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This paper aims to provide a comprehensive review of the state-of–the-art design methods for additive manufacturing (AM) technologies to improve functional performance.

In this survey, design methods for AM to improve functional performance are divided into two main groups. They are design methods for a specific objective and general design methods. Design methods in the first group primarily focus on the improvement of functional performance, while the second group also takes other important factors such as manufacturability and cost into consideration with a more general framework. Design methods in each groups are carefully reviewed with discussion and comparison.

The advantages and disadvantages of different design methods for AM are discussed in this paper. Some general issues of existing methods are summarized below: most existing design methods only focus on a single design scale with a single function; few product-level design methods are available for both products’ functionality and assembly; and some existing design methods are hard to implement for the lack of suitable computer-aided design software.

This study is a useful source for designers to select an appropriate design method to take full advantage of AM.

In this survey, a novel classification method is used to categorize existing design methods for AM. Based on this classification method, a comprehensive review is provided in this paper as an informative source for designers and researchers working in this field.

The technical level of aircraft failure analysis plays a special role in ensuring the safety of civil aviation flight. Using appropriate methods for functional failures analysis can provide a reliable reference for aircraft safety. The purpose of this paper is to provide a new and comprehensive measure based on conventional functional hazard analysis (FHA) and grey system theory to analysis and evaluate the class that each failure belongs to.

This paper integrates multiple methods including the FHA, the fixed weight cluster, the Delphi method and the analytic hierarchy process (AHP). To begin with, use FHA method to sort out the corresponding failure states of a certain system from the perspective of function and determine the evaluation index. And then using group decision and AHP, determine the expert weight and index weight in the fixed weight cluster. The fixed weight cluster function is used to determine the grey class to which a certain functional failure belongs in the complex system.

In the past, the risk assessment of aircraft was mostly dominated by the subjective judgment of the experts, but it was not possible to give an objective observation score for each failure state. This paper addresses the problem efficiently as well as the feature of “little data, poor information.” The risk degree of each failure state can ultimately be replaced by a quantitative value.

This paper uses the idea of clustering in grey system theory to evaluate the risk of landing gear system. In the expert evaluation stage, different experts evaluated the impact degree of the aircraft's failure caused by its functions, so the final risk classification is subjective to some extent.

This study analyzed the different conditions of the landing gear, including the front wheel steering, front wheel damping, front wheel steering system, brake system fault information and so on. It can effectively divide the different failure states and their effects, which is helpful to improve the safety of aircraft landing gear system and provide some useful methods and ideas for studying the safety of aircraft systems.

Based on the FHA analysis process and the grey system theory, this paper determines various potential risks and their consequences of various functions according to the hierarchy, so as to carry out further detailed analysis on the risks that may occur under various functional conditions and take certain measures to prevent them. It is helpful to improve the risk management and control ability of aircraft in the actual flight process and to guarantee the safety of people's lives and property.

This paper is a pioneer in integrating the FHA method and the grey system theory, which exactly can be used to address the problem with the character of “little data, poor information.” The model established in this paper for the defects of FHA can effectively improve the accuracy of FHA, which is of great significance for the study of safety. In this paper, a case about landing gear system is given to illustrate the effectiveness of the model.

This study aims to describe the development of hospitality research in terms of research methods and data sources used in the 2010s.

Content analyses of the research methods and data sources used in original hospitality research published in the 2010s in the Cornell Hospitality Quarterly (CQ), International Journal of Hospitality Management (IJHM), International Journal of Contemporary Hospitality Management (IJCHM), Journal of Hospitality and Tourism Research (JHTR) and International Hospitality Review (IHR) were conducted. It describes whether the time span, functional areas and geographic regions of data sources were related to the research methods and data sources.

Results from 2,759 original hospitality empirical articles showed that marketing research used various research methods and data sources. Most finance articles used archival data, while most human resources articles used survey designs with organizational data. In addition, only a small amount of research used data from Oceania, Africa and Latin America.

This study sheds some light on the development of hospitality research in terms of research method and data source usage. However, it only focused on five English-based journals from 2010–2019. Therefore, future studies may seek to understand the impact of the COVID-19 pandemic on research methods and data source usage in hospitality research.

This is the first study to examine five hospitality journals' research methods and data sources used in the last decade. It sheds light on the development of hospitality research in the previous decade and identifies new hospitality research avenues.

The purpose of this study was to provide contemporary scientific knowledge on the functionality of edible lipids, sources, health benefits, and a special emphasis on different encapsulation strategies to enhance their dietary application and boost the market value.

Novel technologies overcoming these issues are in great demand. Given that, several novel encapsulation techniques have been established aiming at most of the aspects of functional lipids. In addition, these techniques have been designed to enhance the storage stability and controlled release of lipids in food systems.

Plant and marine oils are one of the richest sources of functional lipids but are attached with limitations. Currently, alternative sources, such as different types of algae and microorganisms are gaining attention in terms of sustainable production systems. Advances in various encapsulation techniques have helped to overcome the dispersibility and stability problems of lipids encapsulation. Refinement in physicochemical interaction, colloidal dispersion and core-shell modules between wall and core matrix protect dietary lipids during processing have been implemented. Liposomes, micro/nanoemulsions and micro/nanocapsules are found most suitable for food application by improving the fatty acid profile, stability and sensorial properties.

Functional lipids offer numerous health benefits (i.e., simple health-promoting properties to complex disease preventive and curative effects). However, these functional lipids are associated with several disadvantages, such as region-specific availability, vulnerability to oxidation depending on the level of unsaturation, degradation/hydrolysis on processing, low bioavailability, confined storage stability, and others.

The objective of this study is to propose a functional framework for hydrological applications by treating flood hydrographs as functional data. Discrete flow data are transformed into a smoothing hydrograph curve, which can be analysed at any time interval. The concept of functional data considered the entire curve concerning time as a single observation. This chapter briefly discussed the idea of descriptive statistics, principal components and outliers in a functional framework. These methods were illustrated in the flood study at Sungai Kelantan River Basin, Malaysia. The results showed that five main components accounted for almost 73.8% of the overall flow variance. Based on the results of the factor scores, the hydrograph curves for the years 1988, 1993 and 2014 may be said to have a unique cluster of their own, while the rest of the years which consider having the same pattern. Due to various shapes and magnitudes, the hydrograph curves of 1988 and 2014 are considered outliers. In conclusion, the functional framework has shown that it is capable of representing a wide range of hydrographs and is capable of extracting additional information found in the hydrograph curve that cannot possibly be captured using classical statistical methods.

Tiered systems may hold particular benefit for students with intensive intervention needs, as this continuum of supports is ideally comprised of evidence-based practices. In this chapter, we explore three intensive interventions: functional assessment-based interventions (FABI), First Step to Success, and Read 180 as they feature a range of practices and programs to meet students' academic, behavioral, and social needs. We define and describe each intervention, including information on essential features necessary for drawing valid inferences: treatment integrity, social validity, as well as student performance. We also provide examples of supporting evidence, featuring treatment-outcome studies documenting intervention effectiveness. We close with clarifications and considerations for meeting the multiple needs of students requiring intensive intervention efforts.

The purpose of this paper is the realization of Fast nonlinear finite element analysis (FEA).

Nonlinear magnetic field analysis is achieved by using Newton-Raphson method implemented by relaxed convergence criterion of Krylov subspace method.

This paper mathematically analyzes the reason why nonlinear convergence can be achieved if the convergence criterion for linearized equation is relaxed.

The proposed method is essential to reduce the elapsed time in nonlinear magnetic field analysis of quasi-stationary field.

The proposed method is able to be extended to not only static field but also time domain FEA strongly coupled with circuit equation.

Because the speedup of performance evaluation of electrical machines would be achieved using proposed method, the work efficiency in manufacturing would be accelerated.

It can be seen that the nonlinear convergence can be achieved if the convergence criterion for linearized equation is relaxed. The verification of proposed method is demonstrated using practical nonlinear magnetic field problem.

There are many investigations in design methodologies, but there are also divergences and convergences as there are so many points of view. This study aims to evaluate to corroborate and deepen other researchers’ findings, dissipate divergences and provide directing to future work on the subject from a methodological and convergent perspective.

This study analyzes the previous reviews (about 15 reviews) and based on the consensus and the classifications provided by these authors, a significant sample of research is analyzed in the design for additive manufacturing (DFAM) theme (approximately 80 articles until June of 2017 and approximately 280–300 articles until February of 2019) through descriptive statistics, to corroborate and deepen the findings of other researchers.

Throughout this work, this paper found statistics indicating that the main areas studied are: multiple objective optimizations, execution of the design, general DFAM and DFAM for functional performance. Among the main conclusions: there is a lack of innovation in the products developed with the methodologies, there is a lack of exhaustivity in the methodologies, there are few efforts to include environmental aspects in the methodologies, many of the methods include economic and cost evaluation, but are not very explicit and broad (sustainability evaluation), it is necessary to consider a greater variety of functions, among other conclusions

The novelty in this study is the methodology. It is very objective, comprehensive and quantitative. The starting point is not the case studies nor the qualitative criteria, but the figures and quantities of methodologies. The main contribution of this review article is to guide future work on the subject from a methodological and convergent perspective and this article provides a broad database with articles containing information on many issues to make decisions: design methodology; optimization; processes, selection of parts and materials; cost and product management; mechanical, electrical and thermal properties; health and environmental impact, etc.

This study aims to investigate the extent and pattern of the influence of one of the most important decision-making tools in the context of social commerce. This study demonstrates how much customer testimonials (including verified purchases and ordinary users) can influence the sales rank of experience and search goods.

The data were collected by text mining and performing a content analysis on the XML documents of Web pages and processing them. For search goods, 22,311 opinions were recorded regarding 95 mobile phones. Additionally, for experience goods, 67,817 opinions were recorded regarding 162 books in the Amazon online store. The data were analyzed by functional regression method in longitudinal data analysis.

In terms of importance, the opinions and recommendations of verified purchases had a 60% greater impact on the sales rank of experience goods than the opinions and recommendations of ordinary users. In search goods, the opinions of ordinary users had a greater impact than the opinions of verified purchases. The historical effect of the opinions of ordinary users at the end of the review period on sales rank was evident, while the historical effect of the verified purchase viewpoints during the review period had a nonlinear curve. The results showed that it was necessary to increase the volume of comments to increase their reliability in experience goods.

Measuring the effect of customer testimonials helps the managers of retail websites design algorithms and online suggestion systems, thereby improving the sales of their products by providing information desired by customers.

Individuals can be a source of information and influence the buying decision process of others by sharing their experiences. This issue helps reduce the purchase risk and explains the importance of interaction and sharing the customer’s experience.

Analyzing the impact of customer testimonials by separating verified purchases and ordinary users is one of the advantages of this study. The quantitative estimation of the impact of recommendations and the provision of a model of their historical effect is one of the approaches not addressed in similar studies.

The purpose of this paper is to provide a brief overview of the methodology of several brain imaging techniques and in particular, functional magnetic resonance imaging (fMRI) and its potential implications for market research. The aim is to enable the reader both to understand this emerging methodology and to conduct independent research in the area.

A short introduction on current neuroimaging methods used in behavioral neuroscience is provided by means of a literature review. The ensuing discussion focuses on fMRI as the currently most popular neuroimaging technique. Having described the fMRI methodology, an outline of the analysis of functional neuroimaging data follows, after which there is a discussion of some key research issues.

Although in its infancy, fMRI seems to be a useful and promising tool for market researchers. Initial studies in the field reveal that fMRI is able to shed light on subconscious processes such as affective aspects of consumer behavior.

Because brand positioning, advertising strategies and even pricing strategies are often based on constructs such as emotions, neuropsychological findings and methods should have important implications for practitioners in the field of brand management and advertising. Nonetheless, far more basic research is needed before fMRI can be adopted for marketing practice.

This paper is one of the first in the marketing literature to provide a methodological overview of fMRI and discuss the potential implications for marketing research.