Monday, June 14, 2021

Complex & Intelligent Systems, Volume 7, issue 3, June 2021

Special Issue: Knowledge fusion intelligent optimization for complex systems

3. Artificial bee colony algorithm based on knowledge fusion
Author(s): Hui Wang, Wenjun Wang...Minyang Xu
Pages: 1139 - 1152

6. Genetic programming with separability detection for symbolic regression
Author(s): Wei-Li Liu, Jiaquan Yang...Shibin Wang
Pages: 1185 - 1194

7. FMCGP: frameshift mutation cartesian genetic programming
Author(s): Wei Fang & Mindan Gu
Pages: 1195 - 1206

8. Solving two-stage stochastic route-planning problem in milliseconds via end-to-end deep learning
Author(s): Jie Zheng, Ling Wang...Jize Pan
Pages: 1207 - 1222

9. Knowledge-guided multiobjective particle swarm optimization with fusion learning strategies
Author(s): Wei Li, Xiang Meng...Soroosh Mahmoodi
Pages: 1223 - 1239

10. Explainable recommendation based on knowledge graph and multi-objective optimization
Author(s): Lijie Xie, Zhaoming Hu...Jinjun Chen
Pages: 1241 - 1252

11. Smart healthcare solutions using the internet of medical things for hand gesture recognition system
Author(s): Nourelhoda M. Mahmoud, Hassan Fouad & Ahmed M. Soliman
Pages: 1253 - 1264

15. Industry 4.0, a revolution that requires technology and national strategies
Author(s): Fengwei Yang & Sai Gu
Pages: 1311 - 1325

16. A comprehensive taxonomy of security and privacy issues in RFID
Author(s): Atul KumarAnkit Kumar JainMohit Dua
Pages: 1327 - 1347

17. A solution algorithm for integrated production-inventory-routing of perishable goods with transshipment and uncertain demand
Author(s): Peide Liu, Ayad Hendalianpour...Mohamad Sadegh Sangari
Pages: 1349 - 1365

18. Attention neural collaboration filtering based on GRU for recommender systems
Author(s): Hongbin Xia, Yang Luo & Yuan Liu
Pages: 1367 - 1379

19. Period-doubling bifurcation analysis and chaos control for load torque using FLC
Author(s): Eman Moustafa, Abdel-Azem Sobaih...Amged Sayed A. Mahmoud
Pages: 1381 - 1389

20. A bi-stage surrogate-assisted hybrid algorithm for expensive optimization problems
Author(s): Zhihai Ren, Chaoli Sun...Shufen Qin
Pages: 1391 - 1405

22. Improved bag-of-features using grey relational analysis for classification of histology images
Author(s): Raju Pal, Mukesh Saraswat & Himanshu Mittal
Pages: 1429 - 1443

23. The electric vehicle routing problem with partial recharge and vehicle recycling
Author(s): Yuzhen Zhou, Jincai Huang...Kuihua Huang
Pages: 1445 - 1458

24. Hexagonal fuzzy approximation of fuzzy numbers and its applications in MCDM
Author(s): V. Lakshmana Gomathi Nayagam & Jagadeeswari Murugan
Pages: 1459 - 1487

25. Hybrid structures applied to ideals in near-rings
Author(s): B. Elavarasan, G. Muhiuddin...Y. B. Jun
Pages: 1489 - 1498

26. Two-stage multi-tasking transform framework for large-scale many-objective optimization problems
Author(s): Lu Chen, Handing Wang & Wenping Ma
Pages: 1499 - 1513

28. Modified artificial bee colony algorithm for solving mixed interval-valued fuzzy shortest path problem
Author(s): Ali Ebrahimnejad, Mohammad Enayattabr...Harish Garg
Pages: 1527 - 1545

29. A holistic FMEA approach by fuzzy-based Bayesian network and best–worst method
Author(s): Melih Yucesan, Muhammet Gul & Erkan Celik
Pages: 1547 - 1564

31. Representation and application of Fuzzy soft sets in type-2 environment
Author(s): Biplab Paik & Shyamal Kumar Mondal
Pages: 1597 - 1617

34. Stance detection using improved whale optimization algorithm
Author(s): Avinash Chandra PandeyVinay Anand Tikkiwal
Pages: 1649 - 1672

36. Interval type-2 fuzzy aggregation operator in decision making and its application
Author(s): M. Lathamaheswari, D. Nagarajan...Said Broumi
Pages: 1695 - 1708

Friday, June 11, 2021

Evolving Systems, Volume 12, issue 2, June 2021

Author(s): Amrita Bhandari & K. C. Tiwari
Pages: 239 - 254

2. Parameter identification of nonlinear system using an improved Lozi map based chaotic optimization algorithm (ILCOA)
Author(s): S. Mohammadreza Ebrahimi, Milad Malekzadeh...S. Hassan HosseinNia
Pages: 255 - 272

4. Self-organized direction aware for regularized fuzzy neural networks
Author(s): Paulo Vitor de Campos Souza, Cristiano,  Fraga Guimaraes Nunes...Vincius Jonathan Silva Arajuo
Pages: 303 - 317

5. An efficient method for classifying motor imagery using CPSO-trained ANFIS prediction
Author(s): M. R. Mosavi, A. Ayatollahi & S. Afrakhteh
Pages: 319 - 336

7. A comparative study of cellular automata-based digital image scrambling techniques
Author(s): Zubair Jeelani & Fasel Qadir
Pages: 359 - 375

8. Evaluation of a dynamic classification method for multimodal ambiguities based on Hidden Markov Models
Author(s): Patrizia Grifoni, Maria Chiara Caschera & Fernando Ferri
Pages: 377 - 395

9. Canny edge detector improvement using an intelligent ants routing
Author(s): Karima Benhamza & Hamid Seridi
Pages: 397 - 406

10. Multitask learning applied to evolving fuzzy-rule-based predictors
Author(s): Amanda O. C. Ayres & Fernando J. Von Zuben
Pages: 407 - 422

11. Partitioning of a manufacturing system into machine cells—a practical application
Author(s): Yusuf Tansel İç, Bekir Volkan Ağca & Mustafa Yurdakul
Pages: 423 - 438

12. Restoration of artwork using deep neural networks
Author(s): Varun Gupta, Nitigya Sambyal,...Praveen Kumar
Pages: 439 - 446

13. Edge detection based on type-1 fuzzy logic and guided smoothening
Author(s): Sahil Raheja & Akshi Kumar
Pages: 447 - 462

14. Oppositional Crow Search Algorithm with mutation operator for global optimization and application in designing FOPID controller
Author(s): Santosh Kumar Majhi, Madhusmita Sahoo & Rosy Pradhan
Pages: 463 - 488

17. Automatic pectoral muscle removal in mammograms
Author(s): Samuel Rahimeto, Taye Girma Debelee...Friedhelm Schwenker
Pages: 519 - 526

19. A new flexible pricing mechanism considering price–quality relation for cloud resource allocation
Author(s): Sepideh Adabi, Fatemeh Alayin & Arash Sharifi
Pages: 541 - 565

20. Chest disease radiography in twofold: using convolutional neural networks and transfer learning
Author(s): Prakash Choudhary & Abhishek Hazra
Pages: 567 - 579

Thursday, June 10, 2021

So little time....

Douglas Adams once said "I love deadlines. I love the whooshing sound they make as they go by".

I used to suck at time-management. I have a real grasshopper mind, that jumps from one topic to another at such a rate that few people can keep up with me and they are flummoxed by the connections that I make between topics. That said, I have come up with a few tricks that allow me to manage my time so that I actually get things done. I still sometimes miss deadlines, but that's more due to workload than lack of time management.

1) Keeping a To-Do list. The most effective To-Do list manager I have ever had is a text file on my desktop called ToDo.txt. Each task is one line. When I complete a task, I delete it from ToDo.txt. That's it. No due-dates, no priorities, no having completed tasks hanging around with when it was completed. I put everything I need to do in this list. Even small tasks, like sending an email to someone, get added to the list if I can't do it straight away.

2) Doing one thing at a time. This is hard to do these days, as distractions are just a mouse click away. But I've lost so much time by starting one task, then another task, and not getting either of them done. So I try to get one specific task done, then start on the next. If something pops up during my pursuit of one task, then I put it on my To-Do list.

3) Get one task done first thing. I try to complete one small task when I arrive at work. This gets me into the mindset of working, and it gives me a psychological boost - no  matter what distractions come my way the rest of the day, at least I've gotten that one thing done. What usually happens, though, is I do that one small thing, then another, then another, and before I know it, I've gotten a lot of things done. This ties in with rule #2, doing one thing at a time.

4) Having more than one project to do. No matter what project I'm working on, there will always come a point when I can't stand to work on it any more. Rather than just sit fuming at my lack of productivity, I switch to another task and work on that instead. I might not be moving forward on the first project, but I'm not being completely unproductive either. This is especially useful when working on papers, as I can never finish writing a paper in one sitting.

5) Getting enough rest. It is very tempting to think that working late, sacrificing sleep for work, means you get a lot done. After all, you can spend eight hours sleeping, and not working, or you can spend four hours sleeping and do an extra four hours work, right? Except those four hours extra late at night are nowhere near as productive as spending one hour the next day doing the same work with a clear mind and energetic body. Lack of sleep is terrible for the human body, it slows your mind down and just ruins your ability to handle complex intellectual tasks. You're much more likely to get sick more often, and how much does that impact your productivity? It's much better to sleep eight hours, then spend eight hours the next day at work, and maybe an hour or so working in the evening. You'll get a lot more done. Sometimes you will need to work late to hit a pressing deadline, but those incidents should be rare.

It can be hard to follow these principles. Life has a habit of getting in the way. But when I do follow them, I get a lot more done and I feel a lot better about myself, because I am being productive.

Friday, May 28, 2021

Bias in AI

When my daughter was a toddler, we bought her a batch of Looney Tunes DVDs. She loved watching Daffy Duck, Porky Pig, and Bugs Bunny. On her third birthday, we gave her a Road Runner DVD. She had her birthday at her grandparents' house, and so that's where she first watched Road Runner, after lunch.

The next time we visited, a couple of weeks later, straight after lunch she got up and walked towards the living room, saying she was going to watch "meep meep". I had to explain to her that that DVD was at home, it didn't stay at Grandma and Grandad's house.

Why did my daughter do that? It's because she had only ever seen Road Runner at Grandma and Grandad's house. In other words, she only had one example of where she could see Road Runner, so that was where she thought she would see it.

A couple of years later I was attending the viva of a PhD student, whose thesis I had examined. The thesis topic was predicting a medical condition from gene expression data. Gene expression was assigned certain values according to how much the gene was active. During the viva, the student made the comment that "expression was measured for those patients who had the condition, and was set to zero for those who did not". I was gobsmacked, as this meant that there were really no gene expression values at all for patients who did not have the condition.

A few years after that I was examining a PhD thesis that used neural networks for earthquake prediction. The central idea was that data from seismographs could be used to predict if an earthquake greater than a certain threshold would occur in the next few days. The data was taken from Canterbury in New Zealand, and started from September 2010, and went for just over a year.

The problem with this of course is that on the 4th of September 2010, the Darfield Earthquake struck Canterbury. The aftershocks continued for more than two years, that is, the length of the data set.

These are all examples of making predictions based on biased data. My daughter had biased data because she had only ever seen Road Runner at her grandparents' house. 

The first student had biased data because there was really only data for one class of patient. They got good results, but that was because they trained a model on biased data then tested it on biased data. Their model would have failed utterly if it had been tested on a different data set.

The second student had biased data because the entire data set was constructed over a time when it was known that there were going to be earthquakes. So again, their model worked well when trained and tested on the data set they had, but it would have failed utterly if tested on a different data set. Hilariously, when I challenged the student on this in their viva, they replied "It's the right kind of bias"! A much better data set would have been one that extended over several years before and after the Darfield Earthquake, and had been taken from different regions. 

While biased models in academic settings might not cause of a lot of harm - other than to examiners' calm - such models are being used in production systems. This seems to be quite a widespread problem as well. It can even have deadly consequences.

Biased data leads to biased models. This is such a simple concept, yet so many people who build AI models don't seem to grasp it. Identifying biased data can be tricky, as it requires a solid understanding of what the data represents, how it was gathered, and what it is to be used for. 

More insidiously, models built with biased data can show very good results. They will train well, and they will test well, as long as the test data is from the data set. That is, as long as the test data is biased, the model will show good test results.

This makes the sourcing and use of an independent testing data set essential. And that is probably the number one thing anyone to do to do avoid bias in AI. It's not foolproof - there might still be systemic biases in the process that generates the data - but it is an essential first step.

Saturday, July 25, 2020

Weekly Review 25 July 2020

Below are some of the interesting links I Tweeted about recently.

  1. Why you shouldn't use the term "quantum neural network":
  2. The annual IEEE list of top ten programming languages is out:
  3. Moving Reinforcement Learning off of high-end servers:
  4. Overview of Recurrent Neural Networks:
  5. Perturbing photos to defeat facial recognition:
  6. A Q&A overview of recommender systems:
  7. The legal problems New Zealand is facing with AI in medicine:
  8. So Facebook is finally looking for racial bias in its AI:
  9. Unsurprisingly, the pandemic has accelerated the adoption of technology, including chatbots:

Monday, June 22, 2020

IEEE Transactions on Cognitive and Developmental Systems; Volume 12, Number 2, June 2020

1. Guest Editorial Special Issue on Multidisciplinary Perspectives on Mechanisms of Language Learning
Author(s): Malte Schilling ; Katharina J. Rohlfing ; Paul Vogt ; Chen Yu ; Michael Spranger
Page(s): 134 - 138

2. An Epigenetic Approach to Semantic Categories
Author(s): Peter Gärdenfors
Page(s): 139 - 147

3. Quantifying the Role of Vocabulary Knowledge in Predicting Future Word Learning
Author(s): Nicole M. Beckage ; Michael C. Mozer ; Eliana Colunga
Page(s): 148 - 159

4. Neurocomputational Models Capture the Effect of Learned Labels on Infants’ Object and Category Representations
Author(s): Arthur Capelier-Mourguy ; Katherine E. Twomey ; Gert Westermann
Page(s): 160 - 168

5. Integrating Image-Based and Knowledge-Based Representation Learning
Author(s): Ruobing Xie ; Stefan Heinrich ; Zhiyuan Liu ; Cornelius Weber ; Yuan Yao ; Stefan Wermter ; Maosong Sun
Page(s): 169 - 178

6. Teach Your Robot Your Language! Trainable Neural Parser for Modeling Human Sentence Processing: Examples for 15 Languages
Author(s): Xavier Hinaut ; Johannes Twiefel
Page(s): 179 - 188

7. The Subject–Object Asymmetry Revisited: Experimental and Computational Approaches to the Role of Information Structure in Children’s Argument Omissions
Author(s): Eileen Graf ; Anna Theakston ; Daniel Freudenthal ; Elena Lieven
Page(s): 189 - 197

8. Social Reinforcement in Artificial Prelinguistic Development: A Study Using Intrinsically Motivated Exploration Architectures
Author(s): Juan M. Acevedo-Valle ; Verena V. Hafner ; Cecilio Angulo
Page(s): 198 - 208

9. Beyond the Self: Using Grounded Affordances to Interpret and Describe Others’ Actions
Author(s): Giovanni Saponaro ; Lorenzo Jamone ; Alexandre Bernardino ; Giampiero Salvi
Page(s): 209 - 221

10. When Object Color Is a Red Herring: Extraneous Perceptual Information Hinders Word Learning via Referent Selection
Author(s): Jessica S. Horst ; Katherine E. Twomey ; Anthony F. Morse ; Rosie Nurse ; Angelo Cangelosi
Page(s): 222 - 231

11. Adults Use Cross-Situational Statistics for Word Learning in a Conservative Way
Author(s): Suzanne Aussems ; Paul Vogt
Page(s): 232 - 242

12. Joint Attention in Hearing Parent–Deaf Child and Hearing Parent–Hearing Child Dyads
Author(s): Heather Bortfeld ; John S. Oghalai
Page(s): 243 - 249

13. Self-Supervised Vision-Based Detection of the Active Speaker as Support for Socially Aware Language Acquisition
Author(s): Kalin Stefanov ; Jonas Beskow ; Giampiero Salvi
Page(s): 250 - 259

14. Multimodal Turn-Taking: Motivations, Methodological Challenges, and Novel Approaches
Author(s): Katharina J. Rohlfing ; Giuseppe Leonardi ; Iris Nomikou ; Joanna Rączaszek-Leonardi ; Eyke Hüllermeier
Page(s): 260 - 271

15. Concrete Action Representation Model: From Neuroscience to Robotics
Author(s): John Nassour ; Tran Duy Hoa ; Payam Atoofi ; Fred Hamker
Page(s): 272 - 284

16. Applying a Psychotherapeutic Theory to the Modeling of Affective Intelligent Agents
Author(s): Yanet Sánchez ; Teresa Coma ; Antonio Aguelo ; Eva Cerezo
Page(s): 285 - 299

17. Interactions With Reconfigurable Modular Robots Enhance Spatial Reasoning Performance
Author(s): Minjing Yu ; Yong-Jin Liu ; Yulin Zhang ; Guozhen Zhao ; Chun Yu ; Yuanchun Shi
Page(s): 300 - 310

18. Facial Expression Recognition via Deep Action Units Graph Network Based on Psychological Mechanism
Author(s): Yang Liu ; Xingming Zhang ; Yubei Lin ; Haoxiang Wang
Page(s): 311 - 322

19. Regression-Based Continuous Driving Fatigue Estimation: Toward Practical Implementation
Author(s): Rohit Bose ; Hongtao Wang ; Andrei Dragomir ; Nitish V. Thakor ; Anastasios Bezerianos ; Junhua Li
Page(s): 323 - 331

20. Perceptual Modeling of Tinnitus Pitch and Loudness
Author(s): Richard Gault ; Thomas Martin McGinnity ; Sonya Coleman
Page(s): 332 - 343

21. Domain Adaptation for EEG Emotion Recognition Based on Latent Representation Similarity
Author(s): Jinpeng Li ; Shuang Qiu ; Changde Du ; Yixin Wang ; Huiguang He
Page(s): 344 - 353

22. Intraindividual Completion Time Modulates the Prediction Error Negativity in a Virtual 3-D Object Selection Task
Author(s): Avinash Kumar Singh ; Hsiang-Ting Chen ; Klaus Gramann ; Chin-Teng Lin
Page(s): 354 - 360

23. A Concealed Information Test System Based on Functional Brain Connectivity and Signal Entropy of Audio–Visual ERP
Author(s): Wenwen Chang ; Hong Wang ; Zhiguo Lu ; Chong Liu
Page(s): 361 - 370

Special Issue on Artificial Intelligence and Edge Computing for Trustworthy Robots and Autonomous Systems
Page(s): 371 - 372

Special Issue on Intrinsically Motivated Open-Ended Learning
Page(s): 373 - 373

Special Issue on Emerging Topics on Development and Learning
Page(s): 374 - 374

Sunday, April 5, 2020

Complex & Intelligent Systems. Volume 6 Number 1, April 2020

1. Trade-off between exploration and exploitation with genetic algorithm using a novel selection operator
Author(s): Abid Hussain, Yousaf Shad Muhammad
Pages: 1-14

2. On some distance measures of complex Pythagorean fuzzy sets and their applications in pattern recognition
Author(s): Kifayat Ullah, Tahir Mahmood, Zeeshan Ali, Naeem Jan
Pages: 15-27

3. Pythagorean Dombi fuzzy graphs
Author(s): Muhammad Akram, Jawaria Mohsan Dar, Sumera Naz
Pages: 29-54

4. Accelerating evolutionary computation using a convergence point estimated by weighted moving vectors
Author(s): Jun Yu, Yuhao Li, Yan Pei, Hideyuki Takagi
Pages: 55-65

5. A new similarity measure for Pythagorean fuzzy sets
Author(s): M. Adabitabar Firozja, B. Agheli, E. Baloui Jamkhaneh
Pages: 67-74

6. Improvement of query-based text summarization using word sense disambiguation
Author(s): Nazreena Rahman, Bhogeswar Borah
Pages: 75-85

7. Towards an assessment framework of reuse: a knowledge-level analysis approach
Author(s): Ghassan Beydoun, Achim Hoffmann, Rafael Valencia Garcia…
Pages: 87-95

8. Moment capacity estimation of spirally reinforced concrete columns using ANFIS
Author(s): Hosein Naderpour, Masoomeh Mirrashid
Pages: 97-107

9. Evaluating the sustainability of a smart technology application to mobile health care: the FGM–ACO–FWA approach
Author(s): Tin-Chih Toly Chen
Pages: 109-121

10. Using compression to find interesting one-dimensional cellular automata
Author(s): Nadim Ahmed, William J. Teahan
Pages: 123-146

11. Collaborative filtering recommendation algorithm based on user correlation and evolutionary clustering
Author(s): Jianrui Chen, Chunxia Zhao, Uliji, Lifang Chen
Pages: 147-156

12. Data-driven decision support under concept drift in streamed big data
Author(s): Jie Lu, Anjin Liu, Yiliao Song, Guangquan Zhang
Pages: 157-163

13. Distributed control system architecture for balancing and stabilizing traffic in the network of multiple autonomous intersections using feedback consensus and route assignment method
Author(s): Chairit Wuthishuwong, Ansgar Traechtler
Pages: 165-187

14. A repository of real-world datasets for data-driven evolutionary multiobjective optimization
Author(s): Cheng He, Ye Tian, Handing Wang, Yaochu Jin
Pages: 189-197

15. High efficiency fault-detection and fault-tolerant control approach in Tennessee Eastman process via fuzzy-based neural network representation
Author(s): M. Adeli, A. H. Mazinan
Pages: 199-212

16. Analysis of watermarking framework for color image through a neural network-based approach
Author(s): M. F. Kazemi, M. A. Pourmina, A. H. Mazinan
Pages: 213-220

Friday, March 27, 2020

IEEE Transactions on Cognitive and Developmental Systems Vol.12, No.1, March 2020

1. A Furcated Visual Collision Avoidance System for an Autonomous Microrobot
Author(s): H. Isakhani, N. Aouf, O. Kechagias-Stamatis and J. F. Whidborne
Pages: 1-11

2. Can the Evidence for Explanatory Reasoning Be Explained Away?
Author(s): I. Douven
Pages: 12-17

3. Cooperative Manipulation for a Mobile Dual-Arm Robot Using Sequences of Dynamic Movement Primitives
Author(s): T. Zhao, M. Deng, Z. Li and Y. Hu
Pages: 18-29

4. Abnormal Event Detection From Videos Using a Two-Stream Recurrent Variational Autoencoder
Author(s): S. Yan, J. S. Smith, W. Lu and B. Zhang
Pages: 30-42

5. Robotic-Assisted Rehabilitation Trainer Improves Balance Function in Stroke Survivors
Author(s): J. Ji, T. Song, S. Guo, F. Xi and H. Wu
Pages: 43-53

6. DeepFeat: A Bottom-Up and Top-Down Saliency Model Based on Deep Features of Convolutional Neural Networks
Author(s): A. Mahdi, J. Qin and G. Crosby
Pages: 54-63

7. Selective Perception as a Mechanism to Adapt Agents to the Environment: An Evolutionary Approach
Author(s): M. Ramicic and A. Bonarini
Pages: 64-72

8. Zero-Shot Classification Based on Multitask Mixed Attribute Relations and Attribute-Specific Features
Author(s): P. Gong, X. Wang, Y. Cheng, Z. J. Wang and Q. Yu
Pages: 73-83

9. Semantic Relational Object Tracking
Author(s): A. Persson, P. Zuidberg Dos Martires, L. De Raedt and A. Loutfi
Pages: 84-97

10. Memory Mechanisms for Discriminative Visual Tracking Algorithms With Deep Neural Networks
Author(s): L. Wang, L. Zhang, J. Wang and Z. Yi
Pages: 98-108

11. Usage-Based Learning in Human Interaction With an Adaptive Virtual Assistant
Author(s): C. Delgrange, J. Dussoux and P. F. Dominey
Pages: 109-123

12. A Brain-Inspired Visual Fear Responses Model for UAV Emergent Obstacle Dodging
Author(s): F. Zhao, Q. Kong, Y. Zeng and B. Xu
Pages: 124-132

IEEE Transactions on Cognitive and Developmental Systems, Vol.11, No.4, Dec. 2019

1. Evaluation of Internal Models in Autonomous Learning
Author(s): S. C. Smith and J. M. Herrmann
Pages: 463-472

2. Anomalous Behaviors Detection in Moving Crowds Based on a Weighted Convolutional Autoencoder-Long Short-Term Memory Network
Author(s): B. Yang, J. Cao, N. Wang and X. Liu
Pages: 473-482

3. A Workload Balanced Algorithm for Task Assignment and Path Planning of Inhomogeneous Autonomous Underwater Vehicle System
Author(s): M. Chen and D. Zhu
Pages: 483-493

4. Symbol Emergence in Cognitive Developmental Systems: A Survey
Author(s): T. Taniguchi et al.
Pages: 494-516

5. Electroencephalogram Emotion Recognition Based on Empirical Mode Decomposition and Optimal Feature Selection
Author(s): Z. Liu, Q. Xie, M. Wu, W. Cao, D. Li and S. Li
Pages: 517-526

6. Brain Teleoperation Control of a Nonholonomic Mobile Robot Using Quadrupole Potential Function
Author(s): W. Yuan and Z. Li
Pages: 527-538

7. Semi-Supervised Learning Based on GAN With Mean and Variance Feature Matching
Author(s): C. Hu, X. Wu and J. Kittler
Pages: 539-547

8. Optimal Control of Eye Movements During Visual Search
Author(s): A. Vasilyev
Pages: 548-559

9. Automatic Pupillary Light Reflex Detection in Eyewear Computing
Author(s): H. K. Wong, J. Epps and S. Chen
Pages: 560-572

10. Multitask Learning for Object Localization With Deep Reinforcement Learning
Author(s): Y. Wang, L. Zhang, L. Wang and Z. Wang
Pages: 573-580

11. Project R-CASTLE: Robotic-Cognitive Adaptive System for Teaching and Learning
Author(s): D. Tozadore et al.
Pages: 581-589

Thursday, March 12, 2020

Evolving Systems, Volume 11, Issue 1, March 2020

1. Optimal static and dynamic transmission network expansion planning
Author(s): Manisha D. Khardenvis, V. N. Pande
Pages: 1-14

2. Heart disease detection using hybrid of bacterial foraging and particle swarm optimization
Author(s): Padmavathi Kora, Ajith Abraham, K Meenakshi
Pages: 15-28

3. An aggregation approach to multi-criteria recommender system using genetic programming
Author(s): Shweta Gupta, Vibhor Kant
Pages: 29-44

4. MFOFLANN: moth flame optimized functional link artificial neural network for prediction of earthquake magnitude
Author(s): Santosh Kumar Majhi, Sk Sajeed Hossain, Trilok Padhi
Pages: 45-63

5. A hybridization of grey wolf optimizer and differential evolution for solving nonlinear systems
Author(s): Mohamed A. Tawhid, Abdelmonem M. Ibrahim
Pages: 65-87

6. Clustering subspace generalization to obtain faster reinforcement learning
Author(s): Maryam Hashemzadeh, Reshad Hosseini, Majid Nili Ahmadabadi
Pages: 89-103

7. Artificial bee colony optimization (ABC) for grape leaves disease detection
Author(s): A. Diana Andrushia, A. Trephena Patricia
Pages: 105-117

8. A novel under sampling strategy for efficient software defect analysis of skewed distributed data
Author(s): K. Nitalaksheswara Rao, Ch. Satyananda Reddy
Pages: 119-131

9. Integrating multiple methods to enhance medical data classification
Author(s): Balasaheb Tarle, Sanjay Chintakindi, Sudarson Jena
Pages: 133-142

10. Survey of deep learning in breast cancer image analysis
Author(s): Taye Girma Debelee, Friedhelm Schwenker, Achim Ibenthal
Pages: 143-163

Monday, March 2, 2020

IEEE Transactions on Neural Networks and Learning Systems, Volume 31, Issue 3, March 2020.

1. Heterogeneous Multilayer Generalized Operational Perceptron
Author(s): Dat Thanh Tran; Serkan Kiranyaz; Moncef Gabbouj; Alexandros Iosifidis
Pages: 710 - 724

2. LABIN: Balanced Min Cut for Large-Scale Data
Author(s): Xiaojun Chen; Renjie Chen; Qingyao Wu; Yixiang Fang; Feiping Nie; Joshua Zhexue Huang
Pages: 725 - 736

3. Adaptive Deep Modeling of Users and Items Using Side Information for Recommendation
Author(s): Jiayu Han; Lei Zheng; Yuanbo Xu; Bangzuo Zhang; Fuzhen Zhuang; Philip S. Yu; Wanli Zuo
Pages: 737 - 748

4. Exactly Robust Kernel Principal Component Analysis
Author(s): Jicong Fan; Tommy W. S. Chow
Pages: 749 - 761

5. Distributed Dissipative State Estimation for Markov Jump Genetic Regulatory Networks Subject to Round-Robin Scheduling
Author(s): Hao Shen; Shicheng Huo; Huaicheng Yan; Ju H. Park; Victor Sreeram
Pages: 762 - 771

6. Compact and Computationally Efficient Representation of Deep Neural Networks
Author(s): Simon Wiedemann; Klaus-Robert Müller; Wojciech Samek
Pages: 772 - 785

7. Discriminative Fisher Embedding Dictionary Learning Algorithm for Object Recognition
Author(s): Zhengming Li; Zheng Zhang; Jie Qin; Zhao Zhang; Ling Shao
Pages: 786 - 800

8. Stability-Based Generalization Analysis of Distributed Learning Algorithms for Big Data
Author(s): Xinxing Wu; Junping Zhang; Fei-Yue Wang
Pages: 801 - 812

9. Recurrent Neural Networks With External Addressable Long-Term and Working Memory for Learning Long-Term Dependences
Author(s): Zhibin Quan; Weili Zeng; Xuelian Li; Yandong Liu; Yunxiu Yu; Wankou Yang
Pages: 813 - 826

10. Log-Sum-Exp Neural Networks and Posynomial Models for Convex and Log-Log-Convex Data
Author(s): Giuseppe C. Calafiore; Stephane Gaubert; Corrado Possieri
Pages: 827 - 838

11. A Robust Visual System for Small Target Motion Detection Against Cluttered Moving Backgrounds
Author(s): Hongxin Wang; Jigen Peng; Xuqiang Zheng; Shigang Yue
Pages: 839 - 853

12. Trajectory Tracking on Uncertain Complex Networks via NN-Based Inverse Optimal Pinning Control
Author(s): Carlos J. Vega; Oscar J. Suarez; Edgar N. Sanchez; Guanrong Chen; Santiago Elvira-Ceja; David I. Rodriguez
Pages: 854 - 864

13. Nonsynaptic Error Backpropagation in Long-Term Cognitive Networks
Author(s): Gonzalo Nápoles; Frank Vanhoenshoven; Rafael Falcon; Koen Vanhoof
Pages: 865 - 875

14. Bipartite Differential Neural Network for Unsupervised Image Change Detection
Author(s): Jia Liu; Maoguo Gong; A. K. Qin; Kay Chen Tan
Pages: 876 - 890

15. A Switched Operation Approach to Sampled-Data Control Stabilization of Fuzzy Memristive Neural Networks With Time-Varying Delay
Author(s): Xin Wang; Ju H. Park; Shouming Zhong; Huilan Yang
Pages: 891 - 900

16. Neural Network-Based Adaptive Antiswing Control of an Underactuated Ship-Mounted Crane With Roll Motions and Input Dead Zones
Author(s): Tong Yang; Ning Sun; He Chen; Yongchun Fang
Pages: 901 - 914

17. Robust and Sparse Linear Discriminant Analysis via an Alternating Direction Method of Multipliers
Author(s): Chun-Na Li; Yuan-Hai Shao; Wotao Yin; Ming-Zeng Liu
Pages: 915 - 926

18. From Whole to Part: Reference-Based Representation for Clustering Categorical Data
Author(s): Qibin Zheng; Xingchun Diao; Jianjun Cao; Yi Liu; Hongmei Li; Junnan Yao; Chen Chang; Guojun Lv
Pages: 927 - 937

19. Cognitive Action Laws: The Case of Visual Features
Author(s): Alessandro Betti; Marco Gori; Stefano Melacci
Pages: 938 - 949

20. Convolutional Neural Networks as Asymmetric Volterra Models Based on Generalized Orthonormal Basis Functions
Author(s): Jeremias B. Machado; Sidney N. Givigi
Pages: 950 - 959

21. Synchronization of the Networked System With Continuous and Impulsive Hybrid Communications
Author(s): Wen Sun; Junxia Guan; Jinhu Lü; Zhigang Zheng; Xinghuo Yu; Shihua Chen
Pages: 960 - 971

22. Adaptive Neural Output-Feedback Decentralized Control for Large-Scale Nonlinear Systems With Stochastic Disturbances
Author(s): Huanqing Wang; Peter Xiaoping Liu; Jialei Bao; Xue-Jun Xie; Shuai Li
Pages: 972 - 983

23. Heterogeneous Domain Adaptation via Nonlinear Matrix Factorization
Author(s): Haoliang Li; Sinno Jialin Pan; Shiqi Wang; Alex C. Kot
Pages: 984 - 996

24. Global Stabilization of Fractional-Order Memristor-Based Neural Networks With Time Delay
Author(s): Jia Jia; Xia Huang; Yuxia Li; Jinde Cao; Ahmed Alsaedi
Pages: 997 - 1009

25. Neural Networks-Based Distributed Adaptive Control of Nonlinear Multiagent Systems
Author(s): Qikun Shen; Peng Shi; Junwu Zhu; Shuoyu Wang; Yan Shi
Pages: 1010 - 1021

26. Constrained Quaternion-Variable Convex Optimization: A Quaternion-Valued Recurrent Neural Network Approach
Author(s): Yang Liu; Yanling Zheng; Jianquan Lu; Jinde Cao; Leszek Rutkowski
Pages: 1022 - 1035

27. Consensus Tracking Control of Switched Stochastic Nonlinear Multiagent Systems via Event-Triggered Strategy
Author(s): Wencheng Zou; Peng Shi; Zhengrong Xiang; Yan Shi
Pages: 1036 - 1045

28. The Robustness of Outputs With Respect to Disturbances for Boolean Control Networks
Author(s): Bowen Li; Yang Liu; Jungang Lou; Jianquan Lu; Jinde Cao
Pages: 1046 - 1051

29. Composite Learning Enhanced Robot Impedance Control
Author(s): Tairen Sun; Liang Peng; Long Cheng; Zeng-Guang Hou; Yongping Pan
Pages: 1052 - 1059

30. Robust Event-Triggered Control Invariance of Probabilistic Boolean Control Networks
Author(s): Lin Lin; Jinde Cao; Leszek Rutkowski
Pages: 1060 - 1065

31. Comments on “Fractional Extreme Value Adaptive Training Method: Fractional Steepest Descent Approach”
Author(s): Abdul Wahab; Shujaat Khan
Pages: 1066 - 1068

10th Joint IEEE International Conference on Development and Learning and Epigenetic Robotics 2020

The paper submission deadline for the 10th Joint IEEE International Conference on Development and Learning and Epigenetic Robotics 2020 is 15 March 2020. This conference will be held in Valparaíso, Chile, 7-10 September, 2020.

2020 IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology

The deadline for submitting papers to the 2020 IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB2020) is 1 May 2020. This conference will be held in Viña del Mar, Chile, October 27-29.

7th IEEE International Conference on Data Science and Advanced Aanlytics 2020

The paper submission deadline for the 7th IEEE International Conference on Data Science and Advanced Analytics (DSAA 2020) is 24 May 2020. This conference will be held in Sydney, Australia, 6-9 October, 2020.

2020 IEEE Symposium Series on Computational Intelligence

The paper submission deadline for the 2020 IEEE Symposium Series on Computational Intelligence is 7 August 2020. This conference will be held in Canberra, Australia, 1-4 December, 2020.