• A scalable and license free 5G Internet of radio light architecture for services in homes businesses

      Cosmas, John; Meunier, Ben; Ali, Kareem; Jawad, Nawar; Salih, Mukhald; Meng, Hong-Ying; Ganley, Martin; Gbadamosi, James; Savov, Atanas; Hadad, Zion; et al. (IEEE Computer Society, 2018-08-16)
      In this paper we present a 5G Internet Radio-Light (IoRL) architecture for homes that can be readily deployed because it utilizes unlicensed visible light and millimeter wave part of the spectrum, which does not require Mobile Network Operator (MNO) permission to deploy and which is used to provide inhabitants of houses with accurate location, interaction, access to Internet and Cloud based services such as high resolution video on a Tablet PC. The paper describes the home use cases and the IoRL architecture.
    • Scalable DB+IR technology: processing Probabilistic Datalog with HySpirit

      Frommholz, Ingo; Roelleke, Thomas; University of Bedfordshire; Queen Mary, University of London (Springer Verlag, 2016-01-26)
      Probabilistic Datalog (PDatalog, proposed in 1995) is a probabilistic variant of Datalog and a nice conceptual idea to model Information Retrieval in a logical, rule-based programming paradigm. Making PDatalog work in real-world applications requires more than probabilistic facts and rules, and the semantics associated with the evaluation of the programs. We report in this paper some of the key features of the HySpirit system required to scale the execution of PDatalog programs. Firstly, there is the requirement to express probability estimation in PDatalog. Secondly, fuzzy-like predicates are required to model vague predicates (e.g. vague match of attributes such as age or price). Thirdly, to handle large data sets there are scalability issues to be addressed, and therefore, HySpirit provides probabilistic relational indexes and parallel and distributed processing. The main contribution of this paper is a consolidated view on the methods of the HySpirit system to make PDatalog applicable in real-scale applications that involve a wide range of requirements typical for data (information) management and analysis.
    • Scheduling policies based on dynamic throughput and fairness tradeoff control in LTE-A networks

      Comşa, Ioan-Sorin; Aydin, Mehmet Emin; Zhang, Sijing; Kuonen, Pierre; Wagen, Jean–Frédéric; Lu, Yao; University of Bedfordshire; University of Applied Sciences of Western Switzerland (IEEE Computer Society, 2014-10-16)
      In LTE-A cellular networks there is a fundamental trade-off between the cell throughput and fairness levels for preselected users which are sharing the same amount of resources at one transmission time interval (TTI). The static parameterization of the Generalized Proportional Fair (GPF) scheduling rule is not able to maintain a satisfactory level of fairness at each TTI when a very dynamic radio environment is considered. The novelty of the current paper aims to find the optimal policy of GPF parameters in order to respect the fairness criterion. From sustainability reasons, the multi-layer perceptron neural network (MLPNN) is used to map at each TTI the continuous and multidimensional scheduler state into a desired GPF parameter. The MLPNN non-linear function is trained TTI-by-TTI based on the interaction between LTE scheduler and the proposed intelligent controller. The interaction is modeled by using the reinforcement learning (RL) principle in which the LTE scheduler behavior is modeled based on the Markov Decision Process (MDP) property. The continuous actor-critic learning automata (CACLA) RL algorithm is proposed to select at each TTI the continuous and optimal GPF parameter for a given MDP problem. The results indicate that CACLA enhances the convergence speed to the optimal fairness condition when compared with other existing methods by minimizing in the same time the number of TTIs when the scheduler is declared unfair.
    • Security and forensics challenges to the MK smart project

      Okai, Ebenezer; Feng, Xiaohua; Sant, Paul; University of Bedfordshire (Institute of Electrical and Electronics Engineers Inc., 2020-04-09)
      MK Smart project is a joint initiative which is led by the Open university and supported by Key players such as University of Bedfordshire (Milton Keynes Campus), University of Cambridge, British Telecom (BT), Milton Keynes Council, E. ON, Anglian Water, HR Wallingford Ltd, Satellite Applications Catapult, Community Action MK, Fronesys, Graymatter and Playground Energy. The project is partly funded by HEFCE (the Higher Education Funding Council for England) and led by The Open University with the primarily aim of developing innovative solutions to support the economic growth in Milton Keynes [MK Smart]. MK Data Hub is the central infrastructure to the project which supports the acquisition and management of the big data from various data sources relevant to the city systems. [MK Smart, 2014]. Whilst the data plays crucial part to this project, its forensic value of the data held is also important to the investigation of this project. Data might be required to help in any forensic investigation to be proven in a case of Data integrity. The challenges of security and forensics to this project may be hinderance to its future. Mitigating these challenges can go a long way not only to this project but to other smart cities projects. This paper concentrates on realising the security and forensics challenges of the MK Smart project, primarily looking at the challenges of securing such a huge data on a datahub and concentrating on the best possible way to forensically investigate the large complex data such as the data stored on the Datahub.
    • Security audit in mobile apps security design

      Feng, Xiaohua; Conrad, Marc (Association for Computing Machinery, 2018-11-01)
      Security design of mobile apps is very important, and it is also important that researchers consider and disseminate the continually changing requirements. For mobile application i.e. a software program that runs on a mobile phone, its design, development and management need to consider security impact. In particular, because of mobile app is running on online devices, cyber security defense is required. In this chapter, mobile app security is discussed from the initial planning and design stage to its maintenance after its launch.
    • Security challenges in cyber systems

      Safdar, Ghazanfar Ali; Kalsoom, Tahera; Ramzan, Naeem; University of Bedfordshire; University of the West of Scotland (Institute of Electrical and Electronics Engineers Inc., 2020-09-29)
      CPS (Cyber-Physical Systems) is proposed by the NSF (National Scientific Foundation) to describe a type of necessities which conglomerates hardware and software components and being the next step in development of embedded systems. CPS includes a wide range of research topics from signal processing to data analysis. This paper contains a brief review of the basic infrastructure for CPS including smart objects and network aspects in relation to TCP/IP stack. As CPS reflect the processes of the physical environment onto the cyber space, virtualisation as important tool for abstraction plays crucial role in CPS. In this context paper presents the challenges associated with mobility and vritualisation; accordingly, three main types of virtualisation, namely network, devices and applications virtualisation are presented in the paper. The main focus of the paper is made on security. Different threats, attack types and possible consequences are discussed as well as analysis of various approaches to cope with existing threats is introduced. Furthermore, needs and requirements for safety-critical CPS are reviewed.
    • Selective anticancer effect of Phellinus linteus on epidermoid cell lines studied by atomic force microscopy: anticancer activity on A431 cancer cells and low toxicity on HaCat normal cells

      Gao, Mingyan; Huang, Yuxi; Hu, Cuihua; Hu, Jing; Wang, Ying; Chen, Yujuan; Song, Guicai; Song, Zhengxun; Wang, Zuobin; Ministry of Education Key Laboratory for Cross-Scale Micro and Nano Manufacturing; et al. (Institute of Electrical and Electronics Engineers Inc., 2020-12-02)
      The research on the morphological and mechanical properties of single cells has provided a crucial way of understanding the cellular physiology and metabolism. In this study, the selective anticancer effects of Phellinus linteus on A431 and HaCat cells and their morphological and mechanical properties were systematically investigated by atomic force microscopy (AFM). Notably, the cell morphology on the micronano scale was observed under both the physiological environment and immobilization conditions. The significant morphological changes of A431 cells from the flat to spherical shape, the increase of cell height, and the decrease of the particles on the cell membrane were confirmed to be related to the cell apoptosis under the treatment of the Phellinus linteus water extract (PLWE). Moreover, the small morphology variations of HaCat cells showed that the PLWE presented a high anticancer effect on A431 cells but low toxicity on HaCat cells, which indicated a potential cell selectivity between cancer and normal cells. This work proved that Phellinus linteus could be used as a potential candidate for selective anticancer treatments.
    • Self-fibering growth in the soot-templated CVD coating of silica on mesh for efficient oil/water separation

      Zhang, Feng; Shi, Zhenwu; Xu, Chengyun; Huo, Dayun; Zhang, Wei; Peng, Changsi; Soochow University; University of Bedfordshire (Elsevier, 2018-05-18)
      A comprehensive study of SiO2 grown by chemical vapor deposition is conducted on soot coated copper mesh, from which an excellent superhydrophobic-superoleophilic filter mesh is demonstrated using the structure of nano-fibered network. A dynamical model of “flow-guided dehydration” including the microscopic interplay between “flow-induced diffusion” and dehydration is presented. Furthermore, we present a device based on tubular separator to purify oily wastewater that is very much like tap-water delivering in daily life, which does not cause the problem of water blockage.
    • Self-IQ-demodulation based compensation scheme of frequency-dependent IQ imbalance for wideband direct-conversion transmitters

      Li, Wei; Zhang, Yue; Huang, Li-Ke; Cosmas, John; Maple, Carsten; Xiong, Jian; Cobham Wireless; University of Bedfordshire; Brunel University; University of Warwick; et al. (Institute of Electrical and Electronics Engineers Inc., 2015-09-25)
      A low cost frequency-dependent (FD) I/Q imbalance self-compensation scheme is investigated in this paper. The direct conversion transmitters are widely used in wireless systems. However, the unwanted image-frequencies and distortions are inevitably introduced into the direct conversion system. This problem is even severer in wideband systems. Therefore, the accurate estimation and compensation of I/Q imbalance is crucial. The current compensation method is based on external instruments or internal feedback path which introduces additional impairments and is expensive. This paper proposes a low cost FD I/Q imbalance self-IQ-demodulation based compensation scheme without using external calibration instruments. First, the impairments of baseband and RF components are investigated. Further, I/Q imbalance model is developed. Then, the proposed two-step self-IQ-demodulation based compensation scheme is investigated. In the first step of the scheme, the local oscillator (LO) related I/Q impairments parameters are estimated. Then in the second step, the overall FD I/Q imbalance parameters are estimated by utilizing the transmitter LO. To realize this self-IQ-demodulation algorithm, this paper introduces minor modifications to the current power detector circuit. Afterwards, the estimated parameters are applied to the baseband equivalent compensator. This sophisticated algorithm guarantees low computation complexity and low cost. The compensation performance is evaluated in laboratory measurement.
    • Self-repair behaviour of the neuronal cell membrane by conductive atomic force indentation

      Liu, Caijun; Han, Xueyan; Yang, Xueying; Tian, Liguo; Wang, Ying; Wang, Xinyue; Yang, Huanzhou; Ge, Zenghui; Hu, Cuihua; Liu, Chuanzhi; et al. (The Institution of Engineering and Technology, 2019-09-04)
      Conductive atomic force indentation (CAFI) was proposed to study the self-repair behaviour of the neuronal cell membrane here. CAFI was used to detect the changes of membrane potentials by performing the mechanical indentation on neurons with a conductive atomic force microscope. In the experiment, a special insulation treatment was made on the conductive probe, which turned out to be a conductive nanoelectrode, to implement the CAFI function. The mechanical properties of the neuronal cell membrane surface were tested and the membrane potential changes of neurons cultured in vitro were detected. The self-repair behaviour of the neuronal cell membrane after being punctured was investigated. The experiment results show that CAFI provides a new way for the study of self-repair behaviours of neuronal cell membranes and mechanical and electrical properties of living cells.
    • Semantic Hilbert space for interactive image retrieval

      Jaiswal, Amit Kumar; Liu, Haiming; Frommholz, Ingo; University of Bedfordshire (Association for Computing Machinery, Inc, 2021-07-11)
      The paper introduces a model for interactive image retrieval utilising the geometrical framework of information retrieval (IR). We tackle the problem of image retrieval based on an expressive user information need in form of a textual-visual query, where a user is attempting to find an image similar to the picture in their mind during querying. The user information need is expressed using guided visual feedback based on Information Foraging which lets the user perception embed within the model via semantic Hilbert space (SHS). This framework is based on the mathematical formalism of quantum probabilities and aims to understand the relationship between user textual and image input, where the image in the input is considered a form of visual feedback. We propose SHS, a quantum-inspired approach where the textual-visual query is regarded analogously to a physical system that allows for modelling different system states and their dynamic changes thereof based on observations (such as queries, relevance judgements). We will be able to learn the input multimodal representation and relationships between textual-image queries for retrieving images. Our experiments are conducted on the MIT States and Fashion200k datasets that demonstrate the effectiveness of finding particular images autocratically when the user inputs are semantically expressive.
    • Semantic lifting and reasoning on the personalised activity big data repository for healthcare research

      Yu, Hong Qing; Zhao, Xia; Deng, Zhikun; Dong, Feng (IEEE, 2017-10-01)
      The fast growing markets of smart health monitoring devices and mobile applications provide opportunities for common citizens to have capability for understanding and managing their own health situations. However, there are many challenges for data engineering and knowledge discovery research to enable efficient extraction of knowledge from data that is collected from heterogonous devices and applications with big volumes and velocity. This paper presents research that initially started with the EC MyHealthAvatar project and is under continual improvement following the project’s completion. The major contribution of the work is a comprehensive big data and semantic knowledge discovery framework which integrates data from varied data resources. The framework applies hybrid database architecture of NoSQL and RDF repositories with introductions for semantic oriented data mining and knowledge lifting algorithms. The activity stream data is collected through Kafka’s big data processing component. The motivation of the research is to enhance the knowledge management, discovery capabilities and efficiency to support further accurate health risk analysis and lifestyle summarisation.
    • Semantic lifting and reasoning on the personalised activity big data repository for healthcare research

      Yu, Hong Qing; Dong, Feng (Inderscience Publishers, 2019-10-08)
      The fast growing markets of smart health monitoring devices and mobile applications provide opportunities for common citizens to have capability for understanding and managing their own health situations. However, there are many challenges for data engineering and knowledge discovery research to enable efficient extraction of knowledge from data that is collected from heterogonous devices and applications with big volumes and velocity. This paper presents research that initially started with the EC MyHealthAvatar project and is under continual improvement following the project's completion. The major contribution of the work is a comprehensive big data and semantic knowledge discovery framework which integrates data from varied data resources. The framework applies hybrid database architecture of NoSQL and RDF repositories with introductions for semantic oriented data mining and knowledge lifting algorithms. The activity stream data is collected through Kafka's big data processing component. The motivation of the research is to enhance the knowledge management, discovery capabilities and efficiency to support further accurate health risk analysis and lifestyle summarisation.
    • Semi-supervised learning for cancer detection of lymph node metastases

      Jaiswal, Amit Kumar; Panshin, Ivan; Shulkin, Dimitrij; Aneja, Nagender; Abramov, Samuel; University of Bedfordshire; Perm State University; Schaeffler Group; Universiti Brunei Darussalam; Abramav Software (2019-06-14)
      Pathologists find tedious to examine the status of the sentinel lymph node on a large number of pathological scans. The examination process of such lymph node which encompasses metastasized cancer cells is histopathologically organized. However, the task of finding metastatic tissues is gradual which is often challenging. In this work, we present our deep convolutional neural network based model validated on PatchCamelyon (PCam) benchmark dataset for fundamental machine learning research in histopathology diagnosis. We find that our proposed model trained with a semi-supervised learning approach by using pseudo labels on PCam-level significantly leads to better performances to strong CNN baseline on the AUC metric.
    • Sentiment analysis of Arabic tweets in e-learning

      AL-Rubaiee, Hamed Saad; Qiu, Renxi; Alomar, Khalid; Li, Dayou (Science Publisher, 2016-12-13)
      In this study, we present the design and implementation of Arabic text classification in regard to university students' opinions through different algorithms such as Support Vector Machine (SVM) and Naive Bayes (NB). The aim of the study is to develop a framework to analyse Twitter "tweets" as having negative, positive or neutral sentiments in education or, in other words, to illustrate the relationship between the sentiments conveyed in Arabic tweets and the students' learning experiences at universities. Two experiments were carried out, one using negative and positive classes only and the other one with a neutral class. The results show that in Arabic, a sentiments SVM with an n-gram feature achieved higher accuracy than NB both with using negative and positive classes only and with the neutral class.
    • Setting social media privacy controls: a practical guide to protecting yourself

      Brown, Antony; Gibson, Marcia; Short, Emma; Barnes, Jim; University of Bedfordshire (Andrews UK, 2015-04-19)
    • A simple, cost-effective and practical implementation of SLAM using ROS and Arduino

      Ibáñez, Adrián Lendínez; Qiu, Renxi; Li, Dayou; University of Bedfordshire (Institute of Electrical and Electronics Engineers Inc., 2018-02-01)
      This paper aims to introduce the reader to the Simultaneous Localization and Mapping (SLAM) problem in the context of robot mapping by providing a real, simple and powerful implementation using the Robot Operating System (ROS) framework and Arduino technology. In addition to this, a modest, yet convenient, theoretical explanation of the algorithm (Rao-Blackwellization particle filter) used, is included. The creation of an inexpensive differential drive robot for this purpose is detailed along with the experiments conducted with the platform to map domestic environments. This work is targeted to students willing to get familiar with the presented subject by giving them the means to construct and code their own robot for 2D mapping.
    • Single-cell patterning technology for biological applications

      Wang, Zihui; Lang, Baihe; Qu, Yingmin; Li, Li; Song, Zhengxun; Wang, Zuobin; ; Changchun University of Science and Technology; University of Bedfordshire (AIP Publishing, 2019-11-11)
      Single-cell patterning technology has revealed significant contributions of single cells to conduct basic and applied biological studies in vitro such as the understanding of basic cell functions, neuronal network formation, and drug screening. Unlike traditional population-based cell patterning approaches, single-cell patterning is an effective technology of fully understanding cell heterogeneity by precisely controlling the positions of individual cells. Therefore, much attention is currently being paid to this technology, leading to the development of various micro-nanofabrication methodologies that have been applied to locate cells at the single-cell level. In recent years, various methods have been continuously improved and innovated on the basis of existing ones, overcoming the deficiencies and promoting the progress in biomedicine. In particular, microfluidics with the advantages of high throughput, small sample volume, and the ability to combine with other technologies has a wide range of applications in single-cell analysis. Here, we present an overview of the recent advances in single-cell patterning technology, with a special focus on current physical and physicochemical methods including stencil patterning, trap- and droplet-based microfluidics, and chemical modification on surfaces via photolithography, microcontact printing, and scanning probe lithography. Meanwhile, the methods applied to biological studies and the development trends of single-cell patterning technology in biological applications are also described.
    • Sit-to-stand intention recognition

      Wang, Zuobin; Li, Dayou; Lu, Hang; Qiu, Renxi; Maple, Carsten; University of Bedfordshire; Changchun University of Science and Technology; Warwick University (Springer Science and Business Media Deutschland GmbH, 2021-01-23)
      Sit-to-stand (STS) difficulties are common among elderly because of the decline of their cognitive capabilities and motor functions. The way to help is to encourage them to practice their own functions and to assist only at the point where they need during STS processes. The provision of such support requires the elderly’s intention of standing up to be recognised and the amount of support as well as the moment when the support would be needed to be predicted. The research presented in this paper focuses on intention recognition as it is difficult due to uncertainties existing in STS processes and differences in individual’s biomechanical features. This paper presents fuzzy logic based self-adaptive approach to the recognition of standing up intention from sensor signals that contain the uncertainties.
    • Smart Cities survey

      Okai, Ebenezer; Feng, Xiaohua; Sant, Paul; University of Bedfordshire (Institute of Electrical and Electronics Engineers Inc., 2019-01-24)
      Smart city provides solutions to our rapid urbanisation. There is a general and growing concern of the challenges, that cities will encounter based on the current growth pace. This paper elaborates on the benefits and challenges of smart cities. The paper also discusses about the foreseen future of smart cities and what features characterise a smart city.