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The high-efficient processing of mass data is a primary issue in building and maintaining security video surveillance system. This paper aims to focus on the architecture of security video surveillance system, which was based on Hadoop parallel processing technology in big data environment.

A hardware framework of security video surveillance network cascaded system (SVSNCS) was constructed on the basis of Internet of Things, network cascade technology and Hadoop platform. Then, the architecture model of SVSNCS was proposed using the Hadoop and big data processing platform.

Finally, we suggested the procedure of video processing according to the cascade network characteristics.

Our paper, which focused on the architecture of security video surveillance system in big data environment on the basis of Hadoop parallel processing technology, provided high-quality video surveillance services for security area.

The purpose of this paper is to contribute to the literature of blended learning by practically implementing best practices in employee training.

In response to the Covid-19 pandemic, an organization had modified its training procedures over the course of three years to improve employee and organizational outcomes. Employee candidates who were onboarded into sales positions during the years 2019–2021 were given the opportunity to learn the content in an online format and subsequently evaluated prior to their in-person training and final evaluation to provide them with a self-paced blended learning experience. Both evaluation scores, along with the length it took to complete the trainings, were used to determine the trainings effectiveness and efficiency respectively.

The findings for the study showed that the organization was successfully able to improve upon the efficiency of the training by reducing training length and the effectiveness by improving employee outcomes.

The study’s design was limited to the probation process, which resulted in issues drawing conclusions for employee outcomes that were relevant to their long-term organizational success. This emphasizes the importance of comprehensive investigations for future practical studies.

The findings allow for the improvement of blended learning models within real-world organizational contexts that provide organizations with the opportunity to improve employee outcomes while reducing time costs.

This study provides data from applied blended learning procedures that were validated using empirical findings, which contributes to the practicality of blended learning in workplace training.

To maintain the well integrity, the strength and sealing ability of premium connection should be in the safe scope. ISO 13679 is widely used for evaluating the ability of tubing and casing connection all over the world. FE is adopted to simulate the ISO 13679 tests.

Because of the disadvantage of experiment such as long period, high cost and high requirement on the facility, considering the convenience and universality of finite element method, as well as the contacting nonlinearity and material nonlinearity, three-dimensional finite element model of a certain type of premium connection is established with the consideration of helix angle. The loads exerted on the premium connection are the loads in series B test and thermal cycle test of ISO 13679. The distributions of Von Mises stress and contact pressure in various cases were studied.

The results showed that the bending load has a great influence on the distribution of Von Mises stress and contact pressure for premium connection. The Von Mises stress and contact pressures on the sealing surface are smaller on the tension side and greater on the compression side. With increasing axial compression load, the contact pressures on the tension side are too small, which may lead to sealing failure. The influence of temperature on the performance of premium connection cannot be ignored when choosing or designing premium connections. Both the Von Mises stress and contact pressure decrease slightly during a period of thermal cycle. Although the performance of the premium connection is good in a period of thermal cycle, its performance in a long period should be evaluated. Finite element simulation can effectively simulate the ISO 13679 test procedure and obtain the stress and contact pressure distribution. It can be used as a reference for evaluating the performance of premium connections.

Considering the convenience and universality of finite element method, as well as the contacting nonlinearity and material nonlinearity, three-dimensional finite element model of a certain type of premium connection is established with the consideration of helix angle.

Abundant studies of outpatient visits apply traditional recurrent neural network (RNN) approaches; more recent methods, such as the deep long short-term memory (DLSTM) model, have yet to be implemented in efforts to forecast key hospital data. Therefore, the current study aims to reports on an application of the DLSTM model to forecast multiple streams of healthcare data.

As the most advanced machine learning (ML) method, static and dynamic DLSTM models aim to forecast time-series data, such as daily patient visits. With a comparative analysis conducted in a high-level, urban Chinese hospital, this study tests the proposed DLSTM model against several widely used time-series analyses as reference models.

The empirical results show that the static DLSTM approach outperforms seasonal autoregressive integrated moving averages (SARIMA), single and multiple RNN, deep gated recurrent units (DGRU), traditional long short-term memory (LSTM) and dynamic DLSTM, with smaller mean absolute, root mean square, mean absolute percentage and root mean square percentage errors (RMSPE). In particular, static DLSTM outperforms all other models for predicting daily patient visits, the number of daily medical examinations and prescriptions.

With these results, hospitals can achieve more precise predictions of outpatient visits, medical examinations and prescriptions, which can inform hospitals' construction plans and increase the efficiency with which the hospitals manage relevant information.

To address a persistent gap in smart hospital and ML literature, this study offers evidence of the best forecasting models with a comparative analysis. The study extends predictive methods for forecasting patient visits, medical examinations and prescriptions and advances insights into smart hospitals by testing a state-of-the-art, deep learning neural network method.

Employee voice behavior is an important source of corporate competitiveness but employees often face difficulties in voicing their opinions. This research analyzes how authentic leadership may increase psychological safety perceived by employees, consequently encouraging employees to actively share their ideas. In addition, the authors explore the unique concept of Zhongyong thinking, a way of thinking that is common in cultures rooted in Confucianism. The authors analyze how Zhongyong thinking may affect the relationship between psychological safety and employee voice behavior.

For the empirical analysis of authentic leadership and employee voice behavior in the Chinese context, the authors distributed surveys to employees working in various different industries in various provinces in China. The authors distributed 250 surveys in total and 213 surveys were used for analyses.

The authors' empirical analyzes illustrate that authentic leadership increases employee voice behavior, partially mediated by psychological safety. The authors also analyzed how psychological safety's effect on employee voice behavior could be moderated by Zhongyong thinking. The results demonstrate that the effect of psychological safety on voice behavior is weaker when employees are capable of exercising Zhongyong thinking.

Zhongyong thinking is still a relatively new concept that has not been studied thoroughly, and to the authors' knowledge, Zhongyong thinking has never been studied as a moderator in the relationship between psychological safety and employee voice behavior.

Zhong-yong thinking is a code of conduct of the Chinese people. The purpose of this study is to explore the relationship among Zhong-yong thinking, social capital, knowledge sharing behavior, and employee survival ability.

Zhong-yong thinking including multi-thinking, integration and harmony, taking a case study of private enterprise in Guangxi of China. Based on the literature, the establishment of the theoretical model and hierarchical regression analysis are explored.

The multi-thinking, integration and harmony of Zhong-yong thinking have a significant positive effect on social capital and employee survival ability. In addition, employee survival ability is positively affected by social capital. Moreover, knowledge sharing behavior has a positive moderating between the multi-thinking dimension of Zhong-yong thinking and social capital, and the remaining dimensions have no moderating effect. Knowledge sharing behavior has no moderating effect on the relationship between social capital and employee survival ability.

Zhong-yong thinking and social capital are actively affecting employee survival ability. Therefore, companies need to work harder to improve their employees' Zhong-yong thinking and social capital.

The paper extends Zhong-yong thinking, social capital and employee survival ability literature to fill gaps in how China people require to both access employee survival ability. The policy value of the work is in suggesting ways to facilitate employee survival ability of China.

This study aims to analyse the current trends and set the future research agenda in employee-level innovative work behaviour (IWB) research.

A portfolio of 910 publications on IWB collected from the Scopus database was systematically analysed using different bibliometric techniques.

Based on the performance analysis and science mapping of innovative work behaviour research, the study identifies the most prolific sources of IWB publications and lists several future research directions.

This paper could serve as one-stop information that may facilitate transdisciplinary endeavours by assisting scholars and practitioners in identifying peer-recognised publications and scholarly communities.

Online learning becomes a trendy format for workplace training, particularly during the pandemic. This study aims to examine the effects of a technology-assisted self-adaptive training camp on employees’ learning process and acquired knowledge, and the relationship between employees’ knowledge gained and organisational growth.

The participants were 213 pharmaceutical representatives from a global pharmaceutical business in the Asia-Pacific branch who enrolled in a 21-day professional training camp. Their knowledge gained was calculated by pre-tests and post-test scores captured from an online training system. The company’s profits gained by employees were indicated by individuals’ quarter-over-quarter growth rates. Specifically, the authors applied a series of quantitative analyses to examine the relationship between employees’ knowledge gained, learning quality and organizational growth brought by individuals.

During the online training session, employees obtained increased professional knowledge significantly. The quality of employees’ learning process was a significant predictor of their learning outcomes. In addition, a positive correlation was found between the knowledge obtained by employees and the company’s quarterly growth rates. A followed-up regression analysis indicated that the greater knowledge improvement an individual achieved, the higher quarter-to-quarter growth rate brought by the individual to the organization.

The study provides educational insights for organisations to effectively train employees’ professional competency through online learning. The investigation on the 21-day camp shows that employees received higher-quality training, resulting in increased revenues and greater workplace flexibility. The findings have implications for supporting the integration of educational technology into workplace training to boost the competency development of employees.

The purpose of this paper is to summarize the progress in grey system research during 2000-2015, so as to present some important new concepts, models, methods and a new framework of grey system theory.

The new thinking, new models and new methods of grey system theory and their applications are presented in this paper. It includes algorithm rules of grey numbers based on the “kernel” and the degree of greyness of grey numbers, the concept of general grey numbers, the synthesis axiom of degree of greyness of grey numbers and their operations; the general form of buffer operators of grey sequence operators; the four basic models of grey model GM(1,1), such as even GM, original difference GM, even difference GM, discrete GM and the suitable sequence type of each basic model, and suitable range of most used grey forecasting models; the similarity degree of grey incidences, the closeness degree of grey incidences and the three-dimensional absolute degree of grey incidence of grey incidence analysis models; the grey cluster model based on center-point and end-point mixed triangular whitenization functions; the multi-attribute intelligent grey target decision model, the two stages decision model with grey synthetic measure of grey decision models; grey game models, grey input-output models of grey combined models; and the problems of robust stability for grey stochastic time-delay systems of neutral type, distributed-delay type and neutral distributed-delay type of grey control, etc. And the new framework of grey system theory is given as well.

The problems which remain for further studying are discussed at the end of each section. The reader could know the general picture of research and developing trend of grey system theory from this paper.

A lot of successful practical applications of the new models to solve various problems have been found in many different areas of natural science, social science and engineering, including spaceflight, civil aviation, information, metallurgy, machinery, petroleum, chemical industry, electrical power, electronics, light industries, energy resources, transportation, medicine, health, agriculture, forestry, geography, hydrology, seismology, meteorology, environment protection, architecture, behavioral science, management science, law, education, military science, etc. These practical applications have brought forward definite and noticeable social and economic benefits. It demonstrates a wide range of applicability of grey system theory, especially in the situation where the available information is incomplete and the collected data are inaccurate.

The reader is given a general picture of grey systems theory as a new model system and a new framework for studying problems where partial information is known; especially for uncertain systems with few data points and poor information. The problems remaining for further studying are identified at the end of each section.

The purpose of this paper is to summarize the advances in grey system theory research and various application achievements in science and engineering. At the same time, it commemorates the 40th anniversary of the birth of grey system theory and the 10th anniversary of Grey Systems–Theory and Application.

Firstly, the innovations of theoretical research in grey system theory were summarized and some of the widely recognized new results are briefly described. By searching and combing the research results of grey system theory in China national knowledge infrastructure (CNKI) database and Web of Science by Institute for Scientific Information (ISI), this paper shows the rapid development trend of grey system theory in the past 40 years, and the successful applications of grey system theory in the fields of social sciences, natural sciences and engineering technologies.

More than 227 thousands literature were found by input 10 phrases such as grey system, grey number and sequence operator etc. in CNKI database. After entering the new century, the number of grey system papers included in CNKI database is increasing rapidly. Since 2008, more than 10 thousands papers have been included per year and more than 15 thousands papers have been included per year since 2014. Grey system method and model are widely used in physics, chemistry, biology and other fields of natural science, as well as transportation, electric power, machinery and other fields of engineering technology, and a large number of valuable results have been achieved.

It can be seen that the grey system theory plays an important role in promoting China’s scientific and technological progress, innovation and development and high-level talent training from tens of thousands of literatures marked with important national science and technology projects and a large number of grey system literatures published by China’s double first-class universities and double first-class discipline construction universities.

Both innovations of theoretical research and practical application play important role in the growth of new theory. The innovations of theoretical research provide methods and tools for practical application, which is conducive to improve application efficiency and broaden application fields. A large number of practical applications needs have become the source of theoretical innovation and the solid background for the birth of theoretical innovation achievements.