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The purpose of this paper is to quantify the impact of return migration on the occupational choice in rural China.

The authors’ research uses the two‐stage residuals inclusion estimation, 2SRI, to deal with the endogeneity problem, and then compares the occupational choice between returnees and stayers with multinomial logit estimation and counterfactual analysis.

The authors mainly find that: the migration experience has a significant positive impact on wage‐employment activities, but may be has a negative effect on the entrepreneurial activities. The workers engaged in non‐agricultural activities (self‐employment and wage‐employment) have the same characteristics in the labor market (i.e. younger, male, higher education levels, less average land and parents with little children) compared to the agricultural activities, but these characteristics show no significant affect on the occupation choice between self‐employment and wage‐employment.

This paper extends the empirical analysis in internal migration, but it also has some drawbacks, such as not enough data can be obtained to distinguish the occupations between different types of self‐employment as own account workers and as entrepreneurs. Further research needs more comprehensive data to support.

The authors’ research is the first study which uses self‐selection model to examine the activity choice of return migrants in rural China. They also extend the existing studies in two directions: first, they use nationally‐representative data from the general social survey of China carried out in 2006 to examine the relationship between the return rural migrants and their occupational choices. Second, they propose a more exact category for rural occupational choice including non‐agricultural activities (self‐employee, wage‐employment) and agricultural activities (peasants).

This paper aims to present a case wherein a public archive intervenes in maintaining and preserving digital records (including underlying technological infrastructure) created by a private company to protect the trustworthiness of records, thereby helping the company to discharge their accountability.

This paper details the intervention of Tianjin Municipal Archives in the management of the records of Tianjin Otis Elevator Co., Ltd, the technical infrastructure that enables and supports such configuration, the issues encountered and the theoretical implications of this case.

This case suggests that not only does the concept of archives as a trusted third party remain relevant in the changing technological environment but also, in certain cases (e.g. wherein the supplier of evidentiary documents holds a monopoly over an industry), archives are becoming increasingly critical in maintaining the reliability and authenticity of digital records in the cloud environment.

Given the challenges raised by the emerging cloud environment, it is vital to develop a renewed understanding of the concept of archives as a trusted third party, the relationship between archives and commercial third party services and the relationship between public archives and private records. Furthermore, this case identifies the need to re-examine archival methodologies to protect the authenticity of structured data.

This case exemplifies how archives can help private organizations address issues related to guaranteeing and demonstrating the evidential nature of digital records and provides empirical evidence for archives being conceptualized as a trusted third party in maintaining and preserving digital records.

Analyzing the sentiment orientation of each product aspect/feature might be sufficient to assist the customer to make purchase/usage decisions, but such level of information obtained by sentiment analysis is not detailed enough to assist the company in making product improvement or design decisions. Therefore, this paper aims to propose a novel method to extract more detailed information of the product.

This paper proposed to use a set of trivial lexical-Part-of-Speech patterns to prepare candidate corpus and then adopted a topic model to find the optimal number of topics and get the words distributions in each topic. Finally, combined a priori analysis and compactness rules, the authors found out the expected strong rules in each topic, which make up the final problems.

Experimental results on a real-life data set from Xiaomi forum showed the proposed method can extract the product problems effectively. The authors also explained the errors of experiment, which suggested the direction for future research.

This paper proposed a novel method to obtain information of product problems in detail, which will be useful to assist companies to improve their product performance.

This paper aims to introduce an imitation learning framework for a wheeled mobile manipulator based on dynamical movement primitives (DMPs). A novel mobile manipulator with the capability to learn from demonstration is introduced. Then, this study explains the whole process for a wheeled mobile manipulator to learn a demonstrated task and generalize to new situations. Two visual tracking controllers are designed for recording human demonstrations and monitoring robot operations. The study clarifies how human demonstrations can be learned and generalized to new situations by a wheel mobile manipulator.

The kinematic model of a mobile manipulator is analyzed. An RGB-D camera is applied to record the demonstration trajectories and observe robot operations. To avoid human demonstration behaviors going out of sight of the camera, a visual tracking controller is designed based on the kinematic model of the mobile manipulator. The demonstration trajectories are then represented by DMPs and learned by the mobile manipulator with corresponding models. Another tracking controller is designed based on the kinematic model of the mobile manipulator to monitor and modify the robot operations.

To verify the effectiveness of the imitation learning framework, several daily tasks are demonstrated and learned by the mobile manipulator. The results indicate that the presented approach shows good performance for a wheeled mobile manipulator to learn tasks through human demonstrations. The only thing a robot-user needs to do is to provide demonstrations, which highly facilitates the application of mobile manipulators.

The research fulfills the need for a wheeled mobile manipulator to learn tasks via demonstrations instead of manual planning. Similar approaches can be applied to mobile manipulators with different architecture.

The purpose of this paper is to introduce the performance of traditional collision resolution algorithm (CRA) under self‐similar traffic and present a prediction‐based CRA for wireless media access. With experimentations, the method is there after evaluated.

The traditional traffic models are mostly based on “Poisson” model or “Bernoulli” process, but recent decade traffic measurements found the coexistence of both long‐ and short‐range dependence in network traffic. On the other hand, CRA is an effective strategy to improve the performance of multiple access protocol and it achieves the highest capacity among all known multiple access protocols under the Poisson traffic model. In this paper, a CRA model is built on OPNET to study the effects of different traffic traces such as the fractional autoregressive integrated moving average process with non‐Gaussian white driving sequence and the real traffic data that are captured at a well‐attended ACM Conference. The performance is compared of traditional CRA based on the self‐similar traffic model and Poisson model and a novel CRA based on time – series prediction theory under self‐similar traffic models is designed.

The traditional Poisson traffic model gets the best performance under traditional CRA, while the self‐similar traffic performance under traditional CRA is too poor to be applied in an actual network environment. For example, the Poisson traffic model obtains the biggest throughput, the smallest delay and smallest collision resolution numbers under traditional CRA. This paper demonstrates the first‐come first‐serve (FCFS) must be improved under self‐similar traffic models. The novel collision resolution strategy‐based prediction can provide better performance under self‐similar traffic. The parameters of performance, such as throughput, delay and collision resolution numbers, are better than the traditional CRA.

This paper presents a prediction‐based CRA for self‐similar traffic which is the combination of the FCFS and the prediction theory and also provides a new method to resolve packets colliding.

To strengthen the correlation analysis on risk factors of drug production safety and reduce the influence due to fuzzy judgments, a safety risk assessment method based on Grey-Analytic Network Process (G-ANP) is proposed.

First, an index system evaluating drug production safety risk is constructed according to the “Good Manufacture Practice of Medical Products,” next the influence weight of each risk index is derived by using the Analytic Network Process, then the grey number of each risk index is determined by further utilizing the grey statistical theory, and finally the risk level of drug production is obtained.

An empirical study is conducted and the results support the feasibility and practicability to use G-ANP method for drug production safety risk evaluation. The results of the case show that it is feasible and practical to use G-ANP method for drug production safety risk evaluation.

The innovation lies in the use of G-ANP method to fully consider the interdependence and interaction between the risk factors of drug production safety, which improves the objectivity in judging the risk level of drug production and provides a scientific basis for pharmaceutical manufacturers to formulate further decisions and management in the case of insufficient quantification of risk factors. Based on the findings, more targeted suggestions are made to reduce the production risk of pharmaceutical enterprises.

Members’ sustained participation positively influences success of brand community. Although scholars have confirmed the effects of social capital on continuance intention in third-party hosted communities, little work has been done to explore these relationships in context of enterprise-sponsored brand communities, especially, the precursors of active members’ sustained participation in such context is still unclear. Besides, how to recognize active users with high precision and coverage remains an open question. Therefore, this paper aims to propose a novel method to identify active users effectively and investigate the antecedents of their continuance intention from perspective of social capital in enterprise-sponsored brand community.

This work established several social networks based on the information of Xiaomi smartphone forum users’ posts and feedbacks. Node centrality (out-degree) analysis was adopted to identify the users with high degree of active in these networks, and then behaviour analysis was performed to exclude the community managers from the group of active users. Finally, a research model was proposed based on the theory of social capital. It was tested by applying partial least squares technique, and the data were collected from a survey of members (n = 327) of Xiaomi forum.

The empirical results showed that the proposed method can recognize the active users effectively. Additionally, social tie, identification, trust and shared vision were proved to be significant predictors of active users’ continuance intention in the context of enterprise-sponsored brand community.

This paper contributes to the information system usage literature and provides opinions regarding how social capital influence active users’ sustained participation in enterprise-sponsored brand community. Besides, this work proposed a novel method to identify active users, which will be useful to assist enterprises to improve their community management.

In this study, we develop understanding of factors that shape the propensity of market incumbents to collaborate in response to the threat posed by new market entrants. We are particularly interested in instances when a market's competitive structure becomes unsettled by new entrants who engage in nonconforming strategic tactics. In such situations, we propose two factors – strategic similarity among competitors and market-share instability – will systematically shape competitors' collaborative response to new entrants. To test our theory, we use data on strategic tactics and collaborative dynamics in the US airline industry from 1989 to 2010. We demonstrate that greater strategic similarity among a market's incumbents increases the likelihood of cooperation in response to the threat of a nonconforming new entrant, while greater market-share instability reduces cooperative response. Through this study, we extend existing understanding of the contextual circumstances under which established competitors recognize their mutual interests and band together.

Based on core description, gas logging and laboratory analysis, this paper aims to study the controlling effect of the types of shale sedimentary microfacies in coal formations over shale reservoirs using the example of Shanxi formation in Northern Ordos Basin.

According to core observation, the authors selected typical samples of rock types for thin section analysis to determine the micro features and compositions of rocks.

By using core observation, we found that fine lithology in Shanxi formation included major shale, carbonaceous shale, partially carbonaceous shale, partially silty shale and silty shale with colors of gray, dark gray, black and/or gray. Shanxi Formation shale are deposited in plant-rich and plant-poor swamps, interdistributary depressions of delta plains, interfluvial depressions of meandering rivers as well as microfacies environment of natural levees and the distal crevasse splay.

Currently, the research on the shale gas in Shanxi Formation in the Ordos Basin is still in its infancy. There is yet no research on the fine-grained partition of the sedimentary facies in coal accumulation environment of Shanxi formation and the controlling effect of sedimentary microfacies over shale reservoirs.

This paper aims to propose a novel balance-assistive control strategy for hip exoskeleton robot.

A hierarchical balance assistive controller based on the virtual stiffness model of extrapolated center of mass (XCoM) is proposed and tested by exoskeleton balance assistive control experiments.

Experiment results show that the proposed controller can accelerate the swing foot chasing XCoM and enlarge the margin of stability.

As a proof of concept, this paper shows the potential for exoskeleton to actively assist human regain balance in sagittal plane when human suffers from a forward or backward disturbing force.