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Aims to introduce a self‐adjusting robotic painting process for automotive fuel containers, capable of predicting the required correction action to avoid further defect production.

Presents the development, testing and on‐site implementation of a robotic thermal machine vision system designed for evaluating coat thickness and coverage attributes. Computer simulation is used to study the effect of the painting robot's program on the film build‐up.

Effective technique for the real‐time detection of anti‐corrosive coat's pinholes and pop‐ups. A systematic study for this paint deposition scheme.

The presented detection system and the simulation program methodology could be further studied and modified for other painting applications.

Provides insights validated with on‐site results and systematic study for the automated or the manual adjustments of the robotic painting parameters.

Introduces a novel application of thermal imaging for evaluating coated surfaces. In addition, a first reported case study of automotive fuel container's painting process. Presents potential application to reduce the defects generation thus, improving quality, and reducing production cost.

While Big Data offer marketing managers information that is high in volume, variety, velocity, and veracity (the 4Vs), these features wouldn’t necessarily improve their decision-making. Managers would still be vulnerable to confirmation bias, control illusions, communication problems, and confidence issues (the 4Cs). The authors argue that traditional remedies for such biases don’t go far enough and propose a lean start-up approach to data-based learning in marketing management. Specifically, they focus on the marketing analytics component of Big Data and how adaptations of the lean start-up methodology can be used in some combination with such analytics to help marketing managers improve their decision-making and innovation process. Beyond the often discussed technical obstacles and operational costs associated with handling Big Data, this chapter contributes by analyzing the various learning and decision-making problems that can emerge once the 4Vs of Big Data have materialized.

This study aims to review the recent advancements in high entropy alloys (HEAs) called high entropy materials, including high entropy superalloys which are current potential alternatives to nickel superalloys for gas turbine applications. Understandings of the laser surface modification techniques of the HEA are discussed whilst future recommendations and remedies to manufacturing challenges via laser are outlined.

Materials used for high-pressure gas turbine engine applications must be able to withstand severe environmentally induced degradation, mechanical, thermal loads and general extreme conditions caused by hot corrosive gases, high-temperature oxidation and stress. Over the years, Nickel-based superalloys with elevated temperature rupture and creep resistance, excellent lifetime expectancy and solution strengthening L12 and γ´ precipitate used for turbine engine applications. However, the superalloy’s density, low creep strength, poor thermal conductivity, difficulty in machining and low fatigue resistance demands the innovation of new advanced materials.

HEAs is one of the most frequently investigated advanced materials, attributed to their configurational complexity and properties reported to exceed conventional materials. Thus, owing to their characteristic feature of the high entropy effect, several other materials have emerged to become potential solutions for several functional and structural applications in the aerospace industry. In a previous study, research contributions show that defects are associated with conventional manufacturing processes of HEAs; therefore, this study investigates new advances in the laser-based manufacturing and surface modification techniques of HEA.

The AlxCoCrCuFeNi HEA system, particularly the Al0.5CoCrCuFeNi HEA has been extensively studied, attributed to its mechanical and physical properties exceeding that of pure metals for aerospace turbine engine applications and the advances in the fabrication and surface modification processes of the alloy was outlined to show the latest developments focusing only on laser-based manufacturing processing due to its many advantages.

It is evident that high entropy materials are a potential innovative alternative to conventional superalloys for turbine engine applications via laser additive manufacturing.

The Ba River catchment and delta on the island of Viti Levu, Fiji, supports a wealth of livelihoods and is populated by diverse communities who are living with an increased frequency and intensity of hydro-meteorological hazards (floods, cyclones and droughts). Participatory mapping as part of focus group discussions is a tool that can be used to elucidate communities’ understanding of the differing impacts of multiple hazards, as well as the strategies used to prepare and respond to different hazards. In this chapter, the authors present the results of qualitative research undertaken with members of three communities along the Ba River, from the Nausori highlands to the coastal mangroves, with a particular focus on recent floods (2009, 2012) and Tropical Cyclone Winston (2016). The communities draw on a wide range of livelihood strategies from fishing and agriculture to tourism and outside work. Natural hazard events vary in their impact on these livelihood strategies across the landscape and seascape, so that community members can adjust their activities accordingly. The temporal ‘signatures’ of ongoing impacts are also variable across communities and resources. The results suggest that taking a broad, landscape (and seascape) approach to understanding how communities draw livelihoods is valuable in informing effective and inclusive adaptation strategies for environmental change. Furthermore, documenting how the landscape is used in a mapped output may be a valuable tool for future social impact assessment for resource extraction activities.

Examines Attilio da Empoli’s contributions in the field of public finance. This scholar was endowed with particular scientific qualities which allowed him to give original contributions to the theory of public finance, in particular in the field of oblique and backward tax shifting. The other main topics of da Empoli’s critical reflection concern tax shifting in relation to cost conditions, the shifting of a general income tax and the methodological aspects of the joint analysis of the tax and expenditure sides.

The term “causes” of disasters is used interchangeably very often with other terms, such as “types” of disasters. Also, causes of disasters are usually explained in the literature in an individualistic fashion relating every single disaster with its own causes only. This limits the ability to identify the real causes of disasters. Second, it reduces the ability to create any kind of grouping for the causes of disasters. The purpose of this paper is to identify and discuss causes of disasters in a more categorical manner.

An extensive review of the existing literature has been made in order to identify, introduce and discuss theories related to the causes of disasters. Overall, the approach taken is based on theoretical reasoning informed by the literature.

Disasters, even those which seem to be composite and complex, are not mysterious incidents that cannot be explained or analyzed. Literally, almost all disasters can be diagnosed and the causes of disasters can be identified in a systematic and reasonable manner.

This study provides a better conceptualization and understanding of the causes of disasters. It is believed that this study will improve the decision-making process accompanied with the disaster risk reduction processes by understanding the exact causes of disasters. The study also clarifies the differences between the causes, sources and types of disasters which is extremely significant in disaster lifecycle modeling.

To the author’s knowledge, very few attempts have been made in the literature to capture causes of disasters in a categorical and systematic manner. Almost all disaster occurrences have been discussed in the literature in an individualistic fashion relating every single disaster with its own causes only.

This paper aims to present a new approach to implement a pedestrian tracking algorithm for a passive automotive night vision application.

First, the basic information of passive and active night vision systems is presented, with implementation methods adopted in previous work. The proposed thermal‐image processing is a combination of seed detection, boundary detection and seed growth computations, based on a temperature thresholding scheme.

The processing routine performance is assessed when implemented to a continuous sequence of thermal acquisitions, from a commercial automotive night vision module. Experimental results show good tracking performance for both pedestrians and passing vehicles.

A strategy of multi‐seed growth, directional seed growth and image fusion is proposed to improve the current tracking algorithm.

New thermal image processing routines are applied to commercial, automotive night vision modules, to provide robust pedestrian tracking at real‐time processing speed.

The paper is aimed at assessing the safety of the Giotto's Bell Tower, with special attention to its foundation system, i.e. the foundation works and soil. The tower, well known all over the world, has a squared plan, with sides of 14.45 m each, and a total height equal to 84.7 m. The structural response of the tower is assessed with reference to the gravitational load and to the expected seismic action, quantified according to the seismic hazard of the site and the foundation soil.

A simplified analysis has been performed to check the safety level of the tower to seismic actions. Special attention has been paid to quantify the horizontal actions representing the seismic loads. Such quantification, indeed, has been made both through the elastic spectrum of the tower and by performing a site response analysis on the foundation soil, represented as a one-dimensional stratification of soil layers, described on the basis of experimental investigations. After defining the loading actions, a simplified assessment of the foundation safety has been made by considering the action over foundation, the geotechnical data and the safety factor.

The findings of the paper concern the assessment of the safety of the tower's foundation system. A lot of experimental data on the foundation soil, provided by various geological investigations, have been provided and used for the assessment. Moreover, the mechanical properties of the materials used for the structure have been collected and shown in the paper.

The paper collects a lot of technical information regarding the Giotto's Bell Tower, both regarding its foundation soil and the constituting materials. On the basis of the collected information, a structural analysis has been made to assess the seismic safety of the tower, and the results of such assessment are provided and discussed.

In a previous monograph a discussion took place on stages one and part of stage two of the three stage process in an unfair dismissal action, namely the employee having to show that he has been dismissed (stage one), and some of the reasons for dismissal which fall within the statutory categories, namely the employee's capability and qualifications; misconduct and redundancy (part of stage two). In this monograph an analysis is proposed on the two remaining reasons, these being the contravention of a duty imposed by an enactment and some other substantial reason. There will then follow a discussion on the test of fairness as constituting the third of the three stage process and on the remedies available when the tribunal finds that the employee has been unfairly dismissed.

This chapter explores Prospect Theory — a descriptive model of modelling individual choice making under risk and uncertainty, and its applications to a range of travel behaviour contexts.

The chapter provides background on Prospect Theory, its basic assumptions and formulations, and summarises some of its theoretical developments, applications and evidence in the field of transport research.

A body of empirical evidence has accumulated showing that the principle of maximisation of expected utility provides limited explanation of travel choices under risk and uncertainty. Prospect Theory can be seen as an alternative and promising framework for travel choice modelling (although not without theoretical and practical controversy). These findings are supported by empirical observations reported in the literature reviewed in this chapter.

The chapter provides a detailed account of the design and results of accumulated research in travel behaviour research that is based on Prospect Theory’s observations, insights and formulations. The potential of Prospect Theory for particular decision-making in travel behaviour research is articulated, main findings are presented and discussed, and limitations are identified, leading to further research needs.