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Outputs (45)

A LDA-Based Social Media Data Mining Framework for Plastic Circular Economy (2024)
Journal Article
Xue, Y., Kambhampati, C., Cheng, Y., Mishra, N., Wulandhari, N., & Deutz, P. (2024). A LDA-Based Social Media Data Mining Framework for Plastic Circular Economy. International Journal of Computational Intelligence Systems, 17, Article 8. https://doi.org/10.1007/s44196-023-00375-7

The mass production of plastic waste has caused an urgent worldwide public health crisis. Although government policies and industrial innovation are the driving forces to meet this challenge, trying to understand public attitudes may improve the effi... Read More about A LDA-Based Social Media Data Mining Framework for Plastic Circular Economy.

Dynamic risk stratification using Markov chain modelling in patients with chronic heart failure (2022)
Journal Article
Kazmi, S., Kambhampati, C., Cleland, J., Cuthbert, J., Kazmi, K. S., Pellicori, P., …Clark, A. L. (2022). Dynamic risk stratification using Markov chain modelling in patients with chronic heart failure. ESC Heart Failure, https://doi.org/10.1002/ehf2.14028

Aims: Risk changes with the progression of disease and the impact of treatment. We developed a dynamic risk stratification Markov chain model using artificial intelligence in patients with chronic heart failure (CHF). Methods and results: We describe... Read More about Dynamic risk stratification using Markov chain modelling in patients with chronic heart failure.

Locally fitting hyperplanes to high-dimensional data (2022)
Journal Article
Hou, M., & Kambhampati, C. (2022). Locally fitting hyperplanes to high-dimensional data. Neural Computing and Applications, 34(11), 8885-8896. https://doi.org/10.1007/s00521-022-06909-y

Problems such as data compression, pattern recognition and artificial intelligence often deal with a large data sample as observations of an unknown object. An effective method is proposed to fit hyperplanes to data points in each hypercubic subregio... Read More about Locally fitting hyperplanes to high-dimensional data.

Addressing Optimisation Challenges for Datasets with Many Variables, Using Genetic Algorithms to Implement Feature Selection (2022)
Journal Article
Gordon, N., Kambhampati, C., & Alabad, A. (2022). Addressing Optimisation Challenges for Datasets with Many Variables, Using Genetic Algorithms to Implement Feature Selection. AI, Computer Science and Robotics Technology, 1, 1-21. https://doi.org/10.5772/acrt.01

This article provides an optimisation method using a Genetic Algorithm approach to apply feature selection techniques for large data sets to improve accuracy. This is achieved through improved classification, a reduced number of features, and further... Read More about Addressing Optimisation Challenges for Datasets with Many Variables, Using Genetic Algorithms to Implement Feature Selection.

Genetic Algorithms as a Feature Selection Tool in Heart Failure Disease (2020)
Journal Article
Alabed, A., Kambhampati, C., & Gordon, N. (in press). Genetic Algorithms as a Feature Selection Tool in Heart Failure Disease. Advances in Intelligent Systems and Computing, 1229 AISC, 531-543. https://doi.org/10.1007/978-3-030-52246-9_38

A great wealth of information is hidden in clinical datasets, which could be analyzed to support decision-making processes or to better diagnose patients. Feature selection is one of the data pre-processing that selects a set of input features by rem... Read More about Genetic Algorithms as a Feature Selection Tool in Heart Failure Disease.

Ionic Imbalances and Coupling in Synchronization of Responses in Neurons (2019)
Journal Article
Sadegh-Zadeh, S., Kambhampati, C., & Davis, D. N. (2019). Ionic Imbalances and Coupling in Synchronization of Responses in Neurons. J — Multidisciplinary Scientific Journal, 2(1), 17-40. https://doi.org/10.3390/j2010003

Most neurodegenerative diseases (NDD) are a result of changes in the chemical composition of neurons. For example, Alzheimer's disease (AD) is the product of Aβ peptide deposition which results in changes in the ion concentration. These changes in io... Read More about Ionic Imbalances and Coupling in Synchronization of Responses in Neurons.

Computational methods toward early detection of neuronal deterioration (2019)
Thesis
Sadegh-Zadeh, S. (2019). Computational methods toward early detection of neuronal deterioration. (Thesis). University of Hull. Retrieved from https://hull-repository.worktribe.com/output/4221749

In today's world, because of developments in medical sciences, people are living longer, particularly in the advanced countries. This increasing of the lifespan has caused the prevalence of age-related diseases like Alzheimer’s and dementia. Research... Read More about Computational methods toward early detection of neuronal deterioration.

Autoencoder for clinical data analysis and classification : data imputation, dimensional reduction, and pattern recognition (2017)
Thesis
Al Khaldy, M. (2017). Autoencoder for clinical data analysis and classification : data imputation, dimensional reduction, and pattern recognition. (Thesis). University of Hull. Retrieved from https://hull-repository.worktribe.com/output/4224219

Over the last decade, research has focused on machine learning and data mining to develop frameworks that can improve data analysis and output performance; to build accurate decision support systems that benefit from real-life datasets. This leads to... Read More about Autoencoder for clinical data analysis and classification : data imputation, dimensional reduction, and pattern recognition.

Data mining for heart failure : an investigation into the challenges in real life clinical datasets (2015)
Thesis
Kirke, L. (2015). Data mining for heart failure : an investigation into the challenges in real life clinical datasets. (Thesis). University of Hull. Retrieved from https://hull-repository.worktribe.com/output/4218159

Clinical data presents a number of challenges including missing data, class imbalance, high dimensionality and non-normal distribution. A motivation for this research is to investigate and analyse the manner in which the challenges affect the perform... Read More about Data mining for heart failure : an investigation into the challenges in real life clinical datasets.

Practical approaches to mining of clinical datasets : from frameworks to novel feature selection (2014)
Thesis
Poolsawad, N. (2014). Practical approaches to mining of clinical datasets : from frameworks to novel feature selection. (Thesis). University of Hull. Retrieved from https://hull-repository.worktribe.com/output/4215841

Research has investigated clinical data that have embedded within them numerous complexities and uncertainties in the form of missing values, class imbalances and high dimensionality. The research in this thesis was motivated by these challenges to m... Read More about Practical approaches to mining of clinical datasets : from frameworks to novel feature selection.

Issues in the mining of heart failure datasets (2014)
Journal Article
Poolsawad, N., Moore, L., Kambhampati, C., & Cleland, J. G. (2014). Issues in the mining of heart failure datasets. International Journal of Automation and Computing, 11(2), 162-179. https://doi.org/10.1007/s11633-014-0778-5

This paper investigates the characteristics of a clinical dataset using a combination of feature selection and classification methods to handle missing values and understand the underlying statistical characteristics of a typical clinical dataset. Ty... Read More about Issues in the mining of heart failure datasets.

CernoCAMAL : a probabilistic computational cognitive architecture (2012)
Thesis
Miri, H. (2012). CernoCAMAL : a probabilistic computational cognitive architecture. (Thesis). University of Hull. Retrieved from https://hull-repository.worktribe.com/output/4214117

This thesis presents one possible way to develop a computational cognitive architecture, dubbed CernoCAMAL, that can be used to govern artificial minds probabilistically. The primary aim of the CernoCAMAL research project is to investigate how its pr... Read More about CernoCAMAL : a probabilistic computational cognitive architecture.

A comparative study of missing value imputation with multiclass classification for clinical heart failure data (2012)
Conference Proceeding
Zhang, Y., Kambhampati, C., Davis, D. N., Goode, K., & Cleland, J. G. F. (2012). A comparative study of missing value imputation with multiclass classification for clinical heart failure data. In Fuzzy Systems and Knowledge Discovery (FSKD), 2012 9th International Conference on (2840-2844). https://doi.org/10.1109/fskd.2012.6233805

Clinical data often contains missing values. Imputation is one of the best known schemes to overcome the drawbacks associated with missing values in data mining tasks. In this work, we compared several imputation methods and analyzed their performanc... Read More about A comparative study of missing value imputation with multiclass classification for clinical heart failure data.

Distributed on-line safety monitor based on safety assessment model and multi-agent system (2012)
Thesis
Dheedan, A. A. (2012). Distributed on-line safety monitor based on safety assessment model and multi-agent system. (Thesis). University of Hull. Retrieved from https://hull-repository.worktribe.com/output/4213377

On-line safety monitoring, i.e. the tasks of fault detection and diagnosis, alarm annunciation, and fault controlling, is essential in the operational phase of critical systems. Over the last 30 years, considerable work in this area has resulted in a... Read More about Distributed on-line safety monitor based on safety assessment model and multi-agent system.

A numerical model for Hodgkin-Huxley neural stimulus reconstruction (2011)
Journal Article
Kambhampati, C., & Sarangdhar, M. (2011). A numerical model for Hodgkin-Huxley neural stimulus reconstruction. Iaeng International Journal of Computer Science, 38(1), 89--94

The information about a neural activity is encoded in a neural response and usually the underlying stimulus that triggers the activity is unknown. This paper presents a numerical solution to reconstruct stimuli from Hodgkin-Huxley neural responses wh... Read More about A numerical model for Hodgkin-Huxley neural stimulus reconstruction.

Navigation in unknown environment by building instantaneous spatial structures (2011)
Thesis
Hu, N. (2011). Navigation in unknown environment by building instantaneous spatial structures. (Thesis). University of Hull. Retrieved from https://hull-repository.worktribe.com/output/4210971

A strategy typically employed for mobile robot navigation in an unknown environment is to follow a nominal straight-line path to the goal point. During travelling on the nominal path, the robot uses distance information, e.g. derived from sonar senso... Read More about Navigation in unknown environment by building instantaneous spatial structures.

Stimulus reconstruction from a Hodgkin-Huxley neural response: A numerical solution (2010)
Conference Proceeding
Sarangdhar, M., & Kambhampati, C. (2010). Stimulus reconstruction from a Hodgkin-Huxley neural response: A numerical solution. In Proceedings of the World Congress on Engineering (627 - 632)

Neural responses are the fundamental expressions of any neural activity. Information carried by a neural response is determined by the nature of a neural activity. In majority of cases the underlying stimulus that triggers it remains largely... Read More about Stimulus reconstruction from a Hodgkin-Huxley neural response: A numerical solution.

Dysphonia measures in parkinson's disease and their use in prediction of its progression (2010)
Conference Proceeding
Kambhampati, C., Sarangdhar, M., & Poolsawad, N. (2010). Dysphonia measures in parkinson's disease and their use in prediction of its progression.

Parkinson's Disease (PD) is a neurodegenerative disorder that impairs the motor skills, speech and general muscle coordination. The progression of PD is assessed using a clinically defined rating scale known as Unified Parkinson's Disease Rating Scal... Read More about Dysphonia measures in parkinson's disease and their use in prediction of its progression.

Spiking neurons and synaptic stimuli: Neural response comparison using coincidence-factor (2009)
Book Chapter
Sarangdhar, M., & Kambhampati, C. (2009). Spiking neurons and synaptic stimuli: Neural response comparison using coincidence-factor. In S. Ao, & L. Gelman (Eds.), Lecture Notes in Electrical Engineering; Advances in Electrical Engineering and Computational Science (681-692). Springer Verlag. https://doi.org/10.1007/978-90-481-2311-7_58

In this chapter, neural responses are generated by changing the Inter-Spike-Interval (ISI) of the stimulus. These responses are subsequently compared and a coincidence factor is obtained. Coincidence-factor, a measure of similarity, is expected to ge... Read More about Spiking neurons and synaptic stimuli: Neural response comparison using coincidence-factor.

Predicting cardiovascular risks using pattern recognition and data mining. (2009)
Thesis
Nguyen, T. T. T. (2009). Predicting cardiovascular risks using pattern recognition and data mining. (Thesis). University of Hull. Retrieved from https://hull-repository.worktribe.com/output/4209582

This thesis presents the use of pattern recognition and data mining techniques into risk prediction models in the clinical domain of cardiovascular medicine. The data is modelled and classified by using a number of alternative pattern recognition and... Read More about Predicting cardiovascular risks using pattern recognition and data mining..

Quantum recurrent neural networks for filtering (2009)
Thesis
Ahamed, W. U. (2009). Quantum recurrent neural networks for filtering. (Thesis). University of Hull. Retrieved from https://hull-repository.worktribe.com/output/4209270

The essence of stochastic filtering is to compute the time-varying probability densityfunction (pdf) for the measurements of the observed system. In this thesis, a filter isdesigned based on the principles of quantum mechanics where the schrodinger w... Read More about Quantum recurrent neural networks for filtering.

Robust FDI for FTC coordination in a distributed network system (2008)
Journal Article
Klinkhieo, S., Patton, R. J., & Kambhampati, C. (2008). Robust FDI for FTC coordination in a distributed network system. IFAC Proceedings Volumes/ International Federation of Automatic Control, 41(2), 13551-13556. https://doi.org/10.3182/20080706-5-KR-1001.0468

This paper focuses on the development of a suitable Fault Detection and Isolation (FDI) strategy for application to a system of inter-connected and distributed systems, as a basis for a fault-tolerant Network Control System (NCS) problem. The work fo... Read More about Robust FDI for FTC coordination in a distributed network system.

Spiking neurons and synaptic stimuli : determining the fidelity of coincidence-factor in neural response comparison (2008)
Journal Article
Kambhampati, C., & Sarangdhar, M. (2008). Spiking neurons and synaptic stimuli : determining the fidelity of coincidence-factor in neural response comparison. Engineering Letters International Association of Engineers, 16(4), 512-517

Similarity between two spike trains is generally estimated using a ‘coincidence factor’. This factor relies on counting coincidences of firing-times for spikes in a given time window. However, in cases where there are significant fluctuations in memb... Read More about Spiking neurons and synaptic stimuli : determining the fidelity of coincidence-factor in neural response comparison.

Spiking neurons: Is coincidence-factor enough for comparing responses with fluctuating membrane voltage? (2008)
Conference Proceeding
Sarangdhar, M., & Kambhampati, C. (2008). Spiking neurons: Is coincidence-factor enough for comparing responses with fluctuating membrane voltage?. In Proceedings of the World Congress on Engineering (1640 - 1645)

Similarity between two spike trains is generally estimated using a ‘coincidence factor’. This factor relies on counting coincidences of firing-times for spikes in a given time window. However, in cases where there are significant fluctuations in memb... Read More about Spiking neurons: Is coincidence-factor enough for comparing responses with fluctuating membrane voltage?.

Stable quantum filters with scattering phenomena (2008)
Journal Article
Ahamed, W. U., & Kambhampati, C. (2008). Stable quantum filters with scattering phenomena. International Journal of Automation and Computing, 5(2), 132-137. https://doi.org/10.1007/s11633-008-0132-x

Quantum neural network filters for signal processing have received a lot of interest in the recent past. The implementations of these filters had a number of design parameters that led to numerical inefficiencies. At the same time the solution proced... Read More about Stable quantum filters with scattering phenomena.

Autonomous clustering using rough set theory (2008)
Journal Article
Bean, C., & Kambhampati, C. (2008). Autonomous clustering using rough set theory. International Journal of Automation and Computing, 5(1), 90-102. https://doi.org/10.1007/s11633-008-0090-3

This paper proposes a clustering technique that minimizes the need for subjective human intervention and is based on elements of rough set theory (RST). The proposed algorithm is unified in its approach to clustering and makes use of both local and g... Read More about Autonomous clustering using rough set theory.

A generic strategy for fault-tolerance in control systems distributed over a network (2007)
Journal Article
Patton, R. J., Kambhampati, C., Casavola, A., Zhang, P., Ding, S., & Sauter, D. (2007). A generic strategy for fault-tolerance in control systems distributed over a network. European journal of control / EUCA, European Control Association, 13(2-3), 280-296. https://doi.org/10.3166/ejc.13.280-296

This paper provides a tutorial overview, of a number of aspects and approaches to Control over the Network for Network Control Systems (NCS) that are likely to lead to good fault-tolerant control properties, subject to network faults. In order to ana... Read More about A generic strategy for fault-tolerance in control systems distributed over a network.

An interaction predictive approach to fault-tolerant control in network control systems (2007)
Journal Article
Kambhampati, C., Perkgoz, C., Patton, R. J., & Ahamed, W. (2007). An interaction predictive approach to fault-tolerant control in network control systems. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 221(6), 885-894. https://doi.org/10.1243/09596518jsce377

This paper illustrates some of the capabilities of previously proposed network control system (NCS) architectures to carry on functioning in the event of faults, without recourse to system reconfiguration. The principle of interaction prediction is u... Read More about An interaction predictive approach to fault-tolerant control in network control systems.

Neural observer by coordinate transformation (2005)
Journal Article
Delgado, A., Hou, M., & Kambhampati, C. (2005). Neural observer by coordinate transformation. IEE Proceedings Control Theory and Applications, 152(6), 698-706. https://doi.org/10.1049/ip-cta%3A20045069

Nonlinear control affine systems with maximum relative degree and a class of nonlinear differential equations can be transformed into a state representation known as the normal form. Based on the normal form an observer is designed using neural netwo... Read More about Neural observer by coordinate transformation.

Artificial intelligence in medicine (2004)
Journal Article
Ramesh, A., Kambhampati, C., Monson, J., & Drew, P. (2004). Artificial intelligence in medicine. Annals of the Royal College of Surgeons of England, 86(5), 334-338. https://doi.org/10.1308/147870804290

INTRODUCTION Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting outcome in ma... Read More about Artificial intelligence in medicine.

The current opinion on the use of robots for landmine detection (2003)
Journal Article
Rajasekharan, S., & Kambhampati, C. (2003). The current opinion on the use of robots for landmine detection. Proceedings / IEEE International Conference on Robotics and Automation, 3, 4252-4257. https://doi.org/10.1109/robot.2003.1242257

Anti-Personal landmines are a significant barrier to economic and social development in a number of countries. Several sensors have been developed but each one will probably have to find, if it exists, a specific area of applicability, determined by... Read More about The current opinion on the use of robots for landmine detection.

A stable one-step-ahead predictive control of non-linear systems (2000)
Journal Article
Kambhampati, C., Mason, J. D., & Warwick, K. (2000). A stable one-step-ahead predictive control of non-linear systems. Automatica : the journal of IFAC, the International Federation of Automatic Control, 36(4), 485-495. https://doi.org/10.1016/s0005-1098%2899%2900173-9

In this paper stability of one-step ahead predictive controllers based on non-linear models is established. It is shown that, under conditions which can be fulfilled by most industrial plants, the closed-loop system is robustly stable in the presence... Read More about A stable one-step-ahead predictive control of non-linear systems.

Stable linearization using multilayer neural networks (1996)
Conference Proceeding
Delgado, A., Kambhampati, C., & Warwick, K. (1996). Stable linearization using multilayer neural networks. . https://doi.org/10.1049/cp%3A19960551

The main limitation of linearization theory that prevents its application in practical problems is the need for an exact knowledge of the plant. This requirement is eliminated and it is shown that a multilayer network can synthesise the state feedbac... Read More about Stable linearization using multilayer neural networks.

The relative order of a class of recurrent networks (1994)
Conference Proceeding
Manchanda, S., Kambhampati, C., Tham, M., & Green, G. (1994). The relative order of a class of recurrent networks. . https://doi.org/10.1049/cp%3A19940266

Three types of recurrent network configurations have been proposed since they enable adequate description of temporal behaviour. The concept of relative order has been introduced so as to provide a framework for analysing such network configurations.... Read More about The relative order of a class of recurrent networks.

Approaches to the optimizing control problem (1988)
Journal Article
Ellis, J. E., Kambhampati, C., Sheng, G., & Roberts, P. D. (1988). Approaches to the optimizing control problem. International Journal of Systems Science, 19(10), 1969-1985. https://doi.org/10.1080/00207728808964092

The selection of the steady-state controls which enable a system to operate in an optimum manner is the optimizing control problem. An examination of direct and adaptive model-based approaches to this problem is made. In the direct approach, system m... Read More about Approaches to the optimizing control problem.