• Polarimetric SAR image semantic segmentation with 3D discrete wavelet transform and Markov random field

      Bi, Haixia; Xu, Lin; Cao, Xiangyong; Xue, Yong; Xu, Zongben; University of Derby; University of Bristol; Shanghai Em-Data Technology Co., Ltd.; Xi’an Jiaotong University, Xi’an, China; University of Derby (IEEE, 2020-06-02)
      Polarimetric synthetic aperture radar (PolSAR) image segmentation is currently of great importance in image processing for remote sensing applications. However, it is a challenging task due to two main reasons. Firstly, the label information is difficult to acquire due to high annotation costs. Secondly, the speckle effect embedded in the PolSAR imaging process remarkably degrades the segmentation performance. To address these two issues, we present a contextual PolSAR image semantic segmentation method in this paper.With a newly defined channelwise consistent feature set as input, the three-dimensional discrete wavelet transform (3D-DWT) technique is employed to extract discriminative multi-scale features that are robust to speckle noise. Then Markov random field (MRF) is further applied to enforce label smoothness spatially during segmentation. By simultaneously utilizing 3D-DWT features and MRF priors for the first time, contextual information is fully integrated during the segmentation to ensure accurate and smooth segmentation. To demonstrate the effectiveness of the proposed method, we conduct extensive experiments on three real benchmark PolSAR image data sets. Experimental results indicate that the proposed method achieves promising segmentation accuracy and preferable spatial consistency using a minimal number of labeled pixels.
    • Understanding and managing sound exposure and noise pollution at outdoor events

      Hill, Adam J.; University of Derby (Audio Engineering Society, 2020-05-22)
      This report is intended to present the current state of affairs surrounding the issue of outdoor event-related sound and noise. The two principal areas of investigation are sound exposure on-site and noise pollution off-site. These issues are different in nature and require distinct approaches to mitigate the associated negative short-term and long-term effects. The key message that is presented throughout this report is that the problems/ambiguities with current regulations are due to a lack of unbiased, scientifically-based research. It is possible to deliver acceptably high sound levels to audience members in a safe manner (minimizing risk of hearing damage) while also minimizing annoyance in local communities, where solutions to the on-site and off-site problems should begin with a well-informed sound system design. Only with a properly designed sound system can sound/noise regulations be realistically applied.
    • A famework for data sharing between healthcare providers using blockchain

      Alzahrani, Ahmed G.; Alenezi, Ahmed; Atlam, Hany F.; Wills, Gary; University of Southampton (SCITEPRESS - Science and Technology Publications, 2020-05)
      The healthcare data are considered as a highly valuable source of information that can improve healthcare systems to be more intelligent and improve the quality of the provided services. However, due to security and privacy issues, sharing data between healthcare organisations is challenging. This has led to data shortage in the healthcare sector which is considered as a significant issue not only in the Kingdom of Saudi Arabia (KSA) but also worldwide. The primary objective of conducting this paper is to investigate the various factors that enable secure sharing and exchange of healthcare information between different healthcare providers in the KSA. It starts by discussing the current literature and frameworks for managing healthcare data information and the challenges that health providers encounter, particularly when it comes to issues such as data security, patient privacy, and healthcare information exchange. These challenges in managing healthcare data have necessitated the nee d for implementing a solution that can allow medical providers to have access to updated healthcare information. Attention in the healthcare sector has been drawn to blockchain technology as a part of the solution, especially after the technology was successfully applied in the financial sector to improve the security of financial transactions, particularly involving digital currencies such as Bitcoin. Therefore, a framework based on the blockchain technology has been proposed to achieve the goals of the present research.
    • Optimizing computational resource management for the scientific gateways ecosystems based on the service‐oriented paradigm

      Martins de Oliveira, Edvard; Estrella, Júlio Cézar; Botazzo Delbem, Alexandre Claudio; Souza Pardo, Mário Henrique; Guzzo da Costa, Fausto; Defelicibus, Alexandre; Reiff‐Marganiec, Stephan; Federal University of Itajubá, Brazil; University of Sao Paulo, Brazil; A.C. Camargo Cancer Center, Sao Paulo, Brazil; et al. (Wiley, 2020-02-26)
      Science Gateways provide portals for experiments execution, regardless of the users' computational background. Nowadays its construction and performance need enhancement in terms of resource provision and task scheduling. We present the Modular Distributed Architecture to support the Protein Structure Prediction (MDAPSP), a Service‐Oriented Architecture for management and construction of Science Gateways, with resource provisioning on a heterogeneous environment. The Decision Maker, central module of MDAPSP, defines the best computational environment according to experiment parameters. The proof of concept for MDAPSP is presented in WorkflowSim, with two novel schedulers. Our results demonstrate good Quality of Service (QoS), capable of correctly distributing the workload, fair response times, providing load balance, and overall system improvement. The study case relies on PSP algorithms and the Galaxy framework, with monitoring experiments to show the bottlenecks and critical aspects.
    • 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.
    • MARINE: Man-in-the-middle attack resistant trust model IN connEcted vehicles

      Ahmad, Farhan; Kurugollu, Fatih; Adnane, Asma; Hussain, Rasheed; Hussain, Fatima; University of Derby; Loughborough university; Innopolis University, Russia; API Delivery & Operations, Royal Bank of Canada, Toronto, Canada (IEEE, 2020-01-17)
      Vehicular Ad-hoc NETwork (VANET), a novel technology holds a paramount importance within the transportation domain due to its abilities to increase traffic efficiency and safety. Connected vehicles propagate sensitive information which must be shared with the neighbors in a secure environment. However, VANET may also include dishonest nodes such as Man-in-the-Middle (MiTM) attackers aiming to distribute and share malicious content with the vehicles, thus polluting the network with compromised information. In this regard, establishing trust among connected vehicles can increase security as every participating vehicle will generate and propagate authentic, accurate and trusted content within the network. In this paper, we propose a novel trust model, namely, Man-in-the-middle Attack Resistance trust model IN connEcted vehicles (MARINE), which identifies dishonest nodes performing MiTM attacks in an efficient way as well as revokes their credentials. Every node running MARINE system first establishes trust for the sender by performing multi-dimensional plausibility checks. Once the receiver verifies the trustworthiness of the sender, the received data is then evaluated both directly and indirectly. Extensive simulations are carried out to evaluate the performance and accuracy of MARINE rigorously across three MiTM attacker models and the bench-marked trust model. Simulation results show that for a network containing 35% MiTM attackers, MARINE outperforms the state of the art trust model by 15%, 18%, and 17% improvements in precision, recall and F-score, respectively.
    • 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.
    • 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.
    • 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.
    • Privacy-preserving crowd-sensed trust aggregation in the user-centeric internet of people networks

      Azad, Muhammad; Perera, Charith; Bag, Samiran; Barhamgi, Mahmoud; Hao, Feng; University of Derby; Cardiff University; University of Warwick; Universite Claude Bernard Lyon (ACM, 2020)
      Today we are relying on the Internet technologies for various types of services ranging from personal communication to the entertainment. The online social networks (Facebook, twitter, youtube) has seen an increase in subscribers in recent years developing a social network among people termed as the Internet of People. In such a network, subscribers use the content disseminated by other subscribers. The malicious users can also utilize such platforms for spreading the malicious and fake content that would bring catastrophic consequences to a social network if not identified on time. People crowd-sensing on the Internet of people system has seen a prospective solution for the large scale data collection by leveraging the feedback collections from the people of the internet that would not only help in identifying malicious subscribers of the network but would also help in defining better services. However, the human involvement in crowd-sensing would have challenges of privacy-preservation, intentional spread of false high score about certain user/content undermining the services, and assigning different trust scores to the peoples of the network without disclosing their trust weights. Therefore, having a privacy-preserving system for computing trust of people and their content in the network would play a crucial role in collecting high-quality data from the people. In this paper, a novel trust model is proposed for evaluating the trust of the people in the social network without compromising the privacy of the participating people. The proposed systems have inherent properties of the trust weight assignment to a different class of user i.e. it can assign different weights to different users of the network, has decentralized setup, and ensures privacy properties under the malicious and honest but curious adversarial model. We evaluated the performance of the system by developing a prototype and applying it to different online social network dataset.
    • Security, cybercrime and digital forensics for IoT

      Atlam, Hany F.; Alenezi, Ahmed; Alassafi, Madini O.; Alshdadi, Abdulrahman A.; Wills, Gary B.; University of Southampton; Menoufia University, Menouf, Egypt; Northern Border University, Rafha, Saudi Arabia; King Abdulaziz University, Jeddah, Saudi Arabia; University of Jeddah, Jeddah, Saudi Arabia (Springer International Publishing, 2019-11-14)
      The Internet of Things (IoT) connects almost all the environment objects whether physical or virtual over the Internet to produce new digitized services that improve people’s lifestyle. Currently, several IoT applications have a direct impact on our daily life activities including smart agriculture, wearables, connected healthcare, connected vehicles, and others. Despite the countless benefits provided by the IoT system, it introduces several security challenges. Resolving these challenges should be one of the highest priorities for IoT manufacturers to continue the successful deployment of IoT applications. The owners of IoT devices should guarantee that effective security measures are built in their devices. With the developments of the Internet, the number of security attacks and cybercrimes has increased significantly. In addition, with poor security measures implemented in IoT devices, the IoT system creates more opportunities for cybercrimes to attack various application and services of the IoT system resulting in a direct impact on users. One of the approaches that tackle the increasing number of cybercrimes is digital forensics. Cybercrimes with the power of the IoT technology can cross the virtual space to threaten human life, therefore, IoT forensics is required to investigate and mitigate against such attacks. This chapter presents a review of IoT security and forensics. It started with reviewing the IoT system by discussing building blocks of an IoT device, essential characteristic, communication technologies and challenges of the IoT. Then, IoT security by highlighting threats and solutions regarding IoT architecture layers are discussed. Digital forensics is also discussed by presenting the main steps of the investigation process. In the end, IoT forensics is discussed by reviewing related IoT forensics frameworks, discussing the need for adopting real-time approaches and showing various IoT forensics.
    • 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.
    • The transparency of binaural auralisation using very high order circular harmonics

      Dring, Mark; Wiggins, Bruce; University of Derby (Institute of Acoustics, 2019-11)
      Ambisonics to binaural rendering has become the de facto format for processing and reproducing spatial sound scenes, but direct capture and software generated output is limited to low orders; limiting the accuracy of psycho-acoustic cues and therefore the illusion of a ‘real-world’ experience. Applying a practical method through the use of acoustic modelling software, this study examines the potential of using very high horizontal only Ambisonic orders (up to 31st) to binaural rendering. A novel approach to the scene capturing process is implemented to realise these very high orders for a reverberant space with head-tracking capabilities. A headphone based subjective test is conducted, evaluating specific attributes of a presented auditory scene to determine when a limit to the perceived auditory differences of varying orders has been reached.
    • A case study on sound level monitoring and management at large-scale music festivals

      Hill, Adam J.; Kok, Marcel; Mulder, Johannes; Burton, Jon; Kociper, Alex; Berrios, Anthony; University of Derby; Murdoch University; dBcontrol; Gand Concert Sound (Institute of Acoustics, 2019-11)
      Sound level management at live events has been made immeasurably easier over the past decade or so through use of commercially-available sound level monitoring software. This paper details a study conducted at a large-scale multi-day music festival in Chicago, USA. The focus was twofold: first to explore how the use of noise monitoring software affects the mix level from sound engineers and second on how crowd size, density and distribution affect the mix level. Additionally, sound levels at various points in the audience were monitored to indicate audience sound exposure over the duration of the festival. Results are presented in relation to those from previous studies with key findings pointing towards recommendations for best practice.
    • Remarks on a family of complex polynomials

      Andrica, Dorin; Bagdasar, Ovidiu; University of Derby (University of Belgrade, 2019-10-30)
      Integral formulae for the coefficients of cyclotomic and polygonal polynomials were recently obtained in [2] and [3]. In this paper, we define and study a family of polynomials depending on an integer sequence m1, . . . , mn, . . . , and on a sequence of complex numbers z1, . . . , zn, . . . of modulus one. We investigate some particular instances such as: extended cyclotomic, extended polygonal-type, and multinomial polynomials, for which we obtain formulae for the coefficients. Some novel related integer sequences are also derived.
    • Privacy verification of photoDNA based on machine learning

      Nadeem, Muhammad Shahroz; Franqueira, Virginia N. L.; Zhai, Xiaojun; University of Derby, College of Engineering and Technology; University of Essex, School of Computer Science and Electronic Engineering (The Institution of Engineering and Technology (IET), 2019-10-09)
      PhotoDNA is a perceptual fuzzy hash technology designed and developed by Microsoft. It is deployed by all major big data service providers to detect Indecent Images of Children (IIOC). Protecting the privacy of individuals is of paramount importance in such images. Microsoft claims that a PhotoDNA hash cannot be reverse engineered into the original image; therefore, it is not possible to identify individuals or objects depicted in the image. In this chapter, we evaluate the privacy protection capability of PhotoDNA by testing it against machine learning. Specifically, our aim is to detect the presence of any structural information that might be utilized to compromise the privacy of the individuals via classification. Due to the widespread usage of PhotoDNA as a deterrent to IIOC by big data companies, ensuring its ability to protect privacy would be crucial. In our experimentation, we achieved a classification accuracy of 57.20%.This result indicates that PhotoDNA is resistant to machine-learning-based classification attacks.
    • Calibration approaches for higher order ambisonic microphones

      Middlicott, Charlie; Wiggins, Bruce; University of Derby; Sky Labs (Audio Engineering Society, 2019-10-08)
      Recent years have seen an increase in the capture and production of ambisonic material due to companies such as YouTube and Facebook utilizing ambisonics for spatial audio playback. Consequently, there is now a greater need for affordable high order microphone arrays due to this uptake in technology. This work details the development of a five-channel circular horizontal ambisonic microphone intended as a tool to explore various optimization techniques, focusing on capsule calibration & pre-processing approaches for unmatched capsules.
    • 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.
    • Designing privacy-aware internet of things applications

      Perera, Charith; Barhamgi, Mahmoud; Bandara, Arosha K.; Ajmal, Muhammad; Price, Blaine; Nuseibeh, Bashar; Cardiff University; Universite Claude Bernard Lyon; Open University, United Kingdom; University of Derby (Elsevier BV, 2019-09-28)
      Internet of Things (IoT) applications typically collect and analyse personal data that can be used to derive sensitive information about individuals. However, thus far, privacy concerns have not been explicitly considered in software engineering processes when designing IoT applications. With the advent of behaviour driven security mechanisms, failing to address privacy concerns in the design of IoT applications can also have security implications. In this paper, we explore how a Privacy-by-Design (PbD) framework, formulated as a set of guidelines, can help software engineers integrate data privacy considerations into the design of IoT applications. We studied the utility of this PbD framework by studying how software engineers use it to design IoT applications. We also explore the challenges in using the set of guidelines to influence the IoT applications design process. In addition to highlighting the benefits of having a PbD framework to make privacy features explicit during the design of IoT applications, our studies also surfaced a number of challenges associated with the approach. A key finding of our research is that the PbD framework significantly increases both novice and expert software engineers’ ability to design privacy into IoT applications.
    • 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.