Wednesday, April 11, 2012
Reminder: paper submission deadline for IEEE-SSCI 2013
A reminder that the deadline for the IEEE Symposium Series in Computational Intelligence 2013 is 10 October 2012. This series of symposia will be held in Singapore 16-19 April 2013.
Tuesday, April 10, 2012
Building an online presence as an academic
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
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
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:
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