一种基于节点位置和密度的非均匀分簇路由算法

分析了现有分簇路由算法,提出了基于节点位置和密度的非均匀分簇路由算法。簇头选举阶段,考虑了节点的剩余能量,并引入竞争机制进行簇头选择;成簇阶段,综合考虑节点与基站的距离、节点密度以进行非均匀分簇,达到节点能耗均衡的效果,同时解决路由热区问题;簇间路由阶段,通过设立通信簇头节点,使簇间数据转发任务从簇头中分离,簇头节点只负责簇内的数据收集和融合,而通信簇头节点负责簇间数据传输,减少了簇头的能量消耗。实验结果表明,改进后的路由算法能够有效地均衡网络负载,并显著地延长网络的生命周期。     

基于预分类的逆变异分类器算法

遗传算法已经在许多领域得到了成功的应用,在解决模式识别问题时,由于遗传中的变异过程的存在导致了模式差异,如果能够减少这种差异性,就可以提高模式分类的正确率。针对这种情况,本文提出了在预分类基础上的一种逆变异算法,该算法采用遗传算法中变异过程的逆过程,来减少模式的差异性,达到提高模式分类正确率的目的。在ORL人脸库上的实验结果表明,该分类器的模式识别率明显高于传统的分类器算法及遗传算法。     

Exploring cell tower data dumps for supervised learning-based point-of-interest prediction (industrial paper)

Exploring massive mobile data for location-based services becomes one of the key challenges in mobile data mining. In this paper, we investigate a problem of finding a correlation between the collective behavior of mobile users and the distribution of points of interest (POIs) in a city. Specifically, we use large-scale cell tower data dumps collected from cell towers and POIs extracted from a popular social network service, Weibo. Our objective is to make use of the data from these two different types of sources to build a model for predicting the POI densities of different regions in the covered area. An application domain that may benefit from our research is a business recommendation application, where a prediction result can be used as a recommendation for opening a new store/branch. The crux of our contribution is the method of representing the collective behavior of mobile users as a histogram of connection counts over a period of time in each region. This representation ultimately enables us to apply a supervised learning algorithm to our problem in order to train a POI prediction model using the POI data set as the ground truth. We studied 12 state-of-the-art classification and regression algorithms; experimental results demonstrate the feasibility and effectiveness of the proposed method.     

Game‐Based Valley‐Fill Charging Coordination for Large‐Population Plug‐in Electric Vehicles

Charging coordination of large‐population autonomous plug‐in electric vehicles (PEVs) in the power grid can be formulated as a class of constrained optimization problems. To overcome the computational complexity, a game‐based method is proposed for the charging problems of the PEV population, which is composed of homogeneous subpopulations, such that individuals update their best charging strategies simultaneously with respect to a common electricity price determined by the total demand. To mitigate the oscillation behavior caused by the greedy behavior for the cheap electricity by individuals, a deviation cost is introduced to penalize against the deviation of the individual strategy from the average value of the homogeneous subpopulation. By adopting a proper deviation cost and following a best strategy update mechanism, the game systems may converge to the socially optimal valley‐fill Nash equilibrium. Simulation examples are studied to illustrate the results.     

新闻聚合系统中的数据挖掘技术初探

互联网的迅速发展以及信息的海量增长给数据挖掘技术提供了一个广阔的舞台,数据挖掘技术在信息检索和个性化推荐中占据越来越重要的地位。该文描述了一个新闻聚合系统的组成结构和基本算法,包括一些文本模型和推荐算法等,可以有效地从海量信息中筛选出人们感兴趣的信息。在此基础上,该文提出了一种基于特征模型的推荐算法。特征模型将用户的兴趣偏好特征与新闻的属性特征统一起来,方便表示和计算,为进一步地挖掘用户真实兴趣偏好、更加准确地进行新闻推荐提供了良好的基础。     

A case of Leukonychia with scanning electron microscope observation

Leukonychia is a medical term for white discoloration appearing on nails. The pathophysiologic mechanisms that cause white discoloration are not entirely clear. We processed a case of leukonychia with scanning electron microscope observation and found many crispy, obviously dissociated "layers" in the lower part of the white nail plate. The dissociated "layers" were composed of thick, loose, coarse keratin bundles intertwined with each other. We believe the dissociated "layers" are related to the clinically noted white discoloration appearing on the nails.     

Small‐signal and noise modeling of class of HEMTs using knowledge‐based artificial neural networks

In this article, the neural network approach is exploited for development of bias‐dependent small‐signal and noise models of a class of microwave field effect transistor (FETs) made in the same technology but differing in the gate width. The prior knowledge neural approach is applied. Introducing gate width at the input of proposed neural networks, as well as the S/noise parameters of a device that belongs to the same class as the modeled device representing the prior knowledge, leads to very accurate scattering and noise parameters' modeling, as exemplified by modeling of class of pseudomorphic high electron mobility transistor (pHEMT) devices. © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2013.     

非对称复式断面明渠中污染物输移扩散的大涡模拟

运用大涡模拟计算了两个非对称复式断面明渠内的水流运动和污染物扩散,其中由亚格子尺度涡运动引起的亚格子应力与物质扩散通过Smagorinsky-Lilly亚网格模型模拟.将计算结果与文献中的激光多普勒流速计和激光诱导荧光技术测量的试验数据进行对比,结果表明,计算得到的流场结构和污染物浓度分布均较好地吻合于测量结果.模拟计...     

小湾水电站泄洪洞抗冲耐磨混凝土施工综述

小湾水电站泄洪洞在泄洪时具有高水头、高流速、泄量大的特点,对混凝土冲刷力强,容易产生空蚀破坏.通过合理选择浇筑措施、优选配合比、有效的温度控制以及合理的养护,目前,泄洪洞各方面质量均满足要求,且未发现裂缝.泄洪洞抗冲耐磨混凝土施工及质量控制的成功,为减小泄洪洞过流面空蚀和抗冲耐磨提供了保障.     

蒸汽发电系统的优化

介绍蒸汽发电系统的优化方法,以及时侦测、剔除和校正误差数据,有效保障发电机组正常运行.