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This study aims to ensure reliable analysis of dynamic responses in asphalt pavement structures. It investigates noise reduction and data mining techniques for pavement dynamic response signals.

The paper conducts time-frequency analysis on signals of pavement dynamic response initially. It also uses two common noise reduction methods, namely, low-pass filtering and wavelet decomposition reconstruction, to evaluate their effectiveness in reducing noise in these signals. Furthermore, as these signals are generated in response to vehicle loading, they contain a substantial amount of data and are prone to environmental interference, potentially resulting in outliers. Hence, it becomes crucial to extract dynamic strain response features (e.g. peaks and peak intervals) in real-time and efficiently.

The study introduces an improved density-based spatial clustering of applications with Noise (DBSCAN) algorithm for identifying outliers in denoised data. The results demonstrate that low-pass filtering is highly effective in reducing noise in pavement dynamic response signals within specified frequency ranges. The improved DBSCAN algorithm effectively identifies outliers in these signals through testing. Furthermore, the peak detection process, using the enhanced findpeaks function, consistently achieves excellent performance in identifying peak values, even when complex multi-axle heavy-duty truck strain signals are present.

The authors identified a suitable frequency domain range for low-pass filtering in asphalt road dynamic response signals, revealing minimal amplitude loss and effective strain information reflection between road layers. Furthermore, the authors introduced the DBSCAN-based anomaly data detection method and enhancements to the Matlab findpeaks function, enabling the detection of anomalies in road sensor data and automated peak identification.

Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing system is essential for intelligent robots with various types of sensors. To mimic human-like abilities, sensors similar to human perception capabilities are indispensable. However, most research only concentrated on analyzing literature on single-modal sensors and their robotics application.

This study presents a systematic review of five bioinspired senses, especially considering a brief introduction of multimodal sensing applications and predicting current trends and future directions of this field, which may have continuous enlightenments.

This review shows that bioinspired sensors can enable robots to better understand the environment, and multiple sensor combinations can support the robot’s ability to behave intelligently.

The review starts with a brief survey of the biological sensing mechanisms of the five senses, which are followed by their bioinspired electronic counterparts. Their applications in the robots are then reviewed as another emphasis, covering the main application scopes of localization and navigation, objection identification, dexterous manipulation, compliant interaction and so on. Finally, the trends, difficulties and challenges of this research were discussed to help guide future research on intelligent robot sensors.

This paper investigates the consequences of job insecurity among hotel employees during the COVID-19 pandemic.

Data were obtained from the employees of two five-star chain hotels in Turkey. The study hypotheses were tested via structural equation modeling.

The research findings demonstrate that job insecurity exacerbates job tension. Job tension erodes employees’ trust in organization and aggravates their propensity to leave work early and be late for work. As hypothesized, job tension mediates the effect of job insecurity on organizational trust and the abovementioned outcomes.

This study adds to the hospitality literature by assessing the interrelationships of job insecurity, job tension, organizational trust and nonattendance intentions.

Teleworkers need to use information and communication technology (ICT) to communicate and collaborate with their team members, however, when new and complicated information systems should be used, this can lead to stress. Receiving adequate information and emotional support from team members could reduce the stress caused by technological complexity and subsequent work and occupational strains.

Participants (N = 400) teleworked at least half of their working hours and were employed in organizations with a minimum of 250 employees. Data from the online survey were analyzed using structural equation modeling.

Results demonstrate that aspects of informational and emotional communication contribute to perceived social support from team members, with emotional communication explaining more variance. Stress from technological complexity is mitigated by both supportive team communication and the extent of telework. Perceived stress from technological complexity, however, still increases work and occupational strains.

The findings emphasize the importance of supportive internal communication to foster a collaborative telework environment. Practitioners in internal communication need to encourage teleworkers to help each other with adequate information and provide also emotional support to overcome the negative effects of complex ICT.

The study shows that supportive communication among team members is important for teleworkers to reduce work and occupational strains, especially when facing difficulties with complex ICT.

Involving employees in making management decisions is a powerful way to enhance organizational performance. However, employee involvement (EI) might exacerbate psychosocial stress at work. This paper aims to investigate this issue, illuminating the implications of EI on work-related stress.

Secondary data were collected from the third wave of the European Survey of Enterprises on New and Emerging Risks. A conditional process analysis based on ordinary least square regression and bootstrap sampling was accomplished to obtain evidence of the implications of EI on psychosocial risks (PSR) at work, taking into consideration the mediating role of organizational health promotion initiatives (HPI).

EI increased the sources of psychosocial stress at work, adding to individual job demands. Involving employees was positively related to a greater organizational concern for HPI, which, in turn, lessened psychosocial strain.

Although it contributes to organizational performance, EI propels work-related stress, which undermines individual and collective wellbeing. Involvement practices should be coupled with tailored HPI to address the PSR at work triggered by involvement, empowering people to cope with strain.

Scientific literature emphasizes the positive implications of EI on organizational performance, but little is known about its side effects on work-related stress. The paper provides original insights into this topic, arguing that HPI are necessitated to address the drawback of involvement on work-related stress.

This study aims to investigate the effect of speckle pattern on displacement measurements using different speckle diameters and coverage ratios.

In order to compare the coverage ratio and speckle diameter during the evaluation of the correlation of digital images (DIC) study, template speckle plates were produced on a computer numerical control (CNC) punch press with 600 punches per minute. After the speckle plates were manufactured, the speckled pattern was randomly painted on a plain white side through the manufactured template plates, and then tensile tests were performed under the same loading conditions for each sample to observe displacement variation via correlation parameters.

During the manufacturing of templates with thin plates, a punch diameter of less than 1.7 mm will cause tool failure; therefore, uniform speckle size can be assessed before operation. A higher coverage ratio resulted in more accurate and reliable results in displacement data. With smaller coverage, the facet size should be increased to achieve favorable results.

If thick template plates are selected, speckle painting cannot be done properly; therefore, template thickness shall also be assessed before operation.

For randomly distributed DIC templates, increasing coverage beyond 50% does not make sense due to difficulties in the production process in the punch press.

Evaluating DIC results via templates manufactured in a punch press with different speckle diameters and coverage ratios is a new topic in literature.

This study aims to enhance merging of additive manufacturing (AM) techniques with powder injection molding (PIM). In this way, the prototypes could be 3D-printed and mass production implemented using PIM. Thus, the surface properties and mechanical performance of parts produced using powder/polymer binder feedstocks [material extrusion (MEX) and PIM] were investigated and compared with powder manufacturing based on direct metal laser sintering (DMLS).

PIM parts were manufactured from 17-4PH stainless steel PIM-quality powder and powder intended for powder bed fusion compounded with a recently developed environmentally benign binder. Rheological data obtained at the relevant temperatures were used to set up the process parameters of injection molding. The tensile and yield strengths as well as the strain at break were determined for PIM sintered parts and compared to those produced using MEX and DMLS. Surface properties were evaluated through a 3D scanner and analyzed with advanced statistical tools.

Advanced statistical analyses of the surface properties showed the proximity between the surfaces created via PIM and MEX. The tensile and yield strengths, as well as the strain at break, suggested that DMLS provides sintered samples with the highest strength and ductility; however, PIM parts made from environmentally benign feedstock may successfully compete with this manufacturing route.

This study addresses the issues connected to the merging of two environmentally efficient processing routes. The literature survey included has shown that there is so far no study comparing AM and PIM techniques systematically on the fixed part shape and dimensions using advanced statistical tools to derive the proximity of the investigated processing routes.

This study aims to identify and review research articles to understand the conceptualization of employee engagement (EE) in a remote working environment. Specifically, the aim is to explore the antecedents impacting remote workers’ engagement.

A systematic literature review was conducted, encompassing empirical studies sourced from EBSCO, Emerald and Gale databases. Studies published in peer-reviewed journals between 2013 and 2023 covering countries in the Organization for Economic Co-operation and Development (OECD) were included. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed to capture the review process.

A total of 25 empirical studies published across 18 journals were synthesized, with the results being reported in terms of three research objectives. The researchers identified that individual, organizational/job resources and organizational/job demands are the three main antecedents affecting EE in remote working environments.

This study can serve as an important source of information for academics and practitioners as well as postulate new avenues for the future research. While the Job Demands-Resources model remains relevant in specifying demands and resources as antecedents of workforce engagement, technological antecedents gain prominence as additional factors contribute to the engagement of remote workforce.

This article studies the shifting landscape of EE with the rise of remote working and the need to gain a better understanding of how to keep remote workers engaged.

Urban digital transformation has become a key strategy in global countries. This study aims to provide a comprehensive and dynamic exploration of the intrinsic traits associated with urban digital transformation, in order to yield detailed insights that can contribute to the formulation of well-informed decisions and strategies in the field of urban development initiatives.

Through analysis of parallels between urban digital transformation and gyroscope motion in physics, the study developed the urban digital transformation gyroscope model (UDTGM), which comprises of seven core elements. With the balanced panel dataset from 268 cities at and above the prefecture level in China, we validate the dynamic mechanism of this model.

The findings of this study underscore that the collaboration among infrastructure development, knowledge-driven forces and economic operations markedly bolsters the urban digital transformation gyroscope’s efficacy.

This research introduces a groundbreaking framework for comprehending urban digital transformation, potentially facilitating its balanced and systemic practical implementation.

This study pioneers the UDTGM theoretically and verifies the dynamic mechanism of this model with real data.

This paper aims to explore the research field of digital transformation in small and medium enterprises (SMEs), considering the importance of SMEs in the economic development of countries.

Considering the contributions of researchers and the challenges of SMEs to transform their business models, in this paper, the authors conducted a scientometric analysis using CiteSpace that included 448 documents indexed in Scopus.

The authors appreciated the growth in the number of publications that have studied the digital transformation process in SMEs, showing a niche of researchers interested in the flourishing research topic. Likewise, the authors identified the intention of SMEs to adopt digital technologies such as artificial intelligence, big data, cloud computing, data analytics, electronic commerce and the Internet of Things.

This paper is a valuable resource for academics and researchers in information systems, decision-makers in digital transformation in SMEs and governmental organisations concerned with digital technologies adoption in SMEs to achieve digital transformation and increase competitiveness and productivity.

This study used CiteSpace to conduct a scientometric analysis to explore how researchers have focused on frameworks and maturity models for measuring SME readiness, the impact of Industry 4.0 on SMEs, guides for helping managers evaluate their Industry 4.0 positioning, the development and implementation of digital business strategies for SMEs, the presentation of cases of SMEs that have driven digital transformation and future research opportunities.