• Generalised Catalan polynomials and their properties

      Larcombe, Peter J.; Jarvis, Frazer A.; Fennessey, Eric J.; University of Derby (The Institute of Combinatorics and its Applications, 2014-05)
      We introduce a new type of polynomial, termed a generalised Catalan polynomial. We list essential mathematical properties and give two associated combinatorial interpretations.
    • A generating function approach to the automated evaluation of sums of exponentiated multiples of generalized Catalan number linear combinations.

      Larcombe, Peter J.; O'Neill, Sam T.; University of Derby (The Fibonacci Association, 2018-05)
      Based on a previous technique deployed in some specific low order cases, we develop an automated computational procedure to evaluate instances within a class of infinite series comprising exponentiated multiples of generalized linear combinations of Catalan numbers. The methodology is explained, and new results given.
    • Geometric nonlinear damper design — A frequency based approach

      Uchenna, Diala; Okafor, K.C.; Zi-Qiang, Lang; University of Sheffield (IEEE, 2018-02-08)
      In this study, the vibration transmissibility of a single-degree-of-freedom (SDOF) with a linear damper having a configuration perpendicular to a linear vertical spring is analyzed using a nonlinear frequency analysis method. The concept of the output frequency response function (OFRF) is employed to derive an explicit polynomial relationship between the system output response (relative displacement of the mass) and the parameter of interest which is the nonlinear damping coefficient. With the derived OFRF polynomial, various damping parameters were designed for desired output responses.
    • Getting the most from your subs

      Hill, Adam J.; University of Derby (New Bay, 2015-05-26)
      Dr Adam Hill, sound engineer and lecturer in Audio Engineering at the University of Derby advises on effective bass delivery.
    • Giving effective academic presentations

      Self, Richard; University of Derby (2016-05)
      This Keynote address was presented at the International Journal of Arts and Sciences Multi-disciplinary conference held in Toronto 31May to 3 June 2016 at Ryerson University.
    • Global projective lag synchronization of fractional order memristor based BAM neural networks with mixed time varying delays

      Pratap, A.; Raja, R.; Sowmiya, C.; Bagdasar, Ovidiu; Jinde, Cao; Rajchakit, G.; University of Derby (Wiley InterScience, 2019-05-03)
      This paper addresses Master-Slave synchronization for some memristor- based fractional-order BAM neural networks (MFBNNs) with mixed time varying delays and switching jumps mismatch. Firstly, considering the inherent characteristic of FMNNs, a new type of fractional-order differential inequality is proposed. Secondly, an adaptive switching control scheme is designed to realize the global projective lag synchronization goal of MFBNNs in the sense of Riemann-Liouville derivative. Then, based on a suitable Lyapunov method, under the framework of set-valued map, differential inclusions theory, fractional Barbalat’s lemma and proposed control scheme, some new projective lag synchronization criteria for such MFBNNs are obtained. Finally, some numerical examples are presented to illustrate the effectiveness of the proposed theoretical analysis.
    • Glueing grids and clouds together: a service-oriented approach

      Anjum, Ashiq; Hill, Richard; McClatchey, Richard; Bessis, Nik; Branson, Andrew; University of Derby (Inderscience, 2012)
    • GORTS: genetic algorithm based on one-by-one revision of two sides for dynamic travelling salesman problems

      Xu, Xiaolong; Yuan, Hao; Matthew, Peter; Ray, Jeffrey; Bagdasar, Ovidiu; Trovati, Marcello; University of Derby; Nanjing University of Posts and Telecommunications, Nanjing, China; Edge Hill University, Ormskirk, UK (Springer, 2019-09-21)
      The dynamic travelling salesman problem (DTSP) is a natural extension of the standard travelling salesman problem, and it has attracted significant interest in recent years due to is practical applications. In this article, we propose an efficient solution for DTSP, based on a genetic algorithm (GA), and on the one-by-one revision of two sides (GORTS). More specifically, GORTS combines the global search ability of GA with the fast convergence feature of the method of one-by-one revision of two sides, in order to find the optimal solution in a short time. An experimental platform was designed to evaluate the performance of GORTS with TSPLIB. The experimental results show that the efficiency of GORTS compares favourably against other popular heuristic algorithms for DTSP. In particular, a prototype logistics system based on GORTS for a supermarket with an online map was designed and implemented. It was shown that this can provide optimised goods distribution routes for delivery staff, while considering real-time traffic information.
    • The governance impact of Big Data and the Internet of Things on the practice of knowledge management in organisations

      Self, Richard; University of Derby (2015-08-24)
      The practice of Knowledge Management in many organisations is based on the approach that all “knowledge” in the repositories is carefully curated through a quality assurance and managerial process. This is particularly the case in organisations where KM is closely linked to document management or similar types of systems. Processes such as document review and sign-off are often considered vital to ensure the validity and veracity of the knowledge store. The world of Big Data and the Internet of Things (IoT), however, does not cooperate with this conception. Instead, as John Easton suggested in 2012, it is very probable that over 80% of all data available, especially that which is derived from Big Data and the IoT, is of uncertain veracity. It is not that it is all wrong but that we do not know which data are true and which data are not and that it is often very difficult to determine which is which. This workshop will enable practitioners to develop a clear understanding of how to obtain value from BDA and the IoT in ways that are compatible with Knowledge Management, using the principles of Information and Corporate Governance.
    • Governance strategies for the cloud, Big Data, and other technologies in education

      Self, Richard; University of Derby (IEEE, 2014-12-08)
      The Cloud, Big Data and many emerging technologies are now being considered by many educational establishments as candidates for deriving benefits for both students in their learning and also for the organisation in terms of more effective and efficient operation. This paper considers the governance strategies which need to be developed and implemented in order to ensure that the technologies can be safely incorporated into the technical and operational infrastructure. It demonstrates that synthesising ISO 27002 with a new framework of 12 Vs of Big Data provides an effective approach to identifying some important aspects of new technologies that do not naturally arise from traditional frameworks.
    • Graph data modelling for genomic variants

      Anjum, Ashiq; Aizad, Sanna; University of Derby (IEEE, 2019)
      Genome variant analysis is performed on Variant Call Format (VCF) files. It can take days to process these files for genome analytics due to challenges such as loading the files for each user query and processing them to answer questions of interest. As data sizes grow, timely processing of this data is putting enormous pressure on the computational resources, leading to significant processing delays and may jeopardise the ultimate goal of bringing the genomic discoveries to masses. We believe this problem will not be solved until the underlying data structure to organise and process these files undergoes a transformation. To overcome this problem, we have proposed a graph based system to represent the data in VCF files. This allows the data to be loaded once in a graph model which is then subsequently queried and processed numerous times without any additional computational and data access penalties. This helps reduce data access time by giving a constant time access to any node and addresses performance and scalability challenges that have been a limiting factor for the mass scale adoption of genome analytics. It takes only 2ms to access any data node in our graph model and remains constant for any number of nodes.
    • Green transport planning paradoxes

      Berry, Stuart; Parkes, Chris; University of Derby (The Institute of Mathematics and its Applications (IMA), 2016-08-04)
      System dynamic modelling is used to show that the development of a mass transport network follows a pattern of continuous growth until the system is replaced by what is seen as a better, or now, greener solution to the problem of moving goods and people. This modelling shows the effect, on the transport system, of the dominant means of progressing from canals to rail to roads to trans-urban rail systems, for example rail replaced canals and road replaced rail as the dominant system. These models are then used to demonstrate that although current transport developments emphasise their Green credentials, such as the London Crossrail and Borders railway developments, these developments can have non-Green results, acting to move (further) from city centres and encourage non-Green urban sprawl.
    • Grid workflow validation using ontology-based tacit knowledge: A case study for quantitative remote sensing applications

      Liu, Jia; Liu, Longli; Xue, Yong; Dong, Jing; Hu, Yincui; Hill, Richard; Guang, Jie; Li, Chi; University of Derby (Elsevier, 2016-10-11)
      Workflow for remote sensing quantitative retrieval is the “bridge” between Grid services and Grid-enabled application of remote sensing quantitative retrieval. Workflow averts low-level implementation details of the Grid and hence enables users to focus on higher levels of application. The workflow for remote sensing quantitative retrieval plays an important role in remote sensing Grid and Cloud computing services, which can support the modelling, construction and implementation of large-scale complicated applications of remote sensing science. The validation of workflow is important in order to support the large-scale sophisticated scientific computation processes with enhanced performance and to minimize potential waste of time and resources. To research the semantic correctness of user-defined workflows, in this paper, we propose a workflow validation method based on tacit knowledge research in the remote sensing domain. We first discuss the remote sensing model and metadata. Through detailed analysis, we then discuss the method of extracting the domain tacit knowledge and expressing the knowledge with ontology. Additionally, we construct the domain ontology with Protégé. Through our experimental study, we verify the validity of this method in two ways, namely data source consistency error validation and parameters matching error validation
    • A GRU-based prediction framework for intelligent resource management at cloud data centres in the age of 5G

      Lu, Yao; Liu, Lu; Panneerselvam, John; Yuan, Bo; Gu, Jiayan; Antonopoulos, Nick; University of Leicester; University of Derby; Edinburgh Napier University (IEEE, 2019-11-19)
      The increasing deployments of 5G mobile communication system is expected to bring more processing power and storage supplements to Internet of Things (IoT) and mobile devices. It is foreseeable the billions of devices will be connected and it is extremely likely that these devices receive compute supplements from Clouds and upload data to the back-end datacentres for execution. Increasing number of workloads at the Cloud datacentres demand better and efficient strategies of resource management in such a way to boost the socio-economic benefits of the service providers. To this end, this paper proposes an intelligent prediction framework named IGRU-SD (Improved Gated Recurrent Unit with Stragglers Detection) based on state-of-art data analytics and Artificial Intelligence (AI) techniques, aimed at predicting the anticipated level of resource requests over a period of time into the future. Our proposed prediction framework exploits an improved GRU neural network integrated with a resource straggler detection module to classify tasks based on their resource intensity, and further predicts the expected level of resource requests. Performance evaluations conducted on real-world Cloud trace logs demonstrate that the proposed IGRU-SD prediction framework outperforms the existing predicting models based on ARIMA, RNN and LSTM in terms of the achieved prediction accuracy.
    • Guide to security assurance for cloud computing

      Zhu, Shao Ying; Hill, Richard; Trovati, Marcello; University of Derby (Springer, 2015)
      This practical and didactic text/reference discusses the leading edge of secure cloud computing, exploring the essential concepts and principles, tools, techniques and deployment models in this field. Enlightening perspectives are presented by an international collection of pre-eminent authorities in cloud security assurance from both academia and industry.
    • Handbook of cluster analysis

      Hennig, Christian; Meila, Marina; Murtagh, Fionn; Rocci, Roberto; University College London; University of Washington; University of Derby; University of Rome Tor Vergata (CRC Press, 2015-12-01)
      Handbook of Cluster Analysis provides a comprehensive and unified account of the main research developments in cluster analysis. Written by active, distinguished researchers in this area, the book helps readers make informed choices of the most suitable clustering approach for their problem and make better use of existing cluster analysis tools. The book is organized according to the traditional core approaches to cluster analysis, from the origins to recent developments. After an overview of approaches and a quick journey through the history of cluster analysis, the book focuses on the four major approaches to cluster analysis. These approaches include methods for optimizing an objective function that describes how well data is grouped around centroids, dissimilarity-based methods, mixture models and partitioning models, and clustering methods inspired by nonparametric density estimation. The book also describes additional approaches to cluster analysis, including constrained and semi-supervised clustering, and explores other relevant issues, such as evaluating the quality of a cluster. This handbook is accessible to readers from various disciplines, reflecting the interdisciplinary nature of cluster analysis. For those already experienced with cluster analysis, the book offers a broad and structured overview. For newcomers to the field, it presents an introduction to key issues. For researchers who are temporarily or marginally involved with cluster analysis problems, the book gives enough algorithmic and practical details to facilitate working knowledge of specific clustering areas.
    • Hardware acceleration of an image processing system for dielectrophoretic loading of single neurons inside micro-wells of microelectrode arrays

      Zhai, Xiaojun; Jaber, Fadi; Bensaali, Faycal; Mishra, Arti; University of Derby (IEEE, 2015-03-25)
      This paper describes an image processing algorithm and its efficient architecture. The proposed architecture is used to process images of microelectrode arrays (MEAs) and micro-wells captured by a microscope camera in a dielectrophoresis (DEP)-based system which consists as well of digital switches for turning the DEP force 'on' or 'off'. The images are processed in order to determine if a neuron has entered any of the micro-wells in which case the corresponding switch turns 'off' the DEP force. This process must be in real-time to avoid more than one cell to be loaded in a micro-well. The proposed architecture has been successfully implemented and tested on a Zynq SoC. Results achieved have shown that the system can process one image in 9 ms which meets the minimum real-time requirements of this DEP system.
    • HD number plate localization and character segmentation on the Zynq heterogeneous SoC.

      Al-Zawqari, Ali; Hommos, Omar; Al-Qahtani, Abdulhadi; Farhat, Ali; Bensaali, Faycal; Zhai, Xiaojun; Amira, Abbes; Qatar University; University of Derby (Springer, 2018-02-06)
      Automatic number plate recognition (ANPR) systems have become widely used in safety, security, and commercial aspects. A typical ANPR system consists of three main stages: number plate localization (NPL), character segmentation (CS), and optical character recognition (OCR). In recent years, to provide a better recognition rate, high-definition (HD) cameras have started to be used. However, most known techniques for standard definition (SD) are not suitable for real-time HD image processing due to the computationally intensive cost of processing several-folds more of image pixels, particularly in the NPL stage. In this paper, algorithms suitable for hardware implementation for NPL and CS stages of an HD ANPR system are presented. Software implementation of the algorithms was carried on as a proof of concept, followed by hardware implementation on a heterogeneous system-on-chip (SoC) device that contains an ARM processor and a field-programmable gate array (FPGA). Heterogeneous implementation of these stages has shown that this HD NPL algorithm can localize a number plate in 16.17 ms, with a success rate of 98.0%. The CS algorithm can then segment the detected plate in 0.59 ms, with a success rate of 99.05%. Both stages utilize only 21% of the available on-chip configurable logic blocks.
    • HD Qatari ANPR system

      Hommos, Omar; Al-Qahtani, Abdulhadi; Al-Zawqari, Ali; Bensaali, Faycal; Amira, Abbes; Zhai, Xiaojun; University of Derby (IEEE, 2016-03-13)
    • HD-Video Streaming over an Inexpensive In-Building Radio-over-MMF System

      Torres Vega, M.; Zou, S.; Tangdiongga, E.; Koonen, A. M. J.; Liotta, Antonio (IEEE, 2014)