Near-infrared (NIR) spectroscopy was applied to reagent-free quantitative analysis of polysaccharide of a brand product of proprietary Chinese medicine (PCM) oral solution samples. A novel method, called absorbance up...Near-infrared (NIR) spectroscopy was applied to reagent-free quantitative analysis of polysaccharide of a brand product of proprietary Chinese medicine (PCM) oral solution samples. A novel method, called absorbance upper optimization partial least squares (AUO-PLS), was proposed and successfully applied to the wavelength selection. Based on varied partitioning of the calibration and prediction sample sets, the parameter optimization was performed to achieve stability. On the basis of the AUO-PLS method, the selected upper bound of appropriate absorbance was 1.53 and the corresponding wavebands combination was 400 - 1880 & 2088 - 2346 nm. With the use of random validation samples excluded from the modeling process, the root-mean-square error and correlation coefficient of prediction for polysaccharide were 27.09 mg·L<sup>-</sup><sup>1</sup> and 0.888, respectively. The results indicate that the NIR prediction values are close to those of the measured values. NIR spectroscopy combined with AUO-PLS method provided a promising tool for quantification of the polysaccharide for PCM oral solution and this technique is rapid and simple when compared with conventional methods.展开更多
In this article, we consider nonlinear elliptic systems of divergence type with Dini continuous coefficients. The authors use a new method introduced by Duzaar and Grotowski, to prove partial regularity for weak solut...In this article, we consider nonlinear elliptic systems of divergence type with Dini continuous coefficients. The authors use a new method introduced by Duzaar and Grotowski, to prove partial regularity for weak solutions, based on a generalization of the technique of harmonic approximation and directly establish the optimal HSlder exponent for the derivative of a weak solution on its regular set.展开更多
This paper proposes an improved version of the Partial Reinforcement Optimizer(PRO),termed LNPRO.The LNPRO has undergone a learner phase,which allows for further communication of information among the PRO population,c...This paper proposes an improved version of the Partial Reinforcement Optimizer(PRO),termed LNPRO.The LNPRO has undergone a learner phase,which allows for further communication of information among the PRO population,changing the state of the PRO in terms of self-strengthening.Furthermore,the Nelder-Mead simplex is used to optimize the best agent in the population,accelerating the convergence speed and improving the accuracy of the PRO population.By comparing LNPRO with nine advanced algorithms in the IEEE CEC 2022 benchmark function,the convergence accuracy of the LNPRO has been verified.The accuracy and stability of simulated data and real data in the parameter extraction of PV systems are crucial.Compared to the PRO,the precision and stability of LNPRO have indeed been enhanced in four types of photovoltaic components,and it is also superior to other excellent algorithms.To further verify the parameter extraction problem of LNPRO in complex environments,LNPRO has been applied to three types of manufacturer data,demonstrating excellent results under varying irradiation and temperatures.In summary,LNPRO holds immense potential in solving the parameter extraction problems in PV systems.展开更多
Facing the current situation of global energy consumption and increasingly serious environmental pollution, countries have accelerated the construction of new energy systems and put forward the "3060" double...Facing the current situation of global energy consumption and increasingly serious environmental pollution, countries have accelerated the construction of new energy systems and put forward the "3060" double-carbon target. Photovoltaic power generation attracts peoples attention, and it has the advantages of renewable and pollution-free, and the installed capacity of photovoltaic is doubled every year. In photovoltaic systems, the common factor that affects the electric quantity is partial occlusion. Different local occlusion affects the I-U output of components, so the traditional MPPT tracking algorithm of series inverter cant reach the maximum output of the array, and is only limited to the local optimal output. Therefore, this paper focuses on the nonlinear characteristics of photovoltaic array output, and optimizes the algorithm based on the conventional particle swarm optimization algorithm. The sim ulation model of photovoltaic sequence used in Hainan Tunchang Xinye Power Station is established by MATLAB/Simulink software. By using the disturbance observation method used by the inverter of the power station and the optimization algorithm particle swarm optimization proposed this time, the maximum power tracking of photovoltaic is analyzed under the conditions of uniform illumination and local shadow, and the peak value of the output characteristic curve of the two algorithms when adjusting the maximum power tracking of photovoltaic sequence is verified.展开更多
Environmental protection requires identifying,investigating,and raising awareness about safeguarding nature from the harmful effects of both anthropogenic and natural events.This process of environmental protection is...Environmental protection requires identifying,investigating,and raising awareness about safeguarding nature from the harmful effects of both anthropogenic and natural events.This process of environmental protection is essential for maintaining human well-being.In this context,it is critical to monitor and safeguard the personal environment,which includes maintaining a healthy diet and ensuring plant safety.Living in a balanced environment and ensuring the safety of plants for green spaces and a healthy diet require controlling the nature and quality of the soil in our environment.To ensure soil quality,it is imperative to monitor and assess the levels of various soil parameters.Therefore,an Optimized Reduced Kernel Partial Least Squares(ORKPLS)method is proposed to monitor and control soil parameters.This approach is designed to detect increases or deviations in soil parameter quantities.A Tabu search approach was used to select the appropriate kernel parameter.Subsequently,soil analyses were conducted to evaluate the performance of the developed techniques.The simulation results were analyzed and compared.Through this study,deficiencies or exceedances in soil parameter quantities can be identified.The proposed method involves determining whether each soil parameter falls within a normal range.This allows for the assessment of soil parameter conditions based on the principle of fault detection.展开更多
Teicoplanin(TCP)is an important lipoglycopeptide antibiotic produced by fermenting Acti-noplanes teichomyceticus.The change in TCP concentration is important to measure in the fermentation process.In this study,a reag...Teicoplanin(TCP)is an important lipoglycopeptide antibiotic produced by fermenting Acti-noplanes teichomyceticus.The change in TCP concentration is important to measure in the fermentation process.In this study,a reagent-free and rapid quantification method for TCP in the TCP-Tris-HCl mixture samples was developed using near infrared(NIR)spectroscopy by focusing our attention on the fermentation process for TCP.The absorbance optimization(AO)partial least squares(PLS)was proposed and integrated with the moving window(MW)PLS,which is called AO-MW-PLS method,to select appropriate wavebands.Amodel set that includes various wavebands that were equivalent to the optimal AO-MW-PLS waveband was,proposed based on statistical considerations.The public region of all equivalent wavebands was just one of the equivalent wavebands.The obtained public regions were 1540-1868 nm for TCP and 1114-1310 nm for Tris.The root-mean-square error and correlation coeficient for leave-one-out cross validation were 0.046 mg mL^(-1)and 0.9998 mg mL^(-1)for TCP,and 0.235 mg mL^(-1)and 0.9986 mg mL^(-1)for Tris,respectively.All the models achieved highly accurate prediction effects,and the selected wavebands provided valuable references for designing specialized spectrometers.This study provided a valuable reference for further application of the proposed methods to TCP fermentation broth and to other spectroscopic analysis fields.展开更多
This study examines an optimal inventory strategy when a retailer markets a product at different selling prices through a dual-channel supply chain, comprising an online channel and an offiine channel. Using the opera...This study examines an optimal inventory strategy when a retailer markets a product at different selling prices through a dual-channel supply chain, comprising an online channel and an offiine channel. Using the operating pattern of the offiine-to-online （020） business model, we develop a partial robust optimization （PRO） model. Then, we provide a closed-form solution when only the mean and standard deviation of the online channel demand distribution is known and the offiine channel demand follows a uniform distribution （partial robust）. Specifically, owing to the good structural properties of the solution, we obtain a heuristic ordering formula for the general distribution case （i.e., the offiine channel demand follows a general distribution）. In addition, a series of numerical experiments prove the rationality of our conjecture. Moreover, after comparing our solution with other possible policies, we conclude that the PRO approach improves the performance of incorporating the internet into an existing supply chain and, thus, is able to adjust the level of conservativeness of the solution. Finally, in a degenerated situation, we compare our PRO approach with a combination of information approach. The results show that the PRO approach has more ＂robust＂ performance. As a result, a reasonable trade-off between robustness and performance is achieved.展开更多
In the field of fault tolerance estimation,the increasing attention in electrical motors is the fault detection and diagnosis.The tasks performed by these machines are progressively complex and the enhancements are li...In the field of fault tolerance estimation,the increasing attention in electrical motors is the fault detection and diagnosis.The tasks performed by these machines are progressively complex and the enhancements are likewise looked for in the field of fault diagnosis.It has now turned out to be essential to diagnose faults at their very inception;as unscheduled machine downtime can upset deadlines and cause heavy financial burden.In this paper,fault diagnosis and speed control of permanent magnet synchronous motor(PMSM)is proposed.Elman Neural Network(ENN)is used to diagnose the fault of permanent magnet synchronous motor.Both the fault location and fault severity are considered.In this,eccentricity fault may occur in the motor.To control the speed of the permanent magnet synchronous motor,Dolphin Swarm Optimization(DSO)algorithm is used.The proposed work is simulated by using MATLAB in terms of amplitude,speed and torque.The comparison graph of speed vs.torque obtained by the proposed method gives better result compared to the other existing techniques.The proposed work is also compared with Particle Swarm Optimization(PSO)and Elephant Herding Optimization(EHO)algorithm.The proposed usage of Elman Neural Network to detect the fault and the usage of Dolphin Swarm Optimization algorithm to control the speed of the permanent magnet synchronous motor gives better outcome.展开更多
There are many optimization problems having the following common property:Given a total task consisting of many subtasks,the problem asks to find a solution to complete only part of these subtasks.Examples include the...There are many optimization problems having the following common property:Given a total task consisting of many subtasks,the problem asks to find a solution to complete only part of these subtasks.Examples include the k-Forest problem and the k-Multicut problem,etc.These problems are called partial optimization problems,which are often NP-hard.In this paper,we systematically study the LP-rounding plus greed approach,a method to design approximation algorithms for partial optimization problems.The approach is simple,powerful and versatile.We show how to use this approach to design approximation algorithms for the k-Forest problem,the k-Multicut problem,the k-Generalized connectivity problem,etc.展开更多
Wireless body area networks(WBANs)can provide low-cost,timely healthcare services and are expected to be widely used for e-healthcare in hospitals.In a hospital,space is often limited and multiple WBANs have to coexis...Wireless body area networks(WBANs)can provide low-cost,timely healthcare services and are expected to be widely used for e-healthcare in hospitals.In a hospital,space is often limited and multiple WBANs have to coexist in an area and share the same channel in order to provide healthcare services to different patients.This causes severe interference between WBANs that could significantly reduce the network throughput and increase the amount of power consumed by sensors placed on the body.There-fore,an efficient channel-resource allocation scheme in the medium access control(MAC)layer is crucial.In this paper,we devel-op a centralized MAC layer resource allocation scheme for a WBAN.We focus on mitigating the interference between WBANs and reducing the power consumed by sensors.Channel and buffer state are reported by smartphones deployed in each WBAN,and channel access allocation is performed by a central controller to maximize network throughput.Sensors have strict limitations in terms of energy consumption and computing capability and cannot provide all the necessary information for channel allocation in a timely manner.This deteriorates network performance.We exploit the temporal correlation of the body area channel in order to minimize the number of channel state reports necessary.We view the network design as a partly observable optimization prob-lem and develop a myopic policy,which we then simulate in Matlab.展开更多
This paper studies the problem of partially observed optimal control for forward-backward stochastic systems which are driven both by Brownian motions and an independent Poisson random measure. Combining forward-backw...This paper studies the problem of partially observed optimal control for forward-backward stochastic systems which are driven both by Brownian motions and an independent Poisson random measure. Combining forward-backward stochastic differential equation theory with certain classical convex variational techniques, the necessary maximum principle is proved for the partially observed optimal control, where the control domain is a nonempty convex set. Under certain convexity assumptions, the author also gives the sufficient conditions of an optimal control for the aforementioned optimal optimal problem. To illustrate the theoretical result, the author also works out an example of partial information linear-quadratic optimal control, and finds an explicit expression of the corresponding optimal control by applying the necessary and sufficient maximum principle.展开更多
We consider the partial regularity for weak solutions to superquadratic elliptic systems with controllable growth condition, under the assumption of Dini continuous coefficients. The proof relies upon an iteration sch...We consider the partial regularity for weak solutions to superquadratic elliptic systems with controllable growth condition, under the assumption of Dini continuous coefficients. The proof relies upon an iteration scheme of a decay estimate for a new type of excess functional. To establish the decay estimate, we use the technique of A-harmonic approximation and obtain a general criterion for a weak solution to be regular in the neighborhood of a given point. In particular, the proof yields directly the optimal H¨older exponent for the derivative of the weak solutions on the regular set.展开更多
文摘Near-infrared (NIR) spectroscopy was applied to reagent-free quantitative analysis of polysaccharide of a brand product of proprietary Chinese medicine (PCM) oral solution samples. A novel method, called absorbance upper optimization partial least squares (AUO-PLS), was proposed and successfully applied to the wavelength selection. Based on varied partitioning of the calibration and prediction sample sets, the parameter optimization was performed to achieve stability. On the basis of the AUO-PLS method, the selected upper bound of appropriate absorbance was 1.53 and the corresponding wavebands combination was 400 - 1880 & 2088 - 2346 nm. With the use of random validation samples excluded from the modeling process, the root-mean-square error and correlation coefficient of prediction for polysaccharide were 27.09 mg·L<sup>-</sup><sup>1</sup> and 0.888, respectively. The results indicate that the NIR prediction values are close to those of the measured values. NIR spectroscopy combined with AUO-PLS method provided a promising tool for quantification of the polysaccharide for PCM oral solution and this technique is rapid and simple when compared with conventional methods.
基金Supported by NSF of China (10531020)the Education Department of Fujian Province(JK2009045)the Program of 985 Innovation Engieering on Information in Xiamen University(2004-2007)
文摘In this article, we consider nonlinear elliptic systems of divergence type with Dini continuous coefficients. The authors use a new method introduced by Duzaar and Grotowski, to prove partial regularity for weak solutions, based on a generalization of the technique of harmonic approximation and directly establish the optimal HSlder exponent for the derivative of a weak solution on its regular set.
基金supported in part by the Natural Science Foundation of Zhejiang Province(LTGS23E070001).
文摘This paper proposes an improved version of the Partial Reinforcement Optimizer(PRO),termed LNPRO.The LNPRO has undergone a learner phase,which allows for further communication of information among the PRO population,changing the state of the PRO in terms of self-strengthening.Furthermore,the Nelder-Mead simplex is used to optimize the best agent in the population,accelerating the convergence speed and improving the accuracy of the PRO population.By comparing LNPRO with nine advanced algorithms in the IEEE CEC 2022 benchmark function,the convergence accuracy of the LNPRO has been verified.The accuracy and stability of simulated data and real data in the parameter extraction of PV systems are crucial.Compared to the PRO,the precision and stability of LNPRO have indeed been enhanced in four types of photovoltaic components,and it is also superior to other excellent algorithms.To further verify the parameter extraction problem of LNPRO in complex environments,LNPRO has been applied to three types of manufacturer data,demonstrating excellent results under varying irradiation and temperatures.In summary,LNPRO holds immense potential in solving the parameter extraction problems in PV systems.
文摘Facing the current situation of global energy consumption and increasingly serious environmental pollution, countries have accelerated the construction of new energy systems and put forward the "3060" double-carbon target. Photovoltaic power generation attracts peoples attention, and it has the advantages of renewable and pollution-free, and the installed capacity of photovoltaic is doubled every year. In photovoltaic systems, the common factor that affects the electric quantity is partial occlusion. Different local occlusion affects the I-U output of components, so the traditional MPPT tracking algorithm of series inverter cant reach the maximum output of the array, and is only limited to the local optimal output. Therefore, this paper focuses on the nonlinear characteristics of photovoltaic array output, and optimizes the algorithm based on the conventional particle swarm optimization algorithm. The sim ulation model of photovoltaic sequence used in Hainan Tunchang Xinye Power Station is established by MATLAB/Simulink software. By using the disturbance observation method used by the inverter of the power station and the optimization algorithm particle swarm optimization proposed this time, the maximum power tracking of photovoltaic is analyzed under the conditions of uniform illumination and local shadow, and the peak value of the output characteristic curve of the two algorithms when adjusting the maximum power tracking of photovoltaic sequence is verified.
基金supported by the Deputyship for Research and Innovation,Ministry of Education in Saudi Arabia for funding this research work through the project number(0226-1443-S).
文摘Environmental protection requires identifying,investigating,and raising awareness about safeguarding nature from the harmful effects of both anthropogenic and natural events.This process of environmental protection is essential for maintaining human well-being.In this context,it is critical to monitor and safeguard the personal environment,which includes maintaining a healthy diet and ensuring plant safety.Living in a balanced environment and ensuring the safety of plants for green spaces and a healthy diet require controlling the nature and quality of the soil in our environment.To ensure soil quality,it is imperative to monitor and assess the levels of various soil parameters.Therefore,an Optimized Reduced Kernel Partial Least Squares(ORKPLS)method is proposed to monitor and control soil parameters.This approach is designed to detect increases or deviations in soil parameter quantities.A Tabu search approach was used to select the appropriate kernel parameter.Subsequently,soil analyses were conducted to evaluate the performance of the developed techniques.The simulation results were analyzed and compared.Through this study,deficiencies or exceedances in soil parameter quantities can be identified.The proposed method involves determining whether each soil parameter falls within a normal range.This allows for the assessment of soil parameter conditions based on the principle of fault detection.
基金the Science and Tech-nology Project of Guangdong Province of China,(Nos.2014A020213016 and 2014A020212445)the Science and Technology Project of Guangzhou of China(No.2011Y5-00002).
文摘Teicoplanin(TCP)is an important lipoglycopeptide antibiotic produced by fermenting Acti-noplanes teichomyceticus.The change in TCP concentration is important to measure in the fermentation process.In this study,a reagent-free and rapid quantification method for TCP in the TCP-Tris-HCl mixture samples was developed using near infrared(NIR)spectroscopy by focusing our attention on the fermentation process for TCP.The absorbance optimization(AO)partial least squares(PLS)was proposed and integrated with the moving window(MW)PLS,which is called AO-MW-PLS method,to select appropriate wavebands.Amodel set that includes various wavebands that were equivalent to the optimal AO-MW-PLS waveband was,proposed based on statistical considerations.The public region of all equivalent wavebands was just one of the equivalent wavebands.The obtained public regions were 1540-1868 nm for TCP and 1114-1310 nm for Tris.The root-mean-square error and correlation coeficient for leave-one-out cross validation were 0.046 mg mL^(-1)and 0.9998 mg mL^(-1)for TCP,and 0.235 mg mL^(-1)and 0.9986 mg mL^(-1)for Tris,respectively.All the models achieved highly accurate prediction effects,and the selected wavebands provided valuable references for designing specialized spectrometers.This study provided a valuable reference for further application of the proposed methods to TCP fermentation broth and to other spectroscopic analysis fields.
文摘This study examines an optimal inventory strategy when a retailer markets a product at different selling prices through a dual-channel supply chain, comprising an online channel and an offiine channel. Using the operating pattern of the offiine-to-online （020） business model, we develop a partial robust optimization （PRO） model. Then, we provide a closed-form solution when only the mean and standard deviation of the online channel demand distribution is known and the offiine channel demand follows a uniform distribution （partial robust）. Specifically, owing to the good structural properties of the solution, we obtain a heuristic ordering formula for the general distribution case （i.e., the offiine channel demand follows a general distribution）. In addition, a series of numerical experiments prove the rationality of our conjecture. Moreover, after comparing our solution with other possible policies, we conclude that the PRO approach improves the performance of incorporating the internet into an existing supply chain and, thus, is able to adjust the level of conservativeness of the solution. Finally, in a degenerated situation, we compare our PRO approach with a combination of information approach. The results show that the PRO approach has more ＂robust＂ performance. As a result, a reasonable trade-off between robustness and performance is achieved.
文摘In the field of fault tolerance estimation,the increasing attention in electrical motors is the fault detection and diagnosis.The tasks performed by these machines are progressively complex and the enhancements are likewise looked for in the field of fault diagnosis.It has now turned out to be essential to diagnose faults at their very inception;as unscheduled machine downtime can upset deadlines and cause heavy financial burden.In this paper,fault diagnosis and speed control of permanent magnet synchronous motor(PMSM)is proposed.Elman Neural Network(ENN)is used to diagnose the fault of permanent magnet synchronous motor.Both the fault location and fault severity are considered.In this,eccentricity fault may occur in the motor.To control the speed of the permanent magnet synchronous motor,Dolphin Swarm Optimization(DSO)algorithm is used.The proposed work is simulated by using MATLAB in terms of amplitude,speed and torque.The comparison graph of speed vs.torque obtained by the proposed method gives better result compared to the other existing techniques.The proposed work is also compared with Particle Swarm Optimization(PSO)and Elephant Herding Optimization(EHO)algorithm.The proposed usage of Elman Neural Network to detect the fault and the usage of Dolphin Swarm Optimization algorithm to control the speed of the permanent magnet synchronous motor gives better outcome.
基金The work was supported by the National Natural Science Foundation of China(Grant Nos.61972228,61672323,61672328)the Natural Science Foundation of Shandong Province(ZR2016AM28,ZR2019MF072).
文摘There are many optimization problems having the following common property:Given a total task consisting of many subtasks,the problem asks to find a solution to complete only part of these subtasks.Examples include the k-Forest problem and the k-Multicut problem,etc.These problems are called partial optimization problems,which are often NP-hard.In this paper,we systematically study the LP-rounding plus greed approach,a method to design approximation algorithms for partial optimization problems.The approach is simple,powerful and versatile.We show how to use this approach to design approximation algorithms for the k-Forest problem,the k-Multicut problem,the k-Generalized connectivity problem,etc.
基金supported by a research grant from the Natural Science and Engineering Research Council(NSERC)under grant No.CRDPJ 419147-11Care In Motion Inc.,Canada
文摘Wireless body area networks(WBANs)can provide low-cost,timely healthcare services and are expected to be widely used for e-healthcare in hospitals.In a hospital,space is often limited and multiple WBANs have to coexist in an area and share the same channel in order to provide healthcare services to different patients.This causes severe interference between WBANs that could significantly reduce the network throughput and increase the amount of power consumed by sensors placed on the body.There-fore,an efficient channel-resource allocation scheme in the medium access control(MAC)layer is crucial.In this paper,we devel-op a centralized MAC layer resource allocation scheme for a WBAN.We focus on mitigating the interference between WBANs and reducing the power consumed by sensors.Channel and buffer state are reported by smartphones deployed in each WBAN,and channel access allocation is performed by a central controller to maximize network throughput.Sensors have strict limitations in terms of energy consumption and computing capability and cannot provide all the necessary information for channel allocation in a timely manner.This deteriorates network performance.We exploit the temporal correlation of the body area channel in order to minimize the number of channel state reports necessary.We view the network design as a partly observable optimization prob-lem and develop a myopic policy,which we then simulate in Matlab.
基金This research is supported by the National Nature Science Foundation of China under Grant Nos 11001156, 11071144, the Nature Science Foundation of Shandong Province （ZR2009AQ017）, and Independent Innovation Foundation of Shandong University （IIFSDU）, China.
文摘This paper studies the problem of partially observed optimal control for forward-backward stochastic systems which are driven both by Brownian motions and an independent Poisson random measure. Combining forward-backward stochastic differential equation theory with certain classical convex variational techniques, the necessary maximum principle is proved for the partially observed optimal control, where the control domain is a nonempty convex set. Under certain convexity assumptions, the author also gives the sufficient conditions of an optimal control for the aforementioned optimal optimal problem. To illustrate the theoretical result, the author also works out an example of partial information linear-quadratic optimal control, and finds an explicit expression of the corresponding optimal control by applying the necessary and sufficient maximum principle.
基金Supported by the National Natural Science Foundation of China(No.10976026)Natural Science Foundation of Fujian Province(2012D102)
文摘We consider the partial regularity for weak solutions to superquadratic elliptic systems with controllable growth condition, under the assumption of Dini continuous coefficients. The proof relies upon an iteration scheme of a decay estimate for a new type of excess functional. To establish the decay estimate, we use the technique of A-harmonic approximation and obtain a general criterion for a weak solution to be regular in the neighborhood of a given point. In particular, the proof yields directly the optimal H¨older exponent for the derivative of the weak solutions on the regular set.
