CURRICULUM VITAE - ROBERT IVOR JOHN Personal…

                         CURRICULUM VITAE - ROBERT IVOR JOHN

Personal Information
Qualifications
B.Sc. (Hons) Mathematics First Class ­ Leicester Polytechnic ­ 1979
M.Sc. Statistics ­ UMIST ­ 1981
Ph.D. in Type-2 Fuzzy Systems ­ De Montfort University ­ 2000

Current Employment ­ De Montfort University
Senior Lecturer (1989 ­ 1994)
Principal Lecturer (1994 ­ 2003)
Head of Division of Artificial Intelligence and Computer Modelling (Sept 2002 ­ July 2006)
Reader in Computer Science (January 2003 ­ June 2005)
Professor in Computational Intelligence (June 2005 ­ Present)

Previous Employment
Softserv Ltd (Technical Director) (1986 ­ 1988)
Systems Designers (Senior Systems Engineer) (1985 ­ 1986)
British Gas (Senior Scientist) (1981 ­ 1985)


Management Experience
Throughout my career I have had various positions where I have managed people. At Softserv I managed a
team of 11 software engineers developing products.
    At De Montfort University I was Head of the Division of Artificial Intelligence and Computer Modelling
for four years managing approximately 30 staff including staff appraisal, staff development and all the usual
activities in an academic management post.
    Since RAE 2001 I have been the Director of the Centre for Computational Intelligence (CCI). In 2001
we submitted 3 staff to the RAE and for 2008 we submitted 10 - the largest group in the Computer Science
submission. As Director of the CCI I manage the research activities of eleven academic members of staff and
the Phd students, the resources of the Centre and motivate and generate research.

   · The group has more than doubled in size to eleven academic staff covering a diverse set of computational
     intelligence theories and application areas.

   · I managed the move into a new building where the staff offices and the large PhD students office occupy
     one wing. The group also has a brand new state-of-the-art mobile robotics laboratory with a range of
     robots.

   · The CCI now has 23 PhD students (both full time and part time, self funded and on EPSRC grants).

   · I have deliberately concentrated on developing and improving the research culture of the Centre. For ex-
     ample we hold fortnightly seminars (internal and external speakers), social activities, joint collaboration
     and an internal reviewing process for papers and grant proposals.




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   · We hosted a recent Grand Challenge Workshop1 . This meeting brought together leading academics from
     all over the UK to discuss the way forward for intelligent robotics.

   · The CCI has a MSc in Intelligent Systems and Robotics and MSc Bioinformatics.

   · The CCI is an integral part of the SRIF funded Institute of Creative Technology. I am on the steering
     committee.

   · I mentor staff in the Centre on new grant applications (e.g. EPSRC first grant)

   · I handle PhD applications to the CCI.

Member of the Faculty Research Committee and the Faculty Research Degrees Committee.


Research
National and International Recognition
National Recognition
I have been involved in a number of activities at what would be considered the national level, although most of
my reserach activities have an international dimension.

   · An elected member of the EPSRC College.

   · Conference co-chair for the Recent Advances in Soft Computing 2002 conference.

   · Conference Chair and organiser for EUSFLAT2001 organised on behalf of the European Society of
     Fuzzy Logic and Technology and held at De Montfort University. This conference is one of the leading
     European Fuzzy Logic Conferences and was attended by approximately 150 delegates. Plenary speakers
     included Professor Zadeh - the founder of fuzzy logic. This led to a special issue of Fuzzy Sets and
     Systems (one of the top fuzzy logic journals) [13].

   · The Recent Advances in Soft Computing series conferences at De Montfort University in 1998, 1999
     and 2000 were organised by the Centre for Computational Intelligence and I acted as Conference Chair.
     These averaged about 60 attendees from all over the world. Two of the conference proceedings were
     published by Springer-Verlag [96, 97].

   · Was external member of Southampton Institute Research Degrees Committee.

   · Was external examiner to the various MSc Computing programs at the University of Ulster.

   · Currently external examiner to the MSc Business Intelligence Sheffield Hallam University.

   · Currently external examiner to the MSc Intelligent Agents University of Westminster.

   · Invited speaker at Essex University, Oxford Brookes University and Leicester University.
  1 http://www.cs.bham.ac.uk/research/cogaff/gc/events/workshop-jan-04.html




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International Recognition
The following highlights some of the evidence of international recognition:

   · Invited to give a plenary talk at the World Congress on Computational Intelligence in 2006. This con-
     ference, organised by the IEEE combines three conferences every four years - FUZZ-IEEE, CEC and
     IJCNN.

   · He is part of a national team (with the universities of Essex, Aberystwyth and Bristol) that was awarded
     the right to hold the prestigious FUZZ-IEEE conference in Imperial College, London in 2007. He pre-
     sented the proposal and was Vice Chair of the conference. This is the most important conference in the
     world for fuzzy logic.

   · Vice Chair of the Fuzzy Technical Committee (FTC) of the IEEE Computational Inteligence Society.
     This is a very prestigious committee that drives the fuzzy logic aspects of the Society. I co-chair a special
     task force on `Extensions to Type-1 Fuzzy Sets' which has organised a number of two special sessions at
     FUZZ-IEEE 2004-2007 and edited a special issue of IEEE Transaction on Fuzzy Systems.

   · Member of the `Future in Fuzzy Sets and Systems' Task Force of the IEEE Technical Committee on
     Granular Computing

   · Active member in the Spanish National Network in Decision Making (REDEMAP II - TIN2004-21700-
     E: Preference Modelling and Aggregation) for the period 2005-2006

   · Member of the Editorial Board of the International Journal of Computational Intelligence

   · Member of various program committees (the EUROFUSE 2001 Workshop on Preference Modelling and
     Application; ISDA2001 ;ISDA2002; International Conference on Hybrid Intelligent Systems (HIS 2003),
     RASC (98,99,2000 and 2003), FUZZ-IEEE 2004, FUZZ-IEEE 2005, FUZZ-IEEE 2006, FUZZ-IEEE
     2007, FUZZ-IEEE 2008, UKCI 2004, UKCI 2005, UKCI 2008, PPSN2006, PPSN08, FLINS08, IADIS
     e-Commerce 2005, Scientific Committee of the Eighth International Conference "Artificial Intelligence
     and Soft Computing", 2007 IEEE Symposium Series on Computational Intelligence (SSCI 2007), 2006
     IEEE International Conference on Granular Computing)

   · Member of the Editorial Board of the International Journal of Cognitive Neurodynamics

   · Invited member of the BISC Special Interest Group on Fuzzy Logic and the Internet.

   · Edited a special issue of the Information Sciences Journal [95].

   · Edited a special issue of the Journal of Knowledge Based Intelligent Engineering [17].

   · Edited a special issue of Fuzzy sets and Systems [13].

   · Organised special sessions at NAFIPS 2001, FUZZ-IEEE 2002, 2004, 2005, 2006 and 2008.

   · Have been a referee for a number of journals including IEEE Transactions on Fuzzy Systems, the Journal
     of the O.R. Society, IEEE Transactions on Signal Processing, IEEE Transactions on Neural Networks, In-
     ternational Journal of Electrical Engineering Education, International Journal of Systems Science, FUZZ-
     IEEE conference and various other conferences.

   · Invited speaker at the BISC Workshop on Fuzzy Logic and the Internet held at the University of Berke-
     ley. This workshop was by invitation only and included Professor Zadeh (the father of fuzzy logic),
     James Keller (Editor in Chief IEEE Transactions on Fuzzy Systems) and Professor Burhan Turksen (ex
     President of NAFIPS).

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   · Member of the editorial board of the International Journal for Computational Intelligence and Informa-
     tion and Systems Sciences.

   · Associate Editor of the International Journal of Information & Systems Sciences

   · Funded to give a talk on type-2 fuzzy logic to staff and students at the University of Granada in Spain -
     the premier fuzzy logic group in Spain.

   · Funded to give a talk on type-2 fuzzy logic at the University of Pamplona, Spain.

   · Led type-2 fuzzy logic workshop BCS SigAI 2007.

Research Background
Context
Fuzzy Logic is a mature research area but the applications have been primarily in control. The holy grail as
proposed by Zadeh is `Computing with Words'. That is, can one get a computer to understand the meaning
of words and combine these words in real systems that model human decision making in difficult problems?
Type-2 fuzzy logic is a developing field that appears to offer a step change in moving toward this demanding
goal.
My work is at the forefront of theoretical and application-led research in type-2 fuzzy logic. I believe my work
on type-2 fuzzy logic sits alongside Professor Mendel's at the leading edge. This position has been arrived
at by following the research route outlined in the next section. The type-2 representation theorem and our
decompositional approach have had a significant impact on other researchers.

Research Narrative
Initially I worked on using fuzzy logic in community transport scheduling. This was a unique application and
led to some interesting results and a number of publications [25, 101, 89, 90]. An important strand of my
research is collaborative work (with Peter Innocent of the CCI) on the use of neural networks and fuzzy logic
in medical applications. The work concentrated on the role of neural networks in the classification of stress
fractures of the tibia [84, 24]. Bringing my expertise on fuzzy logic to the problem we combined type-1 fuzzy
logic and neural networks to tackle the same problem [99] and carried out an exhaustive investigation using
type-2 fuzzy sets which led to some interesting results [76, 19]. Other medical applications of type-2 fuzzy sets
include the modelling of nursing intuition [66, 62, 64] and using type-2 fuzzy sets to predict pulmonary emboli
[65]. Our current EPSRC grant is investigating breats cancer diagnosis [27].
A consistent thread throughout my recent work has been that of type-2 fuzzy logic. I have published a number
of papers on the theoretical foundations as well as applications of type-2 fuzzy logic already described. These
include journal review papers [23, 22] and adaptive type-2 fuzzy systems [74, 73]. Recently I have developed
some fundamental new theoretical results in type-2 fuzzy logic [63, 12, 59, 60]. Along with Professor Mendel
and Professor Turksen I am one of the leading researchers into the theoretical underpinning of type-2 fuzzy
logic as well as the use of type-2 fuzzy logic in medical applications. I have also been looking at type-2 OWAs
[26, 30, 31]
Through working with PhD students,colleagues and grants I have published in a number of different areas.
For example, the work of Mooney and I led to a new approach to user modelling using fuzzy logic to enhance
information retrieval [81, 15]. An enhancement and full implementation of this work was included in the ELVIL
project (a web portal for European law and politics) as the `virtual librarian' [61].
I am currently supervising eight Phd students .


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I have successfully supervised the following PhD students:
Anne Chisnall. Grounded Theory for Knowledge Acquisition (1997)
Gary J. Mooney. Fuzzy User Modelling and the World Wide Web (2000)
M.L. Nasir. Forecasting Corporate Bankruptcy using Artificial Neural Networks (2000)
Geraldine Clarke. Consumer Attitudes to the Higher Application Process (2000)
Rafee Ebrahim. Fuzzy Logic Programming (2003)
Dmitri Doubovitsky. Fuzzy Logic and Image Analysis (2005)
Laurence Tyler. Biologically Inspired Mobile Robots (2005) [50, 58]
Paul Baguley. Fuzzy Logic for Cost Modelling (2005)
Simon Coupland. Geometric Fuzzy Logic Systems (2006)
Shihadeh Alqrainy. A Morphological-Syntactical Analysis Approach for Arabic Textual Tagging (2008)
Hasan AlSerhan. Extraction of Arabic Word Roots: An Approach Based on Computational Model and Multi-
Backpropagation Neural Network (2008)

Grants & Patent
   · EPSRC (PI): Towards a Framework for Modelling Variation - EPSRC EP/C542215/1 ­ Grant value:
     £145,356

   · EPSRC (PI): Uncertainty Modelling in Technologies for the Elderly - EP/F013167/1 ­ Grant Value
     £45,447

   · DTI (PI): Improving customer demand and cost forecasting methods - TP/5/DAT/6/1/H025E ­ Grant
     value: £380,000

   · TSB/EPSRC KTP (PI): Knowledge Transfer Partnership with GoMad ­ Grant Value £145,000

   · Lachesis (PI): Data Perspective ­ Grant Value: £250,000

   · Royal Society (PI): Incoming Travel Grant ­ Grant Value: £13,000

   · EPSRC (CI): IMI: Improving the Cost Model Development Process (COSTMOD) - GR/M58818/01 ­
     Grant Value: £293,531

   · EPSRC (CI): Workshop on the Future of (UK) Fuzzy Systems Research - EP/E058388/1 ­ Grant Value:
     £12,026

   · HIRF (CI): Hardware Implementation of a Type-2 Fuzzy Logic System - Grant value: £16,028

   · DTI KTP (PI) KTP002611 Branall Ltd Grant £52,000

   · DTI KTP (PI) KTP005270 Branall Ltd Grant £59,112

I also received other funding from the EU on part of a larger project (ELVIL). I am an international scientific ad-
viser to OPTIMIST-RRT (OPTIMisation: using Intelligent Simulation Tools - Robust & Real-Time extensions)
which has a grant value of 10 Million Swedish Kroner.
     I recently submitted a UK patent application for my work on a new algorithm for fast and efficient type-2
fuzzy inferencing. This will allow for application of generalised type-2 fuzzy logic in control applications for
the first time.
I have conducted various paid consultancy projects for British Gas, Guardian PLC, Donnisthorpe Ltd, NCR,
Manx Telecom, Context Ltd and Barclays Bank. These projects ranged over a variety of topics in statistics,
fuzzy logic, soft computing and knowledge based systems.

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Teaching
Throughout my career I have always considered teaching to be important. The approach I adopt is that of
`active learning'. That is, I believe computing and statistics is best taught by active participation by the student
developing their understanding and skills in an incremental manner. Students learn by being stretched mentally
at an appropriate level for the course they are undertaking. As my research has flourished I have used it to
inform teaching where at all possible. For example a Masters module on artificial intelligence uses my work on
medical image classification as a case study.
I have taught numerous modules at both undergraduate and postgraduate level. It would not be appropriate to
list them all. They can be categorised in the following way:

   · Undergraduate modules on statistics for our Mathematics and Management Science Students.

   · Undergraduate modules on operations research for our Mathematics and Management Science Students.

   · Various undergraduate modules on artificial intelligence (fuzzy logic, neural networks and genetic algo-
     rithms).

   · Modules on artificial intelligence for MSc Computing, MSc Information Technology and MSc Digital
     Signal Processing.

Recently I was instrumental in developing a number of undergraduate computational intelligence modules
covering various aspects of computational intelligence including knowledge based systems, artificial neural
networks, genetic algorithms and fuzzy logic. I have supervised many undergraduate and postgraduate projects
in a variety of topics including fuzzy logic and neural networks.
I jointly led the development of BSc(Hons) Management Science and drove the development of a new advanced
MSc in Computational Intelligence and Robotics for start in 2004.




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References



     International Journals
 [1] S.-M. Zhou, J. Q. Gan, L. Xu and R. I. John (2008) Fuzziness Index Driven Fuzzy Relaxation Algorithm
     and Applications to Image Processing. Accepted for publication in Annals of Operations Research.

 [2] S. -M Zhou, J. M. Garibaldi, R. I. John, and F. Chiclana (2008) On Constructing Parsimonious Type-2
     Fuzzy Logic Systems via Influential Rule Selection. Accepted for publication in IEEE Transactions on
     Fuzzy Systems

 [3] S. Coupland and R. John (2008) A Fast Geometric Method for Defuzzification of Type-2 Fuzzy Sets.
     Accepted for publication in IEEE Transactions on Fuzzy Systems

 [4] Y. Yang and R. John (2008) Generalisation of Roughness Bounds in Rough Set Operations. Accepted for
     publication in International Journal of Approximate Reasoning

 [5] S. Coupland and R. John (2008) New Geometric Inference Techniques for Type-2 Fuzzy Sets. Accepted
     for publication in International Journal of Approximate Reasoning.

 [6] Sarah Greenfield, Francisco Chiclana, Simon Coupland and Robert John (2008) he Collapsing Method
     of Defuzzification for Discretised Interval Type-2 Fuzzy Sets. Accepted for publication in Information
     Sciences.

 [7] S. Coupland and R. I. John (2007) Geometric Type-1 and Type-2 Fuzzy Logic Systems, IEEE Transactions
     on Fuzzy Systems 15(1):3 - 15, February 2007.

 [8] S. -M. Zhou, J. Q. Gan, L.-D. Xu and R. John (2007) Interactive Image Enhancement by Fuzzy Relaxation.
     International Journal of Automation and Computing 4(3):229 ­ 235, (ISSN: 1476-8186, Springer).

 [9] Robert John and Simon Coupland (2007) Type-2 Fuzzy Logic: A Historical View. IEEE Computational
     Intelligence Magazine 2(1):57­62, February.

[10] Mendel, J. M., John, R.I. and Liu, F. (2006) Interval Type-2 Fuzzy Logic Systems Made Simple, IEEE
     Transactions on Fuzzy Systems 14(6):808 ­ 821.

[11] Y. Yang, R.I. John (2006) Roughness Bounds in Rough Set Operations, Information Sciences 176:3256­
     3267.

[12] R.I. John and P.R. Innocent (2005) Modelling Uncertainty in Clinical Diagnosis using Fuzzy Logic. IEEE
     Transactions on System, Man and Cybernetics - Part B: Cybernetics, 35, 6, 1340-1350 (ISSN 1083-4419)

[13] P.R. Innocent, R.I. John, J. Garibaldi (2005) Fuzzy Methods and Medical Diagnosis. Applied Artificial
     Intelligence. Volume 19 (1), 69-98 (November 2004) (ISSN 0883-9514)

[14] P.R. Innocent and R.I. John (2004) Computer Aided Fuzzy Medical Diagnosis Information Sciences,
     162(2), pp 81-104.

[15] Mendel, J and John R.I. (2002) Type-2 Fuzzy Sets Made Simple, IEEE Transactions on Fuzzy Systems,
     10(2) pp 117-127.

[16] John R.I. (2005) Editor Special Issue of Fuzzy Sets and Systems.


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[17] John R.I. (2003) Soft computing and hybrid approaches: An introduction to this special issue Information
     Sciences. 150/1-2 pp. 1­3.

[18] John R I and Mooney G.J. (2001) Fuzzy User Modelling for Information Retrieval on the World Wide
     Web Knowledge and Information Systems 3(1), 81-95.

[19] P.R. Innocent, R.I. John, J.M. Garibaldi (2001) The fuzzy medical group in the Centre for Computational
     Intelligence Artificial Intelligence in Medicine, 21(1-3), 163-170.

[20] John R.I. (2001) Editor Special Issue International Journal of Knowledge-Based Intelligent Engineering
     Systems. 5(1)

[21] Nasir,M.L.,John, R.I.,Bennett, S.C.,Russell, D.M.(2001) Selecting the neural network topology for stu-
     dent modelling of prediction of corporate bankruptcy, Campus-Wide Information Systems, 18(1), 13-22.

[22] John R I, Innocent P R,and Barnes M R (2000) Neuro-Fuzzy Clustering of Radiographic Tibia ImageData
     using Type-2 Fuzzy Sets Information Sciences, 125/1-4, 203-220.

[23] Nasir, M.L., John, R.I., Bennett, S.C. (2000) Predicting Corporate Bankruptcies using Artificial Neural
     Networks Journal of Applied Acccounting Research, 5(iii), 30­52.

[24] Nasir,M.L.,John, R.I.,Bennett, S.C.,Russell, D.M.(2000) Selecting the Neural Network Topology for Pre-
     dicting Corporate Failure, in Journal of Information Systems, December, MCB University Press, Toller
     Lane, Bradford, West Yorkshire, England.

[25] John R. (1999) Fuzzy Sets of Type-2 Journal of Advanced Computational Intelligence, 3(6), 499-508.

[26] John R I (1998) Type 2 Fuzzy Sets: An Appraisal of Theory and Applications, International Journal of
     Uncertainty, Fuzziness and Knowledge Based Systems, 6(6), 563­576.

[27] Innocent P, Barnes M and John R I, (1997) Application of the fuzzy ART/MAP and MinMax/MAP neural
     network models to radiographic image classification, Artificial Intelligence in Medicine, 11(3), 241­263.

[28] John R I and Bennett S C, (1997) The Use of Fuzzy Sets for Resource Allocation in an Advance Request
     Vehicle Brokerage System - a Case Study Journal of the Operational Research Society, 48, 117-123

     International Conferences

[29] S. -M Zhou, F. Chiclana, R. I. John, J. M. Garibaldi (2008) A Practical Approach to Type-1 OWA Opera-
     tion for Soft Decision Making. Accepted for Proc. of The 8th International FLINS Conf. on Computational
     Intelligence in Decision and Control, Madrid, Spain, 2008.

[30] S. -M. Zhou, R. John, X. Y. Wang, J. M. Garibaldi and I. O. Ellis (2008) Compact Fuzzy Rules Induction
     and Feature Extraction Using SVM with Particle Swarms for Breast Cancer Treatments. Accepted for
     Proc. of IEEE Congress on Evolutionary Computation (CEC), Hongkong, China.

[31] Anna Syberfeldt, Henrik Grimm, Amos Ng and Robert John (2008) A Parallel Surrogate-Assisted Multi-
     Objective Evolutionary Algorithm for Computationally Expensive Optimization Problems. Accepted for
     Proc. of IEEE Congress on Evolutionary Computing.

[32] Yang, Y. and John, R. (2008) Global Roughness of Approximation and Boundary Rough Sets. Accepted
     for Proc. of Fuzzy-IEEE .



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[33] S.-M. Zhou, F. Chiclana, R. John and J. M. Garibaldi (2008) On Properties of Type-1 OWA Operators in
     Aggregating Uncertain Information for Soft Decision Making. Accepted for Proc. of the 12th Int. Conf.
     on Information Processing and Management of Uncertainty in Knowledge-based Systems (IPMU) ,

[34] S. -M. Zhou, F. Chiclana, R. John and J. M. Garibaldi (2008) Type-2 Owa Operators -Aggregating Type-
     2 Fuzzy Sets in Soft Decision Making. Accepted for Proc. of IEEE International Conference on Fuzzy
     Systems (FUZZ-IEEE).

[35] Abdulaziz M. S. Aldobhani and Robert John (2008) Maximum Power Point Tracking of PV System
     Using ANFIS Prediction and Fuzzy Logic Tracking. Accepted for Proc. IAENG International Conference
     on Control and Automation,

[36] Greenfield, S. and John, R. (2008) Stratification in the Type-Reduced Set and the Generalised Karnik-
     Mendel Iterative Procedure. Accepted for Proc. Intelligent Processing and the Management of Uncertainty
     2008 - IPMU08.

[37] Stelzer, R., Proell, T., and John, R.I. (2007) Fuzzy Logic Control System for Autonomous Sailboats. Proc.
     FUZZ-IEEE2007,pages 97­102, London, UK.

[38] S. -M Zhou, R. John, F. Chiclana and J. Garibaldi (2007) New Type-2 Rule Ranking Indices for Designing
     Parsimonious Interval Type-2 Fuzzy Logic Systems. In Proc. of the 2007 IEEE International Conference
     on Fuzzy Systems (FUZZ-IEEE2007) London, UK, 23 - 26 July, 2007, pages 853-858, London.

[39] Simon Coupland and Robert John (2007) On the Accuracy of Type-2 Fuzzy Sets. In Proc. FUZZ-IEEE
     2007, pages 131 - 136, London, UK.

[40] Greenfield, S. and John, R. (2007) Optimised Generalised Type-2 Join and Meet Operations. In Proceed-
     ings of International Conference on Fuzzy Systems 2007, pages 141­146, July 2007.

[41] S.-M. Zhou, F. Chiclana, R. John and J. M. Garibaldi (2007) Type-1 OWA Operators for Aggregating
     Fuzzy Sets in Decision Making. In Proc. of EUSFLAT AGOP, 9-14 July, 2007, Ghent, Belgium, pages
     107-112, Ghent, Belgium.

[42] Sarah Greenfield, Francisco Chiclana, Robert John and Simon Coupland (2007) The Collapsing Method
     of Defuzzification for Discretised Interval Type-2 Fuzzy Sets In Proc. UKCI 2007,

[43] John, R. and Coupland, S. (2006) Extensions to Type-1 Fuzzy: Type-2 Fuzzy Logic and Uncertainty. In
     Gary Y. Yen and David B. Fogel, editor, Computational Intelligence: Principles and Practice, pages 89 -
     102, IEEE Computational Intelligence Society, 2006.

[44] S. Coupland, M.Gongora, R. I. John and K.Wills (2006) A Comparative Study of Fuzzy Logic Controllers
     for Autonomous Robots. In Proc. IPMU 2006, pages 1332 - 1339, Paris, France, 2006.

[45] Coupland, S. and John, R. (2006) An Investigation into Alternative Methods for the Defuzzification of an
     Interval Type-2 Fuzzy Set. In Proc. Fuzz-IEEE 2006, pages 7196 - 7203, 2006.

[46] Yang, Y. and John, R. (2006) Roughness Bounds in Set-oriented Rough Set Operations. In Proc. FUZZ-
     IEEE 2006, pages 1461 - 1468, 2006.

[47] John, R., Mendel, J. and Carter, J. (2006) The Extended Sup-Star Composition for Type-2 Fuzzy Sets
     Made Simple. In Proc. FUZZ-IEEE 2006, pages 7212 - 7216, 2006.

[48] Sarah Greenfield, Robert John and Simon Coupland (2005) A Novel Sampling Method for Type-2 De-
     fuzzification. In Proc. UKCI 2005, pages 120 - 127, London, September.

                                                      9
[49] S. Coupland and R. John (2005) Towards More Efficient Type-2 Fuzzy Logic Systems. In Proc FUZZ-
     IEEE 2005, pages 236 - 241, Reno, NV, USA, May.

[50] S. Coupland and R. John (2005) Geometric IntervalType-2 Fuzzy Systems. In Proceedings of the Joint
     EUSFLAT-LFA (IV EUSFLAT and XI LFA), pages 449 - 454, Barcelona, Spain, September 2005.

[51] J. Mendel, R. John and F. Liu (2005) On Using Type-1 Fuzzy Set Mathematics to Derive Interval Type-2
     Fuzzy Logic Systems. Proceedings of NAFIPS'05, pp 528-533.

[52] Wills K., John R.I. and Lake, S. (2004) Combining Categories in Nursing Assessment using Interval
     Valued Fuzzy Sets, IPMU'94

[53] R. John L. Tyler and H. Heischmuller (2004) Cooperative Mobile Robots and Stereo Vision MED'04

[54] Coupland S. and John R.I. (2004) A New and Efficient Method for the Type-2 Meet Operation, in Proc.
     FUZZ-IEEE 2004pages 959 - 964, Budapest, Hugary, July

[55] J. Garibaldi, S. Musikasuwan, T. Ozen and R. John (2004) A Case Study to Illustrate the Use of Non-
     Convex Membership Functions for Linguistic, FUZZ-IEEE 2004

[56] J.M. Garibaldi and R.I. John (2003) Choosing Membership Functions of Linguistic Terms Proceedings of
     the 2003 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2003), 578-583.

[57] John R I (2002) Embedded Interval Valued Fuzzy Sets. Proceedings of Fuzz-IEEE 2002. pp1316-1321.

[58] Coupland S. and John R.I. (2004) An Approach to Type-2 Fuzzy Arithmetic. In Proc. UK Workshop on
     Computational Intelligence, pages 107­ 114, 2003.

[59] K. Wills, R.I. John, P.R. Innocent and S. Lake (2003) Modelling Nursing Intuition - a Non-Deterministic
     Approach Proceedings EUSFLAT2003. pp 751-758.

[60] Y. Yang and R.I. John (2003) Grey Systems and Interval Valued Fuzzy Sets Proceedings EUSFLAT
     2003.pp 193-197

[61] L Tyler, P Innocent and R John (2003) Co-operation and Interference in Mobile Robot Groups. Interna-
     tional Conference on Mechatronics 2003, Loughborough, UK.

[62] John R.I. (2002) Towards a Higher Level of Linguistic Granularity Proceedings of IPMU 2002. Vol. 2 pp
     1129­1133.

[63] Mendel, J and John R.I. (2002) Footprint of Uncertainty and its Importance to Type-2 Fuzzy Sets Proc.
     6th IASTED Intl. Conf. on Artificial Intelligence and Soft Computing (ASC 2002), July 17-19, 2002,
     Banff, Canada.pp. 587-592

[64] R.I. John, I.P. Bloor and P. Zhang (2001) Fuzzy User Modelling and Database Selection Proceedings of
     EUROFUSE 2001 Workshop on Preference Modelling and Applications, 165-168.

[65] John R and Lake S (2001) Modelling Nursing Perceptions Using Type-2 Fuzzy Sets Proceedings of EU-
     ROFUSE 2001 Workshop on Preference Modelling and Applications, 241-246.

[66] Mendel J.M. and John R.I. (2001) A Fundamental Decomposition of Type-2 Fuzzy Sets Proceedings of
     Joint 9th IFSA World Congress and 20th NAFIPS International Conference, pp 1896-1901, ISBN 0-7803-
     7079-1

[67] John R and Lake S (2001) Type-2 Fuzzy Sets for Modelling Nursing Intuition Proceedings of Joint 9th
     IFSA World Congress and 20th NAFIPS International Conference, pp 1920-1925, ISBN 0-7803-7079-1

                                                    10
[68] P.R. Innocent, I. P. Belton , D.B.L. Finlay and R.I. John (2001) Type 2 Fuzzy Representations of Lung
     Scans to Predict Pulmonary EmboliProceedings of Joint 9th IFSA World Congress and 20th NAFIPS
     International Conference, pp 1902-1907. ISBN 0-7803-7079-1

[69] S. Lake and R. I . John (2000). Patient Assessment in Nursing Care using Fuzzy Logic. Nursing Informat-
     ics Conference, Auckland, New Zealand.

[70] Nasir, M.L., John,I., Bennett, S.C., Russell, D.M.(2000).Predicting Corporate Bankruptcies using Mod-
     ular Neural Networks. Proc IEEE/IAFE/INFORMS2000 Conference on Computational Intelligence for
     Financial Engineering, 86-91

[71] John R I (1999) Type 2 Fuzzy Sets Expert Update, Vol. 2, No 2, Summer 1999, ISSN 1465-4091

[72] Nasir, M.L., John, R.I., Bennett, S.C. (1999) Predicting Corporate Bankruptcies using Inter-Connected
     Artificial Neural Networks EUFIT99

[73] Innocent, P.R. and John, R.I. (2002) Type-2 Fuzzy Medical Diagnosis. Proceedings of Fuzz-IEEE 2002.
     pp1326-1331.

[74] Nasir, M. L.; John, R. I.; Bennett, S. C (2000) Predicting Corporate Bankruptcy Using Modular Neu-
     ral Networks Proceedings of the IEEE/IAFE/INFROMS Conference on Computational Intelligence for
     Financial Engineering - 2000 86-91

[75] Nasir, M.L., John, R.I., Bennett, S.C., Russell, D.M.(2000): Handling Non-Convergence in Time Varying
     Neural Networks, Proceedings of the International Joint Conference on Neural Networks,Pittsburg,May
     15-17, Pittsburgh, Pennsylvania,

[76] John R I and Czarnecki C (1999) An Adaptive Type-2 Fuzzy System for Learning Linguistic Membership
     Grades Proc. 8th Intl. Conf. on Fuzzy Systems FUZZ-IEEE99 ,1552­1556.

[77] John R I and Czarnecki C, (1998)A Type 2 Adaptive Fuzzy Inferencing System, Proc. IEEE Systems,
     Man and Cybernetics98, 3, 2068­2073.

[78] John R I, (1998) Type 2 Fuzzy Sets for Knowledge Representation and Inferencing, Proc. 7th Intl Conf.
     on Fuzzy Systems FUZZIEEE 98, 1003­1008.

[79] John R I, Innocent P R and Barnes M R (1998) Type 2 Fuzzy Sets and Neuro-Fuzzy Clustering of Radio-
     graphic Tibia Images. Proc. 7th Intl Conf. on Fuzzy Systems FUZZIEEE 98, 1373­1376.

[80] Nasir, M.L., John, R.I., Bennett, S.C. (1998) Financial Data Sampling and Selection for use in Artificial
     Neural Networks, Fourth International Meeting on Artificial Intelligence and Emerging Technologies in
     Accounting, Finance and Tax, December, University of Huelva, Spain.

[81] Innocent P.R., John R.I. and King J. (1998). Type 2 fuzzyART: A clustering method for linguistic knowl-
     edge. SOFT98 Workhop on Soft Computing. De Montfort University. July.

[82] C.A.Czarnecki and R.I.John (1997) An Intelligent Monitor for Semi-Autonomous Robots Operating in
     Hazardous Environments, Proc. 12th International Conference on Systems Engineering, ICSE97, 9-11
     September 1997, 1, 171­176.

[83] R. I. John and P.R. Innocent and M.R. Barnes, (1997) Type 2 Fuzzy Sets and Neuro-Fuzzy Clustering of
     Radiographic Tibia Images. Proceedings Third Joint Conference on Information Sience, 1, 58­61.

[84] Gary Mooney and Robert John, (1997) Intelligent Information Retrieval from the World Wide Web using
     Fuzzy User Modelling, ELVIRA Fourth International Conference, 6-8 May 1997.

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[85] John, R.I. (1996) Type 2 Fuzzy Sets for Community Transport Scheduling, Proceedings of EUFIT96,
     2,1369­1372.

[86] John R I, (1996) Representing Knowledge with Type 2 Fuzzy Sets, Proceedings of Knowledge Transfer
     96, Ed. A. Behrooz, pp 82-89

[87] Innocent, P and Barnes, M and Keighley J and John R, (1996) Neuro-fuzzy clustering of shin images,
     Proceedings of 2nd International Conference on Neural Networks and Expert Systems in Medicine and
     Healthcare (NNESMED96), Ed. Emmanuel C. Ifeachor, pp 14-21

[88] Chisnall A, Bennett S C and John R I, (1996) The suitability of grounded theory for knowledge acquisi-
     tion,Proceedings of Knowledge Transfer 96, Ed. A. Behrooz, pp 117-123

[89] Chisnall A C, John R I and Bennett S C, (1995) Knowledge Elicitation Techniques for Grounded Theory,
     in Research and Development in Expert Systems XII, (Proceedings of Expert Systems 95), edited by
     Bramer M, Nealon J L, and Milne R., SGES Publications: Oxford., December 1995.

[90] Czarnecki C A, John R I and Bennett S C, (1995) The Application of Fuzzy Logic to Real Time Multiple
     Robot Collision Avoidance, International Symposium on Fuzzy Logic 95, Zurich, Switzerland, May 1995.

[91] Bennett S C and John R I, (1995) Fuzzy Inferencing Applied to Vehicle Assignment in Community Trans-
     port, International Symposium on Fuzzy Logic 95, Zurich, Switzerland, May 1995.

[92] John R I and Bennett S C, (1995) Fuzzy Sets and Community Transport, Applied Decision Technologies
     Conference, Brunel University, April 1995.

[93] Bennett S C and John R I, (1994) The Application of Fuzzy Set Theory to Vehicle Brokerage, 27th ISATA,
     Dedicated Conference on Mechatronics, Aachen, Germany, November 1994.

[94] Gregson M, John R, Teather B, Thompson R (1994) Practical issues in the Application of Back Propaga-
     tion Neural Networks to the Differential Diagnosis of Brain Disease, NNESMED94

[95] Gregson M, John R, Thompson R, Teather BA (1994) Applying Back Propagation Neural Networks to
     the Differential Diagnosis of Brain Disease, Applied Informatics

[96] John R, Monnet S, Bhinder S (1992) The United Benefits System, KBS Methodologies Workshop BCS
     1992

[97] Born G, John R (1987) Expert System Delivery Vehicles, KBS 87
     Books & Book Chapters

[98] John R.I. (2003) Recent Advances in Soft Computing Editor Special Issue of Information Sciences. 150/1-
     2 pp. 1­118, March 2003.

[99] John R and Birkenead R (Eds.) (2001) Developments in Soft Computing in Advances in Soft Computing
     Series, Physica Verlag.

[100] John R and Birkenhead R (2000) Soft Computing Techniques and Applications in Advances in Soft
     Computing Series, Physica Verlag.

[101] John R I (2000) Fuzzy Sets and Knowledge Representation in Fuzzy Systems in Medicine, Studies in
     Fuzziness and Soft Computing, Physica-Verlag, 78­89.

[102] Innocent P R, John R I and Barnes M R (2000) Neuro-fuzzy models of radiographic image classification
     in Fuzzy Systems in Medicine, Studies in Fuzziness and Soft Computing, Physica-Verlag,361­393.

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[103] John R I, (1998) Type 2 Fuzzy Sets for Knowledge Representation and Inferencing, Research Mono-
     graph, 10, School of Computing Sciences, De Montfort University, United Kingdom.

[104] John R I and Bennett S C, (1996) Fuzzy Sets and Community Transport, in Fuzzy Logic, edited by Prof
     J F Baldwin, pp 245-253, John Wiley: Chichester, Sussex. ISBN 0471 96281 3.

[105] John R I, (1995) Fuzzy Inferencing Systems, De Monfort University School of Computing Sciences
     Working Paper No. 64




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