Against the backdrop of active global responses to climate change and the accelerated green and low-carbon energy transition,the co-optimization and innovative mechanism design of multimodal energy systems have become...Against the backdrop of active global responses to climate change and the accelerated green and low-carbon energy transition,the co-optimization and innovative mechanism design of multimodal energy systems have become a significant instrument for propelling the energy revolution and ensuring energy security.Under increasingly stringent carbon emission constraints,how to achieve multi-dimensional improvements in energy utilization efficiency,renewable energy accommodation levels,and system economics-through the intelligent coupling of diverse energy carriers such as electricity,heat,natural gas,and hydrogen,and the effective application of market-based instruments like carbon trading and demand response-constitutes a critical scientific and engineering challenge demanding urgent solutions.展开更多
This paper begins with a discussion of the trust issues that agricultural supply chain finance faces.It then examines the constraints of using blockchain technology to enhance trust in agricultural supply chain financ...This paper begins with a discussion of the trust issues that agricultural supply chain finance faces.It then examines the constraints of using blockchain technology to enhance trust in agricultural supply chain finance in accordance with the technological and institutional logic of combining blockchain with supply chains.This study then proposes the creation of an agricultural“blockchain+supply chain”information service platform and a financing trust mechanism that can effectively ensure the authenticity of the initial information input on the blockchain,consistency between on-chain transaction data and off-chain physical transactions,the controllability of risks in the set up and execution of smart contracts,and the removal of information constraints,resource allocation constraints,and institutional constraints in the agricultural supply chain financing.This aims to improve the efficiency of financing in agricultural supply chains and contribute to the industrial development of rural areas and rural revitalization.展开更多
This study aimed to identify and compensate for the geometric errors of the double swiveling axes in a five-axis computer numerical control(CNC)machining center.Hence,a three-dimensional coordinate calculation algorit...This study aimed to identify and compensate for the geometric errors of the double swiveling axes in a five-axis computer numerical control(CNC)machining center.Hence,a three-dimensional coordinate calculation algorithm for a measured point with additional rotational rigid body motion constraints is proposed.The motion constraints of the rotational rigid body were analyzed,and a mathematical model of the measured point algorithm in the swiveling axes was established.The Levenberg-Marquard method was used to solve the nonlinear superstatically determined equations.The spatial coordinate error was used to separate the spatial deviation of the measured point.An identification model of the position-independent and position-dependent geometric errors was established.The three-dimensional coordinate-solving algorithm of the measured point in the swiveling axis and geometric error identification method based on the Monte Carlo method were analyzed numerically.Geometric error measurement and cutting experiments were performed on a VMC25100U five-axis machining center,which integrated two swiveling axes.Geometric errors of the A-and B-axes were identified and measured experimentally.The angular positioning errors before and after compensation were measured using a laser interferometer,which verified the effectiveness of the proposed algorithm.A cutting experiment of a round table part was performed.The shape and position accuracy of the processed part before and after compensation were detected using a coordinate measuring machine.It verified that the geometric error of the swiveling axis was effectively compensated by the algorithm proposed herein.展开更多
This study examines the moderating role of entrepreneurs’creative cognitive styles in the relationship between resource constraints and bricolage.Drawing on insights from cognitive psychology and entrepreneurial rese...This study examines the moderating role of entrepreneurs’creative cognitive styles in the relationship between resource constraints and bricolage.Drawing on insights from cognitive psychology and entrepreneurial research,we explore how divergent and convergent thinking influence the extent to which entrepreneurs engage in bricolage under resource limitations.Bricolage refers to the creative recombination of available resources to address challenges and seize opportunities,a process often adopted by firms facing financial or knowledge constraints.Yet,individual cognitive differences may determine how effectively entrepreneurs can employ bricolage as a strategic response to scarcity.We propose that divergent thinking—the capacity to generate multiple creative solutions and identify novel resource combinations—strengthens the positive association between resource constraints and bricolage.In contrast,convergent thinking,which emphasizes logical analysis and the pursuit of a single optimal solution,weakens this association.To test these propositions,we collected survey data from 183 entrepreneurs in the United States and employed moderated regression analyses to examine the interactions among cognitive styles,resource constraints,and bricolage behaviors.Our findings reveal that divergent thinking significantly enhances the effect of both financial and knowledge constraints on bricolage,enabling entrepreneurs to creatively leverage limited resources.Conversely,convergent thinking appears to diminish the likelihood of engaging in bricolage when resources are scarce.These results highlight the importance of individual cognitive styles in shaping strategic responses to resource scarcity and contribute to a more nuanced understanding of entrepreneurial bricolage.The study offers practical implications for firms operating in resource-constrained environments by suggesting that enhancing divergent thinking abilities may facilitate more effective resource recombination.Future research should investigate additional cognitive factors and employ longitudinal designs to capture the dynamic nature of entrepreneurial decision-making.These insights open new avenues for further innovative entrepreneurial practices.展开更多
In machine vision,elliptical targets frequently appear within the camera's region of interest(ROI).Ellipse detection is essential for shape detection and geometric measurements in machine vision.However,existing e...In machine vision,elliptical targets frequently appear within the camera's region of interest(ROI).Ellipse detection is essential for shape detection and geometric measurements in machine vision.However,existing ellipse detection algorithms often face issues such as high computational complexity,strong dependence on initial conditions,sensitivity to noise,and lack of robustness to occlusions.In this paper,we propose a fast and robust ellipse detection method to address these challenges.This method first utilizes edge gradient and curvature information to segment the curve into circular arcs.Next,based on the convexity of the arcs,it divides them into different quadrants of the ellipse,groups and fits the arcs according to multiple geometric constraints at a low computational cost.Finally,it reduces the parameter space for hierarchical clustering and then segments the complete ellipse into several sectors for verification.We compare our method across seven datasets,including five public image datasets and two from industrial camera scenes.Experimental results show that our method achieves a precision ranging from 67.1%to 98.9%,a recall ranging from 48.1%to 92.9%,and an F-measure ranging from 58.0%to 95.8%.The average execution time per image ranges from 25 ms to 192 ms,demonstrating both high accuracy and efficiency.展开更多
Learning from demonstration is widely regarded as a promising paradigm for robots to acquire diverse skills.Other than the artificial learning from observation-action pairs for machines,humans can learn to imitate in ...Learning from demonstration is widely regarded as a promising paradigm for robots to acquire diverse skills.Other than the artificial learning from observation-action pairs for machines,humans can learn to imitate in a more versatile and effective manner:acquiring skills through mere“observation”.Video to Command task is widely perceived as a promising approach for task-based learning,which yet faces two key challenges:(1)High redundancy and low frame rate of fine-grained action sequences make it difficult to manipulate objects robustly and accurately.(2)Video to Command models often prioritize accuracy and richness of output commands over physical capabilities,leading to impractical or unsafe instructions for robots.This article presents a novel Video to Command framework that employs multiple data associations and physical constraints.First,we introduce an object-level appearancecontrasting multiple data association strategy to effectively associate manipulated objects in visually complex environments,capturing dynamic changes in video content.Then,we propose a multi-task Video to Command model that utilizes object-level video content changes to compile expert demonstrations into manipulation commands.Finally,a multi-task hybrid loss function is proposed to train a Video to Command model that adheres to the constraints of the physical world and manipulation tasks.Our method achieved over 10%on BLEU_N,METEOR,ROUGE_L,and CIDEr compared to the up-to-date methods.The dual-arm robot prototype was established to demonstrate the whole process of learning from an expert demonstration of multiple skills and then executing the tasks by a robot.展开更多
Dear Editor,This letter addresses distributed optimization for resource allocation problems with time-varying objective functions and time-varying constraints.Inspired by the distributed average tracking(DAT)approach,...Dear Editor,This letter addresses distributed optimization for resource allocation problems with time-varying objective functions and time-varying constraints.Inspired by the distributed average tracking(DAT)approach,a distributed control protocol is proposed for optimal resource allocation.The convergence to a time-varying optimal solution within a predefined time is proved.Two numerical examples are given to illustrate the effectiveness of the proposed approach.展开更多
Background As visual simultaneous localization and mapping(SLAM)is primarily based on the assumption of a static scene,the presence of dynamic objects in the frame causes problems such as a deterioration of system rob...Background As visual simultaneous localization and mapping(SLAM)is primarily based on the assumption of a static scene,the presence of dynamic objects in the frame causes problems such as a deterioration of system robustness and inaccurate position estimation.In this study,we propose a YGC-SLAM for indoor dynamic environments based on the ORB-SLAM2 framework combined with semantic and geometric constraints to improve the positioning accuracy and robustness of the system.Methods First,the recognition accuracy of YOLOv5 was improved by introducing the convolution block attention model and the improved EIOU loss function,whereby the prediction frame converges quickly for better detection.The improved YOLOv5 was then added to the tracking thread for dynamic target detection to eliminate dynamic points.Subsequently,multi-view geometric constraints were used for re-judging to further eliminate dynamic points while enabling more useful feature points to be retained and preventing the semantic approach from over-eliminating feature points,causing a failure of map building.The K-means clustering algorithm was used to accelerate this process and quickly calculate and determine the motion state of each cluster of pixel points.Finally,a strategy for drawing keyframes with de-redundancy was implemented to construct a clear 3D dense static point-cloud map.Results Through testing on TUM dataset and a real environment,the experimental results show that our algorithm reduces the absolute trajectory error by 98.22%and the relative trajectory error by 97.98%compared with the original ORBSLAM2,which is more accurate and has better real-time performance than similar algorithms,such as DynaSLAM and DS-SLAM.Conclusions The YGC-SLAM proposed in this study can effectively eliminate the adverse effects of dynamic objects,and the system can better complete positioning and map building tasks in complex environments.展开更多
The rapid development of digital financial inclusion is profoundly changing the financing environment for small and medium-sized enterprises(SMEs).As an important driver of economic growth and innovation,SMEs account ...The rapid development of digital financial inclusion is profoundly changing the financing environment for small and medium-sized enterprises(SMEs).As an important driver of economic growth and innovation,SMEs account for a significant share of employment and GDP globally.However,the traditional bank credit model has long failed to effectively meet the financing needs of SMEs due to issues such as information asymmetry,high cost,and difficulty in risk assessment,resulting in serious financing constraints.Digital financial inclusion,through technological innovation and big data analysis,has significantly reduced credit costs,alleviated information asymmetry,and provided SMEs with more flexible and efficient financing channels.Research shows that digital financial inclusion can not only ease the financing constraints of SMEs,but also promote their innovation and growth,providing important support for building a more inclusive and sustainable financial ecosystem.展开更多
This paper investigates a distributed heterogeneous hybrid blocking flow-shop scheduling problem(DHHBFSP)designed to minimize the total tardiness and total energy consumption simultaneously,and proposes an improved pr...This paper investigates a distributed heterogeneous hybrid blocking flow-shop scheduling problem(DHHBFSP)designed to minimize the total tardiness and total energy consumption simultaneously,and proposes an improved proximal policy optimization(IPPO)method to make real-time decisions for the DHHBFSP.A multi-objective Markov decision process is modeled for the DHHBFSP,where the reward function is represented by a vector with dynamic weights instead of the common objectiverelated scalar value.A factory agent(FA)is formulated for each factory to select unscheduled jobs and is trained by the proposed IPPO to improve the decision quality.Multiple FAs work asynchronously to allocate jobs that arrive randomly at the shop.A two-stage training strategy is introduced in the IPPO,which learns from both single-and dual-policy data for better data utilization.The proposed IPPO is tested on randomly generated instances and compared with variants of the basic proximal policy optimization(PPO),dispatch rules,multi-objective metaheuristics,and multi-agent reinforcement learning methods.Extensive experimental results suggest that the proposed strategies offer significant improvements to the basic PPO,and the proposed IPPO outperforms the state-of-the-art scheduling methods in both convergence and solution quality.展开更多
The biased allocation of emission reduction target constraints quantifies emission reduction responsibilities and reflects differences in pollutant reductions both across and within cities.This approach represents a s...The biased allocation of emission reduction target constraints quantifies emission reduction responsibilities and reflects differences in pollutant reductions both across and within cities.This approach represents a systematic innovation aims to enhance China’s green competitiveness and facilitate its economic transformation through localized and precise policymaking.Using panel data from 275 Chinese cities spanning 2000-2022,this study applies the difference-in-differences method to estimate the impact of biased allocation of emission reduction target constraints on urban green competitiveness.The findings indicate that such constraints-whether based on chemical oxygen demand or sulfur dioxide targets-significantly improve urban green competitiveness,with both pollutant-specific constraints producing comparable effects.Furthermore,these constraints exhibit significant spatial spillover effects within a 200-km geographical radius.Heterogeneity analysis reveals stronger policy impacts in resource-based cities,eastern regions,and cities designated as key areas for pollution prevention and control.Mechanism analysis demonstrates that the constraints enhance green competitiveness primarily by fostering green technological innovation and optimizing industrial structures.These conclusions provide a practical foundation for addressing China’s enduring conflict between environmental protection and economic development.展开更多
Dear Editor,This letter presents a new secure hierarchical control strategy for steering tracking of in-wheel motor driven(IWMD)electric vehicle(EV)subject to limited network resources,hybrid cyber-attacks,model nonli...Dear Editor,This letter presents a new secure hierarchical control strategy for steering tracking of in-wheel motor driven(IWMD)electric vehicle(EV)subject to limited network resources,hybrid cyber-attacks,model nonlinearities,actuator redundancy and airflow disturbance.A hierarchical control architecture is proposed specifically for solving the problems of nonlinear system modeling and actuator redundancy.By utilizing the advantages of fully actuated system(FAS)approach,a nonlinear virtual controller against airflow disturbance is constructed in upper layer system and an event-triggered nonlinear distributed controller is proposed in lower layer system under stochastic hybrid cyber-attacks.A case study of overtaking task is carried out to validate the FAS-based hierarchical control strategy.展开更多
As an important tool to achieve sustainable economic and environmental development,green finance can effectively alleviate the financing constraints of small and medium-sized enterprises(SMEs),especially in promoting ...As an important tool to achieve sustainable economic and environmental development,green finance can effectively alleviate the financing constraints of small and medium-sized enterprises(SMEs),especially in promoting green transformation plays a key role.SMEs play an important role in economic growth,innovation,and job creation,but due to a lack of collateral,imperfect credit history,and opaque financial information,they face great obstacles in the financing process,especially in the early capital investment required for green transformation.Green finance,through innovative financial instruments such as green credit and green bonds,provides new financing channels for SMEs,helping them reduce financing costs,optimize financing structure,and promote their green transformation and sustainable development.This paper analyzes the current situation and root causes of SMEs’financing dilemma from the perspective of green finance,and probes into the influence of green finance policies on financing behavior.展开更多
Dear Editor,Aiming at the consensus tracking problem of a class of unknown heterogeneous nonlinear multiagent systems(MASs)with input constraints,a novel data-driven iterative learning consensus control(ILCC)protocol ...Dear Editor,Aiming at the consensus tracking problem of a class of unknown heterogeneous nonlinear multiagent systems(MASs)with input constraints,a novel data-driven iterative learning consensus control(ILCC)protocol based on zeroing neural networks(ZNNs)is proposed.First,a dynamic linearization data model(DLDM)is acquired via dynamic linearization technology(DLT).展开更多
Dear Editor,This letter investigates the problem of multi-dimension formation tracking(MDFT)for the cross-domain unmanned systems,including several interconnected agents,namely,unmanned aerial vehicles(UAVs)and unmann...Dear Editor,This letter investigates the problem of multi-dimension formation tracking(MDFT)for the cross-domain unmanned systems,including several interconnected agents,namely,unmanned aerial vehicles(UAVs)and unmanned surface vehicles(USVs).We assume that each agent suffers from by the mixed constraints on its velocity,control input and Euler angle.Solving the MDFT problem implies that 1)The virtual state of each USV is determined in the earth coordinate by expanding its 2D work space to the 3D space.展开更多
Given the existence of real estate market bubbles and risks arising from high government debt,countries are faced with the challenge of preventing systemic risks.This study investigates the macroeconomic dynamics of t...Given the existence of real estate market bubbles and risks arising from high government debt,countries are faced with the challenge of preventing systemic risks.This study investigates the macroeconomic dynamics of the real estate market and local government debt risk from the perspective of liquidity constraints.We build a dynamic stochastic general equilibrium model with real estate and local government debt risk based on the New Keynesian-Dynamic Stochastic General Equilibrium Model(NK-DSGE)model to investigate the transmission path of local government debt risk under real estate regulation.In addition,we analyze the risk transmission between the real estate market and local government under different tax systems and investigate the shock to household welfare from a local government debt default.The results show monetary policy can effectively control the scale of local government debt to reduce default risk.An increase in property taxes that restrains housing demand can effectively regulate the real estate market.Although reducing taxes can increase macroeconomic output,reducing tax rates on consumption,capital,and labor weakens the liquidity of household assets.Further,lowering taxes increases local government default risk,which reduces household welfare and makes it more difficult for local governments to deleverage.Our findings provide important insights for countries seeking an effective real estate regulation mechanism to curb local government default risk.展开更多
Under the socialist market economic system of our country,the government,through the“invisible hand,”carries on macro regulation and control to improve the financing constraints that small and medium-sized enterpris...Under the socialist market economic system of our country,the government,through the“invisible hand,”carries on macro regulation and control to improve the financing constraints that small and medium-sized enterprises are facing.But because of the huge base number of small and medium-sized enterprises in our country,there are many kinds,and the problem of financing constraints is still puzzling the development of enterprises at present.With the continuous promotion of inclusive finance in our country,the problems plaguing SMEs in the last mile of financing are gradually improved.In this context,small and medium-sized enterprises in Hainan Free Trade Port are taken as the research object to study the role of digital inclusive finance on the financing constraints of SMEs.The research shows that,first of all,small and medium-sized enterprises in Hainan Free Trade Port generally have financing problems.The development of digital inclusive finance solves the“last kilometer”problem of traditional finance,enhances financial access ability,broadens the financial service group,provides convenience and diversified services for SMEs'financing,and provides inexhaustible impetus for the long-term healthy development of SMEs.Secondly,digital inclusive finance alleviates the financing difficulties faced by SMEs on the island by reducing financial costs and expanding the scale of credit.展开更多
Digital financial inclusion provides financial services through digital platforms,aiming to improve the ability of MSMEs and low-income groups to access financial resources,thereby easing their financing constraints a...Digital financial inclusion provides financial services through digital platforms,aiming to improve the ability of MSMEs and low-income groups to access financial resources,thereby easing their financing constraints and promoting economic growth and inclusive development.As an innovative financial model,digital financial inclusion utilizes modern technological means to significantly improve the accessibility and convenience of financial services,especially in areas where traditional banking services are under-covered.Digital finance has promoted the popularization of financial services such as micro-credit,micro-savings,and micro-insurance,and helped improve the financing environment of low-income groups and small and micro enterprises.At the same time,digital financial inclusion promotes financial literacy education and digital inclusion construction,and enhances the acceptance and use of digital financial instruments by the general public,which is the key to achieving sustainable development of digital financial inclusion.Therefore,digital financial inclusion can better ease the financing constraints of small and medium-sized enterprises and promote economic development.展开更多
With the establishment of Hainan Free Trade Port,the small and medium-sized enterprises in Hainan Free Trade Port have developed and grown in the continuously optimized enterprise environment.The continuous establishm...With the establishment of Hainan Free Trade Port,the small and medium-sized enterprises in Hainan Free Trade Port have developed and grown in the continuously optimized enterprise environment.The continuous establishment of a large number of small and micro enterprises makes its social and economic development play a non-negligible role.However,due to the small size and insufficient economic strength of small and micro enterprises,their status in the financial system is often very humble.Therefore,under normal circumstances,small and micro enterprises are faced with financing difficulties and high costs,which has a great side effect on their development.The proposal and continuous development of digital inclusive finance,so that small and micro enterprises in access to a wide range of financing opportunities at the same time,their financing methods are more convenient than in the past,the cost is getting lower and lower.This paper deeply discusses the role of digital inclusive finance in easing the financing constraints of small and micro enterprises and puts forward corresponding suggestions[1].展开更多
Due to the NP-hardness of the two-sided assembly line balancing （TALB） problem, multiple constraints existing in real applications are less studied, especially when one task is involved with several constraints. In ...Due to the NP-hardness of the two-sided assembly line balancing （TALB） problem, multiple constraints existing in real applications are less studied, especially when one task is involved with several constraints. In this paper, an effective hybrid algorithm is proposed to address the TALB problem with multiple constraints （TALB-MC）. Considering the discrete attribute of TALB-MC and the continuous attribute of the standard teaching-learning-based optimization （TLBO） algorithm, the random-keys method is hired in task permutation representation, for the purpose of bridging the gap between them. Subsequently, a special mechanism for handling multiple constraints is developed. In the mechanism, the directions constraint of each task is ensured by the direction check and adjustment. The zoning constraints and the synchronism constraints are satisfied by teasing out the hidden correlations among constraints. The positional constraint is allowed to be violated to some extent in decoding and punished in cost fimction. Finally, with the TLBO seeking for the global optimum, the variable neighborhood search （VNS） is further hybridized to extend the local search space. The experimental results show that the proposed hybrid algorithm outperforms the late acceptance hill-climbing algorithm （LAHC） for TALB-MC in most cases, especially for large-size problems with multiple constraints, and demonstrates well balance between the exploration and the exploitation. This research proposes an effective and efficient algorithm for solving TALB-MC problem by hybridizing the TLBO and VNS.展开更多
文摘Against the backdrop of active global responses to climate change and the accelerated green and low-carbon energy transition,the co-optimization and innovative mechanism design of multimodal energy systems have become a significant instrument for propelling the energy revolution and ensuring energy security.Under increasingly stringent carbon emission constraints,how to achieve multi-dimensional improvements in energy utilization efficiency,renewable energy accommodation levels,and system economics-through the intelligent coupling of diverse energy carriers such as electricity,heat,natural gas,and hydrogen,and the effective application of market-based instruments like carbon trading and demand response-constitutes a critical scientific and engineering challenge demanding urgent solutions.
基金an initial outcome of the Research on the Trust Mechanism of Agricultural Supply Chain Financing in the Context of “Blockchain+Supply Chain” Integrated Governance (Project No:20AGL021)a key project under the National Social Science Fund of China (NSSFC)+3 种基金the Research on the Trust Mechanism of Online Bank Lending System Based on Online Social Capital of Long-tail Rural Households (Project No:19BGL155)a project under the NSSFCthe Research on the Cost Formation Mechanism of Data Factor Transactions and the Design of Transaction Mechanism (Project No:23CJY068)a youth project under the NSSFC
文摘This paper begins with a discussion of the trust issues that agricultural supply chain finance faces.It then examines the constraints of using blockchain technology to enhance trust in agricultural supply chain finance in accordance with the technological and institutional logic of combining blockchain with supply chains.This study then proposes the creation of an agricultural“blockchain+supply chain”information service platform and a financing trust mechanism that can effectively ensure the authenticity of the initial information input on the blockchain,consistency between on-chain transaction data and off-chain physical transactions,the controllability of risks in the set up and execution of smart contracts,and the removal of information constraints,resource allocation constraints,and institutional constraints in the agricultural supply chain financing.This aims to improve the efficiency of financing in agricultural supply chains and contribute to the industrial development of rural areas and rural revitalization.
基金Supported by Shanxi Provincial Natural Science Foundation(Grant No.2021JM010)The Youth Innovation Team of Shaanxi Universities.
文摘This study aimed to identify and compensate for the geometric errors of the double swiveling axes in a five-axis computer numerical control(CNC)machining center.Hence,a three-dimensional coordinate calculation algorithm for a measured point with additional rotational rigid body motion constraints is proposed.The motion constraints of the rotational rigid body were analyzed,and a mathematical model of the measured point algorithm in the swiveling axes was established.The Levenberg-Marquard method was used to solve the nonlinear superstatically determined equations.The spatial coordinate error was used to separate the spatial deviation of the measured point.An identification model of the position-independent and position-dependent geometric errors was established.The three-dimensional coordinate-solving algorithm of the measured point in the swiveling axis and geometric error identification method based on the Monte Carlo method were analyzed numerically.Geometric error measurement and cutting experiments were performed on a VMC25100U five-axis machining center,which integrated two swiveling axes.Geometric errors of the A-and B-axes were identified and measured experimentally.The angular positioning errors before and after compensation were measured using a laser interferometer,which verified the effectiveness of the proposed algorithm.A cutting experiment of a round table part was performed.The shape and position accuracy of the processed part before and after compensation were detected using a coordinate measuring machine.It verified that the geometric error of the swiveling axis was effectively compensated by the algorithm proposed herein.
文摘This study examines the moderating role of entrepreneurs’creative cognitive styles in the relationship between resource constraints and bricolage.Drawing on insights from cognitive psychology and entrepreneurial research,we explore how divergent and convergent thinking influence the extent to which entrepreneurs engage in bricolage under resource limitations.Bricolage refers to the creative recombination of available resources to address challenges and seize opportunities,a process often adopted by firms facing financial or knowledge constraints.Yet,individual cognitive differences may determine how effectively entrepreneurs can employ bricolage as a strategic response to scarcity.We propose that divergent thinking—the capacity to generate multiple creative solutions and identify novel resource combinations—strengthens the positive association between resource constraints and bricolage.In contrast,convergent thinking,which emphasizes logical analysis and the pursuit of a single optimal solution,weakens this association.To test these propositions,we collected survey data from 183 entrepreneurs in the United States and employed moderated regression analyses to examine the interactions among cognitive styles,resource constraints,and bricolage behaviors.Our findings reveal that divergent thinking significantly enhances the effect of both financial and knowledge constraints on bricolage,enabling entrepreneurs to creatively leverage limited resources.Conversely,convergent thinking appears to diminish the likelihood of engaging in bricolage when resources are scarce.These results highlight the importance of individual cognitive styles in shaping strategic responses to resource scarcity and contribute to a more nuanced understanding of entrepreneurial bricolage.The study offers practical implications for firms operating in resource-constrained environments by suggesting that enhancing divergent thinking abilities may facilitate more effective resource recombination.Future research should investigate additional cognitive factors and employ longitudinal designs to capture the dynamic nature of entrepreneurial decision-making.These insights open new avenues for further innovative entrepreneurial practices.
基金supported by National Major Scientific Research Instrument Development Project of China(No.51927804)Science Fund for Shaanxi Provincial Department of Education's Youth Innovation Team Research Plan under Grant(No.23JP169).
文摘In machine vision,elliptical targets frequently appear within the camera's region of interest(ROI).Ellipse detection is essential for shape detection and geometric measurements in machine vision.However,existing ellipse detection algorithms often face issues such as high computational complexity,strong dependence on initial conditions,sensitivity to noise,and lack of robustness to occlusions.In this paper,we propose a fast and robust ellipse detection method to address these challenges.This method first utilizes edge gradient and curvature information to segment the curve into circular arcs.Next,based on the convexity of the arcs,it divides them into different quadrants of the ellipse,groups and fits the arcs according to multiple geometric constraints at a low computational cost.Finally,it reduces the parameter space for hierarchical clustering and then segments the complete ellipse into several sectors for verification.We compare our method across seven datasets,including five public image datasets and two from industrial camera scenes.Experimental results show that our method achieves a precision ranging from 67.1%to 98.9%,a recall ranging from 48.1%to 92.9%,and an F-measure ranging from 58.0%to 95.8%.The average execution time per image ranges from 25 ms to 192 ms,demonstrating both high accuracy and efficiency.
基金Supported by Zhejiang Provincial Key Research and Development Program(Grant No.2021C04015)。
文摘Learning from demonstration is widely regarded as a promising paradigm for robots to acquire diverse skills.Other than the artificial learning from observation-action pairs for machines,humans can learn to imitate in a more versatile and effective manner:acquiring skills through mere“observation”.Video to Command task is widely perceived as a promising approach for task-based learning,which yet faces two key challenges:(1)High redundancy and low frame rate of fine-grained action sequences make it difficult to manipulate objects robustly and accurately.(2)Video to Command models often prioritize accuracy and richness of output commands over physical capabilities,leading to impractical or unsafe instructions for robots.This article presents a novel Video to Command framework that employs multiple data associations and physical constraints.First,we introduce an object-level appearancecontrasting multiple data association strategy to effectively associate manipulated objects in visually complex environments,capturing dynamic changes in video content.Then,we propose a multi-task Video to Command model that utilizes object-level video content changes to compile expert demonstrations into manipulation commands.Finally,a multi-task hybrid loss function is proposed to train a Video to Command model that adheres to the constraints of the physical world and manipulation tasks.Our method achieved over 10%on BLEU_N,METEOR,ROUGE_L,and CIDEr compared to the up-to-date methods.The dual-arm robot prototype was established to demonstrate the whole process of learning from an expert demonstration of multiple skills and then executing the tasks by a robot.
基金supported by National Key Research and Development Program of China(2024YFE0214000)National Natural Science Foundation of China(62173308)+3 种基金Natural Science Foundation of Zhejiang Province of China(LRG25F030002)Zhejiang Province Leading Geese Plan(2025C01056)Jinhua Science and Technology Project(2022-1-042)Natural Science Foundation of Jiangsu Province(BK20240009).
文摘Dear Editor,This letter addresses distributed optimization for resource allocation problems with time-varying objective functions and time-varying constraints.Inspired by the distributed average tracking(DAT)approach,a distributed control protocol is proposed for optimal resource allocation.The convergence to a time-varying optimal solution within a predefined time is proved.Two numerical examples are given to illustrate the effectiveness of the proposed approach.
基金Supported by Jiangsu Key R&D Program(BE2021622)Jiangsu Postgraduate Practice and Innovation Program(SJCX23_0395).
文摘Background As visual simultaneous localization and mapping(SLAM)is primarily based on the assumption of a static scene,the presence of dynamic objects in the frame causes problems such as a deterioration of system robustness and inaccurate position estimation.In this study,we propose a YGC-SLAM for indoor dynamic environments based on the ORB-SLAM2 framework combined with semantic and geometric constraints to improve the positioning accuracy and robustness of the system.Methods First,the recognition accuracy of YOLOv5 was improved by introducing the convolution block attention model and the improved EIOU loss function,whereby the prediction frame converges quickly for better detection.The improved YOLOv5 was then added to the tracking thread for dynamic target detection to eliminate dynamic points.Subsequently,multi-view geometric constraints were used for re-judging to further eliminate dynamic points while enabling more useful feature points to be retained and preventing the semantic approach from over-eliminating feature points,causing a failure of map building.The K-means clustering algorithm was used to accelerate this process and quickly calculate and determine the motion state of each cluster of pixel points.Finally,a strategy for drawing keyframes with de-redundancy was implemented to construct a clear 3D dense static point-cloud map.Results Through testing on TUM dataset and a real environment,the experimental results show that our algorithm reduces the absolute trajectory error by 98.22%and the relative trajectory error by 97.98%compared with the original ORBSLAM2,which is more accurate and has better real-time performance than similar algorithms,such as DynaSLAM and DS-SLAM.Conclusions The YGC-SLAM proposed in this study can effectively eliminate the adverse effects of dynamic objects,and the system can better complete positioning and map building tasks in complex environments.
文摘The rapid development of digital financial inclusion is profoundly changing the financing environment for small and medium-sized enterprises(SMEs).As an important driver of economic growth and innovation,SMEs account for a significant share of employment and GDP globally.However,the traditional bank credit model has long failed to effectively meet the financing needs of SMEs due to issues such as information asymmetry,high cost,and difficulty in risk assessment,resulting in serious financing constraints.Digital financial inclusion,through technological innovation and big data analysis,has significantly reduced credit costs,alleviated information asymmetry,and provided SMEs with more flexible and efficient financing channels.Research shows that digital financial inclusion can not only ease the financing constraints of SMEs,but also promote their innovation and growth,providing important support for building a more inclusive and sustainable financial ecosystem.
基金partially supported by the National Key Research and Development Program of the Ministry of Science and Technology of China(2022YFE0114200)the National Natural Science Foundation of China(U20A6004).
文摘This paper investigates a distributed heterogeneous hybrid blocking flow-shop scheduling problem(DHHBFSP)designed to minimize the total tardiness and total energy consumption simultaneously,and proposes an improved proximal policy optimization(IPPO)method to make real-time decisions for the DHHBFSP.A multi-objective Markov decision process is modeled for the DHHBFSP,where the reward function is represented by a vector with dynamic weights instead of the common objectiverelated scalar value.A factory agent(FA)is formulated for each factory to select unscheduled jobs and is trained by the proposed IPPO to improve the decision quality.Multiple FAs work asynchronously to allocate jobs that arrive randomly at the shop.A two-stage training strategy is introduced in the IPPO,which learns from both single-and dual-policy data for better data utilization.The proposed IPPO is tested on randomly generated instances and compared with variants of the basic proximal policy optimization(PPO),dispatch rules,multi-objective metaheuristics,and multi-agent reinforcement learning methods.Extensive experimental results suggest that the proposed strategies offer significant improvements to the basic PPO,and the proposed IPPO outperforms the state-of-the-art scheduling methods in both convergence and solution quality.
基金The funding was provided by National Office for Philosophy and Social ScienceThe authors express their gratitude to the research project titled“Study on Synergistic Governance and Optimization Path of Urban Environment under the Constraint of Biased Emission Reduction Target”[Grant No.23BGL222]this research is also supported by the Hubei Market Entity Vitality Research Center,a Key Research Institute of Humanities and Social Sciences in Hubei Universities[Grant No.00120721].
文摘The biased allocation of emission reduction target constraints quantifies emission reduction responsibilities and reflects differences in pollutant reductions both across and within cities.This approach represents a systematic innovation aims to enhance China’s green competitiveness and facilitate its economic transformation through localized and precise policymaking.Using panel data from 275 Chinese cities spanning 2000-2022,this study applies the difference-in-differences method to estimate the impact of biased allocation of emission reduction target constraints on urban green competitiveness.The findings indicate that such constraints-whether based on chemical oxygen demand or sulfur dioxide targets-significantly improve urban green competitiveness,with both pollutant-specific constraints producing comparable effects.Furthermore,these constraints exhibit significant spatial spillover effects within a 200-km geographical radius.Heterogeneity analysis reveals stronger policy impacts in resource-based cities,eastern regions,and cities designated as key areas for pollution prevention and control.Mechanism analysis demonstrates that the constraints enhance green competitiveness primarily by fostering green technological innovation and optimizing industrial structures.These conclusions provide a practical foundation for addressing China’s enduring conflict between environmental protection and economic development.
基金supported by the National Natural Science Foundation of China(62173209,61773238)the Science Center Program of National Natural Science Foundation of China(62188101).
文摘Dear Editor,This letter presents a new secure hierarchical control strategy for steering tracking of in-wheel motor driven(IWMD)electric vehicle(EV)subject to limited network resources,hybrid cyber-attacks,model nonlinearities,actuator redundancy and airflow disturbance.A hierarchical control architecture is proposed specifically for solving the problems of nonlinear system modeling and actuator redundancy.By utilizing the advantages of fully actuated system(FAS)approach,a nonlinear virtual controller against airflow disturbance is constructed in upper layer system and an event-triggered nonlinear distributed controller is proposed in lower layer system under stochastic hybrid cyber-attacks.A case study of overtaking task is carried out to validate the FAS-based hierarchical control strategy.
文摘As an important tool to achieve sustainable economic and environmental development,green finance can effectively alleviate the financing constraints of small and medium-sized enterprises(SMEs),especially in promoting green transformation plays a key role.SMEs play an important role in economic growth,innovation,and job creation,but due to a lack of collateral,imperfect credit history,and opaque financial information,they face great obstacles in the financing process,especially in the early capital investment required for green transformation.Green finance,through innovative financial instruments such as green credit and green bonds,provides new financing channels for SMEs,helping them reduce financing costs,optimize financing structure,and promote their green transformation and sustainable development.This paper analyzes the current situation and root causes of SMEs’financing dilemma from the perspective of green finance,and probes into the influence of green finance policies on financing behavior.
基金supported by the National Nature Science Foundation of China(U21A20166)the Science and Technology Development Foundation of Jilin Province(20230508095RC)+2 种基金the Major Science and Technology Projects of Jilin Province and Changchun City(20220301033GX)the Development and Reform Commission Foundation of Jilin Province(2023C034-3)the Interdisciplinary Integration and Innovation Project of JLU(JLUXKJC2020202).
文摘Dear Editor,Aiming at the consensus tracking problem of a class of unknown heterogeneous nonlinear multiagent systems(MASs)with input constraints,a novel data-driven iterative learning consensus control(ILCC)protocol based on zeroing neural networks(ZNNs)is proposed.First,a dynamic linearization data model(DLDM)is acquired via dynamic linearization technology(DLT).
基金supported in part by the National Natural Science Foundation of China(62073301,62373162,62473349,U24A20268,62233007)the Shenzhen Science and Technology Program(JCYJ20240813114007010).
文摘Dear Editor,This letter investigates the problem of multi-dimension formation tracking(MDFT)for the cross-domain unmanned systems,including several interconnected agents,namely,unmanned aerial vehicles(UAVs)and unmanned surface vehicles(USVs).We assume that each agent suffers from by the mixed constraints on its velocity,control input and Euler angle.Solving the MDFT problem implies that 1)The virtual state of each USV is determined in the earth coordinate by expanding its 2D work space to the 3D space.
基金supported by the National Natural Science Foundation of China(Nos.72271135,72141304,71901130)National Social Science Fund of China(22&ZD117)+3 种基金Laboratory of Computation and Analytics of Complex Management Systems(Tianjin University)Special Funds for Taishan Scholars(tsqn202211120)2024 Qingdao Finance Society Key Project2024 Qingdao Social Science Planning Project.
文摘Given the existence of real estate market bubbles and risks arising from high government debt,countries are faced with the challenge of preventing systemic risks.This study investigates the macroeconomic dynamics of the real estate market and local government debt risk from the perspective of liquidity constraints.We build a dynamic stochastic general equilibrium model with real estate and local government debt risk based on the New Keynesian-Dynamic Stochastic General Equilibrium Model(NK-DSGE)model to investigate the transmission path of local government debt risk under real estate regulation.In addition,we analyze the risk transmission between the real estate market and local government under different tax systems and investigate the shock to household welfare from a local government debt default.The results show monetary policy can effectively control the scale of local government debt to reduce default risk.An increase in property taxes that restrains housing demand can effectively regulate the real estate market.Although reducing taxes can increase macroeconomic output,reducing tax rates on consumption,capital,and labor weakens the liquidity of household assets.Further,lowering taxes increases local government default risk,which reduces household welfare and makes it more difficult for local governments to deleverage.Our findings provide important insights for countries seeking an effective real estate regulation mechanism to curb local government default risk.
文摘Under the socialist market economic system of our country,the government,through the“invisible hand,”carries on macro regulation and control to improve the financing constraints that small and medium-sized enterprises are facing.But because of the huge base number of small and medium-sized enterprises in our country,there are many kinds,and the problem of financing constraints is still puzzling the development of enterprises at present.With the continuous promotion of inclusive finance in our country,the problems plaguing SMEs in the last mile of financing are gradually improved.In this context,small and medium-sized enterprises in Hainan Free Trade Port are taken as the research object to study the role of digital inclusive finance on the financing constraints of SMEs.The research shows that,first of all,small and medium-sized enterprises in Hainan Free Trade Port generally have financing problems.The development of digital inclusive finance solves the“last kilometer”problem of traditional finance,enhances financial access ability,broadens the financial service group,provides convenience and diversified services for SMEs'financing,and provides inexhaustible impetus for the long-term healthy development of SMEs.Secondly,digital inclusive finance alleviates the financing difficulties faced by SMEs on the island by reducing financial costs and expanding the scale of credit.
文摘Digital financial inclusion provides financial services through digital platforms,aiming to improve the ability of MSMEs and low-income groups to access financial resources,thereby easing their financing constraints and promoting economic growth and inclusive development.As an innovative financial model,digital financial inclusion utilizes modern technological means to significantly improve the accessibility and convenience of financial services,especially in areas where traditional banking services are under-covered.Digital finance has promoted the popularization of financial services such as micro-credit,micro-savings,and micro-insurance,and helped improve the financing environment of low-income groups and small and micro enterprises.At the same time,digital financial inclusion promotes financial literacy education and digital inclusion construction,and enhances the acceptance and use of digital financial instruments by the general public,which is the key to achieving sustainable development of digital financial inclusion.Therefore,digital financial inclusion can better ease the financing constraints of small and medium-sized enterprises and promote economic development.
文摘With the establishment of Hainan Free Trade Port,the small and medium-sized enterprises in Hainan Free Trade Port have developed and grown in the continuously optimized enterprise environment.The continuous establishment of a large number of small and micro enterprises makes its social and economic development play a non-negligible role.However,due to the small size and insufficient economic strength of small and micro enterprises,their status in the financial system is often very humble.Therefore,under normal circumstances,small and micro enterprises are faced with financing difficulties and high costs,which has a great side effect on their development.The proposal and continuous development of digital inclusive finance,so that small and micro enterprises in access to a wide range of financing opportunities at the same time,their financing methods are more convenient than in the past,the cost is getting lower and lower.This paper deeply discusses the role of digital inclusive finance in easing the financing constraints of small and micro enterprises and puts forward corresponding suggestions[1].
基金Supported by National Natural Science Foundation of China(Grant Nos.51275366,50875190,51305311)Specialized Research Fund for the Doctoral Program of Higher Education of China(Grant No.20134219110002)
文摘Due to the NP-hardness of the two-sided assembly line balancing （TALB） problem, multiple constraints existing in real applications are less studied, especially when one task is involved with several constraints. In this paper, an effective hybrid algorithm is proposed to address the TALB problem with multiple constraints （TALB-MC）. Considering the discrete attribute of TALB-MC and the continuous attribute of the standard teaching-learning-based optimization （TLBO） algorithm, the random-keys method is hired in task permutation representation, for the purpose of bridging the gap between them. Subsequently, a special mechanism for handling multiple constraints is developed. In the mechanism, the directions constraint of each task is ensured by the direction check and adjustment. The zoning constraints and the synchronism constraints are satisfied by teasing out the hidden correlations among constraints. The positional constraint is allowed to be violated to some extent in decoding and punished in cost fimction. Finally, with the TLBO seeking for the global optimum, the variable neighborhood search （VNS） is further hybridized to extend the local search space. The experimental results show that the proposed hybrid algorithm outperforms the late acceptance hill-climbing algorithm （LAHC） for TALB-MC in most cases, especially for large-size problems with multiple constraints, and demonstrates well balance between the exploration and the exploitation. This research proposes an effective and efficient algorithm for solving TALB-MC problem by hybridizing the TLBO and VNS.
