Node positioning is a fundamental problem in applications of wireless sensor networks (WSNs). In this paper, a new range-free algorithm, called spring swarm localization algorithm (SSLA), is proposed for positioning W...Node positioning is a fundamental problem in applications of wireless sensor networks (WSNs). In this paper, a new range-free algorithm, called spring swarm localization algorithm (SSLA), is proposed for positioning WSNs. To determine the locations of sensor nodes, the proposed algorithm uses network topology information and a small fraction of sensor nodes which know their locations. Numerical simulations show that high positioning accuracy can be obtained by using the algorithm. Some examples are given to illustrate the effectiveness of the algorithm.展开更多
对发表于《ISI-SCIE(Science Citation Index Expanded)》上的PHARMACOLOGY&PHARMACY学科的论文作者合作研究形成的一个复杂网络进行了研究。分析表明该合作网络共有40个子网络,其最大连通子网络节点的度服从幂律分布且有厚尾趋势,...对发表于《ISI-SCIE(Science Citation Index Expanded)》上的PHARMACOLOGY&PHARMACY学科的论文作者合作研究形成的一个复杂网络进行了研究。分析表明该合作网络共有40个子网络,其最大连通子网络节点的度服从幂律分布且有厚尾趋势,具有较小的平均路径长度,较大的聚类系数,存在少数关键节点,具有典型的小世界性和无标度性。并通过GN算法分析和挖掘了该最大连通子网络的社团结构,用度值、介数值和PAGERANK值等指标评价了网络的中心节点,揭示了合作网络中合作水平较高的科研团队和具有影响力的科学家。展开更多
In this study,a wavelet multi-resolution interpolation Galerkin method(WMIGM)is proposed to solve linear singularly perturbed boundary value problems.Unlike conventional wavelet schemes,the proposed algorithm can be r...In this study,a wavelet multi-resolution interpolation Galerkin method(WMIGM)is proposed to solve linear singularly perturbed boundary value problems.Unlike conventional wavelet schemes,the proposed algorithm can be readily extended to special node generation techniques,such as the Shishkin node.Such a wavelet method allows a high degree of local refinement of the nodal distribution to efficiently capture localized steep gradients.All the shape functions possess the Kronecker delta property,making the imposition of boundary conditions as easy as that in the finite element method.Four numerical examples are studied to demonstrate the validity and accuracy of the proposedwavelet method.The results showthat the use ofmodified Shishkin nodes can significantly reduce numerical oscillation near the boundary layer.Compared with many other methods,the proposed method possesses satisfactory accuracy and efficiency.The theoretical and numerical results demonstrate that the order of theε-uniform convergence of this wavelet method can reach 5.展开更多
Background:Whether non-sentinel lymph node(SLN)-positive melanoma patients can benefit from completion lymph node dissection(CLND)is still unclear.The current study was performed to identify the prognostic role of non...Background:Whether non-sentinel lymph node(SLN)-positive melanoma patients can benefit from completion lymph node dissection(CLND)is still unclear.The current study was performed to identify the prognostic role of nonSLN status in SLN-positive melanoma and to investigate the predictive factors of non-SLN metastasis in acral and cutaneous melanoma patients.Methods:The records of 328 SLN-positive melanoma patients who underwent radical surgery at four cancer centers from September 2009 to August 2017 were reviewed.Clinicopathological data including age,gender,Clark level,Breslow index,ulceration,the number of positive SLNs,non-SLN status,and adjuvant therapy were included for survival analyses.Patients were followed up until death or June 30,2019.Multivariable logistic regression modeling was performed to identify factors associated with non-SLN positivity.Log-rank analysis and Cox regression analysis were used to identify the prognostic factors for disease-free survival(DFS)and overall survival(OS).Results:Among all enrolled patients,220(67.1%)had acral melanoma and 108(32.9%)had cutaneous melanoma.The 5-year DFS and OS rate of the entire cohort was 31.5%and 54.1%,respectively.More than 1 positive SLNs were found in 123(37.5%)patients.Positive non-SLNs were found in 99(30.2%)patients.Patients with positive non-SLNs had significantly worse DFS and OS(log-rank P<0.001).Non-SLN status(P=0.003),number of positive SLNs(P=0.016),and adjuvant therapy(P=0.025)were independent prognostic factors for DFS,while non-SLN status(P=0.002),the Breslow index(P=0.027),Clark level(P=0.006),ulceration(P=0.004),number of positive SLNs(P=0.001),and adjuvant therapy(P=0.007)were independent prognostic factors for OS.The Breslow index(P=0.020),Clark level(P=0.012),and number of positive SLNs(P=0.031)were independently related to positive non-SLNs and could be used to develop more personalized surgical strategy.Conclusions:Non-SLN-positive melanoma patients had worse DFS and OS even after immediate CLND than those with non-SLN-negative me展开更多
The designation of the cluster number K and the initial centroids is essential for K-modes clustering algorithm. However, most of the improved methods based on K-modes specify the K value manually and generate the ini...The designation of the cluster number K and the initial centroids is essential for K-modes clustering algorithm. However, most of the improved methods based on K-modes specify the K value manually and generate the initial centroids randomly, which makes the clustering algorithm significantly dependent on human-based decisions and unstable on the iteration time. To overcome this limitation, we propose a cohesive K-modes (CK-modes) algorithm to generate the cluster number K and the initial centroids automatically. Explicitly, we construct a labeled property graph based on index-free adjacency to capture both global and local cohesion of the node in the sample of the input datasets. The cohesive node calculated based on the property similarity is exploited to split the graph to a K-node tree that determines the K value, and then the initial centroids are selected from the split subtrees. Since the property graph construction and the cohesion calculation are only performed once, they account for a small amount of execution time of the clustering operation with multiple iterations, but significantly accelerate the clustering convergence. Experimental validation in both real-world and synthetic datasets shows that the CK-modes algorithm outperforms the state-of-the-art algorithms.展开更多
基金supported by the National Natural Science Foundation of China (Grant Nos. 10832006 and 60872093)
文摘Node positioning is a fundamental problem in applications of wireless sensor networks (WSNs). In this paper, a new range-free algorithm, called spring swarm localization algorithm (SSLA), is proposed for positioning WSNs. To determine the locations of sensor nodes, the proposed algorithm uses network topology information and a small fraction of sensor nodes which know their locations. Numerical simulations show that high positioning accuracy can be obtained by using the algorithm. Some examples are given to illustrate the effectiveness of the algorithm.
文摘对发表于《ISI-SCIE(Science Citation Index Expanded)》上的PHARMACOLOGY&PHARMACY学科的论文作者合作研究形成的一个复杂网络进行了研究。分析表明该合作网络共有40个子网络,其最大连通子网络节点的度服从幂律分布且有厚尾趋势,具有较小的平均路径长度,较大的聚类系数,存在少数关键节点,具有典型的小世界性和无标度性。并通过GN算法分析和挖掘了该最大连通子网络的社团结构,用度值、介数值和PAGERANK值等指标评价了网络的中心节点,揭示了合作网络中合作水平较高的科研团队和具有影响力的科学家。
基金supported by the National Natural Science Foundation of China (No.12172154)the 111 Project (No.B14044)+1 种基金the Natural Science Foundation of Gansu Province (No.23JRRA1035)the Natural Science Foundation of Anhui University of Finance and Economics (No.ACKYC20043).
文摘In this study,a wavelet multi-resolution interpolation Galerkin method(WMIGM)is proposed to solve linear singularly perturbed boundary value problems.Unlike conventional wavelet schemes,the proposed algorithm can be readily extended to special node generation techniques,such as the Shishkin node.Such a wavelet method allows a high degree of local refinement of the nodal distribution to efficiently capture localized steep gradients.All the shape functions possess the Kronecker delta property,making the imposition of boundary conditions as easy as that in the finite element method.Four numerical examples are studied to demonstrate the validity and accuracy of the proposedwavelet method.The results showthat the use ofmodified Shishkin nodes can significantly reduce numerical oscillation near the boundary layer.Compared with many other methods,the proposed method possesses satisfactory accuracy and efficiency.The theoretical and numerical results demonstrate that the order of theε-uniform convergence of this wavelet method can reach 5.
基金This work was financially supported by the Shanghai Committee of Science and Technology,China(Grant No.19411951700)the Shanghai Anti-cancer Association“Ao Xiang”project(Grant No.SACA-AX112)the National Natural Science Foundation of China(Grant No.81802636).
文摘Background:Whether non-sentinel lymph node(SLN)-positive melanoma patients can benefit from completion lymph node dissection(CLND)is still unclear.The current study was performed to identify the prognostic role of nonSLN status in SLN-positive melanoma and to investigate the predictive factors of non-SLN metastasis in acral and cutaneous melanoma patients.Methods:The records of 328 SLN-positive melanoma patients who underwent radical surgery at four cancer centers from September 2009 to August 2017 were reviewed.Clinicopathological data including age,gender,Clark level,Breslow index,ulceration,the number of positive SLNs,non-SLN status,and adjuvant therapy were included for survival analyses.Patients were followed up until death or June 30,2019.Multivariable logistic regression modeling was performed to identify factors associated with non-SLN positivity.Log-rank analysis and Cox regression analysis were used to identify the prognostic factors for disease-free survival(DFS)and overall survival(OS).Results:Among all enrolled patients,220(67.1%)had acral melanoma and 108(32.9%)had cutaneous melanoma.The 5-year DFS and OS rate of the entire cohort was 31.5%and 54.1%,respectively.More than 1 positive SLNs were found in 123(37.5%)patients.Positive non-SLNs were found in 99(30.2%)patients.Patients with positive non-SLNs had significantly worse DFS and OS(log-rank P<0.001).Non-SLN status(P=0.003),number of positive SLNs(P=0.016),and adjuvant therapy(P=0.025)were independent prognostic factors for DFS,while non-SLN status(P=0.002),the Breslow index(P=0.027),Clark level(P=0.006),ulceration(P=0.004),number of positive SLNs(P=0.001),and adjuvant therapy(P=0.007)were independent prognostic factors for OS.The Breslow index(P=0.020),Clark level(P=0.012),and number of positive SLNs(P=0.031)were independently related to positive non-SLNs and could be used to develop more personalized surgical strategy.Conclusions:Non-SLN-positive melanoma patients had worse DFS and OS even after immediate CLND than those with non-SLN-negative me
基金supported by the National Natural Science Foundation of China under Grant No. 61772534the Excellent Chinese-Foreign Youth Exchange Foundation Program of Chinese Association of Science and Technology under Grant No. 311319000207.
文摘The designation of the cluster number K and the initial centroids is essential for K-modes clustering algorithm. However, most of the improved methods based on K-modes specify the K value manually and generate the initial centroids randomly, which makes the clustering algorithm significantly dependent on human-based decisions and unstable on the iteration time. To overcome this limitation, we propose a cohesive K-modes (CK-modes) algorithm to generate the cluster number K and the initial centroids automatically. Explicitly, we construct a labeled property graph based on index-free adjacency to capture both global and local cohesion of the node in the sample of the input datasets. The cohesive node calculated based on the property similarity is exploited to split the graph to a K-node tree that determines the K value, and then the initial centroids are selected from the split subtrees. Since the property graph construction and the cohesion calculation are only performed once, they account for a small amount of execution time of the clustering operation with multiple iterations, but significantly accelerate the clustering convergence. Experimental validation in both real-world and synthetic datasets shows that the CK-modes algorithm outperforms the state-of-the-art algorithms.
