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The purpose of this study is to establish an assembly accuracy analysis model of deployable arms based on Jacobian–Torsor theory to improve the assembly accuracy. Spacecraft deployable arm is one of the core components of spacecraft. Reducing the errors in assembly process is the main method to improve the assembly accuracy of spacecraft deployable arms.

First, the influence of composite connecting rod, root joint and arm joint on assembly accuracy in the tandem assembly process is analyzed to propose the assembly accuracy analysis model. Second, a non-tandem assembly process of “two joints fixed-composite rod installed-flange gasket compensated” is proposed and analyzed to improve the assembly accuracy of deployable arms. Finally, the feasibility of non-tandem assembly process strategy is verified by assembly experiment.

The experiential results show that the assembly errors are reduced compared with the tandem assembly process. The errors on axes x, y and z directions decreased from 14.1009 mm, 14.2424 mm and 0.8414 mm to 0.922 mm, 0.671 mm and 0.2393 mm, respectively. The errors round axes x and y directions also decreased from 0.0050° and 0.0053° to 0.00292° and 0.00251°, respectively.

This paper presents an assembly accuracy analysis model of deployable arms and applies the model to calculate assembly errors in tandem assembly process. In addition, a non-tandem assembly process is proposed based on the model. The experimental results show that the non-tandem assembly process can improve the assembly accuracy of deployable arms.

The purpose of this study is to propose a new coordinated dynamic demand lot-size and delivery planning problem (CDLSDP), in which the delivery policy is integrated into the coordinated dynamic demand lot-size problem (CDLSP).

As a non-deterministic polynomial complete (NP-complete) problem, this CDLSDP seems difficult to be solved by a polynomial-time method. To handle this problem effectively and efficiently, a four-phase heuristic that balances the setup and inventory costs in the coordinating and delivery stages is designed to find near-optimal solutions.

Numerous computational experiments show that the proposed four-phase heuristic is effective and efficient. For 1,800 experiments with different scales, and different joint setup costs, solutions by the proposed heuristic have an average gap no more than 1.34% from the optimal solution.

To decrease total system cost, the CDLSDP optimizes the time-phased replenishment and delivery schedule, which includes joint setup cost, item setup, delivery and inventory cost, for each period. An effective and efficient four-phase heuristic is designed to solve the CDLSDP.

Compared with the traditional CDLSP, the delivery policy is considered by the new CDLSDP. Moreover, the proposed four-phase heuristic is a good candidate for solving the CDLSDP.

By using an integrated theoretical analysis model and a practice analysis model, this study constructed an evaluation indicator system for public participation in post-disaster housing reconstruction.

This study investigated and summarised the public participation of earthquake victims in house building in Dujiangyan. A total of 16 analysis elements were proposed, including the subject and object for evaluation. A mixed qualitative and quantitative evaluation model was established.

The implementation results indicated that this evaluation index system was objective oriented and had public policy attributes. The index can effectively reflect the diverse needs of disaster victims, address multiple social aspects and evaluate and rate public participation.

This paper proposed a mixed research method that integrates analysis processes, such as theories and practical investigation, which are the pillars of public participation evaluation. The evaluation indicators had quantitative characteristics.

In recent years, knowledge graph completion has gained increasing research focus and shown significant improvements. However, most existing models only use the structures of knowledge graph triples when obtaining the entity and relationship representations. In contrast, the integration of the entity description and the knowledge graph network structure has been ignored. This paper aims to investigate how to leverage both the entity description and the network structure to enhance the knowledge graph completion with a high generalization ability among different datasets.

The authors propose an entity-description augmented knowledge graph completion model (EDA-KGC), which incorporates the entity description and network structure. It consists of three modules, i.e. representation initialization, deep interaction and reasoning. The representation initialization module utilizes entity descriptions to obtain the pre-trained representation of entities. The deep interaction module acquires the features of the deep interaction between entities and relationships. The reasoning component performs matrix manipulations with the deep interaction feature vector and entity representation matrix, thus obtaining the probability distribution of target entities. The authors conduct intensive experiments on the FB15K, WN18, FB15K-237 and WN18RR data sets to validate the effect of the proposed model.

The experiments demonstrate that the proposed model outperforms the traditional structure-based knowledge graph completion model and the entity-description-enhanced knowledge graph completion model. The experiments also suggest that the model has greater feasibility in different scenarios such as sparse data, dynamic entities and limited training epochs. The study shows that the integration of entity description and network structure can significantly increase the effect of the knowledge graph completion task.

The research has a significant reference for completing the missing information in the knowledge graph and improving the application effect of the knowledge graph in information retrieval, question answering and other fields.

The purpose of the study is to evaluate the severity of public events in real time from the perspective of social media and to construct the early warning mechanism of public events.

This study constructed the severity assessment system of public events from the dimensions of the netizens' role, the Internet media's role, the spread of public events and the attitudes and feelings of netizens. The method of analyzing the influence tendency of the public event severity indicators was proposed. A total of 1,107,308 microblogging entries regarding four public events were investigated. The severity of public events was divided into four levels.

It is found that serious public events have higher indicator values than medium level events on the microblogging platform. A quantitative severity classification standard for public events was established and the early warning mechanism of public events was built.

Microblogging and other social media platforms provide rich clues for the real-time study and judgment of public events. This study only investigated the Weibo platform as the data source. Other social media platforms can also be considered in future.

Different from the ex-post evaluation method of judging the severity of public events based on their physical loss, this study constructed a quantitative method to dynamically determine the severity of public events according to the clues reflected by social media. The results can help the emergency management departments judge the severity of public events objectively and reduce the subjective negligence and misjudgment.

This study aims to profile the government microbloggers and evaluate their roles. The results can help improve the governments' response capability to public emergencies.

This study proposes the user profiling and role evaluation model of government microbloggers in the context of public emergencies. The indicators are designed from the four dimensions of time, content, scale and influence, and the feature labels are identified. Three different public emergencies were investigated, including the West Africa Ebola outbreak, the Middle East respiratory syndrome outbreak and the Shandong vaccine case in China.

The results found that most government microbloggers were follower responders, short-term participants, originators, occasional participants and low influencers. The role distribution of government microbloggers was highly concentrated. However, in terms of individual profiles, the role of a government microblogger varied with events.

The findings can provide a reference for the performance assessment of the government microbloggers in the context of public emergencies and help them improve their ability to communicate with the public and respond to public emergencies.

By analyzing the performance of government microbloggers from the four dimensions of time, content, scale and influence, this paper fills the gap in existing literature on designing the user profiling and role evaluation model of government microbloggers in the context of public emergencies.

Multiple topics often exist on social media platforms that compete for users' attention. To explore how users’ attention transfers in the context of multitopic competition can help us understand the development pattern of the public attention.

This study proposes the prediction model for the attention transfer behavior of social media users in the context of multitopic competition and reveals the important influencing factors of users' attention transfer. Microblogging features are selected from the dimensions of users, time, topics and competitiveness. The microblogging posts on eight topic categories from Sina Weibo, the most popular microblogging platform in China, are used for empirical analysis. A novel indicator named transfer tendency of a feature value is proposed to identify the important factors for attention transfer.

The accuracy of the prediction model based on Light GBM reaches 91%. It is found that user features are the most important for the attention transfer of microblogging users among all the features. The conditions of attention transfer in all aspects are also revealed.

The findings can help governments and enterprises understand the competition mechanism among multiple topics and improve their ability to cope with public opinions in the complex environment.

This paper aims to explore the commodity transshipment planning among customers, which is commonly observed in production/sales enterprises to save the operational costs.

A mixed integer programming (MIP) model is built and five types of valid inequalities for tightening the solution space are derived. An improved variable neighborhood search (IVNS) algorithm is presented combining the developed multistart initial solution strategy and modified neighborhood local search procedure.

Experimental results demonstrate that: with less decision variables considered, the proposed model can solve more instances compared to the existing model in previous literature. The valid inequalities utilized to tighten the searching space can efficiently help the model to obtain optimal solutions or high-quality lower bounds. The improved algorithm is efficient to obtain optimal or near-optimal solutions and superior to the compared algorithm in terms of solution quality, computational time and robustness.

This research not only can help reduce operational costs and improve logistics efficiency for relevant enterprises, but also can provide guidance for constructing the decision support system of logistics intelligent scheduling platform to cater for centralized management and control.

This paper develops a more compact model and some stronger valid inequalities. Moreover, the proposed algorithm is easy to implement and performs well.

This study aims to find the impact of supply chain certification (SCCert) on supply chain efficiency (SCEffi) with the inverted U-shaped moderator role of supply chain complexity (SCComp).

In order to test the conceptual model and the hypothesized relationships between all the constructs, the 307 useable survey responses were collected using the purposive sampling technique on a seven-point Likert scale. The SPSS26.0 and AMOS24.0 were used to analyze data, and the hierarchical regression analysis was used to test the model.

This study reached a set of interesting results where it was confirmed that there is a significant relationship between SCCert and SCEffi. It further confirmed the inverted U-shaped moderating effect of SCComp between SCCert and SCEffi: on the left side of the threshold, the increase of SCComp will enhance the promotion effect of SCCert on SCEffi, while on the right side of the threshold, excessive SCComp will rather weaken the promotion effect of SCCert on SCEffi.

The findings provide implications for supply chain efficiency enablers to introduce/promote certification upgrading actions. The study provides a framework for solving the power and constraint problem of supply chain efficiency change.

Findings provide deeper and new insights into threshold feature of supply chain complexity, analyzing how supply chain certification activity realize supply chain efficiency reform through the moderating role of supply chain complexity.

Stochastic computing which is an alternative method of the binary calculation has key merits such as fault-tolerant capability and low hardware cost. However, the hardware response time of it is required to be very fast due to its bit-wise calculation mode. While the complementary metal oxide semiconductor (CMOS) components are difficult to meet the requirements aforementioned. For this, the stochastic computing implementation scheme based on the memristive system is proposed to reduce the response time. The purpose of this paper is to provide the implementation scheme based memristive system for the stochastic computing.

The hardware structure of material logic based on the memristive system is realized according to the advantages of the memristor. After that, the scheme of NOT logic, AND logic and multiplexer are designed, which are the basic units of stochastic computing. Furthermore, a stochastic computing system based on memristive combinational logic is structured and its validity is verified successfully by operating a case.

The numbers of the elements of the proposed stochastic computing system are less than the conventional stochastic computing based on CMOS circuits.

The paper proposed a novel implementation scheme for stochastic computing based on the memristive systems, which are different from the conventional stochastic computing based on CMOS circuits.