• 3D sustainable renewable micro power station for smart grid industrial applications

      Komlanvi, Moglo; Shafik, Mahmoud; Ashu, Mfortaw Elvis; University of Derby (2015)
      The supply of clean energy and its security is becoming a global issue for all countries across the world, due to the limitations of fossil fuels resources usages for energy generations, the relative high dependency on imported fuels, their ever climbing prices and its environmental impacts. Power supply must increase as rapidly as demand to ensure sustained growth. This is the rationale upon which Governments, international organizations, researchers are accelerating investments in expanding the power system, its generation and transmission. This paper presents the preliminary research undertaken to design and develop a 3Dimentional (3D) sustainable renewable micro power station model for smart grid industrial applications. It introduces a solution to challenges in the energy generation sector which do not only refrain only to the safe supply of clean Energy. A major importance for the theoretical study of hybrid systems, based on renewable energy (photovoltaic, wind, hydro system) is the availability of the models that can be utilized to study the behavior of hybrid systems and most important, computer aided design simulation tools. As the available tools are quite limited, this paper would present the most current and up to date model which can be used for the simulation purposes of the 3D sustainable renewable micro power station for smart grid applications as well as for educational purposes.
    • 3ΛH and 3Λ̅H̅ production in Pb–Pb collisions at √sNN = 2.76 TeV

      Alexandre, Didier; Barnby, Lee; Bhasin, Anju; Bombara, Marek; Evans, David; Graham, Katie; Jones, Peter; Jusko, Anton; Krivda, Marian; Lee, Graham; et al. (2016-03-10)
    • Accuracy of no-reference quality metrics in network-impaired video streams

      Vega, Maria Torres; Sguazzo, Vittorio; Mocanu, Decebal Constantin; Liotta, Antonio (ACM, 2015)
    • Achieving dynamic load balancing through mobile agents in small world P2P networks

      Shen, Xiang-Jun; Liu, Lu; Zha, Zheng-Jun; Gu, Pei-Ying; Jiang, Zhong-Qiu; Chen, Ji-Ming; Panneerselvam, John; University of Derby (Elsevier, 2014-05-15)
      Peer-to-Peer (P2P) networks are a class of distributed networking and are being deployed in a wide range of applications. Besides such an importance, P2P networks still incur complexities in the resource location policies and in the load balancing techniques of the nodes, especially in unstructured P2P networks. One potential solution to resolve such issues is to enable the P2P networks to evolve into a self-optimizing overlay network topology by identifying the overloaded peers promptly. This paper introduces a new load balancing method in unstructured P2P networks based on mobile agents and resource grouping techniques. We firstly propose a resource grouping strategy to cluster the nodes which have same set of resources, thereby balancing the load among inter-group nodes. On the other hand, load balancing among intra-group nodes is achieved by using the mobile agents monitoring technique. By using this technique, the mobile agents migrate through the nodes in the same group, for the purpose of identifying the possible network congestion. Thus, queries can reach the desired resources more quickly while congested nodes can be identified promptly. The simulation results show that our proposed network evolves into a group-based small world network significantly. The evolved network exhibits robustness and adaptability under external attacking, high query workload, and higher network churns. The simulation results also illustrate that the proposed model achieves better search performance than the DANTE system.
    • Achieving green IT using VDI in cyber physical society

      Liu, Lu; DaSilva, Don-Anthony; Antonopoulos, Nikolaos; Ding, Zhijun; Zhan, Yongzhao; University of Derby; Tongji University; Jiangsu University (Taiwan Academic Network, 2013-05)
      With rapid advances in Internet technologies and increasing popularity of cyber social networks, the physical world and cyber world are gradually merging to form a new cyber-socio-physical society known as the Cyber Physical Society (CPS). In contrast to the previous research studies in cyber physical society, we are focusing on a different case of CPS-green IT in this paper. The complex cyber physical systems of cloud bring unprecedented challenges in power resource managements. This paper looks at the literature behind virtualization and mainly virtual desktop infrastructure as the solution to these challenges. In this paper, we investigate how to use cutting-edge virtualization technologies to reduce power consumption of IT infrastructure in Cyber Physical Society. This research and the implementation of a testing virtual desktop environment using VMware and Wyse technologies portray the clear improvements that hypervisor and desktop virtualization can be brought to IT infrastructures drawing particular attention to power consumption and the green incentives.
    • Acquiring Guideline-enabled data driven clinical knowledge model using formally verified refined knowledge acquisition method

      Afzal, Muhammad; Malik, Khalid M.; Ali, Taqdir; Ali Khan, Wajahat; Irfan, Muhammad; Jamshrf, Arif; Lee, Sungyoung; Hussain, Maqbool; Sejong University, Seoul, South Korea; Oakland University, Rochester, MI, USA; et al. (Elsevier, 2020-08-19)
      Background and Objective: Validation and verification are the critical requirements for the knowledge acquisition method of the clinical decision support system (CDSS). After acquiring the medical knowledge from diverse sources, the rigorous validation and formal verification process are required before creating the final knowledge model. Previously, we have proposed a hybrid knowledge acquisition method with the support of a rigorous validation process for acquiring medical knowledge from clinical practice guidelines (CPGs) and patient data for the treatment of oral cavity cancer. However, due to lack of formal verification process, it involves various inconsistencies in knowledge relevant to the formalism of knowledge, conformance to CPGs, quality of knowledge, and complexities of knowledge acquisition artifacts.Methods: This paper presents the refined knowledge acquisition (ReKA) method, which uses the Z formal verification process. The ReKA method adopts the verification method and explores the mechanism of theorem proving using the Z notation. It enhances a hybrid knowledge acquisition method to thwart the inconsistencies using formal verification.Results: ReKA adds a set of nine additional criteria to be used to have a final valid refined clinical knowledge model. These criteria ensure the validity of the final knowledge model concerning formalism of knowledge, conformance to GPGs, quality of the knowledge, usage of stringent conditions and treatment plans, and inconsistencies possibly resulting from the complexities. Evaluation, using four medical knowledge acquisition scenarios, shows that newly added knowledge in CDSS due to the additional criteria by the ReKA method always produces a valid knowledge model. The final knowledge model was also evaluated with 1229 oral cavity patient cases, which outperformed with an accuracy of 72.57% compared to a similar approach with an accuracy of 69.7%. Furthermore, the ReKA method identified a set of decision paths (about 47.8%) in the existing approach, which results in a final knowledge model with low quality, non-conformed from standard CPGs.Conclusion: ReKA refined the hybrid knowledge acquisition method by discovering the missing steps in the current validation process at the acquisition stage. As a formally proven method, it always yields a valid knowledge model having high quality, supporting local practices, and influenced by standard CPGs. Furthermore, the final knowledge model obtained from ReKA also preserves the performance such as the accuracy of the individual source knowledge models.
    • An active deep learning approach for minimally supervised polsar image classification

      Xue, Yong; University of Derby; Fudan University, Shanghai, China; X'ian Electronics and Engineering Institute, China (IEEE, 2019-08-01)
      Recently, deep neural networks have received intense interests in polarimetric synthetic aperture radar (PolSAR) image classification. However, its success is subject to the availability of large amounts of annotated data which require great efforts of experienced human annotators. Aiming at improving the classification performance with greatly reduced annotation cost, this paper presents an active deep learning approach for minimally supervised PolSAR image classification, which integrates active learning and fine-tuned convolutional neural network (CNN) into a principled framework. Starting from a CNN trained using a very limited number of labeled pixels, we iteratively and actively select the most informative candidates for annotation, and incrementally fine-tune the CNN by incorporating the newly annotated pixels. Moreover, to boost the performance and robustness of the proposed method, we employ Markov random field (MRF) to enforce class label smoothness, and data augmentation technique to enlarge the training set. We conducted extensive experiments on four real benchmark PolSAR images, and experiments demonstrated that our approach achieved state-of-the-art classification results with significantly reduced annotation cost.
    • Adapting scientific workflow structures using multi-objective optimization strategies

      Habib, Irfan; Anjum, Ashiq; Mcclatchey, Richard; Rana, Omer; University of Derby, UK (Association for Computing Machinery, 2013-04-01)
      Scientific workflows have become the primary mechanism for conducting analyses on distributed computing infrastructures such as grids and clouds. In recent years, the focus of optimization within scientific workflows has primarily been on computational tasks and workflow makespan. However, as workflow-based analysis becomes ever more data intensive, data optimization is becoming a prime concern. Moreover, scientific workflows can scale along several dimensions: (i) number of computational tasks, (ii) heterogeneity of computational resources, and the (iii) size and type (static versus streamed) of data involved. Adapting workflow structure in response to these scalability challenges remains an important research objective. Understanding how a workflow graph can be restructured in an automated manner (through task merge, for instance), to address constraints of a particular execution environment is explored in this work, using a multi-objective evolutionary approach. Our approach attempts to adapt the workflow structure to achieve both compute and data optimization. The question of when to terminate the evolutionary search in order to conserve computations is tackled with a novel termination criterion. The results presented in this article demonstrate the feasibility of the termination criterion and demonstrate that significant optimization can be achieved with a multi-objective approach.
    • An adaptive multilevel indexing method for disaster service discovery

      Wu, Yan; Yan, Chun Gang; Liu, Lu; Ding, Zhijun; Jiang, Changjun; University of Derby (IEEE, 2014-12-05)
      With the globe facing various scales of natural disasters then and there, disaster recovery is one among the hottest research areas and the rescue and recovery services can be highly benefitted with the advancements of information and communications technology (ICT). Enhanced rescue effect can be achieved through the dynamic networking of people, systems and procedures. A seamless integration of these elements along with the service-oriented systems can satisfy the mission objectives with the maximum effect. In disaster management systems, services from multiple sources are usually integrated and composed into a usable format in order to effectively drive the decision-making process. Therefore, a novel service indexing method is required to effectively discover desirable services from the large-scale disaster service repositories, comprising a huge number of services. With this in mind, this paper presents a novel multilevel indexing algorithm based on the equivalence theory in order to achieve effective service discovery in large-scale disaster service repositories. The performance and efficiency of the proposed model have been evaluated by both theoretical analysis and practical experiments. The experimental results proved that the proposed algorithm is more efficient for service discovery and composition than existing inverted index methods.
    • An adaptive secure communication framework for mobile peer-to-peer environments using Bayesian games

      Li, Zhiyuan; Liu, Lu; Chen, Rulong; Bi, Jun-Lei; University of Derby (Springer, 2015-06-12)
      Peers in Mobile P2P (MP2P) networks exploit both the structured and unstructured styles to enable communication in a peer-to-peer fashion. Such networks involve the participation of two types of peers: benign peers and malicious peers. Complexities are witnessed in the determination of the identity of the peers because of the user mobility and the unrestricted switching (ON/OFF) of the mobile devices. MP2P networks require a scalable, distributed and light-weighted secure communication scheme. Nevertheless, existing communication approaches lack the capability to satisfy the requirements above. In this paper, we propose an Adaptive Trusted Request and Authorization model (ATRA) over MP2P networks, by exploiting the limited historical interaction information among the peers and a Bayesian game to ensure secure communication. The simulation results reveal that regardless of the peer’s ability to obtain the other such peer’s trust and risk data, the request peers always spontaneously connect the trusted resource peers and the resource peers always preferentially authorize the trusted request peers. Performance comparison of ATRA with state-of-the-art secure communication schemes over MP2P networks shows that ATRA can: (a) improve the success rate of node typing identification, (b) reduce time required for secure connections found, (c) provide efficient resource sharing, and (d) maintain the lower average cost.
    • An adaptive semantic based mediation system for data interoperability among health information systems

      Khan, Wajahat Ali; Khattak, Asad Masood; Hussain, Maqbool; Amin, Muhammad Bilal; Afzal, Muhammad; Nugent, Christopher; Lee, Sungyoung; Kyung Hee University, Seocheon-dong, Giheung-gu, Yongin-si, Gyeonggi-do, 446-701, Republic of Korea; University of Ulster Newtownabbey, Co. Antrim, Northern Ireland (Springer Science and Business Media LLC, 2014-06-26)
      Heterogeneity in the management of the complex medical data, obstructs the attainment of data level interoperability among Health Information Systems (HIS). This diversity is dependent on the compliance of HISs with different healthcare standards. Its solution demands a mediation system for the accurate interpretation of data in different heterogeneous formats for achieving data interoperability. We propose an adaptive AdapteR Interoperability ENgine mediation system called ARIEN, that arbitrates between HISs compliant to different healthcare standards for accurate and seamless information exchange to achieve data interoperability. ARIEN stores the semantic mapping information between different standards in the Mediation Bridge Ontology (MBO) using ontology matching techniques. These mappings are provided by our System for Parallel Heterogeneity (SPHeRe) matching system and Personalized-Detailed Clinical Model (P-DCM) approach to guarantee accuracy of mappings. The realization of the effectiveness of the mappings stored in the MBO is evaluation of the accuracy in transformation process among different standard formats. We evaluated our proposed system with the transformation process of medical records between Clinical Document Architecture (CDA) and Virtual Medical Record (vMR) standards. The transformation process achieved over 90 % of accuracy level in conversion process between CDA and vMR standards using pattern oriented approach from the MBO. The proposed mediation system improves the overall communication process between HISs. It provides an accurate and seamless medical information exchange to ensure data interoperability and timely healthcare services to patients.
    • Adaptive service discovery on service-oriented and spontaneous sensor systems

      Liu, Lu; Xu, Jie; Antonopoulos, Nikolaos; Li, Jianxin; Wu, Kaigu; University of Derby (Old City Publishing, 2012-03-06)
      Natural and man-made disasters can significantly impact both people and environments. Enhanced effect can be achieved through dynamic networking of people, systems and procedures and seamless integration of them to fulfil mission objectives with service-oriented sensor systems. However, the benefits of integration of services will not be realised unless we have a dependable method to discover all required services in dynamic environments. In this paper, we propose an Adaptive and Efficient Peer-to-peer Search (AEPS) approach for dependable service integration on service-oriented architecture based on a number of social behaviour patterns. In the AEPS network, the networked nodes can autonomously support and co-operate with each other in a peer-to-peer (P2P) manner to quickly discover and self-configure any services available on the disaster area and deliver a real-time capability by self-organising themselves in spontaneous groups to provide higher flexibility and adaptability for disaster monitoring and relief.
    • Addressing robustness in time-critical, distributed, task allocation algorithms.

      Whitbrook, Amanda; Meng, Qinggang; Chung, Paul W. H.; University of Derby; Loughborough University (Springer, 2018-04-18)
      The aim of this work is to produce and test a robustness module (ROB-M) that can be generally applied to distributed, multi-agent task allocation algorithms, as robust versions of these are scarce and not well-documented in the literature. ROB-M is developed using the Performance Impact (PI) algorithm, as this has previously shown good results in deterministic trials. Different candidate versions of the module are thus bolted on to the PI algorithm and tested using two different task allocation problems under simulated uncertain conditions, and results are compared with baseline PI. It is shown that the baseline does not handle uncertainty well; the task-allocation success rate tends to decrease linearly as degree of uncertainty increases. However, when PI is run with one of the candidate robustness modules, the failure rate becomes very low for both problems, even under high simulated uncertainty, and so its architecture is adopted for ROB-M and also applied to MIT’s baseline Consensus Based Bundle Algorithm (CBBA) to demonstrate its flexibility. Strong evidence is provided to show that ROB-M can work effectively with CBBA to improve performance under simulated uncertain conditions, as long as the deterministic versions of the problems can be solved with baseline CBBA. Furthermore, the use of ROB-M does not appear to increase mean task completion time in either algorithm, and only 100 Monte Carlo samples are required compared to 10,000 in MIT’s robust version of the CBBA algorithm. PI with ROB-M is also tested directly against MIT’s robust algorithm and demonstrates clear superiority in terms of mean numbers of solved tasks.
    • Advances in Manufacturing Technology XXXIV

      Shafik, Mahmoud; Case, Keith; University of Derby (IOS Press, 2021-09-07)
      The development of technologies and management of operations is key to sustaining the success of manufacturing businesses, and since the late 1970s, the International Conference on Manufacturing Research (ICMR) has been a major annual event for academics and industrialists engaged in manufacturing research. The conference is renowned as a friendly and inclusive platform that brings together a broad community of researchers who share a common goal. This book presents the proceedings of ICMR2021, the 18th International Conference on Manufacturing Research, incorporating the 35th National Conference on Manufacturing Research, and held in Derby, UK, from 7 to 10 September 2021. The theme of the ICMR2021 conference is digital manufacturing. Within the context of Industrial 4.0, ICMR2021 provided a platform for researchers, academics and industrialists to share their vision, knowledge and experience, and to discuss emerging trends and new challenges in the field. The 60 papers included in the book are divided into 10 parts, each covering a different area of manufacturing research. These are: digital manufacturing, smart manufacturing; additive manufacturing; robotics and industrial automation; composite manufacturing; machining processes; product design and development; information and knowledge management; lean and quality management; and decision support and production optimization. The book will be of interest to all those involved in developing and managing new techniques in manufacturing industry.
    • Allen’s interval algebra and smart-type environments

      Chuckravanen, Dineshen; Daykin, Jacqueline; Hunsdale, Karen; Seeam, Amar; Aberystwyth University (Mauritius Campus) (IARIA, 2017-03)
      Allen’s interval algebra is a calculus for temporal reasoning that was introduced in 1983. Reasoning with qualitative time in Allen’s full interval algebra is nondeterministic polynomial time (NP) complete. Research since 1995 identified maximal tractable subclasses of this algebra via exhaustive computer search and also other ad-hoc methods. In 2003, the full classification of complexity for satisfiability problems over constraints in Allen’s interval algebra was established algebraically. Recent research proposed scheduling based on the Fishburn-Shepp correlation inequality for posets. This article first reviews Allen’s calculus and surrounding computational issues in temporal reasoning. We then go on to describe three potential temporal-related application areas as candidates for scheduling using the Fishburn-Shepp inequality. We also illustrate through concrete examples, and conclude the importance of Fishburn-Shepp inequality for the suggested application areas that are the development of smart homes, intelligent conversational agents and in physiology with emphasis during time-trial physical exercise. The Fishburn-Shepp inequality will enable the development of smart type devices, which will in turn help us to have a better standard of living.
    • Alwyn Francis Horadam, 1923-2016: A personal tribute to the man and his sequence

      Larcombe, Peter J.; University of Derby (The Institute of Combinatorics and its Applications, 2016-09)
      Having received news of the passing of Alwyn Horadam this last July, I was determined that I should write something in his honour in which my own contact with him is described and combined with some introductory details on what I feel is his major endowment to the community of mathematicians - the so called and pre-eminent Horadam sequence whose specialisations thereof are great in number.
    • AmbiFreeVerb 2—Development of a 3D ambisonic reverb with spatial warping and variable scattering

      Wiggins, Bruce; Dring, Mark; University of Derby (Audio Engineering Society, 2016-07-14)
      In this paper the development of a three dimensional Ambisonic reverb based on the open source FreeVerb algorithm will be presented and discussed. This model is then extended to include processing in over-specified A-format, rather than B-format, variable scattering between channels along with controls for warping the distribution of the reflections to implement a reverb that is able to react to the source position in a spatially coherent way with an acoustical analysis of its performance.
    • An exploratory social network analysis of academic research networks

      Toral, Sergio L.; Bessis, Nik; Martinez-Torres, M. R.; Franc, Florian; Barrero, Federico; Xhafa, Fatos; University of Seville, Spain; University of Derby; University of Toulouse (INSA), France; Polytechnic University of Catalonia (UPC), Spain (IEEE, 2011-11)
      For several decades, academics around the world have been collaborating with the view to support the development of their research domain. Having said that, the majority of scientific and technological policies try to encourage the creation of strong inter-related research groups in order to improve the efficiency of research outcomes and subsequently research funding allocation. In this paper, we attempt to highlight and thus, to demonstrate how these collaborative networks are developing in practice. To achieve this, we have developed an automated tool for extracting data about joint article publications and analyzing them from the perspective of social network analysis. In this case study, we have limited data from works published in 2010 by England academic and research institutions. The outcomes of this work can help policy makers in realising the current status of research collaborative networks in England.
    • Analysis and design of a nonlinear vibration-based energy harvester - a frequency based approach

      Uchenna, Diala; Simon, Pope; Lang, Zi-Qiang; University of Sheffield (IEEE, 2017-08-24)
      The benefits of nonlinear damping in increasing the amount of energy (power) harvested by a vibration-based energy harvester (VEH) has been reported where it was revealed that more energy can be harvested using nonlinear cubic damping when compared to a VEH with linear damping. As has been reported, this only occurs when the base excitation on the VEH, at resonance, is less than the maximum base excitation. A maximum harvester base excitation results in a maximum distance the harvester mass can move due to its size and geometric limitations. The present study is concerned with the analysis and design of a VEH using a nonlinear frequency analysis method. This method employs the concept of the output frequency response function (OFRF) to derive an explicit polynomial relationship between the harvested energy (power) and the parameter of the energy harvester of interest, i.e. the nonlinear cubic damping coefficient. Based on the OFRF, a nonlinear damping coefficient can be designed to achieve a range of desired levels of energy harvesting. It is also shown that using the OFRF the harvester throw (the displacement of the mass of the harvester), can be predicted using the designed damping coefficient.
    • Analysis and optimal design of a vibration isolation system combined with electromagnetic energy harvester

      Diala, Uchenna; Mofidian, SM Mahdi; Lang, Zi-Qiang; Bardaweel, Hamzeh; University of Sheffield (SAGE Publications, 2019-07-17)
      This work investigates a vibration isolation energy harvesting system and studies its design to achieve an optimal performance. The system uses a combination of elastic and magnetic components to facilitate its dual functionality. A prototype of the vibration isolation energy harvesting device is fabricated and examined experimentally. A mathematical model is developed using first principle and analyzed using the output frequency response function method. Results from model analysis show an excellent agreement with experiment. Since any vibration isolation energy harvesting system is required to perform two functions simultaneously, optimization of the system is carried out to maximize energy conversion efficiency without jeopardizing the system’s vibration isolation performance. To the knowledge of the authors, this work is the first effort to tackle the issue of simultaneous vibration isolation energy harvesting using an analytical approach. Explicit analytical relationships describing the vibration isolation energy harvesting system transmissibility and energy conversion efficiency are developed. Results exhibit a maximum attainable energy conversion efficiency in the order of 1%. Results suggest that for low acceleration levels, lower damping values are favorable and yield higher conversion efficiencies and improved vibration isolation characteristics. At higher acceleration, there is a trade-off where lower damping values worsen vibration isolation but yield higher conversion efficiencies.