In the public–private partnership (PPP) supply chain, trust serves as the foundation for collaboration between investment companies and suppliers. However, due to many uncertain factors, the evolution of trust remains a “black box” phenomenon. In order to analyze the impact of the evolution of trust in the PPP supply chain on investment companies and suppliers’ strategic choices, and promote the healthy and sustainable development of PPP supply chain projects, this paper establishes a trust evolutionary game model, which analyzes the evolutionary paths under different scenarios and explores the impact of parameters on the cooperative strategies of participants. The findings indicate that trust asymmetry or an increase in trust can facilitate investment companies and suppliers to opt for positive cooperation strategies. Furthermore, both parties’ strategies are less influenced by their initial willingness and more by trust degree. The moral risk coefficient and information asymmetry coefficient have a negative effect on the cooperative strategies, with the moral risk coefficient of investment companies exhibiting a more significant impact on the entire cooperation process. Moreover, both parties can only choose positive strategies when the information asymmetry coefficient is low. This study holds significant implications for promoting cooperation, enhancing contract performance, safeguarding the interests of all parties, and increasing cooperation satisfaction.
{"title":"Evolution Mechanism of Public-Private Partnership Project Trust from the Perspective of the Supply Chain","authors":"Huimin Li, Yu Zhang, Mengxuan Liang, Yongchao Cao, Wenjuan Zhang, Limin Su","doi":"10.3390/systems11070379","DOIUrl":"https://doi.org/10.3390/systems11070379","url":null,"abstract":"In the public–private partnership (PPP) supply chain, trust serves as the foundation for collaboration between investment companies and suppliers. However, due to many uncertain factors, the evolution of trust remains a “black box” phenomenon. In order to analyze the impact of the evolution of trust in the PPP supply chain on investment companies and suppliers’ strategic choices, and promote the healthy and sustainable development of PPP supply chain projects, this paper establishes a trust evolutionary game model, which analyzes the evolutionary paths under different scenarios and explores the impact of parameters on the cooperative strategies of participants. The findings indicate that trust asymmetry or an increase in trust can facilitate investment companies and suppliers to opt for positive cooperation strategies. Furthermore, both parties’ strategies are less influenced by their initial willingness and more by trust degree. The moral risk coefficient and information asymmetry coefficient have a negative effect on the cooperative strategies, with the moral risk coefficient of investment companies exhibiting a more significant impact on the entire cooperation process. Moreover, both parties can only choose positive strategies when the information asymmetry coefficient is low. This study holds significant implications for promoting cooperation, enhancing contract performance, safeguarding the interests of all parties, and increasing cooperation satisfaction.","PeriodicalId":52858,"journal":{"name":"syst mt`lyh","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79672527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Recently, smart products have not only demonstrated more functionality and technical capabilities but have also shown a trend towards emotional expression. Emotional design plays a crucial role in smart products as it not only influences users’ perception and evaluation of the product but also promotes collaborative communication between users and the product. In the future, emotional design of smart products needs to be regarded as an important comprehensive design issue, rather than simply targeting a specific element. It should consider factors such as design systems, values, business strategies, technical capabilities, design ethics, and cultural responsibilities. However, currently, there is a lack of a design model that combines these elements. Currently, there are numerous practices in emotional design for smart products from different perspectives. They provide us an opportunity to build a comprehensive design model based on a large number of design case studies. Therefore, this study employed a standardized grounded theory approach to investigate 80 smart products and conducted interviews with 12 designers to progressively code and generate a design model. Through the coding process, this research extracted 547 nodes and gradually formed 10 categories, ultimately resulting in a design model comprising 5 sequential steps. This model includes user requirements, concept definition, design ideation, design implementation, and evaluation, making it applicable to most current and future emotional design issues in smart products.
{"title":"An Emotional Design Model for Future Smart Product Based on Grounded Theory","authors":"Chiju Chao, Yu Chen, Hongfei Wu, Wenxuan Wu, Zhijie Yi, Liang Xu, Zhiyong Fu","doi":"10.3390/systems11070377","DOIUrl":"https://doi.org/10.3390/systems11070377","url":null,"abstract":"Recently, smart products have not only demonstrated more functionality and technical capabilities but have also shown a trend towards emotional expression. Emotional design plays a crucial role in smart products as it not only influences users’ perception and evaluation of the product but also promotes collaborative communication between users and the product. In the future, emotional design of smart products needs to be regarded as an important comprehensive design issue, rather than simply targeting a specific element. It should consider factors such as design systems, values, business strategies, technical capabilities, design ethics, and cultural responsibilities. However, currently, there is a lack of a design model that combines these elements. Currently, there are numerous practices in emotional design for smart products from different perspectives. They provide us an opportunity to build a comprehensive design model based on a large number of design case studies. Therefore, this study employed a standardized grounded theory approach to investigate 80 smart products and conducted interviews with 12 designers to progressively code and generate a design model. Through the coding process, this research extracted 547 nodes and gradually formed 10 categories, ultimately resulting in a design model comprising 5 sequential steps. This model includes user requirements, concept definition, design ideation, design implementation, and evaluation, making it applicable to most current and future emotional design issues in smart products.","PeriodicalId":52858,"journal":{"name":"syst mt`lyh","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77335347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Government subsidies generally play an important role in the sustainable operations management of a closed-loop supply chain (CLSC). This paper investigates the optimal government subsidy decision and its influence on the sustainable development of the CLSC, consisting of one manufacturer, one retailer, and one third-party collector, from the economic, environmental, and social perspectives. Based on game analysis technology, different Stackelberg game models among the government and the CLSC members are formulated to analyze the optimal decisions under different power structures. By conducting theoretic comparative and sensitivity analyses and a case study, the effects of the government subsidy and the power structure are explored from the total profit, environmental benefit, and social welfare. Results show that the subsidy is good for sustainable development of the CLSC, which improves the total profit of the CLSC members, environmental benefit, and social welfare and the improvement effect is more prominent when the CLSC members have unequal bargaining power. Moreover, according to the growth proportion of profit, the retailer and collector benefit more from the subsidy among the CLSC members when they have different bargaining power, otherwise, the CLSC members benefit equally from the subsidy, and the subsidy is more beneficial to the environment compared with the total supply chain profit and social welfare.
{"title":"Optimal Government Subsidy Decision and Its Impact on Sustainable Development of a Closed-Loop Supply Chain","authors":"Yujie Gu, Menghao Xue, Mingxuan Zhao, Yufu Long","doi":"10.3390/systems11070378","DOIUrl":"https://doi.org/10.3390/systems11070378","url":null,"abstract":"Government subsidies generally play an important role in the sustainable operations management of a closed-loop supply chain (CLSC). This paper investigates the optimal government subsidy decision and its influence on the sustainable development of the CLSC, consisting of one manufacturer, one retailer, and one third-party collector, from the economic, environmental, and social perspectives. Based on game analysis technology, different Stackelberg game models among the government and the CLSC members are formulated to analyze the optimal decisions under different power structures. By conducting theoretic comparative and sensitivity analyses and a case study, the effects of the government subsidy and the power structure are explored from the total profit, environmental benefit, and social welfare. Results show that the subsidy is good for sustainable development of the CLSC, which improves the total profit of the CLSC members, environmental benefit, and social welfare and the improvement effect is more prominent when the CLSC members have unequal bargaining power. Moreover, according to the growth proportion of profit, the retailer and collector benefit more from the subsidy among the CLSC members when they have different bargaining power, otherwise, the CLSC members benefit equally from the subsidy, and the subsidy is more beneficial to the environment compared with the total supply chain profit and social welfare.","PeriodicalId":52858,"journal":{"name":"syst mt`lyh","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73095775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Remote monitoring and maintenance are important for improving the performance of production systems. However, existing studies on this topic usually focus on the monitoring and maintenance of the working conditions of the equipment and pay relatively less attention to the processing craft and processing quality. In addition, as far as we know, there are relatively few industrial case studies on the real applications of remote monitoring and maintenance systems that include both conventional and advanced maintenance techniques under the context of Industry 4.0. Addressing these issues, an industrial case study on the monitoring and maintenance service system for a robot-driven carbon block polishing service system is presented, including its application background and engineering problems, software/hardware architecture and running logic, the monitoring and maintenance-related enabling techniques, and the configuration and operation workflows of the system in the form of screenshots of the functional WebAPPs of the software system. The case study can provide real examples and references for the industrial application of remote monitoring and maintenance service systems on industrial product service systems under the context of Industry 4.0. Advanced techniques such as the Industrial Internet of Things, digital twins, deep learning, and edge/cloud/fog computing have been applied to the system.
{"title":"An Industrial Case Study on the Monitoring and Maintenance Service System for a Robot-Driven Polishing Service System under Industry 4.0 Contexts","authors":"Yuqian Yang, Maolin Yang, Siwei Shangguan, Yifan Cao, Wei Yue, Kaiqiang Cheng, Pingyu Jiang","doi":"10.3390/systems11070376","DOIUrl":"https://doi.org/10.3390/systems11070376","url":null,"abstract":"Remote monitoring and maintenance are important for improving the performance of production systems. However, existing studies on this topic usually focus on the monitoring and maintenance of the working conditions of the equipment and pay relatively less attention to the processing craft and processing quality. In addition, as far as we know, there are relatively few industrial case studies on the real applications of remote monitoring and maintenance systems that include both conventional and advanced maintenance techniques under the context of Industry 4.0. Addressing these issues, an industrial case study on the monitoring and maintenance service system for a robot-driven carbon block polishing service system is presented, including its application background and engineering problems, software/hardware architecture and running logic, the monitoring and maintenance-related enabling techniques, and the configuration and operation workflows of the system in the form of screenshots of the functional WebAPPs of the software system. The case study can provide real examples and references for the industrial application of remote monitoring and maintenance service systems on industrial product service systems under the context of Industry 4.0. Advanced techniques such as the Industrial Internet of Things, digital twins, deep learning, and edge/cloud/fog computing have been applied to the system.","PeriodicalId":52858,"journal":{"name":"syst mt`lyh","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88197129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The anaerobic digestion of sewage sludge in South Korean wastewater treatment plants is affected by seasonal factors and other influences, resulting in lower digestion efficiency and gas production, which cannot reach optimal yields. The aim of this study was to improve the digestion efficiency and gas production of sludge anaerobic digestion in a wastewater treatment plant (WWTP) by using data mining techniques to adjust operational parameters. Through experimental data obtained from the WWTP in Daegu City, South Korea, an artificial neural network (ANN) technology was used to adjust the range of the organic loading rate (OLR) and hydraulic retention rate (HRT) to improve the efficiency and methane gas production from anaerobic sludge digestion. Data sources were normalized, and data analysis including Pearson correlation analysis, multiple regression analysis and an artificial neural network for optimal results. The results of the study showed a predicted 0.5% increase in digestion efficiency and a 1.3% increase in gas production at organic loads of 1.26–1.46 kg/m3 day and an HRT of 26–30 days. This shows that the ANN model that we established is feasible and can be used to improve the efficiency and gas production of sludge anaerobic digestion.
{"title":"Derivation of Optimal Operation Factors of Anaerobic Digesters through Artificial Neural Network Technology","authors":"Yumeng Bao, R. Koutavarapu, Tae‐Gwan Lee","doi":"10.3390/systems11070375","DOIUrl":"https://doi.org/10.3390/systems11070375","url":null,"abstract":"The anaerobic digestion of sewage sludge in South Korean wastewater treatment plants is affected by seasonal factors and other influences, resulting in lower digestion efficiency and gas production, which cannot reach optimal yields. The aim of this study was to improve the digestion efficiency and gas production of sludge anaerobic digestion in a wastewater treatment plant (WWTP) by using data mining techniques to adjust operational parameters. Through experimental data obtained from the WWTP in Daegu City, South Korea, an artificial neural network (ANN) technology was used to adjust the range of the organic loading rate (OLR) and hydraulic retention rate (HRT) to improve the efficiency and methane gas production from anaerobic sludge digestion. Data sources were normalized, and data analysis including Pearson correlation analysis, multiple regression analysis and an artificial neural network for optimal results. The results of the study showed a predicted 0.5% increase in digestion efficiency and a 1.3% increase in gas production at organic loads of 1.26–1.46 kg/m3 day and an HRT of 26–30 days. This shows that the ANN model that we established is feasible and can be used to improve the efficiency and gas production of sludge anaerobic digestion.","PeriodicalId":52858,"journal":{"name":"syst mt`lyh","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80395382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This research proposes a virtual restoration system and method for 3D digital cultural relics based on a fuzzy logic algorithm, aiming to solve the problems of the low classification accuracy and poor splicing effect of Terra Cotta Warrior fragments. This method adopts a series of steps to improve the efficiency and accuracy of fragment splicing. Firstly, features such as curvature, torsion, and left and right chord lengths were extracted from the fracture surface contour lines of the cultural relic fragments to form feature vectors. Then, the feature vector was fused and compressed by using the multilayer perceptron. The multilayer perceptron is a neural network model that can process and learn input data via multiple levels of computation, resulting in more expressive feature representations. Next, we used the calculation results of the multilayer perceptron to perform the splicing operation on the fragments. This means that, based on the calculation results of the feature vectors, the system can automatically select appropriate splicing methods to accurately match and splice fragments. Finally, by adjusting the weight of the multilayer perceptron, the error rate of fragment splicing can be reduced, further improving the accuracy of repair. The experimental results show that the method proposed in this article is significantly better than traditional methods in terms of time consumption and can effectively improve the efficiency of fragment matching and stitching. Conclusion: The fragment-stitching algorithm based on multi-feature adaptive fusion improved the speed and effectiveness of stitching in fragment-stitching tasks. In summary, the fragment-stitching algorithm based on multi-feature adaptive fusion can improve the speed and effectiveness of stitching in fragment-stitching tasks. The application of this method is expected to play an important role in the field of cultural relic protection, such as the restoration of Terra Cotta Warrior fragments.
{"title":"Virtual Restoration System for 3D Digital Cultural Relics Based on a Fuzzy Logic Algorithm","authors":"Feng Li, Yongli Gao, A. Candeias, Yao Wu","doi":"10.3390/systems11070374","DOIUrl":"https://doi.org/10.3390/systems11070374","url":null,"abstract":"This research proposes a virtual restoration system and method for 3D digital cultural relics based on a fuzzy logic algorithm, aiming to solve the problems of the low classification accuracy and poor splicing effect of Terra Cotta Warrior fragments. This method adopts a series of steps to improve the efficiency and accuracy of fragment splicing. Firstly, features such as curvature, torsion, and left and right chord lengths were extracted from the fracture surface contour lines of the cultural relic fragments to form feature vectors. Then, the feature vector was fused and compressed by using the multilayer perceptron. The multilayer perceptron is a neural network model that can process and learn input data via multiple levels of computation, resulting in more expressive feature representations. Next, we used the calculation results of the multilayer perceptron to perform the splicing operation on the fragments. This means that, based on the calculation results of the feature vectors, the system can automatically select appropriate splicing methods to accurately match and splice fragments. Finally, by adjusting the weight of the multilayer perceptron, the error rate of fragment splicing can be reduced, further improving the accuracy of repair. The experimental results show that the method proposed in this article is significantly better than traditional methods in terms of time consumption and can effectively improve the efficiency of fragment matching and stitching. Conclusion: The fragment-stitching algorithm based on multi-feature adaptive fusion improved the speed and effectiveness of stitching in fragment-stitching tasks. In summary, the fragment-stitching algorithm based on multi-feature adaptive fusion can improve the speed and effectiveness of stitching in fragment-stitching tasks. The application of this method is expected to play an important role in the field of cultural relic protection, such as the restoration of Terra Cotta Warrior fragments.","PeriodicalId":52858,"journal":{"name":"syst mt`lyh","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88816191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhifeng Wang, Jialong Yao, Chunyan Zeng, Longlong Li, Cheng Tan
Artificial intelligence (AI) and computer vision technologies have gained significant prominence in the field of education. These technologies enable the detection and analysis of students’ classroom behaviors, providing valuable insights for assessing individual concentration levels. However, the accuracy of target detection methods based on Convolutional Neural Networks (CNNs) can be compromised in classrooms with multiple targets and varying scales, as convolutional operations may result in the loss of location information. In contrast, transformers, which leverage attention mechanisms, have the capability to learn global features and mitigate the information loss caused by convolutional operations. In this paper, we propose a students’ classroom behavior detection system that combines deformable DETR with a Swin Transformer and light-weight Feature Pyramid Network (FPN). By employing a feature pyramid structure, the system can effectively process multi-scale feature maps extracted by the Swin Transformer, thereby improving the detection accuracy for targets of different sizes and scales. Moreover, the integration of the CARAFE lightweight operator into the FPN structure enhances the network’s detection accuracy. To validate the effectiveness of our approach, extensive experiments are conducted on a real dataset of students’ classroom behavior. The experimental results demonstrate a significant 6.1% improvement in detection accuracy compared to state-of-the-art methods. These findings highlight the superiority of our proposed network in accurately detecting and analyzing students’ classroom behaviors. Overall, this research contributes to the field of education by addressing the limitations of CNN-based target detection methods and leveraging the capabilities of transformers to improve accuracy. The proposed system showcases the benefits of integrating deformable DETR, Swin Transformer, and the lightweight FPN in the context of students’ classroom behavior detection. The experimental results provide compelling evidence of the system’s effectiveness and its potential to enhance classroom monitoring and assessment practices.
{"title":"Students' Classroom Behavior Detection System Incorporating Deformable DETR with Swin Transformer and Light-Weight Feature Pyramid Network","authors":"Zhifeng Wang, Jialong Yao, Chunyan Zeng, Longlong Li, Cheng Tan","doi":"10.3390/systems11070372","DOIUrl":"https://doi.org/10.3390/systems11070372","url":null,"abstract":"Artificial intelligence (AI) and computer vision technologies have gained significant prominence in the field of education. These technologies enable the detection and analysis of students’ classroom behaviors, providing valuable insights for assessing individual concentration levels. However, the accuracy of target detection methods based on Convolutional Neural Networks (CNNs) can be compromised in classrooms with multiple targets and varying scales, as convolutional operations may result in the loss of location information. In contrast, transformers, which leverage attention mechanisms, have the capability to learn global features and mitigate the information loss caused by convolutional operations. In this paper, we propose a students’ classroom behavior detection system that combines deformable DETR with a Swin Transformer and light-weight Feature Pyramid Network (FPN). By employing a feature pyramid structure, the system can effectively process multi-scale feature maps extracted by the Swin Transformer, thereby improving the detection accuracy for targets of different sizes and scales. Moreover, the integration of the CARAFE lightweight operator into the FPN structure enhances the network’s detection accuracy. To validate the effectiveness of our approach, extensive experiments are conducted on a real dataset of students’ classroom behavior. The experimental results demonstrate a significant 6.1% improvement in detection accuracy compared to state-of-the-art methods. These findings highlight the superiority of our proposed network in accurately detecting and analyzing students’ classroom behaviors. Overall, this research contributes to the field of education by addressing the limitations of CNN-based target detection methods and leveraging the capabilities of transformers to improve accuracy. The proposed system showcases the benefits of integrating deformable DETR, Swin Transformer, and the lightweight FPN in the context of students’ classroom behavior detection. The experimental results provide compelling evidence of the system’s effectiveness and its potential to enhance classroom monitoring and assessment practices.","PeriodicalId":52858,"journal":{"name":"syst mt`lyh","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76504708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Reza Behinfaraz, Abdolmehdi Bagheri, A. A. Ghavifekr, Paolo Visconti
Risk analysis in control problems is a critical but often overlooked issue in this research area. The main goal of this analysis is to assess the reliability of designed controllers and their impact on applied systems. The chaotic behavior of fractional-order economical systems has been extensively investigated in previous studies, leading to advancements in such systems. However, this chaotic behavior poses unpredictable risks to the economic system. This paper specifically investigates the reliability and risk analysis of chaotic fractional-order systems synchronization. Furthermore, we present a technique as a new mechanism to evaluate controller performance in the presence of obvious effects. Through a series of simulation studies, the reliability and risk associated with the proposed controllers are illustrated. Ultimately, we show that the suggested technique effectively reduces the risks associated with designed controllers.
{"title":"Risk Control for Synchronizing a New Economic Model","authors":"Reza Behinfaraz, Abdolmehdi Bagheri, A. A. Ghavifekr, Paolo Visconti","doi":"10.3390/systems11070373","DOIUrl":"https://doi.org/10.3390/systems11070373","url":null,"abstract":"Risk analysis in control problems is a critical but often overlooked issue in this research area. The main goal of this analysis is to assess the reliability of designed controllers and their impact on applied systems. The chaotic behavior of fractional-order economical systems has been extensively investigated in previous studies, leading to advancements in such systems. However, this chaotic behavior poses unpredictable risks to the economic system. This paper specifically investigates the reliability and risk analysis of chaotic fractional-order systems synchronization. Furthermore, we present a technique as a new mechanism to evaluate controller performance in the presence of obvious effects. Through a series of simulation studies, the reliability and risk associated with the proposed controllers are illustrated. Ultimately, we show that the suggested technique effectively reduces the risks associated with designed controllers.","PeriodicalId":52858,"journal":{"name":"syst mt`lyh","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83275684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
It is important to explore the intrinsic mechanism of green finance’s role in widening the green development space for China, in order to optimize the structure of green financial development and accelerate the construction of a modernized economic system. Taking ecological environment improvement as a new research perspective, this paper presents the impacts and mechanisms of green finance on the green development space of the economy and society through the fixed-effect model and moderating-effect model, based on panel data from 30 provinces and municipalities in China from 2011 to 2020. The findings show that green finance development in China significantly expands the green development space of the economy and society, and this conclusion did not change after robustness tests such as replacing the main variables, adjusting the study interval, and considering endogeneity. In terms of its mechanism of action, ecological environment improvement plays an important mediating and regulating role in the process of green finance, essentially magnifying the green development space of the economy and society. In terms of a heterogeneity analysis, the effect of green finance on the expansion of the green development space is the largest in the eastern region, followed by the northeastern region, and the smallest in the central and western regions. In addition, the positive effect of green finance is relatively larger in regions with a higher urbanization level, government fiscal expenditure level, foreign investment level, and advanced industrial structure. The main contribution of this paper is to the field of green development, revealing the important role of the ecological benefits of green finance, which can help to achieve high-quality sustainable development in the economy and society.
{"title":"Does Green Finance Expand China's Green Development Space? Evidence from the Ecological Environment Improvement Perspective","authors":"Zhe Wang, Yin-Pei Teng, Shuzhao Wu, Huangxin Chen","doi":"10.3390/systems11070369","DOIUrl":"https://doi.org/10.3390/systems11070369","url":null,"abstract":"It is important to explore the intrinsic mechanism of green finance’s role in widening the green development space for China, in order to optimize the structure of green financial development and accelerate the construction of a modernized economic system. Taking ecological environment improvement as a new research perspective, this paper presents the impacts and mechanisms of green finance on the green development space of the economy and society through the fixed-effect model and moderating-effect model, based on panel data from 30 provinces and municipalities in China from 2011 to 2020. The findings show that green finance development in China significantly expands the green development space of the economy and society, and this conclusion did not change after robustness tests such as replacing the main variables, adjusting the study interval, and considering endogeneity. In terms of its mechanism of action, ecological environment improvement plays an important mediating and regulating role in the process of green finance, essentially magnifying the green development space of the economy and society. In terms of a heterogeneity analysis, the effect of green finance on the expansion of the green development space is the largest in the eastern region, followed by the northeastern region, and the smallest in the central and western regions. In addition, the positive effect of green finance is relatively larger in regions with a higher urbanization level, government fiscal expenditure level, foreign investment level, and advanced industrial structure. The main contribution of this paper is to the field of green development, revealing the important role of the ecological benefits of green finance, which can help to achieve high-quality sustainable development in the economy and society.","PeriodicalId":52858,"journal":{"name":"syst mt`lyh","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78678097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The main paths of the knowledge diffusion network can reveal the important actors and diffusion process, which has an important significance in improving the efficiency of knowledge diffusion. Due to the independent path choice of project actors, knowledge diffusion networks show a dynamic characteristic in collaborative innovation projects. Taking into account this dynamic characteristic, dynamic main path analysis method for project context is proposed. The method, constructed by MATLAB simulation modeling, proposes calculation index and analysis strategies. Contrastive application of two main types of path analysis (the main path analysis method and dynamic main path analysis method) is carried out through a collaborative innovation project case, in order to verify the effectiveness and applicability of this method. The comparison results show that the main paths identified by the new method are more consistent with the actual main paths in knowledge diffusion practice, and the level of knowledge flow through main paths is higher. Therefore, our conclusion is that the dynamic main path analysis method proposed in this research has high applicability and accuracy for identifying the main paths in the collaborative innovation projects.
{"title":"A Method to Identify Main Paths of Knowledge Diffusion for Collaborative Innovation Projects","authors":"Lei Xu, Hu Tao, Shanshan Liu, Lei Wang","doi":"10.3390/systems11070370","DOIUrl":"https://doi.org/10.3390/systems11070370","url":null,"abstract":"The main paths of the knowledge diffusion network can reveal the important actors and diffusion process, which has an important significance in improving the efficiency of knowledge diffusion. Due to the independent path choice of project actors, knowledge diffusion networks show a dynamic characteristic in collaborative innovation projects. Taking into account this dynamic characteristic, dynamic main path analysis method for project context is proposed. The method, constructed by MATLAB simulation modeling, proposes calculation index and analysis strategies. Contrastive application of two main types of path analysis (the main path analysis method and dynamic main path analysis method) is carried out through a collaborative innovation project case, in order to verify the effectiveness and applicability of this method. The comparison results show that the main paths identified by the new method are more consistent with the actual main paths in knowledge diffusion practice, and the level of knowledge flow through main paths is higher. Therefore, our conclusion is that the dynamic main path analysis method proposed in this research has high applicability and accuracy for identifying the main paths in the collaborative innovation projects.","PeriodicalId":52858,"journal":{"name":"syst mt`lyh","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81077810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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