Conor Ryan

Conor Ryan
University of Limerick | UL · Department of Computer Science and Information Systems (CSIS)

About

282
Publications
26,201
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5,176
Citations
Citations since 2017
67 Research Items
1638 Citations
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Introduction
Skills and Expertise

Publications

Publications (282)
Article
Full-text available
Health care interoperability unfolds the way for personalized health care services at a reduced cost. Furthermore, a decentralized system holds the promise to prevent compromises such as cyber‐attacks due to data breaches. Hence, there is a need for a framework that seamlessly integrates and shares data across the system stakeholders. We propose SE...
Article
Full-text available
A novel approach to induce Fuzzy Pattern Trees using Grammatical Evolution is presented in this paper. This new method, called Fuzzy Grammatical Evolution, is applied to a set of benchmark classification problems. Experimental results show that Fuzzy Grammatical Evolution attains similar and oftentimes better results when compared with state-of-the...
Conference Paper
Full-text available
The ever-present challenge in the domain of digital devices is how to test their behavior efficiently. We tackle the issue in two ways. We switch to an automated circuit design using Grammatical Evolution (GE). Additionally, we provide two diversity-based methodologies to improve testing efficiency. The first approach extracts a minimal number of t...
Conference Paper
With the growing popularity of machine learning (ML), regression problems in many domains are becoming increasingly high-dimensional. Identifying relevant features from a high-dimensional dataset still remains a significant challenge for building highly accurate machine learning models. Evolutionary feature selection has been used for high-dimensio...
Chapter
Digital circuits are one of the most important enabling technologies in the world today. Powerful tools, such as Hardware Description Languages (HDLs) have evolved over the past number of decades to allow designers to operate at high levels of abstraction and expressiveness, rather than at the gate level, which circuits are actually constructed fro...
Article
Full-text available
This work investigates the potential for using Grammatical Evolution (GE) to generate an initial seed for the construction of a pseudo-random number generator (PRNG) and cryptographically secure (CS) PRNG. We demonstrate the suitability of GE as an entropy source and show that the initial seeds exhibit an average entropy value of 7.940560934 for 8-...
Article
Full-text available
The evolution of complex circuits remains a challenge for the Evolvable Hardware field in spite much effort. There are two major issues: the amount of testing required and the low evolvability of representation structures to handle complex circuitry, at least partially due to the destructive effects of genetic operators. A 64-bit $$\times$$ × 64-bi...
Article
Full-text available
Fuzzy pattern trees evolved using grammatical evolution, a system we call Fuzzy Grammatical Evolution, are shown to be a robust Explainable Artificial Intelligence technique. Experimental results show Fuzzy Grammatical Evolution achieves competitive results when compared against SVM, Random Forest and Logistic Regression on a set of real world benc...
Article
Full-text available
The advent of cloud-based super-computing platforms has given rise to a Data Science (DS) boom. Many types of technological problems that were once considered prohibitively expensive to tackle are now candidates for exploration. Machine Learning (ML) tools that were valued only in academic environments are quickly being embraced by industrial giant...
Conference Paper
Full-text available
Deep learning (DL) networks have the dual benefits due to over parameterization and regularization rendering them more accurate than conventional Machine Learning (ML) models. However, they consume massive amounts of resources in training and thus are computationally expensive. A single experimental run consumes a lot of computational resources, in...
Article
Full-text available
Over the past seven decades since the advent of artificial intelligence (AI) technology, researchers have demonstrated and deployed systems incorporating AI in various domains. The absence of model explainability in critical systems such as medical AI and credit risk assessment among others has led to neglect of key ethical and professional princip...
Conference Paper
Full-text available
Deep learning is an excellent way for effectively addressing image processing, and several Neural Networks designs have been explored in this area. The Spatial Attention U-Net architecture, a version of the famous U-Net but which uses DropBlock and an attention block as well as the common U-Net convolutional blocks, is one notable example. Finding...
Preprint
Full-text available
This work investigates the potential of evolving an initial seed with Grammatical Evolution (GE), for the construction of cryptographically secure (CS) pseudo-random number generator (PRNG). We harness the flexibility of GE as an entropy source for returning initial seeds. The initial seeds returned by GE demonstrate an average entropy value of 7.9...
Article
Full-text available
NAND flash memory – ubiquitous in today’s world of smart phones, SSDs (solid state drives), and cloud storage – has a number of well-known reliability problems. NAND data contains bit errors, which require the use of error correcting codes (ECCs). The raw bit error rate (RBER) increases with program-erase (P-E) cycling, and the number of P-E cycles...
Conference Paper
The desire of human intelligence to surpass its potential has triggered the emergence of artificial intelligence and machine learning. Over the last seven decades, these terms have gained much prominence in the digital arena due to its wide adoption of techniques for designing affluent industry-enabled solutions. In this comprehensive survey on art...
Article
Full-text available
Heuristic-based optimization techniques have been increasingly used to automate different types of code coverage analysis. Several studies suggest that interdependencies (in the form of comparisons) may exist between the condition constructs, of variables and constant values, in the branching conditions of real-world programs, e.g. (i≤100\documentc...
Conference Paper
The computational complexity of Evolutionary Algorithms (EAs) is a well-known concern. This paper is concerned with the resource consumption of GELAB, a novel Grammatical Evolution (GE) system implemented in Matlab. GE is an evolutionary technique for program search that manipulates large populations of computer programs over multiple generations....
Conference Paper
Diversity is a much sought after aspect of any evolutionary system. More diversity means a cornucopia of diverse behaviors and traits among the individuals of a population. Lack of diversity, on the other hand, leads to a stagnant population whose individuals are more or less similar to each other. Subsequently, they fail to produce a variety of of...
Conference Paper
Full-text available
Following the development of Information Technology (IT) techniques, data and the knowledge behind data have been increased exponentially today. The goals to better manage and share such massive big data become more and more critical in many prominent Artificial Intelligence (AI)-based smart industries. Smart healthcare is a typical example in thes...
Article
Full-text available
In this article, we discuss a data sharing and knowledge integration framework through autonomous agents with blockchain for implementing Electronic Health Records (EHR). This will enable us to augment existing blockchain-based EHR Systems. We discuss how major concerns in the health industry, i.e., trust, security and scalability, can be addressed...
Chapter
This paper shows empirically that Fuzzy Pattern Trees (FPT) evolved using Grammatical Evolution (GE), a system we call FGE, meet the criteria to be considered a robust Explainable Artificial Intelligence (XAI) system. Experimental results show FGE achieves competitive results against state of the art black box methods on a set of real world benchma...
Chapter
Scalability problems have hindered the progress of Evolvable Hardware in tackling complex circuits. The two key issues are the amount of testing (for example, a 64-bit \(\times \) 64-bit add-shift multiplier problem has \(2^{64 + 64}\) test cases) and low level that hardware works at: a circuit to implement 64-bit \(\times \) 64-bit add-shift multi...
Conference Paper
Elliptic curve is a major area of research due to its application in elliptic curve cryptography. Due to their small key sizes, they offer the twofold advantage of reduced storage and transmission requirements. This also results in faster execution times. The authors propose an architecture to automatically generate test cases, for verification of...
Data
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Chapter
This research investigates the use of Convolutional Neural Networks (CNN) and specifically, You Only Look Once ver. 4 (YOLOv4) to detect Racing Bib Numbers (RBNs) in images from running races and then to recognise the actual numbers using Optical Character Recognition (OCR) techniques. Pre-processing and Tesseract OCR were employed to achieve this....
Conference Paper
The research work proposes a framework for checking the correctness of Galois field arithmetic operations in digital circuits. The authors propose to automatically generate the test cases from the user input, avoiding reliance upon pre-designed test cases, comprising Galois field-width and respective choice of irreducible polynomial. We do this thr...
Conference Paper
Full-text available
The advent of the Covid-19 pandemic has resulted in a global crisis making the health systems vulnerable, challenging the research community to find novel approaches to facilitate early detection of infections. This open-up a window of opportunity to exploit machine learning and artificial intelligence techniques to address some of the issues related...
Conference Paper
Full-text available
Deep learning is a well suited approach to successfully address image processing and there are several Neural Networks architectures proposed on this research field, one interesting example is the U-net architecture and and its variants. This work proposes to automatically find the best architecture combination from a set of the current most releva...
Conference Paper
Full-text available
The objective of the proposed research is to design a system called Green Artificial Intelligence Powered Cost Pricing Models for Congestion Control (GREE-COCO) for road vehicles that address the issue of congestion control through the concept of cost pricing. The motivation is to facilitate smooth traffic flow among densely congested roads by inco...
Conference Paper
Full-text available
The growing interest in the search and use of alternative resources for renewable energy can lead the future towards substantially decreasing carbon footprint and reduce the effects of global warming. The proposed research explores the possibility of harnessing piezoelectric energy from the environment of moving vehicles on road. Although the techn...
Conference Paper
Full-text available
The quality assurance of circuits is of major importance as the complexity of circuits is rising with their capabilities. Thus a high degree of testing is required to guarantee proper operation. If, on the other hand, too much time is spent in testing then this prolongs development time. The work presented in this paper proposes a methodology to se...
Conference Paper
Full-text available
Blood vessel extraction in digital retinal images is an important step in medical image analysis for abnormality detection and also obtaining good retinopathy diabetic diagnosis; this is often referred to as the Retinal Blood Vessel Segmentation task and current state-of-the-art approaches all use some form of neural networks. Designing neural netw...
Chapter
The volatility incorporated in cryptocurrency prices makes it difficult to earn a profit through day trading. Usually, the best strategy is to buy a cryptocurrency and hold it until the price rises over a long period. This project aims to automate short term trading using Reinforcement Learning (RL), predominantly using the Deep Deterministic Polic...
Chapter
Grammatical Evolution (GE) is a well known technique for program synthesis and evolution. Much has been written in the past about its research and applications. This paper presents a novel approach to performing hybrid optimization using GE. GE is used for structural search in the program space while other meta-heuristic algorithms are used for num...
Conference Paper
Exploiting patterns within a solution or reusing certain functionality is often necessary to solve certain problems. This paper proposes a new method for identifying useful modules. Modules are only considered if they are prevalent in the population and they are seen to have a positive effect on an individual's fitness. This is achieved by finding...
Chapter
Software-based optimization techniques have been increasingly used to automate code coverage analysis since the nineties. Although several studies suggest that interdependencies can exist between condition constructs in branching conditions of real life programs e.g. (\(i<=100\)) or (\(i==j\)), etc., to date, only the Ariadne system, a Grammatical...
Conference Paper
This paper introduces a novel approach to induce Fuzzy Pattern Trees (FPT) using Grammatical Evolution (GE), FGE, and applies to a set of benchmark classification problems. While conventionally a set of FPTs are needed for classifiers, one for each class, FGE needs just a single tree. This is the case for both binary and multi-classification probl...
Chapter
Software testing is a key component in software quality assurance; it typically involves generating test data that exercises all instructions and tested conditions in a program and, due to its complexity, can consume as much as 50% of overall software development budget. Some evolutionary computing techniques have been successfully applied to autom...
Chapter
Full-text available
This paper will review the progress which has been made in Artificial Intelligence and Computer Vision particularly in 3D computer vision. There has been a lot of activity in the development of both hardware and software in 3D imaging systems which will have a huge impact in the capabilities of robotics. This paper reviews the latest advancements i...
Chapter
NAND flash memory is now almost ubiquitous in the world of data storage. However, NAND wears out as it is used, and manufacturers specify the number of times a device can be rewritten (known as program-erase cycles) very conservatively to account for quality variations within and across devices. This research uses machine learning to predict the tr...
Article
Full-text available
Although some of the earliest Estimation of Distribution Algorithms (EDAs) utilized bivariate marginal distribution models, up to now, all discrete bivariate EDAs had one serious limitation: they were constrained to exploiting only a limited O(d) subset out of all possible O(d^2) bivari-ate dependencies. As a first we present a family of discrete b...
Conference Paper
Full-text available
Sensors are key components for all types of autonomous vehicles because they can provide the data required to perceive the surrounding environment and therefore aid the decision-making process. This paper explains how each of these sensors work, their advantages and disadvantages and how sensor fusion techniques can be utilized to create a more opt...
Chapter
NAND Flash memory has been the fastest growing technology in the history of semiconductors and is now almost ubiquitous in the world of data storage. However, NAND devices are not error-free and the raw bit error rate (RBER) increases as devices are programmed and erase (P-E cycled). This requires the use of error correction codes (ECCs), which ope...
Chapter
Grammatical Evolution (GE) is a Evolutionary Algorithm (EA) that takes inspiration from the biological evolutionary process to search for solutions to problems. This chapter gives a brief introduction to EAs, paying particular attention to those involved in automatic program generation.We then describe grammars, the core building blocks of programs...
Conference Paper
For some time, there has been a realisation among Genetic Programming researchers that relying on a single scalar fitness value to drive evolutionary search is no longer a satisfactory approach. Instead, efforts are being made to gain richer insights into the complexity of program behaviour. To this end, particular attention has been focused on the...
Conference Paper
In this paper, we propose a hybrid approach to solving multi-class problems which combines evolutionary computation with elements of traditional machine learning. The method, Grammatical Evolution Machine Learning (GEML) adapts machine learning concepts from decision tree learning and clustering methods and integrates these into a Grammatical Evolu...
Article
Full-text available
The authors present a thinly veiled attack on the popular Grammatical Evolution (GE) system, the second in the space of year. The paper presents itself as a philosophical discussion on a framework they present, based on a handful of Sterelny’s guidelines. However, it quickly degenerates into an assault on GE, initially by attributing assumptions to...
Conference Paper
A new family of Estimation of Distribution Algorithms (EDAs) for discrete search spaces is presented. The proposed algorithms, which we label DICE (Discrete Correlated Estimation of distribution algorithms) are based, like previous bivariate EDAs such as MIMIC and BMDA, on bivariate marginal distribution models. However, bivariate models previously...
Conference Paper
Wave is a novel form of semantic genetic programming which operates by optimising the residual errors of a succession of short genetic programming runs, and then producing a cumulative solution. These short genetic programming runs are called periods, and they have heterogeneous parameters. In this paper we leverage the potential of Wave's heteroge...
Conference Paper
We introduce a new approach to the principled design of evolutionary algorithms (EAs) based on kernel methods. We demonstrate how kernel functions, which capture useful problem domain knowledge, can be used to directly construct EA search operators. We test two kernel search operators on a suite of four challenging combinatorial optimization proble...
Conference Paper
Full-text available
This paper introduces a novel evolutionary approach which can be applied to supervised, semi-supervised and unsupervised learning tasks. The method, Grammatical Evolution Machine Learning (GEML) adapts machine learning concepts from decision tree learning and clustering methods, and integrates these into a Grammatical Evolution framework. With mino...
Conference Paper
Full-text available
Significant recent effort in genetic programming has focused on selecting and combining candidate solutions according to a notion of behaviour defined in semantic space and has also highlighted disadvantages of relying on a single scalar measure to capture the complexity of program performance in evolutionary search. In this paper, we take an alter...
Conference Paper
Full-text available
Although very controversial in the field of evolutionary biology, the notion of evolutionary progress is nevertheless generally accepted in the field of Artificial Life. In this article we adopt the definition proposed by Shanahan (2012) to study the existence of evolutionary progress in an evolutionary simulation which we call HetCA. HetCA is a he...
Conference Paper
Full-text available
Typically, Genetic Programming (GP) attempts to solve a problem by evolving solutions over a large, and usually pre-determined number of generations. However, overwhelming evidence shows that not only does the rate of performance improvement drop considerably after a few early generations, but that further improvement also comes at a considerable c...
Conference Paper
Full-text available
Writing parallel programs is a challenging but unavoidable proposition to take true advantage of multi-core processors. In this paper, we extend Multi-core Grammatical Evolution for Parallel Sorting (MCGE-PS) to evolve parallel iterative sorting algorithms while also optimizing their degree of parallelism. We use evolution to optimize the performa...
Conference Paper
Full-text available
We present an automated, end-to-end approach for Stage~1 breast cancer detection. The first phase of our proposed work-flow takes individual digital mammograms as input and outputs several smaller sub-images from which the background has been removed. Next, we extract a set of features which capture textural information from the segmented images. I...
Conference Paper
Full-text available
This work introduces Wave, a divide and conquer approach to GP whereby a sequence of short, and dependent but potentially heterogeneous GP runs provides a collective solution ; the sequence akins a wave such that each short GP run is a period of the wave. Heterogeneity across periods results from varying settings of system parameters, such as popul...