Entropy generation is often used as a figure of merit in thermodynamic cycle optimizations. In this paper, it is shown that the applicability of the minimum entropy generation method to optimizing output power is cond...Entropy generation is often used as a figure of merit in thermodynamic cycle optimizations. In this paper, it is shown that the applicability of the minimum entropy generation method to optimizing output power is conditional. The minimum entropy generation rate and the minimum entropy generation number do not correspond to the maximum output power when the total heat into the system of interest is not prescribed. For the cycles whose working medium is heated or cooled by streams with prescribed inlet temperatures and prescribed heat capacity flow rates, it is theoretically proved that both the minimum entropy generation rate and the minimum entropy generation number correspond to the maximum output power when the virtual entropy generation induced by dumping the used streams into the environment is considered. However, the minimum principle of entropy generation is not tenable in the case that the virtual entropy generation is not included, because the total heat into the system of interest is not fixed. An irreversible Carnot cycle and an irreversible Brayton cycle are analysed. The minimum entropy generation rate and the minimum entropy generation number do not correspond to the maximum output power if the heat into the system of interest is not prescribed.展开更多
In thermal radiation, taking heat flow as an extensive quantity and defining the potential as temperature T or the black body emissive power U will lead to two different definitions of radiation entransy flow and the ...In thermal radiation, taking heat flow as an extensive quantity and defining the potential as temperature T or the black body emissive power U will lead to two different definitions of radiation entransy flow and the corresponding principles for thermal radiation optimization. The two definitions of radiation entransy flow and the corresponding optimization prin ciples are compared in this paper. When the total heat flow is given, the optimization objectives of the extremum entransy dissipation principles （EEDPs） developed based on potentials T and U correspond to the minimum equivalent temperature difference and the minimum equivalent blackbody emissive power difference respectively. The physical meaning of the definition based on potential U is clearer than that based on potential T, but the latter one can be used for the coupled heat transfer optimization problem while the former one cannot. The extremum entropy generation principle （EEGP） for thermal radiation is also derived, which includes the minimum entropy generation principle for thermal radiation. When the radiation heat flow is prescribed, the EEGP reveals that the minimum entropy generation leads to the minimum equivalent thermodynamic potential difference, which is not the expected objective in heat transfer. Therefore, the minimum entropy generation is not always appropriate for thermal radiation optimization. Finally, three thermal radiation optimization examples are discussed, and the results show that the difference in optimization objective between the EEDPs and the EEGP leads to the difference between the optimization results. The EEDP based on potential T is more useful in practical application since its optimization objective is usually consistent with the expected one.展开更多
Selecting optimization ship form scheme is an important content in the process of concept design of ship. Multi-objective fuzzy decision-making model for ship form demonstration is set up according to the fuzzy patter...Selecting optimization ship form scheme is an important content in the process of concept design of ship. Multi-objective fuzzy decision-making model for ship form demonstration is set up according to the fuzzy pattern-recognition theory. Weight coefficients of each target of ship form scheme are determined by information entropy and individual subjective partiality. This model is used to select the optimal ship form scheme, the example shows that the model is exact and the resuh is credible. It can provide a reference for choosing the optimization scheme of ship form.展开更多
From the viewpoint of quantum information, this paper studies preparation and control of atomic optimal entropy squeezing states （AOESS） for a moving two-level atom under control of the two-mode squeezing vacuum fie...From the viewpoint of quantum information, this paper studies preparation and control of atomic optimal entropy squeezing states （AOESS） for a moving two-level atom under control of the two-mode squeezing vacuum fields. Necessary conditions of preparation of the AOESS are analysed, and numerical verification of the AOESS is finished. It shows that the AOESS can be prepared by controlling the time of the atom interaction with the field, cutting the entanglement between the atom and field, and adjusting squeezing factor of the field. An atomic optimal entropy squeezing sudden generation in different components can alternately be realized by controlling the field-mode structure parameter.展开更多
In this study,an optimization method is proposed to enhance the gas–liquid mass transfer in bubble column reactor based on the entropy generation extremum principle.The mass transfer–induced entropy generation can b...In this study,an optimization method is proposed to enhance the gas–liquid mass transfer in bubble column reactor based on the entropy generation extremum principle.The mass transfer–induced entropy generation can be maximized with the increase of mass transfer rate,based on which the velocity field can be optimized.The oxygen gas–liquid mass transfer is the major rate–limiting step of the toluene emissions biodegradation process in bubble column reactor,so the entropy generation due to oxygen mass transfer is used as the objective function,and the conservation equations of the gas–liquid flow and species concentration are taken as constraints.This optimization problem is solved by the calculus of variations,the optimal liquid flow pattern is obtained and the relationship of the maximum mass transfer enhancement on viscous dissipation is revealed,which can be used to improve the design of internal structure of the bubble column reactor.展开更多
To study the problems of multi-attribute decision making in which the attribute values are given in the form of linguistic fuzzy numbers and the information of attribute weights are incomplete, a new multi-attribute d...To study the problems of multi-attribute decision making in which the attribute values are given in the form of linguistic fuzzy numbers and the information of attribute weights are incomplete, a new multi-attribute decision making model is presented based on the optimal membership and the relative entropy. Firstly, the definitions of the optimal membership and the relative entropy are given. Secondly, for all alternatives, a set of preference weight vectors are obtained by solving a set of linear programming models whose goals axe all to maximize the optimal membership. Thirdly, a relative entropy model is established to aggregate the preference weight vectors, thus an optimal weight vector is determined. Based on this optimal weight vector, the algorithm of deviation degree minimization is proposed to rank all the alternatives. Finally, a decision making example is given to demonstrate the feasibility and rationality of this new model.展开更多
Considering two atomic qubits initially in Bell states, we send one qubit into a vacuum cavity with two-photon resonance and leave the other one outside. Using quantum information entropy squeezing theory, the time ev...Considering two atomic qubits initially in Bell states, we send one qubit into a vacuum cavity with two-photon resonance and leave the other one outside. Using quantum information entropy squeezing theory, the time evolutions of the entropy squeezing factor of the atomic qubit inside the cavity are discussed for two cases, i.e., before and after rotation and measurement of the atomic qubit outside the cavity. It is shown that the atomic qubit inside the cavity has no entropy squeezing phenomenon and is always in a decoherent state before the operating atomic qubit outside the cavity. However,the periodical entropy squeezing phenomenon emerges and the optimal entropy squeezing state can be prepared for the atomic qubit inside the cavity by adjusting the rotation angle, choosing the interaction time between the atomic qubit and the cavity, controlling the probability amplitudes of subsystem states. Its physical essence is cutting the entanglement between the atomic qubit and its environment, causing the atomic qubit inside the cavity to change from the initial decoherent state into maximum coherent superposition state, which is a possible way of recovering the coherence of a single atomic qubit in the noise environment.展开更多
Since the logarithmic form of Shannon entropy has the drawback of undefined value at zero points,and most existing threshold selection methods only depend on the probability information,ignoring the within-class unifo...Since the logarithmic form of Shannon entropy has the drawback of undefined value at zero points,and most existing threshold selection methods only depend on the probability information,ignoring the within-class uniformity of gray level,a method of reciprocal gray entropy threshold selection is proposed based on two-dimensional(2-D)histogram region oblique division and artificial bee colony(ABC)optimization.Firstly,the definition of reciprocal gray entropy is introduced.Then on the basis of one-dimensional(1-D)method,2-D threshold selection criterion function based on reciprocal gray entropy with histogram oblique division is derived.To accelerate the progress of searching the optimal threshold,the recently proposed ABC optimization algorithm is adopted.The proposed method not only avoids the undefined value points in Shannon entropy,but also achieves high accuracy and anti-noise performance due to reasonable 2-D histogram region division and the consideration of within-class uniformity of gray level.A large number of experimental results show that,compared with the maximum Shannon entropy method with 2-D histogram oblique division and the reciprocal entropy method with 2-D histogram oblique division based on niche chaotic mutation particle swarm optimization(NCPSO),the proposed method can achieve better segmentation results and can satisfy the requirement of real-time processing.展开更多
The maximum entropy distribution, which consists of various recognized theoretical distributions, is a better curve to estimate the design thickness of sea ice. Method of moment and empirical curve fitting method are ...The maximum entropy distribution, which consists of various recognized theoretical distributions, is a better curve to estimate the design thickness of sea ice. Method of moment and empirical curve fitting method are common-used parameter estimation methods for maximum entropy distribution. In this study, we propose to use the particle swarm optimization method as a new parameter estimation method for the maximum entropy distribution, which has the advantage to avoid deviation introduced by simplifications made in other methods. We conducted a case study to fit the hindcasted thickness of the sea ice in the Liaodong Bay of Bohai Sea using these three parameter-estimation methods for the maximum entropy distribution. All methods implemented in this study pass the K-S tests at 0.05 significant level. In terms of the average sum of deviation squares, the empirical curve fitting method provides the best fit for the original data, while the method of moment provides the worst. Among all three methods, the particle swarm optimization method predicts the largest thickness of the sea ice for a same return period. As a result, we recommend using the particle swarm optimization method for the maximum entropy distribution for offshore structures mainly influenced by the sea ice in winter, but using the empirical curve fitting method to reduce the cost in the design of temporary and economic buildings.展开更多
It is generally recognized that the optimal distribution of catalyst activity in a spherical catalyst is a Dirac d-function. However, catalyst with other alternative distribution may accomplish the same reaction task ...It is generally recognized that the optimal distribution of catalyst activity in a spherical catalyst is a Dirac d-function. However, catalyst with other alternative distribution may accomplish the same reaction task without necessarily concentrating the catalyst activity in an inside thin layer. Moreover, the alternative with activity on catalyst surface may offer higher reaction rate and better utilization of reaction heat (higher exergy output). Simple cases of first-order exothermal reactions, in particular when the catalyst is limited by the maximum working temperature, are presented to demonstrate the above advantages and to show the importance of studying the optimal activity distribution with the consideration on exergy maximization and entropy production minimization.展开更多
This paper describes and explores a maximum-entropy approach to continuous minimax problem, which is applicable in many fields, such as transportation planning and game theory. It illustrates that the maximum entropy ...This paper describes and explores a maximum-entropy approach to continuous minimax problem, which is applicable in many fields, such as transportation planning and game theory. It illustrates that the maximum entropy approcach has easy framework and proves that every accumulation of {x_k} generated by maximum-entropy programming is -optimal solution of initial continuous minimax problem. The paper also explains BFGS or TR method for it. Two numerical exam.ples for continuous minimax problem are展开更多
This paper presents an algorithm that combines the chaos optimization algorithm with the maximum entropy ( COA-ME) by using entropy model based on chaos algorithm,in which the maximum entropy is used as the second met...This paper presents an algorithm that combines the chaos optimization algorithm with the maximum entropy ( COA-ME) by using entropy model based on chaos algorithm,in which the maximum entropy is used as the second method of searching the excellent solution. The search direction is improved by chaos optimization algorithm and realizes the selective acceptance of wrong solution. The experimental result shows that the presented algorithm can be used in the partitioning of hardware/software of reconfigurable system. It effectively reduces the local extremum problem,and search speed as well as performance of partitioning is improved.展开更多
The segmentation effect of Tsallis entropy method is superior to that of Shannon entropy method, and the computation speed of two-dimensional Shannon cross entropy method can be further improved by optimization. The e...The segmentation effect of Tsallis entropy method is superior to that of Shannon entropy method, and the computation speed of two-dimensional Shannon cross entropy method can be further improved by optimization. The existing two-dimensional Tsallis cross entropy method is not the strict two-dimensional extension. Thus two new methods of image thresholding using two-dimensional Tsallis cross entropy based on either Chaotic Particle Swarm Optimization (CPSO) or decomposition are proposed. The former uses CPSO to find the optimal threshold. The recursive algorithm is adopted to avoid the repetitive computation of fitness function in iterative procedure. The computing speed is improved greatly. The latter converts the two-dimensional computation into two one-dimensional spaces, which makes the computational complexity further reduced from O(L2) to O(L). The experimental results show that, compared with the proposed recently two-dimensional Shannon or Tsallis cross entropy method, the two new methods can achieve superior segmentation results and reduce running time greatly.展开更多
Water-based aerosol is widely used as an effective strategy in electro-optical countermeasure on the battlefield used to the preponderance of high efficiency,low cost and eco-friendly.Unfortunately,the stability of th...Water-based aerosol is widely used as an effective strategy in electro-optical countermeasure on the battlefield used to the preponderance of high efficiency,low cost and eco-friendly.Unfortunately,the stability of the water-based aerosol is always unsatisfactory due to the rapid evaporation and sedimentation of the aerosol droplets.Great efforts have been devoted to improve the stability of water-based aerosol by using additives with different composition and proportion.However,the lack of the criterion and principle for screening the effective additives results in excessive experimental time consumption and cost.And the stabilization time of the aerosol is still only 30 min,which could not meet the requirements of the perdurable interference.Herein,to improve the stability of water-based aerosol and optimize the complex formulation efficiently,a theoretical calculation method based on thermodynamic entropy theory is proposed.All the factors that influence the shielding effect,including polyol,stabilizer,propellant,water and cosolvent,are considered within calculation.An ultra-stable water-based aerosol with long duration over 120 min is obtained with the optimal fogging agent composition,providing enough time for fighting the electro-optic weapon.Theoretical design guideline for choosing the additives with high phase transition temperature and low phase transition enthalpy is also proposed,which greatly improves the total entropy change and reduce the absolute entropy change of the aerosol cooling process,and gives rise to an enhanced stability of the water-based aerosol.The theoretical calculation methodology contributes to an abstemious time and space for sieving the water-based aerosol with desirable performance and stability,and provides the powerful guarantee to the homeland security.展开更多
In this paper, survival data analysis is realized by applying Generalized Entropy Optimization Methods (GEOM). It is known that all statistical distributions can be obtained as distribution by choosing corresponding m...In this paper, survival data analysis is realized by applying Generalized Entropy Optimization Methods (GEOM). It is known that all statistical distributions can be obtained as distribution by choosing corresponding moment functions. However, Generalized Entropy Optimization Distributions (GEOD) in the form of distributions which are obtained on basis of Shannon measure and supplementary optimization with respect to characterizing moment functions, more exactly represent the given statistical data. For this reason, survival data analysis by GEOD acquires a new significance. In this research, the data of the life table for engine failure data (1980) is examined. The performances of GEOD are established by Chi-Square criteria, Root Mean Square Error (RMSE) criteria and Shannon entropy measure, Kullback-Leibler measure. Comparison of GEOD with each other in the different senses shows that along of these distributions (MinMaxEnt)4 is better in the senses of Shannon measure and of Kullback-Leibler measure. It is showed that, (MinMaxEnt)3 ((MaxMaxEnt)4) is more suitable for statistical data among (MinMaxEnt)m,m=1,2,3,4(MaxMaxEnt)m,m=1,2,3,4. Moreover, (MinMaxEnt)3 is better for statistical data than (MaxMaxEnt)4 in the sense of RMSE criteria. According to obtained distribution (MinMaxEnt)3 (MaxMaxEnt)4 estimator of Probability Density Function?f^?(t), Cumulative Distribution Functio?F^ (t) , Survival Function Ŝ(t) and Hazard Rate ĥ(t) are evaluated and graphically illustrated. The results are acquired by using statistical software MATLAB.展开更多
The purpose of this research is to obtain the optimum cutting parameters to achieve the dimensional accuracy of Nimonic alloy miniature gear manufactured using Wire EDM.The cutting parameters investigated in this stud...The purpose of this research is to obtain the optimum cutting parameters to achieve the dimensional accuracy of Nimonic alloy miniature gear manufactured using Wire EDM.The cutting parameters investigated in this study are current,pulse on time(PON),pulse off time(POFF),wire tension(WT)and dielectric fluids.Ethylene glycol,nanopowder of alumina and oxygen are mixed to demineralized water to prepare novel dielectric fluids.Deviation in inner diameter,deviation in outer diameter,deviation in land and deviation in tooth width are considered to check the dimensional accuracy.Taguchi L_(16) is employed for experimental design and multiple response optimization is performed using Entropy TOPSIS and Pareto ANOVA.Results indicate that pulse on time is the most notable parameter for good dimensional accuracy followed by dielectric fluid,current,pulse off time and wire tension.Ethylene glycol mixed demineralized water is preferred for low dimensional deviation.The optimum WEDM parameters are pulse on time at 20μs,Ethylene glycol mixed demineralized water dielectric fluid,current at 3 A,pulse off time at 4μs,and wire tension at 18 N.展开更多
Fusing medical images is a topic of interest in processing medical images.This is achieved to through fusing information from multimodality images for the purpose of increasing the clinical diagnosis accuracy.This fus...Fusing medical images is a topic of interest in processing medical images.This is achieved to through fusing information from multimodality images for the purpose of increasing the clinical diagnosis accuracy.This fusion aims to improve the image quality and preserve the specific features.The methods of medical image fusion generally use knowledge in many differentfields such as clinical medicine,computer vision,digital imaging,machine learning,pattern recognition to fuse different medical images.There are two main approaches in fusing image,including spatial domain approach and transform domain approachs.This paper proposes a new algorithm to fusion multimodal images.This algorithm is based on Entropy optimization and the Sobel operator.Wavelet transform is used to split the input images into components over the low and high frequency domains.Then,two fusion rules are used for obtaining the fusing images.Thefirst rule,based on the Sobel operator,is used for high frequency components.The second rule,based on Entropy optimization by using Particle Swarm Optimization(PSO)algorithm,is used for low frequency components.Proposed algorithm is implemented on the images related to central nervous system diseases.The experimental results of the paper show that the proposed algorithm is better than some recent methods in term of brightness level,the contrast,the entropy,the gradient and visual informationfidelity for fusion(VIFF),Feature Mutual Information(FMI)indices.展开更多
With the rapid increase of new cases with an increased mortality rate,cancer is considered the second and most deadly disease globally.Breast cancer is the most widely affected cancer worldwide,with an increased death...With the rapid increase of new cases with an increased mortality rate,cancer is considered the second and most deadly disease globally.Breast cancer is the most widely affected cancer worldwide,with an increased death rate percentage.Due to radiologists’processing of mammogram images,many computer-aided diagnoses have been developed to detect breast cancer.Early detection of breast cancer will reduce the death rate worldwide.The early diagnosis of breast cancer using the developed computer-aided diagnosis(CAD)systems still needed to be enhanced by incorporating innovative deep learning technologies to improve the accuracy and sensitivity of the detection system with a reduced false positive rate.This paper proposed an efficient and optimized deep learning-based feature selection approach with this consideration.This model selects the relevant features from the mammogram images that can improve the accuracy of malignant detection and reduce the false alarm rate.Transfer learning is used in the extraction of features initially.Na ext,a convolution neural network,is used to extract the features.The two feature vectors are fused and optimized with enhanced Butterfly Optimization with Gaussian function(TL-CNN-EBOG)to select the final most relevant features.The optimized features are applied to the classifier called Deep belief network(DBN)to classify the benign and malignant images.The feature extraction and classification process used two datasets,breast,and MIAS.Compared to the existing methods,the optimized deep learning-based model secured 98.6%of improved accuracy on the breast dataset and 98.85%of improved accuracy on the MIAS dataset.展开更多
基金Project supported by the National Natural Science Foundation of China (Grant No. 51106082)the Tsinghua University Initiative Scientific Research Program, China
文摘Entropy generation is often used as a figure of merit in thermodynamic cycle optimizations. In this paper, it is shown that the applicability of the minimum entropy generation method to optimizing output power is conditional. The minimum entropy generation rate and the minimum entropy generation number do not correspond to the maximum output power when the total heat into the system of interest is not prescribed. For the cycles whose working medium is heated or cooled by streams with prescribed inlet temperatures and prescribed heat capacity flow rates, it is theoretically proved that both the minimum entropy generation rate and the minimum entropy generation number correspond to the maximum output power when the virtual entropy generation induced by dumping the used streams into the environment is considered. However, the minimum principle of entropy generation is not tenable in the case that the virtual entropy generation is not included, because the total heat into the system of interest is not fixed. An irreversible Carnot cycle and an irreversible Brayton cycle are analysed. The minimum entropy generation rate and the minimum entropy generation number do not correspond to the maximum output power if the heat into the system of interest is not prescribed.
基金supported by the Tsinghua University Initiative Scientific Research Programthe National Natural Science Foundation of China(GrantNo.51136001)
文摘In thermal radiation, taking heat flow as an extensive quantity and defining the potential as temperature T or the black body emissive power U will lead to two different definitions of radiation entransy flow and the corresponding principles for thermal radiation optimization. The two definitions of radiation entransy flow and the corresponding optimization prin ciples are compared in this paper. When the total heat flow is given, the optimization objectives of the extremum entransy dissipation principles （EEDPs） developed based on potentials T and U correspond to the minimum equivalent temperature difference and the minimum equivalent blackbody emissive power difference respectively. The physical meaning of the definition based on potential U is clearer than that based on potential T, but the latter one can be used for the coupled heat transfer optimization problem while the former one cannot. The extremum entropy generation principle （EEGP） for thermal radiation is also derived, which includes the minimum entropy generation principle for thermal radiation. When the radiation heat flow is prescribed, the EEGP reveals that the minimum entropy generation leads to the minimum equivalent thermodynamic potential difference, which is not the expected objective in heat transfer. Therefore, the minimum entropy generation is not always appropriate for thermal radiation optimization. Finally, three thermal radiation optimization examples are discussed, and the results show that the difference in optimization objective between the EEDPs and the EEGP leads to the difference between the optimization results. The EEDP based on potential T is more useful in practical application since its optimization objective is usually consistent with the expected one.
文摘Selecting optimization ship form scheme is an important content in the process of concept design of ship. Multi-objective fuzzy decision-making model for ship form demonstration is set up according to the fuzzy pattern-recognition theory. Weight coefficients of each target of ship form scheme are determined by information entropy and individual subjective partiality. This model is used to select the optimal ship form scheme, the example shows that the model is exact and the resuh is credible. It can provide a reference for choosing the optimization scheme of ship form.
基金Project supported by the National Natural Science Foundation of China (Grant No. 19874020)the Natural Science Foundation of Hunan Province of China (Grant Nos. 09JJ3012 and 10JJ9002)the Research Foundation of Education Bureau of Hunan Province of China (Grant No. 10A032)
文摘From the viewpoint of quantum information, this paper studies preparation and control of atomic optimal entropy squeezing states （AOESS） for a moving two-level atom under control of the two-mode squeezing vacuum fields. Necessary conditions of preparation of the AOESS are analysed, and numerical verification of the AOESS is finished. It shows that the AOESS can be prepared by controlling the time of the atom interaction with the field, cutting the entanglement between the atom and field, and adjusting squeezing factor of the field. An atomic optimal entropy squeezing sudden generation in different components can alternately be realized by controlling the field-mode structure parameter.
基金supported by the National Natural Science Foundation of China(91834303 and 22108261)the Open Foundation of State Key Laboratory of Chemical Engineering(SKL-ChE-19B02)+1 种基金Fundamental Research Program of Shanxi Province(20210302124618)Scientific Technological Innovation Programs of Higher Education Institution in Shanxi(2020L0284).
文摘In this study,an optimization method is proposed to enhance the gas–liquid mass transfer in bubble column reactor based on the entropy generation extremum principle.The mass transfer–induced entropy generation can be maximized with the increase of mass transfer rate,based on which the velocity field can be optimized.The oxygen gas–liquid mass transfer is the major rate–limiting step of the toluene emissions biodegradation process in bubble column reactor,so the entropy generation due to oxygen mass transfer is used as the objective function,and the conservation equations of the gas–liquid flow and species concentration are taken as constraints.This optimization problem is solved by the calculus of variations,the optimal liquid flow pattern is obtained and the relationship of the maximum mass transfer enhancement on viscous dissipation is revealed,which can be used to improve the design of internal structure of the bubble column reactor.
基金supported by the National Natural Science Foundation of China(70771041)Chinese Astronautics SupportTechnology Foundation and the Excellent Youth Project of Hubei Provincial Department of Education(Q20082705)
文摘To study the problems of multi-attribute decision making in which the attribute values are given in the form of linguistic fuzzy numbers and the information of attribute weights are incomplete, a new multi-attribute decision making model is presented based on the optimal membership and the relative entropy. Firstly, the definitions of the optimal membership and the relative entropy are given. Secondly, for all alternatives, a set of preference weight vectors are obtained by solving a set of linear programming models whose goals axe all to maximize the optimal membership. Thirdly, a relative entropy model is established to aggregate the preference weight vectors, thus an optimal weight vector is determined. Based on this optimal weight vector, the algorithm of deviation degree minimization is proposed to rank all the alternatives. Finally, a decision making example is given to demonstrate the feasibility and rationality of this new model.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11374096 and 11405052)
文摘Considering two atomic qubits initially in Bell states, we send one qubit into a vacuum cavity with two-photon resonance and leave the other one outside. Using quantum information entropy squeezing theory, the time evolutions of the entropy squeezing factor of the atomic qubit inside the cavity are discussed for two cases, i.e., before and after rotation and measurement of the atomic qubit outside the cavity. It is shown that the atomic qubit inside the cavity has no entropy squeezing phenomenon and is always in a decoherent state before the operating atomic qubit outside the cavity. However,the periodical entropy squeezing phenomenon emerges and the optimal entropy squeezing state can be prepared for the atomic qubit inside the cavity by adjusting the rotation angle, choosing the interaction time between the atomic qubit and the cavity, controlling the probability amplitudes of subsystem states. Its physical essence is cutting the entanglement between the atomic qubit and its environment, causing the atomic qubit inside the cavity to change from the initial decoherent state into maximum coherent superposition state, which is a possible way of recovering the coherence of a single atomic qubit in the noise environment.
基金Supported by the CRSRI Open Research Program(CKWV2013225/KY)the Priority Academic Program Development of Jiangsu Higher Education Institution+2 种基金the Open Project Foundation of Key Laboratory of the Yellow River Sediment of Ministry of Water Resource(2014006)the State Key Lab of Urban Water Resource and Environment(HIT)(ES201409)the Open Project Program of State Key Laboratory of Food Science and Technology,Jiangnan University(SKLF-KF-201310)
文摘Since the logarithmic form of Shannon entropy has the drawback of undefined value at zero points,and most existing threshold selection methods only depend on the probability information,ignoring the within-class uniformity of gray level,a method of reciprocal gray entropy threshold selection is proposed based on two-dimensional(2-D)histogram region oblique division and artificial bee colony(ABC)optimization.Firstly,the definition of reciprocal gray entropy is introduced.Then on the basis of one-dimensional(1-D)method,2-D threshold selection criterion function based on reciprocal gray entropy with histogram oblique division is derived.To accelerate the progress of searching the optimal threshold,the recently proposed ABC optimization algorithm is adopted.The proposed method not only avoids the undefined value points in Shannon entropy,but also achieves high accuracy and anti-noise performance due to reasonable 2-D histogram region division and the consideration of within-class uniformity of gray level.A large number of experimental results show that,compared with the maximum Shannon entropy method with 2-D histogram oblique division and the reciprocal entropy method with 2-D histogram oblique division based on niche chaotic mutation particle swarm optimization(NCPSO),the proposed method can achieve better segmentation results and can satisfy the requirement of real-time processing.
基金supported by the National Natural Science Foundation of China (Nos. 51279186, 51479183, 51509227)the Shandong Province Natural Science Foundation, China (No. ZR2014EEQ030)the Fundamental Research Funds for the Central Universities (No. 201413003)
文摘The maximum entropy distribution, which consists of various recognized theoretical distributions, is a better curve to estimate the design thickness of sea ice. Method of moment and empirical curve fitting method are common-used parameter estimation methods for maximum entropy distribution. In this study, we propose to use the particle swarm optimization method as a new parameter estimation method for the maximum entropy distribution, which has the advantage to avoid deviation introduced by simplifications made in other methods. We conducted a case study to fit the hindcasted thickness of the sea ice in the Liaodong Bay of Bohai Sea using these three parameter-estimation methods for the maximum entropy distribution. All methods implemented in this study pass the K-S tests at 0.05 significant level. In terms of the average sum of deviation squares, the empirical curve fitting method provides the best fit for the original data, while the method of moment provides the worst. Among all three methods, the particle swarm optimization method predicts the largest thickness of the sea ice for a same return period. As a result, we recommend using the particle swarm optimization method for the maximum entropy distribution for offshore structures mainly influenced by the sea ice in winter, but using the empirical curve fitting method to reduce the cost in the design of temporary and economic buildings.
基金Supported by the National Natural Science Foundation of China (No. 20236050)
文摘It is generally recognized that the optimal distribution of catalyst activity in a spherical catalyst is a Dirac d-function. However, catalyst with other alternative distribution may accomplish the same reaction task without necessarily concentrating the catalyst activity in an inside thin layer. Moreover, the alternative with activity on catalyst surface may offer higher reaction rate and better utilization of reaction heat (higher exergy output). Simple cases of first-order exothermal reactions, in particular when the catalyst is limited by the maximum working temperature, are presented to demonstrate the above advantages and to show the importance of studying the optimal activity distribution with the consideration on exergy maximization and entropy production minimization.
基金The Project was supported by National Natural Science Foundation of china.
文摘This paper describes and explores a maximum-entropy approach to continuous minimax problem, which is applicable in many fields, such as transportation planning and game theory. It illustrates that the maximum entropy approcach has easy framework and proves that every accumulation of {x_k} generated by maximum-entropy programming is -optimal solution of initial continuous minimax problem. The paper also explains BFGS or TR method for it. Two numerical exam.ples for continuous minimax problem are
基金Sponsored by the Natural Science Foundation of Heilongjiang Province( Grant No B2007-07)Industrial Research Projects in Qiqihaer( Grant No GYGG-09009)
文摘This paper presents an algorithm that combines the chaos optimization algorithm with the maximum entropy ( COA-ME) by using entropy model based on chaos algorithm,in which the maximum entropy is used as the second method of searching the excellent solution. The search direction is improved by chaos optimization algorithm and realizes the selective acceptance of wrong solution. The experimental result shows that the presented algorithm can be used in the partitioning of hardware/software of reconfigurable system. It effectively reduces the local extremum problem,and search speed as well as performance of partitioning is improved.
基金supported by National Natural Science Foundation of China under Grant No.60872065Open Foundation of State Key Laboratory for Novel Software Technology at Nanjing University under Grant No.KFKT2010B17
文摘The segmentation effect of Tsallis entropy method is superior to that of Shannon entropy method, and the computation speed of two-dimensional Shannon cross entropy method can be further improved by optimization. The existing two-dimensional Tsallis cross entropy method is not the strict two-dimensional extension. Thus two new methods of image thresholding using two-dimensional Tsallis cross entropy based on either Chaotic Particle Swarm Optimization (CPSO) or decomposition are proposed. The former uses CPSO to find the optimal threshold. The recursive algorithm is adopted to avoid the repetitive computation of fitness function in iterative procedure. The computing speed is improved greatly. The latter converts the two-dimensional computation into two one-dimensional spaces, which makes the computational complexity further reduced from O(L2) to O(L). The experimental results show that, compared with the proposed recently two-dimensional Shannon or Tsallis cross entropy method, the two new methods can achieve superior segmentation results and reduce running time greatly.
基金supported by the Preparation and Characterization of Fogging Agents,Cooperative Project of China(Grant No.1900030040)Preparation and Test of Fogging Agents,Cooperative Project of China(Grant No.2200030085)。
文摘Water-based aerosol is widely used as an effective strategy in electro-optical countermeasure on the battlefield used to the preponderance of high efficiency,low cost and eco-friendly.Unfortunately,the stability of the water-based aerosol is always unsatisfactory due to the rapid evaporation and sedimentation of the aerosol droplets.Great efforts have been devoted to improve the stability of water-based aerosol by using additives with different composition and proportion.However,the lack of the criterion and principle for screening the effective additives results in excessive experimental time consumption and cost.And the stabilization time of the aerosol is still only 30 min,which could not meet the requirements of the perdurable interference.Herein,to improve the stability of water-based aerosol and optimize the complex formulation efficiently,a theoretical calculation method based on thermodynamic entropy theory is proposed.All the factors that influence the shielding effect,including polyol,stabilizer,propellant,water and cosolvent,are considered within calculation.An ultra-stable water-based aerosol with long duration over 120 min is obtained with the optimal fogging agent composition,providing enough time for fighting the electro-optic weapon.Theoretical design guideline for choosing the additives with high phase transition temperature and low phase transition enthalpy is also proposed,which greatly improves the total entropy change and reduce the absolute entropy change of the aerosol cooling process,and gives rise to an enhanced stability of the water-based aerosol.The theoretical calculation methodology contributes to an abstemious time and space for sieving the water-based aerosol with desirable performance and stability,and provides the powerful guarantee to the homeland security.
文摘In this paper, survival data analysis is realized by applying Generalized Entropy Optimization Methods (GEOM). It is known that all statistical distributions can be obtained as distribution by choosing corresponding moment functions. However, Generalized Entropy Optimization Distributions (GEOD) in the form of distributions which are obtained on basis of Shannon measure and supplementary optimization with respect to characterizing moment functions, more exactly represent the given statistical data. For this reason, survival data analysis by GEOD acquires a new significance. In this research, the data of the life table for engine failure data (1980) is examined. The performances of GEOD are established by Chi-Square criteria, Root Mean Square Error (RMSE) criteria and Shannon entropy measure, Kullback-Leibler measure. Comparison of GEOD with each other in the different senses shows that along of these distributions (MinMaxEnt)4 is better in the senses of Shannon measure and of Kullback-Leibler measure. It is showed that, (MinMaxEnt)3 ((MaxMaxEnt)4) is more suitable for statistical data among (MinMaxEnt)m,m=1,2,3,4(MaxMaxEnt)m,m=1,2,3,4. Moreover, (MinMaxEnt)3 is better for statistical data than (MaxMaxEnt)4 in the sense of RMSE criteria. According to obtained distribution (MinMaxEnt)3 (MaxMaxEnt)4 estimator of Probability Density Function?f^?(t), Cumulative Distribution Functio?F^ (t) , Survival Function Ŝ(t) and Hazard Rate ĥ(t) are evaluated and graphically illustrated. The results are acquired by using statistical software MATLAB.
基金the Deanship of Scientific Research at King Khalid University,for funding this work through research groups program under Grant No.(R.G.P.1/197/41).
文摘The purpose of this research is to obtain the optimum cutting parameters to achieve the dimensional accuracy of Nimonic alloy miniature gear manufactured using Wire EDM.The cutting parameters investigated in this study are current,pulse on time(PON),pulse off time(POFF),wire tension(WT)and dielectric fluids.Ethylene glycol,nanopowder of alumina and oxygen are mixed to demineralized water to prepare novel dielectric fluids.Deviation in inner diameter,deviation in outer diameter,deviation in land and deviation in tooth width are considered to check the dimensional accuracy.Taguchi L_(16) is employed for experimental design and multiple response optimization is performed using Entropy TOPSIS and Pareto ANOVA.Results indicate that pulse on time is the most notable parameter for good dimensional accuracy followed by dielectric fluid,current,pulse off time and wire tension.Ethylene glycol mixed demineralized water is preferred for low dimensional deviation.The optimum WEDM parameters are pulse on time at 20μs,Ethylene glycol mixed demineralized water dielectric fluid,current at 3 A,pulse off time at 4μs,and wire tension at 18 N.
文摘Fusing medical images is a topic of interest in processing medical images.This is achieved to through fusing information from multimodality images for the purpose of increasing the clinical diagnosis accuracy.This fusion aims to improve the image quality and preserve the specific features.The methods of medical image fusion generally use knowledge in many differentfields such as clinical medicine,computer vision,digital imaging,machine learning,pattern recognition to fuse different medical images.There are two main approaches in fusing image,including spatial domain approach and transform domain approachs.This paper proposes a new algorithm to fusion multimodal images.This algorithm is based on Entropy optimization and the Sobel operator.Wavelet transform is used to split the input images into components over the low and high frequency domains.Then,two fusion rules are used for obtaining the fusing images.Thefirst rule,based on the Sobel operator,is used for high frequency components.The second rule,based on Entropy optimization by using Particle Swarm Optimization(PSO)algorithm,is used for low frequency components.Proposed algorithm is implemented on the images related to central nervous system diseases.The experimental results of the paper show that the proposed algorithm is better than some recent methods in term of brightness level,the contrast,the entropy,the gradient and visual informationfidelity for fusion(VIFF),Feature Mutual Information(FMI)indices.
基金Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2022R151)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.The authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code:(22UQU4310373DSR12).
文摘With the rapid increase of new cases with an increased mortality rate,cancer is considered the second and most deadly disease globally.Breast cancer is the most widely affected cancer worldwide,with an increased death rate percentage.Due to radiologists’processing of mammogram images,many computer-aided diagnoses have been developed to detect breast cancer.Early detection of breast cancer will reduce the death rate worldwide.The early diagnosis of breast cancer using the developed computer-aided diagnosis(CAD)systems still needed to be enhanced by incorporating innovative deep learning technologies to improve the accuracy and sensitivity of the detection system with a reduced false positive rate.This paper proposed an efficient and optimized deep learning-based feature selection approach with this consideration.This model selects the relevant features from the mammogram images that can improve the accuracy of malignant detection and reduce the false alarm rate.Transfer learning is used in the extraction of features initially.Na ext,a convolution neural network,is used to extract the features.The two feature vectors are fused and optimized with enhanced Butterfly Optimization with Gaussian function(TL-CNN-EBOG)to select the final most relevant features.The optimized features are applied to the classifier called Deep belief network(DBN)to classify the benign and malignant images.The feature extraction and classification process used two datasets,breast,and MIAS.Compared to the existing methods,the optimized deep learning-based model secured 98.6%of improved accuracy on the breast dataset and 98.85%of improved accuracy on the MIAS dataset.
基金supported by the National Natural Science Foundation of China (No. 51178141)National Major Science and Technology Program for Water Pollution Control and Treatment (2012ZX07408-002-004-002)
