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Augmented reality (AR) has become one of the most promising technologies in construction since it can seamlessly connect the physical construction environment and virtual contents. In view of the recent research efforts, this study attempts to summarize the latest research achievements and inform future development of AR in construction.

The review was conducted in three steps. First, a keyword search was adopted, and 546 papers were found from Scopus and Web of Science. Second, each paper was screened based on the selection criteria, and a final set of 69 papers was obtained. Third, specific AR applications and the associated technical details were extracted from the 69 papers for further analysis.

The review shows that: (1) design assessment, process monitoring and maintenance management and operation were the most frequently cited AR applications in the design, construction, and operation stages, respectively; (2) information browser and tangible interaction were more frequently adopted than collaborative interaction and hybrid interaction; and (3) AR has been integrated with BIM, computer vision, and cloud computing for enhanced functions.

The contributions of this study to the body of knowledge are twofold. First, this study extends the understanding of AR applications in the construction setting. Second, this study identifies possible improvements in the design and development of AR systems in order to leverage their benefits to construction.

How to make an effective use of building information modeling (BIM) for information management (IM) is a challenging question in the field of construction project and asset management. Chen et al. (2015) answered this question by developing a conceptual framework of “bridging BIM and building (BBB).” However, the underlying mechanism through which BBB can truly impact IM remains unclear. The purpose of this paper is thus to demystify the mechanism linking BBB and IM.

Drawing upon the IM literature, this paper proposes three IM requirements, namely, requirements on information quantity, quality and accessibility, as the significant mediators between BBB and IM. To verify this proposition, a two-year, participatory case study was conducted based on a real-life construction project in which a BBB system was implemented.

The results of the case study supported the proposition that by enhancing the information quantity, quality and accessibility BBB could favorably contribute to IM in construction.

This paper provides knowledge about system architecture, components and their linkage in an operable BBB system. It also provides empirical experience about BBB implementation.

This study is among the first attempts to streamline the theoretical discourses relating to BBB for IM in a construction context. It contributes to the construction IM by directing attention to key IM requirements and processes rooted in the IM literature.

The purpose of this paper is to provide a comprehensive review of a non-contact full-field optical measurement technique known as digital image correlation (DIC).

The approach of this review paper is to introduce the research pertaining to DIC. It comprehensively covers crucial facets including its principles, historical development, core challenges, current research status and practical applications. Additionally, it delves into unresolved issues and outlines future research objectives.

The findings of this review encompass essential aspects of DIC, including core issues like the subpixel registration algorithm, camera calibration, measurement of surface deformation in 3D complex structures and applications in ultra-high-temperature settings. Additionally, the review presents the prevailing strategies for addressing these challenges, the most recent advancements in DIC applications across quasi-static, dynamic, ultra-high-temperature, large-scale and micro-scale engineering domains, along with key directions for future research endeavors.

This review holds a substantial value as it furnishes a comprehensive and in-depth introduction to DIC, while also spotlighting its prospective applications.

The use of mobile devices in handling our daily activities that involve the storage or access of sensitive data (e.g. on-line banking, paperless prescription services, etc.) is becoming very common. These mobile electronic services typically use a knowledge-based authentication method to authenticate a user (claimed identity). However, this authentication method is vulnerable to several security attacks. To counter the attacks and to make the authentication process more secure, this paper aims to investigate the use of touch dynamics biometrics in conjunction with a personal identification number (PIN)-based authentication method, and demonstrate its benefits in terms of strengthening the security of authentication services for mobile devices.

The investigation has made use of three light-weighted matching functions and a comprehensive reference data set collected from 150 subjects.

The investigative results show that, with this multi-factor authentication approach, even when the PIN is exposed, as much as nine out of ten impersonation attempts can be successfully identified. It has also been discovered that the accuracy performance can be increased by combining different feature data types and by increasing the input string length.

The novel contributions of this paper are twofold. Firstly, it describes how a comprehensive experiment is set up to collect touch dynamics biometrics data, and the set of collected data is being made publically available, which may facilitate further research in the problem domain. Secondly, the paper demonstrates how the data set may be used to strengthen the protection of resources that are accessible via mobile devices.

The practice of facility management (FM) has been evolving with the rapid development of pervasive sensing technologies (PSTs) such as sensors, automatic identification (auto-ID), laser scanning and photogrammetry. Despite the proliferation of research on the use of PSTs for FM, a comprehensive review of such research is missing from the literature. This study aims to cover the knowledge void by examining the status quo and challenges of the selected PSTs with a focus on FM.

This paper reviewed 204 journal papers recounting cases of using PSTs for FM. The reviewed papers were extracted from Elsevier Scopus database using the advanced search.

Findings of this study revealed that PSTs and FM applications form a many-to-many mapping, i.e. one PST could facilitate many FM applications, and one application can also be supported by various PSTs. It is also found that energy modeling and management is the most referred purpose in FM to adopt PSTs, while space management, albeit important, received the least attention. Five challenges are identified, which include high investment on PSTs, data storage problem, absence of proper data exchange protocols for data interoperability, a lack of mature data processing methods for data utilization and privacy of users.

This paper paints a full picture of PSTs adoption for FM. It pinpoints the promising explorations for tackling the key challenges to future development.

Although international product-harm crises have become more common, the influence of the country image (CI) associated with foreign goods in such crises remains under researched. This study aims to investigate the extent to which the CI of a foreign made product influences consumers’ attribution of blame and trust and, ultimately, their future purchase intentions after the product is involved in a crisis.

A 2 (country) × 3 (crisis type) quasi experimental design was used, with data collected from Australia (n = 375) and China (n = 401).

CI can influence attribution of blame, subsequent levels of trust and likely purchase intentions. Australian and Chinese consumers have different views when it comes to trusting a company or placing blame, depending on the country of origin or the type of crisis. The direct and positive effect of CI on consumer purchase intentions following a product-harm crisis is sequentially mediated by attribution of blame and trust. Trust is the most powerful influence on future purchase intentions in both samples.

In this research, only one type of crisis response strategy (no comment) was used. Thus, the results of this study must be viewed with caution when considering outcomes relating to other response options. Additionally, the testing was limited to only two samples, focussing on three countries (England, China, Vietnam), and one product context using a hypothetical brand. Further, despite our reasonable sample size (N = 776), the number of respondents represented in each cell would still be considered a limitation overall.

When developing crisis response strategies, managers should take into account the influence of a positive/negative source CI in driving attribution and trust. To minimize the impact of crisis on future purchasing decisions, organizations can leverage positive biases and mitigate negative ones, aiming to maintain or restore trust as a priority.

The study provides cross-country understanding about the significant role of CI during a product-harm crisis in relation to subsequent consumers’ blame attribution, their trust in the focal organization and ultimately their future purchase intentions.

The use of the software package mini‐micro CDS/ISIS for the creation of the “Myco Database” is discussed. The design, development of the database and sorting of records are described step by step. Details of the print format and sample printout of the printed version of the directory are given.

To solve the problem of simulation evaluation with small samples, a fresh approach of grey estimation is presented based on classical statistical theory and grey system theory. The purpose of this paper is to make full use of the difference of data distribution and avoid the marginal data being ignored.

Based upon the grey distribution characteristics of small sample data, the definition about a new concept of grey relational similarity measure comes into being. At the same time, the concept of sample weight is proposed according to the grey relational similarity measure. Based on the new definition of grey weight, the grey point estimation and grey confidence interval are studied. Then the improved Bootstrap resampling is designed by uniform distribution and randomness as an important supplement of the grey estimation. In addition, the accuracy of grey bilateral and unilateral confidence intervals is introduced by using the new grey relational similarity measure approach.

The new small sample evaluation method can realize the effective expansion and enrichment of data and avoid the excessive concentration of data. This method is an organic fusion of grey estimation and improved Bootstrap method. Several examples are used to demonstrate the feasibility and validity of the proposed methods to illustrate the credibility of some simulation data, which has no need to know the probability distribution of small samples.

This research has completed the combination of grey estimation and improved Bootstrap, which makes more reasonable use of the value of different data than the unimproved method.

In the era of social media, users all over the world annotate books with social tags to express their preferences and interests. The purpose of this paper is to explore different tagging behaviours by analysing the book tags in different languages.

This investigation collected nearly 56,000 tags of 1,200 books from one Chinese and two English online bookmarking systems; it combined content analysis and machine-processing methods to evaluate the similarities and differences between different tagging systems from a cross-lingual perspective. Jaccard’s coefficient was adopted to evaluate the similarity level.

The results show that the similarity between mono-lingual tags of the same books is higher than that of cross-lingual tags in different systems and the similarity between tags of books written for specialties is higher than that of books written for the general public.

Those who have more in common annotate books with more similar tags. The similarity between users in tagging systems determines the similarity of the tag sets.

The results and conclusion of this study will benefit users’ cross-lingual information retrieval and cross-lingual book recommendation for online bookmarking systems.

This study may be one of the first to compare cross-lingual tags. Its methodology can be applied to tag comparison between any two languages. The insights of this study will help develop cross-lingual tagging systems and improve information retrieval.

By using small reference samples, the calculation method of confidence value and prediction method of confidence interval for multi-input system are investigated. The purpose of this paper is to offer effective assessing methods of confidence value and confidence interval for the simulation models used in establishing guidance and control systems.

In this paper, first, an improved cluster estimation method is proposed to guide the selection of the small reference samples. Then, based on analytic hierarchy process method, the new calculation method of the weight of each reference sample is derived. By using the grey relation analysis method, new calculation methods of the correlation coefficient and confidence value are presented. Moreover, the confidence interval of the sample awaiting assessment is defined. A new prediction method is derived to obtain the confidence interval of the sample awaiting assessment which has no reference sample. Subsequently, by using the prediction method and original small reference samples, Bootstrap resampling method is used to obtain more correlation coefficients for the sample to reduce the probability of abandoning the true.

The grey relational analysis is used in assessing the confidence value and interval prediction. The numerical simulations are presented to demonstrate the effectiveness of the theoretical results.

Based on the selected small reference samples, new calculation methods of the correlation coefficient and confidence value are presented to assess the confidence value of model awaiting assessment. The calculation methods of maximum confidence interval, expected confidence interval and other required confidence intervals are presented, which can be used in assessing the validities of controller and guidance system obtained from the model awaiting assessment.