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Terrestrial laser scanning (TLS) point clouds have been widely used in deformation measurement for structures. However, reliability and accuracy of resulting deformation estimation strongly depends on quality of each step of a workflow, which are not fully addressed. This study aims to give insight error of these steps, and results of the study would be guidelines for a practical community to either develop a new workflow or refine an existing one of deformation estimation based on TLS point clouds. Thus, the main contributions of the paper are investigating point cloud registration error affecting resulting deformation estimation, identifying an appropriate segmentation method used to extract data points of a deformed surface, investigating a methodology to determine an un-deformed or a reference surface for estimating deformation, and proposing a methodology to minimize the impact of outlier, noisy data and/or mixed pixels on deformation estimation.

In practice, the quality of data point clouds and of surface extraction strongly impacts on resulting deformation estimation based on laser scanning point clouds, which can cause an incorrect decision on the state of the structure if uncertainty is available. In an effort to have more comprehensive insight into those impacts, this study addresses four issues: data errors due to data registration from multiple scanning stations (Issue 1), methods used to extract point clouds of structure surfaces (Issue 2), selection of the reference surface S_ref to measure deformation (Issue 3), and available outlier and/or mixed pixels (Issue 4). This investigation demonstrates through estimating deformation of the bridge abutment, building and an oil storage tank.

The study shows that both random sample consensus (RANSAC) and region growing–based methods [a cell-based/voxel-based region growing (CRG/VRG)] can be extracted data points of surfaces, but RANSAC is only applicable for a primary primitive surface (e.g. a plane in this study) subjected to a small deformation (case study 2 and 3) and cannot eliminate mixed pixels. On another hand, CRG and VRG impose a suitable method applied for deformed, free-form surfaces. In addition, in practice, a reference surface of a structure is mostly not available. The use of a fitting plane based on a point cloud of a current surface would cause unrealistic and inaccurate deformation because outlier data points and data points of damaged areas affect an accuracy of the fitting plane. This study would recommend the use of a reference surface determined based on a design concept/specification. A smoothing method with a spatial interval can be effectively minimize, negative impact of outlier, noisy data and/or mixed pixels on deformation estimation.

Due to difficulty in logistics, an independent measurement cannot be established to assess the deformation accuracy based on TLS data point cloud in the case studies of this research. However, common laser scanners using the time-of-flight or phase-shift principle provide point clouds with accuracy in the order of 1–6 mm, while the point clouds of triangulation scanners have sub-millimetre accuracy.

This study aims to give insight error of these steps, and the results of the study would be guidelines for a practical community to either develop a new workflow or refine an existing one of deformation estimation based on TLS point clouds.

The results of this study would provide guidelines for a practical community to either develop a new workflow or refine an existing one of deformation estimation based on TLS point clouds. A low-cost method can be applied for deformation analysis of the structure.

Although a large amount of the studies used laser scanning to measure structure deformation in the last two decades, the methods mainly applied were to measure change between two states (or epochs) of the structure surface and focused on quantifying deformation-based TLS point clouds. Those studies proved that a laser scanner could be an alternative unit to acquire spatial information for deformation monitoring. However, there are still challenges in establishing an appropriate procedure to collect a high quality of point clouds and develop methods to interpret the point clouds to obtain reliable and accurate deformation, when uncertainty, including data quality and reference information, is available. Therefore, this study demonstrates the impact of data quality in a term of point cloud registration error, selected methods for extracting point clouds of surfaces, identifying reference information, and available outlier, noisy data and/or mixed pixels on deformation estimation.

The purpose of this review is to comprehensively consider the material properties and processing of additive titanium alloy and provide a new perspective for the robotic grinding and polishing of additive titanium alloy blades to ensure the surface integrity and machining accuracy of the blades.

At present, robot grinding and polishing are mainstream processing methods in blade automatic processing. This review systematically summarizes the processing characteristics and processing methods of additive manufacturing (AM) titanium alloy blades. On the one hand, the unique manufacturing process and thermal effect of AM have created the unique processing characteristics of additive titanium alloy blades. On the other hand, the robot grinding and polishing process needs to incorporate the material removal model into the traditional processing flow according to the processing characteristics of the additive titanium alloy.

Robot belt grinding can solve the processing problem of additive titanium alloy blades. The complex surface of the blade generates a robot grinding trajectory through trajectory planning. The trajectory planning of the robot profoundly affects the machining accuracy and surface quality of the blade. Subsequent research is needed to solve the problems of high machining accuracy of blade profiles, complex surface material removal models and uneven distribution of blade machining allowance. In the process parameters of the robot, the grinding parameters, trajectory planning and error compensation affect the surface quality of the blade through the material removal method, grinding force and grinding temperature. The machining accuracy of the blade surface is affected by robot vibration and stiffness.

This review systematically summarizes the processing characteristics and processing methods of aviation titanium alloy blades manufactured by AM. Combined with the material properties of additive titanium alloy, it provides a new idea for robot grinding and polishing of aviation titanium alloy blades manufactured by AM.

The purpose of this paper is to establish a chair-side design and production method for a tooth-supported fixed implant guide and to evaluate its accuracy.

Three-dimensional (3D) data of the alveolar ridge, adjacent teeth and antagonistic teeth were acquired from models of the edentulous area of 30 patients. The implant guides were then constructed using self-developed computer-aided design software and chair-side fused deposition modelling 3D-printing and positioned on a dental model. A model scanner was used to acquire 3D data of the positioned implant guides, and the overall error was then evaluated.

The overall error was 0.599 ± 0.146 mm (n = 30). One-way ANOVA revealed no statistical differences among the 30 implant guides. The gap between the occlusal surface of the teeth covering and the tissue surface of the implant guide was measured. The maximum gap after positioning of the implant guide was 0.341 mm (mean, 0.179 ± 0.019 mm). The implanted axes of the printed implant guide and designed guide were compared in terms of overall, lateral and angular error, which were 0.104 ± 0.004 mm, 0.097 ± 0.003 mm, and 2.053° ± 0.017°, respectively.

The results of this study demonstrated that the accuracy of a new chair-side tooth-supported fixed implant guide can satisfy clinical requirements.

Unmanned aerial vehicles (UAV), colloquially called drones, are widely applied in many sectors of the economy, including the construction industry. They are used for building inspections, damage assessment, land measurements, safety inspections, monitoring the progress of works, and others.

The study notes that UAV pose new, and not yet present, risks in the construction industry. New threats arise, among others, from the development of new technologies, as well as from the continuous automation and robotization of the construction industry. Education regarding the safe use of UAV and the proper use of drones has a chance to improve the safety of work when using these devices.

The procedure (protocol) was developed for the correct and safe preparation and planning of an unmanned aerial vehicle flight during construction operations.

Based on the analysis of available sources, no such complete procedure has yet been developed for the correct, i.e. compliant with applicable legal regulations and occupational health and safety issues, preparation for flying UAV. The verification and validation of the developed flight protocol was performed on a sample of over 100 different flight operations.

The growth of online communities and social media has led to a growing need for methods, concepts, and tools for researching online cultures. Particular attention should be paid to polarizing online discussion cultures and dynamics that increase inequality in online environments. Social media has enormous potential to create good, but in order to unlock its full potential, we also need to examine the mechanisms keeping these spaces monotonous, homogenous, and even hostile toward some groups. With this need in mind, I have developed the concept and theory of othering online discourse (OOD).

This chapter introduces and defines the concept of OOD and explains the key characteristics and different attributes of OOD in relation to other concepts that deal with disruptive and discriminatory behavior in online spaces. The attributes of OOD are demonstrated drawing on examples gathered from the Finnish Suomi24 (Finland24) forum.

The relationships between tourist resorts and transnational crime are rarely analyzed systematically. This paper begins to fill this gap by examining how organized crime groups and individuals linked to them can take advantage of tourist resorts to commit crimes.

Daily commuting trips of higher education (HE) students account for a large proportion of the carbon footprint of a HE institution. Considerations of students underlying their choice of travel mode and their decision to make the trip to campus or to study online are explored as a necessary first step for finding an optimal balance between online and on-campus learning from both a sustainability and an educational perspective.

Focus group conversations were held with student groups from different study programmes of a university of applied sciences in the Netherlands.

Dutch students’ travel mode choices seem to depend on measures regulating travel demand such as a free public transport card and high parking costs. The findings indicate that students make reasoned choices about making a trip to campus. These choices depend on considerations about their schedule, type, lecturer and content of a course, social norms and their own perceived behavioural control. Alternative online options can provide students with more flexibility to make choices adapted to their needs.

While these findings are useful for sustainable and educational reasons, they also seem helpful in times of COVID-19 which calls for a re-design of curricula to allow for blended forms of online and on-campus learning.

To the best of the authors’ knowledge, this paper is one of the first studies looking at students’ considerations when deciding whether to travel to campus to learn or stay at home learning online.

This paper aims to present the internalization process by which Venezuelan migrants and refugees are resettled. Using system dynamics, the authors model a Brazilian humanitarian operation (“Acolhida” – Welcome), simulate the internalization process, propose policies and provide lessons learned for future migratory operations.

Using system dynamics simulation, the authors use Acolhida Operation’s historical data to recreate the reception and resettlement process of Venezuelan migrants and refugees. The authors identify the main bottlenecks in the system and propose policies to respond to scenarios according to the number of internalization vacancies, that is, available places in Brazil where migrants and refugees can be resettled. Finally, based on interviews with former decision-makers, the model represents a first attempt to convert the pressure of public opinion on authorities into temporary shelters as a way of reducing the number of unassisted people.

The results confirm that internalization vacancies are the main constraint when resettling Venezuelan migrants and refugees. Had the internalization program been promoted since the operation’s beginning, there would have been fewer unassisted people in Roraima and fewer shelters. The pressure-converting mechanism presented in this study, although incipient, constitutes a first attempt to support decision-makers in determining when to build temporary shelters.

This study can be useful to public authorities and humanitarian organizations when developing policies to enhance resettlement in migratory crises. In Acolhida’s case, the internalization program should continue to be the operation’s priority and can be enhanced by investing more resources to create internalization vacancies while maintaining logistical capacities.

The authors suggest policies to improve the Acolhida internalization program: give more people the choice to relocate in other cities, increase turnover in shelters and provide a more efficient and effective response to Venezuelan migration in Roraima.

Although a number of studies have applied system dynamics to humanitarian operations, few models have focused on migratory emergencies, such as those occurring in northern Brazil. The model is applied to the largest humanitarian operation carried out in the Brazilian territory and provides decision-makers with valuable insights and alternatives for better implementation in the future. Furthermore, this study narrows the gap between the social sciences and modeling and simulation techniques by proposing ways of predicting migratory implications in the construction of shelters and resettlement policies.

The purpose of this paper is to study the optimization of the geographical location of a network of points of sale, so that each retailer can have access to a potential geographic market. In addition, the authors study the importance of the distance variable in the commercial viability of a point of sale and a network of points of sale, analysing if the best location for each point (local optimum) is always the best location for the whole (global optimum).

Location-allocation models are applied using p-median algorithms and spatial competition maximization to analyse the actual journeys of 64,740 car buyers in 1240 postal codes using a geographic information system (GIS) and geomarketing techniques.

The models show that the pursuit of individual objectives by each concessionaire over the collective provides poorer results for the whole network of points of sale when compared to coordinated competition. The solutions provided by the models considering geographic and marketing criteria permit a reduction in the length of journeys made by the buyers. GIS allows the optimal control of market demand coverage through the collaborative strategies of the supplying retailers, in this case, car dealerships.

The paper contributes to the joint research of geography and marketing from a theoretical and practical point of view. The main contribution is the use of information on actual buyer journeys for the optimal location of a network of points of sale. This research also contributes to the analysis of the correlation between the optimum local and optimum global locations of a commercial network and is a pioneering work in the application of these models to the automotive sector in the territorial area of the study.

This study aims to empirically investigate how an industrial region has reacted to different shocks – competitive, market and environmental – through its economic subsystems – its firms, workers and institutions – in a longitudinal perspective for the period 1985–2021.

The authors used a mixed-method approach applied to a case study of the Brazilian T&C industrial region. The authors used two data sources and two stages for data collection. The first stage involved documentary research and the second in-depth interviews. The analysis of qualitative data took place in two stages. In the first, the authors applied content analysis, and in the second stage, the authors used the exploratory statistical technique of simple correspondence analysis and the categorical data.

The results provide evidence that different types of shock provoke different reactions. However, the shock–reaction relationship is invariable over time. The authors observed proportionality in the size of the shock and the regional actors involved in the regional response – firms, workers and institutions.

The authors went a step further, presenting empirical research on the shock–reaction relationship using the “type of shock” as a variable. This paper provides a holistic understanding of the factors behind regional resilience through insights into the role that resources, structures, institutions and actors play in the regional response to distinct types of shocks, reaching four main conclusions.