Thursday, February 6, 2014

The problem with academic journals 8

It's been a long time since I last blogged about the problems with academic journals. Several of my old posts described the behaviour of the giant academic publisher Elsevier, specifically trying to buy a law in the US Congress that would virtually ban researchers publishing in open-access journals. This resulted in an enormous backlash against Elsevier, including a boycott that now has more than 14,000 names, culminating in the proposed legislation being dropped.

Unfortunately, Elsevier is back to their old bad behaviour: they have been sending notices to researchers and academic network sites demanding the removal from the web of papers that the researchers' had published in Elsevier journals. While Elsevier may be within their legal rights to do so (since they demand that authors sign over copyright to Elsevier), preventing people from self-archiving papers that they wrote is highly
 detrimental to science. In other words, Elsevier gets the research papers for free (submitted by the authors), they get the quality control for free (done by volunteer reviewers), and the administration of journals for free (done by volunteer editors). Then, they do some basic formatting and proof-reading, demand that the authors surrender all rights to the article, and publish it at an enormous profit.

Some publishers like the IEEE work the same way but allow for self-archiving, that is, they allow authors to post papers they have authored on their own websites for other researchers to access. The IEEE seems to be doing quite well out of this practice, but then the high offices of the IEEE are held by engineers and academics rather than businessmen. Does Elsevier really think that they can get away with this kind of bully-boy behaviour?

There are a couple of Elsevier journals that I've published several papers in, and I still have research that I was going to submit to them. But now I think that It's time for me to find some alternative journals to submit my work to. I'm currently reviewing one article for an Elsevier journal, and I took that task on because a friend asked me to, but after that, I won't review for any Elsevier journals. And I will not, under any circumstances, serve on the editorial board of any Elsevier journals.

Wednesday, February 5, 2014

Neural Networks new articles 2 January - 3 February, 2014

1. Safe semi-supervised learning based on weighted likelihood  
Author(s): Masanori Kawakita, Jun’ichi Takeuchi
   
2. Effects of asymmetric and self coupling on metastable dynamical transient rotating waves in a ring of sigmoidal neurons  
Author(s): Yo Horikawa

3. Kernel learning at the first level of inference  
Author(s): Gavin C. Cawley, Nicola L.C. Talbot
   
4. Convergence behavior of delayed discrete cellular neural network without periodic coefficients
Author(s): Jinling Wang, Haijun Jiang, Cheng Hu, Tianlong Ma
    
5. Generalization performance of Gaussian kernels SVMC based on Markov sampling 
Author(s): Jie Xu, Yuan Yan Tang, Bin Zou, Zongben Xu, Luoqing Li, Yang Lu

6. Assist-as-needed robotic trainer based on reinforcement learning and its application to dart-throwing  
Author(s): Chihiro Obayashi, Tomoya Tamei, Tomohiro Shibata
   
7. Cross-person activity recognition using reduced kernel extreme learning machine 
Author(s): Wan-Yu Deng, Qing-Hua Zheng, Zhong-Min Wang
   
8. Robust head pose estimation via supervised manifold learning  
Author(s): Chao Wang, Xubo Song

9. Synchronization control of memristor-based recurrent neural networks with perturbations  
Author(s): Weiping Wang, Lixiang Li, Haipeng Peng, Jinghua Xiao, Yixian Yang

Tuesday, February 4, 2014

IEEE Transactions on Evolutionary Computation, Volume 18, Number 1, February 2014

1. Guest Editorial: Special Issue on Advances in Multiobjective Evolutionary Algorithms for Data Mining
Author(s): Bandyopadhyay, S. ; Maulik, U. ; Coello, C.A.C. ; Pedrycz, W.
Pages: 1-3

2. A Survey of Multiobjective Evolutionary Algorithms for Data Mining: Part I
Author(s): A. Mukhopadhyay, U. Maulik, S. Bandyopadhyay, and C. A. Coello Coello
Pages: 4-19

3. Survey of Multiobjective Evolutionary Algorithms for Data Mining: Part II
Author(s): A. Mukhopadhyay, U. Maulik, S. Bandyopadhyay, and C. A. Coello Coello
Pages: 20-35

4. Large-Scale Experimental Evaluation of Cluster Representations for Multiobjective Evolutionary Clustering
Author(s): A. Garcia-Piquer, A. Fornells, J. Bacardit, A. Orriols-Puig, and E. Golobardes
Pages: 36-53

5. A New Multiobjective Evolutionary Algorithm for Mining a Reduced Set of Interesting Positive and Negative Quantitative Association Rules
Author(s): D. Martin, A. Rosete, J. Alcala-Fdez, and F. Herrera
Pages: 54-69

6. Population Classification in Fire Evacuation: A Multiobjective Particle Swarm Optimization Approach
Author(s): Y.-J. Zheng, H.-F. Ling, J.-Y. Xue, and S.-Y. Chen
Pages: 70-81

7. Complex Network Clustering by Multiobjective Discrete Particle Swarm Optimization Based on Decomposition
Author(s): M. Gong, Q. Cai, X. Chen, and L. Ma
Pages: 82-97

8. A Novel Graph-Based Estimation of the Distribution Algorithm and Its Extension Using Reinforcement Learning
Author(s): X. Li, S. Mabu, and K. Hirasawa
Pages: 98-113

9. Adaptive Operator Selection With Bandits for a Multiobjective Evolutionary Algorithm Based on Decomposition
Author(s): K. Li, A. Fialho, S. Kwong, and Q. Zhang
Pages: 114-131

10. Performance Metric Ensemble for Multiobjective Evolutionary Algorithms
Author(s): G. G. Yen, and Z. He
Pages: 131-144

Monday, February 3, 2014

IEEE Transactions on Fuzzy Systems, Volume 22, Number 1 February 2014

1. Observer-Based Adaptive Decentralized Fuzzy Fault-Tolerant Control of Nonlinear Large-Scale Systems With Actuator Failures
Author(s): S. Tong, B. Huo, and Y. Li
Pages: 1-15

2. A New Possibilistic Programming Approach For Solving Fuzzy Multiobjective Assignment Problem
Author(s): P. Gupta and M. K. Mehlawat
Pages: 16-34

3. Consistency Measures for Hesitant Fuzzy Linguistic Preference Relations
Author(s): B. Zhu and Z. Xu
Pages: 35-45

4. Probabilistically Weighted OWA Aggregation
Author(s): R. R. Yager and N. Alajlan
Pages: 46-56

5. The Parameter Reduction of the Interval-Valued Fuzzy Soft Sets and Its Related Algorithms
Author(s): X. Ma, H. Qin, N. Sulaiman, T. Herawan, and J.H. Abawajy
Pages: 57-71

6. EFIS—Evolving Fuzzy Image Segmentation
Author(s): A. A. Othman, H. R. Tizhoosh, and F. Khalvati
Pages: 72-82

7. Some Hamacher Aggregation Operators Based on the Interval-Valued Intuitionistic Fuzzy Numbers and Their Application to Group Decision Making
Author(s): P. Liu
Pages: 83-97

8. Fuzzy Clustering With a Modified MRF Energy Function for Change Detection in Synthetic Aperture Radar Images
Author(s): M.Gong, L.Su, M.Jia, and W.Chen
Pages: 98-109

9. Linguistic Prototypes for Data From Eldercare Residents
Author(s): A. Wilbik, J. M. Keller, and J. C. Bezdek
Pages: 110-123

10. Stability and Stabilization of Discrete-Time T–S Fuzzy Systems With Stochastic Perturbation and Time-Varying Delay
Author(s): X. Yang, L. Wu, H.-K .Lam, and X. Su
Pages: 124-138

11. Fault Detection for T–S Fuzzy Systems With Unknown Membership Functions
Author(s): X.-J. Li and G.-H. Yang
Pages: 139-152

12. Sampled-Data Fuzzy Control of Chaotic Systems Based on a T–S Fuzzy Model
Author(s): Z.-G. Wu, P. Shi, H. Su, and J. Chu
Pages: 153-163

13. Adaptive Fuzzy Robust Output Feedback Control of Nonlinear Systems With Unknown Dead Zones Based on a Small-Gain Approach
Author(s): Y. Li, S. Tong, Y. Liu, and T. Li
Pages: 164-176

14. Amount of Information and Attitudinal-Based Method for Ranking Atanassov’s Intuitionistic Fuzzy Values
Author(s): K. Guo
Pages: 177-188

15. H-∞ Fuzzy Control With Randomly Occurring Infinite Distributed Delays and Channel Fadings
Author(s): S. Zhang, Z. Wang, D. Ding, and H. Shu
Pages: 189-200

16. An Agent-Based Fuzzy Collaborative Intelligence Approach for Precise and Accurate Semiconductor Yield Forecasting
Author(s): T. Chen and Y.-C. Wang
Pages: 201-211

17. On Energy-to-Peak Filtering for Nonuniformly Sampled Nonlinear Systems: A Markovian Jump System Approach
Author(s): H. Zhang, Y. Shi, and J. Wang
Pages: 212-222

18. Stability Analysis of Polynomial-Fuzzy-Model-Based Control Systems With Mismatched Premise Membership Functions
Author(s): H.K. Lam and S.-H. Tsai
Pages: 223-229

19. Comments on “Finite-Time H-∞ Fuzzy Control of Nonlinear Jump Systems With Time Delays Via Dynamic Observer-Based State Feedback”
Author(s): Y. Zhang, C. Liu, and H. R. Karimi
Pages: 230

Monday, January 27, 2014

Neural Networks, Volume 51, March 2014

1. Editorial Board  
Pages IFC

Neuroscience

2. Global Mittag-Leffler stability and synchronization of memristor-based fractional-order neural networks  
Pages: 1-8
Author(s): Jiejie Chen, Zhigang Zeng, Ping Jiang
   

Learning Systems

3. Feature selection and multi-kernel learning for sparse representation on a manifold  
Pages: 9-16
Author(s):Jim Jing-Yan Wang, Halima Bensmail, Xin Gao
   
4. Long-term time series prediction using OP-ELM
Pages: 50-56
Author(s):Alexander Grigorievskiy, Yoan Miche, Anne-Mari Ventelä, Eric Séverin, Amaury Lendasse
   
5. Least Square Fast Learning Network for modeling the combustion efficiency of a 300WM coal-fired boiler
Pages: 57-66
Author(s):Guoqiang Li, Peifeng Niu, Huaibao Wang, Yongchao Liu
   

Mathematical and Computational Analysis

6. Neural network for solving convex quadratic bilevel programming problems 
Pages: 17-25
Author(s):Xing He, Chuandong Li, Tingwen Huang, Chaojie Li
   
7. Stability analysis of switched stochastic neural networks with time-varying delays  
Pages: 39-49
Author(s):Xiaotai Wu, Yang Tang, Wenbing Zhang
   
8. Lagrangian support vector regression via unconstrained convex minimization  
Pages: 67-79
Author(s):S. Balasundaram, Deepak Gupta, Kapil
   
9. Periodicity and global exponential stability of generalized Cohen–Grossberg neural networks with discontinuous activations and mixed delays
Pages: 80-95
Author(s):Dongshu Wang, Lihong Huang
   

Engineering and Applications

10. A generalized analog implementation of piecewise linear neuron models using CCII building blocks  
Pages: 26-38
Author(s):Hamid Soleimani, Arash Ahmadi, Mohammad Bavandpour, Ozra Sharifipoor
   
11. Current Events  
Pages I-II


Monday, January 20, 2014

Friday, January 17, 2014

IEEE Transactions on Neural Networks and Learning Systems, Volume 25, Issue 2, February 2014

1. What Are the Differences Between Bayesian Classifiers and Mutual-Information Classifiers?
Author(s): Bao-Gang Hu
Pages: 249 - 264

2. Multikernel Least Mean Square Algorithm
Author(s): Felipe A. Tobar; Sun-Yuan Kung; Danilo P. Mandic
Pages: 265 - 277

3. Quantum Neural Network-Based EEG Filtering for a Brain-Computer Interface
Author(s): Vaibhav Gandhi; Girijesh Prasad; Damien Coyle; Laxmidhar Behera; Thomas Martin McGinnity
Pages: 278 - 288

4. Multiclass From Binary: Expanding One-Versus-All, One-Versus-One and ECOC-Based Approaches
Author(s): Anderson Rocha; Siome Klein Goldenstein
Pages: 289 - 302

5. Short-Term Load and Wind Power Forecasting Using Neural Network-Based Prediction Intervals
Author(s): Hao Quan; Dipti Srinivasan; Abbas Khosravi
Pages: 303 - 315

6. HRLSim: A High Performance Spiking Neural Network Simulator for GPGPU Clusters
Author(s): Kirill Minkovich; Corey M. Thibeault; Michael John O’Brien; Aleksey Nogin; Youngkwan Cho; Narayan Srinivasa
Pages: 316 - 331

7. Sliding-Mode Control Design for Nonlinear Systems Using Probability Density Function Shaping
Author(s): Yu Liu; Hong Wang; Chaohuan Hou
Pages: 332 - 343

8. Nanophotonic Reservoir Computing With Photonic Crystal Cavities to Generate Periodic Patterns
Author(s): Martin Andre Agnes Fiers; Thomas Van Vaerenbergh; Francis Wyffels; David Verstraeten; Benjamin Schrauwen; Joni Dambre; Peter Bienstman
Pages: 344 - 355

9. Efficient Probabilistic Classification Vector Machine With Incremental Basis Function Selection
Author(s): Huanhuan Chen; Peter Tino; Xin Yao
Pages: 356 - 369

10. Zhang Neural Network for Online Solution of Time-Varying Linear Matrix Inequality Aided With an Equality Conversion
Author(s): Dongsheng Guo; Yunong Zhang
Pages: 370 - 382

11. Robust Pole Assignment for Synthesizing Feedback Control Systems Using Recurrent Neural Networks
Author(s): Xinyi Le; Jun Wang
Pages: 383 - 393

12. Efficient Dual Approach to Distance Metric Learning
Author(s): Chunhua Shen; Junae Kim; Fayao Liu; Lei Wang; Anton van den Hengel
Pages: 394 - 406

13. Event-Based Visual Flow
Author(s): Ryad Benosman; Charles Clercq; Xavier Lagorce; Sio-Hoi Ieng; Chiara Bartolozzi
Pages: 407 - 417

14. Decentralized Stabilization for a Class of Continuous-Time Nonlinear Interconnected Systems Using Online Learning Optimal Control Approach
Author(s): Derong Liu; Ding Wang; Hongliang Li
Pages: 418 - 428

15. Novel Adaptive Strategies for Synchronization of Linearly Coupled Neural Networks With Reaction-Diffusion Terms
Author(s): Jin-Liang Wang; Huai-Ning Wu; Lei Guo
Pages: 429 - 440

Thursday, January 16, 2014

IEEE Transactions on Computational Intelligence and AI in Games, Volume 5, Number 4, December 2013

1. A Survey of Real-Time Strategy Game AI Research and Competition in StarCraft
Author(s): Ontanon, S. ; Synnaeve, G. ; Uriarte, A. ; Richoux, F. ; Churchill, D. ; Preuss, M.
Pages: 293-311

2. Repeated Goofspiel: A Game of Pure Strategy
Author(s):Dror, M. ; Kendall, G.
Pages: 312-324

3. A Heuristic-Based Planner and Improved Controller for a Two-Layered Approach for the Game of Billiards
Author(s):Landry, J.-F. ; Dussault, J.-P. ; Mahey, P.
Pages: 325-336

4. Automated 3-D Animation From Snooker Videos With Information-Theoretical Optimization
Author(s):Jiang, R. ; Parry, M.L. ; Legg, P.A. ; Chung, D.H.S. ; Griffiths, I.W.
Pages: 337-345

5. Incentive Learning in Monte Carlo Tree Search
Author(s):Kao, K.-Y. ; Wu, I-C. ; Yen, S.-J. ; Shan, Y.-C.
Pages: 346-352

Wednesday, January 15, 2014

Wednesday, January 1, 2014

IEEE Transactions on Neural Networks and Learning Systems: Volume 25, Issue 1, January 2014

1. Guest Editorial: Learning in Nonstationary and Evolving Environments
Author(s): Robi Polikar; Cesare Alippi
Pages: 9 - 11

2. COMPOSE: A Semisupervised Learning Framework for Initially Labeled Nonstationary Streaming Data
Author(s): Karl B. Dyer; Robert Capo; Robi Polikar
Pages: 12 - 26

3. Active Learning With Drifting Streaming Data
Author(s): Indre Zliobaite; Albert Bifet; Bernhard Pfahringer; Geoffrey Holmes
Pages: 27 - 39

4. Online Bayesian Learning With Natural Sequential Prior Distribution
Author(s): Yohei Nakada; Makio Wakahara; Takashi Matsumoto
Pages: 40 - 54

5. PANFIS: A Novel Incremental Learning Machine
Author(s): Mahardhika Pratama; Sreenatha. G. Anavatti; Plamen. P. Angelov; Edwin Lughofer
Pages: 55 - 68

6. PCA Feature Extraction for Change Detection in Multidimensional Unlabeled Data
Author(s): Ludmila I. Kuncheva; William J. Faithfull
Pages: 69 - 80

7. Reacting to Different Types of Concept Drift: The Accuracy Updated Ensemble Algorithm
Author(s): Dariusz Brzezinski; Jerzy Stefanowski
Pages: 81 - 94

8. Mining Recurring Concepts in a Dynamic Feature Space
Author(s): Joao Bartolo Gomes; Mohamed Medhat Gaber; Pedro A. C. Sousa; Ernestina Menasalvas
Pages: 95 - 110

9. Dynamic Learning From Adaptive Neural Network Control of a Class of Nonaffine Nonlinear Systems
Author(s): Shi-Lu Dai; Cong Wang; Min Wang
Pages: 111 - 123

10. Learning in the Model Space for Cognitive Fault Diagnosis
Author(s): Huanhuan Chen; Peter Tino; Ali Rodan; Xin Yao
Pages: 124 - 136

11. Adaptive Approximation for Multiple Sensor Fault Detection and Isolation of Nonlinear Uncertain Systems
Author(s): Vasso Reppa; Marios M. Polycarpou; Christos G. Panayiotou
Pages: 137 - 153

12. Dealing With Concept Drifts in Process Mining
Author(s): R. P. Jagadeesh Chandra Bose; Wil M. P. van der Aalst; Indre Zliobaite; Mykola Pechenizkiy
Pages: 154 - 171

13. Adaptive Convex Combination Approach for the Identification of Improper Quaternion Processes
Author(s): Bukhari Che Ujang; Cyrus Jahanchahi; Clive Cheong Took; Danilo P. Mandic
Pages: 172 - 182

14. Developmental Perception of the Self and Action
Author(s): Ryo Saegusa; Giorgio Metta; Giulio Sandini; Lorenzo Natale
Pages: 183 - 202

15. Linguistic Decision Making for Robot Route Learning
Author(s): Hongmei He; Thomas Martin McGinnity; Sonya Coleman; Bryan Gardiner
Pages: 203 - 215

16. An Interval Type-2 Neural Fuzzy Chip With On-Chip Incremental Learning Ability for Time-Varying Data Sequence Prediction and System Control
Author(s): Chia-Feng Juang; Chi-You Chen
Pages: 216 - 228

17. Learning Geotemporal Nonstationary Failure and Recovery of Power Distribution
Author(s): Yun Wei; Chuanyi Ji; Floyd Galvan; Stephen Couvillon; George Orellana; James Momoh
Pages: 229 - 240

18. Continuous Dynamical Combination of Short and Long-Term Forecasts for Nonstationary Time Series
Author(s): Domingos Savio Pereira Salazar; Paulo Jorge Leitao Adeodato; Adrian Lucena Arnaud
Pages: 241 - 246

Monday, December 23, 2013

Neural Networks Volume 50 Pages 1-182 February 2014

Neural Networks Letters

1. Existence and global exponential stability of periodic solution for high-order discrete-time BAM neural networks 
Pages: 98-109
Author(s): Ancai Zhang, Jianlong Qiu, Jinhua She

2. Cellular computational networks—A scalable architecture for learning the dynamics of large networked systems 
Pages: 120-123
Author(s): Bipul Luitel, Ganesh Kumar Venayagamoorthy

Cognitive Science

3. Supervised orthogonal discriminant subspace projects learning for face recognition  
Pages: 33-46
Author(s): Yu Chen, Xiao-Hong Xu

Learning Systems

4. Direct Kernel Perceptron (DKP): Ultra-fast kernel ELM-based classification with non-iterative closed-form weight calculation 
Pages: 60-71
Author(s): Manuel Fernández-Delgado, Eva Cernadas, Senén Barro, Jorge Ribeiro, José Neves

5. Batch gradient method with smoothing image regularization for training of feedforward neural networks  
Pages: 72-78
Author(s): Wei Wu, Qinwei Fan, Jacek M. Zurada, Jian Wang, Dakun Yang, Yan Liu

6. Compressed classification learning with Markov chain samples 
Pages: 90-97
Author(s): Feilong Cao, Tenghui Dai, Yongquan Zhang, Yuanpeng Tan

7. Semi-supervised learning of class balance under class-prior change by distribution matching  
Pages: 110-119
Author(s): Marthinus Christoffel du Plessis, Masashi Sugiyama

8. Robust support vector machine-trained fuzzy system  
Pages: 154-165
Author(s): Yahya Forghani, Hadi Sadoghi Yazdi

9. Large-scale linear nonparallel support vector machine solver  
Pages: 166-174
Author(s): Yingjie Tian, Yuan Ping

10. Finite time convergent learning law for continuous neural networks  
Pages: 175-182
Author(s): Isaac Chairez
   

Mathematical and Computational Analysis

11. A Bayesian inverse solution using independent component analysis  
Pages: 47-59
Author(s): Jouni Puuronen, Aapo Hyvärinen
   
12. A one-layer recurrent neural network for constrained nonsmooth invex optimization  
Pages: 79-89
Author(s): Guocheng Li, Zheng Yan, Jun Wang
   
13. Pointwise probability reinforcements for robust statistical inference  
Pages: 124-141
Author(s): Benoît Frénay, Michel Verleysen
   
14. A linear recurrent kernel online learning algorithm with sparse updates  
Pages: 142-153
Author(s): Haijin Fan, Qing Song

Engineering and Applications

15. Correcting and combining time series forecasters  
Pages: 1-11
Author(s): Paulo Renato A. Firmino, Paulo S.G. de Mattos Neto, Tiago A.E. Ferreira

16. Hybrid fault diagnosis of nonlinear systems using neural parameter estimators 
Pages: 12-32
Author(s): E. Sobhani-Tehrani, H.A. Talebi, K. Khorasani

Thursday, December 19, 2013

Work-Life Balance

A video of a panel session of two young(ish) professors, talking about work-life balance. I used to work in the same lab as Corey Bradshaw, and have even published with him. He is a straight-speaking person who says what he thinks, so you can be sure that what he says in this session is his honest opinion. That being said, I do have some conflicted feelings about this discussion.



On the one hand, I respect and envy their academic achievements. On the other hand, the sacrifices they have made to get where they are are just terrifying, and strike me as selfish. When Tanya Munro talks about dragging her two tiny babies to a conference, or skipping their end-of-year performance, or both of them talking about leaving their kids at home for the evening again, I can't help but think that that is just so much macho bullsh*t. For me, family comes first, there is no choice. My daughter is smart without being conceited, brave without being reckless, strong without being over-bearing, loving, caring and empathetic, without being clingy. She wouldn't be those things if she didn't have an extended family around her who were fully engaged in her upbringing. I'd rather be a "less-successful" academic, than risk losing what I have with her. She'll grow up soon enough, I can put more energy into my career then. Certainly I could achieve more if I sacrificed more, or if I slept a lot less, but if I worked an 80-hour week, I would die. It's as simple as that. One of the last things my father said to me, just a few days before he died, was "you're not a machine". I refuse to risk depriving my wife of her husband and my daughter of her father.

Another point at which I disagree with Corey is when he mentions telling his post-docs "Start publishing papers or I'm going to have to sack you". I think this is a poor management technique: if someone isn't performing, you as a manager must coach them to lift their game. Management by fear is a poor technique and just breeds resentment. Life may be too short to work with a*holes, but it's also too short to accumulate enemies.

The idea that everything you do should lead to an obvious paper is fine for someone who in only doing research, but personally I couldn't live without undergraduate teaching. I need the surge of energy I get from standing in front of a class and explaining complex concepts. I really love it when someone "gets it", when their face lights up with understanding. Even though I spend most of my time now in management, I'd never take another position where I wasn't teaching.

Finally, everyone's circumstances are different, so you shouldn't compare yourself to others. Tanya Munro may have met her husband during her first year of university, but I met my wife at 28, married her just before turning 30, and had my daughter, finished my PhD, and started my first post-doc at 31. I had problems with my PhD topic, I had health problems, and I had to work to support myself. Now I'm 40 and my career path is finally starting to settle down. I may have achieved less academically than them, but so have most people. What, really, does comparing myself to them achieve? Nothing, except perhaps to make me feel badly about myself.

One thing I do agree with is that you have to find your own balance, your own way. I think I've found mine, and I'm happier for it. The video is well worth the time to view it, if only to gain some perspectives from successful academics.

Wednesday, December 18, 2013

WCCI 2014 Deadline Extension

The deadline for submitting papers to the World Congress on Computational Intelligence (WCCI) 2014 has been extended to the 20th of January, 2014. There will be no further extensions. This conference combines the three major conferences of the IEEE Computational Intelligence Society: The International Joint Conference on Neural Networks (IJCNN); the Congress on Evolutionary Computation (CEC) and the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). This conference will be held in Beijing, China, July 6-11, 2014.

Monday, December 16, 2013

Reminder: paper submission deadline for EAIS 2014

A reminder that the deadline for submitting papers to the IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS) 2014 is January 15, 2014. This conference will be held in Linz, Austria, June 2-4, 2014.

Friday, December 13, 2013

Reminder: paper submission deadline for IEEE SSCI 2014

A reminder that the deadline for submitting papers to the IEEE Symposium Series on Computational Intelligence (SSCI) 2014 is 15 June 2014. This group of symposia will be held in Orlando, Florida, 9-12 December, 2014.

Tuesday, December 10, 2013

Call for papers: Special Session for WCCI 2014 "Applications of Computational lntelligence in Ecological Informatics and Environmental Modelling"

Aim

The aim of this special session is to provide a forum for recent research in the application of computational intelligence in the areas of ecological informatics, ecological modelling and environmental modelling.

Ecological informatics and the related field of ecological modelling involve constructing computational models of ecological systems. These models include such things as the distribution or abundance of particular species, models of the interaction between multiple species, and models of the future development of populations. Environmental modelling is closely related and involves constructing models of the physical environment that biological eco-systems inhabit. These models cover such topics as the climate and climate change and the detection of landscape features from geographical data. Models have also been constructed of such environmental topics as waste management systems, water quality and drainage systems and air pollution. As these are highly-complex systems, algorithms from the field of computational intelligence have already been widely applied to modelling this data. Previous work has successfully applied artificial neural networks, fuzzy systems, evolutionary algorithms, support vector machines and combinations of these including neuro-fuzzy and neuro-evolutionary approaches. In each case, computational intelligence methods were shown to be more effective at solving the problem than the alternative methods.

Scope

Topics relevant to this special session include, but are not limited to, the following applications of computational intelligence, including Artificial Neural Networks, Fuzzy Systems, and Evolutionary Algorithms:

•    Species distribution and ecological niche modelling
•    Predicting species abundance
•    Remote sensing image analysis and content-based image retrieval for Ecological Informatics and Environmental Modelling
•    Analysis of species assemblages
•    Issues in the preparation of ecological data for modelling
•    Modelling of pollutants in air, land or water
•    Modelling water quality
•    Predicting the effects of climate change
•    Predicting crop hazards, pests or diseases
•    Identifying landscape features
•    Modelling ecosystem biomass

Deadline

The deadline for submissions to this special session is 20 January 2014.

Information for Authors

1)    Information on the format and templates for papers can be found here:
       http://www.ieee-wcci2014.org/Paper%20Submission.htm
2)    Papers should be submitted via the IJCNN 2014 paper submission site:
       http://ieee-cis.org/conferences/ijcnn2014/upload.php3)
       Select the Special Session name in the Main Research topic dropdown list
4)    Fill out the input fields, upload the PDF file of your paper and finalize your submission by the deadline of December 20, 2013

Organisers

•    Dr Michael J Watts, AIS St Helens, Auckland, New Zealand. mjwatts@ieee.org
•    Associate Professor Russel Pears, Auckland University of Technology, Auckland, New Zealand, russel.pears@aut.ac.nz
•    Professor Jie Yang, Shanghai Jiao Tong University, Shanghai, China, jieyang@sjtu.edu.cn