Mu He, Jiahui Lu, Juliet Honglei Chen and Kwok Kit Tong
This study aimed to investigate the relationship between spirituality, including religious spirituality (i.e. supernatural beliefs) and secular spirituality (i.e. social beliefs)…
Abstract
Purpose
This study aimed to investigate the relationship between spirituality, including religious spirituality (i.e. supernatural beliefs) and secular spirituality (i.e. social beliefs), and mental health among police trainees.
Design/methodology/approach
Participants in this study were police trainees of a police academy. An online survey was conducted to measure spirituality and mental health among these police trainees. The association between spirituality and mental health was analyzed using hierarchical linear regression and hierarchical logistic regression with demographic variables (i.e. gender and age) controlled for.
Findings
The results revealed that the police trainees with stronger secular spirituality tended to have better general mental health. Higher levels of secular spirituality were significantly associated with lower levels of mental illness risk and suicidal ideation. By contrast, religious spirituality was not significantly related to police trainees' mental health.
Originality/value
The present study is the first to empirically investigate the relationship between spirituality and mental health among police trainees. The findings may be enlightening for future research on the mental health of police officers and trainees, and provide novel perspectives and pragmatic implications for the development of spirituality-based prevention strategies and intervention programs for enhancing the mental health and well-being of the police.
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Qinghua Liu, Lu Sun, Alain Kornhauser, Jiahui Sun and Nick Sangwa
To realize classification of different pavements, a road roughness acquisition system design and an improved restricted Boltzmann machine deep neural network algorithm based on…
Abstract
Purpose
To realize classification of different pavements, a road roughness acquisition system design and an improved restricted Boltzmann machine deep neural network algorithm based on Adaboost Backward Propagation algorithm for road roughness detection is presented in this paper. The developed measurement system, including hardware designs and algorithm for software, constitutes an independent system which is low-cost, convenient for installation and small.
Design/methodology/approach
The inputs of restricted Boltzmann machine deep neural network are the vehicle vertical acceleration power spectrum and the pitch acceleration power spectrum, which is calculated using ADAMS finite element software. Adaboost Backward Propagation algorithm is used in each restricted Boltzmann machine deep neural network classification model for fine-tuning given its performance of global searching. The algorithm is first applied to road spectrum detection and experiments indicate that the algorithm is suitable for detecting pavement roughness.
Findings
The detection rate of RBM deep neural network algorithm based on Adaboost Backward Propagation is up to 96 per cent, and the false positive rate is below 3.34 per cent. These indices are both better than the other supervised algorithms, which also performs better in extracting the intrinsic characteristics of data, and therefore improves the classification accuracy and classification quality. Additionally, the classification performance is optimized. The experimental results show that the algorithm can improve performance of restricted Boltzmann machine deep neural networks. The system can be used for detecting pavement roughness.
Originality/value
This paper presents an improved restricted Boltzmann machine deep neural network algorithm based on Adaboost Backward Propagation for identifying the road roughness. Through the restricted Boltzmann machine, it completes pre-training and initializing sample weights. The entire neural network is fine-tuned through the Adaboost Backward Propagation algorithm, verifying the validity of the algorithm on the MNIST data set. A quarter vehicle model is used as the foundation, and the vertical acceleration spectrum of the vehicle center of mass and pitch acceleration spectrum were obtained by simulation in ADAMS as the input samples. The experimental results show that the improved algorithm has better optimization ability, improves the detection rate and can detect the road roughness more effectively.
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Xin Feng, Xu Wang and Mengxia Qi
In the era of the digital economy, higher demands are placed on versatile talents, and the cultivation of students with innovative and entrepreneurial abilities has become an…
Abstract
Purpose
In the era of the digital economy, higher demands are placed on versatile talents, and the cultivation of students with innovative and entrepreneurial abilities has become an important issue for the further development of higher education, thus leading to extensive and in-depth research by many scholars. The study summarizes the characteristics and patterns of dual-innovation education at different stages of development, hoping to provide a systematic model for the development of dual-innovation education in China and make up for the shortcomings.
Design/methodology/approach
This paper uses Citespace software to visualize and analyze the relevant literature in CNKI and Web of Science databases from a bibliometric perspective, focusing on quantitative analysis in terms of article trends, topic clustering, keyword co-linear networks and topic time evolution, etc., to summarize and sort out the development of innovation and entrepreneurship education research at home and abroad.
Findings
The study found that the external characteristics of the literature published in the field of bi-innovation education in China and abroad are slightly different, mainly in that foreign publishers are more closely connected and have formed a more stable ecosystem. In terms of research hotspots, China is still in a critical period of reforming its curriculum and teaching model, and research on the integration of specialization and creative education is in full swing, while foreign countries focus more on the cultivation of students' entrepreneurial awareness and the enhancement of individual effectiveness. In terms of cutting-edge analysis, the main research directions in China are “creative education”, “new engineering”, “integration of industry and education” and “rural revitalization”.
Originality/value
Innovation and entrepreneurship education in China is still in its infancy, and most of the studies lack an overall overview and comparison of foreign studies. Based on the econometric analysis of domestic and foreign literature, this paper proposes a path for domestic innovation and entrepreneurship education reform that can make China's future education reform more effective.
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Weihua Liu, Jiahui Zhang and Siyu Wang
This study explores the influencing factors affecting smart supply chain innovation (SSCI) performance of commodity distribution enterprises, and proposes the corresponding…
Abstract
Purpose
This study explores the influencing factors affecting smart supply chain innovation (SSCI) performance of commodity distribution enterprises, and proposes the corresponding framework from the perspective of the application of technology to improve the SSCI performance and make up the research gap in this field.
Design/methodology/approach
A multi-case study method is adopted in this study. Four distribution commodity distribution enterprises A, B, C and D in China are chosen as case enterprises. The interviews with senior management team members are used to collect data. The combination of open coding and axial coding are used to process the data. By testing the reliability and validity, the theoretical framework is summarized.
Findings
First, we find that the technology application cost inhibits SSCI and that the level of technology suitable for enterprise development will promote SSCI. Second, SSCI in structure, management and services can improve the performance and innovation ability of enterprises. Third, the quality of multi-channel integration and degree of customization around customer demand can significantly modify the above effects.
Originality/value
Compared with previous studies, this study reveals for the first time the correlation between the SSCI performance and technology application, SSCI in structure, management and service, providing new ideas for relevant researches on SSCI, and providing new theoretical support for managers' decision-making related to SSCI.
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Minghui Pu, Bin Xue, Hu Lin, Haobin Feng, Jiale Fan and Jiahui Chen
Capacitive six-axis force/torque (F/T) sensors require various configurations to fulfill diverse performance requirements; however, a systematic method to assess the feasibility…
Abstract
Purpose
Capacitive six-axis force/torque (F/T) sensors require various configurations to fulfill diverse performance requirements; however, a systematic method to assess the feasibility of any new configuration is lacking. This study aims to propose three criteria for evaluating the rationality of these configurations, enabling a quick determination of the feasibility of the initial structure of the sensor.
Design/methodology/approach
This study used sensitivity isotropy as a performance metric. By examining the signal conversion process from F/T to displacement using the compliance transformation matrix, the authors identified Criterion 1: the symmetry condition. By analyzing the decoupling process of the sensor, the authors discovered Criterion 2: the capacitor arrangement condition. Through the optimization of analog sensors, this study derived Criterion 3: the range and structural parameters conditions. Ultimately, this study designed and fabricated a sensor that fulfills these criteria, thereby demonstrating the feasibility of the approach through its performance.
Findings
By analogy with capacitive six-axis F/T sensors that have demonstrated exceptional performance in recent years, the authors have found that they all meet the criteria proposed in this paper. Furthermore, the sensor designed and fabricated in this study achieves an accuracy of 0.64% FS, surpassing both the accuracy and sensitivity of the commercially available high-performance ATI industrial automation (Gamma) sensor. This underscores the feasibility of this study’s criteria.
Originality/value
By following the configuration guidelines presented in this paper, designers can quickly assess whether a new configuration will perform well at the early stages of the design process. This makes it easier to consider other requirements while meeting the basic performance needs, thereby significantly enhancing design efficiency.
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Abstract
Purpose
Sandwich structures with well-designed cellular cores exhibit superior shock resistance compared to monolithic structures of equal mass. This study aims to develop a comprehensive analytical model for predicting the dynamic response of cellular-core sandwich structures subjected to shock loading and investigate their application in protective design.
Design/methodology/approach
First, an analytical model of a clamped sandwich beam for over-span shock loading was developed. In this model, the incident shock-wave reflection was considered, the clamped face sheets were simplified using two single-degree-of-freedom (SDOF) systems, the core was idealized using the rigid-perfectly-plastic-locking (RPPL) model in the thickness direction and simplified as an SDOF system in the span direction. The model was then evaluated using existing analytical models before being employed to design the sandwich-beam configurations for two typical engineering applications.
Findings
The model effectively predicted the dynamic response of sandwich panels, especially when the shock-loading pulse shape was considered. The optimal compressive cellular-core strength increased with increasing peak pressure and shock-loading impulse. Neglecting the core tensile strength could result in an overestimation of the optimal compressive cellular-core strength.
Originality/value
A new model was proposed and employed to optimally design clamped cellular-core sandwich-beam configurations subjected to shock loading.
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Sawsan Taha, Abdoulaye Kaba and Marzouq Ayed Al-Qeed
This study aims to investigate whether students would accept augmented reality technology in Al Ain University (AAU) libraries as part of digital library services.
Abstract
Purpose
This study aims to investigate whether students would accept augmented reality technology in Al Ain University (AAU) libraries as part of digital library services.
Design/methodology/approach
This study used a modified technology acceptance model–based survey instrument for data collection. Data was collected through an online questionnaire, which was sent to 400 students via email in March 2023. Out of the total participants, 176 students completed the questionnaire.
Findings
This study found that AAU students have a positive perception of augmented technology use in the library. They believe that augmented technology will be useful and easy to use, and students are willing to use it to access library resources and services.
Originality/value
This study contributes to the digital library perspectives in academic libraries.
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Thanh-Tho Quan, Duc-Trung Mai and Thanh-Duy Tran
This paper proposes an approach to identify categorical influencers (i.e. influencers is the person who is active in the targeted categories) in social media channels. Categorical…
Abstract
Purpose
This paper proposes an approach to identify categorical influencers (i.e. influencers is the person who is active in the targeted categories) in social media channels. Categorical influencers are important for media marketing but to automatically detect them remains a challenge.
Design/methodology/approach
We deployed the emerging deep learning approaches. Precisely, we used word embedding to encode semantic information of words occurring in the common microtext of social media and used variational autoencoder (VAE) to approximate the topic modeling process, through which the active categories of influencers are automatically detected. We developed a system known as Categorical Influencer Detection (CID) to realize those ideas.
Findings
The approach of using VAE to simulate the Latent Dirichlet Allocation (LDA) process can effectively handle the task of topic modeling on the vast dataset of microtext on social media channels.
Research limitations/implications
This work has two major contributions. The first one is the detection of topics on microtexts using deep learning approach. The second is the identification of categorical influencers in social media.
Practical implications
This work can help brands to do digital marketing on social media effectively by approaching appropriate influencers. A real case study is given to illustrate it.
Originality/value
In this paper, we discuss an approach to automatically identify the active categories of influencers by performing topic detection from the microtext related to the influencers in social media channels. To do so, we use deep learning to approximate the topic modeling process of the conventional approaches (such as LDA).
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Yixin Zhang, Lizhen Cui, Wei He, Xudong Lu and Shipeng Wang
The behavioral decision-making of digital-self is one of the important research contents of the network of crowd intelligence. The factors and mechanisms that affect…
Abstract
Purpose
The behavioral decision-making of digital-self is one of the important research contents of the network of crowd intelligence. The factors and mechanisms that affect decision-making have attracted the attention of many researchers. Among the factors that influence decision-making, the mind of digital-self plays an important role. Exploring the influence mechanism of digital-selfs’ mind on decision-making is helpful to understand the behaviors of the crowd intelligence network and improve the transaction efficiency in the network of CrowdIntell.
Design/methodology/approach
In this paper, the authors use behavioral pattern perception layer, multi-aspect perception layer and memory network enhancement layer to adaptively explore the mind of a digital-self and generate the mental representation of a digital-self from three aspects including external behavior, multi-aspect factors of the mind and memory units. The authors use the mental representations to assist behavioral decision-making.
Findings
The evaluation in real-world open data sets shows that the proposed method can model the mind and verify the influence of the mind on the behavioral decisions, and its performance is better than the universal baseline methods for modeling user interest.
Originality/value
In general, the authors use the behaviors of the digital-self to mine and explore its mind, which is used to assist the digital-self to make decisions and promote the transaction in the network of CrowdIntell. This work is one of the early attempts, which uses neural networks to model the mental representation of digital-self.
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The purpose of this paper is to examine the relationship between team heterogeneity and team performance in entrepreneurial team and is also of significance in guiding the…
Abstract
Purpose
The purpose of this paper is to examine the relationship between team heterogeneity and team performance in entrepreneurial team and is also of significance in guiding the management practice of an entrepreneurial team.
Design/methodology/approach
The study is carried out based on an experiment, in which a 2×2 experimental group is devised to collect data concerned with the heterogeneity of entrepreneurial team’s expertise and the attitude toward heterogeneity.
Findings
The entrepreneurial team’s heterogeneity has a significant effect on entrepreneurial performance; the entrepreneurial team’s heterogeneity influences entrepreneurial performance through team task conflict; attitudes toward heterogeneity play a mediating role in the above process.
Originality/value
This paper is carried out based on an experiment which can be used to determine the mediating effects of team conflict on the relationship between team expertise heterogeneity and the entrepreneurial performance.