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The implementation of a vector Preisach model for the modelling of anisotropic hysteretic soft magnetic materials is outlined. Some comparisons with measurements on alternate and rotational magnetic field excitations are shown. The hysteresis model is inserted inside a two‐dimensional finite element solver formulated in terms of magnetic vector potential and nonlinear solution is handled by means of the fixed point method with H‐scheme. Results obtained on a two‐dimensional geometry are described and discussed.

Rapid advancements in computer technologies over the past decade have recorded significant growth in the area of computational micromagnetics. As a result, current micromagnetic codes exploit the scalability offered by parallel and distributed computer architectures to deliver maximum performance. The purpose of this paper is to present a review, which explores various aspects of this relationship.

The authors arrange the theme for this paper around the micromagnetic code development process. The review involves a discussion of the micromagnetic model, some new parallel architectures, and computational aspects based on different numerical methods.

As current micromagnetic code is not readily portable to different architectures, most of the development effort goes towards this area, with a focus on writing/rewriting code for streaming hardware (particularly graphic cards).

The paper identifies key challenges and avenues for further research on computational aspects of micromagnetic modelling and suggests recommendations based on the review.

This article reviews the literature on the econometric relationship between DSGE and VAR models from the point of view of estimation and model validation. The mapping between DSGE and VAR models is broken down into three stages: (1) from DSGE to state-space model; (2) from state-space model to VAR( ∞ ); (3) from VAR( ∞ ) to finite-order VAR. The focus is on discussing what can go wrong at each step of this mapping and on critically highlighting the hidden assumptions. I also point out some open research questions and interesting new research directions in the literature on the econometrics of DSGE models. These include, in no particular order: understanding the effects of log-linearization on estimation and identification; dealing with multiplicity of equilibria; estimating nonlinear DSGE models; incorporating into DSGE models information from atheoretical models and from survey data; adopting flexible modeling approaches that combine the theoretical rigor of DSGE models and the econometric model’s ability to fit the data.

Considered from an international and comparative perspective Italian anti‐money laundering legislation appears rigorous and comprehensive. It includes general norms and aggravating circumstances for conspiracy to engage in organised and economic crime; rules which oblige the financial sector to identify and report currency transactions in excess of 20 million lire (approximately £6,600; and hereinafter called ‘large currency transactions’); provisions punishing money laundering as a crime; norms which sanction the failure to report suspicious transactions by financial intermediaries; provisions prohibiting ‘tipping‐off’ and rules which provide for the confiscation and freezing of the proceeds of crime, which shift the burden of proof in cases where the accused fails to demonstrate the origin of the suspicious assets. The legislative structure provides, likewise, norms on ‘sting operations’, establishing an express immunity clause for ‘undercover agents’. Lastly, the legislation further defines the parameters of international judicial assistance.

Various iron loss models can be used for the simulation of electrical machines. In particular, the effect of rotating magnetic flux density at certain geometric locations in a machine is often neglected by conventional iron loss models. The purpose of this paper is to compare the adapted IEM loss model for rotational magnetization that is developed within the context of this work with other existing models in the framework of a finite element simulation of an exemplary induction machine.

In this paper, an adapted IEM loss model for rotational magnetization, developed within the context of the paper, is implemented in a finite element method simulation and used to calculate the iron losses of an exemplary induction machine. The resulting iron losses are compared with the iron losses simulated using three other already existing iron loss models that do not consider the effects of rotational flux densities. The used iron loss models are the modified Bertotti model, the IEM-5 parameter model and a dynamic core loss model. For the analysis, different operating points and different locations within the machine are examined, leading to the analysis of different shapes and amplitudes of the flux density curves.

The modified Bertotti model, the IEM-5 parameter model and the dynamic core loss model underestimate the hysteresis and excess losses in locations of rotational magnetizations and low-flux densities, while they overestimate the losses for rotational magnetization and high-flux densities. The error is reduced by the adapted IEM loss model for rotational magnetization. Furthermore, it is shown that the dynamic core loss model results in significant higher hysteresis losses for magnetizations with a high amount of harmonics.

The simulation results show that the adapted IEM loss model for rotational magnetization provides very similar results to existing iron loss models in the case of unidirectional magnetization. Furthermore, it is able to reproduce the effects of rotational flux densities on iron losses within a machine simulation.

Buildings alone do not matter, it is only the ensemble of streets, squares, and buildings and the way they fit together that comprises the true principles of good urbanism and place making. One of the main rules of good urban design is the quality of the public space. This paper analyzes the importance of creating & maintaining a true public square in contemporary urban condition, as one of the built environments' pillars for sustaining social and cultural identity.

Criticism has been posed towards the (neo) romanticizing the importance of European squares (as some critics would call it “Postcard Squares”) in everyday life and contemporary town planning. Movements such as New Urbanism, which promote good urban design have not put squares that high on their urban design agendas. Also the usage of the historic European city's public realm model - the square - as the important ingredient for all urban places has not been forthcoming. To investigate this phenomena, and facilitate the discourse, The Square of the St. Blaise Church (Luza Square) and the Gunduliceva Poljana Square in the Old City of Dubrovnik, are analyzed and reflected upon through various data collection, theory reflections and urban design evaluation methods, such as Garham's Sense of Place Typology-Taxonomy.

If cities have livable and vibrant social spaces, do residents tend to have a stronger sense of community and sense of place? If such places are lacking, does the opposite happen?. This paper seeks out to answer these questions. Finally the paper also looks at how the phenomenon of creating good social spaces through creating ‘third places’ is achieved and confirmed in the squares of Dubrovnik.

Stochastic uncertainties in material parameters have a significant impact on the analysis of real-world electromagnetic compatibility (EMC) problems. Conventional approaches via the Monte-Carlo scheme attempt to provide viable solutions, yet at the expense of prohibitively elongated simulations and system overhead, due to the large amount of statistical implementations. The purpose of this paper is to introduce a 3-D stochastic finite-difference time-domain (S-FDTD) technique for the accurate modelling of generalised EMC applications with highly random media properties, while concurrently offering fast and economical single-run realisations.

The proposed method establishes the concept of covariant/contravariant metrics for robust tessellations of arbitrarily curved structures and derives the mean value and standard deviation of the generated fields in a single-run. Also, the critical case of geometrical and physical uncertainties is handled via an optimal parameterisation, which locally reforms the curvilinear grid. In order to pursue extra speed efficiency, code implementation is conducted through contemporary graphics processor units and parallel programming.

The curvilinear S-FDTD algorithm is proven very precise and stable, compared to existing multiple-realisation approaches, in the analysis of statistically-varying problems. Moreover, its generalised formulation allows the effective treatment of realistic structures with arbitrarily curved geometries, unlike staircase schemes. Finally, the GPU-based enhancements accomplish notably accelerated simulations that may exceed the level of 120 times. Conclusively, the featured technique can successfully attain highly accurate results with very limited system requirements.

Development of a generalised curvilinear S-FDTD methodology, based on a covariant/contravariant algorithm. Incorporation of the important geometric/physical uncertainties through a locally adaptive curved mesh. Speed advancement via modern GPU and CUDA programming which leads to reliable estimations, even for abrupt statistical media parameter fluctuations.

This study aims to propose and test an innovative methodology for assessing mortgage lending value. The method tries to improve and rationalize, within the canonical and derivative approach that is generally used by the sector operators, the appraisal of the percentage reduction to be applied to the market value.

Considering that the European Mortgage Federation and the Basel Committee highlight the importance of information about the risks of properties to be loaned on, the value at risk approach has been developed so as to assess the mortgage lending value as a technique of risk analysis. With reference to the Italian context, the method elaborates the historical analysis of the property values in 93 major Italian cities for the residential and commercial intended uses in a significant period (1967-2015) and allows to determine the reduction coefficients of the market value as a function of the central, semi-central and peripheral locations of the property.

The results include the reduction coefficients of the market value for the derivative appraisal of the mortgage lending value. The coefficients obtained satisfy the need for a rational assessment of the property risk and the appropriate spatial contextualization of the risk components related to the local demand and supply, thus eliminating any inconsistency and danger of determining the mortgage lending value using a simple and lump-sum percentage deduction of the market value.

The global economic crisis in the past decade, triggered by the 2007 US Subprime mortgage crisis and consequent collapse of property values, has highlighted the need for high level professional skills in the appraisal of properties as securities for credit exposures. The method proposed for the assessment of the mortgage lending value allows to overcome the uncertainties underlying the determination of an independent value through indirect methods (income approach, cost approach) and rationalize the appraisal of the risk in the traditional derivative approach through a flexible procedure, with it being possible to adapt it to any territorial context, as well as any intended use.

In a volatile agricultural postharvest market, producers require more personalized information about market dynamics for informed decisions on the marketed surplus. However, this adaptive strategy fails to benefit them if the selection of a computational price predictive model to disseminate information on the market outlook is not efficient, and the associated risk of perishability, and storage cost factor are not assumed against the seemingly favourable market behaviour. Consequently, the decision of whether to store or sell at the time of crop harvest is a perennial dilemma to solve. With the intent of addressing this challenge for agricultural producers, the study is focused on designing an agricultural decision support system (ADSS) to suggest a favourable marketing strategy to crop producers.

The present study is guided by an eclectic theoretical perspective from supply chain literature that included agency theory, transaction cost theory, organizational information processing theory and opportunity cost theory in revenue risk management. The paper models a structured iterative algorithmic framework that leverages the forecasting capacity of different time series and machine learning models, considering the effect of influencing factors on agricultural price movement for better forecasting predictability against market variability or dynamics. It also attempts to formulate an integrated risk management framework for effective sales planning decisions that factors in the associated costs of storage, rental and physical loss until the surplus is held for expected returns.

Empirical demonstration of the model was simulated on the dynamic markets of tomatoes, onions and potatoes in a north Indian region. The study results endorse that farmer-centric post-harvest information intelligence assists crop producers in the strategic sales planning of their produce, and also vigorously promotes that the effectiveness of decision making is contingent upon the selection of the best predictive model for every future market event.

As a policy implication, the proposed ADSS addresses the pressing need for a robust marketing support system for the socio-economic welfare of farming communities grappling with distress sales, and low remunerative returns.

Based on the extant literature studied, there is no such study that pays personalized attention to agricultural producers, enabling them to make a profitable sales decision against the volatile post-harvest market scenario. The present research is an attempt to fill that gap with the scope of addressing crop producer's ubiquitous dilemma of whether to sell or store at the time of harvesting. Besides, an eclectic and iterative style of predictive modelling has also a limited implication in the agricultural supply chain based on the literature; however, it is found to be a more efficient practice to function in a dynamic market outlook.

The purpose of this paper is to explore the role of tabletop exercises (TTXs) in graduate nuclear security education, their effectiveness and their relationship to traditional forms of classroom instruction. The paper highlights both the benefits and challenges of TTX implementation—the former including higher student motivation and material retention, and the latter including motivational shifts toward “winning” and possible student exclusionary behavior.

Survey results from 49 former students in a US university were collected electronically and combined with anecdotal evidence from student, facilitator and teaching assistant interviews following five iterations of a specifically designed, semester-long, TTX case study. The case study focused on securing a fictional nuclear facility.

Students found the TTX more memorable and retained more course material when asked to compare the TTX’s effectiveness to long-term course projects in other courses. Their in-class motivations tended to shift from traditional classroom motivations toward “winning,” and “not letting down their classmates.” In some iterations, students also observed classmates becoming more tempted to cheat or otherwise violate academic ethics. Mitigation strategies to prevent such temptations (e.g. removing direct student vs student TTX structures) were found to be effective.

This is the first report on the effective use of a semester-long TTX in a graduate nuclear security classroom. The flexibility of this instructional tool demonstrates its applicability to other classroom subjects including homeland security, emergency management, disease outbreak management and public policy among others.