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Articles by Xuan Wang
Total Records ( 10 ) for Xuan Wang
  Waqas Anwar , Xuan Wang , LuLi and Xiaolong Wang
  In this study, we present the preliminary achievement of Hidden Markov Model (HMM) to solve the part of speech tagging problem of Urdu language. The presented HMM is derived from the combination of lexical and transition probabilities. An important feature of our tagger is to combine many distinguished smoothing techniques with HMM model to resolve the data sparseness problem. We note that the proposed HMM based Urdu Part of speech tagger with different smoothing method has achieved significant performance. We evaluate our tagger’s results regarding different smoothing methods and different word level accuracy through Analysis of Variance (ANOVA) and show how present results are significant. Also, we compose a confusion matrix about most frequent error occurring tag pairs. The development of our tagger is an important milestone toward Urdu language processing. This will open some novel research directions to mature Urdu language processing.
  Han Renting , Xuan Wang , Nan Geng , Wenhao Suo , Bei Liu and Yuxiang Huang
  This study utilizes the Cobb-douglas production function and regression analysis to establish a computing model for the contribution rate of agricultural mechanization to agricultural production. The agricultural mechanization and agricultural output data of the Shaanxi Province from 2001 to 2010 were used as examples for the estimation. The results demonstrate that the contribution of agricultural mechanization to agricultural output was 31.46%. A regression analysis of the various input factors revealed that the growth of agricultural output was primarily due to an increase in capital and agricultural machinery. Capital investment displayed the largest contribution to the output, followed, in descending order, by the investment in agricultural machinery and land investment; moreover, the labor investment did not significantly affect the output. With an increased agricultural machinery and capital investment, the agricultural output of the Shaanxi Province exhibited a trend of significant upward growth. This observation suggests that further investment in agricultural machinery and an increase in the mechanization level of agricultural production may extensively contribute to the growth of the agricultural output. The results of this study are relevant for future evaluations of the development level of agricultural mechanization and its potential contribution to the agricultural output.
  Wenting Han , Xuan Wang , Jun Qiao , Jun Chen and Shaoping Xue
  To restore the original power, economy and technical indicators of an overhauled diesel engine, the crank lengthening method was adopted and tested in the study. The crank of a Dongfanghong type 4125A diesel engine was extended by 0.75 mm, which is within the range tolerable to the structure. The internal combustion engine rig test method was adopted and a hydraulic dynamometer, comprehensive engine tester, smoke meter and additional instruments were employed to measure the indicators cylinder pressure, speed control characteristics, power, reliability and economy of the diesel engine before and after rebuilding for comparison. The results show that the rebuilding method in which the crank is lengthened increased the maximum power of the diesel engine by 2.32 kW, decreased fuel consumption by 5 g/(kW·h), decreased the exhaust gas temperature by 27°C, decreased the smoke density by 0.2 BSU and increased the mean pressure of various cylinders by 0.31 MPa. The results confirm that the crank lengthening method is effective at restoring the original power, economy and technical indicators of an overhauled diesel engine.
  Bing Li , Bingjie Sun , Xuan Wang , Xintong Huang and Xiaoyu Xiu
  Due to the advance of many social network applications, social group feature analytics are attracting a lot of attention. In the meantime, microblogging, as a kind of social network application, attracts more and more people to use it. With the utilization of bigger and broader crowds over microblogging, surveying massive user features will be an important aspect of exploitation of crowd-sourced data. For better understanding microblogging user group features, in this study, a user classification approach was proposed by means of Boolean operations and it is easily find different microblogging user group features by this approach. In the experiment, some facts were discussed on the exploratory survey to exploit a great deal of microblogging data and how to analyze the features of the different user groups.
  Zili Zhang , Xuan Wang and Muhammad Waqas Anwar
  Arc segmentation is quite a challenging field in Graphics Recognition and the computation of the coordinates of centers and the radii of circular arcs is a crucial problem which has drawn much attention. Therefore this paper mainly discusses the application of circle fitting skill in scanning engineering drawings to determine correct coordinates of centers and radii. At first we should choose appropriate seed points and improve circle fitting algorithm of Instrumental Variable Estimator (IVE). Then we combine seed points and the improved IVE (IIVE) algorithm to calculate coordinates of centers and radii of circular arcs. In experimental section, the performance of IIVE and other two methods are compared by using classical experimental data and the coordinates of centers and radii are computed by employing the Arc Segmentation contest data. The results show that the proposed algorithm is very effective and efficient and the causes of the unsatisfactory results are analyzed.
  Xinxin Li , Xuan Wang and Muhammad Waqas Anwar
  Strategies of unlabeled data selection are important for semi-supervised learning of natural language processing tasks. To increase the accuracy and diversity of new labeled data, plenty of methods have been proposed, such as ensemble-based self-training, co-training and tri-training methods. In this paper, we propose a simple and effective semi-supervised algorithm for Chinese word segmentation and part-of-speech tagging problem which selects new labeled data agreed by two different approaches: character-based and word-based models. Theoretical and experimental analysis verifies that sentences with same annotation on both models are more accurate than those generated by single models and are suitable for semi-supervised learning as additional data. Experimental results on Chinese Treebank 5.0 demonstrate that our semi-supervised approach is comparable with the best reported semi-supervised approach which employs complex feature engineering.
  Hainan Zhao and Xuan Wang
  This study proposes a novel approach of exploiting a reliable structural appearance model for visual tracking. The proposed method samples overlapped local image patches within the target region and evaluates the reliabilities of these local patches respectively by introducing a sample based local sparse representation for each local patch. The occluded or deteriorative patches are excluded, only the stable ones are employed to construct a reliable structural appearance model, which is used for likelihood computation. In addition, the reliability evaluation of local patch facilitates our selective update scheme, by which we reduce the influence of the occluded target template and alleviate the drift problem. Experiments on challenging video sequences demonstrate that the proposed tracking algorithm performs favorably against several state-of-the-art methods.
  Lu Li , Xuan Wang and XiaoLong Wang
  Conditional maximum entropy models provide a unified framework to integrate arbitrary features from different knowledge sources and have been successfully applied to many natural language processing tasks. Feature selection methods are often used to distinguish good features from bad ones to improve model performance. The selection of features in traditional methods is often performed based on different strategies before or along with feature weight estimation, however, weights themselves should be the only factor to measure the importance of features. This study proposes a new selection method based on divide-and-conquer strategies and well-trained feature spaces of small sizes. Features are divided into small subsets, on each of which a sub-model is built and its features are judged according to their weights. The final model is constructed based on merged feature space from all sub-models. Experiments on part of speech tagging show that this method is feasible and efficient.
  Jun Yao , Xuan Wang and Zhibin Liu
  Brand Experience is a bridge of connection between brand and consumer and is a hot issue on Brand Research currently. With the Brand Experience Identification system (BEIs) construction and research as study object, this paper presents the concept of BEIs at the perspective of consumers’ real Brand Experience and by the approach of human psychological experience cognitive. Subsequently, trying to allow enterprises to have a better application of this system to create or manage the User Experience of brand and be able to make the brand and consumer to establish a real connection, it expounds the content, construction methods and process of the BEIs.
  Xuan Wang , Neal D. Hammer and Matthew R. Chapman
  Amyloid fibers are filamentous proteinaceous structures commonly associated with mammalian neurodegenerative diseases. Nucleation is the rate-limiting step of amyloid propagation, and its nature remains poorly understood. Escherichia coli assembles functional amyloid fibers called curli on the cell surface using an evolved biogenesis machine. In vivo, amyloidogenesis of the major curli subunit protein, CsgA, is dependent on the minor curli subunit protein, CsgB. Here, we directly demonstrated that CsgB+ cells efficiently nucleated purified soluble CsgA into amyloid fibers on the cell surface. CsgA contains five imperfect repeating units that fulfill specific roles in directing amyloid formation. Deletion analysis revealed that the N- and C-terminal most repeating units were required for in vivo amyloid formation. We found that CsgA nucleation specificity is encoded by the N- and C-terminal most repeating units using a blend of genetic, biochemical, and electron microscopic analyses. In addition, we found that the C-terminal most repeat was most aggregation-prone and dramatically contributed to CsgA polymerization in vitro. This work defines the elegant molecular signatures of bacterial amyloid nucleation and polymerization, thereby revealing how nature directs amyloid formation to occur at the correct time and location.
 
 
 
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