To address the issue of disturbance compensation deviation in linear active disturbance rejection control(LADRC),a linear active disturbance rejection control method with reference to the integral chain model(LADRC-R)...To address the issue of disturbance compensation deviation in linear active disturbance rejection control(LADRC),a linear active disturbance rejection control method with reference to the integral chain model(LADRC-R)is proposed.By constructing an ideal control reference model,a dynamic correlation between output deviation and uncompensated disturbances is established,and a dual-loop compensation mechanism is designed.Based on theoretical analysis and frequency-domain characteristics of typical first/second-order systems,this method maintains the parameter-tuning advantages of LADRC while reducing disturbance effects by 50%and introducing no phase lag during low-frequency disturbance suppression.Simulations on second-order systems verify its robustness under parameter perturbations,gain mismatch,and complex disturbances,and an optimized design scheme for the deviation compensator is proposed to suppress discontinuous measurement noise interference.Finally,the engineering effectiveness of this method in precision motion control is validated on an electromagnetic suspension platform,providing a new approach to improving the control performance of LADRC in environments with uncertain disturbances.展开更多
According to the relationships among state transition probability matrixes with different step lengths, an improved Markov chain model based on autocorrelation and entropy techniques was introduced. In the improved Ma...According to the relationships among state transition probability matrixes with different step lengths, an improved Markov chain model based on autocorrelation and entropy techniques was introduced. In the improved Markov chain model, the state transition probability matrixes can be adjusted. The steps of the historical state of the event, which was significantly related to the future state of the event, were determined by the autocorrelation technique, and the impact weights of the event historical state on the event future state were determined by the entropy technique. The presented model was applied to predicting annual precipitation and annual runoff states, showing that the improved model is of higher precision than those existing Markov chain models, and the determination of the state transition probability matrixes and the weights is more reasonable. The physical concepts of the improved model are distinct, and its computation process is simple and direct, thus, the presented model is sufficiently general to be applicable to the prediction problems in hydrology and water resources.展开更多
As the increasing popularity and complexity of Web applications and the emergence of their new characteristics, the testing and maintenance of large, complex Web applications are becoming more complex and difficult. W...As the increasing popularity and complexity of Web applications and the emergence of their new characteristics, the testing and maintenance of large, complex Web applications are becoming more complex and difficult. Web applications generally contain lots of pages and are used by enormous users. Statistical testing is an effective way of ensuring their quality. Web usage can be accurately described by Markov chain which has been proved to be an ideal model for software statistical testing. The results of unit testing can be utilized in the latter stages, which is an important strategy for bottom-to-top integration testing, and the other improvement of extended Markov chain model (EMM) is to present the error type vector which is treated as a part of page node. this paper also proposes the algorithm for generating test cases of usage paths. Finally, optional usage reliability evaluation methods and an incremental usability regression testing model for testing and evaluation are presented. Key words statistical testing - evaluation for Web usability - extended Markov chain model (EMM) - Web log mining - reliability evaluation CLC number TP311. 5 Foundation item: Supported by the National Defence Research Project (No. 41315. 9. 2) and National Science and Technology Plan (2001BA102A04-02-03)Biography: MAO Cheng-ying (1978-), male, Ph.D. candidate, research direction: software testing. Research direction: advanced database system, software testing, component technology and data mining.展开更多
This paper analyses the supply chain models of four types of agricultural products,namely fruits and vegetables,poultry,aquatic products and dairy,and the food safety problems arising from the links of supply chain.In...This paper analyses the supply chain models of four types of agricultural products,namely fruits and vegetables,poultry,aquatic products and dairy,and the food safety problems arising from the links of supply chain.In view of different models,corresponding suggestions are put forward to ensure the quality safety of agricultural products in Heilongjiang Province.展开更多
A precise background theory of computational mechanics is formed. Saint_Venant's principle is discussed in chain model by means of this precise theory. The classical continued fraction is developed into operator c...A precise background theory of computational mechanics is formed. Saint_Venant's principle is discussed in chain model by means of this precise theory. The classical continued fraction is developed into operator continued fraction to be the constrictive formulation of the chain model. The decay of effect of a self_equilibrated system of forces in chain model is decided by the convergence of operator continued fraction, so the reasonable part of Saint_Venant's principle is described as the convergence of operator continued fraction. In case of divergence the effect of a self_equilibrated system of forces may be non_zero at even infinite distant sections, so Saint_Venant's principle is not a common principle.展开更多
In this paper,a deterministic and stochastic fractional-order model of the tri-trophic food chain model incorporating harvesting is proposed and analysed.The interaction between prey,middle predator and top predator p...In this paper,a deterministic and stochastic fractional-order model of the tri-trophic food chain model incorporating harvesting is proposed and analysed.The interaction between prey,middle predator and top predator population is investigated.In order to clarify the characteristics of the proposed model,the analysis of existence,uniqueness,non-negativity and boundedness of the solutions of the proposed model are examined.Some sufficient conditions that ensure the local and global stability of equilibrium points are obtained.By using stability analysis of the fractional-order system,it is proved that if the basic reproduction number R_(0)<1,the predator free equilibrium point E_(1) is globally asymptotically stable.The occurrence of local bifurcation near the equilibrium points is investigated with the help of Sotomayor’s theorem.Some numerical examples are given to illustrate the theoretical findings.The impact of harvesting on prey and themiddle predator is studied.We conclude that harvesting parameters can control the dynamics of the middle predator.A numerical approximation method is developed for the proposed stochastic fractional-order model.展开更多
Kuala Lumpur of Malaysia,as a tropical city,has experienced a notable decline in its critical urban green infrastructure(UGI)due to rapid urbanization and haphazard development.The decrease of UGI,especially natural f...Kuala Lumpur of Malaysia,as a tropical city,has experienced a notable decline in its critical urban green infrastructure(UGI)due to rapid urbanization and haphazard development.The decrease of UGI,especially natural forest and artificial forest,may reduce the diversity of ecosystem services and the ability of Kuala Lumpur to build resilience in the future.This study analyzed land use and land cover(LULC)and UGI changes in Kuala Lumpur based on Landsat satellite images in 1990,2005,and 2021and employed the overall accuracy and Kappa coefficient to assess classification accuracy.LULC was categorized into six main types:natural forest,artificial forest,grassland,water body,bare ground,and built-up area.Satellite images in 1990,2005,and 2021 showed the remarkable overall accuracy values of 91.06%,96.67%,and 98.28%,respectively,along with the significant Kappa coefficient values of 0.8997,0.9626,and 0.9512,respectively.Then,this study utilized Cellular Automata and Markov Chain model to analyze the transition of different LULC types during 1990-2005 and 1990-2021 and predict LULC types in 2050.The results showed that natural forest decreased from 15.22%to 8.20%and artificial forest reduced from 18.51%to 15.16%during 1990-2021.Reductions in natural forest and artificial forest led to alterations in urban surface water dynamics,increasing the risk of urban floods.However,grassland showed a significant increase from 7.80%to 24.30%during 1990-2021.Meanwhile,bare ground increased from 27.16%to 31.56%and built-up area increased from 30.45%to 39.90%during 1990-2005.In 2021,built-up area decreased to 35.10%and bare ground decreased to 13.08%,indicating a consistent dominance of built-up area in the central parts of Kuala Lumpur.This study highlights the importance of integrating past,current,and future LULC changes to improve urban ecosystem services in the city.展开更多
The supply chain modeling technology is research. Firstly, the concept of supply chain and supply chain management is introduced. Secondly, enterprise modeling methods, such as CIM OSA, GIM GRAI, PERA and ARIS, are an...The supply chain modeling technology is research. Firstly, the concept of supply chain and supply chain management is introduced. Secondly, enterprise modeling methods, such as CIM OSA, GIM GRAI, PERA and ARIS, are analyzed and compared. The supply chain modeling technology is studied. Then the ARIS based supply chain modeling method is proposed and the supply chain operation reference model is set up. Finally, the applications of ARIS based supply chain modeling method in Shanghai Turbine Generator Co. Ltd. (STGC) is described in detail.展开更多
In this study, a fuzzy probability-based Markov chain model is developed for forecasting regional long-term electric power demand. The model can deal with the uncertainties in electric power system and reflect the vag...In this study, a fuzzy probability-based Markov chain model is developed for forecasting regional long-term electric power demand. The model can deal with the uncertainties in electric power system and reflect the vague and ambiguous during the process of power load forecasting through allowing uncertainties expressed as fuzzy parameters and discrete intervals. The developed model is applied to predict the electric power demand of Beijing from 2011 to 2019. Different satisfaction degrees of fuzzy parameters are considered as different levels of detail of the statistic data. The results indicate that the model can reflect the high uncertainty of long term power demand, which could support the programming and management of power system. The fuzzy probability Markov chain model is helpful for regional electricity power system managers in not only predicting a long term power load under uncertainty but also providing a basis for making multi-scenarios power generation/development plans.展开更多
In order to improve the accuracy and efficiency of early warning system, the incident chain model and the targeted dissemination technology are proposed in this paper. Firstly, the occurrence probability, affected are...In order to improve the accuracy and efficiency of early warning system, the incident chain model and the targeted dissemination technology are proposed in this paper. Firstly, the occurrence probability, affected area and duration of disaster are predicted with the incident chain model and GIS. According to prediction results, the early warning system can accurately deliver early warning information specifically to the affected areas through targeted dissemination. Moreover, dissemination performance can also be evaluated in real time after early warning information dissemination, so that everyone in the affected area can receive early warning information successfully. The incident chain model and the targeted dissemination technology presented in this study are of great significance for improving the information dissemination ability of early warning system.展开更多
In this paper we proposed an AMH Supply Chain model to obtain optimal solutions for Two-, Three- and Four-Stage for deterministic models. Besides deriving its algebraic solutions, a simple searching method is successf...In this paper we proposed an AMH Supply Chain model to obtain optimal solutions for Two-, Three- and Four-Stage for deterministic models. Besides deriving its algebraic solutions, a simple searching method is successfully applied in obtaining optimal total costs and its integer multipliers. Our model has shown promising results in comparison to Equal Cycle Time and other existing ones. The tests focused on obtaining optimal total annual costs and other related details of Two-, Three- and Four-Stage for deterministic models. The results are run under Visual Basic Programming platform using Intel? CoreTM2 Duo T6500 Processor.展开更多
In this paper,we are concerned about a food chain model with a protection zone for the prey species.Dynamical behavior,nonexistence and existence of positive steady states are obtained and there exist several critical...In this paper,we are concerned about a food chain model with a protection zone for the prey species.Dynamical behavior,nonexistence and existence of positive steady states are obtained and there exist several critical values determined by the parameters and the protection zone for the growth rate of the prey species.The results reveal that the protection zone is effective for the survival of the prey species and beneficial for the coexistence of multiple species.Moreover,different properties of positive steady states from those of the two-species models are shown.The introduction of the prey or the top predator can be either favorable or unfavorable for the coexistence of multiple species.展开更多
Amidst the unique challenges faced by rural educators is their sense of decent work influenced by levels of social support,career self-efficacy,and marginalization.To investigate these relationships,we surveyed 435 ru...Amidst the unique challenges faced by rural educators is their sense of decent work influenced by levels of social support,career self-efficacy,and marginalization.To investigate these relationships,we surveyed 435 rural school teachers(females=69.32%,mean years teaching experience=13.6,SD=7.7 years).The Structural Equation Modeling results indicated that social support positively predicts teachers’perceptions of decent work.Career self-efficacy mediated the relationship between social support and a higher sense of decent work,while marginalization mediated the relationship such that lower social support predicted lower perceptions of decent work.Career self-efficacy and marginalization also had a sequential mediation relationship:higher social support enhanced career self-efficacy,which in turn reduced marginalization experiences,ultimately improving teachers’perceptions of decent work.These findings align with the predictions of Social Cognitive Career Theory and the Psychology of Working Theory,demonstrating that environmental supports enhance personal psychological resources,reduce marginalization risks,and promote positive work-related outcomes.The study findings highlight the necessity for education departments to improve rural teachers’perceptions of decent work by providing social support to foster positive work experiences for teachers at high risk for marginalization and diminished career self-efficacy.展开更多
BACKGROUND Death anxiety(DA)is a prevalent psychological challenge among oncology nurses that affects their emotional well-being and professional competence in coping with death-related situations.Death-related attitu...BACKGROUND Death anxiety(DA)is a prevalent psychological challenge among oncology nurses that affects their emotional well-being and professional competence in coping with death-related situations.Death-related attitudes and resilience are critical factors that may mediate the relationship between DA and coping with death competence(CDC).However,few studies have examined the chain-mediating effect of these factors among Chinese oncology nurses.This study aimed to investigate the association between DA and CDC among Chinese oncology nurses,with a focus on the mediating roles of death attitude and resilience.AIM To investigate the association between DA and CDC among Chinese oncology nurses.using an electronic questionnaire distributed in Wenjuanxing,China.In total,615 valid responses were obtained.The participants completed the Templer death anxiety scale,death attitude profile-revised,Connor-Davidson resilience scale,and coping with death scale.A chain mediation analysis was performed using the PROCESS macro in SPSS to examine the relationships between these variables.RESULTS The findings indicated that DA had a significant direct effect on CDC[effect=0.201,95%confidence interval(CI):0.112-0.322].In addition to this direct effect,three significant indirect pathways were observed:(1)Death attitude(effect=0.118,95%CI:0.056-0.163);(2)Resilience(effect=0.108,95%CI:0.032-0.176);and(3)A sequential mediation pathway involving both death attitude and resilience(effect=0.071,95%CI:0.042-0.123).The total indirect effects of the three mediation paths accounted for 29.7%of the relationship between DA and CDC.CONCLUSION Using a chain mediation model,this study explored the mechanisms linking DA,death attitude,resilience,and CDC among Chinese oncology nurses.These findings highlighted the crucial role of death attitude and resilience in mediating the relationship between DA and CDC.Interventions aimed at fostering adaptive attitudes toward death and enhancing resilience may improve nurses’ability to cope with death-related stressors,ultimately benefiting their psychological well-being and professional competence.展开更多
Weather forecasts from numerical weather prediction models play a central role in solar energy forecasting,where a cascade of physics-based models is used in a model chain approach to convert forecasts of solar irradi...Weather forecasts from numerical weather prediction models play a central role in solar energy forecasting,where a cascade of physics-based models is used in a model chain approach to convert forecasts of solar irradiance to solar power production.Ensemble simulations from such weather models aim to quantify uncertainty in the future development of the weather,and can be used to propagate this uncertainty through the model chain to generate probabilistic solar energy predictions.However,ensemble prediction systems are known to exhibit systematic errors,and thus require post-processing to obtain accurate and reliable probabilistic forecasts.The overarching aim of our study is to systematically evaluate different strategies to apply post-processing in model chain approaches with a specific focus on solar energy:not applying any post-processing at all;post-processing only the irradiance predictions before the conversion;post-processing only the solar power predictions obtained from the model chain;or applying post-processing in both steps.In a case study based on a benchmark dataset for the Jacumba solar plant in the U.S.,we develop statistical and machine learning methods for postprocessing ensemble predictions of global horizontal irradiance(GHI)and solar power generation.Further,we propose a neural-network-based model for direct solar power forecasting that bypasses the model chain.Our results indicate that postprocessing substantially improves the solar power generation forecasts,in particular when post-processing is applied to the power predictions.The machine learning methods for post-processing slightly outperform the statistical methods,and the direct forecasting approach performs comparably to the post-processing strategies.展开更多
Using a modified subgradient extragradient algorithm, this paper proposed a novel approach to solving a supply chain network equilibrium model. The method extends the scope of optimisation and improves the accuracy at...Using a modified subgradient extragradient algorithm, this paper proposed a novel approach to solving a supply chain network equilibrium model. The method extends the scope of optimisation and improves the accuracy at each iteration by incorporating adaptive parameter selection and a more general subgradient projection operator. The advantages of the proposed method are highlighted by the proof of strong convergence presented in the paper. Several concrete examples are given to demonstrate the effectiveness of the algorithm, with comparisons illustrating its superior CPU running time compared to alternative techniques. The practical applicability of the algorithm is also demonstrated by applying it to a realistic supply chain network model.展开更多
In the traditional Markov chain model (MCM), aleatory uncertainty because of inherent randomness and epistemic uncertainty due to the lack of knowledge are not differentiated. Generalized interval probability provides...In the traditional Markov chain model (MCM), aleatory uncertainty because of inherent randomness and epistemic uncertainty due to the lack of knowledge are not differentiated. Generalized interval probability provides a concise representation for the two kinds of uncertainties simultaneously. In this paper, a generalized Markov chain model (GMCM), based on the generalized interval probability theory, is proposed to improve the reliability of prediction. In the GMCM, aleatory uncertainty is represented as probability; interval is used to capture epistemic uncertainty. A case study for predicting the average dynamic compliance in machining processes is provided to demonstrate the effectiveness of proposed GMCM. The results show that the proposed GMCM has a better prediction performance than that of MCM.展开更多
This study developed a new online driving cycle prediction method for hybrid electric vehicles based on a three-dimensional stochastic Markov chain model and applied the method to a driving-cycle-aware energy manageme...This study developed a new online driving cycle prediction method for hybrid electric vehicles based on a three-dimensional stochastic Markov chain model and applied the method to a driving-cycle-aware energy management strategy.The impacts of different prediction time lengths on driving cycle generation were explored.The results indicate that the original driving cycle is compressed by 50%,which significantly reduces the computational burden while having only a slight effect on the prediction performance.The developed driving cycle prediction method was implemented in a real-time energy management algorithm with a hybrid electric vehicle powertrain model,and the model was verified by simulation using two different testing scenarios.The testing results demonstrate that the developed driving cycle prediction method is able to efficiently predict future driving tasks,and it can be successfully used for the energy management of hybrid electric vehicles.展开更多
The molecular biomechanics of DNA ejection from bacteriophage is of interest to not only fundamental biological understandings but also practical applications such as the design of advanced site-specific and controlla...The molecular biomechanics of DNA ejection from bacteriophage is of interest to not only fundamental biological understandings but also practical applications such as the design of advanced site-specific and controllable drug delivery systems. In this paper, we analyze the viscous motion of a semiflexible polymer chain coming out of a strongly confined space as a model to investigate the effects of various structure confinements and frictional resistances encountered during the DNA ejection process. The theoretically predicted relations between the ejection speed, ejection time, ejection length, and other physical parameters, such as the phage type, total genome length and ionic state of external buffer solutions, show excellent agreement with in vitro experimental observations in the literature.展开更多
基金supported by the National Natural Science Foundation of China(Nos.62063009,52262050)the National Key Research and Development Program during the 14th 5-Year Plan(No.2023YFB4302100)the Major Science and Technology Research and Development Special Project in Jiangxi Province(No.20232ACE01011).
文摘To address the issue of disturbance compensation deviation in linear active disturbance rejection control(LADRC),a linear active disturbance rejection control method with reference to the integral chain model(LADRC-R)is proposed.By constructing an ideal control reference model,a dynamic correlation between output deviation and uncompensated disturbances is established,and a dual-loop compensation mechanism is designed.Based on theoretical analysis and frequency-domain characteristics of typical first/second-order systems,this method maintains the parameter-tuning advantages of LADRC while reducing disturbance effects by 50%and introducing no phase lag during low-frequency disturbance suppression.Simulations on second-order systems verify its robustness under parameter perturbations,gain mismatch,and complex disturbances,and an optimized design scheme for the deviation compensator is proposed to suppress discontinuous measurement noise interference.Finally,the engineering effectiveness of this method in precision motion control is validated on an electromagnetic suspension platform,providing a new approach to improving the control performance of LADRC in environments with uncertain disturbances.
基金Under the auspices of Major Special Technological Program of Water Pollution Control and Management (No.2009ZX07106-001)National Natural Science Foundation of China (No. 51079037, 50909063)
文摘According to the relationships among state transition probability matrixes with different step lengths, an improved Markov chain model based on autocorrelation and entropy techniques was introduced. In the improved Markov chain model, the state transition probability matrixes can be adjusted. The steps of the historical state of the event, which was significantly related to the future state of the event, were determined by the autocorrelation technique, and the impact weights of the event historical state on the event future state were determined by the entropy technique. The presented model was applied to predicting annual precipitation and annual runoff states, showing that the improved model is of higher precision than those existing Markov chain models, and the determination of the state transition probability matrixes and the weights is more reasonable. The physical concepts of the improved model are distinct, and its computation process is simple and direct, thus, the presented model is sufficiently general to be applicable to the prediction problems in hydrology and water resources.
文摘As the increasing popularity and complexity of Web applications and the emergence of their new characteristics, the testing and maintenance of large, complex Web applications are becoming more complex and difficult. Web applications generally contain lots of pages and are used by enormous users. Statistical testing is an effective way of ensuring their quality. Web usage can be accurately described by Markov chain which has been proved to be an ideal model for software statistical testing. The results of unit testing can be utilized in the latter stages, which is an important strategy for bottom-to-top integration testing, and the other improvement of extended Markov chain model (EMM) is to present the error type vector which is treated as a part of page node. this paper also proposes the algorithm for generating test cases of usage paths. Finally, optional usage reliability evaluation methods and an incremental usability regression testing model for testing and evaluation are presented. Key words statistical testing - evaluation for Web usability - extended Markov chain model (EMM) - Web log mining - reliability evaluation CLC number TP311. 5 Foundation item: Supported by the National Defence Research Project (No. 41315. 9. 2) and National Science and Technology Plan (2001BA102A04-02-03)Biography: MAO Cheng-ying (1978-), male, Ph.D. candidate, research direction: software testing. Research direction: advanced database system, software testing, component technology and data mining.
基金Supported by Ministry of Education Humanities and Social Sciences Foundation (10YJA630070)
文摘This paper analyses the supply chain models of four types of agricultural products,namely fruits and vegetables,poultry,aquatic products and dairy,and the food safety problems arising from the links of supply chain.In view of different models,corresponding suggestions are put forward to ensure the quality safety of agricultural products in Heilongjiang Province.
文摘A precise background theory of computational mechanics is formed. Saint_Venant's principle is discussed in chain model by means of this precise theory. The classical continued fraction is developed into operator continued fraction to be the constrictive formulation of the chain model. The decay of effect of a self_equilibrated system of forces in chain model is decided by the convergence of operator continued fraction, so the reasonable part of Saint_Venant's principle is described as the convergence of operator continued fraction. In case of divergence the effect of a self_equilibrated system of forces may be non_zero at even infinite distant sections, so Saint_Venant's principle is not a common principle.
基金The authors gratefully acknowledge Qassim University,represented by the Deanship of Scientific Research,on the financial support under the number(cosao-bs-2019-2-2-I-5469)during the academic year 1440 AH/2019 AD.
文摘In this paper,a deterministic and stochastic fractional-order model of the tri-trophic food chain model incorporating harvesting is proposed and analysed.The interaction between prey,middle predator and top predator population is investigated.In order to clarify the characteristics of the proposed model,the analysis of existence,uniqueness,non-negativity and boundedness of the solutions of the proposed model are examined.Some sufficient conditions that ensure the local and global stability of equilibrium points are obtained.By using stability analysis of the fractional-order system,it is proved that if the basic reproduction number R_(0)<1,the predator free equilibrium point E_(1) is globally asymptotically stable.The occurrence of local bifurcation near the equilibrium points is investigated with the help of Sotomayor’s theorem.Some numerical examples are given to illustrate the theoretical findings.The impact of harvesting on prey and themiddle predator is studied.We conclude that harvesting parameters can control the dynamics of the middle predator.A numerical approximation method is developed for the proposed stochastic fractional-order model.
基金supported by the Malaysia-Japan International Institute of Technology(MJIIT),Universiti Teknologi Malaysia.
文摘Kuala Lumpur of Malaysia,as a tropical city,has experienced a notable decline in its critical urban green infrastructure(UGI)due to rapid urbanization and haphazard development.The decrease of UGI,especially natural forest and artificial forest,may reduce the diversity of ecosystem services and the ability of Kuala Lumpur to build resilience in the future.This study analyzed land use and land cover(LULC)and UGI changes in Kuala Lumpur based on Landsat satellite images in 1990,2005,and 2021and employed the overall accuracy and Kappa coefficient to assess classification accuracy.LULC was categorized into six main types:natural forest,artificial forest,grassland,water body,bare ground,and built-up area.Satellite images in 1990,2005,and 2021 showed the remarkable overall accuracy values of 91.06%,96.67%,and 98.28%,respectively,along with the significant Kappa coefficient values of 0.8997,0.9626,and 0.9512,respectively.Then,this study utilized Cellular Automata and Markov Chain model to analyze the transition of different LULC types during 1990-2005 and 1990-2021 and predict LULC types in 2050.The results showed that natural forest decreased from 15.22%to 8.20%and artificial forest reduced from 18.51%to 15.16%during 1990-2021.Reductions in natural forest and artificial forest led to alterations in urban surface water dynamics,increasing the risk of urban floods.However,grassland showed a significant increase from 7.80%to 24.30%during 1990-2021.Meanwhile,bare ground increased from 27.16%to 31.56%and built-up area increased from 30.45%to 39.90%during 1990-2005.In 2021,built-up area decreased to 35.10%and bare ground decreased to 13.08%,indicating a consistent dominance of built-up area in the central parts of Kuala Lumpur.This study highlights the importance of integrating past,current,and future LULC changes to improve urban ecosystem services in the city.
文摘The supply chain modeling technology is research. Firstly, the concept of supply chain and supply chain management is introduced. Secondly, enterprise modeling methods, such as CIM OSA, GIM GRAI, PERA and ARIS, are analyzed and compared. The supply chain modeling technology is studied. Then the ARIS based supply chain modeling method is proposed and the supply chain operation reference model is set up. Finally, the applications of ARIS based supply chain modeling method in Shanghai Turbine Generator Co. Ltd. (STGC) is described in detail.
文摘In this study, a fuzzy probability-based Markov chain model is developed for forecasting regional long-term electric power demand. The model can deal with the uncertainties in electric power system and reflect the vague and ambiguous during the process of power load forecasting through allowing uncertainties expressed as fuzzy parameters and discrete intervals. The developed model is applied to predict the electric power demand of Beijing from 2011 to 2019. Different satisfaction degrees of fuzzy parameters are considered as different levels of detail of the statistic data. The results indicate that the model can reflect the high uncertainty of long term power demand, which could support the programming and management of power system. The fuzzy probability Markov chain model is helpful for regional electricity power system managers in not only predicting a long term power load under uncertainty but also providing a basis for making multi-scenarios power generation/development plans.
文摘In order to improve the accuracy and efficiency of early warning system, the incident chain model and the targeted dissemination technology are proposed in this paper. Firstly, the occurrence probability, affected area and duration of disaster are predicted with the incident chain model and GIS. According to prediction results, the early warning system can accurately deliver early warning information specifically to the affected areas through targeted dissemination. Moreover, dissemination performance can also be evaluated in real time after early warning information dissemination, so that everyone in the affected area can receive early warning information successfully. The incident chain model and the targeted dissemination technology presented in this study are of great significance for improving the information dissemination ability of early warning system.
文摘In this paper we proposed an AMH Supply Chain model to obtain optimal solutions for Two-, Three- and Four-Stage for deterministic models. Besides deriving its algebraic solutions, a simple searching method is successfully applied in obtaining optimal total costs and its integer multipliers. Our model has shown promising results in comparison to Equal Cycle Time and other existing ones. The tests focused on obtaining optimal total annual costs and other related details of Two-, Three- and Four-Stage for deterministic models. The results are run under Visual Basic Programming platform using Intel? CoreTM2 Duo T6500 Processor.
基金support of Natural Science Foundation of Sichuan Province(2022NSFSC1829).
文摘In this paper,we are concerned about a food chain model with a protection zone for the prey species.Dynamical behavior,nonexistence and existence of positive steady states are obtained and there exist several critical values determined by the parameters and the protection zone for the growth rate of the prey species.The results reveal that the protection zone is effective for the survival of the prey species and beneficial for the coexistence of multiple species.Moreover,different properties of positive steady states from those of the two-species models are shown.The introduction of the prey or the top predator can be either favorable or unfavorable for the coexistence of multiple species.
文摘Amidst the unique challenges faced by rural educators is their sense of decent work influenced by levels of social support,career self-efficacy,and marginalization.To investigate these relationships,we surveyed 435 rural school teachers(females=69.32%,mean years teaching experience=13.6,SD=7.7 years).The Structural Equation Modeling results indicated that social support positively predicts teachers’perceptions of decent work.Career self-efficacy mediated the relationship between social support and a higher sense of decent work,while marginalization mediated the relationship such that lower social support predicted lower perceptions of decent work.Career self-efficacy and marginalization also had a sequential mediation relationship:higher social support enhanced career self-efficacy,which in turn reduced marginalization experiences,ultimately improving teachers’perceptions of decent work.These findings align with the predictions of Social Cognitive Career Theory and the Psychology of Working Theory,demonstrating that environmental supports enhance personal psychological resources,reduce marginalization risks,and promote positive work-related outcomes.The study findings highlight the necessity for education departments to improve rural teachers’perceptions of decent work by providing social support to foster positive work experiences for teachers at high risk for marginalization and diminished career self-efficacy.
基金Supported by the Hunan Provincial Natural Science Foundation of China,No.2025JJ80410.
文摘BACKGROUND Death anxiety(DA)is a prevalent psychological challenge among oncology nurses that affects their emotional well-being and professional competence in coping with death-related situations.Death-related attitudes and resilience are critical factors that may mediate the relationship between DA and coping with death competence(CDC).However,few studies have examined the chain-mediating effect of these factors among Chinese oncology nurses.This study aimed to investigate the association between DA and CDC among Chinese oncology nurses,with a focus on the mediating roles of death attitude and resilience.AIM To investigate the association between DA and CDC among Chinese oncology nurses.using an electronic questionnaire distributed in Wenjuanxing,China.In total,615 valid responses were obtained.The participants completed the Templer death anxiety scale,death attitude profile-revised,Connor-Davidson resilience scale,and coping with death scale.A chain mediation analysis was performed using the PROCESS macro in SPSS to examine the relationships between these variables.RESULTS The findings indicated that DA had a significant direct effect on CDC[effect=0.201,95%confidence interval(CI):0.112-0.322].In addition to this direct effect,three significant indirect pathways were observed:(1)Death attitude(effect=0.118,95%CI:0.056-0.163);(2)Resilience(effect=0.108,95%CI:0.032-0.176);and(3)A sequential mediation pathway involving both death attitude and resilience(effect=0.071,95%CI:0.042-0.123).The total indirect effects of the three mediation paths accounted for 29.7%of the relationship between DA and CDC.CONCLUSION Using a chain mediation model,this study explored the mechanisms linking DA,death attitude,resilience,and CDC among Chinese oncology nurses.These findings highlighted the crucial role of death attitude and resilience in mediating the relationship between DA and CDC.Interventions aimed at fostering adaptive attitudes toward death and enhancing resilience may improve nurses’ability to cope with death-related stressors,ultimately benefiting their psychological well-being and professional competence.
基金the Young Investigator Group“Artificial Intelligence for Probabilistic Weather Forecasting”funded by the Vector Stiftungfunding from the Federal Ministry of Education and Research(BMBF)and the Baden-Württemberg Ministry of Science as part of the Excellence Strategy of the German Federal and State Governments。
文摘Weather forecasts from numerical weather prediction models play a central role in solar energy forecasting,where a cascade of physics-based models is used in a model chain approach to convert forecasts of solar irradiance to solar power production.Ensemble simulations from such weather models aim to quantify uncertainty in the future development of the weather,and can be used to propagate this uncertainty through the model chain to generate probabilistic solar energy predictions.However,ensemble prediction systems are known to exhibit systematic errors,and thus require post-processing to obtain accurate and reliable probabilistic forecasts.The overarching aim of our study is to systematically evaluate different strategies to apply post-processing in model chain approaches with a specific focus on solar energy:not applying any post-processing at all;post-processing only the irradiance predictions before the conversion;post-processing only the solar power predictions obtained from the model chain;or applying post-processing in both steps.In a case study based on a benchmark dataset for the Jacumba solar plant in the U.S.,we develop statistical and machine learning methods for postprocessing ensemble predictions of global horizontal irradiance(GHI)and solar power generation.Further,we propose a neural-network-based model for direct solar power forecasting that bypasses the model chain.Our results indicate that postprocessing substantially improves the solar power generation forecasts,in particular when post-processing is applied to the power predictions.The machine learning methods for post-processing slightly outperform the statistical methods,and the direct forecasting approach performs comparably to the post-processing strategies.
文摘Using a modified subgradient extragradient algorithm, this paper proposed a novel approach to solving a supply chain network equilibrium model. The method extends the scope of optimisation and improves the accuracy at each iteration by incorporating adaptive parameter selection and a more general subgradient projection operator. The advantages of the proposed method are highlighted by the proof of strong convergence presented in the paper. Several concrete examples are given to demonstrate the effectiveness of the algorithm, with comparisons illustrating its superior CPU running time compared to alternative techniques. The practical applicability of the algorithm is also demonstrated by applying it to a realistic supply chain network model.
基金supported by the National Key Basic Research Program of China (973 Program) (Grant No. 2011CB706803)the National Natural Science Foundation of China (Grant Nos. 51175208, 51075161)
文摘In the traditional Markov chain model (MCM), aleatory uncertainty because of inherent randomness and epistemic uncertainty due to the lack of knowledge are not differentiated. Generalized interval probability provides a concise representation for the two kinds of uncertainties simultaneously. In this paper, a generalized Markov chain model (GMCM), based on the generalized interval probability theory, is proposed to improve the reliability of prediction. In the GMCM, aleatory uncertainty is represented as probability; interval is used to capture epistemic uncertainty. A case study for predicting the average dynamic compliance in machining processes is provided to demonstrate the effectiveness of proposed GMCM. The results show that the proposed GMCM has a better prediction performance than that of MCM.
基金This research was supported in part by the Young Elite Scientist Sponsorship Program(No.2017QNRC001)the China Association for Science and Technology and a Start-Up Grant(No.M4082268.050)from Nanyang Technological University,Singapore.
文摘This study developed a new online driving cycle prediction method for hybrid electric vehicles based on a three-dimensional stochastic Markov chain model and applied the method to a driving-cycle-aware energy management strategy.The impacts of different prediction time lengths on driving cycle generation were explored.The results indicate that the original driving cycle is compressed by 50%,which significantly reduces the computational burden while having only a slight effect on the prediction performance.The developed driving cycle prediction method was implemented in a real-time energy management algorithm with a hybrid electric vehicle powertrain model,and the model was verified by simulation using two different testing scenarios.The testing results demonstrate that the developed driving cycle prediction method is able to efficiently predict future driving tasks,and it can be successfully used for the energy management of hybrid electric vehicles.
基金supported by the National Natural Science Foundation of China (11032006, 11072094, and 11121202)the PhD Program Foundation of the Ministry of Education of China (20100211110022)+1 种基金New Century Excellent Talents in University (NCET-10-0445)supported by the National Science Foundation through grant CMMI-1028530 to Brown University
文摘The molecular biomechanics of DNA ejection from bacteriophage is of interest to not only fundamental biological understandings but also practical applications such as the design of advanced site-specific and controllable drug delivery systems. In this paper, we analyze the viscous motion of a semiflexible polymer chain coming out of a strongly confined space as a model to investigate the effects of various structure confinements and frictional resistances encountered during the DNA ejection process. The theoretically predicted relations between the ejection speed, ejection time, ejection length, and other physical parameters, such as the phage type, total genome length and ionic state of external buffer solutions, show excellent agreement with in vitro experimental observations in the literature.
