• Multi-weighted complex structure on fractional order coupled neural networks with linear coupling delay: a robust synchronization problem

      Pratap, A.; Raja, R.; Agarwal, Ravi. P.; Cao, J.; Bagdasar, O.; Alagappa University, Karaikudi; Texas A&M University; Southeast University, Nanjing, China; University of Derby (Springer Science and Business Media LLC, 2020-02-19)
      This sequel is concerned with the analysis of robust synchronization for a multi-weighted complex structure on fractional-order coupled neural networks (MWCFCNNs) with linear coupling delays via state feedback controller. Firstly, by means of fractional order comparison principle, suitable Lyapunov method, Kronecker product technique, some famous inequality techniques about fractional order calculus and the basis of interval parameter method, two improved robust asymptotical synchronization analysis, both algebraic method and LMI method, respectively are established via state feedback controller. Secondly, when the parameter uncertainties are ignored, several synchronization criterion are also given to ensure the global asymptotical synchronization of considered MWCFCNNs. Moreover, two type of special cases for global asymptotical synchronization MWCFCNNs with and without linear coupling delays, respectively are investigated. Ultimately, the accuracy and feasibility of obtained synchronization criteria are supported by the given two numerical computer simulations.
    • 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, design and optimization of a nonlinear energy harvester

      Diala, Uchenna; Lang, Zi-Qiang; Pope, Simon; University of Sheffield (International Institute of Acoustics & Vibration/ Curran Associates Ltd, 2017-07)
    • Nonlinear design and optimisation of a vibration energy harvester

      Diala, Uchenna; Gunawardena, Rajintha; Zhu, Yunpeng; Lang, Zi-Qiang; University of Sheffield (IEEE, 2018-11-01)
      Nonlinear behavior has been exploited over the last decade towards improving the efficiency of most engineering systems. The effect of nonlinearities on a vibration energy harvester (VEH) has been widely studied. It has been reported in literature that a cubic damping nonlinearity extends the dynamic range (power/energy level) of a VEH system. It has also been widely shown that the operational bandwidth of a VEH system can be increased using a nonlinear hardening spring. As most energy harvesters have a maximum throw limited by the physical enclosure of the device, it is imperative to improve the operational conditions of the harvester within this limitation. This paper investigates the effects of a nonlinear hardening spring with cubic damping on a VEH system while assuming no limitation to the maximum throw (Practical VEH systems are constrained to a maximum throw and this is considered in a subsequent study). A frequency-based approach known as Output Frequency Response Function (OFRF) determined using the Associated Linear Equations (ALEs) of the nonlinear system model is employed. The OFRF polynomial is a representation of the actual system model hence used for the nonlinear VEH analysis and design. Based on the OFRF, optimal parameter values are designed to achieve any desired level of energy for the VEH.
    • Nonlinear damper design for a vibration isolation system

      Diala, Uchenna; Okafor, K.C.; Udeze, C.C.; University of Sheffield; Federal University of Technology, Owerri, Nigeria; University of Nigeria (Universal Scientific Organization, 2018-04-15)
      In this paper, vibration transmissibility of a single-degree-of-freedom (SDOF) for a mass-springdamper system is presented. This is done with a linear damper having a configuration perpendicular to a linear vertical spring. The method is analyzed using a nonlinear frequency analysis approach. The concept of the output frequency response function (OFRF) is used to derive an explicit polynomial relationship between the system output response (relative displacement of the mass) and the nonlinear damping coefficient which is the parameter of interest. With the derived OFRF polynomial, various damping parameters were designed for desired output responses. Real-time experimental results are presented for the vibration isolation system validation with dampers orientated perpendicularly (at 90 degrees) to the linear spring. The experimental case studies are provided to demonstrate the new OFRFbased nonlinear system design and its significance in isolated vibration system applications. A force transmissibility graph showing the system output using both numerical and the OFRF methods are presented.
    • 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.
    • Energy management and control system with mobile application interface

      Ifediora, E. C.; Okafor, K. C.; Ononiwu, G. C.; Diala, U. H.; Federal University of Technology, Owerri, Nigeria (IEEE, 2018-02-08)
      Existing energy management systems places less emphasis on management of electrical energy at the consumer level while also requiring a standby operator to monitor the system. This paper presents the design, simulation and development of an energy management and control system with mobile application interface for a federated control. The embedded system context is used in managing and controlling the consumption of energy in both residential and non-residential houses. The characteristics components include a local embedded system, and a mobile application, from which the user can set the energy budget either in Kilowatt-Hour. The local embedded system evaluates the data received from the user, to obtain a threshold value. This value is used to monitor and reduces indiscriminate use of energy by detecting human absence, and taking out supply in each room selectively depending on a set priorities. The system has features that allow for automatic change-over performance. This is based on user-set priorities, log energy consumption data, and communicates with the mobile application.
    • Stationary and initial-terminal value problem for collective decision making via mean-field games

      Stella, Leonardo; Bauso, Dario; University of Sheffield (IEEE, 2017-07)
      Given a large number of homogeneous players that are distributed across three possible states, we consider the problem in which these players have to control their transition rates, following some optimality criteria. The optimal transition rates are based on the players' knowledge of their current state and of the distribution of all the other players, thus introducing mean-field terms in the running and the terminal cost. The first contribution is a mean-field model that takes into account the macroscopic and the microscopic dynamics. The second contribution is the study of the mean-field equilibrium resulting from solving the initial-terminal value problem, involving the Kolmogorov equations and the Hamilton-Jacobi ODEs. The third contribution is the analysis of a stationary equilibrium for the system, which can be obtained in the asymptotic limit from the nonstationary equilibrium. We reframe our analysis within the context of Lyapunov's linearisation method and stability theory of nonlinear systems.
    • Bio-inspired evolutionary dynamics on complex networks under uncertain cross-inhibitory signals

      Stella, Leonardo; Bauso, Dario; University of Sheffield (Elsevier BV, 2018-11-22)
      Given a large population of agents, each agent has three possiblechoices between option 1 or 2 or no option. The two options are equally favorable and the population has to reach consensus on one of the two options quickly and in a distributed way. The more popular an option is, the more likely it is to be chosen by uncommitted agents. Agents committed to one option can be attracted by those committed to the other option through a cross-inhibitory signal. This model originates in the context of honeybee swarms, and we generalize it to duopolistic competition and opinion dynamics. The contributions of this work include (i) the formulation of a model to explain the behavioral traits of the honeybees in the case where the interactions are modeled through complex networks, (ii) the study of the individual and collective behavior that leads to deadlock or consensus depending on a threshold for the cross-inhibitory parameter, (iii) the analysis of the impact of the connectivity on consensus, and (iv) the study of absolute stability for the collective system under time-varying and uncertain cross-inhibitory parameter.
    • Bio-inspired evolutionary game dynamics in symmetric and asymmetric models

      Stella, Leonardo; Bauso, Dario; University of Sheffield (Institute of Electrical and Electronics Engineers (IEEE), 2018-05-18)
      A large population of players has to reach consensus in a distributed way between two options. The two options can be equally favorable or one option can have a higher intrinsic value (asymmetric parameters). In both cases, uncommitted players choose one of the two options depending on the popularity of that option, while committed players can be attracted by those committed to the other option via cross-inhibitory signals. We illustrate the model in different application domains including honeybee swarms, duopolistic competition and opinion dynamics. The main contributions of this letter are as follows: 1) we develop an evolutionary game model to explain the behavioral traits of the honeybees where this model originates; 2) we study individuals' and collective behavior including conditions for local asymptotic stability of the equilibria; 3) we study thresholds on the cross-inhibitory signal for the symmetric case and for the corresponding model with heterogeneous connectivity in the case of asymmetric structure with asymmetric parameters; and 4) we study conditions for stability and passivity properties for the collective system under time-varying and uncertain cross-inhibitory parameter in the asymmetric structure and parameters.
    • On the nonexistence of stationary solutions in bio-inspired collective decision making via mean-field game

      Stella, Leonardo; Bauso, Dario; University of Sheffield (IEEE, 2017-12)
      Conditions for nonexistence of stationary solutions in collective decision making are investigated via discrete-state continuous-time mean-field games. The study builds on a bio-inspired model in honeybee swarms. The ultimate goal is to find the best alternative decision in a collective fashion. A cross-inhibition signal, as the one observed in honeybee swarms, is used to capture different types of failures, including disrupted communication channels, computational errors or malevolent behaviour. The model is based on the hypotheses that players control their transition rates from one state to another to minimise a cost, under the presence of an adversarial disturbance. The cost to minimise involves a penalty on control and a congestion-dependent term. As a main result, we prove that the solution obtained as the asymptotic limit of the nonstationary one can be approximated by a closed orbit trajectory. This argument is used to prove the nonexistence of stationary solution under certain conditions.
    • Evolutionary game dynamics for collective decision making in structured and unstructured environments

      Stella, Leonardo; Bauso, Dario; University of Sheffield (Elsevier BV, 2017-10-18)
      For a large population of players we consider a collective decision making process with three possible choices: option A or B or no option. The more popular option is more likely to be chosen by uncommitted players and cross-inhibitory signals can be sent to attract players committed to a different option. This model originates in the context of honeybees swarms, and we generalise it to accommodate other applications such as duopolistic competition and opinion dynamics. The first contribution is an evolutionary game model and a corresponding new game dynamics called expected gain pairwise comparison dynamics explaining how the strategic behaviour of the players may lead to deadlocks or consensus. The second contribution is the study of equilibrium points and stability in the case of symmetric or asymmetric cross-inhibitory signals. The third contribution is the extension of the results to the case of structured environment in which the players are modelled via a complex network with heterogeneous connectivity.
    • Deriving a global and hourly data set of aerosol optical depth over land using data from four geostationary satellites: goes-16, msg-1, msg-4, and himawari-8

      Xie, Yanqing; Xue, Yong; Guang, Jie; Mei, Linlu; She, Lu; Li, Ying; Che, Yahui; Fan, Cheng; China University of Mining and Technology, XuzhouChina; State Key Laboratory of Remote Sensing Science; et al. (IEEE, 2019-11-07)
      Due to the limitations in the number of satellites and the swath width of satellites (determined by the field of view and height of satellites), it is impossible to monitor global aerosol distribution using polar orbiting satellites at a high frequency. This limits the applicability of aerosol optical depth (AOD) data sets in many fields, such as atmospheric pollutant monitoring and climate change research, where a high-temporal data resolution may be required. Although geostationary satellites have a high-temporal resolution and an extensive observation range, three or more satellites are required to achieve global monitoring of aerosols. In this article, we obtain an hourly and global AOD data set by integrating AOD data sets from four geostationary weather satellites [Geostationary Operational Environmental Satellite (GOES-16), Meteosat Second Generation (MSG-1), MSG-4, and Himawari-8]. The integrated data set will expand the application range beyond the four individual AOD data sets. The integrated geostationary satellite AOD data sets from April to August 2018 were validated using Aerosol Robotic Network (AERONET) data. The data set results were validated against: the mean absolute error, mean bias error, relative mean bias, and root-mean-square error, and values obtained were 0.07, 0.01, 1.08, and 0.11, respectively. The ratio of the error of satellite retrieval within ±(0.05 + 0.2 x AODAERONET) is 0.69. The spatial coverage and accuracy of the MODIS/C61/AOD product released by NASA were also analyzed as a representative of polar orbit satellites. The analysis results show that the integrated AOD data set has similar accuracy to that of the MODIS/AOD data set and has higher temporal resolution and spatial coverage than the MODIS/AOD data set.
    • 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.
    • Traffic assignment: on the interplay between optimization and equilibrium problems

      Bagdasar, Ovidiu; Popovici, Nicolae; Berry, Stuart; University of Derby; Babeş-Bolyai University, Romania (Taylor and Francis, 2020-01-13)
      Motorists often have to choose routes helping them to realize faster journey times. Route choices between an origin and a destination might involve direct main roads, shorter routes through narrow side streets, or longer but (potentially) faster journeys using motorways or ring-roads. In the absence of effective traffic control measures, an approximate equilibrium travel time may result between the routes available, which is generally expected to be far from optimal. In this paper, we investigate discrete and continuous optimization and equilibrium-type problems, for a simplified traffic assignment problem on a simple network with parallel links and fixed demand. We explore the interplay between solutions of certain optimization and equilibrium problems which can be solved by dynamic programming. The results are supported by numerical simulations, in which the price of anarchy is calculated to highlight the demand levels where there is a change in road choice and usage.
    • A novel delay-dependent asymptotic stability conditions for differential and Riemann-Liouville fractional differential neutral systems with constant delays and nonlinear perturbation

      Chartbupapan, Watcharin; Bagdasar, Ovidiu; Mukdasai, Kanit; Khon Kaen University; University of Derby (MDPI AG, 2020-01-03)
      The novel delay-dependent asymptotic stability of a differential and Riemann-Liouville fractional differential neutral system with constant delays and nonlinear perturbation is studied. We describe the new asymptotic stability criterion in the form of linear matrix inequalities (LMIs), using the application of zero equations, model transformation and other inequalities. Then we show the new delay-dependent asymptotic stability criterion of a differential and Riemann-Liouville fractional differential neutral system with constant delays. Furthermore, we not only present the improved delay-dependent asymptotic stability criterion of a differential and Riemann-Liouville fractional differential neutral system with single constant delay but also the new delay-dependent asymptotic stability criterion of a differential and Riemann-Liouville fractional differential neutral equation with constant delays. Numerical examples are exploited to represent the improvement and capability of results over another research as compared with the least upper bounds of delay and nonlinear perturbation.
    • Intelligent data fusion algorithm based on hybrid delay-aware adaptive clustering in wireless sensor networks

      Liu, Xiaozhu; Zhu, Rongbo; Anjum, Ashiq; Wang, Jun; Zhang, Hao; Ma, Maode; Wuhan University of Technology, Wuhan, China; South-Central University for Nationalities, Wuhan, China; University of Derby; Nanyang Technological University, Singapore (Elsevier, 2019-10-04)
      Data fusion can effectively reduce the amount of data transmission and network energy consumption in wireless sensor networks (WSNs). However the existing data fusion schemes lead to additional delay overhead and power consumptions. In order to improve the performance of WSNs, an intelligent data fusion algorithm based on hybrid delay-aware clustering (HDC) in WSNs is proposed, which combines the advantages of single-layer cluster structure and multi-layer cluster structure, and adaptive selects the clustering patterns of the cluster by the decision function to achieve the tradeoff between network delay and energy consumption. The network model of HDC is presented, and theoretical analysis of the delay and energy consumption of single-layer cluster and multi-layer cluster are provided. And the energy efficient clustering algorithm and the dynamic cluster head re-selection algorithm are proposed to optimize network energy consumption and load balancing of the network. Simulation results show that, compared with the existing delay-aware models, the proposed scheme can effectively reduce the network delay, network energy consumption, and extend the network lifetime simultaneously.
    • Fog computing-based approximate spatial keyword queries with numeric attributes in IoV

      Li, Yanhong; Zhu, Rongbo; Mao, Shiwen; Anjum, Ashiq; South-Central University for Nationalities, Wuhan, China; Auburn University, USA; University of Derby (Institute of Electrical and Electronics Engineers (IEEE), 2020-01-10)
      Due to the popularity of on-board geographic devices, a large number of spatial-textual objects are generated in Internet of Vehicles (IoV). This development calls for Approximate Spatial Keyword Queries with numeric Attributes in IoV (ASKIV), which takes into account the locations, textual descriptions, and numeric attributes of spatial-textual objects. Considering huge amounts of objects involved in the query processing, this paper comes up with the ideal of utilizing vehicles as fog-computing resource, and proposes the network structure called FCV, and based on which the fog-based Top-k ASKIV query is explored and formulated. In order to effectively support network distance pruning, textual semantic pruning, and numerical attribute pruning simultaneously, a two-level spatial-textual hybrid index STAG-tree is designed. Based on STAG-tree, an efficient Top-k ASKIV query processing algorithm is presented. Simulation results show that, our STAG-based approach is about 1.87x (17.1x, resp.) faster in search time than the compared ILM (DBM, resp.) method, and our approach is scalable.
    • Authentic-caller: Self-enforcing authentication in a next generation network

      Azad, Muhammad Ajmal; Bag, Samiran; Perera, Charith; Barhamgi, Mahmoud; Hao, Feng; University of Derby; University of Warwick; Computational Informatics, CSIRO, Canberra, Australian Capital Territory Australia; Universite Claude Bernard, Lyon, France (Institute of Electrical and Electronics Engineers (IEEE), 2019-09-19)
      The Internet of Things (IoT) or the Cyber-Physical System (CPS) is the network of connected devices, things and people which collect and exchange information using the emerging telecommunication networks (4G, 5G IP-based LTE). These emerging telecommunication networks can also be used to transfer critical information between the source and destination, informing the control system about the outage in the electrical grid, or providing information about the emergency at the national express highway. This sensitive information requires authorization and authentication of source and destination involved in the communication. To protect the network from unauthorized access and to provide authentication, the telecommunication operators have to adopt the mechanism for seamless verification and authorization of parties involved in the communication. Currently, the next-generation telecommunication networks use a digest-based authentication mechanism, where the call-processing engine of the telecommunication operator initiates the challenge to the request-initiating client or caller, which is being solved by the client to prove his credentials. However, the digest-based authentication mechanisms are vulnerable to many forms of known attacks e.g., the Man-In-The-Middle (MITM) attack and the password guessing attack. Furthermore, the digest-based systems require extensive processing overheads. Several Public-Key Infrastructure (PKI) based and identity-based schemes have been proposed for the authentication and key agreements. However, these schemes generally require smart-card to hold long-term private keys and authentication credentials. In this paper, we propose a novel self-enforcing authentication protocol for the SIPbased next-generation network based on a low-entropy shared password without relying on any PKI or trusted third party system. The proposed system shows effective resistance against various attacks e.g., MITM, replay attack, password guessing attack, etc. We analyze the security properties of the proposed scheme in comparison to the state of the art.
    • A cascade learning approach for automated detection of locomotive speed sensor using imbalanced data in ITS

      Li, Bo; Zhou, Sisi; Cheng, Lifang; Zhu, Rongbo; Hu, Tao; Anjum, Ashiq; He, Zheng; Zou, Yongkai; South-Central University for Nationalities, Wuhan, China; University of Derby; et al. (Institute of Electrical and Electronics Engineers (IEEE), 2019-07-11)
      Automatic and intelligent railway locomotive inspection and maintenance are fundamental issues in high-speed rail applications and intelligent transportation system (ITS). Traditional locomotive equipment inspection is carried out manually on-site by workers, and the task is exhausting, cumbersome, and unsafe. Based on computer vision and machine learning, this paper presents an approach to the automatic detection of the locomotive speed sensor equipment, an important device in locomotives. Challenges to the detection of speed sensor mainly concerns complex background, motion blur, muddy noise, and variable shapes. In this paper, a cascade learning framework is proposed, which includes two learning stages: target localization and speed sensor detection, to reduce the complexity of the research object and solve the imbalance of samples. In the first stage, histogram of oriented gradient feature and support vector machine (HOG-SVM) model is used for multi-scale detection. Then, an improved LeNet-5 model is adopted in the second stage. To solve the problem of the imbalance of positive and negative samples of speed sensor, a combination strategy which draws on four individual classifiers is designed to construct an ensemble of classifier for recognition, and the results of three different algorithms are compared. The experimental results demonstrate that our approach is effective and robust with respect to changes in speed sensor patterns for robust equipment identification.