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Proposes to compare two models ‐ finite element method and “magnetic” equivalent scheme ‐ for numerical modelling of electromagnetic systems. Both these approaches coupled with electric circuit equations take into account saturation effects. Uses a machine of 5.5kW as a model to show the validity of these approaches. Compares the results obtained from numerical calculation with experimental ones.

This paper aims to present a review of the design and development of the turbidimeter for measuring the turbidity level in water. Monitoring the turbidity level of water is important because it is related to public health.

A precise and reliable turbidimeter can provide vital data that reveals the water condition level. Several turbidimeter units are discussed briefly. Three types of turbidimeter design – single beam, ratio and modulated four beams – are elaborated with some illustrations of the design concept. Various improvements and innovations for upgrading turbidimeter design are also discussed.

This paper elaborated on a new method of estimating the water turbidity level in water samples using an optical tomography system based on the independent component analysis method. The results showed that a tomography-based turbidimeter can measure slight changes in the level of turbidity when the volume of contaminants is changed slightly. The turbidimeter can also provide a profile of the distribution of the turbidity in the water sample.

A turbidimeter based on the optical tomography concept can be a valuable tool in determining the level of pollution in rivers, sea, etc.

Developing general purpose mobile robots is very much dependent on the availability of suitable sensors. A common choice by researchers is ultrasonics and work at the Laboratory of Applied Advanced Electronic Techniques (LATEA) has resulted in a simple, self‐adapting and self‐correcting ultrasonic sensor,

The aim of this article is to investigate the nature of use and impact of the Improve Your Library self‐evaluation process on school libraries and their integration into whole‐school development planning for pupil learning.

The research is structured in two phases. Phase one seeks to map levels, patterns and experiences of use by those responsible for the library within schools and to establish the nature of support needed for librarians from school library services and training providers. Phase two will track schools in detail to explore the extent of difference the process may have on library integration into the wider school self‐evaluation, development priorities and planning, and on library contribution to pupil reading and learning.

Preliminary investigations indicate that there is considerable diversity in current evaluation practice and in expectations of the Improve Your Library toolkits. There is a need for a national vehicle for sharing individual library experience to inform reflective practice.

The research focused on English schools. Successful delivery of the intended case banks of practice examples is dependent on a good range of schools being willing to share their experience.

Training and support needs and networks will be identified for providers and practitioners. Practical experience will be made available to librarians, school management and policy‐makers.

This is a timely evaluation of the first unified system of library self‐evaluation across English schools within the context of a new approach to whole‐school evaluation. It will provide librarians with a means of sharing and comparing experiences in the absence of a formalised benchmarking system for school libraries and contribute to a national picture of school library activity and priorities.

Feminization of medicine in France has come about in several stages, in connection with student and medical specialists recruitment. Its dynamics show that it can’t be considered as a virtually definitive gender reversal, but should rather be viewed as a dynamic recomposition closely related to societal changes and economic situations. I explain the way women succeeded in entering medicine via the concours, and how their situation has often given rise to wrongful interpretations concerning their ‘choices’. Finally, I reflect on the complex connections between feminization and the democratization of medical recruitment, on the one hand, and with the transformations within the liberal model in medicine, on the other. I conclude that the feminization of medicine questions a wide array of social relations in the domains of family, health, economics and politics, as a complex social fact.

This paper deals with the modelling of transformer supply in the two‐dimensional (2D) finite element (FE) simulation of rotating electrical machines. Three different transformer models are compared. The reference one is based on two 2D FE models, considering a cross‐section either parallel or perpendicular to the laminations of the magnetic core. The parameters of the two other transformer models, a magnetic equivalent circuit and an electrical equivalent circuit, can be derived from the reference model. Particular attention is paid to some common features of the transformer models, e.g. with regard to the inclusion of iron losses. The three models are used in the 2D FE simulation of the steady‐state load operation and the starting from stand‐still of an induction motor.

The purpose of this paper is to provide an outline of the major contributions in the literature on the determination of the least distance in data envelopment analysis (DEA). The focus herein is primarily on methodological developments. Specifically, attention is mainly paid to modeling aspects, computational features, the satisfaction of properties and duality. Finally, some promising avenues of future research on this topic are stated.

DEA is a methodology based on mathematical programming for the assessment of relative efficiency of a set of decision-making units (DMUs) that use several inputs to produce several outputs. DEA is classified in the literature as a non-parametric method because it does not assume a particular functional form for the underlying production function and presents, in this sense, some outstanding properties: the efficiency of firms may be evaluated independently on the market prices of the inputs used and outputs produced; it may be easily used with multiple inputs and outputs; a single score of efficiency for each assessed organization is obtained; this technique ranks organizations based on relative efficiency; and finally, it yields benchmarking information. DEA models provide both benchmarking information and efficiency scores for each of the evaluated units when it is applied to a dataset of observations and variables (inputs and outputs). Without a doubt, this benchmarking information gives DEA a distinct advantage over other efficiency methodologies, such as stochastic frontier analysis (SFA). Technical inefficiency is typically measured in DEA as the distance between the observed unit and a “benchmarking” target on the estimated piece-wise linear efficient frontier. The choice of this target is critical for assessing the potential performance of each DMU in the sample, as well as for providing information on how to increase its performance. However, traditional DEA models yield targets that are determined by the “furthest” efficient projection to the evaluated DMU. The projected point on the efficient frontier obtained as such may not be a representative projection for the judged unit, and consequently, some authors in the literature have suggested determining closest targets instead. The general argument behind this idea is that closer targets suggest directions of enhancement for the inputs and outputs of the inefficient units that may lead them to the efficiency with less effort. Indeed, authors like Aparicio et al. (2007) have shown, in an application on airlines, that it is possible to find substantial differences between the targets provided by applying the criterion used by the traditional DEA models, and those obtained when the criterion of closeness is utilized for determining projection points on the efficient frontier. The determination of closest targets is connected to the calculation of the least distance from the evaluated unit to the efficient frontier of the reference technology. In fact, the former is usually computed through solving mathematical programming models associated with minimizing some type of distance (e.g. Euclidean). In this particular respect, the main contribution in the literature is the paper by Briec (1998) on Hölder distance functions, where formally technical inefficiency to the “weakly” efficient frontier is defined through mathematical distances.

All the interesting features of the determination of closest targets from a benchmarking point of view have generated, in recent times, the increasing interest of researchers in the calculation of the least distance to evaluate technical inefficiency (Aparicio et al., 2014a). So, in this paper, we present a general classification of published contributions, mainly from a methodological perspective, and additionally, we indicate avenues for further research on this topic. The approaches that we cite in this paper differ in the way that the idea of similarity is made operative. Similarity is, in this sense, implemented as the closeness between the values of the inputs and/or outputs of the assessed units and those of the obtained projections on the frontier of the reference production possibility set. Similarity may be measured through multiple distances and efficiency measures. In turn, the aim is to globally minimize DEA model slacks to determine the closest efficient targets. However, as we will show later in the text, minimizing a mathematical distance in DEA is not an easy task, as it is equivalent to minimizing the distance to the complement of a polyhedral set, which is not a convex set. This complexity will justify the existence of different alternatives for solving these types of models.

As we are aware, this is the first survey in this topic.

As the complex influencing factors for financing decisions and limited information at the early project stage often render inappropriate financing mode and scheme (FMS) selection in the large-scale urban rail transit (URT) field, this study aims to identify the multiple influencing factors and establish a revised case-based reasoning (CBR) model by drawing on experience in historical URT projects to provide support for effective FMS decisions.

Our research proposes a two-phase, five-step CBR model for FMS decisions. We first establish a case database containing 116 large-scale URT projects and a multi-attribute FMS indicator system. Meanwhile, grey relational analysis (GRA), the entropy-revised G1 method and the time decay function have been employed to precisely revise the simple CBR model for selecting high-similarity cases. Then, the revised CBR model is verified by nine large-scale URT projects and a demonstration project to prove its decision accuracy and effectiveness.

We construct a similarity case indicator system of large-scale URT projects with 11 indicators across three attributes, in which local government fiscal pressure is considered the most influential indicator for FMS decision-making. Through the verification with typical URT projects, the accuracy of our revised CBR model can reach 89%. The identified high-similarity cases have been confirmed to be effective for recommending appropriate financing schemes matched with a specific financing mode.

This is the first study employing the CBR model, an artificial intelligence approach that simulates human cognition by learning from similar past experiences and cases to enhance the accuracy and reliability of FMS decisions. Based on the characteristics of the URT projects, we revise the CBR model in the case retrieval process to achieve a higher accuracy. The revised CBR model utilizes expert experience and historical information to provide a valuable auxiliary tool for guiding the relevant government departments in making systematic decisions at the early project stage with limited and ambiguous project information.

Physician stress and burnout is a serious and common concern in healthcare, with over half of physicians in the USA meeting at least one criterion for burnout. The paper aims to discuss these issues.

A review on current state of physician stress and burnout research, from 2008 to 2016, was undertaken. A subsequent perspective paper was shaped around these reviews.

Findings reveal research strength in prevalence and incidence with opportunities for stronger intervention studies. While descriptive studies on causes and consequences of physician burnout are available, studies on interventions and prevention of physician burnout are lacking. Future research on physician stress and burnout should incorporate intervention studies and take care to avoid limitations found in current research. Accountability and prevention of physician burnout is the responsibility of the healthcare industry as a whole, and organizational strategies must be emphasized in future research.

The value of this research comes in the original comprehensive review, international inclusion and succinct summary of physician burnout research and strategies.