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Search Results: 1 - 10 of 120011 matches for " Dianhong Wang "
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Energy-Efficient Node Selection for Target Tracking in Wireless Sensor Networks
Yong Wang,Dianhong Wang
International Journal of Distributed Sensor Networks , 2013, DOI: 10.1155/2013/830950
Abnormal Behavior Detection Using Trajectory Analysis in Camera Sensor Networks
Yong Wang,Dianhong Wang,Fenxiong Chen
International Journal of Distributed Sensor Networks , 2014, DOI: 10.1155/2014/839045
Abstract: Camera sensor networks have developed as a new technology for the wide-area video surveillance. In view of the limited power and computational capability of the camera nodes, the paper presents an abnormal behavior detection approach which is convenient and available for camera sensor networks. Trajectory analysis and anomaly modeling are carried out by single-node processing, whereas anomaly detection is performed by multinode voting. The main contributions of the proposed method are summarized as follows. First, target trajectories are reconstructed and represented as symbol sequences. Second, the sequences are taken into account using Markov model for building the transition probability matrix which can be used to automatically analyze abnormal behavior. Third, the final decision of anomaly detection is made through the majority voting of local results of individual camera nodes. Experimental results show that the proposed method can effectively estimate typical abnormal behaviors in real scenes. 1. Introduction Camera sensor networks consist of low-power microcamera nodes, which integrate the image sensor, embedded processor, and wireless transceiver. Multiple camera nodes with different views can provide comprehensive information and enhance the reliability of the captured events. Due to the advantages of enlarging surveillance area and solving target occlusion, camera sensor networks are best suited for real-time visual surveillance applications [1, 2]. One of essential purposes of visual surveillance is to detect moving targets and identify abnormal behaviors. In the past, model-based approaches have been proposed to tackle the anomaly detection problem. The work in [3] adopted dynamic Bayesian networks to model normal activities. An activity will be identified as abnormal if the likelihood of being generated by normal models is less than a threshold. Nevertheless an appropriate threshold is hard to determine in practice. In [4], a hidden Markov model (HMM) was applied to represent normal activities and perform anomaly detection. Note that it is difficult to label all the activities because of the tremendous variety of movement states. Trajectory modeling can determine the movement anomaly in video sequences, and many previous works have discussed the issue. In [5], vision-based trajectory learning and analysis methods were discussed. In [6], a sparse reconstruction analysis of target trajectory was introduced to detect abnormal behaviors. However, most of these works employ supervised learning to recognize normal behaviors, which requires a
Rough Set Approach to Multivariate Decision Trees Inducing
Dianhong Wang,Xingwen Liu,Liangxiao Jiang,Xiaoting Zhang
Journal of Computers , 2012, DOI: 10.4304/jcp.7.4.870-879
Abstract: Aimed at the problem of huge computation, large tree size and over-fitting of the testing data for multivariate decision tree (MDT) algorithms, we proposed a novel rough set-based multivariate decision trees (RSMDT) method. In this paper, the positive region degree of condition attributes with respect to decision attributes in rough set theory is used for selecting attributes in multivariate tests. And a new concept of extended generalization of one equivalence relation corresponding to another one is introduced and used for construction of multivariate tests. We experimentally test RSMDT algorithm in terms of classification accuracy, tree size and computing time, using the whole 36 UCI Machine Learning Repository data sets selected by Weka platform, and compare it with C4.5, classification and regression trees (CART), classification and regression trees with linear combinations (CART-LC), Oblique Classifier 1 (OC1), Quick Unbiased Efficient Statistical Trees (QUEST). The experimental results indicate that RSMDT algorithm significantly outperforms the comparison classification algorithms with improved classification accuracy, relatively small tree size, and shorter computing time.

Yu Dianhong,Li Lin,Lu Bingheng,

光子学报 , 2002,
Abstract: 基于光的波动理论,对紫外光立体成型技术中的聚焦光能量场进行了深入的理论分析,阐明了点光源所辐射的边疆球面波在册椭球面上的反射聚焦理论及反射光波场轴向和侧向的能量分布形式近似于高斯分布;同时从实验分析角度研究得出,经光纤耦合传输及透镜聚焦至树脂液面的光能量也基本上呈高斯分布;研究为立体成型技术中有效地利用紫外点光源的辐射能和提高成型精度,提供了充分的理论依据,对紫外光立体成型的实际光学系统的设计也具有重要的指导作用。
Analysis for the Scanning Distortion in the Stereo-lithography

Yu Dianhong,Li Lin,Lu Bingheng,

光子学报 , 2006,
Abstract: 对立体成型技术中广泛使用的振镜扫描系统进行了理论分析,指出了振镜的二维扫描偏转角和平面坐标之间存在着非线性映射关系.提出了一种实用的校正算法,该算法用理论数据与激光束在相应点的实际数据进行比对,制成校正表,按插值算法校正实际的枕形畸变及其它误差·该算法适用于使用振镜实现二维扫描的系统,能对应用这种原理工作的激光成型设备进行现场校正·
Fractal Phenomenon During Fabricating Ultrthin Silicon Membrane Using Etching-Stop

Yang Daohong,Xu Chen,Dong Dianhong,Zhang Jianming,Yang Qiming,Jin Wenxian,and Shen Guangdi,

半导体学报 , 2005,
Abstract: 利用浓硼扩散腐蚀停止技术制备自由悬空硅薄膜时,在薄膜的表面观察到了呈分形生长的反应生成络合物聚集结构.研究表明,薄膜表面的生成物的分形属于典型的有限扩散集团凝聚模型,其分形维数值约为1.667.实验还发现,反应生成络合物的聚集结构以及能否产生聚集都受腐蚀腔体的深宽比影响.
Software Industry Cluster be Disagreement on Theory and Practice  [PDF]
Yang Wang, Luqian Wang
Intelligent Information Management (IIM) , 2010, DOI: 10.4236/iim.2010.210069
Abstract: In the view of traditional industry cluster theory, it is easy to copy the software industry cluster pattern, or it is easy to copy another Silicon Valley, due to low reliability of the resources and the guidance factors of locations in software industry. But it is much more difficult to copy a Silicon Valley mode practically than imaginatively and the difficulties of bringing up and supporting high-tech initiatives is more than theoretic anticipation. In China, the software companies have just gathered together geographically and therefore no initiative center can be formed. All these above signify that software industry cluster is distinct from the traditional industry clusters, but the cognition of the reasons of software industry cluster is not clear yet. Furthermore, reasonable explanations of the bewilderment in the economical practice of software industry cluster are urgently needed.
The Economic Growth Effect of Logistics Industry FDI Analysis  [PDF]
Yang Wang, Luqian Wang
iBusiness (IB) , 2010, DOI: 10.4236/ib.2010.24049
Abstract: Based on the direction of the international FDI changed, from manufacturing to service industries, we should concern about the influence of the introduction of China’s logistics industry FDI to the national economy. The paper sets up regression model to examine logistics FDI and GDP in two aspects of time series and growth rate, we find that the logistics FDI reaches a high correlation with GDP, and logistics FDI is one of the major driving forces of economic development. Therefore, China should expand the introduction of logistics FDI, improve the quality of foreign investment, develop the positive economic growth effect of logistics FDI and promote the change of China’s economic growth pattern to ensure the development of China’s economy.
The Predictive Effects of Online Communication on Well-Being among Chinese Adolescents  [PDF]
Jinliang Wang, Haizhen Wang
Psychology (PSYCH) , 2011, DOI: 10.4236/psych.2011.24056
Abstract: Based on theories and previous studies on online communication, we proposed two hypotheses to better under- stand the effects of online communication on subjective well-being with a sample of Chinese adolescents (n = 190). The results of liner regression analysis found that online communication was positively related to adoles- cents’ subjective well-being. For boys, the coefficient of determination of online communication on subjective well-being was .143, and for girls the coefficient of determination was .040, indicating that boys benefit more from online communication than do girls.
The Impact of Radical Prostatectomy on the Survival of Patients with Carcinosarcoma of the Prostate  [PDF]
Jue Wang, Fenwei Wang
Journal of Cancer Therapy (JCT) , 2011, DOI: 10.4236/jct.2011.24064
Abstract: Background: The objective of this study was to evaluate the impact of radical prostatectomy on carcinosarcoma of the prostate. Methods: Patients diagnosed with carcinosarcoma of the prostate from 1977 through 2007 were identified in the Surveillance, Epidemiology, and End Results (SEER) database. Outcomes were examined with Kaplan-Meier survival analysis and Cox models. The association between clinical and demographic characteristics and survival of carcinosarcoma of the prostate was examined. Results: A total of fifty-four cases of histology confirmed carcinosarcoma of the prostate were identified. Median age of the patients was 74 years (range 28 - 94). Of the patients with a known tumor stage, all but one patient had a locally advanced or distant stage; all of the patients with known histology grade had poorly or undifferentiated histology. Twenty (37%) patients underwent transurethral resection only and Fourteen (25.9%) patients underwent radical prostatectomy. Eight (14%) patients received radiation therapy in combination with surgery. The median cancer specific survival was 16 months (95% CI 0 - 32 months). 1-, 3-, and 5- year cancer specific survival rate were 55.1%, 32.3% and 21.1%. In a multivariate analysis, radical prostatectomy was found to be a significant prognostic factor for cancer-specific survival. Conclusions: Carcinosarcoma of the prostate commonly occurs in older patients and associated with aggressive disease and poor prognosis. Radical prostatectomy is the only treatment modality that significantly improves survival. Emphasis on early diagnosis and detection and multimodality therapy of this disease is needed to improve the outcome for patients with this malignancy.
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