Present work was designed to quantitatively evaluate the performance of diffusion-weighted magnetic resonance imaging（DWI） in the diagnosis of the presence of metastasis in lymph nodes（LNs）. Eligible studies were ...Present work was designed to quantitatively evaluate the performance of diffusion-weighted magnetic resonance imaging（DWI） in the diagnosis of the presence of metastasis in lymph nodes（LNs）. Eligible studies were identified from systematical Pub Med and EMBASE searches. Data were extracted. Meta-analyses were performed to generate pooled sensitivity and specificity on the basis of per-node, per-lesion and per-patient, respectively. Fourteen publications（2458 LNs, 404 lesions and 334 patients） were eligible. Per-node basis demonstrated the pooled sensitivity and specificity was 0.82（P〈0.0001） and 0.90（P〈0.0001）, respectively. Per-lesion basis illustrated the pooled sensitivity and specificity was 0.73（P=0.0036） and 0.85（P〈0.0001）, respectively. Per-patient basis indicated the pooled sensitivity and specificity was 0.67（P=0.0909） and 0.86（P〈0.0001）, respectively. In conclusion, DWI has rather a negative predictive value for the diagnosis of LN metastasis presence. The difference of the mean apparent diffusion coefficients between benign and malignant LNs is not yet stable. Therefore, the DWI technique has to be further improved.展开更多
Node of network has lots of information, such as topology, text and label information. Therefore, node classification is an open issue. Recently, one vector of node is directly connected at the end of another vector. ...Node of network has lots of information, such as topology, text and label information. Therefore, node classification is an open issue. Recently, one vector of node is directly connected at the end of another vector. However, this method actually obtains the performance by extending dimensions and considering that the text and structural information are one-to-one, which is obviously unreasonable. Regarding this issue, a method by weighting vectors is proposed in this paper. Three methods, negative logarithm, modulus and sigmoid function are used to weight-trained vectors, then recombine the weighted vectors and put them into the SVM classifier for evaluation output. By comparing three different weighting methods, the results showed that using negative logarithm weighting achieved better results than the other two using modulus and sigmoid function weighting, and was superior to directly concatenating vectors in the same dimension.展开更多
Malignant melanoma is a malignancy of pigmentproducing cells(melanocytes) located predominantly in the skin. Nodal metastases are an adverse prognostic factor compromising long term patient survival. Therefore, accura...Malignant melanoma is a malignancy of pigmentproducing cells(melanocytes) located predominantly in the skin. Nodal metastases are an adverse prognostic factor compromising long term patient survival. Therefore, accurate detection of regional nodal metastases is required for optimization of treatment. Computed tomography(CT) and magnetic resonance imaging(MRI) remain the primary imaging modalities for regional staging of malignant melanoma. However, both modalities rely on size-related and morphological criteria to differentiate between benign and malignant lymph nodes, decreasing the sensitivity for detection of small metastases. Surgery is the primary mode of therapy for localized cutaneous melanoma. Patients should be followed up for metastases after surgical removal. We report here a case of inguinal lymph node enlargement with a genital vesicular lesion with a history of surgery for malignant melanoma on her thigh two years ago. CT and diffusion weighted-MRI(DW-MRI) were applied for the lymph node identification. DW-MRI revealed malignant lymph nodes due to malignant melanoma metastases correlation with pathological findings.展开更多
A Dark Network is a network that cannot be accessed through tradition means. Once uncovered, to any degree, dark network analysis can be accomplished using the SNA software. The output of SNA software includes many me...A Dark Network is a network that cannot be accessed through tradition means. Once uncovered, to any degree, dark network analysis can be accomplished using the SNA software. The output of SNA software includes many measures and metrics. For each of these measures and metric, the output in ORA additionally provides the ability to obtain a rank ordering of the nodes in terms of these measures. We might use this information in decision making concerning best methods to disrupt or deceive a given dark network. In the Noordin Dark network, different nodes were identified as key nodes based upon the metric used. Our goal in this paper is to use methodologies to identify the key players or nodes in a Dark Network in a similar manner as we previously proposed in social networks. We apply two multi-attribute decision making methods, a hybrid AHP & TOPSIS and an average weighted ranks scheme, to analyze these outputs to find the most influential nodes as a function of the decision makers’ inputs. We compare these methods by illustration using the Noordin Dark Network with seventy-nine nodes. We discuss sensitivity analysis that is applied to the criteria weights in order to measure the change in the ranking of the nodes.展开更多
To improve the performance of Ad hoc on-demand multipath distance vector (AOMDV) protocol, we proposed NS-AOMDV which is short for “AOMDV based on node state”. In NS-AOMDV, we introduce node state to improve AOMDV’...To improve the performance of Ad hoc on-demand multipath distance vector (AOMDV) protocol, we proposed NS-AOMDV which is short for “AOMDV based on node state”. In NS-AOMDV, we introduce node state to improve AOMDV’s performance in selecting main path. In route discovery process, the routing update rule calculates the node weight of each path and sorts the path weight by descending value in route list, and we choose the path which has the largest path weight for data transmission. NS-AOMDV also uses the technology of route request (RREQ) packet delay forwarding and energy threshold to ease network congestion, limit the RREQ broadcast storm, and avoid low energy nodes to participate in the establishment of the path. The results of simulation show that NS-AOMDV can effectively improve the networks’packets delivery rate, throughput and normalized routing overhead in the situation of dynamic network topology and heavy load.展开更多
Vehicular Ad hoc Networks (VANETs) which is a special form of Mobile Ad hoc Networks (MANETs) has promising application prospects in the future. Due to the rapid changing of topology structure, how to find a route whi...Vehicular Ad hoc Networks (VANETs) which is a special form of Mobile Ad hoc Networks (MANETs) has promising application prospects in the future. Due to the rapid changing of topology structure, how to find a route which can guarantee Quality of Service (QoS) is an important issue in VANETs. This paper presents an improved Greedy Perimeter Stateless Routing (GPSR) protocol based on our proposed next-hop node selection mechanism. Firstly, we define the link reliability in two cases which take the movement direction angle between two vehicles into consideration. Then we propose a next-hop node selection mechanism based on a weighted function which consists of link reliability between the sender node and next-hop candidate node, distance between next-hop candidate node and the destination, movement direction angle of next-hop candidate node. At last, an improved GPSR protocol is proposed based on the next-hop node selection mechanism. Simulation results are presented to evaluate the performance of the improved GPSR protocol, which shows that the performance including packet delivery ratio and average end-to-end delay of the proposed protocol is better in some situations.展开更多
针对基本的快速搜索随机树(rapidly-exploring random tree,RRT)算法用于路径规划时存在的树扩展无导向性、密集障碍物区域规划效率低、局部区域节点聚集等问题,提出一种新的RRT改进算法。该算法采用增强的目标偏向策略,并引入可变的权...针对基本的快速搜索随机树(rapidly-exploring random tree,RRT)算法用于路径规划时存在的树扩展无导向性、密集障碍物区域规划效率低、局部区域节点聚集等问题,提出一种新的RRT改进算法。该算法采用增强的目标偏向策略,并引入可变的权值系数,提高随机树扩展的导向性和灵活性;同时采用局部节点过滤机制,过滤局部区域内聚集的节点;最后,使用节点直连策略对初始路径进行优化处理。仿真实验的结果表明,改进的RRT算法规划路径的速度更快且生成的路径质量更高,充分证明了改进算法的有效可行性。展开更多
现有的对比深度图聚类方法严重依赖输入图的同配性假设,在异配图中容易引发负采样假阴性与特征冗余的问题,导致聚类性能下降.为此,文中提出基于无负采样与权重去相关对比网络的图无关聚类方法(Negative-Free and Weight-Decorrelated Co...现有的对比深度图聚类方法严重依赖输入图的同配性假设,在异配图中容易引发负采样假阴性与特征冗余的问题,导致聚类性能下降.为此,文中提出基于无负采样与权重去相关对比网络的图无关聚类方法(Negative-Free and Weight-Decorrelated Contrastive Network for Graph-Agnostic Clustering,NFWD).首先,利用节点属性相似性构建特征图作为补充视图,通过拉普拉斯平滑滤波与共享参数的多层感知机(Multilayer Perceptron,MLP)分别获得特征图和原始图的节点表示,缓解同配性假设的原始图依赖.然后,针对异配图类冲突导致的负采样假阴性问题,基于自适应融合的节点表示获取聚类信息,构建簇中心节点表示,设计有效解决此问题的节点级与簇级双重特征对比的无负采样策略.最后,对MLP的权重矩阵施加正交约束,主动抑制冗余特征产生.在6个基准图数据集上的实验表明NFWD在图无关场景中的高效性与鲁棒性.展开更多
对于传统的跳点搜索算法(jump point search,JPS)规划的路径中存在着靠近障碍物可能产生剐蹭、存在着较多折点、产生的路径不平滑、路径规划时间长等问题,提出一种SS-JPS(simplify secure-JPS)的改进算法。对地图中的环境信息进行栅格化...对于传统的跳点搜索算法(jump point search,JPS)规划的路径中存在着靠近障碍物可能产生剐蹭、存在着较多折点、产生的路径不平滑、路径规划时间长等问题,提出一种SS-JPS(simplify secure-JPS)的改进算法。对地图中的环境信息进行栅格化,引入权重系数对代价函数进行改进,并且在搜索出新跳点的周围节点与父节点的连线进行节点筛选,筛选出连线中无穿越或斜向剐蹭障碍物的新跳点。由于产生大量跳点使其产生的路径折点多,对产生的路径进行剪枝优化,大大减少了路径中产生的折点,最后用三次B样条曲线平滑路径。仿真结果表明,与现有路径规划算法相比,SS-JPS算法规划出的路径折点更少,搜索节点少且时间更短,并且在加入了平滑优化后的路径更安全,也使得平滑性大大提高。展开更多
文摘Present work was designed to quantitatively evaluate the performance of diffusion-weighted magnetic resonance imaging（DWI） in the diagnosis of the presence of metastasis in lymph nodes（LNs）. Eligible studies were identified from systematical Pub Med and EMBASE searches. Data were extracted. Meta-analyses were performed to generate pooled sensitivity and specificity on the basis of per-node, per-lesion and per-patient, respectively. Fourteen publications（2458 LNs, 404 lesions and 334 patients） were eligible. Per-node basis demonstrated the pooled sensitivity and specificity was 0.82（P〈0.0001） and 0.90（P〈0.0001）, respectively. Per-lesion basis illustrated the pooled sensitivity and specificity was 0.73（P=0.0036） and 0.85（P〈0.0001）, respectively. Per-patient basis indicated the pooled sensitivity and specificity was 0.67（P=0.0909） and 0.86（P〈0.0001）, respectively. In conclusion, DWI has rather a negative predictive value for the diagnosis of LN metastasis presence. The difference of the mean apparent diffusion coefficients between benign and malignant LNs is not yet stable. Therefore, the DWI technique has to be further improved.
文摘Node of network has lots of information, such as topology, text and label information. Therefore, node classification is an open issue. Recently, one vector of node is directly connected at the end of another vector. However, this method actually obtains the performance by extending dimensions and considering that the text and structural information are one-to-one, which is obviously unreasonable. Regarding this issue, a method by weighting vectors is proposed in this paper. Three methods, negative logarithm, modulus and sigmoid function are used to weight-trained vectors, then recombine the weighted vectors and put them into the SVM classifier for evaluation output. By comparing three different weighting methods, the results showed that using negative logarithm weighting achieved better results than the other two using modulus and sigmoid function weighting, and was superior to directly concatenating vectors in the same dimension.
文摘Malignant melanoma is a malignancy of pigmentproducing cells(melanocytes) located predominantly in the skin. Nodal metastases are an adverse prognostic factor compromising long term patient survival. Therefore, accurate detection of regional nodal metastases is required for optimization of treatment. Computed tomography(CT) and magnetic resonance imaging(MRI) remain the primary imaging modalities for regional staging of malignant melanoma. However, both modalities rely on size-related and morphological criteria to differentiate between benign and malignant lymph nodes, decreasing the sensitivity for detection of small metastases. Surgery is the primary mode of therapy for localized cutaneous melanoma. Patients should be followed up for metastases after surgical removal. We report here a case of inguinal lymph node enlargement with a genital vesicular lesion with a history of surgery for malignant melanoma on her thigh two years ago. CT and diffusion weighted-MRI(DW-MRI) were applied for the lymph node identification. DW-MRI revealed malignant lymph nodes due to malignant melanoma metastases correlation with pathological findings.
文摘A Dark Network is a network that cannot be accessed through tradition means. Once uncovered, to any degree, dark network analysis can be accomplished using the SNA software. The output of SNA software includes many measures and metrics. For each of these measures and metric, the output in ORA additionally provides the ability to obtain a rank ordering of the nodes in terms of these measures. We might use this information in decision making concerning best methods to disrupt or deceive a given dark network. In the Noordin Dark network, different nodes were identified as key nodes based upon the metric used. Our goal in this paper is to use methodologies to identify the key players or nodes in a Dark Network in a similar manner as we previously proposed in social networks. We apply two multi-attribute decision making methods, a hybrid AHP & TOPSIS and an average weighted ranks scheme, to analyze these outputs to find the most influential nodes as a function of the decision makers’ inputs. We compare these methods by illustration using the Noordin Dark Network with seventy-nine nodes. We discuss sensitivity analysis that is applied to the criteria weights in order to measure the change in the ranking of the nodes.
文摘To improve the performance of Ad hoc on-demand multipath distance vector (AOMDV) protocol, we proposed NS-AOMDV which is short for “AOMDV based on node state”. In NS-AOMDV, we introduce node state to improve AOMDV’s performance in selecting main path. In route discovery process, the routing update rule calculates the node weight of each path and sorts the path weight by descending value in route list, and we choose the path which has the largest path weight for data transmission. NS-AOMDV also uses the technology of route request (RREQ) packet delay forwarding and energy threshold to ease network congestion, limit the RREQ broadcast storm, and avoid low energy nodes to participate in the establishment of the path. The results of simulation show that NS-AOMDV can effectively improve the networks’packets delivery rate, throughput and normalized routing overhead in the situation of dynamic network topology and heavy load.
文摘Vehicular Ad hoc Networks (VANETs) which is a special form of Mobile Ad hoc Networks (MANETs) has promising application prospects in the future. Due to the rapid changing of topology structure, how to find a route which can guarantee Quality of Service (QoS) is an important issue in VANETs. This paper presents an improved Greedy Perimeter Stateless Routing (GPSR) protocol based on our proposed next-hop node selection mechanism. Firstly, we define the link reliability in two cases which take the movement direction angle between two vehicles into consideration. Then we propose a next-hop node selection mechanism based on a weighted function which consists of link reliability between the sender node and next-hop candidate node, distance between next-hop candidate node and the destination, movement direction angle of next-hop candidate node. At last, an improved GPSR protocol is proposed based on the next-hop node selection mechanism. Simulation results are presented to evaluate the performance of the improved GPSR protocol, which shows that the performance including packet delivery ratio and average end-to-end delay of the proposed protocol is better in some situations.
文摘针对基本的快速搜索随机树(rapidly-exploring random tree,RRT)算法用于路径规划时存在的树扩展无导向性、密集障碍物区域规划效率低、局部区域节点聚集等问题,提出一种新的RRT改进算法。该算法采用增强的目标偏向策略,并引入可变的权值系数,提高随机树扩展的导向性和灵活性;同时采用局部节点过滤机制,过滤局部区域内聚集的节点;最后,使用节点直连策略对初始路径进行优化处理。仿真实验的结果表明,改进的RRT算法规划路径的速度更快且生成的路径质量更高,充分证明了改进算法的有效可行性。
文摘现有的对比深度图聚类方法严重依赖输入图的同配性假设,在异配图中容易引发负采样假阴性与特征冗余的问题,导致聚类性能下降.为此,文中提出基于无负采样与权重去相关对比网络的图无关聚类方法(Negative-Free and Weight-Decorrelated Contrastive Network for Graph-Agnostic Clustering,NFWD).首先,利用节点属性相似性构建特征图作为补充视图,通过拉普拉斯平滑滤波与共享参数的多层感知机(Multilayer Perceptron,MLP)分别获得特征图和原始图的节点表示,缓解同配性假设的原始图依赖.然后,针对异配图类冲突导致的负采样假阴性问题,基于自适应融合的节点表示获取聚类信息,构建簇中心节点表示,设计有效解决此问题的节点级与簇级双重特征对比的无负采样策略.最后,对MLP的权重矩阵施加正交约束,主动抑制冗余特征产生.在6个基准图数据集上的实验表明NFWD在图无关场景中的高效性与鲁棒性.
文摘对于传统的跳点搜索算法(jump point search,JPS)规划的路径中存在着靠近障碍物可能产生剐蹭、存在着较多折点、产生的路径不平滑、路径规划时间长等问题,提出一种SS-JPS(simplify secure-JPS)的改进算法。对地图中的环境信息进行栅格化,引入权重系数对代价函数进行改进,并且在搜索出新跳点的周围节点与父节点的连线进行节点筛选,筛选出连线中无穿越或斜向剐蹭障碍物的新跳点。由于产生大量跳点使其产生的路径折点多,对产生的路径进行剪枝优化,大大减少了路径中产生的折点,最后用三次B样条曲线平滑路径。仿真结果表明,与现有路径规划算法相比,SS-JPS算法规划出的路径折点更少,搜索节点少且时间更短,并且在加入了平滑优化后的路径更安全,也使得平滑性大大提高。
