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Pulse width modulated (PWM) inverters are widely used to feed induction motors for variable speed applications. The use of PWM power supplies induces additional magnetic losses in the magnetic circuit of the electrical machine. The aim of this paper is to present a novel analytical approach to account for these losses.

The methodology proposed here consists in identifying the analytical method with a static Preisach hysteresis model. The Preisach model was validated by comparing it with measurements obtained from an Epstein frame. Then, the results obtained with this approach were compared with a basic analytical method that is widely used.

The authors' model provides a fast way for estimating the minor loop iron losses introduced by static convertors. They compared the proposed model with another analytical model (J. Lavers model) for different wave forms. One can observe that the J. Lavers model overestimates the iron losses introduced by the non‐centred minor loops.

In this paper, an improved analytical model is presented which estimates the non‐centred minor loop iron losses. In order to do a precise estimation of the iron loss introduced by the minor loops, the authors' model takes into account the position and the size of the minor loop. The proposed model is identified from a static Preisach model.

Most source recording device identification models for Web media forensics are based on a single feature to complete the identification task and often have the disadvantages of long time and poor accuracy. The purpose of this paper is to propose a new method for end-to-end network source identification of multi-feature fusion devices.

This paper proposes an efficient multi-feature fusion source recording device identification method based on end-to-end and attention mechanism, so as to achieve efficient and convenient identification of recording devices of Web media forensics.

The authors conducted sufficient experiments to prove the effectiveness of the models that they have proposed. The experiments show that the end-to-end system is improved by 7.1% compared to the baseline i-vector system, compared to the authors’ previous system, the accuracy is improved by 0.4%, and the training time is reduced by 50%.

With the development of Web media forensics and internet technology, the use of Web media as evidence is increasing. Among them, it is particularly important to study the authenticity and accuracy of Web media audio.

This paper aims to promote the development of source recording device identification and provide effective technology for Web media forensics and judicial record evidence that need to apply device source identification technology.

Periodic inspection and maintenance are essential for effective pavement preservation. Cracks not only affect the appearance of the road and reduce the levelness, but also shorten the life of road. However, traditional road crack detection methods based on manual investigations and image processing are costly, inefficiency and unreliable. The research aims to replace the traditional road crack detection method and further improve the detection effect.

In this paper, a crack detection method based on matrix network fusing corner-based detection and segmentation network is proposed to effectively identify cracks. The method combines ResNet 152 with matrix network as the backbone network to achieve feature reuse of the crack. The crack region is identified by corners, and segmentation network is constructed to extract the crack. Finally, parameters such as the length and width of the cracks were calculated from the geometric characteristics of the cracks and the relative errors with the actual values were 4.23 and 6.98% respectively.

To improve the accuracy of crack detection, the model was optimized with the Adam algorithm and mixed with two publicly available datasets for model training and testing and compared with various methods. The results show that the detection performance of our method is better than many excellent algorithms, and the anti-interference ability is strong.

This paper proposed a new type of road crack detection method. The detection effect is better than a variety of detection algorithms and has strong anti-interference ability, which can completely replace traditional crack detection methods and meet engineering needs.

Commodity price volatility and small variations in climate conditions may have an important impact on the creditworthiness of any agricultural project. The evolution of such risk factors is vital for the credit risk analysis of a rural bank. The purpose of this paper is to determine the importance of price volatility and climate factors within a default risk model.

The authors estimate a generalized linear model (GLM) based on a structural default risk model. With the estimated factor loadings, the authors simulate the loss distribution of the portfolio and perform stress test to determine the impact of the relevant risk factors on economic capital.

The results indicate that both the price volatility and climate factors are statistically significant; however, their economic significance is smaller compare to other factors that the authors control for: macroeconomic conditions for the agricultural sector and intermediate input prices.

The analysis of non-systemic risk factors such as price volatility and climate conditions requires statistical methods focussed on measuring causal effects at higher quantiles, not just at the conditional mean, this is, however, a current limitation of GLMs.

The authors provide a design of a portfolio credit risk model, that is more suited to the special characteristics of a rural bank, than commercial credit risk models.

The paper incorporates agricultural-specific risk factors in a default risk model and a portfolio credit risk model.

This article aims to address an outstanding problem dealing with the structure of multi-story buildings subjected to differential settlement of the building's foundation.

Differential settlement between foundation units of multi-story structures has been responsible for causing damage to buildings and often catastrophic failure and loss of life. The dynamic changes in the loading conditions of the structure and the changes in the underlying ground due to environmental changes are causing this undesirable differential settlement, which is manifested in the form of additional stresses in beams, columns and distortion of the structure elements. This study presents the results of an experimental investigation on a prototype model of a multi-story building subjected to differential settlement of the building's foundation. The model is a four-floor aluminum structure, instrumented to measure the stresses induced in the structure elements due to the settlement of a center, edge and corner column, respectively, which represent the critical conditions of the structure.

The experimental results of this study can be used as a guideline for the design of structures.

The current study is the original research developed by the authors.

The purpose of this paper is to understand the main perceived impacts of overtourism in Portugal and the reactions of tourism stakeholders in the main Portuguese cities, especially the host.

This study uses a qualitative approach, based on the analysis of news published in Portuguese newspapers between March 2018 and March 2019, applying Bardin’s (2011) content analysis and matching with the theory as proposed by Laville and Dionne (1999).

The study reveals that the main perceived impacts are the evictions and transformation of old residence into short-term rentals (e.g. Airbnb) and small hotels, besides other impacts such as garbage in the streets, gentrification, loss of security and others.

The study considered the period of one year, being a limitation of analysis for contexts within that period, as well as the possible partiality of how the context of overtourism is dealt by newspapers.

This study seeks to understand the context of overtourism and its perception by the hosts and aims to present a basis of tourism planning for public and private sector stakeholders, in order to provide a better visit experience to the tourist, without losing the hosts’ quality of life.

Studies using newspapers as sources of data are rare. The newspapers are considered local witnesses; therefore, they bear important information for several purposes, not just for tourism but for other realities or contexts.

Robot automatic grasping has important application value in industrial applications. Recent works have explored on the performance of deep learning for robotic grasp detection. They usually use oriented anchor boxes (OABs) as detection prior and achieve better performance than previous works. However, the parameters of their loss belong to different coordinates, this may affect the regression accuracy. This paper aims to propose an oriented regression loss to solve the problem of inconsistency among the loss parameters.

In the oriented loss, the center coordinates errors between the ground truth grasp rectangle and the predicted grasp rectangle rotate to the vertical and horizontal of the OAB. And then the direction error is used as an orientation factor, combining with the errors of the rotated center coordinates, width and height of the predicted grasp rectangle.

The proposed oriented regression loss is evaluated on the YOLO-v3 framework to the grasp detection task. It yields state-of-the-art performance with an accuracy of 98.8% and a speed of 71 frames per second with GTX 1080Ti on Cornell datasets.

This paper proposes an oriented loss to improve the regression accuracy of deep learning for grasp detection. The authors apply the proposed deep grasp network to the visual servo intelligent crane. The experimental result indicates that the approach is accurate and robust enough for real-time grasping applications.

This paper covers a number of pitfalls that could hinder the development of a common methodology for estimating flood damage. Such pitfalls include double counting, ignoring post‐disaster liabilities, ignoring non‐market losses (e.g. recreation, loss of leisure, damage to historic sites and cultural assets, etc.), ignoring the needs of the end user, and questions as to how indirect/systemic losses might be modeled. With one exception, much of what is discussed in the paper is based on off‐the‐shelf economics and will not prove to be contentious. Regional economists are likely to have different opinions as to how to best model indirect and systemic loss; it is this that will lead to a lively debate as to how to proceed. Assessments of economic fallout from the World Trade Center attack are used to illustrate some of the problems reported in this paper.

An estimate is made of the effect of adding a small forward fin on the lift and centre of pressure of a slender wing‐body combination. The fin is assumed to discharge a trailing vortex which interacts with the main lifting surface. Design charts permit rapid estimation of lift loss and centre of pressure movement for a delta wing plus body. At the lower angles of attack, the lift loss on the wing is approximately equal to the lift of the forward surface itself. Most of the lift is lost at the front of the wing, and so wing centre of pressure moves aft with addition of the forward fin. Theoretical estimates are in general agreement with experimental results at Mach numbers 1·65 and 2·41.

The purpose of this study is to shed greater light on the factors that influence consumer compliance behavior, e.g. SRF, in compliance dependent services (CDS). CDS, e.g. weight loss, retirement savings, education, credit repair, are long term in nature, often requiring lifestyle changes. In addition, and importantly, the customer's role in CDS extends beyond the face‐to‐face interaction and requires the consumer to comply with prescribed behaviors when away from the service provider.

The subjects were 243 female clients (aged 20 to 45) at a weight loss/fitness center located in south India. Subjects were selected from among the new clients who signed up for an eight‐week long weight loss and fitness program which seeks to help clients lose modest amounts of excess weight (averaging approximately ten pounds). On signing up, respondents completed a survey that included several scales of regulatory focus, and a question eliciting reasons for wanting to lose weight.

This study exams the role of self‐regulatory focus (SRF) in long‐term customer compliance behavior in weight loss. A specific measure of SRF led to better outcomes than the generalized measures of SRF.

Though this research project examines consumer behavior in the context of weight loss activities, it has far‐ranging implications for various services requiring consumers to engage in prescribed behaviors over the long run. For example, the success of debt counseling services and retirement savings programs require clients to engage in certain behaviors over the long run. Marketers of CDS programs will be able to use the findings of this research project to find new ways to increase long‐term customer compliance behavior.