Search results

The purpose of this paper is to propose the optimal allocation and alignment of probes for current distribution measurement (CDM) in the case of twin cable in conduit conductor (CICC) cables with equal and opposite current.

The most effective approach to CDM in CICC cables is to perform indirect measurements starting from magnetic field map measured externally to the cable. A number of approaches have been proposed to optimize the layout of magnetic field probes external to the cable, but all dealing with single cables. In this paper, an approach to the optimized design of measurement system for twin cables will be proposed, based on the minimization of a suitable cost function.

A method for the optimal allocation of probes both in terms of rejection of the background field and of condition number of the Green matrix has been defined.

The method is valid only in the hypothesis of linear relationship between currents and magnetic field.

The proposed approach allows to design more robust CDM systems, with increased noise and background field rejection capability.

The problem of optimal design of CDM systems has been previously tackled in literature, but typically with reference to single cables. In the paper, an approach able to explicitly deal with twin cables is proposed.

The purpose of this paper is to propose a planning strategy for the radio frequency ablation (RFA) treatment of hepatic tumors. The goal is to give to the surgeon the opportunity of controlling the shape and the size of the treated volume and preserving the healthy tissues.

A FEM model of the human torso is built from radiographic and MRI scans of the patients, and then the RFA treatment “dynamically optimized” by controlling currents in multiple external electrodes, in such a way to drive currents in the desired regions, burning the tumor while trying to preserve healthy regions. A suitable cellular death model is considered in order to achieve an effective description of the biological modifications in the tumor volume.

A numerical method to plan the RFA treatment of hepatic tumors has been defined, aiming to preserve as much as possible healthy tissues.

The method depends on the knowledge of inner structure and properties of the patient's torso; while the structure of tissues can be determined by TAC or MRI scans, the physiological properties are much more uncertain.

The proposed approach allows optimized RFA treatments to be designed, allowing reduction of damage to healthy tissues deriving from application of the treatment.

The problem of optimal design of RFA treatments has been previously tackled in literature, but in this paper, dynamical optimization techniques and a cell death rate model have been included.

The purpose of this paper is to evaluate the performances of a resolution scheme able to follow the dynamics of brain tissue properties in combined ElectroEncefaloGraphic (EEG) – MagnetoEncefaloGraphic (MEG) techniques for the brain analysis, minimizing the computation burden.

The estimation process in combined EEG‐MEG is performed by a Moore‐Penrose pseudo‐inverse computation. This is affected by the uncertain knowledge of the living tissues' electric properties. In principle, it is possible to estimate those properties from the EEG‐MEG signals. The estimation process becomes in this case non‐linear. A resolution scheme is proposed, based on the exploitation of the different dynamics characterizing sources and tissues properties.

The proposed resolution scheme provides a reasonable estimate of the sources for a computationally affordable frequency of non‐liner estimations.

The proposed approach has not been tested yet on experimental data, and as such, its sensitivity to environmental uncertainty is not known yet.

The proposed strategy can be easily implemented to perform realistic measurement processing.

The paper presents a novel strategy to estimate tissues properties and EEG‐MEG signal sources based on the exploitation of their different dynamics, possibly taking advantages from an impedance tomography preliminary analysis for the tissue properties dynamics.

The purpose of the paper is to clarify the influence of introducing magnetic concentrators on the performance of Hall effect based current sensors and to obtain dependencies of the sensor characteristics on the conductor position.

The finite element method and Comsol software are used for analysis of the three-dimensional magnetic field of the constructions of Hall effect based current sensor with different types of magnetic concentrators – closed-core (of rectangular and toroidal type) and open-core of toroidal type – with additional larger air gap. The Hall plate is also included in the model with its real dimensions and the magnetic flux density is obtained by integrating over its volume.

It has been found that there is dependence of the output signal (proportional to the magnetic flux density) of Hall effect based current sensor with both closed- and open-core magnetic concentrators on the position of the current carrying conductor. Distribution of the magnetic flux density and dependencies of its value in the Hall plate on the conductor position and on the additional air gap have been obtained. Optimization is carried out with respect to the additional air gap and cross-section dimensions of the concentrator.

Estimation of the influence of the introducing magnetic concentrators is made with respect to relationships between the output signal and conductor position for different constructions of the magnetic core of the concentrators.

In this chapter, the emerging education workforce management approach known as talent-centered education leadership (TCEL) is reviewed. The approach takes inspiration from progressive and cutting-edge talent management thinking and practices that emphasizes employers' intentional focus on humanizing and authentically engaging with their workforce. Pertinent to the theme of the book, the discussion then segues to the importance of diversity and inclusion as a precursor for these efforts and demonstrates how equity and organizational excellence are mutually compatible in the workplace. Relatedly, consideration is given to how traditional perceptions of “professionalism” can exacerbate inequity in the workplace. The chapter concludes by highlighting the seven core principles of TCEL to prepare school employers to embrace the future of education work.

According to the press at the turn of the year 1999—2000, a good corporate reputation for responsible marketing is a key element in business success. One justification for this is the assumption that consumers are interested in how companies behave and this has an influence upon their consumption behaviour. There is also the suggestion that a financial pay‐off is to be gained from good behaviour. Conflicting reports in previous research cast doubt upon the reliability of these assumptions, and there are few studies which unequivocally support positive consumer purchasing in return for responsible marketing. This paper reviews current opinion and evidence in relation to the growing interest in corporate reputation, and reports findings from focus group research which casts doubt upon the efficacy of corporate reputation in influencing positive consumer purchase behaviour.

This chapter will introduce the concept of the gig economy. It begins with a brief discussion of technological changes and their impact on the workforce and labour market, demonstrating how the trend shifts towards the gig economy. It then examines the trends that are influencing this transformation and discusses various perspectives and the attractiveness of the gig economy for workers and businesses. This chapter will also discuss the gig economy, platform economy, digital platform, and gig worker categories. It concludes with a brief discussion of some of the opportunities, issues, and challenges associated with the gig economy.

Increased emphasis on offering quality education underscores the need for developing a rigorous process for assessing academic programs in higher education. In this chapter, we develop a practical and rigorous framework for comprehensive assessment of academic programs. This framework generates in-depth communication between the academic departments and the university administration. It provides a useful tool for advancing the university mission, setting priorities, allocating resources, and identifying future areas of potential growth. This data-driven framework covers a wide range of qualitative and quantitative variables. To ensure a smooth and efficient implementation of the assessment process we present the critical stages in the development of a successful program assessment framework − from determining the assessment criteria, establishing the organizational climate, appointing the assessment committee, preparing program self-studies, to collecting and analyzing data. We present real examples from the author’s home institution to illustrate and support the reader’s understanding of the framework.

The commercial property market is complex, but the literature suggests that simple models can forecast it. To confirm the claim, the purpose of this paper is to assess a set of models to forecast UK commercial property market.

The employs five modelling techniques, including Autoregressive Integrated Moving Average (ARIMA), ARIMA with a vector of an explanatory variable(s) (ARIMAX), Simple Regression (SR), Multiple Regression, and Vector Autoregression (VAR) to model IPD UK All Property Rents Index. The Bank Rate, Construction Orders, Employment, Expenditure, FTSE AS Index, Gross Domestic Product (GDP), and Inflation are all explanatory variables selected for the research.

The modelling results confirm that increased model complexity does not necessarily yield greater forecasting accuracy. The analysis shows that although the more complex VAR specification is amongst the best fitting models, its accuracy in producing out-of-sample forecasts is poorer than of some less complex specifications. The average Theil’s U-value for VAR model is around 0.65, which is higher than that of less complex SR with Expenditure (0.176) or ARIMAX (3,0,3) with GDP (0.31) as an explanatory variable models.

The paper calls analysts to make forecasts more user-friendly, which are easy to use or understand, and for researchers to pay greater attention to the development and improvement of simpler forecasting techniques or simplification of more complex structures.

The paper addresses the issue of complexity in modelling commercial property market. It advocates for simplicity in modelling and forecasting.