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The membrane wall is one of the most important components in the boiler industry and numerous studs are welded on its surface. The membrane wall welding still remains a sector intensive in the manual and arduous works. This paper aims to propose a dual-robot system to automatically weld studs on the membrane wall.

In this paper, the authors proposed a dual-robot stud welding system for membrane walls. First, the membrane wall is divided into several zones and the welding paths are planned. Then, the pose of the pipes is calculated based on the data measured by light section sensors. The planned paths are compensated by the pose. Finally, the robots weld studs based on the compensated paths.

The method effectively eliminates manufacturing errors and welding distortions. The system can weld straight type and L-type membrane walls with high efficiency, high quality and high accuracy.

The system can weld straight type and L-type membrane walls with high efficiency and high quality. Experiments were performed in a factory to demonstrate the practicability of the method. The dual-robot system with two welding machines has approximately twice the efficiency of the manual welder with only one welding machine. The quality and accuracy of robot welding systems are higher than that of manual welding.

This paper aims on the trajectory tracking of the developed six wheel-legged robot with heavy load conditions under uncertain physical interaction. The accuracy of trajectory tracking and stable operation with heavy load are the main challenges of parallel mechanism for wheel-legged robots, especially in complex road conditions. To guarantee the tracking performance in an uncertain environment, the disturbances, including the internal friction, external environment interaction, should be considered in the practical robot system.

In this paper, a fuzzy approximation-based model predictive tracking scheme (FMPC) for reliable tracking control is developed to the six wheel-legged robot, in which the fuzzy logic approximation is applied to estimate the uncertain physical interaction and external dynamics of the robot system. Meanwhile, the advanced parallel mechanism of the electric six wheel-legged robot (BIT-NAZA) is presented.

Co-simulation and comparative experimental results using the BIT-NAZA robot derived from the developed hybrid control scheme indicate that the methodology can achieve satisfactory tracking performance in terms of accuracy and stability.

This research can provide theoretical and engineering guidance for lateral stability of intelligent robots under unknown disturbances and uncertain nonlinearities and facilitate the control performance of the mobile robots in a practical system.

A successful process of design concept evaluation has positive influence on subsequent processes. This study aims to consider the evaluation information at multiple stages and the interaction among evaluators and improve the credibility of evaluation results.

This paper proposes a multi-stage approach for design concept evaluation based on complex network and bounded confidence. First, a network is constructed according to the evaluation data. Depending on the consensus degree of evaluation opinions, the number of evaluation rounds is determined. Then, bounded confidence rules are applied for the modification of preference information. Last, a planning function is constructed to calculate the weight of each stage and aggregate information at multiple evaluation stages.

The results indicate that the opinions of the evaluators tend to be consistent after multiple stages of interactive adjustment, and the ordering of design concept alternatives tends to be stable with the progress of the evaluation.

Updating preferences according to the bounded confidence rules, only the opinions within the trust threshold are considered. The attribute information of the node itself is inadequately considered.

This method addresses the need for considering the evaluation information at each stage and minimizes the impact of disagreements within the evaluation group on the evaluation results.

Man has been seeking an ideal existence for a very long time. In this existence, justice, love, and peace are no longer words, but actual experiences. How ever, with the American preemptive invasion and occupation of Afghanistan and Iraq and the subsequent prisoner abuse, such an existence seems to be farther and farther away from reality. The purpose of this work is to stop this dangerous trend by promoting justice, love, and peace through a change of the paradigm that is inconsistent with justice, love, and peace. The strong paradigm that created the strong nation like the U.S. and the strong man like George W. Bush have been the culprit, rather than the contributor, of the above three universal ideals. Thus, rather than justice, love, and peace, the strong paradigm resulted in in justice, hatred, and violence. In order to remove these three and related evils, what the world needs in the beginning of the third millenium is the weak paradigm. Through the acceptance of the latter paradigm, the golden mean or middle paradigm can be formulated, which is a synergy of the weak and the strong paradigm. In order to understand properly the meaning of these paradigms, however, some digression appears necessary.

Traditional case-adaptation methods have poor accuracy, low efficiency and limited applicability, which cannot meet the needs of knowledge users. To address the shortcomings of the existing research in the industry, this paper proposes a case-adaptation optimization algorithm to support the effective application of tacit knowledge resources.

The attribute simplification algorithm based on the forward search strategy in the neighborhood decision information system is implemented to realize the vertical dimensionality reduction of the case base, and the fuzzy C-mean (FCM) clustering algorithm based on the simulated annealing genetic algorithm (SAGA) is implemented to compress the case base horizontally with multiple decision classes. Then, the subspace K-nearest neighbors (KNN) algorithm is used to induce the decision rules for the set of adapted cases to complete the optimization of the adaptation model.

The findings suggest the rapid enrichment of data, information and tacit knowledge in the field of practice has led to low efficiency and low utilization of knowledge dissemination, and this algorithm can effectively alleviate the problems of users falling into “knowledge disorientation” in the era of the knowledge economy.

This study provides a model with case knowledge that meets users’ needs, thereby effectively improving the application of the tacit knowledge in the explicit case base and the problem-solving efficiency of knowledge users.

The adaptation model can serve as a stable and efficient prediction model to make predictions for the effects of the many logistics and e-commerce enterprises' plans.

This study designs a multi-decision class case-adaptation optimization study based on forward attribute selection strategy-neighborhood rough sets (FASS-NRS) and simulated annealing genetic algorithm-fuzzy C-means (SAGA-FCM) for tacit knowledgeable exogenous cases. By effectively organizing and adjusting tacit knowledge resources, knowledge service organizations can maintain their competitive advantages. The algorithm models established in this study develop theoretical directions for a multi-decision class case-adaptation optimization study of tacit knowledge.

This study aims to deal with the case adaptation problem associated with continuous data by providing a non-zero base solution for knowledge users in solving a given situation.

Firstly, the neighbourhood transformation of the initial case base and the view similarity between the problem and the existing cases will be examined. Multiple cases with perspective similarity or above a predefined threshold will be used as the adaption cases. Secondly, on the decision rule set of the decision space, the deterministic decision model of the corresponding distance between the problem and the set of lower approximate objects under each choice class of the adaptation set is applied to extract the decision rule set of the case condition space. Finally, the solution elements of the problem will be reconstructed using the rule set and the values of the problem's conditional elements.

The findings suggest that the classic knowledge matching approach reveals the user with the most similar knowledge/cases but relatively low satisfaction. This also revealed a non-zero adaptation based on human–computer interaction, which has the difficulties of solid subjectivity and low adaptation efficiency.

In this study the multi-case inductive adaptation of the problem to be solved is carried out by analyzing and extracting the law of the effect of the centralized conditions on the decision-making of the adaptation. The adaption process is more rigorous with less subjective influence better reliability and higher application value. The approach described in this research can directly change the original data set which is more beneficial to enhancing problem-solving accuracy while broadening the application area of the adaptation mechanism.

The examination of the calculation cases confirms the innovation of this study in comparison to the traditional method of matching cases with tacit knowledge extrapolation.

The algorithm models established in this study develop theoretical directions for a multi-case induction adaptation study of tacit knowledge.

This study designs a multi-case induction adaptation scheme by combining NRS and CBR for implicitly knowledgeable exogenous cases. A game-theoretic combinatorial assignment method is applied to calculate the case view and the view similarity based on the threshold screening.

The public service motivation (PSM) theory implies that public employees are spiritual people called “public servants” who have a desire to affect the community and are characterized by compassion and serving others. Owing to their commitment to public welfare, spirituality is apparently inherited in public employees as an occupation/employment effort, which entails attaching a “meaning” to the work being done in the workplace for the spiritual satisfaction of the employees. A sense of well-being among the employees of an organization can prove instrumental in developing their motivation level and improving the quality of their services. The literature depicts that workplace spirituality (WPS) is a feature that enhances multiple forms of employee well-being (EWB). Considering the importance of these concepts in terms of enhancing the productivity of the organizations, the current study aimed to gain an understanding of the PSM together with two other positive attributes namely WPS and EWB and determine their interrelationship. The aim of this study is to examine a significant positive relationship between PSM and WPS mediated by EWB.

The study has been conducted in the context of the public sector of Pakistan where a sample of the academic staff of higher educational institutions in the Punjab province was selected through probability sampling techniques for conducting the survey. The data collected from 394 respondents from the selected faculties of the universities were analyzed using relevant statistical tools (SPSS and AMOS: 22) to answer the research questions.

This study supported a significant positive relationship between PSM and WPS mediated by EWB. The quantitative findings of this study, thus, demonstrated that the culture of spirituality in the workplace significantly affects the PSM of employees by way of creating a sense of well-being among the employees.

This study is unique as it serves as an effort to understand the spiritual experience of the public sector employees involved in public service. This infers that spirituality in the workplace improved employees’ well-being by giving them a strong sense of purpose and these employees in a healthy state of mind are more likely to perform above and beyond and have a high motivation to serve the public.

The purpose of this paper is to explore recent national human resource development (NHRD) practices in China through a literature review focusing on programs and activities that represent the roles and interactions among the government, industry and universities.

To effectively consolidate previous work and conceptualize the recent development of the NHRD practices in China, a semi-narrative literature review was used to explore and analyze NHRD-related functions and activities.

Findings from the literature review showed that although the central government still plays a predominant role in China, universities and corporations are increasingly playing a critical role in developing an innovative and skilled workforce. At the regional level, NHRD initiatives in China have been increasingly undertaken by universities, industry and government–industry–university collaborations. The authors also found a disparity between developed and underdeveloped regions in terms of NHRD in China.

This study used the triple helix model as a framework that provides an insightful lens for researchers to examine how various social entities interact with each other and jointly contribute to NHRD. Further case studies are needed to generate evidence-based knowledge to the NHRD literature.

A more systematic NHRD leadership structure at both the national and local level is desired to unleash the potential of bottom-up development and active government–industry–university collaboration. To counter regional divergence in NHRD in China, intra- and cross-regional collaborations are helpful in improving resources distribution and workforce development.

Based on open system theory, this study focused on programs and activities that represent the roles and interactions among the government, industry and university in Chinese NHRD through the lens of the triple helix model. In addition, this study offers a conceptual model of Chinese NHRD to help scholars and practitioners understand the transitional efforts in NHRD.

Copper-graphite (Cu/C) is a type of seal material that has been widely used in liquid rocket engines and with normal metal pairs, has a high wear rate under liquid oxygen lubrication. In this study, bearing steel disks were subjected to a high-temperature oxidization and phosphating progress to create an oxidized tricresyl phosphating film (OTCP) film, using tricresyl phosphate (TCP) as the phosphating solvent. It is hoped that the surface wear rate and friction coefficient can be reduced by this method.

This study aim to form an anti-wear film on the surface of bearing steel, which can significantly improve the lubrication performance of Cu/C and bearing steel. The surfaces of bearing steel disks were dried to remove surface water and then put on a heating plate with a magnetic stirrer and a blue glazed oxide film obtained by heating the disks in the air at 200°C for 1 h. To create the OTCP film, bearing steel disks with a blue glazed oxide film were cleaned ultrasonically three times in ethanol and then placed in baths of TCP. After heating for 2 h at 120°C, excess TCP liquid was removed from the disks using ethanol, leaving an OTCP film on the disk surface.

It was found that steel coated with an OTCP film demonstrated better tribological performance (lower coefficient of fiction and wear rate) when pairing with Cu/C than either oxidized or untreated bearing steel. Additional chemical reactions occur when the oxide disk is immersed in TCP and the FePO₄ film is formed after heating. Additionally, the OTCP film coated steel displayed good corrosion resistance, as confirmed by electrochemical corrosion tests. This finding demonstrates the potential for this process in the aerospace industry.

The preparation of OTCP films via high-temperature oxidization and phosphating of bearing steel was demonstrated, with the tribological properties of the OTCP film being investigated alongside those of the original surface and an oxidized film surface. The fabrication of OTCP films is easily scaled up and exhibits significant advantages as a new technology for applications in mechanical contact seal lubrication.

This research aims to propose a comparative environmental analysis of conventional and prefabricated construction techniques utilizing a building information modelling (BIM) technique.

A set of indicators are selected to assess the environmental emissions throughout the construction life cycle, based on BIM platform. An existing project involving ten apartment buildings in Shanghai is selected as a case study.

The results reveal that prefabricated construction demonstrates environment-friendly performance with some exceptions of acidification and mineral resource consumption. Environmental impacts can also be further reduced by increasing the projected area ratio and percentage of project prefabrication.

Overall, the proposed method can be used to identify relevant environmental merits and for decision-making of appropriate construction techniques in building construction projects.