CAN总线网络测试研究

介绍了CAN总线网络开发方法,搭建了CAN总线集成开发测试环境,对实际网络进行了测试,给出了位定时参数计算方法,比较了不同模拟终端电阻下的总线的报文正确率和总线负载率等性能指标.     

Sentiment-oriented contextual advertising

Web advertising (Online advertising), a form of advertising that uses the World Wide Web to attract customers, has become one of the world’s most important marketing channels. This paper addresses the mechanism of Content-based advertising (Contextual advertising), which refers to the assignment of relevant ads to a generic web page, e.g., a blog post. As blogs become a platform for expressing personal opinion, they naturally contain various kinds of expressions, including both facts and comments of both a positive and negative nature. Besides, in line with the major tenet of Web 2.0 (i.e., user-centric), we believe that the web-site owners would be willing to be in charge of the ads which are positively related to their contents. Hence, in this paper, we propose the utilization of sentiment detection to improve Web-based contextual advertising. The proposed sentiment-oriented contextual advertising (SOCA) framework aims to combine contextual advertising matching with sentiment analysis to select ads that are related to the positive (and neutral) aspects of a blog and rank them according to their relevance. We experimentally validate our approach using a set of data that includes both real ads and actual blog pages. The results indicate that our proposed method can effectively identify those ads that are positively correlated with the given blog pages.     

中国传统符号的演变——门

人类学会构筑房屋并为自己的进出留下一个进出方便的口,门就产生了。门是一个极为抽象的形态,一个变化万千的符号,这个古老的符号——门的形态变化一直在随着科技的发展而演变,无论是古人还是后人都在其中精心地演绎着中国的传统民族文化。     

Logistic regression in sealed-bid auctions with multiple rounds: Application in Korean court auction

This paper proposes a forecasting method for court auction information system using logistic regression model with heterogeneity across the multiple round. The goal is to predict whether an individual auction item in a certain round will be sold or not. A simple linear regression and the least angle regression (LARS) containing random effect terms were used to select meaningful variables for our logit model. The link function of the proposed logit model is represented by two bundles of parameters. The former part consists of the parameters whose values do not change over rounds. The latter part has parameters whose values interact with rounds. The observed data corresponding to an appraiser price as well as an intercept term reflecting local characteristics are used without any change. Data that corresponds to all the other parameters is not directly used, but transformed based on similarities between the original item and the surrounding auction items being recommended by the court auction experts. We tested the Bayesian logistic regression by establishing different priors: Dunson’s prior, Gelman’s prior and Ansari’s prior. Dunson’s prior was found to perform the best. Little significant difference was found between the results of the other two priors. These findings indicate that logistic regression taking the heterogeneity of multi-round into account performs better than a one-layered neural network over all time periods.     

A genetic algorithm with gene rearrangement for K-means clustering

In this paper, a new clustering algorithm based on genetic algorithm (GA) with gene rearrangement (GAGR) is proposed, which in application may effectively remove the degeneracy for the purpose of a more efficient search. A new crossover operator that exploits a measure of similarity between chromosomes in a population is also presented. Adaptive probabilities of crossover and mutation are employed to prevent the convergence of the GAGR to a local optimum. Using the real-world data sets, we compare the performance of our GAGR clustering algorithm with K-means algorithm and other GA methods. An application of the GAGR clustering algorithm in unsupervised classification of multispectral remote sensing images is also provided. Experiment results demonstrate that the GAGR clustering algorithm has high performance, effectiveness and flexibility.     

Electronic structures of quasi-one-dimensional ferrimagnetic insulator Ca3Co2O6

The electronic structures of quasi-one-dimensional ferrimagnetic Ca₃Co₂O₆ are investigated using the generalized gradient approximation (GGA) as well as the GGA plus on-site Coulomb interaction (GGA+U) scheme. GGA+U calculations reveal that the interchain ferrimagnetic Ca₃Co₂O₆ is a Mott–Hubbard insulator rather than a metal given from GGA. In addition, we found an on-site U induced 3z²−r² orbital ordering on Co_pri sublattice which drives the intrachain ferromagnetic coupling along c-axis. Our findings suggest that strong electron-electron correlation plays an important role in Ca₃Co₂O₆.     

Prediction of residual stresses in high strength carbon steel pipe weld considering solid-state phase transformation effects

In this paper, prediction of axial and hoop residual stresses produced in high strength carbon steel pipe weld was made by employing a sequentially coupled 3-D thermal, metallurgical and mechanical FE model. Solid-state phase transformation during welding was incorporated into the FE model by allowing for volumetric changes and the associated changes in yield stress induced by austenitic and martensitic transformations. In the FE model, temperature-dependent thermo-physical and mechanical properties were considered, and phase transformation plasticity was also taken into account. The results showed the importance of incorporating solid-state phase transformation in the simulation of the pipe welding.     

The model-based human body motion analysis system

In this paper, we propose a model-based method to analyze the human walking motion. This system consists of three phases: the preprocessing phase, the model construction phase, and the motion analysis phase. In the experimental results, we show that our system not only analyzes the motion characteristics of the human body, but also recognizes the motion type of the input image sequences. Finally, the synthesized motion sequences are illustrated for verification. The major contributions of this research are: (1) developing a skeleton-based method to analyze the human motion; (2) using Hidden Markov Model (HMM) and posture patterns to describe the motion type.     

基于p范式模型的检索

随着电子文本的大量涌现,人们对信息检索工具提出了更高的要求。本文介绍一种扩展的布尔检索模型及其在中文信息检索系统中的应用,并利用相关反馈技术改善检索系统性能。