Based on the location of bromine substituents and conjugation matrix, a new substituent po- sition index ~X not only was defined, but also molecular shape indexes Km and electronega- tivity distance vectors Mm of diph...Based on the location of bromine substituents and conjugation matrix, a new substituent po- sition index ~X not only was defined, but also molecular shape indexes Km and electronega- tivity distance vectors Mm of diphenylamine and 209 kinds of polybrominated diphenylamine （PBDPA） molecules were calculated. Then the quantitative structure-property relationships （QSPR） among the thermodynamic properties of 210 organic pollutants and 0X, K3, M29, M36 were founded by Leaps-and-Bounds regression. Using the four structural parameters as input neurons of the artificial neural network, three satisfactory QSPR models with network structures of 4：21：1, 4：24：1, and 4：24：1 respectively, were achieved by the back-propagation algorithm. The total correlation coefficients R were 0.9999, 0.9997, and 0.9995 respectively and the standard errors S were 1.036, 1.469, and 1.510 respectively. The relative mean deviation between the predicted value and the experimental value of Sθ, AfHe and △fGθ- were 0.11%, 0.34% and 0.24% respectively, which indicated that the QSPR models had good stability and superior predictive ability. The results showed that there were good nonlinear correlations between the thermodynamic properties of PBDPAs and the four structural pa- rameters. Thus, it was concluded that the ANN models established by the new substituent position index were fully applicable to predict properties of PBDPAs.展开更多
在 Ad Hoc 网络中,许多路由协议都是基于节点的位置信息。但是在一些特殊情况下,Ad Hoc 网络中的定位不能依赖于 GPS,必须进行自定位。本文介绍了 Ad Hoc 网络中自定位算法的性能评价和分类方法,着重阐述了具有代表性的算法及其原理和特...在 Ad Hoc 网络中,许多路由协议都是基于节点的位置信息。但是在一些特殊情况下,Ad Hoc 网络中的定位不能依赖于 GPS,必须进行自定位。本文介绍了 Ad Hoc 网络中自定位算法的性能评价和分类方法,着重阐述了具有代表性的算法及其原理和特点,并提出了未来研究的方向。展开更多
标记分布学习是近年来提出的一种新的机器学习范式,它能很好地解决某些标记多义性的问题。现有的标记分布学习算法均利用条件概率建立参数模型,但未能充分利用特征和标记间的联系。本文考虑到特征相似的样本所对应的标记分布也应当相似...标记分布学习是近年来提出的一种新的机器学习范式,它能很好地解决某些标记多义性的问题。现有的标记分布学习算法均利用条件概率建立参数模型,但未能充分利用特征和标记间的联系。本文考虑到特征相似的样本所对应的标记分布也应当相似,利用原型聚类的k均值算法(k-means),将训练集的样本进行聚类,提出基于kmeans算法的标记分布学习(label distribution learning based on k-means algorithm,LDLKM)。首先通过聚类算法kmeans求得每一个簇的均值向量,然后分别求得对应标记分布的均值向量。最后将测试集和训练集的均值向量间的距离作为权重,应用到对测试集标记分布的预测上。在6个公开的数据集上进行实验,并与3种已有的标记分布学习算法在5种评价指标上进行比较,实验结果表明提出的LDLKM算法是有效的。展开更多
Composition vector trees （CVTrees） are inferred from whole-genome data by an alignment-free and parameter-free method. The agreement of these trees with the corresponding taxonomy provides an objective justification...Composition vector trees （CVTrees） are inferred from whole-genome data by an alignment-free and parameter-free method. The agreement of these trees with the corresponding taxonomy provides an objective justification of the inferred phylogeny. In this work, we show the stability and self-consistency of CVTrees by performing bootstrap and jackknife re-sampling tests adapted to this alignment-free approach. Our ultimate goal is to advocate the viewpoint that time-consuming statistical re-sampling tests can be avoided at all in using this alignment-free approach. Agreement with taxonomy should be taken as a major criterion to estimate prokaryotic phylogenetic trees.展开更多
Mosquitoes are an interesting topic due to their medical importance, as they play an active role in the transmission of many pathogens and parasites, acting as vectors for various pathologies that are deadly to humans...Mosquitoes are an interesting topic due to their medical importance, as they play an active role in the transmission of many pathogens and parasites, acting as vectors for various pathologies that are deadly to humans, such as dengue, yellow fever, chikungunya, West Nile virus, encephalitis and malaria, among many others that are less common. In terms of morbidity and mortality caused by vector-borne diseases, mosquitoes are the most dangerous animals for humanity and, although they also play a role in the ecosystem as a food source for other organisms, their importance for public health cannot be overlooked. As highly efficient vectors, they put more than three billion people at risk, mainly in tropical and subtropical regions as well as in Europe, since heat waves and flooding are becoming more frequent and severe, and summers are getting longer and warmer, accelerating mosquito development, biting rates, and the incubation of the pathogens within their bodies. Female mosquitoes bite to acquire proteins for the development of their ovaries and eggs and, in the process, acquire pathogens and/or parasites from one vertebrate host and transmit them to another, usually after a short period of replication. Three of their four life stages are lived in still freshwater, so it is crucial to understand their range of action when they reach adulthood and leave the water, in order to plan and implement local prevention measures. A set of georeferenced abundance data collected in mainland Portugal over seven years was linked to cartographed water bodies in a geographic information system to estimate the distances at which Culex pipiens s.l. had a significant presence, with criteria based on the size of the catches. The result allows for an estimate of the fly range of those mosquitoes, which can be used to focus countermeasures.展开更多
Internet of Things(IoT)networks are characterized by a multitude of wireless,interconnected devices that can dynamically join or exit the network without centralized administration or fixed infrastructure for routing....Internet of Things(IoT)networks are characterized by a multitude of wireless,interconnected devices that can dynamically join or exit the network without centralized administration or fixed infrastructure for routing.While multipath routing in IoT networks can improve data transmission reliability and load balancing by establishing multiple paths between source and destination nodes,these networks are susceptible to security threats due to their wireless nature.Traditional security solutions developed for conventional networks are often ill-suited to the unique challenges posed by IoT environments.In response to these challenges,this paper proposes the integration of the Ad hoc On-demand Multipath Distance Vector(AOMDV)routing protocol with a trust model to enhance network performance.Key findings from this research demonstrate the successful fusion of AOMDV with a trust model,resulting in tangible improvements in network performance.The assessment of trustworthiness bolsters both security and routing capabilities in IoT networks.The trust model plays a crucial role in mitigating black hole attacks in IoT networks by evaluating the trustworthiness of nodes and helping in the identification and avoidance of malicious nodes that may act as black holes.Simulation results validate the efficacy of the proposed trust-based routing mechanism in achieving its objectives.Trust plays a pivotal role in decision-making and in the creation of secure distribution systems.By assessing the trustworthiness of nodes,both network security and routing efficiency can be enhanced.The effectiveness of the proposed trust-based routing mechanism is scrutinized through simulations,offering insights into its potential advantages in terms of improved network security and routing performance in the context of the IoT.展开更多
文摘Based on the location of bromine substituents and conjugation matrix, a new substituent po- sition index ~X not only was defined, but also molecular shape indexes Km and electronega- tivity distance vectors Mm of diphenylamine and 209 kinds of polybrominated diphenylamine （PBDPA） molecules were calculated. Then the quantitative structure-property relationships （QSPR） among the thermodynamic properties of 210 organic pollutants and 0X, K3, M29, M36 were founded by Leaps-and-Bounds regression. Using the four structural parameters as input neurons of the artificial neural network, three satisfactory QSPR models with network structures of 4：21：1, 4：24：1, and 4：24：1 respectively, were achieved by the back-propagation algorithm. The total correlation coefficients R were 0.9999, 0.9997, and 0.9995 respectively and the standard errors S were 1.036, 1.469, and 1.510 respectively. The relative mean deviation between the predicted value and the experimental value of Sθ, AfHe and △fGθ- were 0.11%, 0.34% and 0.24% respectively, which indicated that the QSPR models had good stability and superior predictive ability. The results showed that there were good nonlinear correlations between the thermodynamic properties of PBDPAs and the four structural pa- rameters. Thus, it was concluded that the ANN models established by the new substituent position index were fully applicable to predict properties of PBDPAs.
文摘标记分布学习是近年来提出的一种新的机器学习范式,它能很好地解决某些标记多义性的问题。现有的标记分布学习算法均利用条件概率建立参数模型,但未能充分利用特征和标记间的联系。本文考虑到特征相似的样本所对应的标记分布也应当相似,利用原型聚类的k均值算法(k-means),将训练集的样本进行聚类,提出基于kmeans算法的标记分布学习(label distribution learning based on k-means algorithm,LDLKM)。首先通过聚类算法kmeans求得每一个簇的均值向量,然后分别求得对应标记分布的均值向量。最后将测试集和训练集的均值向量间的距离作为权重,应用到对测试集标记分布的预测上。在6个公开的数据集上进行实验,并与3种已有的标记分布学习算法在5种评价指标上进行比较,实验结果表明提出的LDLKM算法是有效的。
基金supported by the National Basic Research Program of China (the 973 Program, Grant No. 2007CB814800)the Shanghai Leading Academic Discipline Project (Grant No. B111)
文摘Composition vector trees （CVTrees） are inferred from whole-genome data by an alignment-free and parameter-free method. The agreement of these trees with the corresponding taxonomy provides an objective justification of the inferred phylogeny. In this work, we show the stability and self-consistency of CVTrees by performing bootstrap and jackknife re-sampling tests adapted to this alignment-free approach. Our ultimate goal is to advocate the viewpoint that time-consuming statistical re-sampling tests can be avoided at all in using this alignment-free approach. Agreement with taxonomy should be taken as a major criterion to estimate prokaryotic phylogenetic trees.
文摘Mosquitoes are an interesting topic due to their medical importance, as they play an active role in the transmission of many pathogens and parasites, acting as vectors for various pathologies that are deadly to humans, such as dengue, yellow fever, chikungunya, West Nile virus, encephalitis and malaria, among many others that are less common. In terms of morbidity and mortality caused by vector-borne diseases, mosquitoes are the most dangerous animals for humanity and, although they also play a role in the ecosystem as a food source for other organisms, their importance for public health cannot be overlooked. As highly efficient vectors, they put more than three billion people at risk, mainly in tropical and subtropical regions as well as in Europe, since heat waves and flooding are becoming more frequent and severe, and summers are getting longer and warmer, accelerating mosquito development, biting rates, and the incubation of the pathogens within their bodies. Female mosquitoes bite to acquire proteins for the development of their ovaries and eggs and, in the process, acquire pathogens and/or parasites from one vertebrate host and transmit them to another, usually after a short period of replication. Three of their four life stages are lived in still freshwater, so it is crucial to understand their range of action when they reach adulthood and leave the water, in order to plan and implement local prevention measures. A set of georeferenced abundance data collected in mainland Portugal over seven years was linked to cartographed water bodies in a geographic information system to estimate the distances at which Culex pipiens s.l. had a significant presence, with criteria based on the size of the catches. The result allows for an estimate of the fly range of those mosquitoes, which can be used to focus countermeasures.
文摘Internet of Things(IoT)networks are characterized by a multitude of wireless,interconnected devices that can dynamically join or exit the network without centralized administration or fixed infrastructure for routing.While multipath routing in IoT networks can improve data transmission reliability and load balancing by establishing multiple paths between source and destination nodes,these networks are susceptible to security threats due to their wireless nature.Traditional security solutions developed for conventional networks are often ill-suited to the unique challenges posed by IoT environments.In response to these challenges,this paper proposes the integration of the Ad hoc On-demand Multipath Distance Vector(AOMDV)routing protocol with a trust model to enhance network performance.Key findings from this research demonstrate the successful fusion of AOMDV with a trust model,resulting in tangible improvements in network performance.The assessment of trustworthiness bolsters both security and routing capabilities in IoT networks.The trust model plays a crucial role in mitigating black hole attacks in IoT networks by evaluating the trustworthiness of nodes and helping in the identification and avoidance of malicious nodes that may act as black holes.Simulation results validate the efficacy of the proposed trust-based routing mechanism in achieving its objectives.Trust plays a pivotal role in decision-making and in the creation of secure distribution systems.By assessing the trustworthiness of nodes,both network security and routing efficiency can be enhanced.The effectiveness of the proposed trust-based routing mechanism is scrutinized through simulations,offering insights into its potential advantages in terms of improved network security and routing performance in the context of the IoT.
