BACKGROUND An acute myocardial infarction(AMI)is often treated with direct coronary intervention and requires home-based rehabilitation.Caregivers of patients with AMI need adequate social support to maintain high-qua...BACKGROUND An acute myocardial infarction(AMI)is often treated with direct coronary intervention and requires home-based rehabilitation.Caregivers of patients with AMI need adequate social support to maintain high-quality care;however,their social support function is low,and relevant indicators for intervention must be identified.AIM To analyze the correlation between social support for primary caregivers,their anxiety,and depression,when caring for patients with AMI after interventional therapy.METHODS Using convenience sampling,we selected 300 primary caregivers of patients with AMI who had undergone interventional therapy.The Social Support Rating Scale(SSRS),Self-Rating Anxiety Scale(SAS),and Self-Rating Depression Scale(SDS)were used to assess the primary caregivers.A Pearson’s correlation analysis was used to analyze the correlations between the SSRS,SAS,and SDS,and a multiple logistic regression analysis was used to analyze the factors influencing the low social support function of primary caregivers.The receiver operating characteristic curve and area under the curve(AUC)were used to evaluate the predictive ability of the SAS and SDS for low social support function in primary caregivers.RESULTS Considering the norm among Chinese people,AMI caregivers’objective support,subjective support,support utilization,and SSRS scores were lower,while their SAS and SDS scores were higher.The SSRS scores of female caregivers were higher than those of the male caregivers(t=2.123,P=0.035).The Pearson correlation analysis showed that objective support,subjective support,support utilization,and SSRS total scores were significantly correlated with both SAS(r=-0.414,-0.460,-0.416,-0.535)and SDS scores(r=-0.463,-0.379,-0.349,-0.472).Among the 300 AMI caregivers,56 cases(18.67%)had a low level of support function(SSRS≤22 points).Logistic regression model analysis showed that SAS and SDS were independent risk factors for low social support function of AMI caregivers,regardless of adjustment for other variables(P<0.05).SAS and SDS predicted that the AUC of AMI caregivers with low support function was 0.84,sensitivity was 67.9 and 71.4,and specificity was 84.0 and 70.9,respectively.CONCLUSION The social support function of the primary caregiver of patients with AMI after interventional therapy was lower and negatively correlated with anxiety and depression in the primary caregiver.展开更多
The purpose of this paper is to verify the Smulyan lemma for the support function, and also the Gateaux differentiability of the support function is studied on its domain. Moreover, we provide a characterization of Fr...The purpose of this paper is to verify the Smulyan lemma for the support function, and also the Gateaux differentiability of the support function is studied on its domain. Moreover, we provide a characterization of Frechet differentiability of the support function on the extremal points.展开更多
In this paper we show that the unit ball of an infinite dimensional commutative C-algebra lacks strongly exposed points, so they have no predual. Also in the second part, we use the concept of strongly exposed points ...In this paper we show that the unit ball of an infinite dimensional commutative C-algebra lacks strongly exposed points, so they have no predual. Also in the second part, we use the concept of strongly exposed points in the Frechet differentiability of support convex functions.展开更多
Mond-Weir type duality for control problem with support functions is investigated under generalized convexity conditions. Special cases are derived. A relationship between our results and those of nonlinear programmin...Mond-Weir type duality for control problem with support functions is investigated under generalized convexity conditions. Special cases are derived. A relationship between our results and those of nonlinear programming problem containing support functions is outlined.展开更多
A second-order Mond-Weir type dual problem is formulated for a class of continuous programming problems in which both objective and constraint functions contain support functions;hence it is nondifferentiable. Under s...A second-order Mond-Weir type dual problem is formulated for a class of continuous programming problems in which both objective and constraint functions contain support functions;hence it is nondifferentiable. Under second-order strict pseudoinvexity, second-order pseudoinvexity and second-order quasi-invexity assumptions on functionals, weak, strong, strict converse and converse duality theorems are established for this pair of dual continuous programming problems. Special cases are deduced and a pair of dual continuous problems with natural boundary values is constructed. A close relationship between the duality results of our problems and those of the corresponding (static) nonlinear programming problem with support functions is briefly outlined.展开更多
A second-order dual problem is formulated for a class of continuous programming problem in which both objective and constrained functions contain support functions, hence it is nondifferentiable. Under second-order in...A second-order dual problem is formulated for a class of continuous programming problem in which both objective and constrained functions contain support functions, hence it is nondifferentiable. Under second-order invexity and second-order pseudoinvexity, weak, strong and converse duality theorems are established for this pair of dual problems. Special cases are deduced and a pair of dual continuous problems with natural boundary values is constructed. A close relationship between duality results of our problems and those of the corresponding (static) nonlinear programming problem with support functions is briefly outlined.展开更多
In this article, for a differentiable function , we introduce the definition of the higher-order -invexity. Three duality models for a multiobjective fractional programming problem involving nondifferentiability in te...In this article, for a differentiable function , we introduce the definition of the higher-order -invexity. Three duality models for a multiobjective fractional programming problem involving nondifferentiability in terms of support functions have been formulated and usual duality relations have been established under the higher-order -invex assumptions.展开更多
A control problem containing support functions in the integrand of the objective of the functional as well as in the inequality constraint function is considered. For this problem, Fritz John and Karush-Kuhn-Tucker ty...A control problem containing support functions in the integrand of the objective of the functional as well as in the inequality constraint function is considered. For this problem, Fritz John and Karush-Kuhn-Tucker type necessary optimality conditions are derived. Using Karush-Kuhn-Tucker type optimality conditions, Wolfe type dual is formulated and usual duality theorems are established under generalized convexity conditions. Special cases are generated. It is also shown that our duality results have linkage with those of nonlinear programming problems involving support functions.展开更多
This paper introduced a kind of functions associated with spherically convex sets and discussed their basic properties.Finally,it proved the spherical convexity/concavity of these functions in lower dimensional cases,...This paper introduced a kind of functions associated with spherically convex sets and discussed their basic properties.Finally,it proved the spherical convexity/concavity of these functions in lower dimensional cases,which provides useful information for the essential characteristics of these functions determining spherically convex sets.The results obtained here are helpful in setting up a systematic spherical convexity theory.展开更多
Based on KKT complementary condition in optimization theory, an unconstrained non-differential optimization model for support vector machine is proposed. An adjustable entropy function method is given to deal with the...Based on KKT complementary condition in optimization theory, an unconstrained non-differential optimization model for support vector machine is proposed. An adjustable entropy function method is given to deal with the proposed optimization problem and the Newton algorithm is used to figure out the optimal solution. The proposed method can find an optimal solution with a relatively small parameter p, which avoids the numerical overflow in the traditional entropy function methods. It is a new approach to solve support vector machine. The theoretical analysis and experimental results illustrate the feasibility and efficiency of the proposed algorithm.展开更多
The nature of farmer cooperative economy organization( known as FCEO) determines the fact that the economic effects of farmer cooperative economy organization are as important as its social effects. Many experts,howev...The nature of farmer cooperative economy organization( known as FCEO) determines the fact that the economic effects of farmer cooperative economy organization are as important as its social effects. Many experts,however,now would only focus on its economic function, and either neglect or weaken its social influence. Therefore,this paper introduces the theoretical foundation of the farmer cooperative economy organization,and studies the nature of cooperative economics. Based on those typical cases,the future of cooperative organization and four supporting elements were put forward in this paper.展开更多
Path loss prediction models are vital for accurate signal propagation in wireless channels. Empirical and deterministic models used in path loss predictions have not produced optimal results. In this paper, we introdu...Path loss prediction models are vital for accurate signal propagation in wireless channels. Empirical and deterministic models used in path loss predictions have not produced optimal results. In this paper, we introduced machine learning algorithms to path loss predictions because it offers a flexible network architecture and extensive data can be used. We introduced support vector regression (SVR) and radial basis function (RBF) models to path loss predictions in the investigated environments. The SVR model was able to process several input parameters without introducing complexity to the network architecture. The RBF on its part provides a good function approximation. Hyperparameter tuning of the machine learning models was carried out in order to achieve optimal results. The performances of the SVR and RBF models were compared and result validated using the root-mean squared error (RMSE). The two machine learning algorithms were also compared with the Cost-231, SUI, Egli, Freespace, Cost-231 W-I models. The analytical models overpredicted path loss. Overall, the machine learning models predicted path loss with greater accuracy than the empirical models. The SVR model performed best across all the indices with RMSE values of 1.378 dB, 1.4523 dB, 2.1568 dB in rural, suburban and urban settings respectively and should therefore be adopted for signal propagation in the investigated environments and beyond.展开更多
Objective: To explore nutritional support under the Neuman systems model in treating dysphagia in stroke patients. Methods: In this retrospective study, we enrolled 97 patients with dysphagia after stroke admitted to ...Objective: To explore nutritional support under the Neuman systems model in treating dysphagia in stroke patients. Methods: In this retrospective study, we enrolled 97 patients with dysphagia after stroke admitted to our hospital, and randomly divided them into the Neuman group (n = 51) given nursing intervention based on Neuman systems model and a control group (n = 46) given routine nursing intervention. Both groups received nutritional support for 3 months. Nutritional indexes (serum total protein, plasma albumin, serum albumin, hemoglobin and transferrin levels) and immune indexes (immunoglobulin (Ig) A, IgG, IgM and total lymphocyte count (TLC) in both groups were recorded and compared. Pulmonary function recovery, video fluoroscopic swallowing study score, water swallowing test score, complication rate, and health knowledge mastery level were also compared between the two groups. Results: After the intervention, the Neuman group showed less decrease in the nutritional and immune index scores (serum total protein, plasma albumin, hemoglobin, serum albumin;IgA, IgG, IgM, and TLC;all P Conclusion: For patients with stroke and dysphagia, comprehensive nursing intervention (e.g., nutritional support) under theNeuman systems model can promote the recovery of immune, swallowing, and pulmonary function, reduce complication incidence and facilitate comprehensive rehabilitation, ensuring adequate nutritional intake.展开更多
In this paper, we defined a new continuity of supporting function and studyed a new convexity, smoothness of Banach Space and from this we studyed the relations among such convexity, smoothness and differentiability o...In this paper, we defined a new continuity of supporting function and studyed a new convexity, smoothness of Banach Space and from this we studyed the relations among such convexity, smoothness and differentiability of the norm of Banach Space.展开更多
孪生支持向量机(twin support vector machine,TSVM)能有效地处理交叉或异或等类型的数据.然而,当处理集值数据时,TSVM通常利用集值对象的均值、中值等统计信息.不同于TSVM,提出能直接处理集值数据的孪生支持函数机(twin support functi...孪生支持向量机(twin support vector machine,TSVM)能有效地处理交叉或异或等类型的数据.然而,当处理集值数据时,TSVM通常利用集值对象的均值、中值等统计信息.不同于TSVM,提出能直接处理集值数据的孪生支持函数机(twin support function machine,TSFM).依据集值对象定义的支持函数,TSFM在巴拿赫空间取得非平行的超平面.为了抑制集值数据中的离群点,TSFM采用了弹球损失函数并引入了集值对象的权重.考虑到TSFM是无穷维空间的优化问题,测度采用狄拉克测度的线性组合的形式,这构建有限维空间的优化模型.为了有效地求解优化模型,利用采样策略将模型转化成二次规划(quadratic programming,QP)问题并推导出二次规划问题的对偶形式,这为判断哪些采样点是支持向量提供了理论基础.为了分类集值数据,定义集值对象到巴拿赫空间的超平面的距离并由此得出判别规则.也考虑支持函数的核化以便取得数据的非线性特征,这使得提出的模型可用于不定核函数.实验结果表明,TSFM能获取交叉类型的集值数据的内在结构,并且在离群点或集值对象包含少量高维事例的情况下取得了良好的分类性能.展开更多
Smooth support vector machine （SSVM） changs the normal support vector machine （SVM） into the unconstrained op- timization by using the smooth sigmoid function. The method can be solved under the Broyden-Fletcher-G...Smooth support vector machine （SSVM） changs the normal support vector machine （SVM） into the unconstrained op- timization by using the smooth sigmoid function. The method can be solved under the Broyden-Fletcher-Goldfarb-Shanno （BFGS） algorithm and the Newdon-Armijio （NA） algorithm easily, however the accuracy of sigmoid function is not as good as that of polyno- mial smooth function. Furthermore, the method cannot reduce the influence of outliers or noise in dataset. A fuzzy smooth support vector machine （FSSVM） with fuzzy membership and polynomial smooth functions is introduced into the SVM. The fuzzy member- ship considers the contribution rate of each sample to the optimal separating hyperplane and makes the optimization problem more accurate at the inflection point. Those changes play a positive role on trials. The results of the experiments show that those FSSVMs can obtain a better accuracy and consume the shorter time than SSVM and lagrange support vector machine （LSVM）.展开更多
基金The study procedures were approved by the Ethics Committee of the Affiliated Hospital of Jiangnan University(approval No.WXSY-YXLL-AF/SC-02/01.0).
文摘BACKGROUND An acute myocardial infarction(AMI)is often treated with direct coronary intervention and requires home-based rehabilitation.Caregivers of patients with AMI need adequate social support to maintain high-quality care;however,their social support function is low,and relevant indicators for intervention must be identified.AIM To analyze the correlation between social support for primary caregivers,their anxiety,and depression,when caring for patients with AMI after interventional therapy.METHODS Using convenience sampling,we selected 300 primary caregivers of patients with AMI who had undergone interventional therapy.The Social Support Rating Scale(SSRS),Self-Rating Anxiety Scale(SAS),and Self-Rating Depression Scale(SDS)were used to assess the primary caregivers.A Pearson’s correlation analysis was used to analyze the correlations between the SSRS,SAS,and SDS,and a multiple logistic regression analysis was used to analyze the factors influencing the low social support function of primary caregivers.The receiver operating characteristic curve and area under the curve(AUC)were used to evaluate the predictive ability of the SAS and SDS for low social support function in primary caregivers.RESULTS Considering the norm among Chinese people,AMI caregivers’objective support,subjective support,support utilization,and SSRS scores were lower,while their SAS and SDS scores were higher.The SSRS scores of female caregivers were higher than those of the male caregivers(t=2.123,P=0.035).The Pearson correlation analysis showed that objective support,subjective support,support utilization,and SSRS total scores were significantly correlated with both SAS(r=-0.414,-0.460,-0.416,-0.535)and SDS scores(r=-0.463,-0.379,-0.349,-0.472).Among the 300 AMI caregivers,56 cases(18.67%)had a low level of support function(SSRS≤22 points).Logistic regression model analysis showed that SAS and SDS were independent risk factors for low social support function of AMI caregivers,regardless of adjustment for other variables(P<0.05).SAS and SDS predicted that the AUC of AMI caregivers with low support function was 0.84,sensitivity was 67.9 and 71.4,and specificity was 84.0 and 70.9,respectively.CONCLUSION The social support function of the primary caregiver of patients with AMI after interventional therapy was lower and negatively correlated with anxiety and depression in the primary caregiver.
文摘The purpose of this paper is to verify the Smulyan lemma for the support function, and also the Gateaux differentiability of the support function is studied on its domain. Moreover, we provide a characterization of Frechet differentiability of the support function on the extremal points.
基金Supported by the Research Institute of Fundamental Sciences, Tabriz, Iran.
文摘In this paper we show that the unit ball of an infinite dimensional commutative C-algebra lacks strongly exposed points, so they have no predual. Also in the second part, we use the concept of strongly exposed points in the Frechet differentiability of support convex functions.
文摘Mond-Weir type duality for control problem with support functions is investigated under generalized convexity conditions. Special cases are derived. A relationship between our results and those of nonlinear programming problem containing support functions is outlined.
文摘A second-order Mond-Weir type dual problem is formulated for a class of continuous programming problems in which both objective and constraint functions contain support functions;hence it is nondifferentiable. Under second-order strict pseudoinvexity, second-order pseudoinvexity and second-order quasi-invexity assumptions on functionals, weak, strong, strict converse and converse duality theorems are established for this pair of dual continuous programming problems. Special cases are deduced and a pair of dual continuous problems with natural boundary values is constructed. A close relationship between the duality results of our problems and those of the corresponding (static) nonlinear programming problem with support functions is briefly outlined.
文摘A second-order dual problem is formulated for a class of continuous programming problem in which both objective and constrained functions contain support functions, hence it is nondifferentiable. Under second-order invexity and second-order pseudoinvexity, weak, strong and converse duality theorems are established for this pair of dual problems. Special cases are deduced and a pair of dual continuous problems with natural boundary values is constructed. A close relationship between duality results of our problems and those of the corresponding (static) nonlinear programming problem with support functions is briefly outlined.
文摘In this article, for a differentiable function , we introduce the definition of the higher-order -invexity. Three duality models for a multiobjective fractional programming problem involving nondifferentiability in terms of support functions have been formulated and usual duality relations have been established under the higher-order -invex assumptions.
文摘A control problem containing support functions in the integrand of the objective of the functional as well as in the inequality constraint function is considered. For this problem, Fritz John and Karush-Kuhn-Tucker type necessary optimality conditions are derived. Using Karush-Kuhn-Tucker type optimality conditions, Wolfe type dual is formulated and usual duality theorems are established under generalized convexity conditions. Special cases are generated. It is also shown that our duality results have linkage with those of nonlinear programming problems involving support functions.
文摘This paper introduced a kind of functions associated with spherically convex sets and discussed their basic properties.Finally,it proved the spherical convexity/concavity of these functions in lower dimensional cases,which provides useful information for the essential characteristics of these functions determining spherically convex sets.The results obtained here are helpful in setting up a systematic spherical convexity theory.
基金the National Natural Science Foundation of China (60574075)
文摘Based on KKT complementary condition in optimization theory, an unconstrained non-differential optimization model for support vector machine is proposed. An adjustable entropy function method is given to deal with the proposed optimization problem and the Newton algorithm is used to figure out the optimal solution. The proposed method can find an optimal solution with a relatively small parameter p, which avoids the numerical overflow in the traditional entropy function methods. It is a new approach to solve support vector machine. The theoretical analysis and experimental results illustrate the feasibility and efficiency of the proposed algorithm.
基金Supported by the Youth Program of Chongqing Social Science Plan(No.2012QNGL047)West Program of Humanistic and Social Science of Education Department(No.13XJC630006)+1 种基金Education and Teaching Program of Southwest University(No.2012JY037)Chongqing Science Committee Decision-making Subject(No.2013KXKT07)
文摘The nature of farmer cooperative economy organization( known as FCEO) determines the fact that the economic effects of farmer cooperative economy organization are as important as its social effects. Many experts,however,now would only focus on its economic function, and either neglect or weaken its social influence. Therefore,this paper introduces the theoretical foundation of the farmer cooperative economy organization,and studies the nature of cooperative economics. Based on those typical cases,the future of cooperative organization and four supporting elements were put forward in this paper.
文摘Path loss prediction models are vital for accurate signal propagation in wireless channels. Empirical and deterministic models used in path loss predictions have not produced optimal results. In this paper, we introduced machine learning algorithms to path loss predictions because it offers a flexible network architecture and extensive data can be used. We introduced support vector regression (SVR) and radial basis function (RBF) models to path loss predictions in the investigated environments. The SVR model was able to process several input parameters without introducing complexity to the network architecture. The RBF on its part provides a good function approximation. Hyperparameter tuning of the machine learning models was carried out in order to achieve optimal results. The performances of the SVR and RBF models were compared and result validated using the root-mean squared error (RMSE). The two machine learning algorithms were also compared with the Cost-231, SUI, Egli, Freespace, Cost-231 W-I models. The analytical models overpredicted path loss. Overall, the machine learning models predicted path loss with greater accuracy than the empirical models. The SVR model performed best across all the indices with RMSE values of 1.378 dB, 1.4523 dB, 2.1568 dB in rural, suburban and urban settings respectively and should therefore be adopted for signal propagation in the investigated environments and beyond.
文摘Objective: To explore nutritional support under the Neuman systems model in treating dysphagia in stroke patients. Methods: In this retrospective study, we enrolled 97 patients with dysphagia after stroke admitted to our hospital, and randomly divided them into the Neuman group (n = 51) given nursing intervention based on Neuman systems model and a control group (n = 46) given routine nursing intervention. Both groups received nutritional support for 3 months. Nutritional indexes (serum total protein, plasma albumin, serum albumin, hemoglobin and transferrin levels) and immune indexes (immunoglobulin (Ig) A, IgG, IgM and total lymphocyte count (TLC) in both groups were recorded and compared. Pulmonary function recovery, video fluoroscopic swallowing study score, water swallowing test score, complication rate, and health knowledge mastery level were also compared between the two groups. Results: After the intervention, the Neuman group showed less decrease in the nutritional and immune index scores (serum total protein, plasma albumin, hemoglobin, serum albumin;IgA, IgG, IgM, and TLC;all P Conclusion: For patients with stroke and dysphagia, comprehensive nursing intervention (e.g., nutritional support) under theNeuman systems model can promote the recovery of immune, swallowing, and pulmonary function, reduce complication incidence and facilitate comprehensive rehabilitation, ensuring adequate nutritional intake.
文摘In this paper, we defined a new continuity of supporting function and studyed a new convexity, smoothness of Banach Space and from this we studyed the relations among such convexity, smoothness and differentiability of the norm of Banach Space.
文摘孪生支持向量机(twin support vector machine,TSVM)能有效地处理交叉或异或等类型的数据.然而,当处理集值数据时,TSVM通常利用集值对象的均值、中值等统计信息.不同于TSVM,提出能直接处理集值数据的孪生支持函数机(twin support function machine,TSFM).依据集值对象定义的支持函数,TSFM在巴拿赫空间取得非平行的超平面.为了抑制集值数据中的离群点,TSFM采用了弹球损失函数并引入了集值对象的权重.考虑到TSFM是无穷维空间的优化问题,测度采用狄拉克测度的线性组合的形式,这构建有限维空间的优化模型.为了有效地求解优化模型,利用采样策略将模型转化成二次规划(quadratic programming,QP)问题并推导出二次规划问题的对偶形式,这为判断哪些采样点是支持向量提供了理论基础.为了分类集值数据,定义集值对象到巴拿赫空间的超平面的距离并由此得出判别规则.也考虑支持函数的核化以便取得数据的非线性特征,这使得提出的模型可用于不定核函数.实验结果表明,TSFM能获取交叉类型的集值数据的内在结构,并且在离群点或集值对象包含少量高维事例的情况下取得了良好的分类性能.
基金supported by the National Natural Science Foundation of China (60974082)
文摘Smooth support vector machine （SSVM） changs the normal support vector machine （SVM） into the unconstrained op- timization by using the smooth sigmoid function. The method can be solved under the Broyden-Fletcher-Goldfarb-Shanno （BFGS） algorithm and the Newdon-Armijio （NA） algorithm easily, however the accuracy of sigmoid function is not as good as that of polyno- mial smooth function. Furthermore, the method cannot reduce the influence of outliers or noise in dataset. A fuzzy smooth support vector machine （FSSVM） with fuzzy membership and polynomial smooth functions is introduced into the SVM. The fuzzy member- ship considers the contribution rate of each sample to the optimal separating hyperplane and makes the optimization problem more accurate at the inflection point. Those changes play a positive role on trials. The results of the experiments show that those FSSVMs can obtain a better accuracy and consume the shorter time than SSVM and lagrange support vector machine （LSVM）.
