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The purpose of this study is to provide an in-depth understanding about the indoor-orbital electrical inspection robot, which is useful for motivating the further investigation on the inspection of electrical equipment. Currently, electric energy has a strong correlation with the economic development of the country. Intelligent substations play an important role in the transmission and distribution of the electricity; the maintenance of the substation has attracted intensive attention due to the requirement of reliability and safety. The indoor-orbital electrical inspection robot has increasingly become the main tool to realize the unmanned. Hence, a systematic review is conducted systematically reviewing the current technical status of the indoor-orbital electrical inspection robot and discuss the existed problems.

In this paper, the most essential achievements in the field of indoor-orbital electrical inspection robots were reported to present the current status, and the mechanical structures and key inspective technologies were also discussed.

Four recommendations are provided from the analyzed review, which have made constructive comments on the overall structural design, functionality, intelligence and future development direction of the indoor-orbital electrical inspection robot, respectively.

To the best of the authors’ knowledge, this is the first systematic review study on indoor-orbital electrical inspection robots; it fills the theoretical gap and proffers design ideas and directions for the development of the indoor-orbital electrical inspection robot.

Manufacturing systems design is a complex task and is crucial to the future of a company. Computer simulation provides an efficient and visual method for system designers. The popularity of simulation is owing to its ability to model systems in a fast and cost‐effective way, its flexibility and its ability to model the time dynamic behavior of systems. This paper demonstrates the use of computer simulation as a tool for assisting managers and engineers in the design and analysis of a new manufacturing system by presenting a case study. The case study is a study of proposed instrument panel/crashpad production and assembly work‐cells in an automotive industry. The emphasis on the case study was to evaluate alternative designs, predict system performance, detect any potential problems, experiment with system parameters and determine the sensitivity of the system to these parameters. The case study results show that computer simulation can be a useful decision‐making support tool for the analysis of the system performance and the selection of the design alternatives before the system is actually implemented.

In the early industrial age which with high intensity of machine and labor, using financial measurement index was good enough to tie in company’s mechanization and philosophy of management and been in efficiency. But being comply with “New Economic age,” a new economic environment is full of knowledge and information, the enterprise competition had changed from tangible assets, plants to intangible innovation ability of knowledge. As recognizing the new tendency by enterprise, they value gradually the growth and influence from learning. Practice of organization learning not only needs firm structure and be in coordination with both hardware and software, but also needs an affect measurement model to offer enterprise to estimate learning performance. It’s a good instrument of financial performance measure mold in the past years, But it’s for measuring the past, couldn’t formulate enterprise trend to future, hard to estimate investment for future, such as development of products, organization learning, knowledge management etc, as which intangible assets and knowledge ability just the key factors of being win around competition environment in the future. In 1992, Kaplan and Norton brought up Balance Scorecard (BSC) on Harvard Business Review, as an instrument helping enterprise to measure performance, which is being considered to be a most influence management instrument. It added non‐financial index such as customer, internal process and learning growth besides traditional financial index, as offering enterprise an index to measure and manage intangible assets and intellectual property. As being aware of organization learning is hard to be ignored in the new economic age, this research is based on learning and growth of BSC, and citing one national material company try to let the most difficult measurement performance of organization learning, to be estimate through BSC, analyze of factor and individual case, to discuss the company how to make the related strategy and vision of organization learning to develop learning and growth of the structure of BSC, subject the matter of out put factors to be discussed, and measure the outcomes as a result of research. The research affect offers (1) the base implement procedure of carrying out BSC; (2) the reference of formulating measurement index while enterprise using BSC to estimate performance of organization learning; (3) the possibility bottleneck maybe forcing while carrying out BSC, to be an improvement or preventive for enterprise.

To gain accurate support for large aircraft structures by ball joints in aircraft digital assembly, this paper aims to propose a novel approach based on visual servoing such that the positioner’s ball-socket can automatically and adaptively approach the ball-head fixed on the aircraft structures.

Image moments of circular marker labeled on the ball-head are selected as visual features to control the three translational degrees of freedom (DOFs) of the positioner, where the composite Jacobian matrix is full rank. Kalman–Bucy filter is adopted for its online estimation, which makes the control scheme more flexible without system calibration. A combination of proportional control with sliding mode control is proposed to improve the system stability and compensate uncertainties of the system.

The ball-socket can accurately and smoothly reach its desired position in a finite time (50 s). Positional deviations between the spherical centers of ball-head and ball-socket in the X-Y plane can be controlled within 0.05 mm which meets the design requirement.

The proposed approach has been integrated into the pose alignment system. It has shown great potential to be widely applied in the leading support for large aircraft structures in aircraft digital assembly.

An adaptive approach for accurate support of large aircraft structures is proposed, which possesses characteristics of high precision, high efficiency and excellent stability.

The purpose of this study is to evaluate freely available machine translation (MT) services' performance in translating metadata records.

Randomly selected metadata records were translated from English into Chinese using Google, Bing, and SYSTRAN MT systems. These translations were then evaluated using a five point scale for both fluency and adequacy. Missing count (words not translated) and incorrect count (words incorrectly translated) were also recorded.

Concerning both fluency and adequacy, Google and Bing's translations of more than 70 percent of test data received scores equal to or greater than three, representative of “non‐native Chinese” and “much coverage,” respectively. SYSTRAN scored lowest in both measures. However, these differences were not statistically significant. A Pearson correlation analysis demonstrated a strong relationship (r=0.86) between fluency and adequacy. Missing count and incorrect count strongly correlated with fluency and adequacy.

Most existing digital collections can be accessed in English alone. Few digital collections in the USA support multilingual information access (MLIA) that enables users of differing languages to search, browse, recognize and use information in the collections. Human translation is one solution, but it is neither time nor cost effective for most libraries. This study serves as a first step to understand the performance of current MT systems and to design effective and efficient MLIA services for digital collections.

A cross-domain intelligent software-defined network (SDN) routing method based on a proposed multiagent deep reinforcement learning (MDRL) method is developed.

First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between the root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to acquire global network state information in real time. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a network traffic state prediction mechanism is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time.

Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and open shortest path first (OSPF) routing methods.

Message transmission and message synchronization for multicontroller interdomain routing in SDN have long adaptation times and slow convergence speeds, coupled with the shortcomings of traditional interdomain routing methods, such as cumbersome configuration and inflexible acquisition of network state information. These drawbacks make it difficult to obtain global state information about the network, and the optimal routing decision cannot be made in real time, affecting network performance. This paper proposes a cross-domain intelligent SDN routing method based on a proposed MDRL method. First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to realize the real-time acquisition of global network state information. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a prediction mechanism for the network traffic state is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time. Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and OSPF routing methods.

The purpose of this paper is to understand the boundary-spanning behaviors of Party organizations, and the processes and constraints of these behaviors in controlling worker unrest in Chinese resource-based state-owned enterprises in the “new work-unit system” using boundary-spanning theory.

This case study was carried out in a resource-based state-owned enterprise in the “new work-unit system” in China. The research utilized interviews and archival documents, and then coded and analyzed the data using NVivo.

In China, Party organizations’ boundary-spanning behaviors (PBSBs) in labor relations management are identified, and classified into the behaviors of the ambassador, task coordinator, and scout. Worker unrest can be controlled by these behaviors through the mediation effect of the behaviors of agents in the “new work-unit system” but can also be provoked in the transformation of the “new work-unit system.”

The Communist Party plays a key role in labor relations management in China’s SOEs; however, this role has not been explored in any depth. This study builds a model to reveal the “black box” in which the PBSBs influence the agents’ behaviors and how the agents’ behaviors then influence the workers, and in this way control worker unrest.

With the rapid development of social media, many organizations have begun to attach importance to social media platforms. This research studies the management and the use of social media in academic music libraries, taking the Center for Chinese Music Studies of the Chinese University of Hong Kong (CCMS) as a case study.

We conducted a sentiment analysis of posts on Facebook’s public page to analyze the reaction to the posts with some exploratory analysis, including the communication trend and relevant factors that affect user interaction.

Our results show that the Facebook channel for the library has a good publicity effect and active interaction, but the number of posts and interactions has a downward trend. Therefore, the library needs to pay more attention to the management of the Facebook channel and take adequate measures to improve the quality of posts to increase interaction.

Few studies have analyzed existing data directly collected from social media by programming based on sentiment analysis and natural language processing technology to explore potential methods to promote music libraries, especially in East Asia, and about traditional music.

This study aims to provide a time- and price-sensitive market strategy for merchants to handle the markdown price strategy. The market demand for perishable products is usually price – and quality (freshness) – sensitive. The proper handling of markdown-price strategies can help merchants enhance competitiveness and maximize operational performance.

A markdown strategy consisting of price and markdown time was developed to explore the properties of market strategies based on the dynamic quality evaluation. The strategy considers multiple price discounts and multiple markdown times. The optimal price decisions in each stage and the optimal markdown times were derived during the selling season.

The results showed the following. A retailer always raises the initial price if it wants to adopt multiple price-markdown strategies. A high initial price may lead to a high inventory at the early stage and bring the next price reduction in advance. Large price discounts can be used to reduce the inventory later. The higher the previous price, the shorter the interval between the next price reduction. The markdown strategies showed that the regular discount as a new business model is not the best pricing model for perishable products. A time- and price-sensitive strategy, however, can increase operational performance and provide new insights for perishable products.

The results showed the following. A retailer always raises the initial price if it wants to adopt multiple price-markdown strategies. A high initial price may lead to a high inventory at the early stage and bring the next price reduction in advance. Large price discounts can be used to reduce the inventory later. The higher the previous price, the shorter the interval between the next price reduction. The markdown strategies showed that the regular discount as a new business model is not the best pricing model for perishable products. A time- and price-sensitive strategy, however, can increase operational performance and provide new insights for perishable products.