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The purpose of this study is to improve the position and posture accuracy of posture alignment mechanism. The automatic drilling and riveting machine is an important equipment for aircraft assembly. The alignment accuracy of position and posture of the bracket type posture alignment mechanism has a great influence on the operation effect of the machine. Therefore, it is necessary to carry out the kinematic calibration.

Based on analysis of elastic deformation of the bracket and geometric errors of the posture alignment mechanism, an improved method of kinematic calibration was proposed. The position and posture errors of bracket caused by geometric errors were separated from those caused by gravity. The method of reduction of dimensions was applied to deal with the error coefficient matrix in error identification, and it did not change the coefficient of the error terms. The target position and its posture were corrected to improve the error compensation accuracy. Furthermore, numerical simulation and experimental verification were carried out.

The simulation and experimental results show that considering the influence of the elastic deformation of the bracket on the calibration effect, the error identification accuracy and compensation accuracy can be improved. The maximum value of position error is reduced from 5.33 mm to 1.60 × 10⁻¹ mm and the maximum value of posture error is reduced from 1.07 × 10⁻³ rad to 6.02 × 10⁻⁴ rad, which is superior to the accuracy without considering the gravity factor.

This paper presents a calibration method considering the effects of geometric errors and gravity. By separating position and posture errors caused by different factors and correcting the target position and its posture, the results of the calibration method are greatly improved. The proposed method might be applied to any parallel mechanism based on the positioner.

The purpose of this paper is to use the redundancy of a new hybrid automatic fastening system (HAFS) for aircraft assembly in the best way.

First, the kinematic model of HAFS is divided into three sub-models, which are the upper/lower tool and parallel robot. With the geometric coordination relationship, a comprehensive kinematic model of the HAFS is built by mathematically assembling the sub-models based on the DH method. Then, a novel master-slave decoupling strategy for inverse kinematics solution is proposed. With the combination of the minimum energy consumption and the comfortable configuration, a multi-objective redundancy resolution method is developed to optimize the fastening configuration of the HAFS, which keep the HAFS away from the joint-limits and collision avoiding in the aircraft panel assembly process.

An efficient multi-objective posture optimization algorithm to use the redundancy in the best way is obtained. Simulation and an experiment are used to demonstrate the correctness of the proposed method. Moreover, the position and orientation errors of the drilling holes are within 0.222 mm and 0.356°, which are accurate enough for the automatic fastening in aircraft manufacturing.

This method has been used in the HAFS control system, and the practical results show the aircraft components can be fastened automatically through this method with high efficiency and high quality.

This paper proposes a comprehensive kinematic model and a novel decoupling strategy for inverse kinematic solution of the HAFS, which provides a reference to utilize the redundancy in the best way for a hybrid machine with redundant function.

The paper aims to explore multilingual thesauri automation construction based on the freely available digital library resources. The key methods and study results are presented in the paper. It also proposes a way that terms are automatically extracted from multilingual parallel corpus.

The study adopted the technology of natural language processing to analyze the linguistics characteristics of terms, and combined this with statistical analyses to extract the terms from technological documents. The methods consist of automatically extracting and filtering terms, judging and building relationship among terms, building the multilingual parallel corpus, and extracting term pairs between Chinese and foreign languages through calculating their associated probability. The experiments run on the Java test platform.

The study obtains the following conclusions: finding the similarities and differences between the Chinese thesaurus standard and international thesaurus standard. The methods for automatically extracting terms and building relationships among them are presented. Eventually the multilingual terms' translation sets are generated based on real corpora. The results of the study show that the proposed methods can obtain better performance. The effect of automatic terms' translation alignment method is better than that of traditional IBM model method.

The study results can provide references for further study and application of multilingual thesauri automation construction using Chinese as a pivot.

The paper proposes new ideas on thesaurus automation construction in the digital age. The presented method based on linguistics and statistics is a new attempt. According to the experimental results, this exploration and study is innovative and valuable. In addition, these ideas and methods give a good start for improving information services of the PRC's National Science and Technology Digital Library.

Despite a ravaging pandemic worldwide, Vietnam managed to contain the local outbreak, partly owing to its carefully implemented risk communications campaign. This chapter investigated the effectiveness of official Vietnam government communications, the sentiment of foreign media reporting on Vietnam, and any challenges. Content analysis was applied to samples from government communications (43 samples); international articles (46); and social media conversations (33). Official government communications were quite accurate, timely, and effective in displaying transparency, employing war symbolism, and shared responsibility, but should more clearly separate between state and expert, offer differing views, and highlight the benefits of compliance. International articles praised the government's viral PSA TikTok video, its transparency, and the netizens' nationalist narratives. While some evidence was found for infodemic, blaming, and heroization, the sample was too small to be conclusive. Future studies should expand the timeframe to a longer duration, quantitatively appraise a wider sampling of social media conversations, and possibly conduct primary interviews with experts, policy makers, and the public.

This paper analyzes Fang Fang's 2020 Wuhan Diary‐Dispatches from a Quarantined City, to show how the author communicates the coronavirus crisis in Wuhan in a global information ecosystem. The success of the diary showcases how the actual health emergency has been transformed into a communication issue.

This study is exploratory and qualitative in nature. The authors conducted a thematic analysis (TA) of Wuhan Diary, in which we decided to focus on the aspects of sousveillance and solidarity. For the purposes of our paper, we used the English translation of the text by Dr. Michael Berry.

The authors focus on two major themes in their exploration of the corona crisis as a global communication issue: sousveillance and solidarity. The authors argue that the diary's ways of seeing perform a version of “sousveillance” or “undersight” in juxtaposition to surveillance or “oversight” (Mann, 2017). Fang Fang calls for solidarity as an effective measure for individuals, communities and societies to contain the pandemic and a potential misinfodemic.

Since Wuhan was the early epicenter of the COVID-19 pandemic, Wuhan Diary presents an unprecedented narrative account of life under quarantine that could function as a litmus test for other cities and countries. Fang Fang's diary provides a countermeasure to official accounts of the pandemic in Wuhan, which has resonated both with people in China and abroad.

The paper aims to address wireless sensor network (WSN) security by proposing new cluster-based mobile key management scheme (CMKMS). The growing demands of WSNs in variety of real-time and mission-critical applications increase the challenges in terms of energy efficiency, security and mobility. The security is important to avoid malicious attacks and improve the energy efficiency, while mobility helps to improve the reachability of network. The CMKMS algorithm focuses on the management and maintenance of keys under cluster-based mobile WSN network.

The paper studied the related work in the area of key management and compared the different key management algorithms according to the technique used. The comparative study shows that the available key management algorithms are efficient in terms of security, but they are not scaleable enough to the changing conditions of network and do not work efficiently under node mobility. The research uses cluster-based approach for improving scalability, where cluster head (CH) acts as a key manager. The work developed by considering both static and mobile CH.

The CMKMS considers two phases, first for key maintenance which establishes the two private keys, home key for own cluster and foreign key when node moves from one cluster to another. The second phase maintains the keys when CH moves from one cluster to another. The proposed algorithm improves the efficiency of key management algorithm in terms of security, mobility, energy efficiency and scalability of network. The simulation of scheme in different realistic situation shows that proposed solution shows less computational overheads, energy consumption and delay as compared with state-of-art solution.

The research is validated using computer-based simulation, which limits the testing of research by considering external environmental conditions. Therefore, research can be further test using WSN test bed.

The research address the issues in key management, developed the scaleable, and node mobility supportable key management algorithms, for addressing the demands of growing WSN applications.

This paper accomplish the security of WSN using scaleable and mobility-supported key management algorithms.

Today clothing has become the largest category in online shopping in China, and even in Asia-Pacific. The satisfaction degree of apparel online shopping can be improved by effective personalized recommendation. The purpose of this paper is to propose a personalized recommendation model and algorithm based on Kansei engineering, traditional filtering algorithm and the knowledge relating to apparel.

Users’ perceptual image and the design elements of apparel based on Kansei engineering are discussed to build the mapping relation between the design elements and user ratings employing verbal protocol, semantic differential and partial least squares. The implicit knowledge and emotional needs pertaining to users are accessed using analytic hierarchy process. A personalized recommendation model for apparel online shopping is established and the algorithm for the personalized recommendation process is proposed. To present the personalized recommendation model, men’s plaid shirts are taken as the example, and the recommendations of apparel for online shopping were implemented and ranked in the context of differing users’ emotional needs. A comparison between the traditional model and this model is made to verify the effectiveness.

The recommendation model is capable of analyzing data and information effectively, and providing fast, personalized apparel recommendation services in accordance with users’ emotional needs. The experimental results suggest that the model is effective.

Similar researches of recommendation mainly focus on the field of computer science, the basic idea of which is using users’ history accessing records or the preferences of other similar users for determination of users’ preferences. Since the attributes of apparel products are not factored in the approach referred above, the issue of personalized recommendation cannot be solved in a really effective way. Combining Kansei engineering and recommendation algorithm, a framework for apparel product recommendation is presented and it is a new way for improvement of recommendations for apparel products on shopping sites.