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Current practices for inspecting highway construction predominantly rely on manual processes, which result in subjective assessments, errors and time inefficiencies. The purpose of this study is to address the inefficiencies and potential inaccuracies inherent in manual highway construction inspections. By leveraging computer vision and ontology reasoning, the study seeks an automated and efficient approach to generate structured construction inspection knowledge in the format of checklists for construction activities on highway construction job sites.

This study proposes a four-module framework based on computer vision and ontology reasoning to enable the automatic generation of checklists for quality inspection. The framework includes: (1) the interpretation of construction scenes based on computer vision, (2) the representation of inspection knowledge into structured checklists through specification processing, (3) the connection of construction scenes and inspection knowledge via ontology reasoning and (4) the development of a prototype for the automatic generation of checklists for highway construction.

The proposed framework is implemented across four distinct highway construction scenarios. The case demonstrations show that the framework can interpret construction scenes and link them with relevant inspection knowledge automatically, resulting in the efficient generation of structured checklists. Therefore, the proposed framework indicates considerable potential for application in the automatic generation of inspection knowledge for the quality inspection of highway construction.

The scientific and practical values of this study are: (1) the establishment of a new method that promotes the automated generation of structured inspection knowledge for highway construction by integrating computer vision and ontology reasoning and (2) the development of a novel framework that provides efficient and immediate access to inspection knowledge related to what needs to be inspected at highway construction job sites.

This study quantitatively investigates the impacts of digital and learning orientations on supply chain resilience (SCR) and firm performance (FP), aiming to fill the gaps in understanding their specific impacts in the context of Industry 4.0 developments and supply chain disruptions.

This study utilized survey techniques and structural equation modelling (SEM) to gather and analyse data through a questionnaire based on a seven-point Likert scale. Hypotheses were formulated based on an extensive literature review and tested using Amos software.

The study confirms SCR’s significant impact on FP, aligning with existing research on resilience’s role in organizational competitiveness. This study uncovers the nuanced impacts of digital and learning orientations on SCR and FP. Internal digital orientation (DOI) positively impacts SCR, while external digital orientation (DOE) does not. Specific dimensions of learning orientation – shared vision (LOS), open-mindedness (LOO) and intraorganizational knowledge sharing (LOI) – enhance SCR, while commitment to learning (LOC) does not. SCR mediates the relationship between DOI and FP but not between DOE and FP.

This research focuses on digital and learning orientations, recommending that future studies investigate other strategic orientations and examine the specific contributions of various digital technologies to SCR across diverse contexts.

The empirical findings emphasize the significance of developing internal digital capabilities and specific learning orientations to enhance SCR and FP, aligning these initiatives with resilience strategies.

This study advances knowledge by distinguishing the impacts of internal and external digital orientations and specific learning dimensions on SCR and FP, offering nuanced insights and empirical validation.

Due to the conflicts between left turn traffic and opposite straight-going traffic in urban traffic network, some of the traffic lanes cannot be used to discharge vehicles during its green phases and the intersection capacity can be greatly reduced. This study/paper aims to reduce the effect of conflicts and increase its capacity through the reasonable pre-signal phase time with the exchangeable lanes.

This paper took into consideration various influence factors to intersection capacity and formulated the capacity optimization model based on 0-1 mixed-integer programming model. This model is efficiently solved by standard branch-and-bound algorithms.

The authors took an intersection as an example and solved the optimal signal timing and entrance lane capacity via this model. Then, simulations were carried out to verify the effect of the exchangeable lanes strategy of this intersection through the simulation software VISSIM and take the traffic volume and delay as outputs, which indicated that this model has better performance.

The front-end control strategy can not only exploit the full potential of the intersection but also significantly improve the operational efficiency of the intersection. It plays a positive role in improving urban intersection congestion.

Fixed mode noise and random mode noise always exist in the image sensor, which affects the imaging quality of the image sensor. The charge diffusion and color mixing between pixels in the photoelectric conversion process belong to fixed mode noise. This study aims to improve the image sensor imaging quality by processing the fixed mode noise.

Through an iterative training of an ergoable long- and short-term memory recurrent neural network model, the authors obtain a neural network model able to compensate for image noise crosstalk. To overcome the lack of differences in the same color pixels on each template of the image sensor under flat-field light, the data before and after compensation were used as a new data set to further train the neural network iteratively.

The comparison of the images compensated by the two sets of neural network models shows that the gray value distribution is more concentrated and uniform. The middle and high frequency components in the spatial spectrum are all increased, indicating that the compensated image edges change faster and are more detailed (Hinton and Salakhutdinov, 2006; LeCun et al., 1998; Mohanty et al., 2016; Zang et al., 2023).

In this paper, the authors use the iterative learning color image pixel crosstalk compensation method to effectively alleviate the incomplete color mixing problem caused by the insufficient filter rate and the electric crosstalk problem caused by the lateral diffusion of the optical charge caused by the adjacent pixel potential trap.

Laser cleaning, as a new type of cleaning technology, has the advantages of environment-friendliness, better selectivity, better controllability and higher efficiency compared to traditional chemical cleaning or grinding. This paper aims to use ultra-fast surface laser cleaning equipment built in laboratory to study the influence of different energy density (7.6, 11.5 and 15.3 J/cm²) on corrosion resistance of the aluminum alloy A7N01P-T4, a high-speed train body material.

SEM, white light interferometer, EDS and XPS were used to analyze the surface morphology, roughness, element content and oxide layer composition of aluminum alloy before and after cleaning. The corrosion resistance was studied by electrochemical experiments and exfoliation corrosion experiments.

The results showed that new oxide scale was formed on the surface after laser cleaning. The changes of surface roughness and chemical composition of oxide scale made a significant influence on corrosion behaviors. Better corrosion resistance was obtained with the energy density increased, and at the energy density of 11.5 J/cm², aluminum alloy exhibited the best corrosion resistance.

The paper only studies specific aluminum alloys and is not universal. Laser cleaning equipment is set up for the laboratory and has not yet been put into industrial production.

This paper indicated that ultra-fast laser processing was a new direction for the development of industrial equipment surface cleaning and carried out ultra-fast laser of aluminum alloy surface cleaning had certain research significance for its corrosion resistance.

Compared with the conventional cleaning methods such as air abrasives grinding or chemical cleaning, laser cleaning has advantages of environment-friendliness, better selectivity, better controllability and higher efficiency. Laser cleaning can not only protect the environment, but also improve cleaning efficiency.

Changes in the surface of aluminum alloys after ultra-fast surface laser treatment were found, and the mechanism of changes in aluminum alloy corrosion properties was clarified.

Lesson study (LS) is generally regarded as a pathway for teachers' professional development and a method for teachers' instructional research. LS has been regarded as having the potential to drive large-scale reform but little is known about how it does so from a district level. Therefore, this paper aims to reveal how lesson study promote district education reform.

This study offers an in-depth case study of how District Y of Shanghai, China, took LS as the primary method in promoting its District Project of Building Curriculum Leadership in Schools. By analyzing the key project documents and achievements in project promotion, and interviews with the major Project leaders at District and school levels, this study explored the practice and impact of LS as a tool to promote district reform.

In the District Project, LS has been a medium to address each individual school's real problems of practice and turn them into reform vision and reform will in alignment with District goals. Five levels of school curriculum texts have been planned, designed, translated, implemented, reflected on, updated and mutually adjusted systematically through LS to ensure consistency in transforming District reform vision into classroom practice. Different models of teaching-research community building were found in sampled project schools and professional expertise was built with district support to promote reform. The curriculum leadership development through LS has shaped reform leader schools and formed a collection of LS exemplars circulated in schools as high-quality curriculum packages, which laid the foundation for district-wide reform.

The innovative practice of LS in China's education reform has expanded its reach from within one classroom to the entire district curriculum system and made it an important tool to drive large-school district-based education reform.

This paper aims to explore the adsorption kinetics of syringin from Syringa oblata Lindl. leaves on macroporous resin and develop an efficient, simple and recyclable technology for the separation and purification of syringin.

Static adsorption and desorption properties of six resins were tested to select a suitable resin for the purification of syringin. Langmuir and Freundlich isotherm models were used to estimate the adsorption behavior of syringin on AB-8 resin. Breakthrough point and eluent volume were determined by dynamic adsorption and desorption tests. High-performance liquid chromatography-electrospray ionization-mass spectrometry was applied to identify the syringin in the purified product [syringin product (SP)]. Antioxidant and antibacterial activities of SP in vitro were evaluated by free radical scavenging ability and biofilm formation inhibitory tests.

AB-8 exhibited the most suitable adsorption and desorption capacity. Adsorption isotherm parameters indicated favorable adsorption between AB-8 and syringin. The optimal results were as follows: for adsorption, the sample concentration was 1.85 mg/mL, the sample volume was 3.5 bed volume (BV), the flow rate was 0.5 mL/min; for desorption, the ethanol concentration was 70%, the elution volume was 2.5 BV, the elution velocity was 1.0 mL/min. SP with 80.28% syringin displayed the potent antioxidant activities and inhibitory effects on biofilm formation of Streptococcus suis.

To the best of authors’ knowledge, there are no reports on purifying syringin from Syringa oblata Lindl. leaves using macroporous resins. This paper may also provide a theoretical reference for the purification of other phenylpropanoid glucosides.

What kind of robotic service do customers prefer when they dine out alone? This study aims to investigate how robotic service type affects solo diners’ attitude toward robotic service and restaurant revisit intention, through the mediation of rapport. It also examines the moderating effects of the need to belong and restaurant type.

Three experiments were conducted. Study 1 used a one-factor between-subjects design to test the effect of robotic service type on rapport and solo diners’ responses. Study 2 conducted a 2 (robotic service type: service-delivery vs entertainment) × need to belong quasi-experimental design to examine the moderation of need to belong. Study 3 used a 2 (robotic service type: service-delivery vs entertainment) × 2 (restaurant type: traditional restaurant vs solo-friendly restaurant) factorial between-subjects design to test the moderation of restaurant type. A qualitative study (Study 4) complements the experimental results based on semistructured interviews.

Entertainment (vs service-delivery) robotic service has a stronger effect on solo diners’ responses, with rapport serving as a mediator. Additionally, solo diners with a heightened need to belong demonstrate an intensified rapport effect when receiving entertainment-oriented robotic service. Furthermore, restaurant type plays a moderating role between robotic service type and consumer responses. For traditional restaurants, solo diners who receive entertainment (vs service-delivery) robotic service tend to form stronger rapport and favorable responses. The results of the qualitative study elucidate and support the hypothesized relationships of the experimental studies.

Restaurant operators could consider offering entertainment-based smart devices that allow solo diners to indulge themselves during the dining encounter. Restaurants could also design environmental cues that can signify a sense of comfort, such as redesigning tables with individual seats for solo diners to enhance their perceptions of shared characteristics among other solo diners in the same space.

This research advances the literature on solo dining and robotic service, by investigating how human–robot interaction can fulfill solo diners’ relatedness goals, as self-determination theory suggests. This inquiry also represents an early attempt in the hospitality literature to empirically examine the influence of robotic service type on consumer responses through the mediation of rapport.

Have you been to a smart restaurant, and how were its services? A common limitation of hospitality studies stems from the lack of research on how service quality is shaped within smart technology. This study aims to fill this literature void not merely to reiterate the importance of technology but also to recast service quality through the lens of information technology. It synthesizes the 5-S model of smart service quality (AKA SSQ) as a new conceptualization of service quality application in smart hospitality contexts such as smart restaurants.

This study undertook a qualitative research design based on theoretical synthesis from service quality, information technology and attention restoration. Drawing from online review comments and semistructured interviews from smart restaurants, the authors improvised the SSQ model to identify the essence of smart service in smart dining establishments.

“5-S” reflects an extension of the literature to denote a new SSQ abstraction pertinent to s-servicescape, s-assurance, s-responsiveness, s-reliability and s-empathy. A nomological network was posited to better understand the importance of smart design and consequence of SSQ.

The emergence of smart dining gives rise to smart restaurants, which puts technology at center stage. As consumers are becoming increasingly comfortable with self-service technology, auto-payment and ordering systems and robotic services, technology in foodservice will continue to play an essential role to better serve diners. Geared with advanced innovations and intelligent devices, smart restaurants are now more than mere eateries. It is a trend and a lifestyle.

This novel SSQ concept adds new nuances to the literature by acknowledging the technological essence in today’s hospitality industry. By integrating smart technology into the service quality paradigm, the authors are able to observe several interesting behaviors exhibited during smart dining, including tech-induced restoration, which opens a new avenue to understand how attention restoration could be attained through immersion in a technologically advanced setting. By synthesizing theoretical essence from service quality, attention restoration and information technology, the authors are able to create a new dialog that should warrant a forum of discussion in future studies.