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All Outputs (29)

A systematic review of adaptive wildlife management for the control of invasive, non-native mammals, and other human–wildlife conflicts (2020)
Journal Article
Richardson, S., Mill, A., Davis, D., Jam, D., & Ward, A. (2020). A systematic review of adaptive wildlife management for the control of invasive, non-native mammals, and other human–wildlife conflicts. Mammal Review, 50(2), 147-156. https://doi.org/10.1111/mam.12182

1. We are entering an era where species declines are occurring at their fastest ever rate, and the increased spread of non-native species is among the top causes. High uncertainty in biological processes makes the accurate prediction of the outcomes... Read More about A systematic review of adaptive wildlife management for the control of invasive, non-native mammals, and other human–wildlife conflicts.

DMP_MI: an effective diabetes mellitus classification algorithm on imbalanced data with missing values (2019)
Journal Article
Wang, Q., Cao, W., Guo, J., Ren, J., Cheng, Y., & Davis, D. N. (2019). DMP_MI: an effective diabetes mellitus classification algorithm on imbalanced data with missing values. IEEE Access, 7, 102232-102238. https://doi.org/10.1109/ACCESS.2019.2929866

© 2019 Institute of Electrical and Electronics Engineers Inc.. All rights reserved. As a widely known chronic disease, diabetes mellitus is called a silent killer. It makes the body produce less insulin and causes increased blood sugar, which leads t... Read More about DMP_MI: an effective diabetes mellitus classification algorithm on imbalanced data with missing values.

Ionic Imbalances and Coupling in Synchronization of Responses in Neurons (2019)
Journal Article
Sadegh-Zadeh, S.-A., 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.

An adaptive ensemble approach to ambient intelligence assisted people search (2018)
Journal Article
Xue, D., Wang, X., Zhu, J., Davis, D. N., Wang, B., Zhao, W., Peng, Y., & Cheng, Y. (2018). An adaptive ensemble approach to ambient intelligence assisted people search. Applied System Innovation, 1(3), 1-18. https://doi.org/10.3390/asi1030033

Some machine learning algorithms have shown a better overall recognition rate for facial recognition than humans, provided that the models are trained with massive image databases of human faces. However, it is still a challenge to use existing algor... Read More about An adaptive ensemble approach to ambient intelligence assisted people search.

Security feature measurement for frequent dynamic execution paths in software system (2018)
Journal Article
Wang, Q., Ren, J., Yang, X., Cheng, Y., Davis, D. N., & Hu, C. (2018). Security feature measurement for frequent dynamic execution paths in software system. Security and communication networks, 2018, 1-10. https://doi.org/10.1155/2018/5716878

© 2018 Qian Wang et al. The scale and complexity of software systems are constantly increasing, imposing new challenges for software fault location and daily maintenance. In this paper, the Security Feature measurement algorithm of Frequent dynamic e... Read More about Security feature measurement for frequent dynamic execution paths in software system.

Capturing the dynamics of cellular automata, for the generation of synthetic persian music, using conditional restricted Boltzmann machines (2017)
Book Chapter
Davis, D. N., & Arshi, S. (2017). Capturing the dynamics of cellular automata, for the generation of synthetic persian music, using conditional restricted Boltzmann machines. In Artificial Intelligence XXXIV; Lecture Notes in Computer Science (72-86). Springer Verlag. https://doi.org/10.1007/978-3-319-71078-5_6

© Springer International Publishing AG 2017. In this paper the generative and feature extracting powers of the family of Boltzmann Machines are employed in an algorithmic music composition system. Liquid Persian Music (LPM) system is an audio generat... Read More about Capturing the dynamics of cellular automata, for the generation of synthetic persian music, using conditional restricted Boltzmann machines.

Reasoning with BDI robots: from simulation to physical environment – implementations and limitations (2017)
Journal Article
Davis, D. N., & Ramulu, S. K. (2017). Reasoning with BDI robots: from simulation to physical environment – implementations and limitations. Paladyn journal of behavioural robotics, 8(1), 39-57. https://doi.org/10.1515/pjbr-2017-0003

In this paper an overview of the state of research into cognitive robots is given. This is driven by insights arising from research that has moved from simulation to physical robots over the course of a number of sub-projects. A number of major issue... Read More about Reasoning with BDI robots: from simulation to physical environment – implementations and limitations.

An algorithm for fast mining top-rank-k frequent patterns based on node-list data structure (2017)
Journal Article
Wang, Q., Ren, J., N Davis, D., & Cheng, Y. (2018). An algorithm for fast mining top-rank-k frequent patterns based on node-list data structure. Intelligent Automation and Soft Computing, 24(2), 399-404. https://doi.org/10.1080/10798587.2017.1340135

Frequent pattern mining usually requires much run time and memory usage. In some applications, only the patterns with top frequency rank are needed. Because of the limited pattern numbers, quality of the results is even more important than time and m... Read More about An algorithm for fast mining top-rank-k frequent patterns based on node-list data structure.

Combining depth and intensity images to produce enhanced object detection for use in a robotic colony (2017)
Journal Article
Balding, S., & Davis, D. N. (2017). Combining depth and intensity images to produce enhanced object detection for use in a robotic colony. Lecture notes in computer science, 10454, 115-125. https://doi.org/10.1007/978-3-319-64107-2_10

Robotic colonies that can communicate with each other and interact with their ambient environments can be utilized for a wide range of research and industrial applications. However amongst the problems that these colonies face is that of the isolatin... Read More about Combining depth and intensity images to produce enhanced object detection for use in a robotic colony.

Analysis of the EPSRC Principles of Robotics in regard to key research topics (2017)
Journal Article
Gning, A., Davis, D. N., Cheng, Y., & Robinson, P. (2017). Analysis of the EPSRC Principles of Robotics in regard to key research topics. Connection Science, 29(3), 249-253. https://doi.org/10.1080/09540091.2017.1323456

© 2017 Informa UK Limited, trading as Taylor & Francis Group. In this paper, we review the five rules published in EPSRC Principles of Robotics with a specific focus on future robotics research topics. It is demonstrated through a pictorial represe... Read More about Analysis of the EPSRC Principles of Robotics in regard to key research topics.

Artificial minds with consciousness and common sense aspects (2017)
Journal Article
Shylaja, K., Vijayakumar, M., Prasad, E. V., & Davis, D. N. (2017). Artificial minds with consciousness and common sense aspects. International journal of agent technologies and systems, 9(1), 20-42. https://doi.org/10.4018/ijats.2017010102

The research work presented in this article investigates and explains the conceptual mechanisms of consciousness and common-sense thinking of animates. These mechanisms are computationally simulated on artificial agents as strategic rules to analyze... Read More about Artificial minds with consciousness and common sense aspects.

Missing Value Imputation Using Stratified Supervised Learning for Cardiovascular Data (2016)
Journal Article
Davis, D., & Rahman, M. (2016). Missing Value Imputation Using Stratified Supervised Learning for Cardiovascular Data. Journal of Informatics and Data Mining, 1(2), Article 13. https://doi.org/10.21767/2472-1956.100013

Legacy (and current) medical datasets are rich source of information and knowledge. However, the use of most legacy medical datasets is beset with problems. One of the most often faced is the problem of missing data, often due to oversights in data c... Read More about Missing Value Imputation Using Stratified Supervised Learning for Cardiovascular Data.

Mining frequent biological sequences based on bitmap without candidate sequence generation (2015)
Journal Article
Wang, Q., Davis, D. N., & Ren, J. (2016). Mining frequent biological sequences based on bitmap without candidate sequence generation. Computers in biology and medicine, 69, 152-157. https://doi.org/10.1016/j.compbiomed.2015.12.016

Biological sequences carry a lot of important genetic information of organisms. Furthermore, there is an inheritance law related to protein function and structure which is useful for applications such as disease prediction. Frequent sequence mining i... Read More about Mining frequent biological sequences based on bitmap without candidate sequence generation.

Fuzzy rule-based system applied to risk estimation of cardiovascular patients (2013)
Journal Article
Bohacik, J., & Davis, D. N. (2013). Fuzzy rule-based system applied to risk estimation of cardiovascular patients. Journal of Multiple-Valued Logic and Soft Computing, 20(5-6), 445-466

Cardiovascular decision support is one area of increasing research interest. On-going collaborations between clinicians and computer scientists are looking at the application of knowledge discovery in databases to the area of patient diagnosis, based... Read More about Fuzzy rule-based system applied to risk estimation of cardiovascular patients.

Diagnosis and management of cardiovascular disease with an intelligent decision-making support system (2012)
Journal Article
Bohacik, J., & Davis, D. (2012). Diagnosis and management of cardiovascular disease with an intelligent decision-making support system. ULAB journal of science and engineering, 3(1), Article 42888

Cardiovascular disease is the principal cause of death in most European countries and may have a major negativeimpact on the patients' functional status, productivity, and quality of life. It seems an automatic decision support system couldlower thes... Read More about Diagnosis and management of cardiovascular disease with an intelligent decision-making support system.

Risk estimation of cardiovascular patients using Weka (2012)
Presentation / Conference Contribution
Bohacik, J., Davis, D., & Benedikovic, M. Risk estimation of cardiovascular patients using Weka. Presented at International Conference on Open Source Software in Education, Research and IT Solution, Zilina, Slovakia

Cardiovascular diseases remain the most prevalent cause of deaths worldwideand their prevention requires major life-style changes using limited health-care resources.Remote decision support for cardiovascular patients seems to allow them to lead a pr... Read More about Risk estimation of cardiovascular patients using Weka.

A comparative study of missing value imputation with multiclass classification for clinical heart failure data (2012)
Presentation / Conference Contribution
Zhang, Y., Kambhampati, C., Davis, D. N., Goode, K., & Cleland, J. G. F. A comparative study of missing value imputation with multiclass classification for clinical heart failure data. Presented at 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery

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.

Alert rules for remote monitoring of cardiovascular patients (2012)
Journal Article
Bohacik, J., & Davis, D. (2012). Alert rules for remote monitoring of cardiovascular patients. Journal of information technologies, 5(1), 16 - 23

Cardiovascular disease is the leading cause of death in most European countries and its prevention requires major life-style changes using limited health-care resources. Remote cardiovascular decision support seems to allow cardiovascular patients to... Read More about Alert rules for remote monitoring of cardiovascular patients.

Data mining applied to cardiovascular data (2010)
Journal Article
Bohacik, J., & Davis, D. (2010). Data mining applied to cardiovascular data. Journal of information technologies, 3(2), 14 - 21

Medical decision support is one area of increasing research interest. Ongoing collaborations between cardiovascular clinicians and computer scientists are looking at the application of data mining techniques to the area of individual patient diagnosi... Read More about Data mining applied to cardiovascular data.