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Traditional Korean buildings do not differ significantly in form or structural style according to era or building type. The authors interpret this from a generative rather than a typological perspective. The generation perspective considers factors forming the buildings and is connected to the prevailing thoughts of the era.

This study analyzes the generation method of seowon facilities in the Joseon Dynasty (1392–1897), focusing on the Dosan Seowon. Based on Koreans' long-term thinking, the authors applied the extracted architectural space generation layers for analysis, and present an integrated method of generation layers when the Dosan Seowon was built.

The immanent, physical and body perceptual layers presented for seowon formation analysis are represented by thought, form and territory. Specific aspects of these layers in the Dosan Seowon are analyzed, including the architectural arrangement that connects the land conditions with neo-Confucian courtesy and order, the collective architectural form considering the energy of yin and yang, and the elements of objects that affect the human body perception. This form of architecture was closely linked with and strongly influenced by monistic philosophy.

After the Korean War, architects judged traditional buildings only by shapes, and quickly accepted Western architecture's forms. Presenting a generative perspective of traditional Korean architecture expands the theoretical research direction of modern succession.

This is the first attempt to examine the generation method based on the Dosan Seowon's generation layers.

High-resolution remote sensing images possess a wealth of semantic information. However, these images often contain objects of different sizes and distributions, which make the semantic segmentation task challenging. In this paper, a bidirectional feature fusion network (BFFNet) is designed to address this challenge, which aims at increasing the accurate recognition of surface objects in order to effectively classify special features.

There are two main crucial elements in BFFNet. Firstly, the mean-weighted module (MWM) is used to obtain the key features in the main network. Secondly, the proposed polarization enhanced branch network performs feature extraction simultaneously with the main network to obtain different feature information. The authors then fuse these two features in both directions while applying a cross-entropy loss function to monitor the network training process. Finally, BFFNet is validated on two publicly available datasets, Potsdam and Vaihingen.

In this paper, a quantitative analysis method is used to illustrate that the proposed network achieves superior performance of 2–6%, respectively, compared to other mainstream segmentation networks from experimental results on two datasets. Complete ablation experiments are also conducted to demonstrate the effectiveness of the elements in the network. In summary, BFFNet has proven to be effective in achieving accurate identification of small objects and in reducing the effect of shadows on the segmentation process.

The originality of the paper is the proposal of a BFFNet based on multi-scale and multi-attention strategies to improve the ability to accurately segment high-resolution and complex remote sensing images, especially for small objects and shadow-obscured objects.

The desire of international retail brands to implement sustainable supply chain practices in the fashion value chain and improve suppliers' sustainability efforts; this research paper elucidates the relationship between blockchain technology and sustainability to impact apparel firms' triple bottom line.

For studying the impact of sustainable supply chain practices on the triple bottom line, a survey questionnaire was chosen and sent out to 500 garment companies simultaneously, of which 371 responded. The data collected is cross-sectional. The questionnaire survey was developed keeping in mind a few demographic elements such as experience, age and qualification to generalize the findings. For analysis, SmartPLS is used to run model structuring and regression analysis.

Test runs on model structure confirm the instrument's validity and reliability. Bootstrapping on the theoretical model to test developed hypotheses suggests that supply chain sustainability practices positively affect social, environmental and economic performance in a direct relationship. Further, indirect relation testing conducted to test blockchain technology's moderation influences only the constructs' relations.

The clubbing of sustainable supply chain practices and blockchain technology is a novel idea in the apparel industry; however, there are more constructs in the context of practice-based theory and supply chain which impact firm performance. Also, the research limits itself from discussing IT infrastructure and smart contract types that impact the technology's performance.

The study provides a framework for interpreting the synergetic influence of SSCP on firm social, environmental and economic performances, which is demanded both by consumers and regulators in an industry. The results suggest that managers sustainably design the production ecosystem, thus eliminating any discrepancy or slackness in the complete chain. Usually, suppliers are ignored, which are precursors in implementing SSCP.

The paper studies sustainability problems through ecological modernization theory and practical-based theory giving a unique perspective on the issue faced by the apparel industry and combining sustainable supply chain practices and blockchain.

The aim of this study is to first investigate the surface integrity of cylindrical rollers under grinding process and then design a reasonable superfinishing process that improve the anti-fatigue performance of cylindrical rollers by optimization of the surface integrity.

First, the white and dark layers produced by the grinding process is analyzed by microscope. Then, the influence of oilstone pressure on the stock removal, surface precision and crowned profile are explored. Finally, an optimal superfinishing process and a novel turnaround device are designed to improve surface integrity.

The experimental results show that as the oilstone pressure increases, the stock removal first increases and then remains stable. This hints that the stock removal of a single-time superfinishing process has an upper limit. In the current conditions, the maximum stock removal is 6 µm. Double-time superfinishing process and the turnover device can effectively eliminate the white and dark layers and improve the symmetric of roller profile. In addition, the surface precision is also improved.

The surface integrity of bearing rollers is very important to the application of industry field. The findings and the methods in the study can be helpful to improve the surface integrity of the bearing rollers.

This paper aims to further develop stator permanent magnet (PM) type memory machines by providing generalized design guidelines for double-stator memory machines (DSMMs) with hybrid PMs. This paper discusses the design experience of DSMMs and presents a comparative study of radial magnetization (RM) and circumferential magnetization (CM) types.

It begins with an introduction to RM and CM operating principles and magnetization mechanisms. Then, a comparative study is conducted for one of the RM-DSMM rotor pole pairs, inner and outer stator clamping angles and low coercive force PMs thickness. Finally, the two machines’ finite element simulation performance is compared. The validity of the proposed machine structure is demonstrated.

In this paper, the double-stator structure is extended to parallel hybrid PM memory machines, and two novel DSMMs with RM and CM configurations are proposed. Two types of DSMMs have PMs and magnetizing windings on the inner stator and armature windings on the outer stator. The main difference between the two is the arrangement of PMs on the inner stator.

Conventional stator PM memory machines have geometrical space conflicts between the PM and armature windings. The proposed double-stator structure can alleviate these conflicts and increase the torque density accordingly. In addition, this paper contributes to comparing the arrangement of hybrid PMs for DSMMs.

In the stock market, herding behavior occurs when investors mimic the actions of others in their investment decisions. As a result, the market becomes inefficient and speculative bubbles form. This study aims to investigate the relationship between information, overconfidence, market sentiment, experience and national culture, and herding behavior among Malaysian investors. A total of 400 questionnaires are distributed to bank institutions' investors. The survey design based on cross-sectional data is analyzed using the Partial Least Squares Structural Equation Model. The results indicate that information, market sentiment, experience, and national culture are positively related to herding behavior, while overconfidence has no effect. With this, the government should strengthen regulations to prevent the dissemination of misleading information. Moreover, investors are encouraged to overcome narrow thinking by expanding their understanding of different cultures when making investment decisions.

This study aims to use event system theory and job demands–resources (JD-R) model to examine the double-edged sword effect of event strength of Beijing Winter Olympics (BWO) on volunteers’ in-role performance and proactive behavior as mediated by work overload and meaningfulness.

The sample included 193 volunteer–leader dyads working at one BWO venue. The authors conducted a multitime and multisource study using Mplus 8 to examine the hypotheses.

Volunteers’ perceived BWO event strength was positively related to work overload, which reduced in-role performance and proactive behavior. Volunteers’ perceived BWO event strength was also positively related to work meaningfulness, which promoted in-role performance and proactive behavior. Perceived organizational support served as a moderator by mitigating the positive relationship between perceived BWO event strength and work overload; however, it did not strengthen the positive relationship between perceived BWO event strength and work meaningfulness.

This study developed a comprehensive model of how BWO event strength affected volunteers’ performance from the perspective of event system theory and the JD-R model, which enriches theoretical application and research in the context of mega sport events.

本研究运用事件系统理论和工作需求-资源(JD-R)模型, 探讨了2022年北京冬奥会（BWO）事件强度通过工作负荷和工作意义感知进而对志愿者角色内绩效和主动性行为的双刃剑效应。

我们在冬奥会场所之一实施了多时点、多来源的收集数据的方式, 最终样本包括193份志愿者-领导配对数据, 并使用Mplus 8来检验我们的假设。

志愿者感知的BWO事件强度与工作负荷呈正相关, 进而会降低他们的角色内绩效和主动性行为。志愿者感知的BWO事件强度与工作意义感也呈正相关, 进而会促进他们的角色内绩效和主动性行为。感知的组织支持通过弱化BWO事件强度与工作负荷之间的正相关关系, 进而调节了志愿者的角色内绩效和主动性行为; 然而, 感知的组织支持并没有强化BWO事件强度与工作意义感之间的正相关关系。

本研究结合事件系统理论和JD-R模型, 发展了一个BWO事件强度对志愿者绩效表现影响的综合模型, 丰富了有关大型体育赛事志愿者的理论应用和研究。

Este estudio utiliza la teoría del sistema de eventos y el modelo de demandas de trabajo-recursos (JD-R) para examinar el efecto de doble filo de la fuerza del evento de los Juegos Olímpicos de Invierno de Pekín (BWO) sobre el rendimiento en el rol y el comportamiento proactivo de los voluntarios, mediado por la sobrecarga laboral y la significatividad del trabajo.

Nuestra muestra incluyó 193 díadas de voluntarios-líderes que trabajaban en una sede de BWO. Realizamos un estudio multitemporal y multifuente utilizando Mplus 8 para examinar nuestras hipótesis.

La intensidad percibida por los voluntarios en los eventos de BWO también se relacionó positivamente con la significación del trabajo, que promovió el rendimiento en el rol y el comportamiento proactivo. Además, el apoyo organizativo percibido sirvió como moderador al mitigar la relación positiva entre la intensidad percibida del evento BWO y la sobrecarga de trabajo; sin embargo, no reforzó la relación positiva entre la intensidad percibida del evento BWO y la significatividad del trabajo.

Este estudio desarrolló un modelo integral de cómo la fuerza del evento BWO afectaba al rendimiento de los voluntarios desde la perspectiva de la teoría del sistema de eventos y el modelo JD-R, lo que enriquece la aplicación teórica y la investigación en el contexto de los megaeventos deportivos.

Based on the principal–agent and stakeholder theories, this study aims to put forward an intermediary model to verify the intermediary role of corporate social responsibility (CSR) in executive equity incentives and corporate innovation performance to improve corporate innovation performance.

The 2012–2018 A-share listed companies’ disclosure of executive equity incentives data was used as the research sample. This study used CSR as an intermediary to explore the relationship between executive equity incentives and corporate innovation performance. A verification analysis was carried out.

The research results show that: a positive correlation exists between executive equity incentives and corporate innovation performance, and executives’ reasonable equity incentives can promote the growth of corporate innovation performance. A positive correlation exists between executive equity incentives and CSR. Implementing equity incentives for executives can stimulate their motivation to assume CSR. A positive correlation exists between CSR and corporate innovation performance. The more a company fulfills its social responsibility, the more it can promote the improvement of corporate innovation performance. CSR plays a mediating role between executive equity incentives and corporate innovation performance. CSR promotes executive equity incentives’ impact on corporate innovation performance and exerts a “complete mediating effect” between the two.

The number of samples and the time span of samples can be expanded in the future. This research has tested the mediating effect of CSR, but other mediating variables may play a role in the process of executive equity incentives in promoting corporate innovation performance. Further research should be conducted to explore the mediating effect of financing constraints and media attention on corporate innovation performance. This study only verifies the influence of equity incentives on CSR and innovation performance of senior executives. In the future, other incentive methods should be explored, such as salary incentives.

Foreign research on equity incentives has matured, but the experience of foreign countries cannot necessarily produce the expected effect in China. More than ten years have passed since the China A-share market began implementing equity incentives on December 31, 2005. As of December 31, 2017, about one-third of enterprises in the high-tech industry that had introduced equity incentives had stopped implementing the policy. Data from 2012 to 2018 were selected to analyze the relationship between executive equity incentives, CSR and corporate innovation performance to explore the influence mechanism of equity incentives. This study provides a comprehensive theoretical framework to examine the interaction among executive equity incentives, CSR and corporate innovation performance. Because most previous studies have focused on the relationship between executive equity incentives, CSR and corporate innovation performance, they are rarely been used as an intermediary variable to explore the impact of executive equity incentives on corporate innovation performance. This study explores the impact of executive equity incentives on corporate innovation performance under the influence of CSR. Moreover, this study explores the mediating role of CSR in corporate governance, which provides a new perspective for CSR research and verifies relevant literature on the mediating effect model.

Research countermeasures and suggestions: the research results are significant for enterprises implementing executive equity incentives, fulfilling CSR, enhancing corporate reputation, improving corporate innovation performance and ultimately obtaining market competitiveness. Therefore, the following suggestions are proposed: establish and improve the executive equity incentive mechanism and strengthen the promotion effect of executive equity incentives in CSR and corporate innovation performance. Strengthen the awareness of enterprises to actively fulfill CSR and give full play to the role of CSR in promoting corporate innovation performance. Improve the profitability of enterprises and focus on the promotion effect of enterprise profitability on corporate innovation performance.

This study focuses on executive equity incentives and introduces CSR as an intermediary variable to explore the influence path of executive equity incentives on corporate innovation performance. Based on the research results, this study takes targeted measures to improve corporate innovation performance and maintain its healthy growth of corporate innovation performance. This is significant in enhancing enterprises’ core competitiveness and promoting the enterprise economy’s sustainable development. Meanwhile, the enterprise has significant reference value in actively fulfilling its CSR and realizing its stable and healthy development.

The paper aims to propose an innovative two-stage decision model to address the sustainable-resilient supplier selection and order allocation (SSOA) problem in the single-valued neutrosophic (SVN) environment.

First, the sustainable and resilient performances of suppliers are evaluated by the proposed integrated SVN-base-criterion method (BCM)-an acronym in Portuguese of interactive and multi-criteria decision-making (TODIM) method, with consideration of the uncertainty in the decision-making process. Then, a novel multi-objective optimization model is formulated, and the best sustainable-resilient order allocation solution is found using the U-NSGA-III algorithm and TOPSIS method. Finally, based on a real-life case in the automotive manufacturing industry, experiments are conducted to demonstrate the application of the proposed two-stage decision model.

The paper provides an effective decision tool for the SSOA process in an uncertain environment. The proposed SVN-BCM-TODIM approach can effectively handle the uncertainties from the decision-maker’s confidence degree and incomplete decision information and evaluate suppliers’ performance in different dimensions while avoiding the compensatory effect between criteria. Moreover, the proposed order allocation model proposes an original way to improve sustainable-resilient procurement values.

The paper provides a supplier selection process that can effectively integrate sustainability and resilience evaluation in an uncertain environment and develops a sustainable-resilient procurement optimization model.

As a common form of failure in industry, corrosion causes huge economic losses. At present, with the development of computational techniques, artificial intelligence (AI) is playing a more and more important role in the field of scientific research. This paper aims to review the application of AI in corrosion protection research.

In this paper, the role of AI in corrosion protection is systematically described in terms of anticorrosion materials and methods, corrosion image recognition and corrosion life prediction.

With efficient and in-depth data processing methods, AI can rapidly advance the research process in terms of anticorrosion materials and methods, corrosion image recognition and corrosion life prediction and save on costs.

This paper summarizes the application of AI in corrosion protection research and provides the basis for corrosion engineers to quickly and comprehensively understand the role of AI and improve production processes.