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This study aims to investigate the effect of combined use of granular graphite and petroleum coke on the properties of copper-based friction materials and the friction and wear mechanisms.

Copper-based friction materials with different proportions of petroleum coke and granular graphite were prepared by using powder metallurgy. The friction surfaces were analyzed.

Changing the ratio of petroleum coke/granular graphite affects the formation of oxides and sulfides on the surface of the materials. Increasing the petroleum coke promotes the production of metal sulfide and sulfate in the friction materials and reduces coefficient of friction (COF) and wear. Increasing petroleum coke also increases the amount of carbonic oxide (CO) released during the braking process and promotes the reduction process of iron oxide on the friction surface.

The synergistic effect of carbon materials on copper-based friction materials was studied in terms of the tribological chemical reaction. This research provides useful information for the selection of carbon materials in friction materials.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2020-0075/

As we know, the quality of processes is technically depicted by variation, a product or process with the best quality must naturally require the variation as less as possible. The variation is usually reduced with many ways, say, by adjusting parameters settings under robust design with many turns expensive experiements. So ones are trying to reach the robusiness by detecting cheap and simple methods. In this paper, a both practical and simple technique for quality improvement, namely reducing the variation, by data classification is studied. First, all possible system factors are included, which may dominate the variation law. And then we make use of the past observations and their classification as well as boxplot charts to find out the internal rule between the variation and the system factor. Next, adjust the location of the system factor according to the rule so that the variation could, to some extent, be lessened. Finally, two typical quality improvement cases based on data classification are presented.

Fabric defect detection plays an important role in textile quality control. The purpose of this paper is to propose a fabric defect detection algorithm via context-based local texture saliency analysis.

In the proposed algorithm, a target image is first divided into blocks, then the Local Binary Pattern (LBP) technique is used to extract the texture features of blocks. Second, for a given image block, several other blocks are randomly chosen for calculating the LBP contrast between a given block and the randomly chosen blocks. Based on the obtained contrast information, a saliency map is produced. Finally, saliency map is segmented by using an optimal threshold, which is obtained by an iterative approach.

The experimental results show that the proposed algorithm, integrating local texture features and global image texture information, can detect texture defects effectively.

In this paper, a novel fabric defect detection algorithm via context-based local texture saliency analysis is proposed.

The purpose of this paper is to employ a fractional approach to predict the permeability of nonwoven fabrics by simulating diffusion process.

The method described here follows a similar approach to anomalous diffusion process. The relationship between viscous hydraulic permeability and electrical conductivity of porous material is applied in the derivation of fractional power law of permeability.

The presented power law predicted by fractional method is validated by the results obtained from simulation of fluid flow around a 3D nonwoven porous material by using the lattice-Boltzmann approach. A relation between the fluid permeability and the fluid content (filling fraction), namely, following the power law of the form, was derived via a scaling argument. The exponent n is predominantly a function of pore-size distribution dimension and random walk dimension of the fluid.

The fractional scheme by simulating diffusion process presented in this paper is a new method to predict wicking fluid flow through nonwoven fabrics. The forecast approach can be applied to the prediction of the permeability of other porous materials.

The purpose of this paper is to realize dynamical grey incidence order of influencing factors of grain production in Henan province using grey systems theory.

Starting from choosing influence factors on grain production and dividing the 30 years (from 1979 to 2009 year) of grain production in Henan province into three periods, the authors calculate grey incidence degree between grain yield and every influencing factor by grey incidence analysis method, respectively, then obtain the grey incidence order of influencing factors in every period. Also based on the three grey incidence orders from different periods, the authors find a changeable tendency of influencing factors on grain production and key influencing factors on grain production in different periods. Finally, to keep Henan province grain production stable and sustainable, several policy suggestions are given.

The results are convincing: it is effective and powerful to analyze dynamically influencing factors of grain production using grey systems theory, and it is urgent to strengthen agricultural science and technology input, and pay close attention to the influence of dosage of pesticide and fertilizers on grain production.

Grey incidence analysis and findings exposed in the paper can be used by agricultural firms to optimize grain production plans, and by government to formulate reasonable agricultural production policies.

The paper succeeds in getting dynamical grey incidence order of influencing factors of grain production in Henan province using grey systems theory.

A new model called the G‐C‐D model, which is used to measure the technological advance, is built in this paper. The progress in non‐technical elements in Solow's “remaining value” is removed by using the idea, method and modeling technique of grey system theory. So, the difficult technical problem in the measurement of technological advance has been solved to a certain extent. The periodic G‐C‐D model of Henan Province is built in four different periods and the contribution rate of periodic technological advance of Henan Province is measured.

The construction project is implemented under uncertainty environment, and the product of construction is very complex. Selecting a project delivery system/approach is a critical task, which determines the project schedule, quality and investment objectives. The purpose of this paper is to propose a decision-making model for the selection of project delivery system which is based on information entropy and unascertained measure model.

A decision-making model based on information entropy and unascertained set is employed to select project delivery approach. In order to overcome the subjective evaluations from the experts, the theory of “entropy weight” is applied to modify the experts’ subjective weight. The multi-attribute unascertained measure decision making is fitted to deal with the uncertainty information for selection of project delivery system.

The proposed methodology is more comprehensive compared with the previous work, especially in the uncertainty environment.

There is some further work that should be considered, such as how to deal with the imprecise and subjective information given by the experts; how to determine the weight of the experts’; finding a set of importance factors influencing the selection of a delivery system is a complex task to further research.

The proposed method can help the construction owner to select a most fitted project delivery system of a construction project.

A new approach to select project delivery approach is proposed based on information entropy and unascertained set.

To explore the influence factors and pathways of users’ willingness to participate in the misinformation purification process on the Weibo platform. The findings of this study are expected to provide valuable insights that can enhance the self-purification mechanisms for misinformation on Weibo, thereby contributing to the effective misinformation control.

The theoretical framework of the quantitative study is a conceptual model integrated with the theory of planned behavior (TPB), social exchange theory (SET) and co-dependency theory. This model was developed to elucidate the influence factors of users’ willingness to participate in the purification of misinformation on the Weibo platform, the conceptual model was tested and refined through questionnaire surveys, structural equation modeling (SEM) was used to assess its validity and reliability.

The findings reveal that the attitude toward misinformation purification on the Weibo platform exerts the most significant positive influence on the willingness to engage in such activities. Within the context of this research, community involvement and reciprocity are identified as the factors that have the most substantial positive impact on users’ attitude toward misinformation purification. Conversely, risk perception does not demonstrate a significant influence on users’ attitude toward misinformation purification.

Taking the Weibo platform as an example, this is a pioneering study on the investigation and mechanism of social media self-purification on misinformation and proposes a new perspective to improve the effectiveness of the social media self-purification mechanism from the perspective of focusing on user intention and motivation.

The purpose of this paper is to find how those uncertainty factors influence transaction costs generated and to identify ways to minimize the transaction costs borne by the construction owner.

The literature indicates that there is no consensus on a standard definition of transaction costs in the construction industry. A detailed literature review of research work on transaction costs in construction is conducted in order to identify the determinants of transaction costs in construction projects. A structural equation model is tested on data collected by means of a survey administered to construction owners.

The findings indicate that the transaction costs borne by the owner can be minimized if the owner minimizes the uncertainties inherent in the construction project by making sure the engineering design is as complete as possible before bids are sought from contractors; harmonious relationships between project participants; fair risk allocation; have experience in similar type projects; and contractor selection practices that routinely detect irregular behavior.

The data used in this research are primarily based on the experiences of public owners and the markets in which they operate; a larger representation of private owners could make the conclusions more general. Another limitation of the study is that it relies on a survey of opinions rather than actual records of costs and other hard data.

No empirical study has ever been conducted of transaction-related issues in the construction industry because of the lack of a common understanding of transaction cost. This paper provides the groundwork for such a study.

This paper attempts to reconcile the many determinants of transaction costs in construction projects under uncertainty considered by different researchers in a multitude of research studies.

The purpose of this paper is to develop a potential nanoparticles lubricant additive for solving the problem of the insolubility and stable dispersity; the complex nanoparticles with core-shell structures are less studied in the field. Therefore, this paper determines novel complex nanoparticles and their tribological properties.

According to the conventional preparation method, the complex nanoparticle styrene/calcium borate (PS/O-CaB) was synthesized. The microstructures of the as-obtained samples were characterized by X-ray diffraction infrared spectroscopy and thermogravimetric analysis. Tribological properties of PS/O-CaB used as lubricating oil additive were evaluated on four-ball tribometer. The worn surface of the steel ball was investigated by a three-dimensional non-contact surface profilometer and X-ray photoelectron spectroscopy (XPS).

The results of the structure characteristic indicate two different crystalline forms, namely, Ca₂B₆O₁₁ and Ca₂B₂O₅, and the average size of calcium borate nanoparticles in PS/O-CaB is about 20-40 nm. Moreover, the good tribological properties are due to a wear resistance film containing both depositions and the tribochemical reaction products which comprise B2O3, FeB and Fe2O3.

Novel complex nanoparticles with core-shell structure (PS/O-CaB) were successfully prepared. Moreover, the PS/O-CaB shows excellent tribological capacity such as load-carrying, friction-reducing and antiwear property.