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The increasing adoption of electric vehicles (EVs) due to technical advancements and environmental concerns requires wide deployment of public charging stations (CSs). In order to accelerate the EV penetration and predict the future CSs requirements and adopt proper policies for their deployment, studying the charging behavior of EV drivers is inevitable. This paper introduces a stochastic model that takes into consideration the behavioral characteristics of EV drivers in particular, in terms of their reaction to the EV battery charge level when deciding to charge or disconnect at a CS. The proposed model is applied in two case studies to describe the resultant collective behavior of EV drivers in a community using real field EV data obtained from a major North American campus network and part of London urban area. The model fits well to the datasets by tuning the model parameters. The sensitivity analysis of the model indicates that changes in the behavioral parameters affect the statistical characteristics of charging duration, vehicle connection time, and EV demand profile, which has a substantial effect on congestion status in CSs. This proposed model is then applied in several scenarios to simulate the congestion status in public parking lots and predict the future charging points needed to guarantee the appropriate level of service quality. The results show that studying and controlling the EV drivers’ behavior leads to a significant saving in CS capacity and results in consumer satisfaction, thus, profitability of the station owners. [ABSTRACT FROM AUTHOR]

Reducing radiation dose in cardiac catheter-based X-ray procedures increases safety but also image noise and artifacts. Excessive noise and artifacts can compromise vital image information, which can affect clinical decision-making. Developing more effective X-ray denoising methodologies will be beneficial to both patients and healthcare professionals by allowing imaging at lower radiation dose without compromising image information. This paper proposes a framework based on a convolutional neural network (CNN), namely Ultra-Dense Denoising Network (UDDN), for low-dose X-ray image denoising. To promote feature extraction, we designed a novel residual block which establishes a solid correlation among multiple-path neural units via abundant cross connections in its representation enhancement section. Experiments on synthetic additive noise X-ray data show that the UDDN achieves statistically significant higher peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) than other comparative methods. We enhanced the clinical adaptability of our framework by training using normally-distributed noise and tested on clinical data taken from procedures at St. Thomas’ hospital in London. The performance was assessed by using local SNR and by clinical voting using ten cardiologists. The results show that the UDDN outperforms the other comparative methods and is a promising solution to this challenging but clinically impactful task. [ABSTRACT FROM AUTHOR]

Cellular network deployment with three sectors per site and a frequency reuse factor of one is key to supporting high data rate applications in LTE Advanced Networks. However, such configurations result in increased inter-cell interference. In this paper we model the effects of inter-cell interference on an LTE-Advanced network at two carrier frequencies. We consider two urban environments and four cell ranges. The effects of inter-cell interference are separated into inter-site interference and inter-sector interference. A site-specific 3D ray-tracing tool is used to model the communication channel between the base stations (serving and interfering links) and the user equipment terminals. The inter-site interference is first modelled in terms of its dominant interference proportion and then validated using previously reported field measurements recorded in London (U.K.). Secondly, the inter-site and inter-sector interference components are modelled as a function of user equipment relative position from the serving base stations. Our approach is compatible with the standardized ITU-R model and our proposal can easily be added to these international models. Our model requires no system layout for the interferers and reduces the required channel generation time by a factor of 12 compared with the system layout method. [ABSTRACT FROM AUTHOR]

This paper describes a novel adaptive battery model based on a remapped variant of the well-known Randles' lead-acid model. Remapping of the model is shown to allow improved modeling capabilities and accurate estimates of dynamic circuit parameters when used with subspace parameter-estimation techniques. The performance of the proposed methodology is demonstrated by application to batteries for an all-electric personal rapid transit vehicle from the Urban Light TRAnsport (ULTRA) program, which is designated for use at Heathrow Airport, U.K. The advantages of the proposed model over the Randles' circuit are demonstrated by comparisons with alternative observer/estimator techniques, such as the basic Utkin observer and the Kalman estimator. These techniques correctly identify and converge on voltages associated with the battery state-of-charge (SoC), despite erroneous initial conditions, thereby overcoming problems attributed to SoC drift (incurred by Coulomb-counting methods due to overcharging or ambient temperature fluctuations). Observation of these voltages, as well as online monitoring of the degradation of the estimated dynamic model parameters, allows battery aging (state-of-health) to also be assessed and, thereby, cell failure to be predicted. Due to the adaptive nature of the proposed algorithms, the techniques are suitable for applications over a wide range of operating environments, including large ambient temperature variations. Moreover, alternative battery topologies may also be accommodated by the automatic adjustment of the underlying state-space models used in both the parameter-estimation and observer/estimator stages. [ABSTRACT FROM AUTHOR]

In August 2020, students took to the streets of London in a mass protest over their A-level results (that determine entry to university), chanting “F*ck the algorithm.” Their A-level grades had been determined by an algorithm that depended on past school performance, a system of teacher ratings, and for smaller student groups, the use of Centre Assessed Grades. Commendably Ofqual (the U.K. Government Office of Qualifications and Examinations Regulation) were transparent in their use of the algorithm so that affected stakeholders were informed of the algorithm’s existence and the key details of how it was developed. The design of the data set produced an algorithm with biased outputs, which hardcoded preexisting educational, policy, and societal biases. Due to the large numbers of students, the single “results day” output and the wider interests of schools, teachers, parents, and universities, the unfairness of the outcome was magnified. Add to this that the students were, by definition, academically proficient individuals, many of whom derived from privileged and supportive backgrounds, which meant that they had the awareness and capacity to challenge. Hence, the impact of this biased algorithm was not received silently and so it was hard to deny, deflect, and dismiss. However, this is not always the case, and many systems are deployed with similar biases and harmful outcomes but the impact is dissipated over time and individuals, and therefore not so immediately obvious and easy to challenge. This is particularly the case when the people impacted do not have the advantages that enabled the A-level students to challenge. [ABSTRACT FROM AUTHOR]

In this article, a compact unconditionally stable two-dimensional (2-D) stochastic weighted Laguerre polynomial finite-difference time-domain (S-WLP-FDTD) method for geometric uncertainty in superconducting transmission lines is proposed. It calculates both the Maxwell equations and the London equations and uses a weighted Laguerre polynomial (WLP) scheme to eliminate the stability constraint. The mean and the standard deviation of electromagnetic fields, voltages, and currents are calculated. Compared with the Monte Carlo method and 2-D S-FDTD method, the proposed method has the same accuracy but much higher efficiency. The runtime of the proposed S-WLP-FDTD method is only 2.4% of that of the S-FDTD method. Thus, the proposed method is suitable for predicting the influence of geometric uncertainty on superconducting transmission lines. [ABSTRACT FROM AUTHOR]

An advanced model-based control technique for regulating the blood glucose for patients with Type 1 diabetes is presented. The optimal insulin delivery rate is obtained off-line as an explicit function of the current blood glucose concentration of the patient by using novel parametric programming algorithms, developed at Imperial College London. The implementation of the optimal insulin delivery rate, therefore, requires simple function evaluation and minimal on-line computations. The proposed framework also addresses the uncertainty in the model due to interpatient and intrapatient variability by identifying the model parameters which ensure that a feasible control law can be obtained. The developments reported in this paper are expected to simplify the insulin delivery mechanism, thereby enhancing the quality of life of the patient. [ABSTRACT FROM AUTHOR]

In this article, a stochastic finite-difference time-domain (S-FDTD) method is proposed for analyzing the influence of physical size uncertainty on the time-domain response of superconducting transmission lines. The formulations of the proposed method are, in detail, derived with the two-fluid model and London equation. A typical superconducting microstrip line is simulated to verify the effectiveness of the proposed algorithm. Compared with the Monte Carlo simulation, the proposed method has the same accuracy but much higher efficiency. The computation time of the proposed S-FDTD method is only about 3% of that of the Monte Carlo simulation. Therefore, the proposed method shows a promising prospect on predicting the variability in transmission line's performance caused by variation in superconducting manufacturing. [ABSTRACT FROM AUTHOR]

According to the Encyclopadia Britannica, the establishment of the Royal Society of London for Improving Natural Knowledge (Royal Society), the "oldest national scientific society in the world," was on November 28, 1660. In 1818, the Institution of Civil Engineers (ICE), the first professional engineering body, was also set up in London. Ten years later King Georges IV granted ICE its Royal Charter. Throughout the past 200 years, the world, and Western societies in particular, have experienced deep social changes. The engineering profession has not been an exception, and today its ethos is much broader and complex than the roots and conditions that were found at its origins. What elements are required for professional self-awareness in 21st century engineers? Our goal here is to outline these potential characteristics of contemporary engineering. [ABSTRACT FROM AUTHOR]

This article is a slightly amended and extended verison of a talk given by the writer at Dieletrics 2009, organized by the Dieletrics Group of the Institute of Physics (IOP), London UK and held at the University of Reading 15-17 April 2009. It gives a breif history of the Dieletrics Discussion Group (1968-1974) and the Dieletrics Society(1974-2001) in the United Kingdom and summarizes some of the major advances in studies of dynamics of polymeric materials that occured during that period and subsequently using broadband dieletric spectroscopy (BDS). [ABSTRACT FROM AUTHOR]

This case study examines how the lean ideas behind the Toyota production system can be applied to software project management. It is a detailed investigation of the performance of a nine-person software development team employed by BBC Worldwide based in London. The data collected in 2009 involved direct observations of the development team, the kanban boards, the daily stand-up meetings, semistructured interviews with a wide variety of staff, and statistical analysis. [ABSTRACT FROM PUBLISHER]

When business strategists use option-like thinking to inform investments in physical infrastructure, developers need to operationalize leaving the options open at project implementation. This study defines safeguard as the design and physical development work for ensuring, or enhancing, the embedment of an option in the project outcome. Safeguards account for design changes stemming from option exercising if the environmental uncertainties resolve favorably in the future. They range from a design effort to secure space in a master plan (passive) to the construction of an integral component (active). A multiple-case study on the expansion of Heathrow airport shows how the confluence of two contingencies underscores decisions to safeguard under a limited budget. Safeguarding is more attractive when: 1) the assumed uncertainty that the option will get in the money is low because the outlay sunk on safeguards is more likely to pay off; and 2) the infrastructure architecture is modular because only the interfaces between components may require safeguarding. Irreversible investments on safeguards increase the option cost and reduce the exercising costs in the future. Safeguards therefore play out as a control point for strategic option-like thinking at project implementation. The empirical findings are summarized in a conceptual framework. [ABSTRACT FROM AUTHOR]

Discusses the medical imaging research activities at Guy's Hospital, King's College in London, England. Image-guided interventions; Automated image registration based on Voxel similarity; Importance of the joint histogram or joint probability distribution of image intensities; Ability to align three-dimensional models to X-ray and optical images acquired during an intervention.

The article discusses personal transportation in the 21st century, and postulates a national system of automated transport. The article discusses Cybercars, which are fully automated road vehicles. A fleet of such vehicles forms a cybernetic transportation system (CTS) for passengers or goods, operating on either a simple route or an elaborate network to provide on-demand door-to-door transportation. The CTS controls the fleet through a central management system. In 1997, a fleet of four cybercars was put into operation at Schiphol Airport in Amsterdam, Netherlands. A larger system is planned to be put into operation at Heathrow Airport in London, England in 2008. Issues discussed include obstacle avoidance, platoon operation of closely spaced vehicles, navigation, and communications.