Qualification: 
Ph.D, MSc, BSc
mrkaimal@am.amrita.edu

Dr. Ramachandran Kaimal currently serves as Professor at the Department of Computer Science at Amrita School of Engineering, Amritapuri.

Dr. Kaimal earned his Ph. D. in 1978 from the Mehta Research Institute, now known as the Harish Chandra Institute in Allahabad under the guidance of (Late) Padmabhushan Prof. P. L. Bhatnagar and Prof. Phoolan Prasad. During the years 1981-1984, he served as Visiting Fellow at the National Institute of Health in Bethesda, Maryland in USA. He was Professor and Head of the Department of Computer Science during the period March 1987 - April 2009. Dr. Kaimal also served as Dean of the Faculty of Applied Sciences at the University of Kerala during the periods 1993-1995 and 2004-2006. In August 2008, he served as Visiting Scientist at the Mobile Intelligent and Autonomous Systems (MIAS) Unit, CSIR in South Africa. He has worked on a major ISRO-funded research project titled Development of Methodologies based on Neuro-Fuzzy and Genetic Algorithms for Modelling and Control of Systems.

Dr. Kaimal has over 30 years of teaching and research experience. In his illustrious career, he has published about 60 papers in top journals including the Journal of Math, Imaging and Vision, Computer Journal, IEEE Signal Proc. Letters, International Journal of Engineering Science, Transactions of ASME, IEEE Transactions, Fuzzy Systems, Sadhana and Foundations of Computer Science.

Dr. Kaimal's current research focuses on Artificial Intelligence and its applications to Image Processing and Knowledge Discovery. Other areas of interest include Machine Learning Algorithms, Pattern Recognition, Data Compression and Coding Algorithms. 

Dr. Kaimal has successfully guided 13 Ph.D.s in Computer Science and 1 Ph.D. in Mathematics. In addition he has overseen the theses work of nearly 40 M.Tech. students and several M.Phil. students.

Publications

Publication Type: Journal Article

Year of Publication Publication Type Title

2017

Journal Article

M. Geetha and Dr. Kaimal, M. R., “A 3D stroke based representation of sign language signs using key maximum curvature points and 3D chain codes”, Multimedia Tools and Applications, pp. 1-34, 2017.[Abstract]


Sign Language is a visual spatial language used by deaf and dumb community to convey their thoughts and ideas with the help of hand gestures and facial expressions. This paper proposes a novel 3D stroke based representation of dynamic gestures of Sign Language Signs incorporating local as well as global motion information. The dynamic gesture trajectories are segmented into strokes or sub-units based on Key Maximum Curvature Points (KMCPs) of the trajectory. This new representation has helped us in uniquely representing the signs with fewer number of key frames. We extract 3D global features from global trajectories using a scheme of representing strokes as 3D codes, which involves dividing strokes into smaller units (stroke subsegment vectors or SSVs), and representing them as belonging to one of the 22 partitions. These partitions are obtained using a discretisation procedure which we call an equivolumetric partition (EVP) of sphere. The codes representing the strokes are referred to as an EVP code. In addition to global hand motion and local hand motion, facial expressions are also considered for non-manual signs to interpret the meaning of words completely. In contrast to existing methods, our method of stroke based representation has less expensive training phase since it only requires the training of key stroke features and stroke sequences of each word. © 2017 Springer Science+Business Media New York

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2017

Journal Article

R. R. K. Menon, Joseph, D., and Dr. Kaimal, M. R., “Semantics-based topic inter-relationship extraction”, Journal of Intelligent and Fuzzy Systems, vol. 32, pp. 2941-2951, 2017.[Abstract]


Maintaining large collection of documents is an important problem in many areas of science and industry. Different analysis can be performed on large document collection with ease only if a short or reduced description can be obtained. Topic modeling offers a promising solution for this. Topic modeling is a method that learns about hidden themes from a large set of unorganized documents. Different approaches and alternatives are available for finding topics, such as Latent Dirichlet Allocation (LDA), neural networks, Latent Semantic Analysis (LSA), probabilistic LSA (pLSA), probabilistic LDA (pLDA). In topic models the topics inferred are based only on observing the term occurrence. However, the terms may not be semantically related in a manner that is relevant to the topic. Understanding the semantics can yield improved topics for representing the documents. The objective of this paper is to develop a semantically oriented probabilistic model based approach for generating topic representation from the document collection. From the modified topic model, we generate 2 matrices-a document-topic and a term-topic matrix. The reduced document-term matrix derived from these two matrices has 85 similarity with the original document-term matrix i.e. we get 85 similarity between the original document collection and the documents reconstructed from the above two matrices. Also, a classifier when applied to the document-topic matrix appended with the class label, shows an 80 improvement in F-measure score. The paper also uses the perplexity metric to find out the number of topics for a test set. © 2017-IOS Press and the authors. All rights reserved.

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2007

Journal Article

R. Rajesh and Dr. Kaimal, M. R., “A Novel Method for the Design of Takagi-Sugeno Fuzzy Controllers with Stability Analysis using Genetic Algorithm”, Engineering Letters, vol. 14, pp. 15-26, 2007.

2004

Journal Article

R. Mathew and Dr. Kaimal, M. R., “A fuzzy approach to the 2 × 2 games and an analysis of the game of chicken”, International Journal of Knowledge-Based and Intelligent Engineering Systems, vol. 8, no. Volume 8, Number 4/2004, pp. 181-188, 2004.[Abstract]


A fuzzy approach which is useful to arrive at a solution of 2 × 2 strategic games has been recently introduced in [13]. In this, a player is given an option to construct a fuzzy set over his opponent's strategic space in order to represent his beliefs about his opponent's strategic choice and also he is allowed to optimize a number of goals simultaneously in the game. The existing method of analyzing this fuzzy approach is found to be very tedious. This present paper utilizes the expected value of a fuzzy variable in order to achieve the optimal strategies in the game. It is shown that a table look up procedure can be developed for the solution of 2 × 2 games. The Game of Chicken, with general payoff parameters, has been fully analyzed using this method and simulation studies reveal that the new method improves the quality of the optimal decision achieved. More »»

2004

Journal Article

R. Mathew and Dr. Kaimal, M. R., “A Fuzzy Approach to Strategic Games Using Fuzzy Expected Value Models”, Journal of Computer Society of India, vol. 34, No. 2 vol., pp. pp.40-47, 2004.

2003

Journal Article

R. Rajesh and Dr. Kaimal, M. R., “Semi-Circular Membership Function for Fuzzy systems”, Journal of Computer Society of India, 2003.

2002

Journal Article

R. Rajesh, Mohanlal., P. P., and Dr. Kaimal, M. R., “An Optimal Rule generation Scheme Using Genetic Algorithms for the Design of a Fuzzy Logic Controller”, Jl of System society of India, 2002.

1995

Journal Article

M. R. Dr. Kaimal and Sreekumar, R., “ On Selecting Best Replacement Node in Point Quad tree Deletion”, SRC-95, Computer Society of India, , 1995.

1992

Journal Article

A. P. Korah and Dr. Kaimal, M. R., “A Short Note on Perfectly Balanced Binary Search Trees”, Comput. J., vol. 35, pp. 660-662, 1992.[Abstract]


We present a perfect balancing method for a binary search tree. During the updates the algorithm allows the structure to grow gracefully and maintains the optimal shape without degeneration. The algorithm uses swapping as the basic operation. Since the tree produced by the algorithm is optimal it can favourably be compared with that produced by other balancing algorithms. In worst case situation, the algorithm takes O(n) time, n being the total number of nodes in the tree. This is an added significance when it is compared with the static optimal binary search trees. More »»

1990

Journal Article

A. P. Korah and Dr. Kaimal, M. R., “Dynamic Optimal Binary Search Tree”, Int. J. Found. Comput. Sci., vol. 1, pp. 449-464, 1990.[Abstract]


In this paper we present a strategy to maintain a dynamic optimal binary search tree. The algorithms for insertion and deletion use swapping as the basic operation. Since in average situations the tree reorganization is limited to local changes, it can be favourably compared with the local balancing algorithms. The present algorithms dynamically maintain the optimal tree with an amortized time of O(log2 n), where n is the total number of nodes in the tree. In the worst case situations, the algorithms take only O(n) time. This is significant when they are compared to the algorithms producing static optimal binary search trees. More »»

1981

Journal Article

R. Acharya, Chandra, P., and Dr. Kaimal, M. R., “ A Hydrodynamic Study of the Flow in Renal Tubules”, Bull. Math. Biol., , vol. Vol. 43, pp. pp 151- 163 , 1981.

1981

Journal Article

M. R. Dr. Kaimal, “Propagation Characteristics in Distensible Tubes containing a Viscoelastic Fluid”, J. Biomechanics, , vol. vol.14, pp. pp 47-63, 1981.

1978

Journal Article

P. L. Bhatnagar and Dr. Kaimal, M. R., “Free Convection Flow Past a Vertical Wall,”, J. Math. Phy. Sci. , vol. vol. 13(5) , pp. pp 283-305 , 1978.

Publication Type: Conference Paper

Year of Publication Publication Type Title

2014

Conference Paper

S.a Harikumar, Reethima, R., and Dr. Kaimal, M. R., “Semantic integration of heterogeneous relational schemas using multiple L1 linear regression and SVD”, in International Conference on Data Science and Engineering, ICDSE 2014, 2014, pp. 105-111.[Abstract]


The challenge of semantic integration of heterogeneous databases is one of the critical areas of interest due to scalability of data and the need to share the existing data as the technology advances. The schema level heterogeneity of the relations is the major issue for such integration. Though various approaches of schema analysis, transformation and integration have been explored, sometimes those become too general to solve the problem especially when the data is very high-dimensional and the schema information is unavailable or inadequate. In this paper, a method to integrate heterogeneous relational schema at instance-level is proposed, rather than the schema level. A global schema is designed consisting of the integration of most relevant attributes of different relational schema of a particular domain. In order to find the significant attributes, multiple linear regressions based on LI norm and Singular Value Decomposition(SVD) is applied on the data iteratively. This is a variant of L1-PCA, which is efficient, effective and meaningful method of linear subspace estimation. The most prominent instance - level similarity is found by finding the most significant attributes of each relational data source and then finding the similarity among those attributes using L1-norm. Thus an integrated schema is created that maps the relevant attributes of each local schema to a global schema. © 2014 IEEE.

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2014

Conference Paper

S.a Harikumar, Shyju, M., and Dr. Kaimal, M. R., “SQL-MapReduce hybrid approach towards distributed projected clustering”, in International Conference on Data Science and Engineering, ICDSE 2014, 2014, pp. 18-23.[Abstract]


Clustering high dimensional data is a major challenge in data mining due to the existence of inherent complexity and sparsity of the data. Projected clustering is one of the clustering approaches that determine the clusters in the subspaces of such high dimensional data. However, projected clustering within DBMS is quite computationally expensive in time and space complexity, when the volume of records is in terms of terabytes, petabytes and more. This expensive computation becomes a hurdle especially when the data clustering on transactional data is used as a preprocessing step for other tasks such as frequent decision making, efficient indexing, compression, etc. Hence, parallelizing and distributing expensive data clustering tasks becomes attractive in terms of speed-up of computation and the increased amount of memory available in a computing cluster. Inorder to achieve this, we propose a SQL-MapReduce hybrid approach for scalable projected clustering. © 2014 IEEE.

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2013

Conference Paper

M. Geetha, Aswathi, P. V., and Dr. Kaimal, M. R., “A Stroke Based Representation of Indian Sign Language Signs Incorporating Global and Local Motion Information”, in Second International Conference on Advanced Computing, Networking and Security, 2013.[Abstract]


Sign Language is a visual gesture language used by speech impaired people to convey their thoughts and ideas with the help of hand gestures and facial expressions. This paper presents a stroke based representation of dynamic gestures of Indian Sign Language Signs incorporating both local as well as global motion information. This compact representation of a gesture is analogous to phonemic representation of speech signals. To incorporate the local motion of the hand, each stroke contains the features corresponding to the hand shape as well. The dynamic gesture trajectories are segmented based on Maximum Curvature Points(MCPs). MCPs are selected based on the direction change of trajectories. The frames corresponding to the MCP points of the trajectory are considered as the key frames. Local information features are taken as the hand shape of the Key frames. The existing methods of Sign Language Recognition has scalability problems apart from high complexity and the need for extensive training data. In contrast, our proposed method of stroke based representation has less expensive training phase since it only requires the training of stroke features and stroke sequences of each word. Our algorithms also address the issue of scalability. We have tested our approach in the context of Indian Sign Language recognition and we present the results from this study More »»

2012

Conference Paper

Aa George, Poornachandran, Pb, and Dr. Kaimal, M. R., “Adsvm: Pre-processor plug-in using support vector machine algorithm for snort”, in ACM International Conference Proceeding Series, Kerala, 2012, pp. 179-184.[Abstract]


Anomaly detection has been considered as a critical problem in any application area. In computer networks, anomaly detection is important as any kind of abnormal behavior in the network data is considered harmful to the end user. Snort is an open source NIDS tool that uses misuse detection method for intrusion detection. There are many pre-processor and detection plug-ins for Snort. Pre-processor plug-ins is meant to process the packet captured but some are meant for detection of anomalies also. Hence we are implementing a preprocessor plug-in for Snort meant for anomaly detection approach using the machine learning algorithm support vector machine and integrating into Snort. The anomalies detected by the plug-in are new compared with the anomalies detected by the available pre-processor plug-ins. Also we created an intrusion detection dataset which is important for any process using the machine learning algorithms. The detection rate of the plug-in is high and the false alarm rate is low which is very important for any anomaly detection system. Hence integrating this plug-in into Snort helps to improve the detection rate of the plugins that can be run in packet sniffer mode. Copyright 2012 ACM.

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2009

Conference Paper

J. Rajan, Kannan, K., and Dr. Kaimal, M. R., “Smoothening and Sharpening Effects of Theta in Complex Diffusion for Image Processing”, in Seventh International Conference on Advances in Pattern Recognition, , 2009.[Abstract]


In this paper we present a study on how the changing values of theta in complex diffusion affects the images. Normally it is considered that the low value of theta is suitable for image smoothening using complex diffusion, because at higher values of theta the imaginary part may feed back into the real part, creating wave-like ringing effects. Our study shows that as the value of theta increases, ringing effects starts appearing and reaches its peak at 1800 and then it starts disappearing, and the process continues in a 360 degree cycle, where the peak of the wave indicates image with maximum ringing effects (or the maximum sharpened image, property of inverse diffusion). Regarding non-linear complex diffusion we experimentally proved the smoothening is fast at higher values of theta, which can be used for image denoising purpose. More »»

2009

Conference Paper

S. Aji, Jayanthi, T., and Dr. Kaimal, M. R., “Gender Identification in Face Images using KPCA”, in Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on, Coimbatore, 2009.[Abstract]


The data in face images are distributed in a complex manner due to the variation of light intensity, facial expression and pose. In this paper the Kernel Principal Component Analysis (KPCA) is used to extract the feature set of male and female faces. A Gaussian model of skin segmentation method is applied here to exclude the global features such as beard, eyebrow, moustache, etc. both training and test images are randomly selected from four different data bases to improve the training. The experimental results show that the proposed framework is efficient for recognizing the gender of a face image even though it is an impersonation face. More »»

2006

Conference Paper

M. George and Dr. Kaimal, M. R., “On the Storage Capabilities of Radial Basis Function Neural Networks”, in Digital Information Management, 2006 1st International Conference on, Bangalore, 2006.[Abstract]


Pattern classification and function approximation have been found in many applications. The radial basis function network (RBFN) has shown a great promise in this sort of problems because of its faster learning capacity. Though RBFNs have storage properties similar to that ofHopfield networks, these properties have not been well explored so far. In this paper, an approach for analyzing the storage capacity of the RBFN is presented. An upper bound on cost function is found and the error over weighted input vectors is minimized by increasing the number of hidden units. The storage capacity is defined and the proposed method can be used to estimate the capacity in terms of the total probability density function by adding the partial information content associated with each class. More »»

2006

Conference Paper

T. S. Bindulal and Dr. Kaimal, M. R., “Adaptive Scalable Wavelet Difference Reduction Method for Efficient Image Transmission”, in ICVGIP, 2006.[Abstract]


This paper presents a scalable image transmission scheme based on the wavelet-based coding technique supporting region of interest properties. The proposed scheme scalable WDR (SWDR), is based on the wavelet difference reduction scheme, progresses adaptively to get different resolution images at any bit rate required and is supported with the spatial and SNR scalability. The method is developed for the limited bandwidth network where the image quality and data compression are mopst important. Simulations are performed on the medical images, satellite images and Standard test images like Barbara, fingerprint images. The simulation results show that the proposed scheme is up to 20-40% better than other famous scalable schemes like scalable SPIHT coding schemes in terms of signal to noise ratio values (dB) and reduces execution time around 40% in various resolutions. Thus, the proposed scalable coding scheme becomes increasingly important. More »»

2006

Conference Paper

B. T. S. and Dr. Kaimal, M. R., “Embedded WDR algorithm with Selective Region Growing for DICOM Images”, in Proc. of 3rd Workshop on Computer Vision (WCVGIP 2006), Hyderabad, 2006.

2006

Conference Paper

B. T. S. and Dr. Kaimal, M. R., “ Efficient Medical Image Compression and Transmission based on Scalable Wavelet Difference Reduction Method, International Conference on Information and Automation”, in International Conference on Information and Automation, Sri Lanka, 2006.

2006

Conference Paper

J. Rajan and Dr. Kaimal, M. R., “Comparative Analysis of Fourth Order and Complex PDEs for Noise Removal”, in Proc. International Conference on Systemics, Cybernetics and Informatics (ICSCI) , 2006.

2004

Conference Paper

P. P. Mohanlal and Dr. Kaimal, M. R., “Design of optimal fuzzy observer based on TS fuzzy model”, in FUZZ-IEEE, 2004.[Abstract]


In this paper, optimal fuzzy observer is developed for discrete time nonlinear stochastic system based on Takagi-Sugeno (TS) fuzzy model. We design a optimal fuzzy observer using the mathematical duality and by extending the nonlinear Bayesian estimation using Gaussian sum approach to the TS fuzzy model. More »»

2004

Conference Paper

P. P. Mohanlal and Dr. Kaimal, M. R., “Fuzzy modeling and optimal control of nonlinear second order systems”, in FUZZ-IEEE, 2004.[Abstract]


This paper presents the exact fuzzy modeling and optimal control of a class of second order nonlinear dynamic systems. Input saturation, output slew rate limit and nonlinear stiffness are considered. Conventionally, the TSK fuzzy modeling blends local linear models to represent a nonlinear system, which in general does not exactly represent the nonlinear system under consideration. Here, instead of local linear models, a set of 'boundary linear models' (BLM) and associated membership-functions are so chosen that the fuzzy blending of these models result in an exact representation of the overall nonlinear system. An optimal fuzzy controller is designed based on this exact fuzzy model and the results are compared with a conventional design. More »»

2004

Conference Paper

R. Rajesh and Dr. Kaimal, M. R., “Takagi-Sugeno Fuzzy Controller for six dimensional inverted pendulum system”, in Inter. Conf. Systemics, Cybernetics and Informatics, 2004.

2003

Conference Paper

R. Mathew and Dr. Kaimal, M. R., “A Fuzzy Approach to the Game of Chicken Based on Fuzzy Expected Value Models”, in IICAI, 2003.

2002

Conference Paper

P. P. Mohanlal, Dr. Kaimal, M. R., and Dasgupta, S., “Exact Fuzzy Modeling and Optimal control of a Launch Vehicle in the atmospheric phase”, in ICARCV, 2002.[Abstract]


This paper presents a novel method of Exact Fuzzy Modeling and Optimal control of a Launch Vehicle in the atmospheric phase. Time varying plant is considered with control power plant nonlinearity. Plant modeling, controller design and analysis are carried out for Rigid Body with Actuator dynamics. The results are compared with a classical design. Conventionally, the TSK fuzzy modeling blends local linear models to represent a nonlinear system, which in general does not exactly represent the nonlinear system under consideration. Here, instead of local linear models, a set of 'boundary linear models' and associated membership-functions are so chosen that the fuzzy blending of these models result in an exact representation of the overall nonlinear time varying system. Optimal control laws are designed for each of these fuzzy subsystems, and overall control is again the fuzzy blending of these individual control laws. This procedure results in an exact optimal control solution for the Launch Vehicle control in the atmospheric phase. More »»

2002

Conference Paper

R. Rajesh and Dr. Kaimal, M. R., “Automatic Fuzzy Controllers for Gyros.”, in National Systems Society Conference, 2002.

Publication Type: Conference Proceedings

Year of Publication Publication Type Title

2006

Conference Proceedings

R. Rajesh, T. Kumar, S., Dr. Kaimal, M. R., and Suresh, K. K., “Teaching The design of T-S Fuzzy Controllers for an Under-Graduate Course”, Control, Virtual Instrumentation and Digital Systems, Research in Computing Science, vol. 24. pp. pp. 131-140, 2006.

2005

Conference Proceedings

R. Mathew and Dr. Kaimal, M. R., “ Some remarks on the stability conditions of Takagi-Sugeno Fuzzy Controllers”, Proc. of the 8th IASTED International Conference on Intelligent System and Control (ISC-2005). Cambridge, USA, 2005.

2001

Conference Proceedings

M. R. Dr. Kaimal, Bhat, C. S., and , “Application of Chaotic Noise Reduction Techniques to Chaotic data trained by ANN”. Bangalore , 2001.

1997

Conference Proceedings

M. R. Dr. Kaimal, K., M. Y. M., P., B., and P, K. V., “Computer Aided Assessment of Risk of Stone Formation”, Proceedings of the Ninth Kerala Science Congress. pp. pp 391 - 394, 1997.

1994

Conference Proceedings

M. R. Dr. Kaimal and Sherly, E., “ A Neural Network Approach to Air Quality Prediction”, Proceedings of the fifth Kerala Science Congress, . pp. pp. 413 – 416,, 1994.

OTHERS

1. P.P.Mohanlal, M. R. Kaimal, Exact Fuzzy Modelling and Optimal Control of the Inverted Pendulum on Cart,  ICARCV - 2002, Singapore, 2002.

2. P. P. Mohanlal, S Dasgupta , M. R. Kaimal, Exact Fuzzy Modelling and Optimal Control of a Launch Vehicle in the Atmospheric Phase, International (IEEE) Con. of Control., Las Vegas, 2002.

3. R. Rajesh, M. R. Kaimal, Fuzzy Logic Controllers with Guaranteed stability: A design using Genetic Algorithm, High Performance Computing HPC Asia 2002 , Bangalore, 2002.

4. M. R. Kaimal, Liza Jo,  A Progressive Coding Scheme for Efficient Image Compression Using Discrete Cosine Transform, Proceedings of the IEEE Int.Natl.Conf., ADCOM 2000, Cochin, 2000.

5. R. Rajesh, M. R. Kaimal, Design of an Adaptive Fuzzy Logic Controller Using MATLAB, MATLAB India Millennium Conference, MATH WORKS Inc., Bangalore, Nov 2000.

6. Liza Jo, M. R. Kaimal, Preserving Visual Quality in Image Compression Using Self- Organizing Maps, Proc. Of Conference on Engineering Application of Neural Networks (EANN - 99), Poland, September 1999.

7. Liza Jo, M. R. Kaimal, A Self Organizing Neural Network for Second Generation Image Coding, Proceedings of the Turkish Symposium on Artificial Intelligence and Neural Networks (TAINN -99), Turkey, June 1999.

8. Liza Jo, M. R. Kaimal, Image Compression using Self-Organizing Neural Networks,  Proc. National Seminar on Artificial Neural Networks, and Cognitive Systems, CUSAT, September 1998.

9. Liza Jo, M. R. Kaimal, Image Compression Using Self-Organizing Neural Networks Modified to Treat Edge Degradation, Proc. Of International Conference on Cognitive Systems, (ICCS -98), December 1998.

10. M. R. Kaimal, Neuro Fuzzy Systems (in Neuro Fuzzy Control Systems), Narosa Publishing House,    1997.

11. M. R. Kaimal, Chandra Sekhara Bhat,  Identification and construction of Bifurcation diagram of Logistic Map Using artificial neural networks in Neuro Fuzzy Control Systems, Narosa Publishing House,  1997.

12. M. R. Kaimal, Chandra Sekhara Bhat, Application of artificial neural network to chaos proceedings of the 4th international conference on AI Bangalore, published by Tata McGraw Hill Ed. M. Vidyasagar, 1996.

13. Elizabeth Sherly, M. R. Kailmal, An Artificial Neural Network Approach for a Biological Control System, Proceedings of the 4th International Computing Congress, Tata McGraw Hill (Pub), pp 104-110, 1993.

14. A. P. Korah, M. R. Kaimal, Globally Balancing of Binary Search Tree - A Recursive Algorithm, In: Compute Systems and Applications Recent Trends, Tata McGraw Hill (pub), pp 36-43), 1990.

15. M.R. Kaimal, J. L. Stephenson, Analysis of p-Aminohippurate Transport in the Kidney, Proceedings of the Federation of American Societies for Experimental Biology, NEW ORLEANS, USA, 1982.

16.  R. Rajesh, M. R. Kaimal, Automatic Fuzzy Controllers for Gyros., National Systems Society Conference, December 2002.

17. R. Rajesh, P. P. Mohanlal., M. R. Kaimal,  An Optimal Rule generation Scheme Using Genetic Algorithms for the Design of a Fuzzy Logic Controller, Jl of System society of India, 2002.

18. M. R. Kaimal, Marikkar Y. M. K., Brinda P., Kulkarni V. P., Computer Aided Assessment of Risk of Stone Formation, Proceedings of the Ninth Kerala Science Congress, pp 391 - 394, January 1997.

19. M. R. Kaimal, R. Sreekumar, On Selecting Best Replacement Node in Point Quad tree Deletion, SRC-95, Computer Society of India, 1995.

20. M. R. Kaimal, Elizabeth Sherly,  A Neural Network Approach to Air Quality Prediction, Proceedings of the fifth Kerala Science Congress, pp. 413 – 416, 1994.

21. M. R. Kaimal, A. P. Korah, Non- linear Hashing: A fast accessing method for large dynamic files, Proceedings of the fifth Kerala Science Congress, pp. 456 – 460, 1993.

22. M. R. Kaimal, A. P. Korah, Optimal Binary Search Tree and its performance under prolonged Random updates, Proceedings of the Third Kerala Science Congress, pp. 386 – 390, 1991.

23. M. R. Kaimal, Joemon M. Jose, Knowledge Representation: A Fuzzy Approach, 2nd Kerala Science Congress, Trivandrum, February 1990.

24. M. R. Kaimal, A. P. Korah,  A Dynamic Hashing Scheme Achieving One access Retrieval and Insertion, Proceedings of the Second Kerala Science Congress, 1990.

25. M. R. Kaimal, Elizabeth Sherly, Dynamics of Glomerular Filtration - A computer aided study, Proceedings of the National Symposium on Computer-oriented Research in Mathematical Science, pp. 27 - 40, 1989.

26. M. R. Kaimal, Bifurcation Theory: Basic Concepts and some Computational Methods, Presented in the symposium on Bifurcation Theory IMS Conference, December 1985.

27. M. R. Kaimal, Mathematical Models of the Renal Medulla (invited paper presented at the International Symposium on Mathematical Modelling, KANPUR IIT, August 1985.

28. M. R. Kaimal, A Mathematical Model of Urea Cycling in the inner Renal Medulla, Presented at IMS Conference, February 1985.

29. Mercy Mani, M. R. Kaimal, On the Bifurcation solutions of B-Z Reaction Equations, IMS Conference 1985.

30. M. R. Kaimal, On Peristaltic Pumping, Presented at the Second Annual Conference, Alld Math. Sec., Allahabad, 1978.

Ph. D. Thesis Guided

  1. Studies on Non Linear Dynamics of Certain Reaction Systems: Mathematics - Cochin University of Science & Technology, 1989
  2. Data Structures and Applications: (Computer Science - University of Kerala, 1993
  3. Parallel Computing Methodology for Flight Simulation: Computer Science - University of Kerala, 1994
  4. Artificial Neural Network Approach for the Study of Certain Control System: Computer Science - University of Kerala, 1995
  5. Image Representation Techniques: Computer Science - University Of Kerala, 1999
  6. Self Organizing Maps and Transform Coding Methods for Image Compression: University Of Kerala, 1999
  7. Application of ANN approach to the study of Chaotic Systems. University of Kerala, 2002
  8. A Parallel Processing System for on-line Analysis of AE, 2003
  9. Analysis of Game Theory Models using Fuzzy Approaches and Genetic Algorithms. University of Kerala, 2005
  10. Development of Methodologies for the Design and Analysis Optimal Fuzzy logic Controllers and Models. University of Kerala, 2005
  11. Fuzzy Models and Model Based Control for Non-linear Systems. University of Kerala, 2005
  12. Artificial Neural Networks in Pattern Storage. University of Kerala, 2008
  13. Neuro-Fuzzy Approach for the Analysis of Myocardial Infarction.University of Kerala, 2008
  14. Adaptive Coding Techniques for Efficient Image Processing, 2009

No. of students presently working for Ph.D : 5

M.Phil. / M.Tech. : He also guided more than 40 M. Tech. Dissertation works.

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