A genetic programming system with an epigenetic mechanism for traffic signal control

Traffic congestion is an increasing problem in most cities around the world. It impacts businesses as well as commuters, small cities and large ones in developing as well as developed economies. One approach to decrease urban traffic congestion is to optimize the traffic signal behaviour in order to be adaptive to changes in the traffic conditions. From the perspective of intelligent transportation systems, this optimization problem is called the traffic signal control problem and is considered a large combinatorial problem with high complexity and uncertainty. A novel approach to the traffic signal control problem is proposed in this thesis. The approach includes a new mechanism for Genetic Programming inspired by Epigenetics. Epigenetic mechanisms play an important role in biological processes such as phenotype differentiation, memory consolidation within generations and environmentally induced epigenetic modification of behaviour. These properties lead us to consider the implementation of epigenetic mechanisms as a way to improve the performance of Evolutionary Algorithms in solution to real-world problems with dynamic environmental changes, such as the traffic control signal problem. The epigenetic mechanism proposed was evaluated in four traffic scenarios with different properties and traffic conditions using two microscopic simulators. The results of these experiments indicate that Genetic Programming was able to generate competitive actuated traffic signal controllers for all the scenarios tested. Furthermore, the use of the epigenetic mechanism improved the performance of Genetic Programming in all the scenarios. The evolved controllers adapt to modifications in the traffic density and require less monitoring and less human interaction than other solutions because they dynamically adjust the signal behaviour depending on the local traffic conditions at each intersection

A Syntactical Reverse Engineering Approach to Fourth Generation Programming Languages Using Formal Methods

Fourth-generation programming languages (4GLs) feature rapid development with minimum configuration required by developers. However, 4GLs can suffer from limitations such as high maintenance cost and legacy software practices. Reverse engineering an existing large legacy 4GL system into a currently maintainable programming language can be a cheaper and more effective solution than rewriting from scratch. Tools do not exist so far, for reverse engineering proprietary XML-like and model-driven 4GLs where the full language specification is not in the public domain. This research has developed a novel method of reverse engineering some of the syntax of such 4GLs (with Uniface as an exemplar) derived from a particular system, with a view to providing a reliable method to translate/transpile that system's code and data structures into a modern object-oriented language (such as C\#). The method was also applied, although only to a limited extent, to some other 4GLs, Informix and Apex, to show that it was in principle more broadly applicable. A novel testing method that the syntax had been successfully translated was provided using 'abstract syntax trees'. The novel method took manually crafted grammar rules, together with Encapsulated Document Object Model based data from the source language and then used parsers to produce syntactically valid and equivalent code in the target/output language. This proof of concept research has provided a methodology plus sample code to automate part of the process. The methodology comprised a set of manual or semi-automated steps. Further automation is left for future research. In principle, the author's method could be extended to allow the reverse engineering recovery of the syntax of systems developed in other proprietary 4GLs. This would reduce time and cost for the ongoing maintenance of such systems by enabling their software engineers to work using modern object-oriented languages, methodologies, tools and techniques

An evaluation of partial differential equations based digital inpainting algorithms

Partial Differential equations (PDEs) have been used to model various phenomena/tasks in different scientific and engineering endeavours. This thesis is devoted to modelling image inpainting by numerical implementations of certain PDEs. The main objectives of image inpainting include reconstructing damaged parts and filling-in regions in which data/colour information are missing. Different automatic and semi-automatic approaches to image inpainting have been developed including PDE-based, texture synthesis-based, exemplar-based, and hybrid approaches. Various challenges remain unresolved in reconstructing large size missing regions and/or missing areas with highly textured surroundings. Our main aim is to address such challenges by developing new advanced schemes with particular focus on using PDEs of different orders to preserve continuity of textural and geometric information in the surrounding of missing regions. We first investigated the problem of partial colour restoration in an image region whose greyscale channel is intact. A PDE-based solution is known that is modelled as minimising total variation of gradients in the different colour channels. We extend the applicability of this model to partial inpainting in other 3-channels colour spaces (such as RGB where information is missing in any of the two colours), simply by exploiting the known linear/affine relationships between different colouring models in the derivation of a modified PDE solution obtained by using the Euler-Lagrange minimisation of the corresponding gradient Total Variation (TV). We also developed two TV models on the relations between greyscale and colour channels using the Laplacian operator and the directional derivatives of gradients. The corresponding Euler-Lagrange minimisation yields two new PDEs of different orders for partial colourisation. We implemented these solutions in both spatial and frequency domains. We measure the success of these models by evaluating known image quality measures in inpainted regions for sufficiently large datasets and scenarios. The results reveal that our schemes compare well with existing algorithms, but inpainting large regions remains a challenge. Secondly, we investigate the Total Inpainting (TI) problem where all colour channels are missing in an image region. Reviewing and implementing existing PDE-based total inpainting methods reveal that high order PDEs, applied to each colour channel separately, perform well but are influenced by the size of the region and the quantity of texture surrounding it. Here we developed a TI scheme that benefits from our partial inpainting approach and apply two PDE methods to recover the missing regions in the image. First, we extract the (Y, Cb, Cr) of the image outside the missing region, apply the above PDE methods for reconstructing the missing regions in the luminance channel (Y), and then use the colourisation method to recover the missing (Cb, Cr) colours in the region. We shall demonstrate that compared to existing TI algorithms, our proposed method (using 2 PDE methods) performs well when tested on large datasets of natural and face images. Furthermore, this helps understanding of the impact of the texture in the surrounding areas on inpainting and opens new research directions. Thirdly, we investigate existing Exemplar-Based Inpainting (EBI) methods that do not use PDEs but simultaneously propagate the texture and structure into the missing region by finding similar patches within the rest of image and copying them into the boundary of the missing region. The order of patch propagation is determined by a priority function, and the similarity is determined by matching criteria. We shall exploit recently emerging Topological Data Analysis (TDA) tools to create innovative EBI schemes, referred to as TEBI. TDA studies shapes of data/objects to quantify image texture in terms of connectivity and closeness properties of certain data landmarks. Such quantifications help determine the appropriate size of patch propagation and will be used to modify the patch propagation priority function using the geometrical properties of curvature of isophotes, and to improve the matching criteria of patches by calculating the correlation coefficients from the spatial, gradient and Laplacian domains. The performance of this TEBI method will be tested by applying it to natural dataset images, resulting in improved inpainting when compared with other EBI methods. Fourthly, the recent hybrid-based inpainting techniques are reviewed and a number of highly performing innovative hybrid techniques that combine the use of high order PDE methods with the TEBI method for the simultaneous rebuilding of the missing texture and structure regions in an image are proposed. Such a hybrid scheme first decomposes the image into texture and structure components, and then the missing regions in these components are recovered by TEBI and PDE based methods respectively. The performance of our hybrid schemes will be compared with two existing hybrid algorithms. Fifthly, we turn our attention to inpainting large missing regions, and develop an innovative inpainting scheme that uses the concept of seam carving to reduce this problem to that of inpainting a smaller size missing region that can be dealt with efficiently using the inpainting schemes developed above. Seam carving resizes images based on content-awareness of the image for both reduction and expansion without affecting those image regions that have rich information. The missing region of the seam-carved version will be recovered by the TEBI method, original image size is restored by adding the removed seams and the missing parts of the added seams are then repaired using a high order PDE inpainting scheme. The benefits of this approach in dealing with large missing regions are demonstrated. The extensive performance testing of the developed inpainting methods shows that these methods significantly outperform existing inpainting methods for such a challenging task. However, the performance is still not acceptable in recovering large missing regions in high texture and structure images, and hence we shall identify remaining challenges to be investigated in the future. We shall also extend our work by investigating recently developed deep learning based image/video colourisation, with the aim of overcoming its limitations and shortcoming. Finally, we should also describe our on-going research into using TDA to detect recently growing serious “malicious” use of inpainting to create Fake images/videos

IKUWA6. Shared Heritage

Celebrating the theme ‘Shared heritage’, IKUWA6 (the 6th International Congress for Underwater Archaeology), was the first such major conference to be held in the Asia-Pacific region, and the first IKUWA meeting hosted outside Europe since the organisation’s inception in Germany in the 1990s. A primary objective of holding IKUWA6 in Australia was to give greater voice to practitioners and emerging researchers across the Asia and Pacific regions who are often not well represented in northern hemisphere scientific gatherings of this scale; and, to focus on the areas of overlap in our mutual heritage, techniques and technology. Drawing together peer-reviewed presentations by delegates from across the world who converged in Fremantle in 2016 to participate, this volume covers a stimulating diversity of themes and niche topics of value to maritime archaeology practitioners, researchers, students, historians and museum professionals across the world

EG-ICE 2021 Workshop on Intelligent Computing in Engineering

The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways

Representing air pollution in future energy scenarios

Decarbonisation of a country’s energy system requires a change in energy supply chains, infrastructure and the introduction of new technologies. These lead to changes in the scale and type of combustion processes, the fuels used, as well as the activities required to supply fuels and operate energy infrastructure. They lead to changes in emission budgets of greenhouse gases and air pollutants that will have environmental and public health impacts. Such impacts can be highly dependent on the location and on the implementation of emerging energy technologies. This study compares the capabilities of tools for describing atmospheric emissions of air pollutants and greenhouse gases in future energy scenarios, for costing them and for cost-optimising deployment strategy. Case studies of technology choices for deploying decentralised CHP and for the uptake of hybrid vehicles are used to illustrate the challenges of representing emerging technologies in these models. The effectiveness of these technologies of reducing emissions budgets, together with synergies and antagonisms between delivering reductions in greenhouse gas emissions and air pollutant budgets are also explored. Recommendations are made on the using of incumbent models to assess air pollution, on the inclusion of novel technologies in energy scenarios and on how modelling systems might be better adapted to represent these. Spatial and temporal resolution are identified as key influences on models’ capabilities. In the hybrid vehicles case study, the precise technology options for vehicles – particularly hybrid powertrain architectures – is a key influence on optimising the benefits of atmospheric emissions reduction from future road transport. In the case of decentralised CHP, the surface morphology close to emission sources or in high population density areas will play a major role in impacts and costs of atmospheric emissions.Open Acces

EG-ICE 2021 Workshop on Intelligent Computing in Engineering

The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways

Smart Energy Management for Smart Grids

This book is a contribution from the authors, to share solutions for a better and sustainable power grid. Renewable energy, smart grid security and smart energy management are the main topics discussed in this book

Using software as a service to support the academic activities of students in higher education institutions with a relative lack of resources

The contribution of Software as a Service (SaaS) towards improved access to software, cost reduction, better quality of learning and enhanced communication and collaboration in higher education institutions (HEIs) cannot be over emphasised. Some HEIs are faced with issues such as tight budget, lack of needed software, inadequate human resources and lack of adequate infrastructure. This research refers to such HEIs as those with a relative lack of resources because the resources intended for a single student are often shared among ten or more students. Hence many students are unable to cope with their academic activities and some end up failing or even dropping out. Finding alternative ways to provide the necessary software for students is therefore a priority for HEIs with a relative lack of resources. SaaS offers a possible alternative for them and it is gaining their attention. The goal of this research was to empower HEIs, their students, lecturers and Information Technology (IT) staff by providing them with a better understanding of SaaS and to provide them with a tool to manage the adoption and implementation of SaaS. Also, the intention was to make practical, theoretical and methodological contributions to the scientific body of knowledge in the area of Software as a Service. To achieve the goals, this research investigated the use of SaaS in HEIs with a relative lack of resources and found SaaS to be effective in providing wider access to software for students in HEIs with a relative lack of resources. This research also identified benefits and limitations of SaaS and how SaaS can help in addressing the barriers to learning and contribute towards the creation of a conducive learning environment for students. The different SaaS offerings available for education and the issues and contradictions associated with the use of SaaS in HEIs were also identified. Furthermore, a set of propositions and an integrated framework were developed using the data from the literature, books, institutional documents and interview data. Although HEIs are continuously introducing SaaS offerings into their academic activities and SaaS promises to improve the learning experience of students in HEIs by improving access to software, improving the sharing of documents and files, improving collaboration as well as communication, this research found that the use of SaaS by students in HEIs is still relatively low and uncovered the reasons for this. The HEIs in Nigeria and South Africa were used as exemplars and the problems they face with regards to resource availability were identified using the activity theory (AT) as a theoretical lens. The Astin’s IEO model and the Students involvement theory were also used to explain some issues relating to the importance of student participation in academic activities involving the use of SaaS. Although the study was focused on students, data from lecturers and IT staff was used for triangulation to increase the credibility and validity of the data obtained from the students. This research found that students believe that SaaS can improve their learning experience and there is an unwavering support for the campus wide implementation of SaaS among students. In the Nigerian HEIs, software piracy was found to be a major problem as students cannot afford to buy the original software needed for academic activities. Another major finding from the Nigerian HEIs is the rampant claims that corruption affects the implementation of SaaS and other ICT initiatives as funds meant for implementation are often diverted for personal gains. In both Nigeria and South Africa, this research found that there is limited or no internet access in some areas and the students who come from such areas are unable to access SaaS from home. This limits their ability to enjoy the anytime, anywhere access advantage of SaaS. This research concluded by suggesting the need for the government and education institutions to provide training for learners and encourage them to be computer literate from an early stage as this could improve their confidence in using technologies such as SaaS when they get to higher education level