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In response to the severe lag in tracking the response of the Stewart stability platform after adding overload, as well as the impact of nonlinear factors such as load and friction on stability accuracy, a new error attenuation function and a parallel stable platform active disturbance rejection control (ADRC) strategy combining cascade extended state observer (ESO) are proposed.

First, through kinematic modeling of the Stewart platform, the relationship between the desired pose and the control quantities of the six hydraulic cylinders is obtained. Then, a linear nonlinear disturbance observer was established to observe noise and load, to enhance the system’s anti-interference ability. Finally, verification was conducted through simulation.

Finally, stability analysis was conducted on the cascaded observer. Experiments were carried out on a parallel stable platform with six degrees of freedom involving rotation and translation. In comparison to traditional PID and ADRC control methods, the proposed control strategy not only endows the stable platform with strong antiload disturbance capability but also exhibits faster response speed and higher stability accuracy.

A new error attenuation function is designed to address the lack of smoothness at d in the error attenuation function of the ADRC controller, reducing the system ripple caused by it. Finally, a combination of linear and nonlinear ESOs is introduced to enhance the system's response speed and its ability to observe noise and load disturbances. Stability analysis of the cascade observer is carried out, and experiments are conducted on a six-degree-of-freedom parallel stable platform with both rotational and translational motion.

This systematic review synthesizes the recent literature (2010–2020) on hospitality employees’ emotions, affect and moods. This study has three objectives: to clarify the definitions of emotions, affect and moods; to explain how theories are integrated into understanding hospitality employees’ emotions, affect and moods; and to assess how emotions, affect and moods are measured.

Using seven major databases, the authors selected 61 peer-reviewed academic journal articles published in hospitality outlets for review. We based our study on five stages of conducting a systematic review: scoping, planning, identification, screening and eligibility.

Affect is an umbrella term encompassing moods and emotions. Emotions are distinct from emotion-laden constructs, such as emotional labor and emotional intelligence. Theories on conservation of resources, emotional labor and social exchange have been most frequently used to understand hospitality employees’ emotions. However, they overlooked the dynamic nature of emotions when using these theories. Hospitality researchers often used a subset of the positive and negative affect scale and did not discuss back-translation.

Hospitality employees’ emotions lead to far-reaching consequences in attitudes, intentions and behaviors in work and non-work domains. Effective practices (e.g. creating a supportive climate) that help evoke positive employee emotions and reduce negative employee emotions are thus desirable.

Our findings crystallize the understanding of emotions, affect and moods of hospitality employees. We further provide a roadmap for future research on hospitality employees’ emotions. Data triangulation, cross-cultural research and mixed emotions are novel opportunities for future research.

The purpose of this paper is to integrate tenets from the appraisal-based model of self-conscious emotions and the compass of shame theory to examine restaurant frontline employees’ experience of shame following service failures, and how shame influences employees’ job attitude and behaviors. In addition, employees’ industry tenure is identified as an individual factor influencing the impacts of shame in resorting to literature on aging in emotion regulation.

Using a survey methodology, 217 restaurant frontline employees and their supervisors in Turkey provided survey data. Partial least squares (PLS) method using SmartPLS 3.3.3 was used for data analysis.

The results indicated the maladaptive nature of shame following service failures as a salient self-conscious emotion, as it was negatively related to employee outcomes. Moreover, employees’ industry tenure played a moderating role that influences the impacts of shame on commitment to customer service.

Managers should attend to frontline employees’ shame experience depending on their industry experience and adopt appropriate emotion intervention (e.g. cognitive reappraisal) or create error management culture to eliminate the negative effects of shame.

This study advances our understanding of a powerful but understudied emotional experience, shame, in a typical shame-eliciting hospitality work setting (e.g. service failures). Shame has been linked with commitment to customer service and error reporting. In addition, industry tenure has been identified as a boundary condition to help clarify previous inconsistent findings in regard to the adaptive/maladaptive nature of shame.

This paper aims to understand the influences of tris (2-hydroxyethyl) isocyanurate oleate and oleic acid tris (2-hydroxyethyl) isocyanurate phosphate ester on biodegradability and tribological performances of mineral lubricating oil.

Tris (2-hydroxyethyl) isocyanurate oleate and oleic acid tris (2-hydroxyethyl) isocyanurate phosphate ester were prepared and characterized by Fourier transform infrared spectrometer. The biodegradability and tribological properties of neat oil and its formulations were studied on a tester for fast evaluating biodegradability of lubricants and a four-ball tester, respectively. The worn surfaces were investigated by scanning electron microscope and X-ray photoelectron spectroscope.

Tris (2-hydroxyethyl) isocyanurate oleate and oleic acid tris (2-hydroxyethyl) isocyanurate phosphate ester both improved markedly the biodegradability, the anti-wear properties, friction-reducing properties and extreme pressure properties of base oil. The effect of oleic acid tris (2-hydroxyethyl) isocyanurate phosphate ester was better than tris (2-hydroxyethyl) isocyanurate oleate. The improvement of tribological performances was mainly ascribed to the formation of a complicated boundary lubrication film of tris (2-hydroxyethyl) isocyanurate oleate and oleic acid tris (2-hydroxyethyl) isocyanurate phosphate ester on the friction surfaces.

This paper has indicated that tris (2-hydroxyethyl) isocyanurate oleate and oleic acid tris (2-hydroxyethyl) isocyanurate phosphate ester effectively improve the biodegradability and tribological performances of mineral lubricating oil. Promoting biodegradation of mineral lubricant by additives is very significant for the development of petroleum-based biodegradable lubricants. These two additives not merely improve the tribological performances; more importantly, they improve the ecological performances.

Considerable research has examined the negative consequences of customer incivility on employees (e.g. turnover intention and sabotage behavior toward the customer). However, there is scant research investigating how other customers, as observers, may react to incivility. This knowledge gap should be filled because hospitality services are often consumed in the public setting where customers can observe and be influenced by each other. The purpose of this study is to fill this gap by examining observing customers’ willingness to revisit the company following customer incivility.

Participants are American consumers recruited from a crowdsourced online panel. Two scenario-based experimental studies in the restaurant setting are conducted. Customer incivility and relationship norms (communal versus exchange) are manipulated, while relationship closeness is measured.

Study 1 shows that following fellow customer incivility (vs civility), observing customers’ intention to revisit the company was lower when they perceive a distant relationship with the employee. This intention did not differ regardless of incivility and civility when they perceive a close relationship with the employee. Study 2 shows that when observing customers perceive a communal relationship with the employee, their revisit intention was even higher following customer incivility (vs civility).

Hospitality managers need to train employees to identify signs of customer incivility and assume appropriate actions to reduce the negative consequences on observers. Hospitality managers should also communicate their expectations for respectful customer behaviors through an organization-wide campaign. Finally, hospitality businesses should foster a close relationship with their customers, particularly a communal relationship to offset the negative consequences of customer incivility on observers.

This study adds to previous research by challenging the universally negative view of customer incivility. The authors do so by examining the moderating effects of relationship closeness and norms in observer reactions to customer incivility. This study contributes to previous research drawing on script theory and deontic justice theory.

Smartphone multitasking behavior has become prevalent in our daily lives, yet factors influencing smartphone multitasking behavior have not been fully investigated. This study aimed to examine the roles of a set of demographic, personality and motivational factors on smartphone multitasking behavior, and how these factors were related to general and application-specific types of smartphone multitasking behavior.

A cross-sectional study was conducted in which 2,659 smartphone users were invited to complete an online survey on smartphone multitasking behavior. Hierarchical multiple regression analyses were used to examine the roles of demographic, personality and motivational factors on smartphone multitasking behavior.

The results showed that, in general, demographic factors, such as gender, age, occupation status, education and smartphone usage time significantly predicted smartphone multitasking behavior. People characterized by agreeableness, extraversion, neuroticism and openness to experience were more likely to multitask with smartphones. Information seeking, efficiency and habit motivations were identified as major motivational factors for smartphone multitasking behavior. The roles of demographic, personality and motivational factors differed much across varied types of application-specific smartphone multitasking behavior.

This study extends and advances the literature on media multitasking, smartphone multitasking in particular, by identifying a set of demographic, personality and motivational factors as antecedents of smartphone multitasking behavior. In addition, this study revealed the differentiated roles of the above-mentioned factors across varied types of smartphone application usages. The findings provide important implications for practitioners to tailor smartphone applications and services to different target smartphone users and use situations.

Synthetic aperture radar (SAR) imaging is the most computational intensive algorithm and this makes its implementation challenging for real-time application. This paper aims to present the chirp-scaling algorithm (CSA) for real-time SAR applications, using advanced field programmable gate array (FPGA) processor.

A chirp signal is generated and compressed using range Doppler algorithm in MATAB for validation. Fast Fourier transform (FFT) and multiplication operations with complex data types are the major units requiring heavy computation. Therefore, hardware acceleration is proposed and implemented on NEON-FPGA processor using NE10 and CEPHES library.

The heuristic analysis of the algorithm using timing analysis and resource usage is presented. It has been observed that FFT execution time is reduced by 61% by boosting the performance of the algorithm and speed of multiplication operation has been doubled because of the optimization.

Very few literatures have presented the FPGA-based SAR imaging implementation, where analysis of windowing technique was a major interest. This is a unique approach to implement the SAR CSA using a hybrid approach of hardware–software integration on Zynq FPGA. The timing analysis propagates that it is suitable to use this model for real-time SAR applications.

The purpose of this study is to investigate consumers' emotional responses to artificial intelligence (AI) defeating people. Meanwhile, the authors investigate the negative spillover effect of AI defeating people on consumers' attitudes toward AI companies. The authors also try to alleviate this spillover effect.

Using four studies to test the hypotheses. In Study 1, the authors use the fine-tuned Bidirectional Encoder Representations from the Transformers algorithm to run a sentiment analysis to investigate how AI defeating people influences consumers' emotions. In Studies 2 to 4, the authors test the effect of AI defeating people on consumers' attitudes, the mediating effect of negative emotions and the moderating effect of different intentions.

The authors find that AI defeating people increases consumers' negative emotions. In terms of downstream consequences, AI defeating people induces a spillover effect on consumers' unfavorable attitudes toward AI companies. Emphasizing the intention of helping people can effectively mitigate this negative spillover effect.

The authors' findings remind governments, policymakers and AI companies to pay attention to the negative effect of AI defeating people and take reasonable steps to alleviate this negative effect. The authors help consumers rationally understand this phenomenon and correctly control and reduce unnecessary negative emotions in the AI era.

This paper is the first study to examine the adverse effects of AI defeating humans. The authors contribute to research on the dark side of AI, the outcomes of competition matches and the method to analyze emotions in user-generated content (UGC).