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The Wiener-Hammerstein nonlinear system is made up of two dynamic linear subsystems in series with a static nonlinear subsystem, and it is widely used in electrical, mechanical, aerospace and other fields. This paper considers the parameter estimation of the Wiener-Hammerstein output error moving average (OEMA) system.

The idea of multi-population and parameter self-adaptive identification is introduced, and a multi-population self-adaptive differential evolution (MPSADE) algorithm is proposed. In order to confirm the feasibility of the above method, the differential evolution (DE), the self-adaptive differential evolution (SADE), the MPSADE and the gradient iterative (GI) algorithms are derived to identify the Wiener-Hammerstein OEMA system, respectively.

From the simulation results, the authors find that the estimation errors under the four algorithms stabilize after 120, 30, 20 and 300 iterations, respectively, and the estimation errors of the four algorithms converge to 5.0%, 3.6%, 2.7% and 7.3%, which show that all four algorithms can identify the Wiener-Hammerstein OEMA system.

Compared with DE, SADE and GI algorithm, the MPSADE algorithm not only has higher parameter estimation accuracy but also has a faster convergence speed. Finally, the input–output relationship of laser welding system is described and identified by the MPSADE algorithm. The simulation results show that the MPSADE algorithm can effectively identify parameters of the laser welding system.

To present the mechanism, on which the first module was successfully designed – the automated installation application system, in the grand automated management and evaluation for community health service (CHS) sector of China.

The automated installation application system is constructed on the platform of Visual FoxPro8.0. The construction consists of five steps. The first is to establish the “item.” The function of “the item” is to trace all procedures, forms, menus, and various databases, such as tabulated data, summary data, and other types of data. The second is to establish the customer log‐in module. This module needs to contain a roll book of authorized customers. The third is to construct the subsystem management interface. This interface includes: entering installation the application, modifying and saving and transferring out the information, searching, printing blank form and statement. The fourth is to establish a roll book of all forms and the database of all the forms. The fifth is to establish the main procedure, connecting all the modules in the working order.

The main advantage of the system is that it is helpful for the characteristics of speedy information importation, clear and straight to the point, as well as the secure and accurate data transfer.

Automated management and evaluation for CHS heavily depends on the initial activation and this initiation is started using the system of installation application.

Wear greatly influences the machine lifetime, performance and reliability and its quantification is very important. This paper aims to propose a modified bearing area curve method by combining the theory of the bearing area curve, and the relocation technique to calculate wear accurately and efficiently.

H13 steel was chosen as the material of wear pair, and the wear experiments were carried out at 50 N, 60 r/min for 20 min. The surface was measured before and after wear experiments. The relocation was made by comparing the mean lines (planes) of the unworn and worn surface profiles. The calculated results using the proposed method were compared with that of the surface profile method for a two-dimensional surface to validate its accuracy. The method was then applied for a three-dimensional (3D) wear analysis.

The worn surface shows clearly displacement compared to the unworn surface and implies the importance of including relocation in the bearing area curve method. The results from the proposed method are 98 per cent close to that from the surface profile method, indicating that the method is accurate for wear evaluation.

As no feature point or relocation mark is needed to calculate the relocation value using the proposed method, the method can be applied to mild to severe wear. Also, as the deviation of different scans does not affect the relocation calculation, and no matching and stitching is required, this method can be easily applied to a wide wear area and 3D surface wear analysis.

The paper seeks to attempt to solve a decision‐making problem for breeding target character shown as an interval number.

A new comprehensive evaluation method is proposed based on similarity‐difference theory and interval number theory. Data from Winter Wheat Group I Variety Regional Test in Henan Province in 2009‐2010 were analysed using the proposed method.

The results showed that Zhou 99233 was a good variety; Yuxhan No. 7, An 05‐28, Xun K8, Jinyumai 378 and Zhoumai 18 were better ones; 08 luo 36,and Xuke 718 ordinary ones, and others worse ones. Based on this, the feasibility of the method was discussed. It showed that the proposed method had some obvious merits, such as simple arithmetic, convenient operation, flexible and practical, fast and effective.

The application of a live example indicated that its evaluation effect was satisfactory.

The paper succeeds in solving a decision‐making problem for breeding target character shown as an interval number.

The purpose of this paper is to understand the effect of platform characteristics (i.e. media richness and interactivity) on individual perception (i.e. outcome expectations) and consequent behavioral response (i.e. user participation in online health communities (OHCs)) based on the stimulus-organism-response (S-O-R) model.

This study developed a research model to test the proposed hypotheses, and the proposed model was tested using partial least squares structural equation modeling (PLS-SEM) for which data were collected from 321 users with OHC experience using an online survey.

The empirical results show the following: (1) the three dimensions of media richness significantly affect the three outcome expectations, except that richness of expression has no significant effect on the outcome expectation of health self-management competence. (2) Human-to-human interaction significantly affects the three outcome expectations. Moreover, compared with human-to-human interaction, human-to-system interaction has a stronger impact on the outcome expectation of health self-management competence. (3) The three outcome expectations have a significant influence on user participation in OHCs.

This study extends the understanding about how platform characteristics (i.e. media richness and interactivity) motivate user participation in the context of OHCs. Drawing on the S-O-R model, this study reveals the underlying mechanisms by which media richness and interactivity are associated with outcome expectations and by which outcome expectations is associated with user participation in OHCs. This study enriches the literature on media richness, interactivity, outcome expectations and user participation in OHCs, providing insights for developers and administrators of OHCs.

The current popular image processing technologies based on convolutional neural network have the characteristics of large computation, high storage cost and low accuracy for tiny defect detection, which is contrary to the high real-time and accuracy, limited computing resources and storage required by industrial applications. Therefore, an improved YOLOv4 named as YOLOv4-Defect is proposed aim to solve the above problems.

On the one hand, this study performs multi-dimensional compression processing on the feature extraction network of YOLOv4 to simplify the model and improve the feature extraction ability of the model through knowledge distillation. On the other hand, a prediction scale with more detailed receptive field is added to optimize the model structure, which can improve the detection performance for tiny defects.

The effectiveness of the method is verified by public data sets NEU-CLS and DAGM 2007, and the steel ingot data set collected in the actual industrial field. The experimental results demonstrated that the proposed YOLOv4-Defect method can greatly improve the recognition efficiency and accuracy and reduce the size and computation consumption of the model.

This paper proposed an improved YOLOv4 named as YOLOv4-Defect for the detection of surface defect, which is conducive to application in various industrial scenarios with limited storage and computing resources, and meets the requirements of high real-time and precision.

In the context of carbon peaking and neutrality, effectively controlling agricultural carbon emissions has gained academic attention. As an essential form of agricultural service scale management, this study investigates whether and how trusteeship affects the carbon emission behavior in planting production.

The authors established a theoretical framework to analyze the impact of agricultural production trusteeship on carbon emissions from planting. China's provincial panel data in the 2012–2021 period were selected to test the impact, mechanisms and heterogeneity of agricultural production trusteeship on carbon emissions from planting using the bidirectional fixed effect model and the panel correction standard error regression model.

The findings indicate that agricultural production trusteeship significantly inhibits carbon emissions from planting, especially in the dimensions of fertilizer input, pesticide application, agricultural film use and mechanical fuel. Agricultural production trusteeship primarily affects the intensity of these carbon emissions through contiguous farmland management and planting structure adjustment. Further examinations revealed that the influence of agricultural production trusteeship on carbon emissions from planting was heterogeneous with respect to geographical location, proportion of non-farming income and scale of agricultural production.

This study is the first to systematically evaluate the impact of agricultural production trusteeship on carbon emissions from planting.

Organizations increasingly manage innovation projects jointly with suppliers to use external resources to fill internal competencies. However, little is known about the practices of how companies configure internal and external resources to enhance competitiveness. Drawing on resource orchestration theory, this study aims to propose a novel approach to explain organizational performance using purchasing orchestration (PO) as an antecedent. The paper then tests an empirical model to assess the impact of PO practices on innovation and financial performance.

Cross-sectional survey data from 247 supply chain managers are used to test hypotheses relating PO to performance. SPSS PROCESS is applied to test conditional direct and indirect effects.

The positive impact of PO practices on innovation and financial performance is confirmed. Results indicate an organization’s entrepreneurial orientation (EO) can strengthen the positive relationship between PO and financial performance. Structuring, bundling and leveraging external resources are introduced as new organizational capabilities.

This research is based on cross-sectional data, and unidimensional constructs are used.

This research guides managers on the innovation process in light of the growing importance of external resources. The manuscript highlights the role of strategic purchasing in establishing new resource capabilities as a competitive advantage.

This research provides new insights into the relationship between purchasing practices and organizational performance and helps better understand the implications of orchestrating supply chain resources. A novel construct, PO, is introduced as a theoretical basis for studying supply chain-enabled innovation.

The purpose of this paper is to improve the mechanical and tribological properties of Si₃N₄ ceramics and to make the application of Si₃N₄ ceramics as tribological materials more extensive.

Si₃N₄-based composite ceramics (SN-2L) containing nitrogen-doped graphene quantum dots (N-GQDs) were prepared by hot press sintering process through adding 2 Wt.% nanolignin as precursor to the Si₃N₄ matrix, and the dry friction and wear behaviors of Si₃N₄-based composite against TC4 disc were performed at the different loads by using pin-on-disc tester.

The friction coefficients and wear rates of SN-2L composite against TC4 were significantly lower than those of the single-phase Si₃N₄ against TC4 at the load range from 15 to 45 N. At higher load of 45 N, SN-2L/TC4 pair presented the lowest friction coefficient of 0.25, and the wear rates of the pins and discs were as low as 1.76 × 10⁻⁶ and 2.59 × 10⁻⁴mm³/N·m. The low friction and wear behavior could be attributed to the detachment of N-GQDs from the ceramic matrix to the worn surface at the load of 30 N or higher, and then an effective lubricating film containing N-GQDs, SiO₂, TiO₂ and Al₂SiO₅ formed in the worn surface. While, at the same test condition, the friction coefficient of the single-phase Si₃N₄ against TC4 was at a range from 0.45 to 0.58. The spalling and cracking morphology formed on the worn surface of single-phase Si3N4, and the wear mechanism was mainly dominated by adhesive and abrasive wear.

Overall, a high-performance green ceramic composite was prepared, and the composite had a good potential for application in engineering tribology fields (such as aerospace bearings).

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0161/

In this paper, we provide a simple conceptual framework with empirical analysis to investigate the effect of product attributes and e-vendor characteristics that are potentially included in the online shopper’s information search on their online shopping behavior in China.

This paper examines consumers’ online shopping frequency for food/grocery using an ordered logit model and for fresh food (a subcategory of food/grocery) using a two-part model, considering product attributes, e-vendor characteristics, and consumer perceptions and characteristics.

The results show that product origin is an influencing factor in shopping for fresh food online, reflecting consumers’ growing interests in imported food or specialty food from other areas. Consumers are more likely to shop online for fresh food if they perceive online shopping as having a price advantage. But consumers who view price as a top factor are less likely to buy fresh food online frequently. Thus competitive prices might be a motive for online fresh food shopping, but consumers concerned about price do not necessarily shop frequently. Negative perceptions of product freshness reduce consumers’ likelihood and frequency of shopping for fresh food online. Concerns on food quality and e-vendors’ credibility prevent consumers from frequently shopping for fresh food online. Social and demographic characteristics also influence consumers’ decisions.

This paper provides a better understanding of consumer’s online grocery shopping preferences and sheds light on policy and regulation design and implementation in the e-commerce industry, which will ultimately protect and benefit consumers.