• Battery-assisted electric vehicle charging: data driven performance analysis

      Ali, Junade; Dyo, Vladimir; Zhang, Sijing (2020-11-10)
      As the number of electric vehicles rapidly increases, their peak demand on the grid becomes one of the major challenges. A battery-assisted charging concept has emerged recently, which allows to accumulate energy during off-peak hours and in-between charging sessions to boost-charge the vehicle at a higher rate than available from the grid. While prior research focused on the design and implementation aspects of battery- assisted charging, its impact at large geographical scales remains largely unexplored. In this paper we analyse to which extent the battery-assisted charging can replace high-speed chargers using a dataset of over 3 million EV charging sessions in both domestic and public setting in the UK. We first develop a discrete-event EV charge model that takes into account battery capacity, grid supply capacity and power output among other parameters. We then run simulations to evaluate the battery-assisted charging performance in terms of delivered energy, charging time and parity with conventional high-speed chargers. The results indicate that in domestic settings battery-assisted charging provides 98% performance parity of high-speed chargers from a standard 3 kW grid connection with a single battery pack. For non-domestic settings, the battery-assisted chargers can provide 92% and 99% performance parity of high-speed chargers with 10 battery packs using 3kW and 7kW grid supply respectively.
    • Bayesian averaging over Decision Tree models for trauma severity scoring

      Schetinin, Vitaly; Jakaite, Livija; Krzanowski, Wojtek (Elsevier, 2017-12-21)
      Health care practitioners analyse possible risks of misleading decisions and need to estimate and quantify uncertainty in predictions. We have examined the “gold” standard of screening a patient's conditions for predicting survival probability, based on logistic regression modelling, which is used in trauma care for clinical purposes and quality audit. This methodology is based on theoretical assumptions about data and uncertainties. Models induced within such an approach have exposed a number of problems, providing unexplained fluctuation of predicted survival and low accuracy of estimating uncertainty intervals within which predictions are made. Bayesian method, which in theory is capable of providing accurate predictions and uncertainty estimates, has been adopted in our study using Decision Tree models. Our approach has been tested on a large set of patients registered in the US National Trauma Data Bank and has outperformed the standard method in terms of prediction accuracy, thereby providing practitioners with accurate estimates of the predictive posterior densities of interest that are required for making risk-aware decisions.
    • Bayesian averaging over decision tree models: an application for estimating uncertainty in trauma severity scoring

      Schetinin, Vitaly; Jakaite, Livija; Krzanowski, Wojtek; University of Bedfordshire; University of Exeter (Elsevier, 2018-01-11)
      Introduction For making reliable decisions, practitioners need to estimate uncertainties that exist in data and decision models. In this paper we analyse uncertainties of predicting survival probability for patients in trauma care. The existing prediction methodology employs logistic regression modelling of Trauma and Injury Severity Score(external) (TRISS), which is based on theoretical assumptions. These assumptions limit the capability of TRISS methodology to provide accurate and reliable predictions. Methods We adopt the methodology of Bayesian model averaging and show how this methodology can be applied to decision trees in order to provide practitioners with new insights into the uncertainty. The proposed method has been validated on a large set of 447,176 cases registered in the US National Trauma Data Bank in terms of discrimination ability evaluated with receiver operating characteristic (ROC) and precision–recall (PRC) curves. Results Areas under curves were improved for ROC from 0.951 to 0.956 (p = 3.89 × 10−18) and for PRC from 0.564 to 0.605 (p = 3.89 × 10−18). The new model has significantly better calibration in terms of the Hosmer–Lemeshow Hˆ" role="presentation"> statistic, showing an improvement from 223.14 (the standard method) to 11.59 (p = 2.31 × 10−18). Conclusion The proposed Bayesian method is capable of improving the accuracy and reliability of survival prediction. The new method has been made available for evaluation purposes as a web application.
    • Bayesian learning of models for estimating uncertainty in alert systems: application to air traffic conflict avoidance

      Schetinin, Vitaly; Jakaite, Livija; Krzanowski, Wojtek; University of Bedfordshire; University of Exeter (IOS Press, 2018-05-17)
      Alert systems detect critical events which can happen in the short term. Uncertainties in data and in the models used for detection cause alert errors. In the case of air traffic control systems such as Short-Term Conflict Alert (STCA), uncertainty increases errors in alerts of separation loss. Statistical methods that are based on analytical assumptions can provide biased estimates of uncertainties. More accurate analysis can be achieved by using Bayesian Model Averaging, which provides estimates of the posterior probability distribution of a prediction. We propose a new approach to estimate the prediction uncertainty, which is based on observations that the uncertainty can be quantified by variance of predicted outcomes. In our approach, predictions for which variances of posterior probabilities are above a given threshold are assigned to be uncertain. To verify our approach we calculate a probability of alert based on the extrapolation of closest point of approach. Using Heathrow airport flight data we found that alerts are often generated under different conditions, variations in which lead to alert detection errors. Achieving 82.1% accuracy of modelling the STCA system, which is a necessary condition for evaluating the uncertainty in prediction, we found that the proposed method is capable of reducing the uncertain component. Comparison with a bootstrap aggregation method has demonstrated a significant reduction of uncertainty in predictions. Realistic estimates of uncertainties will open up new approaches to improving the performance of alert systems.
    • Benefits, barriers and guideline recommendations for the implementation of serious games in education for stakeholders and policymakers

      Tsekleves, Emmanuel; Cosmas, John; Aggoun, Amar (Blackwell Publishing Ltd, 2014-10-24)
      Serious games and game-based learning have received increased attention in recent years as an adjunct to teaching and learning material. This has been well echoed in the literature with numerous articles on the use of games and game theory in education. Despite this, no policy for the incorporation of serious games in education exists to date. This review paper draws from the literature to provide guideline recommendations that would help educators and policymakers in making the first step towards this.
    • Between virtual and real: exploring hybrid interaction and communication in virtual worlds

      Christopoulos, Athanasios; Conrad, Marc; Shukla, Mitul; University of Bedfordshire (Inderscience Publishers, 2016-03-01)
      In this paper we aim to explore the potential advantages of interactions on student engagement and provide guidance to educators who seek interactive and immersive learning experiences for their students through the use of hybrid virtual learning approaches. We define as hybrid virtual learning the educational model where students are co-present and interacting simultaneously both within a virtual world and the physical classroom receiving stimuli related to the learning material in the virtual world from both directions. In order to achieve our aim, we categorised interactions in various categories and observed the complex network of interactions which can be developed in a virtual world when groups of people are working together in order to achieve different goals. The findings suggest that students spontaneously tend to use the interaction channels only when it is deemed to be necessary.
    • Bibliometric-enhanced information retrieval: 7th international BIR workshop

      Mayr, Philipp; Frommholz, Ingo; Cabanac, Guillaume; Leibniz Institutefor the Social Sciences; University of Bedfordshire; University of Toulouse (ACM, 2018-08-01)
      The Bibliometric-enhanced Information Retrieval (BIR) workshop series has started at ECIR in 2014 and serves as the annual gathering of IR researchers who address various information-related tasks on scientific corpora and bibliometrics. We welcome contributions elaborating on dedicated IR systems, as well as studies revealing original characteristics on how scientific knowledge is created, communicated, and used. This report presents all accepted papers at the 7th BIR workshop at ECIR 2018 in Grenoble, France.
    • Bibliometric-enhanced information retrieval: 8th international BIR workshop

      Cabanac, Guillaume; Frommholz, Ingo; Mayr, Philipp (Springer Verlag, 2019-04-07)
      The Bibliometric-enhanced Information Retrieval workshop series (BIR) at ECIR tackles issues related to academic search, at the crossroads between Information Retrieval and Bibliometrics. BIR is a hot topic investigated by both academia (e.g., ArnetMiner, CiteSeer χ, DocEar) and the industry (e.g., Google Scholar, Microsoft Academic Search, Semantic Scholar). An 8th iteration of the one-day BIR workshop was held at ECIR 2019.
    • Biomechanical measurement and analysis of colchicine-induced effects on cells by nanoindentation using an atomic force microscope

      Liu, Lanjiao; Zhang, Wenxiao; Li, Li; Zhu, Xinyao; Liu, Jinyun; Wang, Xinyue; Song, Zhengxun; Xu, Hongmei; Wang, Zuobin; Changchun University of Science and Technology; et al. (Elsevier, 2017-12-17)
      Colchicine is a drug commonly used for the treatment of gout, however, patients may sometimes encounter side-effects induced by taking colchicine, such as nausea, vomiting, diarrhea and kidney failure. In this regard, it is imperative to investigate the mechanism effects of colchicine on biological cells. In this paper, we present a method for the detection of mechanical properties of nephrocytes (VERO cells), hepatocytes (HL-7702 cells) and hepatoma cells (SMCC-7721 cells) in culture by atomic force microscope(AFM) to analyze the 0.1 μg/mL colchicine-induced effects on the nanoscalefor two, four and six hours. Compared to the corresponding control cells, the biomechanical properties of the VERO and SMCC-7721 cells changed significantly and the HL-7702 cells did not considerably change after the treatment when considering the same time period. Based on biomechanical property analyses, the colchicine solution made the VERO and SMCC-7721 cells harder. We conclude that it is possible to reduce the division rate of the VERO cells and inhibit the metastasis of the SMCC-7721 cells. The method described here can be applied to study biomechanics of many other types of cells with different drugs. Therefore, this work provides an accurate and rapid method for drug screening and mechanical analysis of cells in medical research.
    • Biomedical applications of capsule and rehabilitation robots

      Zhang, Guangda; Yue, Yong; Liang, Hai-Ning; Li, Dayou; Qiu, Renxi; Wang, Zuobin; Maple, Carsten; Xi'an Jiaotong-Liverpool University; University of Bedfordshire; Changchun University of Science and Technology; et al. (Institute of Electrical and Electronics Engineers Inc., 2016-03-07)
      The rapid development of emerging technologies in the areas of traditional mechanical machinery, electronic engineering and advanced micro-processors, has brought a great opportunity for the development and applications of biomedical engineering instruments with robot technology in traditional medicine. At the same time, because of the progress of human civilisation and improvement of living standards, people have higher and more critical requirements to the bio-medical technology. Under these circumstances, researchers from all over the world have made fruitful achievements in promoting the development of medical robots, medical automation and robotic manipulation. Medical robot engineering is a discipline which applies the latest results of research and development to the medical treatment and rehabilitation. This paper reviews a range of widely-used applications of the micro-robot and rehabilitation robots to provide an overview and understanding of the current development in this area.
    • Biometric behavior authentication exploiting propagation characteristics of wireless channel

      Zhao, Nan; Ren, Aifeng; Ur-Rehman, Masood; Zhang, Zhiya; Yang, Xiaodong; Hu, Fangming; Xidian University; University of Bedfordshire (Institute of Electrical and Electronics Engineers Inc., 2016-08-24)
      Massive expansion of wireless body area networks (WBANs) in the field of health monitoring applications has given rise to the generation of huge amount of biomedical data. Ensuring privacy and security of this very personal data serves as a major hurdle in the development of these systems. An effective and energy friendly authentication algorithm is, therefore, a necessary requirement for current WBANs. Conventional authentication algorithms are often implemented on higher levels of the Open System Interconnection model and require advanced software or major hardware upgradation. This paper investigates the implementation of a physical layer security algorithm as an alternative. The algorithm is based on the behavior fingerprint developed using the wireless channel characteristics. The usability of the algorithm is established through experimental results, which show that this authentication method is not only effective, but also very suitable for the energy-, resource-, and interface-limited WBAN medical applications.
    • BIRDS-bridging the gap between information science, information retrieval and data science

      Frommholz, Ingo; Liu, Haiming; Melucci, Massimo; University of Bedfordshire; University of Padova (Association for Computing Machinery, Inc, 2020-07-30)
      The BIRDS workshop aimed to foster the cross-fertilization of Information Science (IS), Information Retrieval (IR) and Data Science (DS). Recognising the commonalities and differences between these communities, the proposed full-day workshop brought together experts and researchers in IS, IR and DS to discuss how they can learn from each other to provide more user-driven data and infor-mation exploration and retrieval solutions. Therefore, the papers aimed to convey ideas on how to utilise, for instance, IS concepts and theories in DS and IR or DS approaches to support users in data and information exploration.
    • Call blocking and outage probability in energy-efficient LTE networks

      Kanwal, Kapil; Safdar, Ghazanfar Ali; Rehman, Masood Ur; University of Bedfordshire (Wiley, 2018-04-19)
      Mobile operators are continuously expanding network infrastructure through the deployment of additional base stations to satisfy ever growing user demands. In parallel, number of users is also increasing due to advancement in mobile applications. Enlarged number of users and base stations introduce major problems, such as call blocking and outage probability, due to limited resources and interference caused by frequency reuse, respectively. Both these parameters play a key role in estimation of overall system performance. Alongside, energy efficiency (EE) is a vital parameter to enable portability and longevity of mobile user equipment. This paper investigates call blocking and channel outage probability in reduced early handover (REHO) deployed Long‐Term Evolution networks. System level simulations are performed in MATLAB to analyze the performance of REHO before it is compared with Long‐Term Evolution standard and other state of the art for key performance‐related parameters including EE, outage probability, and call blocking probability. Besides increased EE, REHO is also found to be competitive enough in terms of call blocking probability in the presence of Poisson process call arrivals.
    • Can sustainable water monitoring be a reality?

      Ajmal, Tahmina; Guimares, Laura; Genthe, Bettina; Rivett, Ulrike; University of Bedfordshire; University of Porto; Water Resources - CSIR; University of Cape Town (Institute of Physics Publishing, 2020-05-13)
      In this paper, authors discuss the current methods used for surface water monitoring and the gaps left in monitoring in context of a low resourced area. Water quality monitoring [1] is a complex problem that can only be tackled through a systemic application of a transdisciplinary approach. This paper suggests use of a variety of innovative solutions adapted to the local conditions encouraging the prospect of sustainability. The approach relies on an emphasis on environmental and water quality for human life that will contribute to: 1) improved capacity building of local actors, including the role of women; 2) increased economic and social well-being at local and regional levels; and 3) protect natural capital in the region. This article reviews the state of water monitoring in low resourced area, example is taken here from Southern Arica and attempts to establish a sustainable water quality monitoring plan for application to cross-boundary water resources in the region. These are essential to diagnose and raise understanding on water quality problems in resources shared by countries with contrasting development levels. The innovative vision presented here proposes to resolve this multidimensional water quality problem by considering the broader system ranging from aquatic ecosystems providing this service to supply systems serving final consumers.
    • Cardiomyocyte contractile force changes in response to AGRWE detected by AFM

      Qu, Yingmin; Zhao, Feihu; Wang, Xinyue; Liu, Jinyun; Li, Jingmei; Song, Zhengxun; Wang, Zuobin; Changchun University of Science and Technology; Eindhoven University of Technology; University of Bedfordshire (The Institution of Engineering and Technology, 2019-05-01)
      The cardiac contractile force is an important predictor of healthy and cardiovascular diseases. The changes of cardiomyocyte contractile force in response to American ginseng root water extract (AGRWE) detected by atomic force microscope have not been investigated yet. This study examined the effects of AGRWE on single beating cardiomyocytes extracted from a newborn rat. The same cardiomyocytes were incubated with AGRWE at a concentration of 50 μg/ml for about 30 min, and the cardiomyocytes’ contractile force increased from 1.74 ± 1.01 to 3.49 ± 1.53 nN. The mean value of the contractile strain calculated was 3.32 ± 1.55% for the cardiomyocyte before the treatment with AGRWE, while for the cardiomyocyte treated with AGRWE it increased to 4.60 ± 1.35%. The results also showed that the beating rate of the same single beating cardiomyocytes was decreased from 34 ± 11 beats/min (control, n = 10) to 20 ± 9 beats/min. In conclusion, the experimental results have shown clearly that the contractile forces and strain of single beating cardiomyocytes treated with AGRWE are significantly higher than the control group, while the heart rate was decreased. It suggests that ginseng agents are promising candidates in improving cardiac functions for treating heart failure.
    • A cell range expansion framework for closed access Femtocell networks

      Tariq, Faisal; Dooley, Laurence S.; Allen, Ben; Poulton, Adrian S.; Liu, Enjie; University of Bedfordshire; Open University (Springer New York LLC, 2014-12-17)
      While femtocell networks represent a promising solution for extending high data-rate wireless services in indoor environments, despite their many benefits the short coverage distances involved can lead to frequent handovers being triggered resulting in overloading the macrocells. This handover problem is further exacerbated for users operating at the cell boundary. One solution is to keep the mobile station (MS) connected to the femtocell access points (FAP) by applying a handover bias to expand the femtocells coverage, though arbitrarily increasing the cell range can have a detrimental effect on system performance as the received interference will increase and may exceed tolerable levels. Many disparate factors including: FAP deployment density; resource constraints; and cell range expansion (CRE) influence the crucial interference-system performance nexus, and this was the motivation to analyse this relationship in order to facilitate successful FAP deployment. This paper critically analyses the impact of femtocell range expansion with a system-level simulation being undertaken for cooperative and non-cooperative resource allocation strategies. A new CRE framework for femtocell networks is then proposed, which takes cognisance of the interplay between key system parameters, with results confirming the cooperative model consistently outperforms the non-cooperative approach so affording enhanced system flexibility in terms of FAP range expansion.
    • Challenges in ROS forensics

      Abeykoon, Iroshan; Feng, Xiaohua; University of Bedfordshire (Institute of Electrical and Electronics Engineers Inc., 2020-04-09)
      The usage of robot is rapidly growth in our society. The communication link and applications connect the robots to their clients or users. This communication link and applications are normally connected through some kind of network connections. This network system is amenable of being attached and vulnerable to the security threats. It is a critical part for ensuring security and privacy for robotic platforms. The paper, also discusses about several cyber-physical security threats that are only for robotic platforms. The peer to peer applications use in the robotic platforms for threats target integrity, availability and confidential security purposes. A Remote Administration Tool (RAT) was introduced for specific security attacks. An impact oriented process was performed for analyzing the assessment outcomes of the attacks. Tests and experiments of attacks were performed in simulation environment which was based on Gazbo Turtlebot simulator and physically on the robot. A software tool was used for simulating, debugging and experimenting on ROS platform. Integrity attacks performed for modifying commands and manipulated the robot behavior. Availability attacks were affected for Denial-of-Service (DoS) and the robot was not listened to Turtlebot commands. Integrity and availability attacks resulted sensitive information on the robot.
    • Characteristics of turbulent premixed oxy-fuel combustion - a DNS study

      Peng, Zhijun; Zhong, Shenghui; Zhang, F,; University of Bedfordshire; Tianjin University (Institute of Physics Publishing, 2018-08-31)
      A 3D DNS numerical study with detail chemistry mechanism has been carried out to investigate turbulent premixed combustion with oxyfuel mixtures under similar operating conditions as happened in spark ignition Internal Combustion Engine (ICE). H2O and CO2 are adopted as the dilution in oxy-fuel combustion. The temperature profiles of oxy-H2O and oxy-CO2 combustion are consistent with those of air-fired conditions in laminar premixed flame when the molar fraction of H2O and CO2 are 73% and 66% in oxidizer, respectively. 79%, 67% molar fraction of H2O and 79%, 56% molar fraction of CO2 are also conducted to learn the effects of the dilution molar fraction on the process of flame propagation. With the molar fraction of dilution increases, the mass of C2H2 increases the flame propagation speed and the mass of CO does an opposite influence. With the investigation for effects of turbulent intensity under conditions of 73% H2O and 66% CO2 with the initial u′ of 0.8, 1.6 and 2.4 m/s, respectively, results show that the turbulent intensity has little effect on the formation of CO. It is also demonstrated that for oxy-fuel combustion, due to the disparity in laminar flame speed, an appropriate u′ is necessary to keep consistent with the flame propagation speed meanwhile to maintain suitable temperature profiles.
    • A circular patch frequency reconfigurable antenna for wearable applications

      Farooq, Waqas; Ur-Rehman, Masood; Abbasi, Qammer Hussain; Qaraqe, Khalid; University of Bedfordshire; Texas A & M University at Qatar (Institute of Electrical and Electronics Engineers Inc., 2015-12-07)
      A novel frequency reconfigurable microstrip patch antenna has been presented for 3.6 GHz and 5 GHz. Compared to the traditional, complicated and high cost frequency reconfigurable antennas, our work is featured by a simple and concise design. The frequency reconfiguration is obtained by using layers of mercury and liquid crystal polymer (LCP) on conventional patch antenna. The proposed structure was modelled and simulated using CST Microwave Studio. The antenna was first simulated in free space to check the antenna parameters such as return loss, gain, radiation pattern and efficiency. After obtaining the results, the antenna was simulated for analysing the on-body performance by using numerical model of human body. The simulated return loss for both the configurations is less than -10 dB at the radiating frequencies. The free space simulated results show the close agreement with the on-body test results.
    • Classification of colloquial Arabic tweets in real-time to detect high-risk floods

      Alabbas, Waleed; al-Khateeb, Haider; Mansour, Ali; Epiphaniou, Gregory; Frommholz, Ingo; University of Bedfordshire (Institute of Electrical and Electronics Engineers Inc., 2017-10-06)
      Twitter has eased real-time information flow for decision makers, it is also one of the key enablers for Open-source Intelligence (OSINT). Tweets mining has recently been used in the context of incident response to estimate the location and damage caused by hurricanes and earthquakes. We aim to research the detection of a specific type of high-risk natural disasters frequently occurring and causing casualties in the Arabian Peninsula, namely 'floods'. Researching how we could achieve accurate classification suitable for short informal (colloquial) Arabic text (usually used on Twitter), which is highly inconsistent and received very little attention in this field. First, we provide a thorough technical demonstration consisting of the following stages: data collection (Twitter REST API), labelling, text pre-processing, data division and representation, and training models. This has been deployed using 'R' in our experiment. We then evaluate classifiers' performance via four experiments conducted to measure the impact of different stemming techniques on the following classifiers SVM, J48, C5.0, NNET, NB and k-NN. The dataset used consisted of 1434 tweets in total. Our findings show that Support Vector Machine (SVM) was prominent in terms of accuracy (F1=0.933). Furthermore, applying McNemar's test shows that using SVM without stemming on Colloquial Arabic is significantly better than using stemming techniques.