In this paper we aim to analyse temporal variation of CD4 cell counts for HIV-infected individuals under antiretroviral therapy by using statistical methods. This is achieved by resorting to recursive binary regressio...In this paper we aim to analyse temporal variation of CD4 cell counts for HIV-infected individuals under antiretroviral therapy by using statistical methods. This is achieved by resorting to recursive binary regression tree approach [1]?[2]. This approach has made it possible to highlight the existence of several segments of the population of interest described by the interactions between the predictive covariates of the response to the treatment regimen.展开更多
When travelling,people are accustomed to taking and uploading photos on social media websites,which has led to the accumulation of huge numbers of geotagged photos.Combined with multisource information(e.g.weather,tra...When travelling,people are accustomed to taking and uploading photos on social media websites,which has led to the accumulation of huge numbers of geotagged photos.Combined with multisource information(e.g.weather,transportation,or textual information),these geotagged photos could help us in constructing user preference profiles at a high level of detail.Therefore,using these geotagged photos,we built a personalised recommendation system to provide attraction recommendations that match a user’s preferences.Specifically,we retrieved a geotagged photo collection from the public API for Flickr(Flickr.com)and fetched a large amount of other contextual information to rebuild a user’s travel history.We then created a model-based recommendation method with a two-stage architecture that consists of candidate generation(the matching process)and candidate ranking.In the matching process,we used a support vector machine model that was modified for multiclass classification to generate the candidate list.In addition,we used a gradient boosting regression tree to score each candidate and rerank the list.Finally,we evaluated our recommendation results with respect to accuracy and ranking ability.Compared with widely used memory-based methods,our proposed method performs significantly better in the cold-start situation and when mining‘long-tail’data.展开更多
目的探讨非综合征性唇腭裂(nonsyndromic cleft lip and palate,NSCL/P)发病的主要危险因素;评估这些主要危险因素在NSCL/P发病中的相对重要性,最终确立NSCL/P发病概率的预测模型,为优生网络的构建奠定基础。方法采用1∶1配对病例对照研...目的探讨非综合征性唇腭裂(nonsyndromic cleft lip and palate,NSCL/P)发病的主要危险因素;评估这些主要危险因素在NSCL/P发病中的相对重要性,最终确立NSCL/P发病概率的预测模型,为优生网络的构建奠定基础。方法采用1∶1配对病例对照研究,病例组来源于2006年9月至2007年9月在潍坊医学院附属医院、潍坊市人民医院、菏泽市立医院、烟台毓璜顶医院口腔科住院,年龄在12岁以下患有NSCL/P的儿童76例;对照组为来源于同一机构门诊或病房或同一居住区符合配对条件的非唇腭裂儿童76名。根据拟定的42项危险因素编制调查表,对病例组患儿与对照组儿童的父母进行调查,数据经审核后录入Excel 2003建立数据库。首先使用条件Logistic回归对资料进行单因素分析,再对单因素筛选的变量结合专业知识进行多因素分析,筛选主要危险因素并建立回归模型,根据危险因素分别建立分类树与LogitBoost算法的发病概率预测模型,采用受试者工作特征曲线(ROC曲线)对两模型进行评价,从而确立本研究中NSCL/P发病概率的预测模型。结果病例组与对照组作对比分析,进入条件Logistic回归模型的变量有:母亲孕期感染史(P=0.010)、家族遗传史(P=0.009)、母孕期饮食是否规律(P=0.007)、胎次(P=0.004)、母亲孕期异常情绪史(P<0.001)、父亲学历(P<0.001)。经ROC曲线评价,确立分类树模型可用来预测NSCL/P的发病概率。结论母亲孕期感染、家族遗传、母亲孕期饮食不规律、胎次、母亲孕期异常情绪是NSCL/P发病的促进因素,且其对NSCL/P发病的影响作用依次增强;父亲学历是该病的保护因素。经ROC曲线评价,最终确立分类树模型为NSCL/P发病概率的预测模型。展开更多
交通拥堵检测是城市交通管理工作的重点和难点之一,现有的拥堵检测以路段为单位,不利于拥堵时空演变规律信息的提取,且检测内容大多只涉及拥堵程度,缺少对拥堵类型的识别。基于CART(classification and regression tree)分类树算法,提...交通拥堵检测是城市交通管理工作的重点和难点之一,现有的拥堵检测以路段为单位,不利于拥堵时空演变规律信息的提取,且检测内容大多只涉及拥堵程度,缺少对拥堵类型的识别。基于CART(classification and regression tree)分类树算法,提出一种以路段点为检测单元的拥堵点分类检测方法,该方法可根据路段平均行驶速度实时检测拥堵点及其类型。首先,将路段等距离划分后映射为路段点,根据时空维路况异常规则和异常模式,以路段点为单元分析了4种拥堵类型的时空演变模式;其次,在路段路况检测的基础上,提取路段点路况时空序列,根据不同类型的拥堵模式对路况时空序列进行分类标记;然后,选取4种速度指标作为样本属性集合,按照属性集合提取各路段点在各时段的速度,以此作为决策树学习的数据集;最后,基于CART分类树算法,采用交叉验证的方式训练出最优模型,使其达到最佳的泛化能力。与支持向量机(support vector machine,SVM)分类模型进行比较,实验结果表明,该方法在分类检测交通拥堵点时具有较高的正确率和召回率,且分类检测时效性较好。展开更多
Automatic prosodic break detection and annotation are important for both speech understanding and natural speech synthesis. In this paper, we discuss automatic prosodic break detection and feature analysis. The contri...Automatic prosodic break detection and annotation are important for both speech understanding and natural speech synthesis. In this paper, we discuss automatic prosodic break detection and feature analysis. The contributions of the paper are two aspects. One is that we use classifier combination method to detect Mandarin and English prosodic break using acoustic, lexical and syntactic evidence. Our proposed method achieves better performance on both the Mandarin prosodic annotation corpus Annotated Speech Corpus of Chinese Discourse and the English prosodic annotation corpus -- Boston University Radio News Corpus when compared with the baseline system and other researches＇ experimental results. The other is the feature analysis for prosodic break detection. The functions of different features, such as duration, pitch, energy, and intensity, are analyzed and compared in Mandarin and English prosodic break detection. Based on the feature analysis, we also verify some linguistic conclusions.展开更多
文摘In this paper we aim to analyse temporal variation of CD4 cell counts for HIV-infected individuals under antiretroviral therapy by using statistical methods. This is achieved by resorting to recursive binary regression tree approach [1]?[2]. This approach has made it possible to highlight the existence of several segments of the population of interest described by the interactions between the predictive covariates of the response to the treatment regimen.
基金supported by grants from the National Key Research and Development Program of China[grant number 2017YFB0503602]the National Natural Science Foundation of China[grant number 41771425],[grant number 41625003],[grant number 41501162]the Beijing Philosophy and Social Science Foundation[grant number 17JDGLB002].
文摘When travelling,people are accustomed to taking and uploading photos on social media websites,which has led to the accumulation of huge numbers of geotagged photos.Combined with multisource information(e.g.weather,transportation,or textual information),these geotagged photos could help us in constructing user preference profiles at a high level of detail.Therefore,using these geotagged photos,we built a personalised recommendation system to provide attraction recommendations that match a user’s preferences.Specifically,we retrieved a geotagged photo collection from the public API for Flickr(Flickr.com)and fetched a large amount of other contextual information to rebuild a user’s travel history.We then created a model-based recommendation method with a two-stage architecture that consists of candidate generation(the matching process)and candidate ranking.In the matching process,we used a support vector machine model that was modified for multiclass classification to generate the candidate list.In addition,we used a gradient boosting regression tree to score each candidate and rerank the list.Finally,we evaluated our recommendation results with respect to accuracy and ranking ability.Compared with widely used memory-based methods,our proposed method performs significantly better in the cold-start situation and when mining‘long-tail’data.
基金Supported by the National Natural Science Foundation of China under Grant Nos. 90820303,90820011the Natural Science Foundation of Shandong Province of China under Grant No. ZR2011FQ024
文摘Automatic prosodic break detection and annotation are important for both speech understanding and natural speech synthesis. In this paper, we discuss automatic prosodic break detection and feature analysis. The contributions of the paper are two aspects. One is that we use classifier combination method to detect Mandarin and English prosodic break using acoustic, lexical and syntactic evidence. Our proposed method achieves better performance on both the Mandarin prosodic annotation corpus Annotated Speech Corpus of Chinese Discourse and the English prosodic annotation corpus -- Boston University Radio News Corpus when compared with the baseline system and other researches＇ experimental results. The other is the feature analysis for prosodic break detection. The functions of different features, such as duration, pitch, energy, and intensity, are analyzed and compared in Mandarin and English prosodic break detection. Based on the feature analysis, we also verify some linguistic conclusions.
