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This paper aims to describe a method for efficient frequency domain model order reduction. The method attempts to combine the desirable attributes of Krylov reduction and proper orthogonal decomposition (POD) and is entitled Krylov enhanced POD (KPOD).

The KPOD method couples Krylov’s moment-matching property with POD’s data generalization ability to construct reduced models capable of maintaining accuracy over wide frequency ranges. The method is based on generating a sequence of state- and frequency-dependent Krylov subspaces and then applying POD to extract a single basis that generalizes the sequence of Krylov bases.

The frequency response of a pre-stressed microelectromechanical system resonator is used as an example to demonstrate KPOD’s ability in frequency domain model reduction, with KPOD exhibiting a 44 per cent efficiency improvement over POD.

The results indicate that KPOD greatly outperforms POD in accuracy and efficiency, making the proposed method a potential asset in the design of frequency-selective applications.

In the community of visual tracking or object tracking, discriminatively learned correlation filter (DCF) has gained more importance. When it comes to speed, DCF gives the best performance. The main objective of this study is to anticipate the object visually. For tracking the object visually, the authors proposed a new model based on the convolutional regression technique. Features like HOG & Harris are used for the process of feature extraction. The proposed method will give the best results when compared to other existing methods.

This paper introduces the concept and research status of tracks; later the authors focus on the representative applications of deep learning in visual tracking.

Better tracking algorithms are not mentioned in the existing method.

Visual tracking is the ability to control eye movements using the oculomotor system (vision and eye muscles working together). Visual tracking plays an important role when it comes to identifying an object and matching it with the database images. In visual tracking, deep learning has achieved great success.

The authors implement the multiple tracking methods, for better tracking purpose.

The main theme of this paper is to review the state-of-the-art tracking methods depending on deep learning. First, we introduce the visual tracking that is carried out manually, and secondly, we studied different existing methods of visual tracking based on deep learning. For every paper, we explained the analysis and drawbacks of that tracking method. This paper introduces the concept and research status of tracks, later we focus on the representative applications of deep learning in visual tracking.

The tribological behavior, i.e. friction coefficient and wear rate, and vibration characteristics of the water-lubricated bearing was investigated. The water-lubricated bearing is made of three different materials, i.e. polyether-ether-ketone (PEEK), polyimide (PI) and nitrile-butadiene rubber (NBR).

The tribological behavior was investigated experimentally on a specially designed test rig. Three vibration sensors were used to record the vibration of the bearing.

The results indicated that the variation of friction coefficient with rotation speed agrees well with the trend of Stribeck curve. The tested friction coefficient of rubber bearing is higher than that of the other two bearings whether it is in the state of mixed-lubrication or hydrodynamic lubrication, and which causing a larger wear rate in rubber bearing. The PEEK bearing exhibits the best tribological properties due to it has smaller friction coefficient and wear rate. However, it can be found that the rubber bearing gives the minimum vibration acceleration, which means that the rubber bearing has the most potential to improve the stability of water-lubricated bearing rotor system.

In this study, a group of experiment studies conducted on a specially designed test rig. The comprehensive performance, including friction coefficient, vibration acceleration and wear rate, of water-lubricated bearing with three different materials, i.e. PEEK, PI and NBR, was compared systematically. The experiment research may offer a reference for the selection of material in water-lubricated bearing in specific operating conditions.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2019-0447/

Based on the textual-analyzed data covering 2148 IPO firms in China’s stock market during the 2007–2018 period, the authors’ purpose is to examine the influence of anti-takeover provision (ATP) adoption on initial public offerings (IPO) underpricing and identify the reducing effect of the former.

The authors examine the sample consisting of Chinese A-share listed IPO firms between 2007 and 2018 from China Stock Market Accounting Research and Chinese Research Data Services, with ATP data collected from the IPO firm chapters. Specifically, the authors use text analysis to identify whether there are ATPs in the IPO firm chapters, as well as the number of ATPs. H1: IPO underpricing is less severe for firms adopting ATPs. H2: The effect of ATP adoption on IPO underpricing is more salient for firms in worse information environments.

The authors examine the influence of ATP adoption on IPO underpricing and identify the reducing effect of the former. This effect can be explained by the fact that adopting ATPs in IPO firm chapters can reduce information asymmetry to a large extent by helping external investors obtain more private information, which alleviates IPO underpricing. The authors also find that the reducing effect is more significant in the worsened information environment. Furthermore, the authors explore the influence of adopting ATPs on other IPO characteristics and find positive effects on IPO over-subscription, funds raised and trading activity and negative effects on listing fees.

This study mainly contributes to the literature from the following two aspects. First, the study enriches the literature about the influencing factors of IPO underpricing. Second, the study also enriches the literature about the economic consequences of ATP adoption. This study also has important policy implications. With the coming of the era of decentralized ownership in China’s capital market, ATP adoption has become more important and attracted more attention. Also, investors focus more on pricing efficiency. The findings in this paper provide a more comprehensive understanding of the relationship between ATP adoption and IPO underpricing.

This study aims to examine the factors influencing hotel employee satisfaction and explores the different sentiments expressed in these factors in online reviews by hotel type (premium versus economy) and employment status (current versus former).

A total of 78,535 online reviews by employees of 29 hotel companies for the period of 2011-2019 were scraped from Indeed.com. Structural topic modeling (STM) and sentiment analysis were used to extract topics influencing employee satisfaction and examine differences in sentiments in each topic.

Results showed that employees of premium hotels expressed more positive sentiments in their reviews than employees of economy hotels. The STM results demonstrated that 20 topics influenced employee satisfaction, the top three of which were workplace bullying and dirty work (18.01%), organizational support (16.29%) and career advancement (8.88%). The results indicated that the sentiments in each topic differed by employment status and hotel type.

Rather than relying on survey data to explore employee satisfaction, hotel industry practitioners can analyze employees’ online reviews to design action plans.

This study is one of only a few to use online reviews from an employment search engine to explore hotel employee satisfaction. This study found that workplace bullying and dirty work heavily influenced employee satisfaction. Moreover, analysis of the comments from previous employees identified antecedents of employees’ actual turnover behavior but not their turnover intention.

The purpose of the paper is to predict the erosion rate of the components of centrifugal pump under certain operating condition to identify the maximum erosion area and to discuss the factors affecting them. This helps to optimize design and estimate service life.

In the paper, the Eulerian–Lagrangian approach method coupled with the erosion model to investigate the mixed sand characteristics on erosion characteristics of centrifugal pump flow-through wall. The hydraulic performance and wear characteristics experiment of the pump is used to verify the accuracy of the numerical simulation.

The blade erosion area mainly occurs near the blade inlet and the trailing edge of the pressure surface, the main erosion area of the impeller back shroud is near the outlet of the flow passage and the main erosion area of the volute is near the tongue and the I section. With the change of the average diameter and density of sand particles, the average erosion rate on different flow-through walls is positively correlated with the average mass concentration to a certain extent. However, for different sand shape factors, there is little correlation between the average erosion rate and the average mass concentration. In addition, compared with other erosion areas, the increase of average sand particle diameter and density has the greatest impact on the total erosion rate of blade pressure surface, while the shape of sand particles has a greater impact on the total erosion rate of each flow-through wall of centrifugal pump.

In this work, according to the characteristics of the mixed distribution of different sand diameters in the Yellow River Basin, the erosion characteristics of centrifugal pumps used in the Yellow River Basin are studied. The numerical calculation method for predicting the wall erosion of centrifugal pump is established and compared with the experimental results. The results can provide reference for optimizing design and increasing service life.

When processing 11Cr-3Co-3W martensitic heat-resistant steel, the traditional pouring cooling method often appears large cutting force, high cutting temperature, serious tool wear and poor surface quality. This paper aims to use new cooling methods for processing this problem.

Different performance indicators such as cutting force, tool wear and surface quality were measured and analysed under different continuous milling times. The relationship between liquid nitrogen flow and cutting force and surface roughness was analysed and measured.

The results show that with the increase of liquid nitrogen flow, the cutting force decreases, especially the Fx component, which decreases by 10%. When the liquid nitrogen flow reaches 8 L/min, the effect of increasing the liquid nitrogen flow on reducing the cutting force becomes smaller. The cutting force reduced by up to 15%, and the tool life increased up to 20% using liquid nitrogen cryogenic cooling than in cutting liquids cooling. When minimal quantities of lubricant (MQL) was added, the cutting force was reduced by 23%, and the tool life increased by 25%. When the cutting speed increases from 100 m/min to 250 m/min, the cutting force with cutting liquid cooling does not change significantly while the cutting force with liquid nitrogen cooling decreases with the cutting speed increasing. It shows that liquid nitrogen cooling is more suitable for high-speed machining. After the cutting length reaches 66 m, the surface roughness of the workpiece using liquid nitrogen cooling method larger than that of the cutting liquid cooling method. When MQL is added into liquid nitrogen, the lubrication performance is improved, and the surface roughness of the workpiece is reduced about 8%.

Many studies had focused on the improvement of tool life and surface quality by different cooling methods, or on the injection process and chip mechanism. However, there are few relevant studies on the variation of cooling and lubrication properties with the change of cutting length in liquid nitrogen cryogenic processing. In this research, different performance indicators such as cutting force, tool wear and surface quality were measured and analysed under different continuous milling times. The relationship between liquid nitrogen flow and cutting force and surface roughness was analysed and measured.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2023-0053/

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.

This study aims to develop a new method to treat the numerical singularity at the critical nodes of two skew coordinates, and optimize the leakage of micro herringbone grooved journal bearings (MHGJBs) with this method.

A side leakage numerical algorithm is proposed by using the skew meshes with a virtual node (SMVN) method to evaluate the effects of groove angle, bank/groove ratio, groove depth and groove number on load capacity, friction and side leakage of MHGJB.

The SMVN method is effective in treating the numerical singularity at the critical nodes of two skew coordinates. Besides, a group of optimized parameters of micro herringbone groove is obtained which can not only minimize the side leakage but also improve the load capacity and friction force.

A virtual node method was proposed, which can significantly improve the calculation accuracy in the side leakage model.

With the increasing abundance of network resources and big data, multi-modal information search (MMIS) has been paid more and more attention, but the research results of MMIS are relatively few. This paper attempts to put forward constructive suggestions for the design of multi-modal information system, so that the system can have a better user experience, help users improve the efficiency of obtaining information and optimize the information service mode.

A research model of influencing factors is established by using the TAM (technology acceptance model) theory. The influencing factors of users' multi-modal information search behavior (MMISB) are analyzed by using questionnaire, experiment and the structural equation model. On the basis of this, some suggestions are put forward to build the multi-modal search (MMS) system and improve the efficiency of MMIS.

The research shows that users' MMISB is directly related to their search intention, and the search intention can influence users' cognition of the usefulness and ease of MMIS through their own information search ability and system characteristics. The user's MMIS ability is affected by the demand expression ability and retrieval ability cognition; the user's cognition of system characteristics is affected by the system function and information quality. This shows that the user's MMISB is closely related to the user's cognitive situation, but due to the author's limited time and research ability, only the questionnaire survey method cannot be used to in-depth research and explore the influencing factors of MMIS. Therefore, in the future research, we should combine the interview method to further track the user's emotional factors and scene factors.

For the first time, TAM theory is combined with cross-modal retrieval behavior and the paper explores the influencing factors and evaluation indexes of users' MMISB. The second, the questionnaire was compiled to investigate the influencing factors of the MMISB of the university group, and the reliability analysis, validity analysis, correlation analysis and structural equation model analysis of the survey data are carried out . The survey data and analysis results are original, which can provide a theoretical basis for improving the service level of MMIS.