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Stephen G. Matthews

Stephen G. Matthews

About

21
Publications
2,401
Reads
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367
Citations
Additional affiliations
October 2014 - June 2018
Newcastle University
Position
  • Research Associate
October 2012 - October 2014
University of Bristol
Position
  • Research Assistant

Publications

Publications (21)
Article
We address the use of accelerometery to automatically monitor lying behaviour in free-farrowing sows; due to their freedom of movement and the consequent increased variety of movements the sows are able to exhibit, the challenges in automating this are greater than in sows housed in movement restricting farrowing environments. The methodology devel...
Article
Full-text available
Since animals express their internal state through behaviour, changes in said behaviour may be used to detect early signs of problems, such as in animal health. Continuous observation of livestock by farm staff is impractical in a commercial setting to the degree required to detect behavioural changes relevant for early intervention. An automated m...
Article
Full-text available
Early detection of health and welfare compromises in commercial piggeries is essential for timely intervention to enhance treatment success, reduce impact on welfare, and promote sustainable pig production. Behavioural changes that precede or accompany subclinical and clinical signs may have diagnostic value. Often referred to as sickness behaviour...
Conference Paper
Full-text available
Evolvability is the capacity of a genotype to rapidly adjust to certain types of environmental challenges or opportunities. This capacity, documented in nature, reflects foresight enabled by the capacity of evolution to capture and represent regularities not only in extant environments, but in the ways in which the environments tend to change. Here...
Conference Paper
Projected clustering discovers clusters in subsets of locally relevant attributes. There is uncertainty and imprecision about how groups of categorical values are learnt from data for projected clustering and also the data itself. A method is presented for learning discrete possibility distributions of categorical values from data for projected clu...
Conference Paper
Sigma count measures scalar cardinality of fuzzy sets. A problem with sigma count is that values of scalar cardinality are calculated entirely from many small membership grades or entirely from few large membership grades. Two novel scalar cardinality measures are proposed for the fitness of a genetic algorithm for tuning membership functions prior...
Article
In Web usage mining, fuzzy association rules that have a temporal property can provide useful knowledge about when associations occur. However, there is a problem with traditional temporal fuzzy association rule mining algorithms. Some rules occur at the intersection of fuzzy sets’ boundaries where there is less support (lower membership), so the r...
Article
Full-text available
A novel method is presented for mining fuzzy association rules that have a temporal pattern. Our proposed method contributes towards discovering temporal patterns that could otherwise be lost from defining the membership functions before the mining process. The novelty of this research lies in exploring the composition of fuzzy and temporal associa...
Article
The Computational Intelligence Society (CIS), as well as IEEE, strive to assist and support younger members in entering their professional career after graduation. IEEE young professionals are automatically added to the GOLD member community when they graduate. These GOLD benefits are available for the first ten years after graduation from universi...
Conference Paper
Modern organisations now collect very large volumes of data about customers, suppliers and other factors which may impact upon their business. There is a clear need to be able to mine this data and present it to decision makers in a clear and coherent manner. Fuzzy association rules are a popular method to identifying important and meaningful relat...
Conference Paper
Full-text available
This paper reports on an approach that contributes towards the problem of discovering fuzzy association rules that exhibit a temporal pattern. The novel application of the 2-tuple linguistic representation identifies fuzzy association rules in a temporal context, whilst maintaining the interpretability of linguistic terms. Iterative Rule Learning (...
Article
Full-text available
The author talks about the experiences as a computational intelligence (CI) researcher. Building a tool set of nature inspired concepts and methods is a great challenge for young CI researchers, as it requires a broad level of knowledge combining areas of nature, like biology and psychology, with foundational principles of computer science such as...
Conference Paper
Full-text available
We present a novel method for mining itemsets that are both quantitative and temporal, for association rule mining, using multi-objective evolutionary search and optimisation. This method successfully identifies temporal itemsets that occur more frequently in areas of a dataset with specific quantitative values represented with fuzzy sets. Current...
Conference Paper
Full-text available
A novel method for mining association rules that are both quantitative and temporal using a multi-objective evolutionary algorithm is presented. This method successfully identifies numerous temporal association rules that occur more frequently in areas of a dataset with specific quantitative values represented with fuzzy sets. The novelty of this r...
Article
Full-text available
The field of computational intelligence is the successor of artificial intelligence. It combines elements of learning, evolution and fuzzy logic to create programs that can exhibit, to some degree, intelligent behaviour. The last few years have seen a growth in theoretical and practical developments in this field. This paper presents an extensive s...
Conference Paper
Full-text available
A novel framework for mining temporal association rules by discovering itemsets with a genetic algorithm is introduced. Metaheuristics have been applied to association rule mining, we show the efficacy of extending this to another variant - temporal association rule mining. Our framework is an enhancement to existing temporal association rule minin...
Article
Full-text available
This paper demonstrates the concept of adaptive cruise control and vehicle follow-ing where by a safe distance is maintained between vehicles. A follower robot identi-fies a leader by using a stereo vision cam-era that determines the distance between the robots. The speed and direction of the robot are controlled by fuzzy logic controllers. The sys...
Article
Full-text available
You are at a friend's party and the inevitable question arises "What do you do?". It may be an everyday question but for highly technical fields, such as Computational Intelligence (CI), it can be tricky to answer. To reply with something like "AI research into ...", appreciating that CI would sound alien, can lead your new pal, perhaps your next d...

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