Search results

To enhance the performance of hydrostatic bearings, graphene serves as a lubricant additive. Using the high thermal conductivity of graphene, the purpose of this study is to focus on the impact of graphene nano-lubricating oil hydrostatic bearing temperature rise at various speeds and eccentricities.

The thermal conductivity of graphene nano-lubricating oil was calculated by molecular dynamics method and based on the viscosity–temperature effect, the coupled heat transfer finite element model of hydrostatic bearing was established; temperature rise of pure lubricating oil and graphene nano-lubricating oil hydrostatic bearing were analysed at different speed and eccentricity based on computational fluid dynamics method.

With the increase of speed and eccentricity, the temperature rise of 0.2% graphene nano-lubricating oil bearings is lower than that of pure lubricating oil bearings; in addition with the increase of graphene mass fraction, the temperature rise of graphene nano-lubricating oil bearings is always higher than that of pure lubricating oil bearings, and the higher the speed, the more obvious the phenomenon.

The effects of graphene as a lubricant additive on the thermal conductivity of nano-lubricating oil and the variation of the temperature rise of graphene nano-lubricating oil bearings compared to pure lubricating oil bearings were analysed by combining micro and macro methods.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2023-0388

The set-union knapsack problem is one of the most significant generalizations of the Non-deterministic Polynomial (NP)-hard 0-1 knapsack problem in combinatorial optimization, which has rich application scenarios. Although some researchers performed effective algorithms on normal-sized instances, the authors found these methods deteriorated rapidly as the scale became larger. Therefore, the authors design an efficient yet effective algorithm to solve this large-scale optimization problem, making it applicable to real-world cases under the era of big data.

The authors develop three targeted strategies and adjust them into the adaptive tabu search framework. Specifically, the dynamic item scoring tries to select proper items into the knapsack dynamically to enhance the intensification, while the age-guided perturbation places more emphasis on the diversification of the algorithm. The lightweight neighborhood updating simplifies the neighborhood operators to reduce the algorithm complexity distinctly as well as maintains potential solutions. The authors conduct comparative experiments against currently best solvers to show the performance of the proposed algorithm.

Statistical experiments show that the proposed algorithm can find 18 out of 24 better solutions than other algorithms. For the remaining six instances on which the competitor also achieves the same solutions, ours performs more stably due to its narrow gap between best and mean value. Besides, the convergence time is also verified efficiency against other algorithms.

The authors present the first implementation of heuristic algorithm for solving large-scale set-union knapsack problem and achieve the best results. Also, the authors provide the benchmarks on the website for the first time.

With the upgrade of natural language interaction technology, the simulation extension of intelligent voice assistants (IVAs) and the uncertainty of products and services have received more and more attention. However, most of the existing research focuses on investigating the application of theories to explain consumer behavior related to intention to use and adopt IVAs, while ignoring the impact of its privacy issues on consumer resistance. This article especially examines the negative impact of artificial intelligence-based IVAs’ privacy concerns on consumer resistance, and studies the mediating effect of perceived creepiness in the context of privacy cynicism and privacy paradox and the moderating effect of anthropomorphized roles of IVAs and perceived corporate social responsibility (CSR) of IVAs’ companies. The demographic variables are also included.

Based on the theory of human–computer interaction (HCI), this study addresses the consumer privacy concerns of IVAs, builds a model of the influence mechanism on consumer resistance, and then verifies the mediating effect of perceived creepiness and the moderating effect of anthropomorphized roles of IVAs and perceived CSR of IVAs companies. This research explores underlying mechanism with three experiments.

It turns out that consumers’ privacy concerns are related to their resistance to IVAs through perceived creepiness. The servant (vs. partner) anthropomorphized role of IVAs is likely to induce more privacy concerns and in turn higher resistance. At the same time, when the company’s CSR is perceived high, the impact of the concerns of IVAs’ privacy issues on consumer resistance will be weakened, and the intermediary mechanism of perceiving creepiness in HCI and anthropomorphism of new technology are further explained and verified. The differences between different age and gender are also revealed in the study.

The research conclusions have strategic reference significance for enterprises to build the design framework of IVAs and formulate the response strategy of IVAs’ privacy concerns. And it offers implications for researchers and closes the research gap of IVAs from the perspective of innovation resistance.

Online influencers are increasingly used by brands around the globe to establish brand communication. This study aims to investigate the characteristics of social media content in terms of presentation style and brand communication among online influencers in China. The authors identified how characteristics of social media posts influence young consumers’ engagement with the posts.

The authors analyzed 1,779 posts from the Sina Weibo accounts of ten top-ranked online influencers by combining traditional content analysis with Web data crawling of audience engagement with social media posts.

Online influencers in China more frequently used photos than videos to communicate with their social media audience. Altogether 8% and 6% of posts carried information about promotion and event, respectively. Posts with promotional incentives as well as event information were more likely to engage audiences. Altogether 22% of the sampled social media posts mentioned brands. Posts with brand information, however, were less likely to engage audiences. Furthermore, having long text is more effective than photos/images in generating likes from social media audiences.

Combining content analysis of social media posts and engagement analytics obtained via Web data crawling, this study is, to the best of the authors’ knowledge, one of the first empirical studies to analyze influencer marketing and young consumers’ reactions to social media in China.

The development of complex products and systems is a continuously iterative process from customer requirements to a mature design. Design changes derived from multisources occur frequently during the design process. Furthermore, change propagation will impose impacts on design costs and lead times. In view of this, how to predict and control the propagation of multisource design change to reduce the changes impact is an urgent issue in the development of complex product.

In this paper, a new four-phase routing approach based on weighted and directed complex networks is proposed for multisource design change propagation. Phase I: as the foundation of this research, a product network model is established to quantify describe the complex product. Phase II: the hub nodes are identified based on the LeaderRank algorithm, which can be regarded as multisource nodes of design changes. Phase III: a calculation method for change propagation intensity is proposed, which improves the systematicness and accuracy of the evaluation results. In this paper, change propagation intensity is defined by four assessment factors: importance degree of parts, execution time of design tasks, coupling strength between parts and propagation likelihood. Phase IV: a routing method of multisource design change propagation and ant colony optimization algorithm are proposed in this paper, which can solve the coupling conflicts among change propagation paths and improve the search efficiency by using the parallel search strategy.

The proposed method and another method are used to search the optimal propagation path of multisource design change of a motorcycle engine; the results indicate that this method designed in this study has a positive effect on reducing the change impact, market response time and product design costs when design change occurs in the products design process.

The authors find a new method (a network-based four-phase routing approach) to search the optimal propagation path of multisource design change in complex products design.

Artificial intelligence (AI) has a large number of applications at the industry and user levels. However, AI's uniqueness neglect is becoming an obstacle in the further application of AI. Based on the theory of innovation resistance, this paper aims to explore the effect of AI's uniqueness neglect on consumer resistance to AI.

The authors tested four hypothesis across four studies by conducting lab experiments. Study 1 used a questionnaire to verify the hypothesis that AI's uniqueness neglect leads to consumer resistance to AI; Studies 2 focused on the role of human–AI interaction trust as an underlying driver of resistance to medical AI. Study 3–4 provided process evidence by way of a measured moderator, testing whether participants with a greater sense of non-verbal human–AI communication are more reluctant to have consumer resistance to AI.

The authors found that AI's uniqueness neglect increased users' resistance to AI. This occurs because the uniqueness neglect of AI hinders the formation of interaction trust between users and AI. The study also found that increasing the gaze behavior of AI and increasing the physical distance in the interaction can alleviate the effect of AI's uniqueness neglect on consumer resistance to AI.

This paper explored the effect of AI's uniqueness neglect on consumer resistance to AI and uncovered human–AI interaction trust as a mediator for this effect and gaze behavior and physical distance as moderators for this effect.

The purpose of this study is to investigate the effect of nano ZrC particles on the mechanical and electrochemical corrosion properties of FeCrAl alloys, providing a beneficial reference basis for the development of high-performance carbide reinforced FeCrAl alloys with good mechanical and corrosion properties in the future.

Nano ZrC reinforced FeCrAl alloys were prepared by mechanical alloying and spark plasma sintering. Phases composition, tensile fractography, corrosion morphology and chemical composition of nano ZrC reinforced FeCrAl alloys were analyzed by X-ray diffraction, scanning electron microscopy and energy dispersive X-ray spectroscopy, respectively. Microhardness and tensile properties of nano ZrC reinforced FeCrAl alloys were investigated by mechanical testing machine and Vickers hardness tester. Electrochemical corrosion properties of nano ZrC reinforced FeCrAl alloys were investigated by electrochemical workstation in 3.5 wt.% NaCl solution.

The results showed that addition of nano ZrC can effectively improve the mechanical and corrosion properties. However, excessive nano ZrC could decrease the mechanical properties and reduce the corrosion resistance. In all the FeCrAl alloys, FeCrAl–0.6 wt.% ZrC alloy exhibits the optimum mechanical properties with an ultimate tensile strength, elongation and hardness of 990.7 MPa, 24.1% and 335.8 HV1, respectively, and FeCrAl–0.2 wt.% ZrC alloy has a lower corrosion potential (−0.179 V) and corrosion current density (2.099 µA/cm2) and larger pitting potential (0.497 V) than other FeCrAl–ZrC alloys, showing a better corrosion resistance.

Adding proper nano ZrC particles can effectively improve the mechanical and corrosion properties, while the excessive nano ZrC is harmful to the mechanical and corrosion properties of FeCrAl alloys, which provides an instruction to develop high-performance FeCrAl cladding materials.

The purpose of this study is to discover the uniqueness of China's online livestreaming industry and to make preliminary predictions about its future.

Providing a panoramic description of China's online livestreaming industry and a comparative analysis with other countries' online livestreaming industries.

China's online livestreaming industry is world leader in general. In terms of user size and age structure, although China has a high proportion of online livestreaming users, the proportion of anchors is not high, while the age structure of users in both China and other countries shows the characteristics of younger users. In terms of policy, the difference between China and foreign support in online livestreaming is small, but developed countries have stricter regulations.

The research in this paper has great significance in gaining an in-depth understanding of the development status and trends of China's online livestreaming industry and in designing accurate support policies.

This paper aims to address the problem of uncertain product quality in digital light processing (DLP) three-dimensional (3D) printing, a scheme is proposed to qualitatively estimate whether a layer is printed with the qualified quality or not cured .

A thermochromic pigment whose color fades at 45°C is prepared as the indicator and it is mixed with the resin. A visual surveillance framework is proposed to monitor the visual variation in a period of the entire curing process. The exposure region is divided into 30 × 30 sub-regions; gray-level variation curves (curing curves) in all sub-regions are classified as normal or abnormal and a corresponding printing control strategy is designed to improve the percentage of qualified printed objects.

The temperature variation caused by the releasing reaction heat on the exposure surface is consistent in different regions under the homogenized light intensity. The temperature in depth begins to rise at different times. The temperature in the regions near the light source rises earlier, and that far from the light source rises later. Thus, the color of resin mixed with the thermochromic pigment fades gradually over a period of the entire solidification process. The color variation in the regions with defects of bubbles, insufficient material filling, etc., is much different from that in the normal curing regions.

A temperature-sensitive organic chromatic chemical pigment is prepared to present the visual variation over a period of the entire curing process. A novel 3D printing scheme with visual surveillance is proposed to monitor the layer-wise curing quality and to timely stop the possible unqualified printing resulted from bubbles, insufficient material filling, etc.

Artificial intelligence (AI) is experiencing growth and prosperity worldwide because of its convenience and other benefits. However, AI faces challenges related to consumer resistance. Thus, drawing on the user resistance theory, this study explores factors that influence consumers’ resistance to AI and suggests ways to mitigate this negative influence.

This study tested four hypotheses across four studies by conducting lab experiments. Study 1 used a questionnaire to verify the hypothesis that AI’s “substitute” image leads to consumer resistance to AI; Study 2 focused on the role of perceived threat as an underlying driver of resistance to AI. Studies 3–4 provided process evidence by the way of a measured moderator, testing whether AI with servant communication style and literal language style is resisted less.

This study showed that AI’s “substitute” image increased users' resistance to AI. This occurs because the substitute image increases consumers’ perceived threat. The study also found that using servant communication and literal language styles in the interaction between AI and consumers can mitigate the negative effects of AI-substituted images.

This study reveals the mechanism of action between AI image and consumers’ resistance and sheds light on how to choose appropriate image and expression styles for AI products, which is important for lowering consumer resistance to AI.