The 16th IEEE International Conference on
Cognitive Informatics & Cognitive Computing
University of Oxford, UK, July 26-28, 2017 http://www.ucalgary.ca/icci_cc2017/
Edited by:
Newton Howard Yingxu Wang Amir Hussain Freddie Hamdy Bernard Widrow Lotfi A. Zadeh
Proceedings of 2017 IEEE 16th International Conference on
Cognitive Informatics & Cognitive Computing ICCI*CC 2017 July 26 – 28, 2017 University of Oxford, UK
Edited by
N. Howard, Y. Wang, A. Hussain, F. Hamdy, B. Widrow and L.A. Zadeh Sponsored by
Los Alamitos, California Washington ● Brussels ● Tokyo
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PREFACE Welcome to the 16th IEEE International Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC’17), a flagship conference in this field, at University of Oxford, UK! Cognitive Informatics (CI) is a transdisciplinary field that studies the internal information processing mechanisms of the brain, the underlying abstract intelligence (I) theories and denotational mathematics, and their engineering applications in cognitive computing, computational intelligence, and cognitive systems. Cognitive Computing (CC) is a cutting-edge paradigm of intelligent computing methodologies and systems based on cognitive informatics, which embodies computational intelligence by autonomous inferences and perceptions mimicking the mechanisms of the brain. CI and CC not only synergize theories of modern information science, computer science, communication theories, AI, cybernetics, computational intelligence, cognitive science, intelligence science, neuropsychology, brain science, systems science, software science, knowledge science, cognitive robots, cognitive linguistics, and life science, but also reveal exciting applications in cognitive computers, cognitive communications, computational intelligence, cognitive robots, cognitive systems, and the AI, IT, and software industries. The IEEE ICCI*CC Series of International Conference has been successfully organized annually since 2002 such as ICCI’02 (University of Calgary, Canada), ICCI’03 (London, UK), ICCI’04 (Victoria, Canada), ICCI’05 (UC Irvine, USA), ICCI’06 (Beijing, China), ICCI’07 (Lake Tahoe, USA), ICCI’08 (Stanford Univ., USA), ICCI’09 (Hong Kong), ICCI’10 (Tsinghua Univ., China), ICCI*CC’11 (Banff, Canada), ICCI*CC’12 (Kyoto, Japan), ICCI*CC’13 (New York, USA), ICCI*CC’14 (London, UK), ICCI*CC’15 (Tsinghua Univ., China) and ICCI*CC’16 (Stanford Univ., USA). ICCI*CC’17 (Univ. of Oxford, UK) focuses on the theme of Neurocomputation, Cognitive Machine Learning and Brain-Inspired Systems towards developing cognitive systems in cognitive informatics, cognitive computing, computational intelligence, and neural informatics. The ICCI*CC’17 technical program encompasses 74 regular papers selected from 256 submissions from more than twenty countries (regions) all over the world. The acceptance rate of ICCI*CC’17 is 28.9% based on rigorous reviews. The program is enriched by 4 invited keynotes and a plenary panel of internationally renowned scientists in cognitive informatics and cognitive computing. The growing field of CI and CC covers transdisciplinary areas such as natural intelligence, abstract intelligence, neuroinformatics, cognitive computing, computational intelligence, cognitive robots/agents, cognitive linguistics, and their engineering applications structured as follows: Cognitive Informatics Informatics models of the brain Cognitive processes of the brain The cognitive foundation of big data Machine consciousness Neuroscience foundations of information processing Denotational mathematics (DM) Cognitive knowledge bases Autonomous machine learning Neural models of memory Internal information processing Cognitive sensors and networks Cognitive linguistics Abstract intelligence (I) Cognitive information theory Cognitive information fusion
Cognitive Computing Cognitive computers Cognitive robotics Autonomous Computing Knowledge processors Cognitive semantics of big data Cognitive machine learning Knowledge manipulations Pattern recognition Cognitive agent technologies Cognitive inferences Computing with words (CWW) Cognitive decision theories Concept & semantic algebras Fuzzy/rough sets/logic Affective computing
Computational Intelligence Cognitive computers Cognitive systems Cognitive man-machine communication Cognitive Internet World-Wide Wisdoms (WWW+) Mathematical engineering for AI Cognitive vehicle systems Semantic computing Distributed intelligence Mathematical models of AI Cognitive signal processing Cognitive image processing Artificial neural nets Genetic computing MATLAB models of AI
Brain Informatics Brain-inspired systems Neuroinformatics Neurological foundations of the brain Computational brain science Software simulations of the brain Brain-system interfaces Neurocomputing eBrain models DNA and genome cognition Computational neurology Brain image processing Bioinformatics System models of the brain Cognitive process models Neurocircuit theories
The ICCI*CC’17 program as presented in the proceedings is the result of great efforts and contributions of many people. We would like to thank all authors who submitted interesting papers to ICCI*CC’17. We appreciate the professional work of the Program Committee, special session organizers, and external reviewers for their effective review and improvement of the quality of submitted papers. We acknowledge the invaluable sponsorships of IEEE Computer Society, IEEE Computational Intelligence Society, International Institute of Cognitive Informatics and Cognitive Computing (ICIC, http://www.ucalgary.ca/icic), The IEEE ICCI*CC Steering Committee, IEEE CS Press, University of Oxford, and University of Calgary. We thank the keynote speakers and distinguished panelists for presenting their visions and insights on fostering the transdisciplinary fields of CI and CC. We acknowledge the organization committee members, particularly Rebecca Howard, Mastuk Ayub and Yousheng Tian, as well as all student volunteers who have helped to make the event a success. General and PC Co-Chairs iii
Conference Organization Honorary Chairs
Lotfi A. Zadeh and Bernard Widrow General Co-Chairs
Freddie Hamdy, Newton Howard and Yingxu Wang Program Committee Co-Chairs
Newton Howard and Amit Hussain Organization Co-Chairs
Rebecca Howard and Yingxu Wang Program Committee Murtagh, Fionn (UK) Nishida, Toyoaki (Japan) Orgun, Mehmet A. (Australia) Patel, Dilip (UK) Patel, Shushma (UK) Pedrycz, Witold (Canada) Pelayo, F. Lopez (Spain) Peng, Jun (China) Petersen, Kirstin (Gernany) Raskin, Victor (USA) Rayz, Julia (USA) Rolls, Edmund (UK) Rubio, Fernando (Spain) Schweikert, Christina (USA) Shel, Duane Sheu, Phillip (USA) Skowron, Andrzej (Poland) Sugawara, Kenji (Japan) Taksa, Isak (USA) Tsai, Jefferey (USA) Tsumoto, Shusaku (Japan) Valdes, Julio J. (Canada) Wang, Yingxu (Canada) Widrow, Bernard (USA) Wood, Sally (USA) Xue, Xiangyang (China) Yarman Vural, Fatos (Turkey) Zanzotto, Fabio (USA) Zhang, Bo (China) Zhang, Du (USA) Zhang, Kaizong (Canada) Zhang, Wen-Ran (USA) Zhong, Yixin (China) Zhu, Haibin (Canada) Zhu, Hong (UK) Zhu, Qingsheng (China)
Altman, Russ (USA) Anderson, James (USA) Baciu, George (Hong Kong) Barthes, Jean-Paul (France) Berwick, Robert C. (USA) Bhavsar, Virendra C. (Canada) Boukadoum, Mounir (Canada) Budin, Gerhard (Austria) Bukovsky, Ivo (Czech) Chan, Christine (Canada) Chan, Keith (Hong Kong) Chen, Liang (Canada) Chen, Shu-Ching (USA) Ferens, Ken (Canada) Fiorini, Rodolfo (Italy) Frieder, Ophir (USA) Fujita, Shigeru (Japan) Gavrilova, Marina (Canada) Guo, Mingyi (China) Howard, Newton (USA) Haykin, Simon (Canada) Howard, Newton (UK) Hsu, D. Frank (USA) Hu, Mou (Canada) Hussain, Amir (UK) Ishizuka, Mitsuru (Japan) Kacprzyk, Janusz (Poland) Kinsner, Witold (Canada) Li, Jianmin (China) Liu, Cheng-Lin (China) Liu, Hongzhi (China) Liu, Jiming (Canada) Lu, Jianhua (China) Luo, Guiming (China) Mizoguchi, Fumio (Japan) Moulin, Claude (France)
Organization Committee
Rebecca Howard, Mustak Ayub, Yousheng Tian, Newton Howard, and Yingxu Wang Additional Reviewers Adeel Ahsan, Nustak Ayub, Basabi Chakraborty, Bin Fu, Jike Ge, Mandar Gogate, Xiaohua Gu, Hsin-Yu Ha, Taku Harada, Tiantian He, Hironori Hiraishi, Yu-An Huang, Zhengshen Jiang, Shangzhu Jin, Shannon Jing, Liang Lei, Zuojin Li, Yi Liu, Summrina Malik, Jose A.G. Martin, Hiroyuki Nishiyama, Hayato Ohwada, Soujanya Poria, Samira Pouyanfar, Maria Presa, Ji Qi, Vitaliy Rayz, Ashraya Shiva, Lepeng Song, Weiping Sun, Haiman Tian, Rui Wang, Siyuan Wang, Yan Wu, Bo Yang, Peipei Yang, Akira Yoshizawa, Omar Zatarain, Mingyang Zhang, Xu-Yao Zhang, Yanming Zhang, Boxu Zhao, Liang Zhewei and Pei-Yuan Zhou
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International Institute of Cognitive Informatics and Cognitive Computing (CI)
http://www.ucalgary.ca/icic
The Steering Committee of IEEE International Conference on Cognitive Informatics and Cognitive Computing (IEEE ICCI*CC)
Name Prof. Wang, Yingxu Prof. Anderson, James Prof. Fariello, Gabriele Prof. Kinsner, Witold Prof. Widrow, Bernard Prof. Nishida, Toyoaki Prof. Patel, Shushma Prof. Zadeh, Lotfi A. Prof. Zhang, Bo
(Chair)
Affiliation Univ. of Calgary Brown University Harvard University University of Manitoba Stanford University Kyoto University London South Bank University University of California, Berkeley Tsinghua University
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Country Canada USA USA Canada USA Japan UK USA China
Table of Contents Preface
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Conference Organization
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Table of Contents
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Keynotes The Power of Cognitive Computing: An Example of Cognitive Dynamic Regional Development Modeling Prof. Janusz Kacprzyk
1 1
Searching in Harsh Environments Prof. Ophir Frieder
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Semantic Computing and Cognitive Computing/Informatics Prof. Phillip Sheu
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Cognitive Foundations of Knowledge Science and Deep Knowledge Learning by Cognitive Robots Prof. Yingxu Wang
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Session A1 - Cognitive Informatics Formal Ontology Generation by Deep Machine Learning Yingxu Wang, Mehrdad Valipour, Omar A. Zatarain, Marina Gavrilova, Amir Hussain, Newton Howard and Shushma Patel
6 6
Extending Reference into Cognitive Computing: Through the Eyes of Ontological Victor Raskin and Libby C. Chernouski
16
Model-based Polynomial Function Approximation with Spiking Neural Networks Stefan Ulbrich, Terrence Steward, Igor Peric, Arne Roennau, Marius Zoellner and Ruediger Dillmann
22
Visualizing the Functional Connectivity of Bilingual and Monolingual Brain during Multitasking Monica Ashokumar, Rosheema Bala J. B., Geethanjali B. and Mahesh Veezhinathan
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Session A2 - Cognitive Computing Cognitive Imaging: Using Knowledge Representation for Reliable Segmentation of MR Angiography Data Julia Rayz, Vitaliy Rayz and Victor Raskin
37 37
Formal Rules for Concept and Semantics Manipulations in Cognitive Linguistics and Machine Learning Yingxu Wang
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Building Semantic Hierarchies of Formal Concepts by Deep Cognitive Machine Mehrdad Valipour and Yingxu Wang
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Cognitive Exploration of Regions through Analyzing Geo-tagged Social Media Data Yunzhe Wang, George Baciu and Chenhui Li
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Session A3 – Cognitive Machine Learning Transfer Learning for Brain Decoding using Deep Architectures Burak Velioglu and Fatos T. Yarman Vural
65 65
Formal Concept Refinement by Deep Cognitive Machine Learning Omar A. Zatarain and Yingxu Wang
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Persian Named Entity Recognition Kia Dashtipour, Mandar Gogate, Ahsan Adeel, Abdulrahman Algarafi, Newton Howard and Amir Hussain
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From Computing with Numbers to Computing with Numeric Words Rodolfo A. Fiorini
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An Improved KNN Text Classification Algorithm based on Simhash Jie Liu, Ting Jin, Kejia Pan, Yi Yang, Yan Wu and Xin Wang
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Session A4 – Affective Computing Class Discovery from Semi-Structured EGG Data for Affective Computing and Personalisation Aladdin Ayesh, Miguel Arevalillo-Herráez and Pablo Arnau-Gonzalez
96 96
Cognitive Modulation of Appraisal Variables in the Emotion Process of Autonomous Agents Sergio Castellanos, Luis-Felipe Rodriguez, Luis A. Castro and Joaquin Pérez
102
Classification of EEG Signal by WT-CNN Model in Emotion Recognition System Benyu Zhang, Huiping Jiang and Linshan Dong
109
Modeling of the Chasing Behaviors for Developmental Program of Children with Autism Spectrum Disorders Airi Tsuji, Satoru Sekine, Takuya Enomoto, Soichiro Matsuda, Junichi Yamamoto and Kenji Suzuki
115
Music Emotions Recognition by Cognitive Classification Methodologies Junjie Bai, Kan Luo, Jun Peng, Jinliang Shi, Ying Wu, Lixiao Feng, Jianqing Li and Yingxu Wang
121
Session A5 – Cognitive Image Processing A Linear Regression Model for Estimating Facial Image Quality Fatema Tuz Zohra, Andrei Dmitri Gavrilov, Omar A. Zatarain and Marina Gavrilova
130 130
Machine Learning based Computer-Aided Diagnosis of Liver Tumours Liaqat Ali, Khaled Khelil, Summrina K. Wajid, Zain U. Hussain, Moiz A. Shah, Adam Howard, Ahsan Adeel, Amir A. Shah, Unnam Sudhakar, Newton Howard and Amir Hussain
139
A Novel Brain Image Processing Method for the Application of Detecting the GBM Disease Patterns in Anatomic Sections of T1-weighted 3D Magnetic Resonance Imaging Peifang Guo and Prabir Bhattacharya
146
Investigations on the Brain Connectivity Patterns in Progression of Alzheimer’s Disease using Functional MR Imaging and Graph Theoretical Measures Bhuvaneshwari Bhaskaran and Kavitha Anandan
151
Session A6 – Brain Informatics and Consciousness Complex-Valued Computational Model of Hippocampus CA3 Recurrent Collaterals Ashraya Samba Shiva, Mandar Gogate, Newton Howard, Bruce Graham and Amir Hussain
161 161
Formulation of Cognitive Skills: A Theoretical Model Based on Psychological and Neuroscience Studies Sadique Ahmad, Kan Li, Yang Li, Humera Qureshi and Siraj Khan
167
The Effects of Typing Demand on Learner’s Motivation/Attitude-Driven Behaviour (MADB) Model with Mouse and Keystroke Behaviours Yee Mei Lim, Aladdin Ayesh and Martin Stacey
175
Exact Spike Timing Computational Model of Convolutional Associative Memories Igor Peric, Felix Schneider, Cameron Price, Stefan Ulbrich, Arne Roennau, Marius Zoellner and Ruediger Dillmann
182
Session A7 – Cognitive Systems (I) Indoor Localization with Occlusion Removal Yushi Li, George Baciu, Yu Han and Chenhui Li
191 191
A Study on Merging Mechanisms of Simple Hopfield Network Models for Building Associative Memory Peter Mungai and Runhe Huang
199
Model Based Formal Design for MVB System Ji Qi and Guiming Luo
207
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NBPMF: Novel Network-Based Inference Methods for Peptide Mass Fingerprinting Zhewei Liang, Gilles Lajoie and Kaizhong Zhang
213
Random Neural Networks based Cognitive Controller for HVAC in Non-Domestic Building using LoRa Abbas Javed, Hadi Larijani, Andrew Wixted and Rohinton Emmanuel
220
Session A8 – Cognitive Linguistics and Semantics Extracting Aspects of Online Reviews: What Can We Make of Text Similarity? Penghao Wang and Julia Rayz
227 227
An Interval Particle Swarm Optimization Algorithm for Numerical Function Optimization Xiaoyu Lin, Yiwen Zhong and Riqing Chen
233
A Fuzzy Ontology for Geography Knowledge of China`s College Entrance Examination Xingyu Chen, Guangping Zeng, Qingchuan Zhang, Liu Chen, Danfeng Wu
237
Question Answering over Knowledgebase with Attention-based LSTM Networks and Knowledge Embeddings Liu Chen, Guangping Zeng, Qingchuan Zhang, Xingyu Chen and Danfeng Wu
243
Session A9 – Brain Informatics A Functional Connectivity based Approach to Visualize the Event Related Changes in Depression through Cognitive Information Processing during Working Memory Tasks V. Ritu, M Keerthana, B Geethanjali and Mahesh Veezhinathan
247 247
Functional Connectivity Assessment for Episodic Memory Functional Connectivity Assessment for Episodic Memory Kapardi Mallampalli and Kavitha A.
257
Early Diagnosis in Mild Cognitive Impairment: A Case Study in Approaches to Inductive Logic Programming Niken Prasasti Martono, Hayato Ohwada and Takehiko Yamaguchi
262
Session B1 – Brain-Inspired Systems Brain-Inspired Systems and Predicative Competence Rodolfo A. Fiorini
268 268
An Engineering Model of the Cognitive Mind Carla V.M. Marques, Carlo E.T. de Oliveira and Cibele R.C. Oliveira
276
(1+1=2) — A Quantum Model of Neurobiology and Cognition Wen-Ran Zhang
283
Adaptive Step Mechanism in Glowworm Swarm Optimization Hong-Bo Wang, Ke-Na Tian, Xue-Na Ren and Xu-Yan Tu
291
Session B2 – Neural Networks and Machine Learning Fractal Based Cognitive Neural Network to Detect Obfuscated and Indistinguishable Internet Threats Sana Siddiqui, Muhammad Salman Khan, Ken Ferens and Witold Kinsner
297 297
Study on Hydrocarbon of Seismic Data Structure Characteristics based on Grey System Thoery Wei Zhou and Haimin Guo
309
A Mathematical and Simulation Model on Stability and Parameters of Multi-equilibrium Points in CNNs Qi Han, Jun Peng, Sk Md Mizanur Rahman, Ahmad Almogren, Atif Alamri, Tengfei Weng and Jin Liu
315
A Cognitive Approach for Attribute Selection in Internet Dataset Danish Kaleem and Ken Ferens
319
Session B3 – Cognitive Vehicles and Self-Driving Route-planning based on a Passenger Condition for Self-driving Vehicles Hironori Hiraishi
329 329
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Common-Sense Approach to Avoid Near-Miss Incidents of Pedestrians Suddenly Crossing Narrow Roads Fumio Mizoguchi, Akira Yoshizawa and Hirotoshi Iwasaki
337
Study of Cognitive Route Search Technique for Self-driving Vehicles Hironori Hiraishi and Fumio MizoguchiHironori Hiraishi and Fumio Mizoguchi
341
Detecting Driver’s Visual Attention Area by using Vehicle-mounted Device Nobuhiro Mizuno, Akira Yoshizawa, Akihiro Hayashi and Takahiro Ishikawa
348
Analysis of Driver’s Visual Attention Using Near-Miss Incident Cases Akira Yoshizawa and Hirotoshi Iwasaki
353
Session B4 - Cognitive Algorithms Combining Multiple Algorithms for Portfolio Management using Combinatorial Fusion Yuxiao Luo, Bruce Kristal, Christina Schweikert and D. Frank Hsu
361 361
The Integrated Loading and Unloading Quay Crane Scheduling Problem by AFSA-GA Algorithm Yi Liu, Sabina Shahbazzade and Jian Wang
367
Influence of Type and Level of Noise on the Performance of an Adaptive Novelty Detector Matous Cejnek and Ivo Bukovsky
373
The Tornadogenesis Optimization Algorithm Ravi Kumar Saidala and Nagaraju Devarakonda
378
A Multi-View Fusion Approach for Entity Alignment Chunxia Zhang, Xiuzhang Yang, Shuliang Wang, Zhendong Niu and Yu Guo
390
Session B5 – Big Data Cognition and Mining A RST-based Stateful Data Analytics Within Spark Jike Ge, Zuqin Chen, Can Liu, Jun Peng Wenbo He, Nan Zhu
394 394
Big Data Processing Framework of Learning Weather Information and Road Traffic Collision using Distributed CEP from CCTV Video: Cognitive Image Processing In Jeong Lee
402
Towards MapReduce Approach with Dynamic Fuzzy Inference/Interpolation for Big Data Classification Problems Shangzhu Jin, Jun Peng and Dong Xie
407
A Computational Cognitive Model for Political Positioning and Reactions in Web Media Eric F. de M. Araujo and Michel Klein
414
Session B6 – Bioinformatics Kinect Gait Skeletal Joint Feature-Based Person Identification Md Wasiur Rahman and Marina Gavrilova
423 423
Estimation of Biomarkers for Autism and its Co-morbidities using Resting State EEG Vishnu P. Kandasamy and Kavitha A.
431
Towards Multimodal Saliency Detection: An Enhancement of Audio-visual Correlation Estimation Antonio Rodríguez-Hidalgo, Carmen Peláez-Moreno and Ascensión Gallardo-Antolín
438
Establishment and Optimization of Human Skin Charge Modeling Lixiao Feng, Dong Xie, Jun Peng, Guorong Chen, Chengyuan Chen and Junjie Bai
444
Session B7 – Computational Intelligence and Applications Two Term Controller Design for Multivariable Linear Time Delay Systems Sonal Singh and Shubhi Purwar
450 450
Identification of Finger Vein using Neural Network Recognition Research Based on PCA
456
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Changlong He, Zuojin Li, Liukui Chen and Jun Peng Application of Artificial Intelligence in Continuous Emission Monitoring System Dedong Tang, Julan Mou, Dong Xie and Xi Tang
461
Self-Powered Intelligent door handle based on Triboelectric Nanogenerator Yiping Deng, Lu Liao, Gang Hu, Junjie Bai, Xiaoyun Zhang, Yuan Zhai, Ying Wu and Guang Zhu
465
Application of PSO LS-SVM Forecasting Model in Oil and Gas Production Forecast Yudeng Qiao, Jun Peng, Lan Ge and Hongjin Wang
470
Session B8 – Cognitive Systems (II) Algorithmic Knowledge Profiles for Introspective Monitoring in Artificial Cognitive Agents Manuel Caro, Adan Gomez and Juan Giraldo
475 475
Design of Information Value Determination Method for Information-Sharing Systems During Large-Scale Disasters Tatsuya Sonobe, Akiko Takahashi and Takuo Suganuma
482
From Standardized Data Formats to Standardized Tools for Optimization Algorithm Benchmarking Thomas Weise
490
Autonomic Computing Meets SCADA Security Sajid Nazir, Shushma Patel and Dilip Patel
498
Session B9 – Hybrid Man-machine Systems Semantic Framework to Enhance Human-Robot Interaction using EKRL Omar Adjali and Amar Ramdane-Cherif
503 503
Construction of Discharge Summaries Classifier Shusaku Tsumoto, Tomohiro Kimura, Haruko Iwata and Shoji Hirano
513
A Cognitive Anti-jamming and Interference-Avoidance Stochastic Game Mohamed A. Aref and Sudharman K. Jayweera
520
Author Index
528
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The Power of Cognitive Computing: An Example of Cognitive Dynamic Regional Development Modeling Janusz Kacprzyk, Fellow, IEEE Full Member, Polish Academy of Sciences Foreign Member, Bulgarian Academy of Sciences Foreign Member, Spanish Royal Academy of Economic and Financial Sciences (RACEF) Systems Research Institute, Polish Academy of Sciences Ul. Newelska 6, 01-447 Warsaw, Poland Email:
[email protected] science, (neuro)psychology, brain science, linguistics, etc. to just mention a few. We try to show on an example of a dynamic systems modeling, more specifically scenario based regional development planning, that cognitive computing can provide new conceptual and implementation vistas. Basically, we consider a region that is characterized by 7 life quality indicators related to economic, social, environmental, etc. qualities, which evolve over some planning horizon due to some investments, mostly by some regional or governmental agencies. There are some scenarios of investment levels over the planning horizon, meant for the development of the particular life quality indexes, and some desired levels of these indexes, both objective, i.e. set by authorities, and subjective, i.e. perceived by the inhabitant groups. As a result of a particular investment scenario, the life quality indexes evolve over the planning horizon, and their temporal evolution is evaluated by the authorities and inhabitants. This evaluation has both an objective, i.e. against the “officially” set thresholds, and subjective, i.e. as perceived by various humans and their groups. Basically, we employ Kacprzyk’s fuzzy dynamic programming based approach to the modeling and planning/programming of sustainable regional development, with soft constraints and goals, but we advocated a more sophisticated assessment of variability, stability, balancedness of consecutive investments. In this process we try to develop evaluation measures, and then the optimization type model using concepts that can be effectively and efficiently handled by cognitive computing, notably the inclusion of the so called decision making and behavioral biases, biases in probability and belief, social biases, memory errors, etc. Moreover, we strongly reflect the so called status quo and minimal change biases. By using many results from social sciences, psychology, behavioral economics, neuroeconomics, etc. on human judgments and human centric evaluations, we augment a traditional purely effectiveness and efficiency oriented analysis by a more sophisticated analysis of effects of variability of temporal evolution of some life quality indicators on the human perception of its goodness. The model presented, which has been employed for years as part of large mathematical modeling projects for sustainable regional development in many regions in Asia
Abstract This presentation concerns some idea of what could be done, in the author’s view, to help make Wang’s cognitive informatics a powerful and viable source of tools and techniques for solving various real life problems. First, we give a brief account of cognitive informatics meant as a multidisciplinary field within informatics, or computer science, that is based on results of cognitive and information sciences, and which deals with human information processing mechanisms and processes and their decision theoretic, engineering, etc. applications in broadly perceived computing. We focus on its purpose, i.e. to develop and implement technologies to facilitate and extend the information acquisition, comprehension and processing capacity of humans. Emphasis is on underlying processes in the brain. However, we advocate an extended approach in which though the very cognitive informatics is the foundation, as those processes in the brain are crucial, some sort of an “outer” cognitive informatics is needed which explicitly makes reference not what proceeds “internally” in the brain, because we do not “see” this, but “externally”, i.e. what people can see, judge, evaluate, etc., and what is clearly a result of cognitive information specific processes in the brain. This line of reasoning is in line with the very essence of comprehension, memorizing, learning, choice and decision making, satisfaction with partial truth, allowing for not perfect solutions, etc. dealt with using tools and techniques derived from many areas like psychology, behavioral science, neuroscience, artificial intelligence, linguistics, neuroeconomics etc. In our case, we will concentrate on some cognitive informatics type elements that mostly have been inspired by psychology and behavioral sciences, as our problem is inherently related to human judgments and perceptions, but we will mentioned some inspirations from neuroscience, notably along the lines of neuroeconomics. Cognitive informatics constitutes a foundation of its related new field, cognitive computing, which is basically a new direction in broadly perceived intelligent computing and systems that synergistically combines results from many areas, e.g., information science, computational sciences, computer science, artificial and computational intelligence, cybernetics, systems science, cognitive
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and Europe, is illustrated on an example with scenario analysis for a rural region plagued by social and economic difficulties in which subsidies should properly be distributed over time to obtain a best overall socioeconomic effect. In this talk we present the model in a different perspective, based first on the basic Wang’s cognitive informatics and its Wang and Ruhe’s decision making application, and then based on new, more comprehensive cognitive computing. We show that this provides a novel insight.
He has been a frequent visiting professor in the USA, Italy, UK, Mexico, China, and Austria. He has been a member of evaluation commissions of many foreign universities. His main research interests include the use of modern computation computational and artificial intelligence tools, notably fuzzy logic, in decisions, optimization, control, data analysis and data mining, with applications in databases, ICT, mobile robotics, systems modeling etc. He authored 6 books, (co)edited more than 100 volumes, (co)authored ca. 550 papers, including ca. 80 in journals indexed by the WoS. His bibliographic data are: due to Google Scholar - citations: 21563; h-index: 66, due to Scopus: citations: 5498; h-index: 33; due to WoS: citation: 5297, h-index: 32. He is the editor in chief of 6 book series at Springer, and of 2 journals, and is on the editorial boards of ca. 40 journals. He is a member of the IEEE CIS Fellows Committee, was Chair of 2016 IEEE CIS Award Committee, was in 2011 – 2016 a member of Adcom of IEEE CIS, and was a Distinguished Lecturer of IEEE CIS. He received many awards: 2006 IEEE CIS Pioneer Award in Fuzzy Systems, 2006 Sixth Kaufmann Prize and Gold Medal for pioneering works on soft computing in economics and management, 2007 Pioneer Award of the Silicon Valley Section of IEEE CIS for contribution in granular computing and computing in words, 2010 Award of the Polish Neural Network Society for exceptional contributions to the Polish computational intelligence community, IFSA 2013 Award for his lifetime achievements in fuzzy systems and service to the fuzzy community, and the 2014 World Automation Congress Lifetime Award for contributions in soft computing, the 2016 Award of the International Neural Network Society – Indian Chapter for Outstanding Contributions to Computational Intelligence. He is President of the Polish Operational and Systems Research Society and Past President of International Fuzzy Systems Association.
ABOUT THE KEYNOTE SPEAKER Janusz Kacprzyk graduated from Warsaw University of Technology, Poland, with M.Sc. in automatic control and computer science, obtained in 1977 Ph.D. in systems analysis and in 1991 D.Sc. in computer science. He is Professor of Computer Science at the Systems Research Institute, Polish Academy of Sciences, and at WIT – Warsaw School of Information Technology, and Professor of Automatic Control at PIAP – Industrial Institute of Automation and Measurements. He is Honorary Foreign Professor at the Department of Mathematics, Yli Normal University, Xinjiang, China, and Visiting Scientist at RIKEN Brain Research Institute, Tokyo, Japan. He is Full Member of the Polish Academy of Sciences, Member of Academia Eueopaea (Informatics), Member of European Academy of Sciences and Arts (Technical Sciences), Foreign Member of the Spanish Royal Academy of Economic and Financial Sciences (RACEF), and Foreign Member of the Bulgarian Academy of Sciences. He is Fellow of IEEE, IFSA, EurAI (ECCAI) and SMIA.
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Searching in Harsh Environments Ophir Frieder, Fellow, IEEE Robert L. McDevitt, K.S.G., K.C.H.S. and Catherine H. McDevitt L.C.H.S. Chair in Computer Science and Information Processing Georgetown University, USA Email:
[email protected] and filtering via a threshold, our approach statistically significantly improves traditional Soundex and n-gram based search techniques used in the search of such texts. Thus, previously unsuccessful searches are now supported. Using a similar approach, within the medical domain, automated term corrections are made to reduce transcription errors.
Abstract Many consider "searching" a solved problem, and for digital text processing, this belief is factually based. The problem is that many "real world" search applications involve "complex documents", and such applications are far from solved. Complex documents, or less formally, "real world documents", comprise of a mixture of images, text, signatures, tables, etc., and are often available only in scanned hardcopy formats. Some of these documents are corrupted. Some of these documents, particularly of historical nature, contain multiple languages. Accurate search systems for such document collections are currently unavailable.
Finally, we focus analyzing social media, an additional, non-traditional search environment. By searching and mining such data, unknown or unexpected trends are detected. We explore and demonstrate the validity of the approach in the healthcare space.
We describe our efforts at building a complex document information-processing prototype. This prototype integrates "point solution" (mature) technologies, such as document readability enhancement, OCR capability, signature matching and handwritten word spotting techniques, search and mining approaches, among others, to yield a system capable of searching "real world documents". The described prototype demonstrates the adage that "the whole is greater than the sum of its parts". Our previous complex document benchmark development efforts are likewise presented.
About the Keynote Speaker Ophir Frieder holds the Robert L. McDevitt, K.S.G., K.C.H.S. and Catherine H. McDevitt L.C.H.S. Chair in Computer Science and Information Processing, and previously served as the Chair of the Department of Computer Science at Georgetown University. He is also Professor of Biostatistics, Bioinformatics and Biomathematics in the Georgetown University Medical Center. In addition to his academic positions, he is the Chief Scientific Officer for UMBRA Health Corp.(UHC). He is a Fellow of the AAAS, ACM, IEEE, and NAI.
Having described "real world" search issues, we focus on spelling correction in adverse environments. Two environments are discussed: foreign name search and medical term search. In support of the Yizkor Books project of the Archives Section of the United States Holocaust Memorial Museum, novel foreign name search approaches that favorably compare against the state of the art are developed. By segmenting names, fusing individual results,
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SEMANTIC COMPUTING AND COGNITIVE COMPUTING/INFORMATICS Phillip Sheu, Fellow, IEEE University of California, Irvine, USA Email:
[email protected]
About the Keynote Speaker
ABSTRACT
Phillip C.-Y. Sheu is a professor of EECS, CS, and BME at the University of California, Irvine. He received his B.S. degree in EE from National Taiwan University, and MS and Ph.D degrees in EECS from the University of California at Berkeley.
Semantic Computing (SC) addresses the derivation, description, integration, and use of semantics (“meaning”, "context", “intention”) for all types of resource including data, document, tool, device, process and people. A broader definition of Semantic Computing includes the computing technologies (e.g., artificial intelligence, natural language, software engineering, data and knowledge engineering, computer systems, signal processing, etc.), and their interactions, that may be used to extract or process computational content.
Dr. Sheu’s current research interests include semantic computing, robotic computing, and complex biomedical systems. He has published three books: Intelligent Robotic Planning Systems, and Software Engineering and Environment - An Object-Oriented Perspective, and Semantic Computing. He also has published extensively in object-relational data and knowledge engineering, semantic computing, robotic computing, and biomedical computing. He is the founder of the Institute for Semantic Computing and Robotic Computing (SC-RC), the IEEE International Conference of Semantic Computing (ICSC), the IEEE Computer Society Technical Committee on Semantic Computing (TCSEM), and the Knowledge Societies, an accredited member of UNESCO/USFUCA. He is the founding editor-in-chief of the International Journal of Semantic Computing (IJSC) and the Encyclopedia with Semantic Computing and Robotic Intelligence (ESCRI), and a co-founder of the IEEE International Conference of Multimedia Big Data (BigMM), the IEEE International Conference on Robotic Computing (ICRC), and the Bay Area Multimedia Forum (BAMMF).
This connection between content and the user is made via Semantic Analysis, which analyzes content with the goal of converting it to machine processable descriptions (semantics); Semantic Integration, which integrates content and semantics from multiple sources; Semantic Applications, which utilize content and descriptions to solve problems; and Semantic Interface, which interprets users' intentions expressed in natural language or other communicative forms. The reverse connection converts the intentions of users to create content via analysis and synthesis techniques. This talk introduces Semantic Computing based on its broader and narrower definitions, its relationship with Artificial Intelligence, Cognitive Computing and Informatics, and other branches of Computer Science. It also discusses several case studies showing how it can be used to solve more complex problems.
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Cognitive Foundations of Knowledge Science and Deep Knowledge Learning by Cognitive Robots Yingxu Wang, Senior Member, IEEE; Fellow, ICIC and WIF President, International Institute of Cognitive Informatics and Cognitive Computing (ICIC) Visiting Professor: Stanford Univ. (2008|16), MIT (2012), UC Berkeley (2008), Oxford Univ. (1995) Dept. of Electrical and Computer Engineering Schulich School of Engineering and Hotchkiss Brain Institute University of Calgary 2500 University Drive, NW, Calgary, Alberta, Canada T2N 1N4 http://www.ucalgary.ca/icic/ Email:
[email protected]
Fellow of ICIC, a Fellow of WIF (UK), a P.Eng of Canada, and a Senior Member of IEEE and ACM. He has been visiting professor (on sabbatical leave) at Oxford University (1995), Stanford University (2008 | 2016), UC Berkeley (2008), and MIT (2012), respectively. He received a PhD in Computer Science from the Nottingham Trent University in 1998 and has been a full professor since 1994. He is the founder and steering committee chair of the annual IEEE International Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC) since 2002. He is founding Editor-in-Chief of Int’l Journal of Cognitive Informatics & Natural Intelligence, founding Editor-in-Chief of Int’l Journal of Software Science & Computational Intelligence, Associate Editor of IEEE Trans. on SMC - Systems, Editor-in-Chief of Journal of Advanced Mathematics & Applications, and Editor-in-Chief of Journal of Mathematical & Computational Methods. Dr. Wang is the initiator of a few cutting-edge research fields such as cognitive informatics, denotational mathematics (concept algebra, process algebra, system algebra, semantic algebra, inference algebra, big data algebra, fuzzy truth algebra, fuzzy probability algebra, fuzzy semantic algebra, visual semantic algebra, and granular algebra), abstract intelligence (I), the neural circuit theory, mathematical models of the brain, cognitive computing, cognitive learning engines, cognitive knowledge base theory, and basic studies across contemporary disciplines of intelligence science, robotics, knowledge science, computer science, information science, brain science, system science, software science, data science, neuroinformatics, cognitive linguistics, and computational intelligence. He has published 460+ peer reviewed papers and 32 books in aforementioned transdisciplinary fields. He has presented 36 invited keynote speeches in international conferences. He has served as general chairs or program chairs for more than 22 international conferences. He has led 10+ international, European, and Canadian research projects as PI by intensive collaborations with renowned peers and leading industrial partners. He is the recipient of dozens international awards on academic leadership, outstanding contributions, best papers, and teaching in the last three decades. He is a top 2.5% scholar worldwide and top 10 at UCalgary according to the big data system of Research Gate’s international statistics.
Abstract — Recent basic studies reveal that novel solutions to fundamental AI problems are deeply rooted in both the understanding of the natural intelligence and the maturity of suitable mathematical means for rigorously modeling the brain in machine understandable forms. Learning is a cognitive process of knowledge and behavior acquisition. Learning can be classified into five categories known as object identification, cluster classification, functional regression, behavior generation, and knowledge acquisition. The latest discovery in knowledge science by Wang revealed that the basic unit of knowledge is a binary relation (bir) as that of bit for information and data. A fundamental challenge to knowledge learning different from those of deep and recurring neural network technologies has led to the emergence of the field of cognitive machine learning on the basis of recent breakthroughs in denotational mathematics and mathematical engineering. This keynote lecture presents latest advances in formal brain studies and cognitive systems for deep reasoning and deep learning. It is recognized that key technologies enabling cognitive robots mimicking the brain rely not only on deep learning, but also on deep reasoning and thinking towards machinable thoughts and cognitive knowledge bases built by cognitive systems. Fundamental theories and novel technologies for implementing deep thinking robots are demonstrated based on concept algebra, semantics algebra and inference algebra. Keywords — Cognitive informatics, cognitive computers, cognitive robotics, brain-inspired systems, deep learning, deep reasoning, deep thinking, knowledge learning, denotational mathematics, mathematical engineering, semantic computing, cognitive linguistics, and applications. ABOUT THE KEYNOTE SPEAKER Yingxu Wang is professor of cognitive informatics, brain science, software science, and denotational mathematics. He is President of International Institute of Cognitive Informatics and Cognitive Computing (ICIC, http://www.ucalgary.ca/icic/). He is a
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