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The purpose of this paper is to demonstrate the applications of big data in personal knowledge management (PKM).

Five conventional knowledge management dimensions, namely, the value of data, data collection, data storage, data application and data presentation, were applied for integrating big data in the context of PKM.

This study concludes that time management, computer usage efficiency management, mobile device usage behavior management, health management and browser surfing management are areas where big data can be applied to PKM.

While the literature discusses PKM without considering the impact of big data, this paper aims to extend existing knowledge by demonstrating the application of big data in PKM.

This paper aims to establish the predictive equations of height, area and volume of printed solder paste during solder paste stencil printing (SPSP) process in surface mount technology (SMT) to better understand the effect of process parameters on the printing quality.

An experiment plan is proposed based on the response surface method (RSM). Experiments with 30 different combinations of process parameters are performed using a solder paste printer. After printing, the volume, area and height of the printed SAC105 solder paste are measured by a solder paste inspection machine. Using RSM, the predictive equations associated with the printing parameters and the printing quality of the solder paste are formed.

The optimal printing parameters are 175.08 N printing pressure, 250 mm/s printing speed, 0.1 mm snap-off height and 15.7 mm/s stencil snap-off speed if the target height of solder paste is 100 µm. As the target printing area of solder paste is 1.1 mm × 1.3 mm, the optimized values of the printing parameters are 140.29 N, 100.52 mm/s, 0.63 mm and 20.25 mm/s. When both the target printing height and area are optimized together, the optimal values for the four parameters are 86.67 N, 225.76 mm/s, 0.15 mm and 1.82 mm/s.

A simple RSM-based experimental method is proposed to formulate the predictive polynomial equations for height, area and volume of printed solder paste in terms of important SPSP parameters. The predictive equation model can be applied to the actual SPSP process, allowing engineers to quickly predict the best printing parameters during parameter setting to improve production efficiency and quality.

This chapter examines how the breakthrough of Zhang Ziyi's depiction of a female kung fu master in The Grandmaster (2013) transforms the figure of the heroine in Chinese action films. Zhang is well known for her acting in action films conducted by renowned directors, such as Ang Lee, Zhang Yimou and Wong Kar-wai. After winning 12 different Best Actress awards for her portrayal of Gong Ruomei in The Grandmaster, Zhang announced that she would no longer perform in any action films to show her highest respect for the superlative character Gong. Tracing Zhang's transformational portrait of a heroine in The Grandmaster alongside her other action roles, this analysis demonstrates how her performance projects the directors' distinctive gender viewpoints. I argue that Zhang's characterisation of Gong remodels heroine-hood in Chinese action films. Inheriting the typical plot of a daughter's use of martial arts for revenge for her father's death, Gong breaks from conventional Chinese action films that highlight romantic love during a woman's adventure and the decisive final battle scene. Beyond the propensity for sensory stimulation, Gong's characterisation enables Zhang to determine that women can really act in action films – demonstrating their inner power and ability to create multi-layered characters – not merely relying upon physical action. This chapter offers a relational perspective of how women transform the action film genre not merely as gender spectacles but as embodied figures that represent emerging female subjectivity.

This study aims to explore the relationship between job standardization and employee innovative behavior, as well as the mediating and moderating effects of employee psychological empowerment. Little research has been focused on the conflicting concepts of job standardization and employee innovative behavior.

Respondents chosen from frontline services in tourist hotels in Taiwan were used to examine the mediating and moderating roles of psychological empowerment on the established relationships between job standardization and employee innovative behavior. The results were analyzed using hierarchical regression models.

The results show that job standardization had a negative effect on employee innovative behavior. In addition, employee psychological empowerment mediated the effect of job standardization on innovative behavior. Subsequently, employee psychological empowerment played a buffering role and moderated the job standardization–innovative behavior relationship.

Hotel management needs to use both training and work process review to help employees innovate while still understanding the meaning of their work, enhancing self-efficacy, self-determination and the impact of decision-making.

This study gives both theoretical and empirical evidence to clarify the effect of psychological empowerment on the importance of job standardization and innovative behavior in organizations. This is the only study that has investigated this topic in the hospitality field and therefore makes significant strides in understanding the impact of psychological empowerment on hotel employees’ innovative behavior.

This paper is a study of the current trends and conditions of electronic resources for Chinese studies, based on a recent survey on the Internet of 29 Chinese libraries in North America and eight Chinese libraries in China, Taiwan and Hong Kong. The survey discussed current electronic resources for Chinese studies, with a union list of major Chinese language databases currently used in libraries in Asia and the US. Current views on the use and development of electronic resources for Chinese studies were summarised.

Apart from, the smart edge computing (EC) robot (SECR) provides the tools to manage Internet of things (IoT) services in the edge landscape by means of real-world test-bed designed in ECR. Eventually, based on the results from two experiments held in little constrained condition, such as the maximum data size is 2GB, the performance of the proposed techniques demonstrate the effectiveness, scalability and performance efficiency of the proposed IoT model.

Certainly, the proposed SECR is trying primarily to take over other traditional static robots in a centralized or distributed cloud environment. One aspect of representation of the proposed edge computing algorithms is due to challenge to slow down the consumption of time which happened in an artificial intelligence (AI) robot system. Thus, the developed SECR trained by tiny machine learning (TinyML) techniques to develop a decentralized and dynamic software environment.

Specifically, the waste time of SECR has actually slowed down when it is embedded with Edge Computing devices in the demonstration of data transmission within different paths. The TinyML is applied to train with image data sets for generating a framework running in the SECR for the recognition which has also proved with a second complete experiment.

The work presented in this paper is the first research effort, and which is focusing on resource allocation and dynamic path selection for edge computing. The developed platform using a decoupled resource management model that manages the allocation of micro node resources independent of the service provisioning performed at the cloud and manager nodes. Besides, the algorithm of the edge computing management is established with different path and pass large data to cloud and receive it. In this work which considered the SECR framework is able to perform the same function as that supports to the multi-dimensional scaling (MDS).

This study aims to empirically investigate the role of contracts in tacit knowledge acquisition in research and development (R&D) alliances. By combining the perspectives of sensemaking and transaction cost economics (TCE), this study proposes a model about the mechanisms through which shared goals and contract completeness jointly affect tacit knowledge acquisition.

This study adopted a quantitative design and used the questionnaire survey method to collect data. The authors finally collected data on 196 R&D alliance samples in China. Multiple regression analysis was used to test the hypotheses.

There is strong empirical support that contract completeness has a positive effect on shared goals and that shared goals have a positive effect on tacit knowledge acquisition. Meanwhile, contract completeness weakens the positive effect of shared goals on tacit knowledge acquisition. Therefore, this study reveals that contract completeness has an inverted U-shaped effect on tacit knowledge acquisition.

The findings suggest that managers should consider both the psychological and rational effects of contract governance simultaneously, thus recognizing the importance of a moderate level of contract completeness for tacit knowledge acquisition in R&D alliances.

This study enhances the current understanding of contract governance by integrating the sensemaking and TCE perspectives. The findings provide a possible explanation of how contracts affect tacit knowledge acquisition in R&D alliances. The authors expand the research on contract governance and alliance knowledge acquisition by revealing the inverted U-shaped relationship between contract governance and tacit knowledge acquisition.

The article aims to investigate the effects of ownership and capital structure on postacquisition operating performance.

The article extends the ongoing literature from an operating loss perspective and provides empirical evidence on the probability of acquirers’ operating loss in relation to ownership and capital structure. The operating performance of publicly listed manufacturing firms in China was tracked up to five years since the completion of the mergers and acquisitions (M&A) during 2003–2014.

The empirical results show that, in a five-year postacquisition period, state-owned enterprises (SOEs) are more likely to experience operating loss than non-SOEs. The likelihood of the operating loss is negatively associated with ownership concentration, implying that concentrated ownership may serve as an effective corporate governance mechanism in the emerging economy and improve postacquisition performance. The rise in leverage increases the likelihood of postacquisition operating loss, indicating that the costs of debt may outweigh the benefits.

The findings contribute to the literature on ownership, debt governance and post-M&A performance from an emerging economy perspective.

The purpose of this paper is to describe work aimed to control the Al alloy welding penetration through the passive vision for welding robot.

First a passive vision system was established. The system can capture the Al alloy welding image. Based on the analysis of the characteristic of the welding image, the composite edge detectors were developed to recognize the shape of the weld seam and the weld pool. To realize the automatic control of the Al alloy‐weld process, the relation between the welding parameter and the quality of the weld appearance was established through the random welding experiment. The wire feed was chosen with PID controller adjusting the wire feed rate according to the weld gap variation.

This paper finds that the passive vision system can be captured the clear weld seam and weld pool image simultaneously. the method of composite edge detectors can be effectively and accurately recognize the weld seam edges. The wire feed rate controller ensured the welding robot to adjust the wire feed rate according to the gap variation.

This system has been applied to the industrial welding robot production.

The weld seam and weld pool image can be simultaneously captured by the passive vision system. The composite edge detectors have been developed for the passive vision method. The controller has been set up for Al alloy welding process based on the neural network.