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With the increasing use of small unmanned aircrafts (SUAs), many countries have enacted laws and regulations to ensure the safe use of SUAs. However, there is a lack of industry-specific regulations accounting for the unique features of construction-related SUA operations. Operating SUAs in the construction industry is attributed to specific risks and challenges, which should be regulated to maximize the utility of SUAs in construction. This study, therefore, aims to develop a multi-dimensional regulatory framework for using SUAs in the construction industry.

A combination of quantitative and qualitative methods was used to compare seven selected national/regional SUA regulations to identify the applicability of implementing the existing regulations in construction. The interview surveys were then conducted to diagnose the challenges of construction-related SUA operations and gather interviewees' suggestions on the regulatory framework for SUA uses in construction.

The research found that some challenges of construction-related SUAs operations were not addressed in the current regulations. These challenges included the complex and time-consuming SUA operation permit, lack of regulation for special SUA operations in construction, insufficient regulatory compliance monitoring and a lack of construction-related remote pilots' training. A regulatory framework was then developed based on the findings of comparative analysis and interview surveys.

This study mainly compared seven representative countries/regions' regulations, leading to a small sample size. Further research should be carried out to study the SUA regulations in other places, such as South Africa, South America or Middle East countries. Besides, this study's respondents to the interviews were primarily concentrated in Hong Kong, which may cause the interview results to differ from the construction industry in other countries/regions. A large-scale interview survey should be conducted in other places in the future to validate the current findings.

The proposed regulatory framework provides a reference for the policy-makers to formulate appropriate industry-specific SUA regulations and improve the applicability of SUA regulations in the construction industry. It sheds light upon the future of SUA regulations and the development of regulatory practice in this area.

This study is the first to propose a multi-dimensional regulatory framework for operating SUAs in construction by comprehensive policy comparisons and interviews. The regulatory framework offers a fresh insight into the unexplored research area and points out the direction for subsequent studies on SUA regulations in the construction industry.

In the last decades, various building information modeling–life cycle assessment (BIM-LCA) integration approaches have been developed to assess the environmental impact of the built asset. However, there is a lack of consensus on the optimal BIM-LCA integration approach that provides the most accurate and efficient assessment outcomes. To compare and determine their accuracy and efficiency, this study aimed to investigate four typical BIM-LCA integration solutions, namely, conventional, parametric modeling, plug-in and industry foundation classes (IFC)-based integration.

The four integration approaches were developed and applied using the same building project. A quantitative technique for evaluating the accuracy and efficiency of BIM-LCA integration solutions was used. Four indicators for assessing the performance of BIM-LCA integration were (1) validity of LCA results, (2) accuracy of bill-of-quantity (BOQ) extraction, (3) time for developing life cycle inventories (i.e. developing time) and (4) time for calculating LCA results (i.e. calculation time).

The results show that the plug-in-based approach outperforms others in developing and calculation time, while the conventional one could derive the most accuracy in BOQ extraction and result validity. The parametric modeling approach outperforms the IFC-based method regarding BOQ extraction, developing time and calculation time. Despite this, the IFC-based approach produces LCA outcomes with approximately 1% error, proving its validity.

This paper forms one of the first studies that employ a quantitative and objective method to determine the performance of four typical BIM-LCA integration solutions and reveal the trade-offs between the accuracy and efficiency of the integration approaches. The findings provide practical references for LCA practitioners to select appropriate BIM-LCA integration approaches for evaluating the environmental impact of the built asset during the design phase.

The purpose of this paper is to present a novel photomask auto‐correction method for the area‐forming rapid prototyping (RP) system.

A digital light processing (DLP) projector was used in this research as a light source to generate the photomask image. A set of optical lenses were mounted in front of the DLP to rescale the photomask image. The rescaled photomask image was collected into a computer via a camera. By using the technique of image processing, the actual size of the photomask was then calculated. The designed size of the photomask image was eventually achieved by adjusting the relative locations of the lenses.

It was found that this proposed photomask auto‐correction method can produce a more accurate dimension of the photomask image and perform with higher efficiency than the manual calibration processes.

The paper is believed to be the first work to use the image‐processing technique to calibrate the photomask of an area‐forming RP system, as well as to employ a method of adjusting the relative position between the lenses to rescale the photomask image size.

The purpose of this paper is to show how previous studies have demonstrated that non‐professional users prefer using event‐based conceptual descriptions, such as “a woman wearing a hat”, to describe and search images. In many art image archives, these conceptual descriptions are manually annotated in free‐text fields. This study aims to explore technologies to automate event‐based knowledge extractions from these free‐text image descriptions.

This study presents an approach based on semantic role labeling technologies for automatically extracting event‐based knowledge, including subject, verb, object, location and temporal information from free‐text image descriptions. A query expansion module is applied to further improve the retrieval recall. The effectiveness of the proposed approach is evaluated by measuring the retrieval precision and recall capabilities for experiments with real life art image collections in museums.

Evaluations results indicate that the proposed method can achieve a substantially higher retrieval precision than conventional keyword‐based approaches. The proposed methodology is highly applicable for large‐scale collections where the image retrieval precision is more critical than the recall.

The study provides the first attempt in literature for automating the extraction of event‐based knowledge from free‐text image descriptions. The effectiveness and ease of implementation of the proposed approach make it feasible for practical applications.

Introduction: Traditional recruitment system relied heavily on the applicants’ curriculum vitae (CV). This system, besides becoming redundant, has proved to be a futile exercise leading to the hiring of candidates that eventually turn out to be ‘misfits’. CVs were the only source of candidates’ data available for the recruiters a few years back. Face-to-face interviews was considered to be the ultimate solution for hiring suitable candidates. However, evidence suggests that interview scores and job performances do not complement each other. Advancement in artificial intelligence (AI) has introduced several techniques in the recruitment process.

Purpose: This chapter underscores the drawbacks of the traditional recruitment process. Evidence suggests that the traditional recruitment process is prone to subjectivity and is time-consuming. Surprisingly, despite the disadvantages, the integration of AI into the recruitment process is still slow. This chapter highlights the need to harness AI and the advantage technology could bring to the recruitment process. Some of the techniques that are garnering attention and widely used by organisations, such as chatbots, gamification, virtual employment interviews, and resume screening are described to enable the readers to understand with less effort. Chatbots and gamification techniques are described through process flow charts. We also describe the various types of interviews that could be conducted through virtual platforms and the modality by which the resume screening technique operates. Today, we are at a juncture wherein it is pertinent to acknowledge the superiority of technology-driven processes over traditional ones. This chapter will help the readers to understand the modus operandi to implement chatbots, gamification, virtual interviews and online resume screening techniques besides their advantages.

Scope: Although chatbots, resume screening, virtual interviews, and gamification are used in other areas, too, such as training and development, marketing, etc., in this chapter, we restrict solely to employee recruitment processes.

Methodology: Scoping review is used to examine the existing literature from various databases such as Google Scholar, IEEE, Proquest, Emerald, Elsevier, and JSTOR databases are used for extracting relevant articles.

Findings: Automation and analytics in recruitment and selection remove bias which is otherwise increasingly found in manual hiring processes. Also, previous studies have observed that candidates engage in impression management tactics in traditional face-to-face interviews. However, through automated recruitment processes, the influence of these tactics can be eliminated. AI-based virtual interviews reduce human bias. It also helps recruiters to hire talents across the globe. Gamification improves the candidate’s perception of the work and work environments. Through gamified techniques, the recruiters can understand whether a candidate possesses the required job skills. Chatbots are an interactive technique that can respond to interviewees’ queries. Resume screening techniques can save the recruiter’s time by screening and selecting the most appropriate candidates from a large pool. Hence, the chosen candidates alone can be referred to the next stage of the recruitment cycle. AI improves the efficiency of the recruitment process. It reduces mundane tasks. It saves time for the human resources (HR) team.

Historically, hot springs have been regarded as hedonic and foodie destinations, yet the antecedents that affect tourists' intentions for local cuisine in hot springs remain unexplored. The present study aims to address this knowledge gap by considering the role of nostalgia and hedonic values in tourist food consumption.

Data were collected from 315 domestic tourists by intercept surveys conducted in the Beitou Hot Spring, Taiwan. Covariance-based structural equation modeling (SEM) and bootstrapping were used to test the hypotheses as well as mediating effects.

Nostalgia positively influences hedonic values, which affect tourists' intentions for local food consumption. Unexpectedly, nostalgia does not directly influence tourists' preferences due to complete mediation through hedonic values.

Given a growing number of young consumers visiting hot springs, hedonic experience is essential and more effective for pulling visitors and stimulating local food consumption than nostalgia vibes are. Cross-cultural samples and qualitative research are suggested for future studies.

The study demonstrates different levels of nostalgia in different ages. It highlights the mediating role of hedonic values between nostalgia and tourists' intentions for local cuisine in the hot spring destinations, which has been overlooked in previous studies. Originality is also established by simultaneously investigating hedonic values and behavioral intentions within the context of food tourism.

Wire and arc additive manufacturing (WAAM) technology-based cold metal transfer (CMT) to produce large aluminum alloy parts has become more and more popular. In WAAM, wire is the only raw material. The purpose of this paper is to study the effect of wire composition on the microstructure and properties of the ZAlCu5MnCdVA alloy deposited by WAAM.

Two thin-walled ZAlCu5MnCdVA alloys with different wire compositions were prepared by WAAM. The copper contents were 4.7% (Al-4.7Cu) and 5.0% (Al-5.0Cu), respectively. The microstructure, element distribution and evolution of precipitated phases of the two samples were characterized and analyzed by optical microscopy, scanning electron microscopy and transmission electron microscopy. Hardness and tensile properties of samples were tested, and strengthening mechanism was analyzed in detail.

The results show that grain sizes of Al-4.7Cu and Al-5.0Cu are less than 40 μm. The average mass fraction of Cu in Al matrix and the number of nanometer scale θ'' and θ' phases are the main factors affecting the tensile properties of Al-Cu alloy. Tensile properties of two materials show different characteristics at room temperature and high temperature. Al-5.0Cu is better at room temperature and Al-4.7Cu is better at high temperature. The yield strength (YS), ultimate tensile strength (UTS) and elongation in the x direction of Al-5.0Cu at room temperature are 451 ± 10.2 MPa, 486 ± 10.2 MPa and 9 ± 0.5%, respectively. The YS, UTS and elongation in the x direction of Al-4.7Cu at high temperature are 290 ± 4.5 MPa, 356 ± 7.0 MPa and 13% ± 0.2%, respectively.

Experiments show that the increase of Cu element can improve the properties at room temperature of the ZAlCu5MnCdVA alloy by WAAM, but its properties at high temperature decrease.

Bumpless Cu/SiO₂ hybrid bonding, which this paper aims to, is a key technology of three-dimensional (3D) high-density integration to promote the integrated circuits industry’s continuous development, which achieves the stacks of chips vertically connected via through-silicon via. Surface-activated bonding (SAB) and thermal-compression bonding (TCB) are used, but both have some shortcomings. The SAB method is overdemanding in the bonding environment, and the TCB method requires a high temperature to remove copper oxide from surfaces, which increases the thermal budget and grossly damages the fine-pitch device.

In this review, methods to prevent and remove copper oxidation in the whole bonding process for a lower bonding temperature, such as wet treatment, plasma surface activation, nanotwinned copper and the metal passivation layer, are investigated.

The cooperative bonding method combining wet treatment and plasma activation shows outstanding technological superiority without the high cost and additional necessity of copper passivation in manufacture. Cu/SiO₂ hybrid bonding has great potential to effectively enhance the integration density in future 3D packaging for artificial intelligence, the internet of things and other high-density chips.

To achieve heterogeneous bonding at a lower temperature, the SAB method, chemical treatment and the plasma-assisted bonding method (based on TCB) are used, and surface-enhanced measurements such as nanotwinned copper and the metal passivation layer are also applied to prevent surface copper oxide.