IEEE Transactions on Fuzzy Systems, Volume 24, Issue 5

1. On Pythagorean and Complex Fuzzy Set Operations
Author(s): Scott Dick; Ronald R. Yager; Omolbanin Yazdanbakhsh
Page(s): 1009 - 1021

2. Classification of Type-2 Fuzzy Sets Represented as Sequences of Vertical Slices
Author(s): Lorenzo Livi; Hooman Tahayori; Antonello Rizzi; Alireza Sadeghian; Witold Pedrycz
Page(s): 1022 - 1034

3. Power Average of Trapezoidal Intuitionistic Fuzzy Numbers Using Strict t-Norms and t-Conorms
Author(s): Shu-Ping Wan; Zhi-Hong Yi
Page(s): 1035 - 1047

4. Aperiodic Sampled-Data Sliding-Mode Control of Fuzzy Systems With Communication Delays Via the Event-Triggered Method
Author(s): Shiping Wen; Tingwen Huang; Xinghuo Yu; Michael Z. Q. Chen; Zhigang Zeng
Page(s): 1048 - 1057

5. Fault Detection and Isolation for Affine Fuzzy Systems With Sensor Faults
Author(s): Huimin Wang; Guang-Hong Yang; Dan Ye
Page(s): 1058 - 1071

6. Knowledge Measure for Atanassov's Intuitionistic Fuzzy Sets
Author(s): Kaihong Guo
Page(s): 1072 - 1078

7. Takagi–Sugeno–Kang Transfer Learning Fuzzy Logic System for the Adaptive Recognition of Epileptic Electroencephalogram Signals
Author(s): Changjian Yang; Zhaohong Deng; Kup-Sze Choi; Shitong Wang
Page(s): 1079 - 1094

8. A Survey of Adaptive Fuzzy Controllers: Nonlinearities and Classifications
Author(s): Meng Joo Er; Sayantan Mandal
Page(s): 1095 - 1107

9. Optimal Design of Constraint-Following Control for Fuzzy Mechanical Systems
Author(s): Ruiying Zhao; Ye-Hwa Chen; Shengjie Jiao
Page(s): 1108 - 1120

10. Multiscale Opening of Conjoined Fuzzy Objects: Theory and Applications
Author(s): Punam K. Saha; Subhadip Basu; Eric A. Hoffman
Page(s): 1121 - 1133

11. Decentralized State Feedback Control of Uncertain Affine Fuzzy Large-Scale Systems With Unknown Interconnections
Author(s): Huimin Wang; Guang-Hong Yang
Page(s): 1134 - 1146

12. Fuzzy Adaptive Control With State Observer for a Class of Nonlinear Discrete-Time Systems With Input Constraint
Author(s): Yan-Jun Liu; Shaocheng Tong; Dong-Juan Li; Ying Gao
Page(s): 1147 - 1158

13. Fuzzy-Based Goal Representation Adaptive Dynamic Programming
Author(s): Yufei Tang; Haibo He; Zhen Ni; Xiangnan Zhong; Dongbin Zhao; Xin Xu
Page(s): 1159 - 1175

14. Nonparametric Statistical Active Contour Based on Inclusion Degree of Fuzzy Sets
Author(s): Maoguo Gong; Hao Li; Xiang Zhang; Qiunan Zhao; Bin Wang
Page(s): 1176 - 1192

15. The Role of Crisp Elements in Fuzzy Ontologies: The Case of Fuzzy OWL 2 EL
Author(s): Fernando Bobillo
Page(s): 1193 - 1209

16. Transfer Prototype-Based Fuzzy Clustering
Author(s): Zhaohong Deng; Yizhang Jiang; Fu-Lai Chung; Hisao Ishibuchi; Kup-Sze Choi; Shitong Wang
Page(s): 1210 - 1232

17. Observer-Based Fuzzy Control for Nonlinear Networked Systems Under Unmeasurable Premise Variables
Author(s): Hongyi Li; Chengwei Wu; Shen Yin; Hak-Keung Lam
Page(s): 1233 - 1245

18. Adaptive Fuzzy Hysteresis Internal Model Tracking Control of Piezoelectric Actuators With Nanoscale Application
Author(s): Pengzhi Li; Peiyue Li; Yongxin Sui
Page(s): 1246 - 1254

Neural Networks Volume 83, Pages 1-120, November 2016

1. Simbrain 3.0: A flexible, visually-oriented neural network simulator  
Author(s): Zachary Tosi, Jeffrey Yoshimi
Pages: 1-10

2. Relating observability and compressed sensing of time-varying signals in recurrent linear networks  
Author(s): Mohammad Mehdi Kafashan, Anirban Nandi, ShiNung Ching
Pages: 11-20

3. Rank-based pooling for deep convolutional neural networks  
Author(s): Zenglin Shi, Yangdong Ye, Yunpeng Wu
Pages: 21-31

4. Stability analysis for uncertain switched neural networks with time-varying delay  
Author(s): Wenwen Shen, Zhigang Zeng, Leimin Wang
Pages: 32-41

5. Massively parallel WRNN reconstructors for spectrum recovery in astronomical photometrical surveys  
Author(s): Christian Napoli, Emiliano Tramontana
Pages: 42-50

6. A theory of local learning, the learning channel, and the optimality of backpropagation  
Author(s): Pierre Baldi, Peter Sadowski
Pages: 51-74

7. Approximate Bayesian MLP regularization for regression in the presence of noise  
Author(s): Jung-Guk Park, Sungho Jo
Pages: 75-85

8. Synchronization of Markovian jumping inertial neural networks and its applications in image encryption  
Author(s): M. Prakash, P. Balasubramaniam, S. Lakshmanan
Pages: 86-93

9. Implementation of Imitation Learning using Natural Learner Central Pattern Generator Neural Networks  
Author(s): Hamed Shahbazi, Reyhaneh Parandeh, Kamal Jamshidi
Pages: 94-108

10. Computational analysis of memory capacity in echo state networks  
Author(s): Igor Farkaš, Radomír Bosák, Peter Gergeľ
Pages: 109-120

IEEE Transactions on Neural Networks and Learning Systems, Volume 27, Issue 10, October 2016

1. Why Deep Learning Works: A Manifold Disentanglement Perspective
Author(s): Pratik Prabhanjan Brahma; Dapeng Wu; Yiyuan She
Page(s): 1997 - 2008

2. Feedback Solution to Optimal Switching Problems With Switching Cost
Authors: Ali Heydari
Page(s): 2009 - 2019

3. Geometric Bioinspired Networks for Recognition of 2-D and 3-D Low-Level Structures and Transformations Metrics by Information Projection
Authors: Eduardo Bayro-Corrochano; Eduardo Vazquez-Santacruz; Eduardo Moya-Sanchez; Efrain Castillo-Muñis
Page(s): 2020 - 2034

4. Classifying Stress From Heart Rate Variability Using Salivary Biomarkers as Reference
Authors: Wei Shiung Liew; Manjeevan Seera; Chu Kiong Loo; Einly Lim; Naoyuki Kubota
Page(s): 2035 - 2046

5. Space Structure and Clustering of Categorical Data
Authors: Yuhua Qian; Feijiang Li; Jiye Liang; Bing Liu; Chuangyin Dang
Page(s): 2047 - 2059

6. Kohonen’s Map Approach for the Belief Mass Modeling
Authors: Imen Hammami; Grégoire Mercier; Atef Hamouda; Jean Dezert
Page(s): 2060 - 2071

7. Multiple Ordinal Regression by Maximizing the Sum of Margins
Authors: Onur C. Hamsici; Aleix M. Martinez
Page(s): 2072 - 2083

8. Adaptive Filter Design Using Type-2 Fuzzy Cerebellar Model Articulation Controller
Authors: Chih-Min Lin; Ming-Shu Yang; Fei Chao; Xiao-Min Hu; Jun Zhang
Page(s): 2084 - 2094

9. Directional Clustering Through Matrix Factorization
Authors: Thomas Blumensath
Page(s): 2095 - 2107

10. Learning With Jensen-Tsallis Kernels
Authors: Debarghya Ghoshdastidar; Ajay P. Adsul; Ambedkar Dukkipati
Page(s): 2108 - 2119

11. Tensor LRR and Sparse Coding-Based Subspace Clustering
Authors: Yifan Fu; Junbin Gao; David Tien; Zhouchen Lin; Xia Hong
Page(s): 2120 - 2133

12. Model-Free Optimal Tracking Control via Critic-Only Q-Learning
Authors: Biao Luo; Derong Liu; Tingwen Huang; Ding Wang
Page(s): 2134 - 2144

IEEE Transactions on Cognitive and Developmental Systems, Vol. 8, No. 3, September 2016

1) Emergence of Altruistic Behavior Through the Minimization of Prediction Error
Author(s): Jimmy Baraglia; Yukie Nagai; Minoru Asada
Pages: 141-151

2) Interplay of Rhythmic and Discrete Manipulation Movements During Development: A Policy-Search Reinforcement-Learning Robot Model
Author(s): Valentina Cristina Meola; Daniele Caligiore; Valerio Sperati; Loredana Zollo; Anna Lisa Ciancio; Fabrizio Taffoni; Eugenio Guglielmelli; Gianluca Baldassarre
Pages: 152-170

3) Nonparametric Bayesian Double Articulation Analyzer for Direct Language Acquisition From Continuous Speech Signals
Author(s): Tadahiro Taniguchi; Shogo Nagasaka; Ryo Nakashima
Pages: 171-185

4) Evolutionary Fuzzy Integral-Based Gaze Control With Preference of Human Gaze
Author(s): Bum-Soo Yoo; Jong-Hwan Kim
Pages: 186-200

5) Lifelong Augmentation of Multimodal Streaming Autobiographical Memories
Author(s): Maxime Petit; Tobias Fischer; Yiannis Demiris
Pages: 201-213

6) GRAIL: A Goal-Discovering Robotic Architecture for Intrinsically-Motivated Learning
Author(s): Vieri Giuliano Santucci; Gianluca Baldassarre; Marco Mirolli
Pages: 214-231

Neural Networks Volume 82, Pages: 1-100, October 2016

1) Micro-level dynamics of the online information propagation: A user behavior model based on noisy spiking neurons  
Pages: 1-29
Author(s): Ilias N. Lymperopoulos, George D. Ioannou

2) A new EEG synchronization strength analysis method: S-estimator based normalized weighted-permutation mutual information  
Pages: 30-38
Author(s): Dong Cui, Weiting Pu, Jing Liu, Zhijie Bian, Qiuli Li, Lei Wang, Guanghua Gu

3) Event-triggered image filter design for delayed neural network with quantization  
Pages: 39-48
Author(s): Jinliang Liu, Jia Tang, Shumin Fei

4) Boundedness and convergence analysis of weight elimination for cyclic training of neural networks  
Pages: 49-61
Author(s): Jian Wang, Zhenyun Ye, Weifeng Gao, Jacek M. Zurada

5) A local Vapnik–Chervonenkis complexity  
Pages: 62-75
Author(s): Luca Oneto, Davide Anguita, Sandro Ridella

6) Global oscillation regime change by gated inhibition
Pages: 76-83
Author(s): August Romeo, Hans Supèr

7) Stability analysis of switched cellular neural networks: A mode-dependent average dwell time approach  
Pages: 84-99
Author(s): Chuangxia Huang, Jie Cao, Jinde Cao

IEEE Transactions on Fuzzy Systems, Voume 24, Issue 4, 2016

1. Modeling Fuzzy and Interval Fuzzy Preferences Within a Graph Model Framework
Author(s):  M. Abul Bashar; Amer Obeidi; D. Marc Kilgour; Keith W. Hipel
Page(s):  765- 778

2. Privacy-Protected Facial Biometric Verification Using Fuzzy Forest Learning
Author(s):  Richard Jiang; Ahmed Bouridane; Danny Crookes; M. Emre Celebi; Hua-Liang Wei
Page(s):  779- 790

3. A Novel Adaptive Possibilistic Clustering Algorithm
Author(s):  Spyridoula D. Xenaki; Konstantinos D. Koutroumbas; Athanasios A. Rontogiannis
Page(s):  791- 810

4. On Viewing Fuzzy Measures as Fuzzy Subsets
Author(s):  Ronald R. Yager
Page(s):  811- 818

5. Linear–Quadratic Uncertain Differential Game With Application to Resource Extraction Problem
Author(s):  Xiangfeng Yang; Jinwu Gao
Page(s):  819- 826

6. Distributivity of the Ordinal Sum Implications Over t-Norms and t-Conorms
Author(s):  Yong Su; Wenwen Zong; Hua-Wen Liu
Page(s):  827- 840

7. Hybrid Fuzzy Adaptive Output Feedback Control Design for Uncertain MIMO Nonlinear Systems With Time-Varying Delays and Input Saturation
Author(s):  Yongming Li; Shaocheng Tong; Tieshan Li
Page(s):  841- 853

8. New Formulation for Representing Higher Order TSK Fuzzy Systems
Author(s):  GholamAli Heydari; AliAkbar Gharaveisi; MohammadAli Vali
Page(s):  854- 864

9. Encoding Words Into Normal Interval Type-2 Fuzzy Sets: HM Approach
Author(s):  Minshen Hao; Jerry M. Mendel
Page(s):  865- 879

10. Fuzzy Opinion Networks: A Mathematical Framework for the Evolution of Opinions and Their Uncertainties Across Social Networks
Author(s):  Li-Xin Wang; Jerry M. Mendel
Page(s):  880- 905

11. Fuzzy Observed-Based Adaptive Consensus Tracking Control for Second-Order Multiagent Systems With Heterogeneous Nonlinear Dynamics
Author(s):  C. L. Philip Chen; Chang-E. Ren; Tao Du
Page(s):  906- 915

12. Ensembles of Fuzzy Linear Model Trees for the Identification of Multioutput Systems
Author(s):  Darko Aleksovski; Juš Kocijan; Sašo Džeroski
Page(s):  916- 929

13. Discovering Fuzzy Exception and Anomalous Rules
Author(s):  M. Dolores Ruiz; Daniel Sánchez; Miguel Delgado; Maria J. Martin-Bautista
Page(s):  930- 944

14. M-Estimates of Location for the Robust Central Tendency of Fuzzy Data
Author(s):  Beatriz Sinova; María Ángeles Gil; Stefan Van Aelst
Page(s):  945- 956

15. Evaluating Choquet Integrals Whose Arguments are Probability Distributions
Author(s):  Ronald R. Yager
Page(s):  957- 965

16. Mean-Based Fuzzy Control for a Class of MIMO Robotic Systems
Author(s):  Wei-Yen Wang; Yi-Hsing Chien; Yih-Guang Leu; Chen-Chien Hsu
Page(s):  966- 980

17. On Computing the Edge-Connectivity of an Uncertain Graph
Author(s):  Yuan Gao; Zhongfeng Qin
Page(s):  981- 991

18. On the Use of Fuzzy Constraints in Semisupervised Clustering
Author(s):  Irene Diaz-Valenzuela; M. Amparo Vila; Maria J. Martin-Bautista
Page(s):  992- 999

19. Join and Meet Operations for Type-2 Fuzzy Sets With Nonconvex Secondary Memberships
Author(s):  Gonzalo Ruiz; Hani Hagras; Héctor Pomares; Ignacio Rojas; Humberto Bustince
Page(s):  1000- 1008

IEEE Transactions on Fuzzy Systems, vol. 24, issue 3, 2016

1. Nonfragile  H_{\infty } Fuzzy Filtering With Randomly Occurring Gain Variations and Channel Fadings
Author(s):  Sunjie Zhang ; Zidong Wang ; Derui Ding ; Hongli Dong ; Fuad E. Alsaadi ; Tasawar Hayat
Page(s):  505- 518

2. Chain and Substitution Rules of Intuitionistic Fuzzy Calculus
Author(s):  Qian Lei ; Zeshui Xu
Page(s):  519- 529

3. Extended Fuzzy Logic: Sets and Systems
Author(s):  Farnaz Sabahi ; Mohammad Reza Akbarzadeh-T
Page(s):  530- 543

4. Fuzzy-Model-Based Robust  H_{\infty } Design of Nonlinear Packetized Networked Control Systems
Author(s):  Bin Tang ; Shiguo Peng ; Yun Zhang
Page(s):  544- 557

5. Extensions of Atanassov's Intuitionistic Fuzzy Interaction Bonferroni Means and Their Application to Multiple-Attribute Decision Making
Author(s):  Yingdong He ; Zhen He
Page(s):  558- 573

6. Evolving Type-2 Fuzzy Classifier
Author(s):  Mahardhika Pratama ; Jie Lu ; Guangquan Zhang
Page(s):  574- 589

7. Multicriteria Decision Making With Ordinal/Linguistic Intuitionistic Fuzzy Sets For Mobile Apps
Author(s):  Ronald R. Yager
Page(s):  590- 599

8. Improving Linguistic Pairwise Comparison Consistency via Linguistic Discrete Regions
Author(s):  Hengshan Zhang ; Qinghua Zheng ; Ting Liu ; Zijiang Yang ; Minnan Luo ; Yu Qu
Page(s):  600- 614

9. Law of Large Numbers for Uncertain Random Variables
Author(s):  Kai Yao ; Jinwu Gao
Page(s):  615- 621

10. Output Feedback Direct Adaptive Fuzzy Controller Based on Frequency-Domain Methods
Author(s):  Krzysztof Wiktorowicz
Page(s):  622- 634

11. Stability and Stabilization of Takagi–Sugeno Fuzzy Systems via Sampled-Data and State Quantized Controller
Author(s):  Yajuan Liu ; S. M. Lee
Page(s):  635- 644

12. Parameterizing the Semantics of Fuzzy Attribute Implications by Systems of Isotone Galois Connections
Author(s):  Vilem Vychodil
Page(s):  645- 660

13. Decentralized Sampled-Data Fuzzy Observer Design for Nonlinear Interconnected Systems
Author(s):  Geun Bum Koo ; Jin Bae Park ; Young Hoon Joo
Page(s):  661- 674

14. Robust Stability Analysis and Systematic Design of Single-Input Interval Type-2 Fuzzy Logic Controllers
Author(s):  Tufan Kumbasar
Page(s):  675- 694

15. Rough-Set-Theoretic Fuzzy Cues-Based Object Tracking Under Improved Particle Filter Framework
Author(s):  Pojala Chiranjeevi ; Somnath Sengupta
Page(s):  695- 707

16. Fuzzy Multiobjective Modeling and Optimization for One-Shot Multiattribute Exchanges With Indivisible Demand
Author(s):  Zhong-Zhong Jiang ; Zhi-Ping Fan ; W. H. Ip ; Xiaohong Chen
Page(s):  708- 723

17. Global Fuzzy Adaptive Hierarchical Path Tracking Control of a Mobile Robot With Experimental Validation
Author(s):  Chih-Lyang Hwang ; Wei-Li Fang
Page(s):  724- 740

18. Asymmetric Fuzzy Preference Relations Based on the Generalized Sigmoid Scale and Their Application in Decision Making Involving Risk Appetites
Author(s):  Wei Zhou ; Zeshui Xu
Page(s):  741- 756

19. Possibilistic Functional Dependencies and Their Relationship to Possibility Theory
Author(s):  Sebastian Link ; Henri Prade
Page(s):  757- 763

IEEE Transactions on Neural Networks and Learning Systems: Volume 27, Issue 9, September 2016

1. Near Optimal Event-Triggered Control of Nonlinear Discrete-Time Systems Using Neurodynamic Programming
Author(s): Avimanyu Sahoo; Hao Xu; Sarangapani Jagannathan
Page(s): 1801 - 1815

2. Dynamical Behavior of Delayed Reaction–Diffusion Hopfield Neural Networks Driven by Infinite Dimensional Wiener Processes
Authors: Xiao Liang; Linshan Wang; Yangfan Wang; Ruili Wang
Page(s): 1816 - 1826

3. Semisupervised Support Vector Machines With Tangent Space Intrinsic Manifold RegularizationMetrics by Information Projection
Authors: Shiliang Sun; Xijiong Xie
Page(s): 1827 - 1839

4. Efficient Implementation of the Backpropagation Algorithm in FPGAs and Microcontrollers
Authors: Francisco Ortega-Zamorano; José M. Jerez; Daniel Urda Muñoz; Rafael M. Luque-Baena; Leonardo Franco
Page(s): 1840 - 1850

5. On the Performance of Manhattan Nonnegative Matrix Factorization
Authors: Tongliang Liu; Dacheng Tao
Page(s): 1851 - 1863

6. Sequence Prediction With Sparse Distributed Hyperdimensional Coding Applied to the Analysis of Mobile Phone Use Patterns
Authors: Okko J. Räsänen; Jukka P. Saarinen
Page(s): 1878 - 1889

7. A Granular Self-Organizing Map for Clustering and Gene Selection in Microarray Data
Authors: Shubhra Sankar Ray; Avatharam Ganivada; Sankar K. Pal
Page(s): 1890 - 1906

8. Hierarchical Temporal Memory Based on Spin-Neurons and Resistive Memory for Energy-Efficient Brain-Inspired Computing
Authors: Deliang Fan; Mrigank Sharad; Abhronil Sengupta; Kaushik Roy
Page(s): 1907 - 1919

9. Image Understanding Applications of Lattice Autoassociative Memories
Authors: Manuel Graña; Darya Chyzhyk
Page(s): 1920 - 1932

10. Robust Low-Rank Tensor Recovery With Regularized Redescending M-Estimator
Authors: Yuning Yang; Yunlong Feng; Johan A. K. Suykens
Page(s): 1933 - 1946

11. Oversampling the Minority Class in the Feature Space
Authors: María Pérez-Ortiz; Pedro Antonio Gutiérrez; Peter Tino; César Hervás-Martínez
Page(s): 1947 - 1961

12. Adaptive Neural Control for a Class of Pure-Feedback Nonlinear Systems via Dynamic Surface Technique
Authors: Zongcheng Liu; Xinmin Dong; Jianping Xue; Hongbo Li; Yong Chen
Page(s): 1969 - 1975

13. Intelligent Tracking Control for a Class of Uncertain High-Order Nonlinear Systems
Authors: Xudong Zhao; Peng Shi; Xiaolong Zheng; Jianhua Zhang
Page(s): 1976 - 1982

14. A Derivative-Free Riemannian Powell’s Method, Minimizing Hartley-Entropy-Based ICA Contrast
Authors: Amit Chattopadhyay; Suviseshamuthu Easter Selvan; Umberto Amato
Page(s): 1983 - 1990

15. Feedback Controller Design for the Synchronization of Boolean Control Networks
Authors: Yang Liu; Liangjie Sun; Jianquan Lu; Jinling Liang
Page(s): 1991 - 1996

Evolving Systems, Volume 7, Issue 3

1. A self tuning regulator design for nonlinear time varying systems based on evolving linear models
Author(s): Sina Jahandari, Ahmad Kalhor & Babak Nadjar Araabi
Pages: 159-172

2. A fast online learning algorithm of radial basis function network with locality sensitive hashing
Author(s): Siti Hajar Aminah Ali, Kiminori Fukase & Seiichi Ozawa
Pages: 173-186

3. Maintenance of a Bayesian network: application using medical diagnosis
Author(s): Ahlem Refai, H. F. Merouani & Hayet Aouras
Pages: 187-196

4. Parallelization of filtered back-projection algorithm for computed tomography
Author(s): Akram Boukhamla, Hayet Farida Merouani & Hocine Sissaoui
Pages: 197-205

5. Understanding and modeling the complex dynamics of the online social networks: a scalable conceptual approach
Author(s): Ilias N. Lymperopoulos & George D. Ioannou
Pages: 207-232

Complex & Intelligent Systems Volume 2, Issue 2, June 2016

1. Real-time high-resolution detection approach considering eyes and its states in video frames through intelligence-based representation
Author(s): S. N. Yahyavi, A. H. Mazinan, M. Khademi
Pages:: 75-81

2. FPGA implementation of rule optimization for stand-alone tunable fuzzy logic controller using GA
Author(s): Bhaskara Rao Jammu, Pushpak Pati, S. K. Patra, K. K. Mahapatra
Pages: 83-98

3. Policy control framework-based algorithm for uncertain QoS harmonization in IP-based live video surveillance communications
Author(s): Abhishek Mishra
Pages: 99-110

4. Run-time architectural modeling for future internet applications
Author(s): Marina Mongiello, Simona Colucci, Elvis Vogli, Luigi Alfredo Grieco, Massimo Sciancalepore
Pages: 111-124

5. Prognostics: a literature review
Author(s): Hatem M. Elattar, Hamdy K. Elminir, A. M. Riad
Pages: 125-154

Complex & Intelligent Systems Volume 2, Issue 1, March 2016

1. Bayesian network as an adaptive parameter setting approach for genetic algorithms
Author(s): Guillaume Corriveau, Raynald Guilbault, Antoine Tahahan, Robert Sabourin
Pages: 1-22

2. Emergence in the U.S. Science, Technology, Engineering, and Mathematics (STEM) workforce: an agent-based model of worker attrition and group size in high-density STEM organizations
Author(s): Ronald Iammartino, John Bischoff, Christopher Willy, Paul Shapiro
Pages: 23-34

3. A state equation for the Schelling’s segregation model
Author(s): Jae Kyun Shin, Hiroki Sayama, Seung Ryul Choi
Pages: 35-43

4. Interoperable multi-agent framework for unmanned aerial/ground vehicles: towards robot autonomy
Author(s): Willson Amalraj Arokiasami, Prahlad Vadakkepat, Kay Chen Tan, Dipti Srinivasan
Pages: 45-59

5. Fuzzy radial basis function network for fuzzy regression with fuzzy input and fuzzy output
Author(s): Nimet Yapıcı Pehlivan, Ayşen Apaydın
Pages: 61-73

Weekly Review 8 August 2016

It's been a while since my last review post. This is because I have been away at the ITx conference in Wellington, followed by the WCCI 2016 conference in Vancouver, B.C. Below are some of the interesting links I Tweeted about in the last few weeks.

1. A more and more common story, this is why I went into the private tertiary education sector, better job security: http://www.abc.net.au/radionational/programs/scienceshow/catherine-osborne-how-australia-fails-mid-career-scientists/7588644
2. An overview of Bayesian machine learning: http://www.kdnuggets.com/2016/07/bayesian-machine-learning-explained.html
3. An AI-based VC fund: https://techcrunch.com/2016/07/13/non-artificial-intelligence-please/
4. An improved Turing Test shows how dumb chatbots really are: https://www.technologyreview.com/s/601897/tougher-turing-test-exposes-chatbots-stupidity/
5. A tutorial on machine learning in Python: http://www.datasciencecentral.com/profiles/blogs/would-you-survive-the-titanic-a-guide-to-machine-learning-in
6. An AI that detects hints of depression in speech: http://motherboard.vice.com/en_au/read/machine-learning-algorithm-spots-depression-based-on-speech-patterns
7. The kinds of problems that AI still can't do: http://www.kdnuggets.com/2016/07/hard-problems-ai-cant-yet-touch.html
8. How machine learning is driving artificial intelligence: http://www.datanami.com/2016/07/11/report-machine-learning-driving-ai/
9. Five open-source deep learning projects: http://www.kdnuggets.com/2016/07/five-deep-learning-projects-cant-overlook.html
10. The coming clash between EU regulations and artificial intelligence: http://www.wired.com/2016/07/artificial-intelligence-setting-internet-huge-clash-europe/?utm_content=buffer08177&utm_medium=social&utm_source=facebook.com&utm_campaign=buffer
11. How AI-driven companies like Google depend on public data: https://techcrunch.com/2016/07/09/we-need-to-talk-about-ai-and-access-to-publicly-funded-data-sets/
12. The problems with current chatbots: https://techcrunch.com/2016/07/16/bursting-the-chatbot-bubble/
13. The application of supercomputers in deep learning: http://nextbigfuture.com/2016/07/supercomputers-can-accelerate-machine.html
14. Zoom.ai is launching an AI executive assistant: https://techcrunch.com/2016/07/14/zoom-ai/
15. A list of resources for learning about deep learning: http://www.kdnuggets.com/2016/07/start-learning-deep-learning.html
16. A machine learning based email autoresponder: https://techcrunch.com/2016/07/13/zendesks-automatic-answers-taps-machine-learning-ai-to-generate-bot-style-email-responses/
17. Predicting Game of Thrones betrayals using machine learning: http://dataconomy.com/machine-learning-can-predict-game-of-thrones-betrayals/
18. Ten categories for machine learning and AI algorithms: http://www.kdnuggets.com/2016/07/10-algorithm-categories-data-science.html
19. Helping AI better understand what we are saying to them: https://techcrunch.com/2016/07/15/pat-launches-private-beta-to-help-ai-understand-what-you-say/
20. The AI boom in Silicon Valley: http://www.nytimes.com/2016/07/18/technology/on-wheels-and-wings-artificial-intelligence-swarms-silicon-valley.html?partner=IFTTT&_r=1
21. Good news, 9 mill. people will be liberated from sweatshops by robots-Bad news, 9 mill. people without jobs: https://www.theguardian.com/sustainable-business/2016/jul/16/robot-factories-threaten-jobs-millions-garment-workers-south-east-asia-women
22. Google's using deep learning to optimise the energy efficiency of cooling its server farms: http://www.bloomberg.com/news/articles/2016-07-19/google-cuts-its-giant-electricity-bill-with-deepmind-powered-ai
23. A list of more than 50 machine learning API: http://www.datasciencecentral.com/profiles/blogs/list-of-50-machine-learning-apis
24. How deep learning networks scale: http://www.kdnuggets.com/2016/07/deep-learning-networks-scale.html
25. Using machine learning to manage virtual servers: http://www.datanami.com/2016/08/02/machine-learning-brings-real-insight-jordans-virtual-environment/
26. Google, Microsoft, IBM, Amazon, Facebook are all renting-out access to their AI systems: https://www.technologyreview.com/s/602037/google-and-microsoft-want-every-company-to-scrutinize-you-with-ai/
27. Current developments in deep learning: http://www.datasciencecentral.com/profiles/blogs/on-going-developments-and-outlook-for-deep-learning
28. Yes, AI is just as biased as people, because AI are made by people. That has been obvious for a long time: https://www.theguardian.com/technology/2016/aug/03/algorithm-racist-human-employers-work
29. Diagnosing autism using machine learning: https://www.sciencedaily.com/releases/2016/07/160712142403.htm
30. Why Open Source programming languages are winning over proprietary languages: http://www.techrepublic.com/article/why-open-source-programming-languages-are-crushing-proprietary-peers/ Better to learn R than Matlab?
31. An overview of deep learning neural networks applied to machine translation: https://kv-emptypages.blogspot.co.nz/2016/06/the-emerging-world-of-neural-net-driven.html
32. A commented list of resources explaining NoSQL: http://www.kdnuggets.com/2016/07/seven-steps-understanding-nosql-databases.html
33. A new version of PMML - Predictive Modelling Markup Language - has been released: http://www.kdnuggets.com/2016/08/data-mining-group-pmml-v43.html 
34. Ten simple rules for using statistics properly and effectively: http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004961
35. How to use machine learning for face recognition: https://medium.com/@ageitgey/machine-learning-is-fun-part-4-modern-face-recognition-with-deep-learning-c3cffc121d78#.wlicrwx4j
36. Using machine learning to predict the genetic basis of autism: http://www.natureworldnews.com/articles/26110/20160802/predict-autism-machine-learning.htm
37. Why Harvard Business School is teaching its MBA students about AI: http://www.businessbecause.com/news/full-time-mba/4100/harvard-business-school-is-teaching-mbas-about-ai
38. Two more Google machine learning API are now in open beta: https://www.sdxcentral.com/articles/news/google-clouds-machine-learning-apis-hit-beta/2016/07/
39. Top programming languages for 2016 - Python & R are now numbers 3 & 5, respectively. http://spectrum.ieee.org/static/interactive-the-top-programming-languages-2016?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+IeeeSpectrum+%28IEEE+Spectrum%29&utm_content=FaceBook
40. Detecting sarcasm using a neural network: https://techcrunch.com/2016/08/04/this-neural-network-tries-to-tell-if-youre-being-sarcastic-online/ A lot of people still struggle to detect sarcasm...
41. Developing chatbots for HR: https://www.technologyreview.com/s/602068/the-hr-person-at-your-next-job-may-actually-be-a-bot/ 
42. Will artificial intelligence's ever get common sense? http://www.kdnuggets.com/2016/08/common-sense-artificial-intelligence-2026.html
43. How investors feel about artificial intelligence: http://techemergence.com/how-investors-feel-about-artificial-intelligence-from-29-ai-founders-and-executives/
44. Intelligent security and surveillance systems: http://www.extremetech.com/extreme/232728-when-you-look-at-the-camera-and-it-looks-back-how-artificial-intelligence-is-revolutionizing-home-security
45. OpenAI is calling for an "AI Police" http://www.wired.com/2016/08/openai-calling-techie-cops-battle-code-gone-rogue/?mbid=social_twitter - I seem to remember the "Turing Police" in Neuromancer...
46. Using machine learning to predict crop-yield from satellite images: http://www.theverge.com/2016/8/4/12369494/descartes-artificial-intelligence-crop-predictions-usda 
47. IBM is arguing that AI should be assisting people rather than replacing them: http://www.informationweek.com/government/leadership/ibm-ai-should-stand-for-augmented-intelligence/d/d-id/1326496?
48. Arthur C. Clarke was writing about IA - Intelligence Amplifiers - in 1986: http://www.informationweek.com/government/leadership/ibm-ai-should-stand-for-augmented-intelligence/d/d-id/1326496?
49. Using machine learning to find zero-day exploits on the dark web: https://www.technologyreview.com/s/602115/machine-learning-algorithm-combs-the-darknet-for-zero-day-exploits-and-finds-them/
50. Yahoo has used machine learning to develop a troll-detecting algorithm: http://www.wired.co.uk/article/yahoo-online-abuse-algorithm
51. The paper describing Yahoo's troll-detector: http://www2016.net/proceedings/proceedings/p145.pdf
52. A paper on estimating crop yield from images, this time in China: http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=7524771&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D7524771

IEEE Transactions on Evolutionary Computation, Volume 20, Number 4, August 2016

1. Entropy-Based Termination Criterion for Multiobjective Evolutionary Algorithms
Author(s): Dhish Kumar Saxena ; Arnab Sinha ; João A. Duro ; Qingfu Zhang
Page(s): 485 - 498

2. A Hybrid Multiobjective Memetic Metaheuristic for Multiple Sequence Alignment
Author(s): Álvaro Rubio-Largo ; Miguel A. Vega-Rodríguez ; David L. González-Álvarez
Page(s): 499 - 514

3. An Optimality Theory-Based Proximity Measure for Set-Based Multiobjective Optimization
Author(s): Kalyanmoy Deb ; Mohamed Abouhawwash
Page(s): 515 - 528

4. The Effects of Developer Dynamics on Fitness in an Evolutionary Ecosystem Model of the App Store
Author(s): Soo Ling Lim ; Peter J. Bentley ; Fuyuki Ishikawa
Page(s): 529 - 545

5. Subpermutation-Based Evolutionary Multiobjective Algorithm for Load Restoration in Power Distribution Networks
Author(s): Eduardo Gontijo Carrano ; Gisele P. da Silva ; Edgard P. Cardoso ; Ricardo H. C. Takahashi
Page(s): 546 - 562

6. A Primary Theoretical Study on Decomposition-Based Multiobjective Evolutionary Algorithms
Author(s): Yuan-Long Li ; Yu-Ren Zhou ; Zhi-Hui Zhan ; Jun Zhang
Page(s): 563 - 576

7. Discrete Planar Truss Optimization by Node Position Variation Using Grammatical Evolution
Author(s): Michael Fenton ; Ciaran McNally ; Jonathan Byrne ; Erik Hemberg ; James McDermott ; Michael O’Neill
Page(s): 577 - 589

8. An Adaptive Multipopulation Framework for Locating and Tracking Multiple Optima
Author(s): Changhe Li ; Trung Thanh Nguyen ; Ming Yang ; Michalis Mavrovouniotis ; Shengxiang Yang
Page(s): 590 - 605

9. A Survey on Evolutionary Computation Approaches to Feature Selection
Author(s): Bing Xue ; Mengjie Zhang ; Will N. Browne ; Xin Yao
Page(s): 606 - 626

10. An Enhanced Genetic Algorithm for Ab Initio Protein Structure Prediction
Author(s): Mahmood A. Rashid ; Firas Khatib ; Md Tamjidul Hoque ; Abdul Sattar
Page(s): 627 - 644

IEEE Transactions on Fuzzy Systems, Volume 24, Issue 1, 2016

1. Representing Uncertainty With Information Sets
Author(s):  Manish Aggarwal ; Madasu Hanmandlu
Page(s):  1 - 15

2. Fuzzy Approximation-Based Adaptive Backstepping Optimal Control for a Class of Nonlinear Discrete-Time Systems With Dead-Zone
Author(s):  Yan-Jun Liu ; Ying Gao ; Shaocheng Tong ; Yongming Li
Page(s):  16 - 28

3. Probabilistic Variable Precision Fuzzy Rough Sets
Author(s):  Manish Aggarwal
Page(s):  29 - 39

4. A Survey of Fuzzy Systems Software: Taxonomy, Current Research Trends, and Prospects
Author(s):  Jesús Alcalá-Fdez ; José M. Alonso
Page(s):  40 - 56

5. Adaptive Fuzzy Control of Multilateral Asymmetric Teleoperation for Coordinated Multiple Mobile Manipulators
Author(s):  Di-Hua Zhai ; Yuanqing Xia
Page(s):  57 - 70

6. Learning of Fuzzy Cognitive Maps With Varying Densities Using A Multiobjective Evolutionary Algorithm
Author(s):  Yaxiong Chi ; Jing Liu
Page(s):  71 - 81

7. The Multiplicative Consistency Index of Hesitant Fuzzy Preference Relation
Author(s):  Haifeng Liu ; Zeshui Xu ; Huchang Liao
Page(s):  82 - 93

8. A New Sum-of-Squares Design Framework for Robust Control of Polynomial Fuzzy Systems With Uncertainties
Author(s):  Kazuo Tanaka ; Motoyasu Tanaka ; Ying-Jen Chen ; Hua O. Wang
Page(s):  94 - 110

9. Min-Max Programming Problem Subject to Addition-Min Fuzzy Relation Inequalities
Author(s):  Xiao-Peng Yang ; Xue-Gang Zhou ; Bing-Yuan Cao
Page(s):  111 - 119

10. Design of Fuzzy Cognitive Maps for Modeling Time Series
Author(s):  Witold Pedrycz ; Agnieszka Jastrzebska ; Wladyslaw Homenda
Page(s):  120 - 130

11. A Categorical Isomorphism Between Injective Stratified Fuzzy T_{bm 0} Spaces and Fuzzy Continuous Lattices
Author(s):  Wei Yao
Page(s):  131 - 139

12. Adaptive Fuzzy Control for a Class of Stochastic Pure-Feedback Nonlinear Systems With Unknown Hysteresis
Author(s):  Fang Wang ; Zhi Liu ; Yun Zhang ; C. L. Philip Chen
Page(s):  140 - 152

13. Recurrent Fuzzy Neural Cerebellar Model Articulation Network Fault-Tolerant Control of Six-Phase Permanent Magnet Synchronous Motor Position Servo Drive
Author(s):  Faa-Jeng Lin ; I-Fan Sun ; Kai-Jie Yang ; Jin-Kuan Chang
Page(s):  153 - 167

14. OWA Generation Function and Some Adjustment Methods for OWA Operators With Application
Author(s):  LeSheng Jin ; Gang Qian
Page(s):  168 - 178

15. A Historical Account of Types of Fuzzy Sets and Their Relationships
Author(s):  Humberto Bustince ; Edurne Barrenechea ; Miguel Pagola ; Javier Fernandez ; Zeshui Xu ; Benjamin Bedregal ; Javier Montero ; Hani Hagras ; Francisco Herrera ; Bernard De Baets
Page(s):  179 - 194

16. Fuzzy Membership Descriptors for Images
Author(s):  Mohit Kumar ; Norbert Stoll ; Kerstin Thurow ; Regina Stoll
Page(s):  195 - 207

17. Robust Fuzzy  H_{\infty } Estimator-Based Stabilization Design for Nonlinear Parabolic Partial Differential Systems With Different Boundary Conditions
Author(s):  Shih-Ju Ho ; Bor-Sen Chen
Page(s):  208 - 222

18. Fuzzy Adaptive Output Feedback Fault-Tolerant Tracking Control of a Class of Uncertain Nonlinear Systems With Nonaffine Nonlinear Faults
Author(s):  Yuan-Xin Li ; Guang-Hong Yang
Page(s):  223 - 234

19. Control of Switched Nonlinear Systems via T–S Fuzzy Modeling
Author(s):  Xudong Zhao ; Yunfei Yin ; Lixian Zhang ; Haijiao Yang
Page(s):  235 - 241

20. Ambiguity-Based Multiclass Active Learning
Author(s):  Ran Wang ; Chi-Yin Chow ; Sam Kwong
Page(s):  242 - 248

21. Comments on "Interval Type-2 Fuzzy Sets are Generalization of Interval-Valued Fuzzy Sets: Towards a Wide View on Their Relationship"
Author(s):  Jerry M. Mendel ; Hani Hagras ; Humberto Bustince ; Francisco Herrera
Page(s):  249 - 250

Neural Networks, Volume 81, Pages: 1-102, September 2016

1. Global exponential stability of impulsive complex-valued neural networks with both asynchronous time-varying and continuously distributed delays  
Author(s): Qiankun Song, Huan Yan, Zhenjiang Zhao, Yurong Liu
Pages: 1-10

2. A note on finite-time and fixed-time stability  
Author(s): Wenlian Lu, Xiwei Liu, Tianping Chen
Pages: 11-15

3. Synchronization of fractional-order complex-valued neural networks with time delay  
Author(s): Haibo Bao, Ju H. Park, Jinde Cao
Pages: 16-28

4. Real-time object tracking based on scale-invariant features employing bio-inspired hardware  
Author(s): Shinsuke Yasukawa, Hirotsugu Okuno, Kazuo Ishii, Tetsuya Yagi
Pages: 29-38

5. A neural model of the frontal eye fields with reward-based learning  
Author(s): Weijie Ye, Shenquan Liu, Xuanliang Liu, Yuguo Yu
Pages: 39-51

6. New results on anti-synchronization of switched neural networks with time-varying delays and lag signals  
Author(s): Yuting Cao, Shiping Wen, Michael Z.Q. Chen, Tingwen Huang, Zhigang Zeng
Pages: 52-58

7. Pseudo-inverse linear discriminants for the improvement of overall classification accuracies  
Author(s): Gao Daqi, Dastagir Ahmed, Guo Lili, Wang Zejian, Wang Zhe
Pages: 59-71

8. Neural network training as a dissipative process  
Author(s): Marco Gori, Marco Maggini, Alessandro Rossi
Pages: 72-80

9. Pointwise and uniform approximation by multivariate neural network operators of the max-product type  
Author(s): Danilo Costarelli, Gianluca Vinti
Pages: 81-90

10. Extreme learning machine and adaptive sparse representation for image classification  
Author(s): Jiuwen Cao, Kai Zhang, Minxia Luo, Chun Yin, Xiaoping Lai
Pages: 91-102

IEEE Transactions on Neural Networks and Learning Systems, Volume 27, Issue 8, August 2016

1. Guest Editorial Special Issue on "Neural Networks and Learning Systems Applications in Smart Grid"
Author: Dipti Srinivasan; Ganesh Kumar Venayagamoorthy
Page(s): 1601 - 1603

2. Dynamic State Estimation of Power Systems With Quantization Effects: A Recursive Filter Approach Metrics by Information Projection
Authors: Liang Hu; Zidong Wang; Xiaohui Liu
Page(s): 1604 - 1614

3. Assessing the Influence of an Individual Event in Complex Fault Spreading Network Based on Dynamic Uncertain Causality Graph Metrics by Information Projection
Authors: Chunling Dong; Yue Zhao; Qin Zhang
Page(s): 1615 - 1630

4. Improved Fault Classification in Series Compensated Transmission Line: Comparative Evaluation of Chebyshev Neural Network Training Algorithms
Authors: Bhargav Y. Vyas; Biswarup Das; Rudra Prakash Maheshwari
Page(s): 1631 - 1642

5. Dynamic Energy Management System for a Smart Microgrid
Authors: Ganesh Kumar Venayagamoorthy; Ratnesh K. Sharma; Prajwal K. Gautam; Afshin Ahmadi
Page(s): 1643 - 1656

6. Storage Free Smart Energy Management for Frequency Control in a Diesel-PV-Fuel Cell-Based Hybrid AC Microgrid
Authors: P. C. Sekhar; S. Mishra
Page(s): 1657 - 1671

7. Cooperative Strategy for Optimal Management of Smart Grids by Wavelet RNNs and Cloud Computing
Authors: Christian Napoli; Giuseppe Pappalardo; Giuseppe Marco Tina; Emiliano Tramontana
Page(s): 1672 - 1685

8. Assessing Short-Term Voltage Stability of Electric Power Systems by a Hierarchical Intelligent System
Authors: Yan Xu; Rui Zhang; Junhua Zhao; Zhao Yang Dong; Dianhui Wang; Hongming Yang; Kit Po Wong
Page(s): 1686 - 1696

9. Fair Energy Scheduling for Vehicle-to-Grid Networks Using Adaptive Dynamic Programming
Authors: Shengli Xie; Weifeng Zhong; Kan Xie; Rong Yu; Yan Zhang
Page(s): 1697 - 1707

10. Automatic Learning of Fine Operating Rules for Online Power System Security Control
Authors: Hongbin Sun; Feng Zhao; Hao Wang; Kang Wang; Weiyong Jiang; Qinglai Guo; Boming Zhang; Louis Wehenkel
Page(s): 1708 - 1719

11. Adaptive Portfolio Optimization for Multiple Electricity Markets Participation
Authors: Tiago Pinto; Hugo Morais; Tiago M. Sousa; Tiago Sousa; Zita Vale; Isabel Praça; Ricardo Faia; Eduardo José Solteiro Pires
Page(s): 1720 - 1733

12. Two Machine Learning Approaches for Short-Term Wind Speed Time-Series Prediction
Authors: Ronay Ak; Olga Fink; Enrico Zio
Page(s): 1734 - 1747

13. Online Supplementary ADP Learning Controller Design and Application to Power System Frequency Control With Large-Scale Wind Energy Integration
Authors: Wentao Guo; Feng Liu; Jennie Si; Dawei He; Ronald Harley; Shengwei Mei
Page(s): 1748 - 1761

14. Adaptive Modulation for DFIG and STATCOM With High-Voltage Direct Current Transmission
Authors: Yufei Tang; Haibo He; Zhen Ni; Jinyu Wen; Tingwen Huang
Page(s): 1762 - 1772

15. Machine Learning Methods for Attack Detection in the Smart Grid
Authors: Mete Ozay; Iñaki Esnaola; Fatos Tunay Yarman Vural; Sanjeev R. Kulkarni; H. Vincent Poor
Page(s): 1773 - 1786

16. Smart-Grid Backbone Network Real-Time Delay Reduction via Integer Programming
Authors: Sasikanth Pagadrai; Muhittin Yilmaz; Pratyush Valluri
Page(s): 1787 - 1792

17. A Novel Empirical Mode Decomposition With Support Vector Regression for Wind Speed Forecasting
Authors: Ye Ren; Ponnuthurai Nagaratnam Suganthan; Narasimalu Srikanth
Page(s): 1793 - 1798

Weekly Review 9 July 2016

Some interesting links that I Tweeted about in the last week:

1. Mining emails to identify disgruntled employees: http://fortune.com/insider-threats-email-scout/
2. The origins of Support Vector Machines: http://www.kdnuggets.com/2016/07/guyon-data-mining-history-svm-support-vector-machines.html - gosh, I was in high school in 1989...
3. A robot using deep learning to identify items has won Amazon's robot worker challenge: http://www.techrepublic.com/article/amazons-robot-worker-challenge-won-by-ai-powered-suction-arm/
4. DeepMind is planning to use deep learning to diagnose degenerative eye diseases: https://www.theguardian.com/technology/2016/jul/05/google-deepmind-nhs-machine-learning-blindness
5. Anomaly detection with machine learning: http://www.prcconsulting.net/2016/07/machine-learning-anomaly-detection-finding-a-needle-in-a-haystack/
6. More on DeepMind's project to detect degenerative eye diseases: https://techcrunch.com/2016/07/05/deepmind-partners-with-nhs-eye-hospital-to-conduct-ai-research/
7. A description of Facebook's AI-based multi-language composer - no details of what kind of AI, though: http://www.computerworld.com/article/3090558/social-media/facebook-looks-to-break-language-barriers-with-new-translation-tool.html
8. Can AI predict the next US president? http://www.techrepublic.com/article/election-tech-the-trump-clinton-race-can-ai-forecast-the-winner/
9. Current key trends in AI and machine learning: https://techcrunch.com/2016/07/06/key-trends-in-machine-learning-and-ai/
10. The ideal cloud platforms for machine learning applications: http://www.datanami.com/2016/07/06/seeking-ideal-clouds-ml-workloads/
11. Google buys yet another machine learning startup: http://www.theverge.com/2016/7/6/12105322/google-machine-vision-moodstocks-acquisition
12. How to disconnect from work when you're away from work: http://www.computerworld.com/article/2936764/it-careers/cant-disconnect-on-vacation-these-it-pros-offer-their-hard-earned-tips.html
13. A high-level overview of Support Vector Machines: http://www.kdnuggets.com/2016/07/support-vector-machines-simple-explanation.html
14. How Microsoft plans to out-do Google in AI: http://www.theverge.com/2016/7/7/12111028/microsoft-bot-framework-artificial-intelligence-satya-nadella-interview
15. The four forces shaping AI today: https://www.oreilly.com/ideas/the-four-dynamic-forces-shaping-ai
16. Diagnosing Alzheimer's disease with machine learning: http://medicalxpress.com/news/2016-07-artificial-intelligence-aid-alzheimer-diagnosis.html
17. Modernising PhD examinations: http://www.nature.com/news/what-s-the-point-of-the-phd-thesis-1.20203?WT.mc_id=TWT_NatureNews - I remember I didn't do an oral exam
18. Any model needs to be tested, & the results need to be statistically sound: http://www.techrepublic.com/article/decision-making-algorithms-is-anyone-making-sure-theyre-right/ - see post here: http://computational-intelligence.blogspot.com/2011/11/cargo-cult-statistics.html
19. Computer might get smarts, but they'll never get consciousness: http://www.livemint.com/Opinion/MsbteoWOJMwMQkIQDej4dJ/The-debate-on-artificial-intelligence.html
20. Using AI to improve beer brewing, via a Facebook chatbot: http://www.cnet.com/uk/news/robot-brews-how-ai-could-flavor-your-next-beer/
21. Sounds like Darktrace is using an artificial immune system algorithm to detect network intrusion: http://www.techrepublic.com/article/darktrace-bolsters-machine-learning-based-security-tools-to-automatically-attack-threats/
22. Microsoft open-sources its system for testing AI in Minecraft: http://www.computerworld.com/article/3093413/artificial-intelligence/microsoft-lets-ai-experiments-loose-in-world-of-minecraft.html

Review 12 June - 3 July

I was travelling on business, and got behind on the weekly review posts. Here is a review of the links that I tweeted about over the last three weeks:

1. Facebook's race to catch-up in AI: http://www.fastcompany.com/3060570/facebooks-formula-for-winning-at-ai
2. How AI is making inroads into the legal profession: http://www.thecollegefix.com/post/27773/
3. Google vs Baidu in speech recognition: http://techcrunch.com/2016/06/11/google-baidu-and-the-race-for-an-edge-in-the-global-speech-recognition-market/
4. A philosopher's views on the dangers of artificial intelligence: https://www.theguardian.com/technology/2016/jun/12/nick-bostrom-artificial-intelligence-machine
5. Five ways engineers can improve their writing: http://theinstitute.ieee.org/career-and-education/career-guidance/five-ways-engineers-can-improve-their-writing
6. Dango uses neural networks to recommend emojis: http://motherboard.vice.com/en_au/read/with-dango-app-ai-is-learning-to-meme
7. Watch Sunspring, a sci-fi movie written by an AI: http://techcrunch.com/2016/06/11/watch-this-short-sci-fi-movie-with-a-script-written-by-an-ai/
8. Using machine learning to fight ransomeware: http://www.datanami.com/2016/06/14/machine-learning-enlisted-fight-ransomware/
9. How to select the kernel of a support vector machine: http://www.kdnuggets.com/2016/06/select-support-vector-machine-kernels.html
10. Next step for AI research is how they can learn on their own: http://theinstitute.ieee.org/technology-focus/technology-topic/the-next-step-for-artificial-intelligence-is-machines-that-get-smarter-on-their-own
11. Where machine learning is going to disrupt businesses next: http://tomtunguz.com/key-ingredient-machine-learning/?platform=hootsuite
12. AI have now passed the Turing test for sound: http://www.techrepublic.com/article/how-new-ai-fools-humans-into-thinking-artificial-sounds-are-real/
13. Springboard, Google's enterprise AI assistant: http://techcrunch.com/2016/06/14/google-launches-springboard-an-ai-powered-assistant-for-its-enterprise-customers/
14. Apple is opening-up Siri to third-party developers: http://www.computerworld.com/article/3083149/mac-os-x/apple-touts-a-i-in-ios-and-opens-crown-jewels-to-devs.html - Joining other companies with open AI platforms
15. How to construct parsimonious binary classification trees: http://www.kdnuggets.com/2016/06/breiman-stone-parsimonious-binary-classification-trees.html
16. I think every academic has come across a workplace bully at some time, academia attracts egotistical people: https://www.insidehighered.com/advice/2016/06/15/advice-dealing-bullying-behavior-essay
17. A neural network-based system that turns rough sketches into photorealistic portraits: https://www.technologyreview.com/s/601684/machine-vision-algorithm-learns-to-transform-hand-drawn-sketches-into-photorealistic-images/ Includes link to paper
18. Finding bugs with AI: http://motherboard.vice.com/en_au/read/cyber-grand-challenge The ultimate goal is to patch the bugs, too.
19. Is the future of smartphones a single AI? http://www.theverge.com/2016/6/14/11939310/andy-rubin-google-android-playground-ai-robotics
20. Developing an "ethical" AI that can make life-or-death decisions: http://www.techrepublic.com/article/building-ethical-machines-how-it-can-help-ai-make-life-or-death-decisions/
21. How is AI going to surprise us in the future? http://www.kdnuggets.com/2016/06/how-much-ai-surprise.html
22. Six lessons for getting the best out of machine learning: http://www.techrepublic.com/article/ibm-watson-six-lessons-from-an-early-adopter-on-how-to-do-machine-learning/
23. Using deep learning neural networks for drug discovery: http://scienmag.com/deep-learning-system-for-drug-discovery-to-be-presented-at-the-machine-intelligence-summit-in-berlin/
24. A smart car dashcam that rates everyone else's driving: http://spectrum.ieee.org/cars-that-think/transportation/sensors/the-ai-dashcam-app-that-wants-to-rate-every-driver-in-the-world?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+IeeeSpectrum+%28IEEE+Spectrum%29&utm_content=FaceBook 
25. A concise history of data mining: http://dataconomy.com/history-data-mining/
26. How to get started with mining Twitter data with Python: http://www.kdnuggets.com/2016/06/mining-twitter-data-python-part-1.html
27. A nice overview of the key concepts of machine learning for people who know nothing about it: http://www.techrepublic.com/article/machine-learning-the-smart-persons-guide/
28. Using machine learning to buy advertising: http://www.datasciencecentral.com/profiles/blogs/when-milliseconds-count-using-ai-to-buy-advertising
29. Neural networks and the future of AI: https://techcrunch.com/2016/06/16/neural-networks-artificial-intelligence-and-our-future/
30. Using machine learning to improve performance of power plants: http://www.informationweek.com/iot/ge-uses-machine-learning-to-restore-italian-power-plant/d/d-id/1325918?
31. A basic explanation of how backpropagation works: http://www.kdnuggets.com/2016/06/visual-explanation-backpropagation-algorithm-neural-networks.html
32. Google has opened a dedicated machine learning research lab in Zurich: http://www.informationweek.com/big-data/big-data-analytics/google-launches-ai-machine-learning-research-center-/d/d-id/1325942
33. On the importance of open API for data science: http://www.kdnuggets.com/2016/06/open-api-economy-growth-big-data-analytics.html
34. Analysing sport teams play using machine learning - heading towards an AI coach? http://motherboard.vice.com/en_au/read/coach-bots-nba-ai
35. Student evaluations of lecturers are very blunt instruments, it's not surprising that there is bias in them: https://www.insidehighered.com/advice/2016/06/17/removing-bias-student-evaluations-faculty-members-essay
36. Machine learning for personalised advertising: http://www.pubexec.com/article/the-future-of-marketing-will-be-built-on-personalization-artificial-intelligence/
37. Machine learning libraries in Javascript: http://www.kdnuggets.com/2016/06/top-machine-learning-libraries-javascript.html
38. We're getting close to Sci-Fi levels of AI: http://www.huffingtonpost.com/entry/the-amazing-artificial-intelligence-we-were-promised-is-coming-finally_b_10592674.html?section=india
39. Future trends in AI: http://www.kdnuggets.com/2016/06/machine-learning-trends-future-ai.html
40. Machine learning with Python for complete beginners: http://pythonforengineers.com/machine-learning-for-complete-beginners/
41. A brief, point-by-point history of data mining: http://www.kdnuggets.com/2016/06/rayli-history-data-mining.html
42. A short FAQ on RankBrain, how Google applies deep learning to search: http://searchengineland.com/faq-all-about-the-new-google-rankbrain-algorithm-234440#.V2xDOlIYrKc.twitter
43. Review of deep learning models and applications: http://www.kdnuggets.com/2016/06/review-deep-learning-models.html
44. Generating sculptures with a deep neural network and an EA: http://www.popsci.com/creative-ai-learns-to-sculpt-3d-printable-objects
45. Five myths about machine learning: http://www.forbes.com/sites/teradata/2015/11/13/five-myths-about-machine-learning-you-need-to-know-today/#37831dd2275c
46. According to this article, compliance is the knowledge job most likely to be taken over by AI: https://hbr.org/2016/06/the-knowledge-jobs-most-likely-to-be-automated
47. Identifying NSFW images using machine learning: http://www.kdnuggets.com/2016/06/algorithmia-improving-nudity-detection-nsfw-image-recognition.html
48. How Google is putting machine learning into everything: https://backchannel.com/how-google-is-remaking-itself-as-a-machine-learning-first-company-ada63defcb70#.n1ai2xwao
49. A good argument in favour of all research publications being open-access: http://arstechnica.com/science/2016/06/what-is-open-access-free-sharing-of-all-human-knowledge/
50. The impact of machine-generated screenplays: http://motherboard.vice.com/en_au/read/how-machine-generated-screenplays-may-affect-artists
51. The AI lawyer named Ross has been hired by its first real law firm: http://futurism.com/artificially-intelligent-lawyer-ross-hired-first-official-law-firm/
52. An AI that predicts human actions after being trained on TV programmes: http://www.geekwire.com/2016/computer-binge-watches-tv-predict-ai/
53. Google's suggested rules for AI that prevent AI from becoming harmful: http://www.extremetech.com/extreme/230718-google-researchers-tackle-ai-and-robotics-safety-prevent-future-toasters-from-killing-us-in-our-sleep
54. A cheat-sheet on machine learning algorithms: http://www.datasciencecentral.com/profiles/blogs/the-making-of-a-cheatsheet-emoji-edition
55. Applying cloud-based intelligence to off-the-shelf robots: http://www.theverge.com/circuitbreaker/2016/6/24/12027808/tend-ai-cloud-machine-learning-co-working-robots
56. AI will create jobs as well as destroy jobs - it just won't create as many jobs as it destroys: http://www.informationweek.com/strategic-cio/it-strategy/robots-ai-wont-destroy-jobs-yet/d/d-id/1326056
57. A beginners experiences with deep learning: https://www.theguardian.com/technology/2016/jun/28/google-says-machine-learning-is-the-future-so-i-tried-it-myself
58. Predictions that AI will replace 16 % of white collar jobs by 2025, but create another 9 %: http://www.theregister.co.uk/2016/06/28/forrester_reports_ai_will_create_jobs/
59. An adaptive AI for air combat: http://www.newsmax.com/Newsfront/air-force-ai-top-gun-software/2016/06/27/id/735925/
60. Google has built an AI that picks out the most important parts of an image: https://techcrunch.com/2016/06/28/google-researchers-teach-ais-to-see-the-important-parts-of-images-and-tell-you-about-them/
61. According to the paper, the air combat AI is a genetic-fuzzy system: http://www.omicsgroup.org/journals/genetic-fuzzy-based-artificial-intelligence-for-unmanned-combat-aerialvehicle-control-in-simulated-air-combat-missions-2167-0374-1000144.php?aid=72227 
62. An overview of deep learning: http://www.datasciencecentral.com/profiles/blogs/guide-to-deep-learning
63. Why we need to stop worrying about AI: http://fortune.com/2016/06/28/artificial-intelligence-potential/
64. A list of deep learning libraries in different languages: http://www.datasciencecentral.com/profiles/blogs/deep-learning-libraries-by-language
65. Landing a job in artificial intelligence: http://theinstitute.ieee.org/technology-focus/technology-topic/how-to-land-a-job-in-artificial-intelligence
66. Infographic on the current state of artificial intelligence: http://www.datasciencecentral.com/profiles/blogs/the-state-of-artificial-intelligence-infographic
67. Looking inside convolutional neural networks: http://www.kdnuggets.com/2016/06/peeking-inside-convolutional-neural-networks.html
68. Are journal editors cheating the impact factor measure? https://www.insidehighered.com/views/2016/07/01/examination-whether-academic-journal-rankings-are-being-manipulated-essay
69. Predicting cancer metastasis - seems to be using machine learning of some description: http://www.digitaltrends.com/cool-tech/cancer-spread-prediction-algorithm/
70. I like #4, "don't multi-task". I have to keep reminding myself "one thing at a time!" https://elearningindustry.com/5-ways-survive-student-email-avalanche
71. Although to be honest, it's not an avalanche of email from students that usually takes up my time:   https://elearningindustry.com/5-ways-survive-student-email-avalanche
72. Brief introduction to text mining: http://www.kdnuggets.com/2016/07/text-mining-101-topic-modeling.html
73. Experts' opinions on Satya Nadella's 10 rules for AI: http://www.techrepublic.com/article/ai-experts-weigh-in-on-microsoft-ceos-10-new-rules-for-artificial-intelligence/
74. The promise, and problems, of machine learning in cybersecurity: https://techcrunch.com/2016/07/01/exploiting-machine-learning-in-cybersecurity/
75. Intel is tuning its Xeon Phi chips to make them better suited to machine learning: http://www.computerworld.com/article/3090991/computer-hardware/intel-tunes-its-mega-chip-for-machine-learning.html
76. Satya Nadella calls for accountability in AI, biased systems already exist: https://www.technologyreview.com/s/601812/microsofts-ceo-calls-for-accountable-ai-ignores-the-algorithms-that-already-rule-our-lives/
77. Implementing recursive neural networks in TensorFlow: http://www.kdnuggets.com/2016/06/recursive-neural-networks-tensorflow.html
78. AI can see the world, but it doesn't see the world the same way we do: https://www.technologyreview.com/s/601819/ai-is-learning-to-see-the-world-but-not-the-way-humans-do/