文章运用WordSmith 8.0对艾丽斯·沃克小说《紫色》中的关键词和特殊词簇进行分析,揭示了《紫色》在词汇上的整体分布特征,并指出文中所使用的词汇与句式均与主人公非裔女性这一人物形象相吻合。通过Word Smith 8.0检索发现,沃克小...文章运用WordSmith 8.0对艾丽斯·沃克小说《紫色》中的关键词和特殊词簇进行分析,揭示了《紫色》在词汇上的整体分布特征,并指出文中所使用的词汇与句式均与主人公非裔女性这一人物形象相吻合。通过Word Smith 8.0检索发现,沃克小说中的关键词和词簇搭配对于促进故事情节和人物刻画方面有重要作用。研究结果表明,语料库文体学有助于学者发现以往研究中忽视的深层文本含义,是对以往《紫色》文学定性研究结果的再次验证,是定性研究和定量研究的积极结合,也是对学界“经典重读”的积极响应。展开更多
With the SPSS and the help of factor method and hierarchical clustered method,journal articles on digital information resources(DIR) from CNKI in the past ten years are analyzed with a co-word analytical method in thi...With the SPSS and the help of factor method and hierarchical clustered method,journal articles on digital information resources(DIR) from CNKI in the past ten years are analyzed with a co-word analytical method in this paper. The hot issues of studies on DIR and the relationship between those subjects are analyzed in this investigation as well.展开更多
Objective:The aim of this study is to discover research status and hotspots of economic evaluation(EE)in nursing area using co-word cluster analysis.Methods:Medical Subject Heading(MeSH)term“cost–benefit analysis”w...Objective:The aim of this study is to discover research status and hotspots of economic evaluation(EE)in nursing area using co-word cluster analysis.Methods:Medical Subject Heading(MeSH)term“cost–benefit analysis”was searched in PubMed and nursing journals were limited by the function of filter.The information of author,country,year,journal,and keywords of collected paper was extracted and exported to Bicomb 2.0 system,where high-frequency terms and other data could be further mined.SPSS 19.0 was used for cluster analysis to generate dendrogram.Results:In all,3,020 articles were found and 10,573 MeSH terms were detected;among them,1,909 were MeSH major topics and generated 42 high-frequency terms.The consequence of dendrogram showed seven clusters,representing seven research hotspots:skin administration,infection prevention,education program,nurse education and management,EE research,neoplasm patient,and extension of nurse function.Conclusions:Nursing EE research involved multiple aspects in nursing area,which is an important indicator for decision-making.Although the number of papers is increasing,the quality of study is not promising.Therefore,further study may be required to detect nurses’knowledge of economic analysis method and their attitude to apply it into nursing research.More nursing economics course could carry out in nursing school or hospitals.展开更多
"视觉词袋"(Bag of Visual Words,BOV)算法是一种有效的基于语义特征表达的物体识别算法。针对传统BOV模型存在的不足,综合利用SAR图像的灰度和纹理特征,提出基于感兴趣目标(Target of Interest,TOI)的"视觉词袋"..."视觉词袋"(Bag of Visual Words,BOV)算法是一种有效的基于语义特征表达的物体识别算法。针对传统BOV模型存在的不足,综合利用SAR图像的灰度和纹理特征,提出基于感兴趣目标(Target of Interest,TOI)的"视觉词袋"算法。首先,对训练图像进行TOI选取,用灰度共生矩阵模型提取TOI的纹理特征,再结合灰度特征,组成多维特征向量集,以簇内相似度最高、数据分布密度最大为准则,生成"视觉词袋"。其次,对测试图像,依据已生成的"视觉词袋",采用支持向量机(Support Vector Machine,SVM)分类器,实现SAR图像感兴趣目标的有效分类。实验结果表明,与传统的"视觉词袋"构建算法相比,该算法在分类正确率提高的同时,能够在训练图像较少的情况下达到良好的分类效果。展开更多
将Bag of Words算法引入木材图像识别领域中,介绍Bag of Words算法在木材识别上的实现过程。首先用SURF提取特征点,然后再对这些特征点进行聚类,得到类心。基于类心得到各个训练树种的向量柱形图和待识别树种图片的向量柱形图。选择分...将Bag of Words算法引入木材图像识别领域中,介绍Bag of Words算法在木材识别上的实现过程。首先用SURF提取特征点,然后再对这些特征点进行聚类,得到类心。基于类心得到各个训练树种的向量柱形图和待识别树种图片的向量柱形图。选择分类器对用向量柱形图描述的木材图像进行分类。这将提高木材识别的效率,为没有木材专业知识的人能较为准确地辨别树种提供较为可靠的方法。展开更多
Category-based statistic language model is an important method to solve the problem of sparse data.But there are two bottlenecks:1) The problem of word clustering.It is hard to find a suitable clustering method with g...Category-based statistic language model is an important method to solve the problem of sparse data.But there are two bottlenecks:1) The problem of word clustering.It is hard to find a suitable clustering method with good performance and less computation.2) Class-based method always loses the prediction ability to adapt the text in different domains.In order to solve above problems,a definition of word similarity by utilizing mutual information was presented.Based on word similarity,the definition of word set similarity was given.Experiments show that word clustering algorithm based on similarity is better than conventional greedy clustering method in speed and performance,and the perplexity is reduced from 283 to 218.At the same time,an absolute weighted difference method was presented and was used to construct vari-gram language model which has good prediction ability.The perplexity of vari-gram model is reduced from 234.65 to 219.14 on Chinese corpora,and is reduced from 195.56 to 184.25 on English corpora compared with category-based model.展开更多
Firstly,this paper analyzed current situations,major practice and existing problems of under-forest economy in Henan Province.Then,it made an in-depth discussion of guiding thought,principle and objectives,constructio...Firstly,this paper analyzed current situations,major practice and existing problems of under-forest economy in Henan Province.Then,it made an in-depth discussion of guiding thought,principle and objectives,construction task and safeguarding measures of the underforest economic development plan. Besides,it analyzed benefits of the under-forest economic development plan. By 2017,the area of underforest economic land will reach 1. 60 million hm2,create output value of 155. 2 billion yuan( accounting for more than 20% of forest output value),provide 3. 27 million jobs,and will greatly increase ecological carrying capacity of construction and development of the Central Plains Economic Region( CPER).展开更多
A modified DBSCAN algorithm is presented for deinterleaving of radar pulses in modern EW environments.A main characteristic of the proposed method is that using only time of arrival of pulses,the method can sort the p...A modified DBSCAN algorithm is presented for deinterleaving of radar pulses in modern EW environments.A main characteristic of the proposed method is that using only time of arrival of pulses,the method can sort the pulses efficiently.Other PDW information such as rise time,carrier frequency,pulse width,modulation on pulse,fall time and direction of arrival are not required.To identify the valid PRIs in a set of interleaved pulses,an innovative modification of the DBSCAN algorithm is introduced which is accurate and easy to implement.The proposed method determines valid PRIs more accurately and neglects the spurious ones more efficiently as compared to the classical histogram based algorithms such as SDIF.Furthermore,without specifying any input parameter,the proposed method can deinterleave radar pulses while up to 30%jitter is present in the associated PRI.The accuracy and efficiency of the proposed method are verified by computer simulations and real data results.Experimental simulations are based on different real and operational scenarios where the presence of missing and spurious pulses are also considered.So,the simulation results can be of practical significance.展开更多
文摘文章运用WordSmith 8.0对艾丽斯·沃克小说《紫色》中的关键词和特殊词簇进行分析,揭示了《紫色》在词汇上的整体分布特征,并指出文中所使用的词汇与句式均与主人公非裔女性这一人物形象相吻合。通过Word Smith 8.0检索发现,沃克小说中的关键词和词簇搭配对于促进故事情节和人物刻画方面有重要作用。研究结果表明,语料库文体学有助于学者发现以往研究中忽视的深层文本含义,是对以往《紫色》文学定性研究结果的再次验证,是定性研究和定量研究的积极结合,也是对学界“经典重读”的积极响应。
基金supported by the Fund for Philosophy and Social Sciences,Ministry of Education of China(Grant No.05JZD00024)
文摘With the SPSS and the help of factor method and hierarchical clustered method,journal articles on digital information resources(DIR) from CNKI in the past ten years are analyzed with a co-word analytical method in this paper. The hot issues of studies on DIR and the relationship between those subjects are analyzed in this investigation as well.
文摘Objective:The aim of this study is to discover research status and hotspots of economic evaluation(EE)in nursing area using co-word cluster analysis.Methods:Medical Subject Heading(MeSH)term“cost–benefit analysis”was searched in PubMed and nursing journals were limited by the function of filter.The information of author,country,year,journal,and keywords of collected paper was extracted and exported to Bicomb 2.0 system,where high-frequency terms and other data could be further mined.SPSS 19.0 was used for cluster analysis to generate dendrogram.Results:In all,3,020 articles were found and 10,573 MeSH terms were detected;among them,1,909 were MeSH major topics and generated 42 high-frequency terms.The consequence of dendrogram showed seven clusters,representing seven research hotspots:skin administration,infection prevention,education program,nurse education and management,EE research,neoplasm patient,and extension of nurse function.Conclusions:Nursing EE research involved multiple aspects in nursing area,which is an important indicator for decision-making.Although the number of papers is increasing,the quality of study is not promising.Therefore,further study may be required to detect nurses’knowledge of economic analysis method and their attitude to apply it into nursing research.More nursing economics course could carry out in nursing school or hospitals.
文摘"视觉词袋"(Bag of Visual Words,BOV)算法是一种有效的基于语义特征表达的物体识别算法。针对传统BOV模型存在的不足,综合利用SAR图像的灰度和纹理特征,提出基于感兴趣目标(Target of Interest,TOI)的"视觉词袋"算法。首先,对训练图像进行TOI选取,用灰度共生矩阵模型提取TOI的纹理特征,再结合灰度特征,组成多维特征向量集,以簇内相似度最高、数据分布密度最大为准则,生成"视觉词袋"。其次,对测试图像,依据已生成的"视觉词袋",采用支持向量机(Support Vector Machine,SVM)分类器,实现SAR图像感兴趣目标的有效分类。实验结果表明,与传统的"视觉词袋"构建算法相比,该算法在分类正确率提高的同时,能够在训练图像较少的情况下达到良好的分类效果。
文摘将Bag of Words算法引入木材图像识别领域中,介绍Bag of Words算法在木材识别上的实现过程。首先用SURF提取特征点,然后再对这些特征点进行聚类,得到类心。基于类心得到各个训练树种的向量柱形图和待识别树种图片的向量柱形图。选择分类器对用向量柱形图描述的木材图像进行分类。这将提高木材识别的效率,为没有木材专业知识的人能较为准确地辨别树种提供较为可靠的方法。
基金Project(60763001) supported by the National Natural Science Foundation of ChinaProject(2010GZS0072) supported by the Natural Science Foundation of Jiangxi Province,ChinaProject(GJJ12271) supported by the Science and Technology Foundation of Provincial Education Department of Jiangxi Province,China
文摘Category-based statistic language model is an important method to solve the problem of sparse data.But there are two bottlenecks:1) The problem of word clustering.It is hard to find a suitable clustering method with good performance and less computation.2) Class-based method always loses the prediction ability to adapt the text in different domains.In order to solve above problems,a definition of word similarity by utilizing mutual information was presented.Based on word similarity,the definition of word set similarity was given.Experiments show that word clustering algorithm based on similarity is better than conventional greedy clustering method in speed and performance,and the perplexity is reduced from 283 to 218.At the same time,an absolute weighted difference method was presented and was used to construct vari-gram language model which has good prediction ability.The perplexity of vari-gram model is reduced from 234.65 to 219.14 on Chinese corpora,and is reduced from 195.56 to 184.25 on English corpora compared with category-based model.
文摘Firstly,this paper analyzed current situations,major practice and existing problems of under-forest economy in Henan Province.Then,it made an in-depth discussion of guiding thought,principle and objectives,construction task and safeguarding measures of the underforest economic development plan. Besides,it analyzed benefits of the under-forest economic development plan. By 2017,the area of underforest economic land will reach 1. 60 million hm2,create output value of 155. 2 billion yuan( accounting for more than 20% of forest output value),provide 3. 27 million jobs,and will greatly increase ecological carrying capacity of construction and development of the Central Plains Economic Region( CPER).
文摘A modified DBSCAN algorithm is presented for deinterleaving of radar pulses in modern EW environments.A main characteristic of the proposed method is that using only time of arrival of pulses,the method can sort the pulses efficiently.Other PDW information such as rise time,carrier frequency,pulse width,modulation on pulse,fall time and direction of arrival are not required.To identify the valid PRIs in a set of interleaved pulses,an innovative modification of the DBSCAN algorithm is introduced which is accurate and easy to implement.The proposed method determines valid PRIs more accurately and neglects the spurious ones more efficiently as compared to the classical histogram based algorithms such as SDIF.Furthermore,without specifying any input parameter,the proposed method can deinterleave radar pulses while up to 30%jitter is present in the associated PRI.The accuracy and efficiency of the proposed method are verified by computer simulations and real data results.Experimental simulations are based on different real and operational scenarios where the presence of missing and spurious pulses are also considered.So,the simulation results can be of practical significance.
