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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 examines the relationship between higher education improvement and tacit knowledge importance. In this context, the scarcity of empirical and theoretical studies on acquiring tacit knowledge to enhance academic performance in higher education suggests that this research area holds significant importance for experts and policymakers. Consequently, this study aims to explore the factors that influence academic research performance at Chinese universities by acquiring tacit knowledge.

To achieve the study aims, the current approach utilizes the research technique based on the socialization, externalization, internalization and combination (SECI) model and knowledge management (KM) theory. To analyze the study objective, the authors collected data from post-graduate students at Chinese universities and analyzed it using structural equation modeling (SEM) to test the model and hypotheses.

The results indicated that social interaction, internalization and self-motivation have a positive impact on academic research performance through the acquisition of tacit knowledge. Furthermore, the findings suggest that academic researchers can acquire more knowledge through social interaction than self-motivation, thereby advancing research progress.

This study addresses the critical issues surrounding the acquisition of tacit knowledge and presents a comprehensive framework and achievements that can contribute to achieving exceptional academic performance.

Continuous knowledge contribution behaviors (CKCB) are critical for the healthy development of online medical communities (OMCs). However, it is unclear that if and how contributors' prior actions and the responses they received from the community influence the nature of their future contributions. Drawing upon the Information Systems Continuance theory and Service Feedback theory, the purpose of the study is to examine the impact of knowledge contribution performance (KCP) on doctors' CKCB. Evaluation of social motivation, financial incentive and the moderating influence of expertise level (EL) provided further insight into the pathways that motivate various forms of CKCB.

In order to better understand the CKCB of physicians in OMCs, the authors divided it into two categories: A_CKCB (active CKCB) and P_CKCB (passive CKCB). Information Systems Continuance theory and Service Feedback theory are adapted and integrated with empirical findings from previous research on OMCs to develop a model of CKCB. This study used ordinary least squares (OLS) regression to test hypotheses in the preexisting research model based on data collected from a Chinese OMC platform.

The results show that KCP helps develop several facets of CKCB. According to the findings, doctors' CKCB improved dramatically after receiving feedback from A_CKCB and P_CKCB, but feedback from peers did not promote CKCB. This study found that financial rewards only have a significant positive effect on P_CKCB, and that the level of expertise has a negative effect on the effect. The findings also demonstrated that doctors' level of expertise moderates the relationship between fA_CKCB (a comprehensive evaluation of doctors' A_CKCB) and A_CKCB.

Future studies should look at the role of self-efficacy as a mediator and attitudes as a moderator in the link between KCP and various forms of CKCB. This will help authors figure out how important KCP is for physicians' CKCB. And future research should use more than one way to gather data to prove the above roles.

This study makes a significant contribution to understanding the association between CKCB and KCP by highlighting the significance of distinguishing between the various forms of CKCB and their underlying causes.

This research has advanced both the theory and practice of OMCs' user management by illuminating the central role of KCP in this context.

To effectively implement knowledge management, one prerequisite is to understand and implement the knowledge management enablers in the sense of optimal institutional efficiency. This paper aims to analyze and measure the significant enablers in overseeing knowledge management in the construction sector.

The mixed-method technique was used to achieve the objective of this study and involved the application of detailed questions to project engineers and project managers within leading construction engineering companies, provided by the Institution of Engineering and Technology Ghana. In total, 150 questionnaires were collected and analyzed using the Statistical Package for Social Sciences v. 26.

The study confirms that the knowledge management enablers such as employees knowledge, motivations, effective decisions and strategic planning are some of the important ways in which construction professionals can achieve different strategic goals in many processes and concluded that the progress of the next generation knowledge management strategy will be based on content sharing, decision-making and by promoting the free flow of ideas.

The study offers perspectives into knowledge management enablers and recommends key performance factors, championed by Ghanaian construction contractors for institutional knowledge capture.

Creativity and productivity are important factors for corporate and government institutions in the COVID-19 era. As a result, there is an urgent need to ensure that construction projects can recover adequately to survive potential surges or even potential epidemics. Therefore, this study aims to explore social capital by examining the effect/impact of knowledge creation on construction performance in the COVID-19 era.

A simple random sampling approach focused on Ghanaian construction firms was used. Completed responses were obtained and analyzed from employees who had tasks on sites. SmartPLS 3.3.3 and Statistical Package for Social Sciences v. 26 was used.

One key finding from this research was that construction firms with solid social capital built by their management staff are more connected and have better adaptive systems than firms with low capital. A company’s development programs must concentrate not only on the development of targeted or selective know-how and professional abilities but also on capacity creating, collaboration and knowledge creation and sharing among its employees.

Using this study’s findings, construction professionals can develop successful solutions to the COVID-19 epidemic and future emergencies. Additionally, the comprehensive exposition of the implications, constraints and preventive methods in this study may enable scholars to discover current gaps in the literature and investigate other elements of the pandemic’s influence on the construction industry.

The purpose of this study is to investigate the application of non-destructive testing methods in measuring bearing oil film thickness to ensure that bearings are in a normal lubrication state. The oil film thickness is a crucial parameter reflecting the lubrication status of bearings, directly influencing the operational state of bearing transmission systems. However, it is challenging to accurately measure the oil film thickness under traditional disassembly conditions due to factors such as bearing structure and working conditions. Therefore, there is an urgent need for a nondestructive testing method to measure the oil film thickness and its status.

This paper introduces methods for optically, electrically and acoustically measuring the oil film thickness and status of bearings. It discusses the adaptability and measurement accuracy of different bearing oil film measurement methods and the impact of varying measurement conditions on accuracy. In addition, it compares the application scenarios of other techniques and the influence of the environment on detection results.

Ultrasonic measurement stands out due to its widespread adaptability, making it suitable for oil film thickness detection in various states and monitoring continuous changes in oil film thickness. Different methods can be selected depending on the measurement environment to compensate for measurement accuracy and enhance detection effectiveness.

This paper reviews the basic principles and latest applications of optical, electrical and acoustic measurement of oil film thickness and status. It analyzes applicable measurement methods for oil film under different conditions. It discusses the future trends of detection methods, providing possible solutions for bearing oil film thickness detection in complex engineering environments.

The minimum wage has been regarded as an important element of public policy for reducing poverty and inequality. Increasing the minimum wage is supposed to raise earnings for millions of low-wage workers and therefore lower earnings inequality. However, there is no consensus in the existing literature from industrialized countries regarding whether increasing the minimum wage has helped lower earnings inequality. China has recently exhibited rapid economic growth and widening earnings inequality. Since China promulgated new minimum wage regulations in 2004, the magnitude and frequency of changes in the minimum wage have been substantial, both over time and across jurisdictions. The growing importance of research on the relationship between the minimum wage and earnings inequality and its controversial nature have sparked heated debate in China, highlighting the importance of rigorous research to inform evidence-based policy making. We investigate the contribution of the minimum wage to the well-documented rise in earnings inequality in China from 2004 to 2009 by using city-level minimum wage panel data and a representative Chinese household survey, and we find that increasing the minimum wage reduces inequality – by decreasing the earnings gap between the median and the bottom decile – over the analysis period.

This study aims to focus on the surface curvature, jet to target spacing and jet Reynolds number effects on the heat transfer and fluid flow characteristics of a slot jet impinging on a confined concave target surface at constant jet to target spacing.

Numerical simulations are used in this research. Jet to target spacing, H/B is varying from 1.0 to 2.2, B is the slot width. The jet Reynolds number, Rej, varies from 8,000 to 40,000, and the surface curvature, R2/B, varies from 4 to 20. Results of the target surface heat transfer, flow parameters and fluid flow in the concave channel are performed.

It is found that an obvious backflow occurs near the upper wall. Both the local and averaged Nusselt numbers considered in the defined region respond positively to the Rej. The surface curvature plays a positive role in increasing the averaged Nusselt number for smaller surface curvature (4-15) but affects little as the surface curvature is large enough (> 15). The thermal performance is larger for smaller surface curvature and changes little as the surface curvature is larger than 15. The jet to target spacing shows a negative effect in heat transfer enhancement and thermal performance.

The surface curvature effects are conducted by verifying the concave surface with constant jet size. The flow characteristics are first obtained for the confined impingement cases. Then confined and unconfined slot jet impingements are compared. An ineffective point for surface curvature effects on heat transfer and thermal performance is obtained.

The process of predicting construction costs and forecasting price fluctuations is a significant and challenging undertaking for project managers. This study aims to develop a construction cost index (CCI) for Jordan’s construction industry using fuzzy analytic hierarchy process (FAHP) and predict future CCI values using traditional and machine learning (ML) techniques.

The most influential cost items were selected by conducting a literature review and confirmatory expert interviews. The cost items’ weights were calculated using FAHP to develop the CCI formula.

The results showed that the random forest model had the lowest mean absolute percentage error (MAPE) of 1.09%, followed by Extreme Gradient Boosting and K-nearest neighbours with MAPEs of 1.41% and 1.46%, respectively.

The novelty of this study lies within the use of FAHP to address the ambiguity of the impact of various cost items on CCI. The developed CCI equation and ML models are expected to significantly benefit construction managers, investors and policymakers in making informed decisions by enhancing their understanding of cost trends in the construction industry.

During the service condition of residential constructions with concrete structure, the influence of inside and exterior factors will result in different degrees of harm to concrete engineering. Therefore, it is very necessary to continue engineering work toward the concrete structure. Therefore, the purpose of this study is to evaluate the influence of the factors on the comprehensive performance of the concrete structure engineering.

Applying a mathematics method to establish the comprehensive evaluation model of the concrete structure engineering performance, qualitative and quantitative methods were adopted for reinforced concrete structural performance analysis.

The key to a safe construction project is to require all bidders to submit a written safety plan with their bids. The instruction to bidders must include guidelines for an acceptable safety plan and state clearly that the substance of the safety plan will be reviewed, and its adequacy will be a determining factor in who shall be selected as the contractor.

Based on the characteristics of concrete structure, applying the analytic hierarchy process to evaluate the concrete structure engineering comprehensive performance, an evaluation index system was built. The research combines quantitative method with qualitative method evaluation was made.