2012
Reminder: paper submission deadline for PPSN 2012
A reminder that the deadline for submitting papers to the 12th International Conference on Parallel Problem Solving from Nature (PPSN) 2012 is the 12th of March, 2012. This conference will be held in Taormina, Italy, 1-5 September 2012.
Friday, February 10, 2012
Paper deadline extension: ICIC 2012
The deadline for papers submitted to the International Conference on Intelligent Computing (ICIC) 2012 has been extended to March 31, 2012. This conference will be held in Huangshan, China, July 25-29, 2012.
Conference paper submission deadline for UKCI 2012
The paper submission deadline for the 12th UK Annual Workshop on Computational Intelligence (UKCI) 2012 is May 1, 2012. This workshop will be held in Edinburgh, Scotland, UK, 5-7 September, 2012.
Thursday, February 9, 2012
New article: IEEE CIS social media
An article I co-wrote with Albert Lam, Dongrui Wu and Pablo Estevez, describing the social media presence of the IEEE Computational Intelligence Society:
Via IEEE Xplore.
Alternative link.
Via IEEE Xplore.
Alternative link.
Conference paper deadline: iCAST 2012
The deadline for submitting papers to the 4th International Conference on Awareness Science and Technology (iCAST) 2012 is 15 April 2012. The conference will be held in Seoul, Korea, 21-24 August, 2012.
Wednesday, February 8, 2012
Call for papers: AI'12
The deadline for submitting papers to the 25th Australasian Joint Conference on Artificial Intelligence (AI) 2012 is 29 June, 2012. This conference will be held in Sydney, Australia, 4-7 December, 2012.
Tuesday, February 7, 2012
Reminder: Paper submission deadline for ECAI 2012
A reminder that the deadline for papers submitted to the 20th European Conference on Artificial Intelligence (ECAI) 2012 is 6 March 2012. This conference will be held in Montpellier, France, 27-21 August, 2012.
Monday, February 6, 2012
Conference paper deadline: NAFIPS 2012
The paper submission deadline for the 31st annual meeting of the North American Fuzzy Information Processing Society (NAFIPS) 2012 is February 26, 2012. This conference will be held in Berkeley, California, USA,
Friday, February 3, 2012
The problem with academic journals 4
Or, why I'm not boycotting Elsevier.
"You never change something by fighting the existing reality. To change something build a new model that makes the existing model obsolete." - R. Buckminster Fuller
This is the fourth post in a series about the problems with the big academic journal publishers. In summary: the journals get their content for free; get their quality control (peer review / refereeing) for free; and get their editors for free, yet they charge many thousands of dollars for subscriptions. This bad situation has been compounded by publishers like Elsevier basically trying to buy a law that directly attacks open-access journals.
In response to this, and to other bad behaviour, calls for a boycott of Elsevier have culminated in this website being launched, where scientists can pledge to not submit, referee or edit for Elsevier journals. At the time of writing, around 3000 scientists have already done so.
I am not one of them, and I will not be one of them. I have several reasons for taking this position, some of them idealistic, and others pragmatic.
Firstly, I agree with the sentiment from Fuller above: it is better to create something new than to tear down the old. In this case, it means that it is better to support open access journals than to boycott traditional journals. In other words, let the old journals wither away into history because they have been made obsolete, not because one particular publisher has been throttled by a boycott.
Secondly, boycotting one publisher (Elsevier, in this case) won't achieve much. Other publishers, who are guilty of much the same behaviour as Elsevier, will simply pick up the slack, that is, they will see an increase in submissions that would have otherwise have gone to Elsevier journals. The boycott might hurt Elsevier, but it won't fix the problem with academic journals.
Thirdly, there is a lack of alternative venues for some fields. For my ecological research, the most appropriate journals are Ecological Informatics and Ecological Modelling, both of which are published by Elsevier. There is an open-access alternative to them, Computational Ecology and Software, but it is less than a year old and has yet to become anywhere near as established as the incumbents.
Fourthly, students and junior researchers do not have much of a choice where they submit their papers. If your supervisor says to submit your paper to an Elsevier journal, do you really have a choice about it?
Finally, any early-career researcher who signs on to this boycott is setting themselves up for some trouble down the line. As an early-career researcher myself, I ask myself, do I want to mark myself as someone who will not try to publish in the top journals in my field, just because they are published by Elsevier? I need to publish in the most appropriate and highly-ranked journals in my field, and for me, most of those are published by Elsevier. Put another way, I don't have a permanent job yet, so I need to publish in the most appropriate and highly-ranked journals for the sake of my career. I need to develop my career because I have a family to support. If that makes me a coward, at least I'll be a coward who can feed his family.
We will not solve the problems with academic journals by boycotting any one publisher. We will solve the problems with academic journals by supporting open access journals. That means submitting papers to them, refereeing papers for them, and volunteering on their editorial boards. I am supporting CES, by publishing papers with them, and by working on their editorial board. I might even start my own open-access journal one day. But we need more top researchers to get involved with open access journals. We need the big names to support them, so they get the citations they need to increase their impact factors, so the journals become more desirable venues in which to publish.
If there were a site where scientists could pledge to submit, referee and do editorial work for open-access journals, I would sign up there. I might even set it up myself - it's not like I need to sleep, is it?
"You never change something by fighting the existing reality. To change something build a new model that makes the existing model obsolete." - R. Buckminster Fuller
This is the fourth post in a series about the problems with the big academic journal publishers. In summary: the journals get their content for free; get their quality control (peer review / refereeing) for free; and get their editors for free, yet they charge many thousands of dollars for subscriptions. This bad situation has been compounded by publishers like Elsevier basically trying to buy a law that directly attacks open-access journals.
In response to this, and to other bad behaviour, calls for a boycott of Elsevier have culminated in this website being launched, where scientists can pledge to not submit, referee or edit for Elsevier journals. At the time of writing, around 3000 scientists have already done so.
I am not one of them, and I will not be one of them. I have several reasons for taking this position, some of them idealistic, and others pragmatic.
Firstly, I agree with the sentiment from Fuller above: it is better to create something new than to tear down the old. In this case, it means that it is better to support open access journals than to boycott traditional journals. In other words, let the old journals wither away into history because they have been made obsolete, not because one particular publisher has been throttled by a boycott.
Secondly, boycotting one publisher (Elsevier, in this case) won't achieve much. Other publishers, who are guilty of much the same behaviour as Elsevier, will simply pick up the slack, that is, they will see an increase in submissions that would have otherwise have gone to Elsevier journals. The boycott might hurt Elsevier, but it won't fix the problem with academic journals.
Thirdly, there is a lack of alternative venues for some fields. For my ecological research, the most appropriate journals are Ecological Informatics and Ecological Modelling, both of which are published by Elsevier. There is an open-access alternative to them, Computational Ecology and Software, but it is less than a year old and has yet to become anywhere near as established as the incumbents.
Fourthly, students and junior researchers do not have much of a choice where they submit their papers. If your supervisor says to submit your paper to an Elsevier journal, do you really have a choice about it?
Finally, any early-career researcher who signs on to this boycott is setting themselves up for some trouble down the line. As an early-career researcher myself, I ask myself, do I want to mark myself as someone who will not try to publish in the top journals in my field, just because they are published by Elsevier? I need to publish in the most appropriate and highly-ranked journals in my field, and for me, most of those are published by Elsevier. Put another way, I don't have a permanent job yet, so I need to publish in the most appropriate and highly-ranked journals for the sake of my career. I need to develop my career because I have a family to support. If that makes me a coward, at least I'll be a coward who can feed his family.
We will not solve the problems with academic journals by boycotting any one publisher. We will solve the problems with academic journals by supporting open access journals. That means submitting papers to them, refereeing papers for them, and volunteering on their editorial boards. I am supporting CES, by publishing papers with them, and by working on their editorial board. I might even start my own open-access journal one day. But we need more top researchers to get involved with open access journals. We need the big names to support them, so they get the citations they need to increase their impact factors, so the journals become more desirable venues in which to publish.
If there were a site where scientists could pledge to submit, referee and do editorial work for open-access journals, I would sign up there. I might even set it up myself - it's not like I need to sleep, is it?
Thursday, February 2, 2012
Reminder: paper submission deadline SEAL 2012
A reminder that the deadline for submitting papers to the 9th International Conference on Evolution and Learning (SEAL) 2012 is 1 May 2012. This conference will be held in Hanoi, Vietnam, 16-19 December, 2012.
Wednesday, February 1, 2012
Reminder: paper submission deadline for ICARIS 2012
A reminder that the deadline for submitting papers to the 11th International Conference on Artificial Immune Systems (ICARIS) 2012 is 1 March 2012. This conference will be held in Taormina, Italy, 28-21 July, 2012.
Tuesday, January 31, 2012
Reminder: Paper submission deadline for PRICAI 2012
A reminder that the deadline for papers submitted to the 12th Pacific Rim International Conference on Artificial Intelligence (PRICAI) 2012 is March 1, 2012. This conference will be held in Kuching, Malaysia, September 3-7, 2012.
Monday, January 30, 2012
Publishing or perishing
The single most important metric by which an academic is judged is their peer-reviewed publication record. Promotion, grant applications, and finding new jobs all depends on having a strong publication record. This has long been described as "Publish or perish", because if you don't publish, you perish - either you don't advance in your job, you can't find a job, or you don't keep your job. Now, I've got a reasonably long publication record, but I'm always looking for ways of boosting my research output (see my previous posts on publishing in computational intelligence).
Several years ago, biologist Phil Clapham published an excellent essay on the need for academics to publish their research. One of his rules, that I am applying to my own work, is to have at least one paper under review at all times. Now, this can be pretty hard work - there is always variation in the amount of time that papers spend in review, and reviewer comments can take a long time to address. But, it does lead to building up your publication record quite quickly.
One outcome of this rule, though, is that one should also be writing at least one paper at any given time, while also generating sufficient publishable results for at least one paper at any given time. That is, while at least one paper is in review, you need to be writing at least one paper, and also writing code / designing experiments / performing analyses to go into at least one other paper. So, publishing is like being on a treadmill: as soon as you submit one paper, you need to get to work on getting the next submitted, while lining up the material for the one after that.
While this does encourage the practice of breaking research projects into small, easily published (and easily understood) chunks, I suspect it may also encourage further proliferation of single publon papers. Whether or not this is a bad thing, I've leave to you to decide.
Another way to boost your publication count is to collaborate. A lot. Computational intelligence is a particularly useful field to come from for collaborating, as the algorithms we study can be applied to so many problems. But that's all a topic for another post.
Several years ago, biologist Phil Clapham published an excellent essay on the need for academics to publish their research. One of his rules, that I am applying to my own work, is to have at least one paper under review at all times. Now, this can be pretty hard work - there is always variation in the amount of time that papers spend in review, and reviewer comments can take a long time to address. But, it does lead to building up your publication record quite quickly.
One outcome of this rule, though, is that one should also be writing at least one paper at any given time, while also generating sufficient publishable results for at least one paper at any given time. That is, while at least one paper is in review, you need to be writing at least one paper, and also writing code / designing experiments / performing analyses to go into at least one other paper. So, publishing is like being on a treadmill: as soon as you submit one paper, you need to get to work on getting the next submitted, while lining up the material for the one after that.
While this does encourage the practice of breaking research projects into small, easily published (and easily understood) chunks, I suspect it may also encourage further proliferation of single publon papers. Whether or not this is a bad thing, I've leave to you to decide.
Another way to boost your publication count is to collaborate. A lot. Computational intelligence is a particularly useful field to come from for collaborating, as the algorithms we study can be applied to so many problems. But that's all a topic for another post.
Friday, January 27, 2012
Call for papers: Applications of ECoS
Special issue of Evolving Systems on
Applications of Evolving Connectionist Systems
Guest Editor
Scope
The topic of this special issue is “Applications of Kasabov’s Evolving Connectionist Systems”.
In modern society, the volume and rate of data production are huge and set to increase. To process and utilise this avalanche of data, methods are needed that can rapidly and accurately model it as it becomes available. These models must be able to learn throughout their lifetimes, without forgetting what they have previously learned, and be able to explain themselves.
Kasabov’s Evolving Connectionist Systems (ECoS) are able to fulfil each of these requirements. They are a class of constructive neural networks that learn via structural growth and adaptation. They have a fast, one-pass learning algorithm, where all that can be learnt from the data is learned in the first training pass. Because of their open structure, they exhibit continuous, life-long learning whereby the structure expands as necessary to accommodate new data. Finally, they have a strong resistance to catastrophic forgetting following additional training on new data.
Examples of ECoS networks include the Evolving Fuzzy Neural Network (EFuNN), which was the first ECoS network published and is characterised by embedded fuzzy logic elements. There is also the Simple Evolving Connectionist System (SECoS), which is essentially an EFuNN with the fuzzy elements removed, and the Dynamic Evolving Fuzzy Inference System (DENFIS) for discovering Takagi-Sugeno style fuzzy rules. Many ECoS networks use fuzzy rule extraction algorithms that allow for the explanation of what the networks have learned, in a comprehensible manner.
ECoS networks are well suited to applications that are dealing with new data continuously and that have dynamic, time-critical aspects. Previous applications of ECoS include:
- Stock market prediction and macroeconomic modelling
- Speech recognition, especially multi-speaker speech recognition
- Bioinformatics and medical modelling
- Image and video parsing
- Robot control
- Information system security
The special issue is concerned with all aspects of the application of ECoS networks to real-life problems and data sets. Topics of interest include, but are not limited to:
- Applications of ECoS to real-world problems
- Data mining of complex data sets using ECoS
- Comparisons of ECoS with other algorithms over real-world data sets
- Modifications of ECoS algorithms to fit them to real-world problems
Proposed Schedule
- Submission due date: 16 April, 2012
- Preliminary notification of acceptance: 4 June, 2012
- Revised manuscripts due: 9 July, 2012
- Final acceptance notification: 6 August, 2012
- Final version due: 3 September, 2012
- Intended publication date: January, 2013
Submission
The special issue invites original contributions within the specified scope. Manuscripts must not be under review elsewhere, nor can they have been previously published. Extended conference papers must contain at least 30% new material. Please format all manuscripts according to the Instructions for Authors:
Please submit all papers via the online submission system:
Conference paper deadline: IJCCI 2012
The deadline for submitting papers to the International Joint Conference on Computational Intelligence (IJCCI) 2012 is 19 April 2012. This conference will be held in Barcelona, Spain, 5-7 October, 2012.
Thursday, January 26, 2012
Paper submission deadline: IEEE CIG 2012
The deadline for submitting papers to the IEEE Conference on Computational Intelligence in Games (IEEE CIG) 2012 is 15 April 2012. This conference will be held in Granada, Spain, 12-15 September, 2012.
Wednesday, January 25, 2012
Call for papers: IEEE CIMSA 2012
The deadline for submitting papers to the IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (IEEE CIMSA) 2012 is 15 March 2012. This conference will be held in Tianjin, China, 2-4 July 2012.
Tuesday, January 24, 2012
Reminder: paper submission deadline for ICML 2012
A reminder that the deadline for submitting papers to the International Conference on Machine Learning (ICML) 2012 is 24 February 2012. This conference will be held in Edinburgh, Scotland, June 26 - July 1, 2012.
Monday, January 23, 2012
Call for papers: CIDM 2012
The deadline for submitting papers to the Third International Workshop on Computational Intelligence for Disaster Management (CIDM) 2012 is March 25 2012. This workshop will be held in Bucharest, Romania, 19-21 September 2012.
Saturday, January 21, 2012
Conference paper deadline: AAIA 2012
The deadline for submitting papers to the 7th International Symposium Advances in Artificial Intelligence and Applications (AIAA) 2012 is 22 April 2012. This conference will be held in Wroclaw, Poland, 9-12 September, 2012.
Thursday, January 19, 2012
The problem with academic journals 3
I've tried to stay away from politics on this blog, as I want to keep it as professional as I can, and politics is one of the two things (along with religion) guaranteed to make otherwise pleasant and rational people lose all self control. But sometimes, politics intrudes into the academy: as Pericles put it "Just because you do not take an interest in politics does not mean politics won't take an interest in you".
I've discussed the problems with academic journals twice before. What has prompted me to revisit the topic, and break my taboo on politics on this blog, is the Research Works Act, which is nothing less than a direct assault by the US government on open access journals. Not that the US government per se has anything against open access journals: journal publishers like Elsevier do, though, so what they've done is whack down a sack of cash in front of their tame congress members and bought a law. This law, if passed, would ban US government funding agencies from requiring that papers resulting from their funding be made available as open access publications. This has caused a firestorm in the academic blogosphere, with calls for scholarly societies to withdraw from the American Association of Publishers (one of the groups lobbying in favour of the law), and with some even going so far as to call academic publishers enemies of science.
I have published in open-access journals. I'm even on the editorial board of one, and I find this law extremely disturbing. It is in direct contrast to other countries such as the UK, where a new policy from the science minister requires the results of publicly funded research to be open-access. It is simply a desperate attempt by the established journal publishers to protect a business model that is going the way of horse-drawn carriages and rotary-dial telephones.
Although one could argue that, as a New Zealand citizen resident in Australia, this will not really effect me, the USA has a habit of forcing it's laws on other countries. How long before other countries, like Australia or New Zealand, get similar laws? Even if this proposed law is defeated in the USA, does anyone seriously think that the publishers will give up trying to kill open access journals?
Open access is the future of academic publishing. Publishers are trying to protect a failing business model by exploiting a political system that seems, to someone raised in a Westminster-style democracy, quite corrupt. Since we have no chance of changing that system, the only response open to scientists is to move away from publishing in the journals published by companies like Elsevier, and publish instead in open-access journals. In other words, cut the journal publishers out completely and starve them of the quality papers they need to be successful.
Over the next several weeks, I will be collating a list of open-access computational intelligence journals, and reviewing a selection of papers from each. It's time to take open-access seriously. It's time to embrace the future, and to leave the old publishers in the dustbin of history.
I've discussed the problems with academic journals twice before. What has prompted me to revisit the topic, and break my taboo on politics on this blog, is the Research Works Act, which is nothing less than a direct assault by the US government on open access journals. Not that the US government per se has anything against open access journals: journal publishers like Elsevier do, though, so what they've done is whack down a sack of cash in front of their tame congress members and bought a law. This law, if passed, would ban US government funding agencies from requiring that papers resulting from their funding be made available as open access publications. This has caused a firestorm in the academic blogosphere, with calls for scholarly societies to withdraw from the American Association of Publishers (one of the groups lobbying in favour of the law), and with some even going so far as to call academic publishers enemies of science.
I have published in open-access journals. I'm even on the editorial board of one, and I find this law extremely disturbing. It is in direct contrast to other countries such as the UK, where a new policy from the science minister requires the results of publicly funded research to be open-access. It is simply a desperate attempt by the established journal publishers to protect a business model that is going the way of horse-drawn carriages and rotary-dial telephones.
Although one could argue that, as a New Zealand citizen resident in Australia, this will not really effect me, the USA has a habit of forcing it's laws on other countries. How long before other countries, like Australia or New Zealand, get similar laws? Even if this proposed law is defeated in the USA, does anyone seriously think that the publishers will give up trying to kill open access journals?
Open access is the future of academic publishing. Publishers are trying to protect a failing business model by exploiting a political system that seems, to someone raised in a Westminster-style democracy, quite corrupt. Since we have no chance of changing that system, the only response open to scientists is to move away from publishing in the journals published by companies like Elsevier, and publish instead in open-access journals. In other words, cut the journal publishers out completely and starve them of the quality papers they need to be successful.
Over the next several weeks, I will be collating a list of open-access computational intelligence journals, and reviewing a selection of papers from each. It's time to take open-access seriously. It's time to embrace the future, and to leave the old publishers in the dustbin of history.
Wednesday, January 18, 2012
IEEE Computational Intelligence Society Call for Social Media Subcommittee members
Dear CIS members,
This is a call for active participation in the CIS Social Media Subcommittee.
The Social Media Subcommittee, established in 2011, is a subcommittee under the Member Activities committee of CIS. Our objectives are to promote CIS membership and activities, to leverage our online presence, and build our leadership in CIS-related research and industrial communities.
Social Media have become very popular in recent years. Examples include Facebook, Twitter, LinkedIn, and Second Life. They have become part of our lives and some of the major channels to get updates about our friends and the rest of the world. Our mission is to keep you up-to-date about CIS and computational intelligence-related information in the most direct and timely manner. You will no longer miss deadlines for submitting papers to our conferences and you will be able to get involved in discussions of the hottest topics in computational intelligence with our professionals.
The Subcommittee is continuously seeking to develop new and innovative initiatives for promoting CIS with Social Media. We are looking for enthusiastic members who are keen to get involved in the activities of the Subcommittee. The main tasks are to set up and manage the accounts in some of the major Social Media (i.e., Facebook, Twitter, LinkedIn, Second Life, etc.) and to pursue suggestions for using Social Media to other parties of CIS. Experience in programming in Facebook and Second Life is preferred.
We believe you may have experience in and use one or more Social Media on a regular basis. To be a Subcommittee member, you will just need to spare some of your time working with Social Media for CIS. You will provide valuable experience in committee membership and society involvement that could be useful on your CV, or as a stepping-stone towards further CIS technical committee involvement.
Being a member will require enthusiasm, dedication and the investment of some of your time for meetings, preparing documents for initiatives, and managing the CIS Social Media activities. As the Chairs of the IEEE CIS Social Media Subcommittee, we would like to invite any interested IEEE CIS members worldwide to join us.
If you are interested in joining this Social Media Subcommittee and further promoting your professional careers, please send your CV to us (cis.socialmedia@gmail.com) with email subject title “[SMS] Recruitment 2012” before January 28, 2012.
If you are not interested in joining the Subcommittee but are keen to provide input and feedback on CIS initiatives for Social Media, please also contact us.
We would appreciate it if you could forward this call to any IEEE CIS members who may be interested.
We look forward to hearing from you. Thank you very much for your attention.
Best Regards,
Albert Y.S. Lam
Chair, IEEE CIS Social Media Subcommittee
Monday, January 16, 2012
Reminder: paper deadline for ICCCI 2012
A reminder that the deadline for papers submitted to the 4th International Conference on Computational Collective Intelligence (ICCCI) 2012 is 15 April 2012. This conference will be held in Ho Chi Minh City, Vietnam, 28-30 November, 2012.
Friday, January 13, 2012
Reminder: paper submission deadline for ISICA 2012
A reminder that the deadline for papers submitted to the International Symposium on Intelligence Computing and Applications (ISICA) 2012 is 15 April 2012. This conference will be held in Wuhan, China, 27-28 October, 2012.
Thursday, January 12, 2012
Reminder: paper submission deadline for CBR-MD 2012
A reminder that the deadline for submitting papers to the International Workshop Case-Based Reasoning (CBR-MD) 2012 is 13 April 2012. This workshop will be held in Berlin, Germany, 20 July 2012.
Friday, December 30, 2011
Reminder: conference paper deadline for EANN
A reminder that the deadline for submitting papers to the 13th International Conference on Engineering Applications of Neural Networks (EANN 2012) is 31 March 2012. This conference will be held in London, UK, 20-23 September, 2012.
Friday, December 23, 2011
Reminder: paper submission deadline for UCNC 2012
A reminder that the deadline for submitting papers to the 11th Conference on Unconventional Computation and Natural Computation (UCNC) 2012 is 26 March 2012. This conference will be held in Orleans, France, 3-6 September, 2012.
Monday, December 19, 2011
Reminder: paper submission deadline for IEEE CISDA 2012
A reminder that the deadline for papers submitted to the IEEE Workshop on Computational Intelligence for Security and Defence Applications (IEEE CISDA) 2012 is 19 March 2012. This workshop will be held in Ottawa, Canada, 11-13 July 2012.
Friday, December 16, 2011
Reminder: paper submission deadline for BICS 2012
A reminder that the deadline for submitting papers to the International Conference on Brain Inspired Cognitive Systems (BICS) 2012 is 15 January 2012. This conference will be held in Shenyang, China, 11-14 July, 2012.
Subscribe to:
Posts (Atom)
Posts
